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Biodiversity Baseline Survey of the Wangchhu Watershed Section”A” Alpine zone
Andrew N. Gillison
Biodiversity specialist
Center for Biodiversity Management P.O. Box 120
Yungaburra 4884 Queensland, Australia Tel. +61-740-953224
Email: [email protected] www.cbmglobe.org
Including an additional report on:
The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the
Upper Wangchhu
Hans van Noord and Tshering Dorji
SLMP-NSSC
Semtokha
11 November 2009
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Executive summary
1. Following the Phase I stakeholder workhop it was agreed that a training course in rapid resource and biodiversity assessment should precede a baseline survey of one of Bhutan’s key watersheds – the Wangchhu. A reconnaissance of the Wangchhu and adjoining watersheds was completed by land management experts from SLMP and consulting hydrology and biodiversity specialists.
2. A training workshop with 12 participants from governmental and non-governmental agencies in Bhutan was conducted at Zhemgang. The location provided access to a variety of land form and land cover types representative of land use in the mid-elevational range of the Wangchhu. A separate report covers the training workshop.
3. Because of its size, the watershed was divided into three operational sections: “A” High elevation (3,000-5,000m), “B” (1,500-3,000m) and “C” 150 – 1,500m). Here we report the results of survey “A” covering 2,600 to 4,500m.
4. The survey was coordinated jointly through NSSC by a land management and a soil survey specialist and a consulting biodiversity specialist (CBM). Technical assistance was provided by two field botanists (NBC, RSPN) and a plant ecologist (RNR-RC, CoRRB). Field support was arranged through a local trekking company.
5. Apart from data acquisition, the survey was designed to consolidate in-field training for trainees from the previous training workshop – in the present case the soil specialist, plant ecologist and two new trainees (field botanists).
6. Survey design was based on an environmental gradient-directed transect (gradsect) methodology taking into account a primary elevational (thermal) gradient from approximately 5,000m to 150m above sealevel. Other key environmental gradients included drainage, land form, land use and land cover. The gradsect provided the necessary environmental framework for vegetation survey for which a rapid survey method (VegClass) was used to record core biophysical data. Due to the complex logistic nature of the survey, avifauna (presence only) data were recorded only in each general site location.
7. Geomorphological observations of the current status of glacial dynamics, provide valuable additional information about the underlying physical structure of the survey area and tend to confirm increased rates of glacial melting observed elsewhere in the Eastern Himalaya. Geo-located VegClass transects established on the moraines provide sensitive reference points for monitoring future changes.
8. Preliminary statistical analyses confirm the primary influence of climate (temperature, precipitation, seasonality) on plant biodiversity and to a lesser degree soil properties.
9. As this is the first of a three-part survey, the analyses here provide only a limited basis for establishing biodiversity indicators. The predictive nature of these indicators is almost certain to change as additional survey data are acquired from Wangchhu sections ‘B’ and ‘C’. For this reason only very tentative conclusions can be drawn from this initial survey.
10. The biophysical data (land cover, land use, vegetation, soils, geomorphology) recorded from this survey will, nonetheless, make a significant contribution to the biodiversity and land use component of the developing DrukDIF.
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List of tables Table 1. Team membership and area of expertise Table 2. Transect locations and site physical properties Table 3. Temperature and annual precipitation Table 4. Vegetation typology and land use Table 5. Summary of species, PFTs and PFC Table 6. Vegetation structural features Table 7. Cover-abundance scores of lichens Table 8. List of birds observed during survey ‘A’ upper Wangchhu watershed Table 9a. Soil properties Table 9b. Soil properties (cont.) Annexes I Terms of Reference II List of data variables recorded for each 40x5m transect III Vascular plant species listed according to transect IV List of Plant Functional types (PFTs) recorded per transect V Overview of soil characteristics of the 22 sampled transects
List of Figures Figure 1. General area of the alpine section of the Wangchhu watershed covered in this
survey – (white ellipse). Figure 2. Transect locations within the upper Wangchhu watershed (H. van Noord) Figure 3. Geological map of Bhutan Figure 4. Frontal moraine stages of Jhomolhari glacier at 4150m (red), 4300m purple and
4400m (green). The pro-glacial lake is indicated in light blue with the present glacier front marked with a dotted blue line.
Figure 5. Jichu Drakey glacier front with its pro-glacial lake and two streams draining the lake.
Figure 6. The frontal moraine of Jichu Drakey glacier with dead-ice bodies exposed bordering the pro-glacial lake (indicated with red arrows)
Figure 7. Spatially referenced transect monitoring site (WC04) of frontal moraine recorded using VegClass. This transect was the third highest in plant diversity (63 species, 45 PFTs) and the second most complex PFT site (PFC = 292)
Figure 8. The “A” team. Alpine survey of the upper Wangchhu L->R from back: Dorji Gyaltshen, Tshering Dorji, Tandin Wangdi, Rebecca Pradhan, Andrew Gillison, Hans van Noord. At Jhomolhari base camp (4,300m elevn.)
Figure 9. a. Landform at Jhomolhari base camp; b. Frontal moraine, Jichu Drakey (WC04); c. Data collection on near-vertical slopes (WC03); d. Birch (Betula utilis) forest on 70% slope on shallow (40cm) soils (WC02); e. Juniper (Juniperus pseudosabina) and Salix daltonia remnant forest (WC09); f. Disturbed mixed
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conifer-broadleaf (Abies, Betula, Juniperus) and Rhododendron and Rubus understorey on 90% slope (WC13).
Figure 10. a. Mature stand of Larch (Larix griffithiana) and Fir (Abies densa) (WC16); b. Regenerating Birch (Betula utilis) forest with Acer, Larix and dense herb layer (WC14); c. Mixed conifer/broadleaf forest with understorey of dying bamboo (Thamnocalamus spathiflorus) (WC15); d. Cultivated Buckwheat field (WC21); e. Foliose lichen on Acer pectinatum; f. Crustose lichens; g. Fruticose lichen on Larix griffithiana.
Figure 11. a. High elevation (4600m) megaherb Rheum nobile (Polygonaceae) (Photo HvN); b. Megaherbs Senecio amplexicaulis (Asteraceae) and Heracleum nepalensis (Apiaceae). c. Mixed PFTs and leaf types (Alliaceae, Asteraceae, Poaceae, Ranunculaceae, Rosaceae, Scrophulariaceae); d. Nanophyllous Cotoneaster sp. (Rosaceae). e. Nanophyllous succulent (Sedum sp.)
Figure 12. a. Birch (B. utilis) subject to cascading rocks (WC02). b. Hillside ‘scalds’ possibly due to overgrazing and unstable substrate 4300m. c. Multiple successional patterns, Salix, Juniperus, Betula on unstable slopes 4000m. d. Oldgrowth conifer-broadleaf forest Parochhu gorge 3500m. e. Cool, moist mixed conifer-broadleaf forest with dense internal cover of ferns, bryophytes and lichens (WC16) 3400m. f. Dense groundlayer of Urticaceae (Pilea, Elatostema) and Asteraceae (WC16).
Figure 13. Plant species diversity regressed against PFT diversity Figure 14. Fruticose lichens and mean canopy height Figure 15. Fruticose lichens and plant litter Figure 16. Foliose lichens and bryophyte cover-abundance Figure 17. Foliose lichens and plant species diversity Figure 18. Foliose lichens and PFT diversity Figure 19. Common Fauna: a. Yaks (Bos grunniens) >3500m; b. Blue sheep (Pseudois
nayaur) 4300m; c. Himalayan Marmot (Marmota himalayana) 4300m; d. Grey Langur (Presbytis entellus) 3200m; e. Azure Sapphire (Heliophorus androcles) 3000m; f. Common Copper (Lycaena phlaeas) 3000m; g. Blue Pansy (Precis orithrya) 2600m.
Figure 20. Soil pH and frequency of PFTs with greenstem photosynthesis (green exernal bark cortex (ct)) across transects
Figure 21. Vegetation and soil relationships expressed via ordination
Acronyms* CNR College of Natural Resources, Royal University of Bhutan, Lobesa DANIDA Danish International Development Assistance DHSVM Distributed Hydrology Soil Vegetation Model DrukDIF Bhutan Dynamic Information Framework FAO Food and Agriculture Organization, Rome FRA2000 Forest Resource Assessment 2000 (FAO) GEF Global Environment Facility GIS Geographic Information System ICIMOD International Center for Integrated Mountain Development IUCN International Union for the Conservation of Nature, Gland,
Switzerland
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KL Kangchenjunga Landscape MoA Ministry of Agriculture NAP National Action Plan on Land Degradation NAPA National Adaptation Plan of Action NBC National Biodiversity Centre NCD Nature Conservation Division (Dept. Forests, MoA) NEC National Environment Commission NGO Non-Government Organization NSSC National Soil Services Center PFE Plant Functional Element PFT Plant Functional Type RGoB Royal Government of Bhutan RNR RNR-RC, CoRRB
Renewable Natural Resources (MoA oversight) Renewable Narural Resources – Council of Renewable Natural Resources Research of Bhutan
RSPN Royal Society for Protection of Nature SLMP Sustainable Land Management Project TOR Terms of Reference UNDP United Nations Development Programme UNEP United nations Environment Programme URL Unique Record Locator USGS United States Geological Survey (US Department of the Interior) USGS-NPS United States Geological Survey, National Parks Service UW University of Washington, Seattle, USA VIC Variable Infiltration Capacity Model WB The World Bank WWF Worldwide Fund for Nature * Used in this and previous DrukDIF reports Bhutanese Terms
Term Meaning Chathrim Act, rules and regulations, codes of conduct Chhu River or rivulet Chimi Representative at the National Assembly Dasho Administrative Head of a district or Dzongkhag Dzongdag Head of a district Dzongkhag District Dzongkhag Yargye Tshogchung District Development Committee Dungkhag Sub-district Dungpa Head of a sub-district Geog (chiog) Block, which is usually made up of few to several villagesGeog Yargye Tshogchung Block Development Committee Gup Head of a block Mangmi Elected representative of a geog Tseri Slash and burn cultivation Tshogpa Representative of a village, or a cluster of villages
1. Introduction This the first of three connected survey reports that, when combined, will complete a framework for further resource assessment of the Wangchhu watershed as part of the developing DrukDIF. For operational reasons, because of its size, the watershed was divided into three sections: “A” High elevation (3,000-5,000m), “B” Medium elevation (1,500-3,000m) and “C” Low elevation (150 – 1,500m). Here we report the results of survey “A” that covered an elevational range of 2,600 to 4,900m. Experience in similar surveys in other countries shows that predictive models derived from observations and statistical analyses of the relationship between plants and animals and their physical environment depend largely on the environmental context. (Gillison and Liswanti, 2004) As sampling of the distribution range of species improves, so too does the predictive basis for modelling species performance along key environmental gradients. Outcomes from this report are therefore most likely to be further modified by the analysis of data yet to be acquired from the survey of additional environments in sections “B” and “C”. For this reason, the report includes only a tentative account of the outcomes of the statistical analyses of the present survey. A complete account of statistical and exploratory data analysis will be provided for the entire watershed when data from the three connected surveys are available. This study follows logically from earlier development in the DrukDIF1 and is consistent with the aims and targeted deliverables as outlined in a following extract from a more detailed TOR (Annex I) in which the intended survey of Section “A” of the Wangchhu watershed is described within a broader operational and environmental context. While not included in the TOR, significant, additional information and data on geomorphology and soil properties are included in this report by H. van Noord and T. Dorji of SLMP. This is consistent with the general aims and is included in an introduction to the general biophysical background of the study area together with a report on soil properties. 2. Terms of reference (not included here)
1 Gillison, A.N. (2009) . Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase I: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. June 5 2009.
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3. Location and biophysical background to the survey area 3.1 Location The survey area lies in northwest Bhutan and is included within an area of the Eastern Himalaya broadly referred to as the Kanchenjunga landscape (Fig. 1). The area embraces a significant section of the upper Paro and Jangotang river systems that are fed by both natural precipitation and glacial meltwater. The significance of the area for conservation management and the nature of land cover and land use are outlined in an earlier report for Phase I of DrukDIF dealing with a review of biodiversity in Bhutan. The underlying topography and land form (see below) combined with thermal and precipitation gradients are closely linked with changes in land cover and vegetation types ranging from tall closed conifer-broadleaf forest at lower elevations to exposed higher elevation, alpine grasslands and shrublands. More detailed accounts of vegetation typology and related ecosystem dynamics are described
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Figure 4. General area of the alpine section of the Wangchhu watershed covered in this survey – (white ellipse).
in the results section of this report. While much of the area, especially the more accessible alpine grassland ecosystems, appears to be ‘pristine’, the prevailing condition is rather more representative of a state of partial equilibrium as a consequence of long periods of human occupation where, apart from climate, animal husbandry and the use of fire remain primary drivers in ecosystem performance. The area sampled (Fig. 2) typifies many upland areas of the world that have experienced similar evolutionary pressures due to fire and the omnipresent domestic and indigenous grazing animals. Within the overal gradsect, sample sites were also located to represent a cross section of apparent land use intensity.
Figure 5. Transect locations within the upper Wangchhu watershed (H. van Noord)
3.2 The physical base of the survey gradsect: geology, geomorphology and soil development along the upper Wangchhu [ H. van Noord and T. Dorji ] 3.2.1 Geology Surprisingly little is known about the geology of the Upper Wangchhu watershed. Apart from the pioneering work by Augusto Gansser, as presented in his classic work ‘The Geology of the Bhutan Himalayas’ (1983), and earlier work by Ganesan et al. (1974) (quoted by Bhargava, 1995) on the Tethyan (young sedimentary) rocks of the Lingshi area, as discussed in Bhargava’s, ‘The Bhutan Himalaya, A Geological Account’ (1995), very few studies have been published about this spectacular landscape. Grujic (2002) published the most recent simplified geological map of Bhutan with a new stratigraphic and tectonic description, (see Figure 3), on which the survey gradsect has been indicated with a blue dotted line. At
8Figure 6. Geological map of Bhutan
lower elevation it commences from Drukyel Dzong through the Greater Himalayan Sequence of the Thimphu Formation, with high-grade metamorphic rocks, mainly gneisses including the Taktsang granites. In the middle of the survey section it is dominated by intrusive leucogranites and towards the higher altitudes the survey transect crosses the Chekha Formation with phyllites and phyllitic quartzites. Pure Tethyan sediments of the Lingshi Klippen Formation (LK), including shales and slates, are found on the higher slope segments to the east of Paro Chhu and in the alluvial, fluvioglacial and glacial deposits of the valley bottom. As in most parts of Bhutan the general orientation of the strata is North to North-East, and measured for transect point 2 as 310/18, meaning trending to the NW with a dip of 18 degrees. Rock types of importance for the survey are granites, gneisses, phyllites, quartzites and phyllitic quartzites. Besides the consolidated rock types the transects run through an important series of unconsolidated materials consisting of alluvial and debris flow deposits in the lower section and a mixture of alluvial, debris, fluvio-glacial and glacial deposits in the upper section. In the Himalayas, with increasing elevation, one often finds older rocks overlain with younger rocks, with the older Precambrian basal gneisses and granites overlain with younger Cambrian phyllites and quartzites and youngest, surface sedimentary Tethyan rock all intruded by young leucogranites. Bhargava (1995) gives a more detailed account of multiple formations as Shodug, Barishong, Lingshi and Chekha, but here preference is given to the generalized map as presented by Grujic (2002). Of interest is the description of the Jhangothang Fault by Bhargava (l.c.) that forms a direct contact between Barishong and Thimphu Formations. This fault line in the landscape is reflected by a distinct morphological difference between the western and eastern valley slopes of the Upper Paro Chhu Valley, resulting in obvious asymmetrical valley development. 3.2.2 Geomorphology The landscape along the survey gradsect is the combined result of the characteristics of the geological substratum and its orientation, the physical processes of weathering, erosion and deposition and the interaction with vegetation and human interference. As the gradsect follows essentially an elevational gradient from 2600m to about 4500m it represents a gradsect across a range of surface processes determined by climate, altitude and aspect. Within the dominating geomorphological features and related processes, the overall gradsect can be partitioned into three main subsections2: 2600-2900m Broad alluvial valley (WC22-20) A relatively wide valley bottom with enough space for considerable infill with alluvial deposits of the main river, the Paro Chhu, combined with alluvial fan and debris fan deposits of the many tributaries from side valleys. The relatively gentle sloping land of the alluvial terraces and fans is partially cultivated, especially downstream from Gunitshawa. 2900-3700m Narrow V-shaped alluvial valley (WC19-14) In this middle section the Paro Chhu is trapped in a narrow gorge-like valley floor with no opportunity to meander or deposit material. The river is actively incising and has a steep elevational gradient. The steep valley floor is filled in with rock-fall debris and colluvium combined with alluvial deposits wherever the Paro Chhu has sufficient space to form deposits. While tributaries are able to form steep alluvial and debris fans with 2 See Table 2 for transect listing
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steep gradients, these are of limited volume in restricted space and the main river is actively eroding. The valley floor is almost completely covered by natural primary forest. 3700-4500m Wide U-shaped glacial valley (WC13-1) The upper section is characterized by a relatively wide valley floor with steep valley slopes, often developed in hard rock. The eroding action of the main valley glacier (originating from Jichu Drakey) has oversteepened3 the slopes and deepened the valley floor. Post-glacially the valley floor has been infilled with fluvio-glacial and fluvial deposits, although glacial deposits gain importance with increasing elevation as witnessed by conspicuous moraine deposits along the valley slopes and closer to the glacier front by frontal moraine relicts across the valley floor. It must be be noted that this glacial valley system is largely asymmetrical with the south-eastern valley slope predominantly developed in hard rock with very steep slopes by glacial action. The much gentler north-western valley slope on the other hand is largely covered by glacial and colluvial deposits originating from the glacial valley systems to the north. The glacial valley development is geologically very young with the retreat of the main Jichu Drakey glacier occurring only during the last 10,000 years. In the upper section above 4000m the retreat of the main glacier has occurred over the last few hundred years (between Jhomolhari BC and Jangothang village) with accelerated retreat of the glacier front over the last decades, as witnessed by pro-glacial lakes in front of the Jichu Drakey and Jhomolhari glaciers. The wide glacial valley is occupied by permanent settlements and the steep valley slopes are used as grazing ground for yaks. 3.2.3 Disappearing glaciers Global warming is severely impacting the Himalayan glaciers with recent studies forecasting that by 2035 most of the glaciers will have disappeared (Anthal et al. 2006). Others (Alford et al. 2009) dispute this opinion, but do not contest that the Himalayan glaciers are on the retreat. Our visits to the glacier fronts of both Jichu Drakey glacier, the main source of Paro Chhu, and Jhomolhari glacier seem to confirm the retreat. Both glaciers have developed a series of distinct lateral and frontal moraines along the valley slopes and valley floor downstream of their present glacier front. These stages could be interpreted as related to a last advance stage described worldwide as the “Little Ice Age” climaxing around 1850AD. The Jhomolhari glacier has formed three clear morainic stages indicated in red, purple and green on the satellite image depicted in Figure 4. The red stage is at about 4150m, the purple at 4300m and the green at 4400. A recently formed pro-glacial lake appears to be growing relatively quickly as the size has clearly increased when compared to the satellite image of about 3 years ago (present shape indicated in solid light blue). The present glacier front is indicated by a dotted blue line and it is alarming to note that less than 1.5km of valley glacier remains of the Jhomolhari glacier tongue. A similar trend can be observed for the Jichu Drakey glacier where a pro-glacial lake of about 200m wide and 350m in length has formed. The lake is drained by three different outlets reducing a risk for outburst of the pro-glacial lake. However, during the survey, close to transect WC05 at about 4250m, it was observed that the moraine contains ice
3 ‘Oversteepening’ is the result of glacial erosion resulting in very steep valley slopes with a U-shaped profile beyond the normal influence of erosional and denudational slope processes
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cores. Signs of dead-ice morphology are present, witnessing collapse processes as the dead-ice bodies melt and destabilize the covering morainic material. Presence of dead-ice bodies in a frontal and lateral moraine can lead to failure of the moraine. These should be monitored as they may exacerbate the risk posed by the pro-glacial lake of Jichu Drakey glacier, see Figures 5 and 6. These ecological significance of these unsettling trends strongly indicates a need for a systematic approach to monitoring change in both biological as well as physical properties. To that end the team established spatially-referenced transects (WC04, WC05) on moraine fronts and ridges (Fig. 7) (see methods and discussion). [AG] Figure 4. Frontal moraine stages of Jhomolhari glacier at 4150m (red), 4300m purple and 4400m (green). The pro-glacial lake is indicated in light blue with the present glacier front marked with a dotted blue line.
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Figure 5. Jichu Drakey glacier front with its pro-glacial lake and two streams draining the lake.
Figure 6. The frontal moraine of Jichu Drakey glacier with dead-ice bodies exposed bordering the pro-glacial lake (indicated with red arrows)
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Figure 7. Spatially referenced transect monitoring site (WC04) on frontal moraine recorded using VegClass. This transect was the third highest in plant diversity (63 species, 45 PFTs) and the second most complex PFT site (PFC = 292) 4. Team structure The multidisciplinary expertise of the six-member survey team ( Table 1., Fig. 8) greatly facilitated an integrated aproach to survey. While each team member contributed specific expertise in the recording of field data, the survey was designed and coordinated jointly by NSSC and CBM. Table 1. Team membership and area of expertise No. Name Institution Task/Expertise 1 Tshering Dorji NSSC Soil specialist 2 Dorji Gyaltshen RNR-RC, CoRRB Plant ecologist 3 Tandin Wangdi NBC Botanist 4 Rebecca Pradhan RSPN Botanist/ ornithologist 5 Hans van Noord NSSC Geomorphologist 6 Andrew N. Gillison CBM Biodiversity specialist
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Figure 8. The “A” team. Alpine survey of the upper Wangchhu L->R from back: Dorji Gyaltshen, Tshering Dorji, Tandin Wangdi, Rebecca Pradhan, Andrew Gillison, Hans van Noord. At Jhomolhari base camp (4,300m elevn.)
5. Methodology As with the present survey, a uniform sampling methodology using well-established rapid survey design is to be applied to each of the planned sections of the Wangchhu watershed. Methods of data and information acquisition about the living natural resource must be tailored to management purpose and scale both in the present and foreseeable future. In addition the data acquired must be analyzable using standard, repeatable procedures, with outcomes readily interpretable to policy planners and decision makers. The present system of survey design and data collection is based on experience in many developing countries. Designing and implementing biodiversity baseline studies can be extremely costly and time-demanding if applied using standard statistical approaches and purely species-based inventory. Where the intent is to improve chances of locating taxa, rapid appraisal methods using low-cost, high-return, gradient-directed transects or gradsects are usually far more cost-effective (Gillison and Brewer 1985; Wessels et al. 1998; USGS-NPS 2003). Gradsects are now widely used in surveys in both developed and developing countries where there is a need for rapid appraisal of the distribution of existing biota. They are now the preferred option for the National Vegetation Classification of the mainland USA as implemented by the Parks Service and The Nature Conservancy. When coupled with a standard recording protocol (VegClass) for species, plant functional types (PFTs) (Gillison and Carpenter 1997; Gillison 2002), vegetation structure and key site physical variables, gradsects provide a potentially useful means of rapidly establishing a knowledge baseline for planning and management. The user-friendly VegClass system is
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fully described elsewhere4 has been used in 12 developing countries to successfully train personnel with limited field experience and for whom English is not a first language. Unlike the majority of surveys that employ non-standard approaches, data acquired from more than 1800 sites worldwide using the standard rapid survey VegClass protocol provide a ready means of data comparison and evaluation. Biodiversity baseline data are but one element of the resource management matrix and are too often considered as stand-alone data. The reasons for this lie in the nature of the data that are often highly qualitative or else are restricted to species lists that when used in the absence of other biophysical data, can be relatively meaningless for sustainable management. To counter this problem, the VegClass system includes rapid, quantitative measurements of plant features, including morphological elements that reflect photosynthetic activity and other aspects of plant adaptation to environment (Plant Functional Types or PFTs) as well as vegetation structure, plant species and key site physical variables. In this respect the methodology differs from standard inventory procedures that focus more on species and broader aspects of vegetation physiognomy and structure. A review of literature of survey methods in cool temperate environments such as the upland Wangchhu, indicates that lichens as well as bryophyte can carry useful information about biodiversity. Surveys in the Siberian Arctic using VegClass (P. Krestov, pers. comm.) suggest that the recording of lichens might be useful in the present study. To that end we included cover-abundance estimates of fruticose, crustose and foliose lichens that are broadly representative classes of lichens as a whole. To be considered as a useful resource component, biodiversity should play an integral part in contributing to management goals in a way that facilitates decision-making and trade-offs with respect to profitable land use and the prevention and rehabilitation of degraded lands. Case studies using the standardized VegClass approach combined with gradsects in baseline surveys in Africa, Brazil, Indonesia and Thailand have shown that when combined with soil, faunal and remotely sensed data, the robust statistical linkages provide a science-based approach to selecting readily observable field indicators for biodiversity and agricultural productivity. All plant-based data collected using this system are quantitative - thereby facilitating numerical analysis and reducing dependence on subjective interpretation. The user-friendly, open-source (public domain) software includes a means of internal data analysis and provides a ready means of exporting data according to industry-standard, spread-sheet or database programs. The spatially referenced data acquired using this methodology also lend themselves to spatial analysis such as predictive (GIS) modeling and mapping of species, functional types or biodiversity patterns. In the present study, information from a variety of institutional and online sources (maps, remote sensing) and literature indicated that a thermal gradient was most likely to account for species performance and distribution, followed by soil moisture (cf. Wangdo and Ohsawa, 2006). Sample sites were therefore located using gradsects derived according to a hierarchy of nested environmental gradients (thermal (elevation), drainage,
4 www.cbmglobe.org
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terrain (slope, aspect), lithology, land cover and land use). Despite careful attention to these criteria, final locations were necessarily influenced by the extreme physical characteristics of the mountainous terrain. At each site we positioned a 200 m2 (40 x 5m) transect according to the standard VegClass recording procedure (Gillison, 2002), where we recorded site physical details, vegetation structure, presence of all indigenous and introduced vascular plant species and plant functional types (PFTs) (Annex II). A rule set and grammar (Gillison & Carpenter, 1997) incorporated in the VegClass software were used to construct PFTs from a generic set of 36 plant functional elements (PFEs) ( based on the plant functional attributes of Gillison (1981)). We used VegClass to generate a plant functional complexity (PFC) value as a complement to PFT richness. PFC is not a measure of functional diversity in the usual ecological sense ( cf. Magurran 2004) but is potentially useful when comparing transects where PFT richness may be identical but where PFT composition varies (Gillison, 2002). Faunal observations (birds, mammals, butterflies) were observed on an opportunistic basis only due to logistic constraints and prevailing weather conditions. Records of avifauna were made in the general area of each transect where possible (R. Prabhan). Landuse history was documented where possible from interviews with local farmers. Within each transect, soils were described according a a standard NSSC proforma that included soil texture, color, diagnostic horizons and aggregates. An auger was used to establish soil depth at multiple locations along the transect. A composite 1 kg soil sample was taken of the topoil and bulk density was sampled using standard 100cc rings. The extremely rocky surface of several sites made sampling difficult and in one case (WC05) sampling was abandoned for this reason. Standard laboratory procedures were applied to determine soil physico-chemical properties. The soil data acquired in both field and laboratory were entered in a standard NSSC soil database format consistent with the developing soil database for Bhutan. Preliminary linear and non-linear regression analysis was used to explore statistical relationships between the variables recorded by VegClass and the full range of soil properties. Only correlates with P < 0.05 were considered for potential indicator value. Under conditions where single attribute correlations may carry very limited information, improvements in predictive value can be explored through multidimensional scaling (MDS) of defined composite attribute sets. In our case we used MDS via the PATN multivariate software package (Belbin, 2008) with a Bray-Curtis similarity measure and a semi-strong hybrid scaling (SSH) procedure (Belbin, 2008). In many ecological studies, two or three-dimensional ordinations are commonly run to visualize the distribution sites on significant environmental gradients. In many such cases the first axis tends to account for more environmental variability than the others. For this reason, and because single axis rather than multiple axis solutions are better suited to correlative analyses, we extracted single axis values for each set of plant, soil and remotely sensed variables. Each set of axis scores for plant, soil and remote sensing was then regressed against the other in turn. We also applied SSH to a sub-set of six plant-based variables (species and PFT richness, species:PFT richness ratio, mean canopy height, basal area, litter depth) known from similar studies in other countries to correlate well with soil properties and faunal species richness (Gillison 2000, Gillison et al. 2003). Where significant correlates occur, it is then possible to compare the relative contribution of each variable to each axis in turn and thus identify those carrying best indicator value.
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6. Results 6.1 The survey gradsect: The team sampled 22 transects that, apart from accommodating a primary elevational (thermal) gradient, included a range of natural vegetation cover and a land use intensity gradients ranging from forest exploitation and sedentary agriculture to alpine grazing systems (Tables 2,3,4). The steepness of the terrain combined with changing weather patterns limited access to higher elevations, particularly in forested locations in steep gorges with near vertical slopes and rocky terrain. Nonetheless, several transects were sampled along slopes > 70%. Plant species and PFT diversity together with vegetation structural features are listed in Tables 5,6. All recorded vascular plant species are tabulated in Annex III and PFTs in Annex IV. A cross-section of habitat types and lichens is displayed in Figs. 9,10. Table 2. Transect locations and site physical properties
Transect Location Lat. S Long. E Elevn (m)
Slope%
AspectDeg.
WC01 Jangotang River (Parochhu) 27.78277 89.34315 4105 2 215 WC02 Jangatang (Parochhu) Near Jhomolhari Base camp 27.78162 89.33900 4141 75 50 WC03 Jangathang river, near Jhomolhari base camp 27.78205 89.34169 4121 84 155 WC04 Jichu Drake, frontal moraine 27.79916 89.35176 4248 45 200 WC05 Jitcha Drake (soil-less) morainal ridge. 27.80207 89.35950 4350 20 185 WC06 Hillside above Jitchu Drake lake. Yak herder hut 27.80232 89.35453 4401 35 280 WC07 Below WC5, Yak herder's hut, nr J. Drake. glacier lake 27.80144 89.35369 4389 30 245 WC08 About 500m NE of Jhomolhari base camp 27.78460 89.34583 4039 5 200 WC09 Near Jangothang river, Jhomolhari base camp 27.78405 89.34341 4134 40 150 WC10 Jhomolhari base camp near Jangothang river 27.78183 89.34199 4084 0 0 WC11 Near Jangothang river, Jhomolhari base camp 27.78079 89.34220 4084 4 125 WC12 Jamphu village 27.74684 89.29714 3865 30 120 WC13 Between Jamphu and Soi Thangtangka campsite 27.73254 89.29136 3825 90 150 WC14 Below Soe Thangthangka campsite 27.70538 89.28930 3647 20 160 WC15 Near junction to Soe Soe Yaksa 27.69880 89.29124 3500 75 290 WC16 Ca. 3km downstream from Soe Yaksa bridge 27.68598 89.27512 3405 10 310 WC17 Below Shingkarab (500m S) 27.64218 89.25940 3100 45 100 WC18 3km S from Shinkarab towards Shana 27.63088 89.25492 2992 22 120 WC19 Ca. 2km North of Shana 27.61720 89.25948 2939 17 75 WC20 500m E of Gunitsawa Army camp 27.59274 89.29328 2811 25 200 WC21 Chubisa 27.58545 89.29440 2732 5 270 WC22 Ca. 2km NW of Meni Zampa 27.54749 89.31267 2603 5 160
17
Table 3. Temperature and annual precipitation*
Transect Min temp
°C Max temp
°C Precip. mm yr-1
WC01 -18.3 12.4 343 WC02 -18.3 12.4 343 WC03 -18.3 12.4 343 WC04 -18.3 12.4 343 WC05 -18.3 12.4 340 WC06 -18.3 12.4 340 WC07 -18.3 12.4 343 WC08 -18.3 12.4 343 WC09 -18.3 12.4 343 WC10 -18.3 12.4 343 WC11 -18.3 12.4 343 WC12 -17.5 13.0 375 WC13 -17.5 13.0 375 WC14 -17.3 13.0 387 WC15 -17.3 13.0 387 WC16 -15.6 14.2 453 WC17 -12.7 16.2 599 WC18 -12.7 16.2 599 WC19 -12.7 16.2 599 WC20 -11.7 16.8 663 WC21 -11.7 16.8 663 WC22 -14.4 14.7 541
* Derived from climate surface supplied by H. Greenberg UW
Table 4. Vegetation typology and land use Transect Vegetation type and land use WC01 Low Salix shrubland WC02 Betula utilis forest - almost krummholz form. Dense herbaceous ground layer WC03 Mixed woody and herbaceous vegetation on old moraine face. WC04 Mixed woody but mostly herb cover. Rhododendron, Asteraceae, Cotoneaster WC05 Mixed herbaceous species with some Rhododendron, Myricaria, Ephedra WC06 Mixed shrubland and alpine meadow WC07 Alpine meadow, mostly herbaceous WC08 Alpine meadow dominated by Senecio amplexicaulis and Allium micrantha WC09 Remnant Juniper, Salix forest WC10 Herbaceous meadow dominated by Rumex nepalensis WC11 Alpine meadow, heavily grazed, dominance of cryptophytes WC12 Mixed conifer-broadleaf forest (Juniperus-Betula). Dense woody understorey WC13 Mixed Abies-Juniperus-Betula-Salix forest
18
Transect Vegetation type and land use WC14 Regenerating Betula forest with Juniperus, Larix, Acer and dense herb ground layer WC15 Mixed conifer broadleaf forest; Abies, Betula, Acer WC16 Conifer-broadleaf tall forest; Larix, Betula, Acer WC17 Mixed broadleaf-conifer forest, Quercus, Abies, Betula WC18 Mixed broadleaf, conifer forest; Quercus, Tsuga, Picea, Acer,dense herb ground layer WC19 Mixed conifer-broadleaf forest, Spruce, blue pine, Oak, Maple, with dense understoreyWC20 Conifer-broadleaf forest with dense regen Oak understorey WC21 Buckwheat crop being harvested for fodder WC22 Regenerating Pinus wallichiana on abandoned land
Table 5. Summary of species, PFTs and PFC
Transect Species PFTs Spp:PFT PFCWC01 70 55 1.27 342 WC02 55 47 1.17 284 WC03 63 45 1.40 292 WC04 48 38 1.26 218 WC05 23 21 1.10 172 WC06 64 38 1.68 208 WC07 34 25 1.36 96 WC08 48 35 1.37 220 WC09 62 44 1.41 236 WC10 54 42 1.29 218 WC11 32 27 1.19 150 WC12 52 42 1.24 258 WC13 60 45 1.33 246 WC14 50 43 1.16 246 WC15 35 33 1.06 216 WC16 38 38 1.00 216 WC17 28 28 1.00 186 WC18 55 46 1.20 248 WC19 39 35 1.11 232 WC20 38 33 1.15 190 WC21 15 11 1.36 88 WC22 54 44 1.23 230
Table 6. Vegetation structural features * Transect Ht CCTot CCWdy CCNwdy Bryo WPlts Litt BA MFI FICV
WC01 2.00 98 95 3 9 5 Lit 3.00 100.00 0.00 WC02 5.00 90 80 10 3 7 0.20 24.00 87.70 16.93 WC03 0.70 75 30 45 6 7 5.00 1.00 100.00 0.00 WC04 0.40 40 10 30 4 5 0.01 0.10 100.00 0.00 WC05 0.20 10 1 9 1 4 0.20 0.01 100.00 0.00 WC06 0.40 98 50 48 7 6 0.01 1.00 100.00 0.00 WC07 0.10 98 5 93 1 7 0.50 0.01 100.00 0.00
19
20
Transect Ht CCTot CCWdy CCNwdy Bryo WPlts Litt BA MFI FICV
WC08 0.50 98 2 96 3 6 0.10 0.01 100.00 0.00 WC09 6.00 85 60 25 2 9 0.00 37.33 85.50 27.90 WC10 0.80 98 2 96 3 7 5.00 1.00 100.00 0.00 WC11 0.05 95 1 94 1 3 1.00 0.01 100.00 0.00 WC12 12.00 99 70 29 6 7 0.10 12.00 64.40 48.13 WC13 8.00 90 60 30 6 8 1.50 20.67 49.30 90.27 WC14 10.50 95 90 5 5 8 2.00 35.33 44.25 73.71 WC15 35.00 95 90 5 4 8 2.00 26.00 46.90 101.68WC16 35.00 90 88 2 5 8 7.00 62.67 6.50 195.08WC17 17.00 99 95 4 8 9 6.00 24.33 68.25 51.49 WC18 45.00 98 90 8 5 9 15.00 36.67 44.00 96.75 WC19 16.00 95 90 5 6 8 12.00 50.67 79.50 51.37 WC20 17.00 95 90 5 9 6 15.00 17.33 15.00 244.23WC21 0.90 98 0 98 0 1 7.00 0.00 0.00 0.00 WC22 2.00 95 60 35 5 1 0.20 1.00 73.25 59.44 * Ht = Mean canopy height (m); Cctot= Total canopy projective foliage cover percent; Ccwdy = projective foliage cover percent of woody plants; CCNwdy, PFC of non-woody plants; Bryo = cover-abundance of bryophytes; Wplts = cover-abundance of woody plants <2m tall; Litt = plant litter depth (cm); BA = basal area of all woody plants (m2ha-1); MFI = mean furcation index; FICV = coefficient of variation percent of FI. (See also Annex II for complete listing of site variables)
c Table 7. Cover-abundance scores of lichens
Transect No. Fruticose Crustose FolioseWC01 0 3 2 WC02 4 1 4 WC03 1 6 5 WC04 4 2 1 WC05 4 4 0 WC06 1 1 3 WC07 1 6 2 WC08 0 7 4 WC09 1 2 3 WC10 0 5 4 WC11 0 0 0 WC12 2 2 6 WC13 6 5 6 WC14 7 5 6 WC15 6 4 6 WC16 5 4 6 WC17 8 4 7 WC18 9 3 7 WC19 8 5 6 WC20 3 2 6 WC21 0 0 0 WC22 0 4 1
dc
ba
fe
Figure 9. a. Landform at Jhomolhari base camp; b. Frontal moraine, Jichu Drakey (WC04); c. Data collection on near-vertical slopes (WC03); d. Birch (Betula utilis) forest on 70% slope on
shallow (40cm) soils (WC02); e. Juniper (Juniperus pseudosabina) and Salix daltonia remnant
forest (WC09); f. Disturbed mixed conifer-broadleaf (Abies, Betula, Juniperus) and Rhododendron and Rubus understorey on 90% slope (WC13).
21
a b
c d
g f e
Figure 10. a. Mature stand of Larch (Larix griffithiana) and Fir (Abies densa) (WC16); b. Regenerating Birch (Betula utilis) forest with Acer, Larix and dense herb layer (WC14); c. Mixed conifer/broadleaf forest with understorey of dying bamboo (Thamnocalamus spathiflorus) (WC15); d. Cultivated Buckwheat field (WC21); e. Foliose lichen on Acer pectinatum; f. Crustose lichens on rock face; g. Fruticose lichen on Larix griffithiana.
22
a
b
c
d e
Figure 11. a. Variation in leaf types. High elevation (4600m) megaherb Rheum nobile (Polygonaceae)
(Photo HvN); b. Megaherbs Senecio amplexicaulis (Asteraceae) and Heracleum nepalensis (Apiaceae). c. Mixed PFTs and leaf types (Alliaceae, Asteraceae, Poaceae, Ranunculaceae, Rosaceae, Scrophulariaceae);
d. Nanophyllous Cotoneaster sp. (Rosaceae). e. Nanophyllous succulent (Sedum sp.)
23
e
a b
c d
f
Figure 12. a. Birch (B. utilis) subject to cascading rocks (WC02). b. Hillside ‘scalds’ possibly due to overgrazing and unstable substrate 4300m. c. Multiple successional patterns, Salix, Juniperus, Betula on unstable slopes 4000m. d. Oldgrowth conifer-broadleaf forest Paro Chhu gorge 3500m. e. Cool, moist mixed conifer-broadleaf forest with dense internal cover of ferns, bryophytes and lichens (WC16) 3400m. f. Dense groundlayer of Urticaceae (Pilea, Elatostema) and Asteraceae (WC16).
24
6.2 Plant species and plant functional type diversity Of 1045 vascular plant species recorded during the survey, approximately 577 have been identified so far as unique species. It is anticipated this figure is likely to decrease by a further 5 percent as further indentification proceeds (NBC, RSPN). The team recorded 357 unique (species-independent) PFTs. Although mean annual precipitation is relatively low (<500m), at elevations between approximately 4100 – 5000m, low temperatures combined with frequent mist provide conditions consistent with the occurrence of a wide range of leaf size classes ranging from picophyll (<2mm2) to macrophyll (36,400 mm2) (the latter belonging to so-called ‘megaherbs’) Fig. 11. Patterns of species and PFT richness and composition are closely related to successional stages of vegetation that, in turn, is influenced by a combination of land use pressure and the stability of the substrate. Even in apparently well established Birch forests, cascading rock debris is frequently intercepted by trees ( Fig. 12. a). At the broader scale successional patterns are readily visible (Fig. 12.b,c). In the better protected ravines of the larger waterways, climax or oldgrowth forest has a better chance of development (Fig. 12 d) and understorey structure is manifestly richer in bryophytes and lichens (Fig. 12 e). Under these cool, moist environments herbaceous ground cover proliferates (Fig. 12 f). When species richness (diversity) is regressed against PFT richness the highly significant outcome (P< 0.0001, RSq(adj.) 0.845) (Fig. 13) provides a robust basis for predicting species richness from more readily determined PFT richness. For future assessment and monitoring purposes this may be of benefit where expertise is not at hand to identify species. The highly linear response also suggests a high level of observer consistency. Figure 13. Plant species diversity regressed against PFT diversity
25
6.3 Lichens as potential biodiversity indicators As the use of lichens as biodiversity indicators is relatively novel with respect to the VegClass system, the results of the present survey are reported here as a matter of interest. With additional data from surveys of the remaining sections of the Wangchhu watershed predictive values may change. When results from different team members were compared, observer consistency was deemed adequate in estimating cover-abundance values of the three major classes of lichens (fruticose, crustose and foliose, Fig 10. e,f,g). Of the three classes of lichens, fruticose and foliose lichens provided the most promising indicators (Figs 14 -18).
Figure 14. Fruticose lichens and mean canopy height
26Figure 15. Fruticose lichens and plant litter
Figure 16. Foliose lichens and bryophyte cover-abundance
Figure 17. Foliose lichens and plant species diversity
27
Figure 18. Foliose lichens and PFT diversity
28
From the above figures, fruticose lichens were sigificantly correlated with species:PFT ratio (P< 0.004), mean canopy height (P< 0.0001), basal area (P< 0.0001) and plant litter depth (P< 0.0001). foliose lichens showed a positive linear response to projective crown cover percent of woody plants (P< 0.0001) and a negative linear response to projective crown cover percent of non-woody plants (P< 0.018). Curvilinear (quadratic) response of foliose lichens was exhibited with bryophytes (P< 0.0001), species richness (P< 0.002), PFT richness (P< 0.007). Lichens were only weakly correlated with soil properties. Fruticose and foliose lichens were correlated most closely with soil pHH20 (P< 0.011 and P< 0.001 respectively). 7. Fauna As no systematic survey of fauna was undertaken, the observations contained in this section are essentially opportunistic, recorded as time and weather conditions permitted. In the opionion of RSPN ornithologist R. Pradhan who has wide experience in the alpine area, the species listed in Table 8 represent a reasonable cross-section of the alpine avifauna. By far the dominant faunal influence on the alpine ecosystem is that of the grazing animal. As with plants, the distribution of herbivorous species appears to be determined by temperature – as reflected in elevation. Below 3500m domestic livestock dominate the valley floors and footslopes while above 3500m domesticated Yaks (Bos grunniens) are the main driving influence, associated to a lesser degree with Blue Sheep (Pseudois nayaur) and domestic pack animals – mainly mules. Other mammals included the Himalayan Marmot (Marmota himalayana) that was observed occupying frontal moraine screes (4300m) and at lower elevations Grey Langur (Presbytis entellus) 2800m (Fig. 19). We observed considerable butterfly activity, especially between 2600 and 3400m, possibly as a result of unseasonally mild weather conditions. Among the most common occurrences were the Azure Sapphire (Heliophorus androcles), Common Copper (Lycaena phlaeas) and Blue Pansy (Precis orithrya). (Fig. 19).
Table 8. List of birds observed during survey ‘A’ upper Wangchhu watershed* (R. Pradhan)
Sl. no.
English Name
Scientific Name Zhangothang
4093-4800m
Soe Yaksha Confluence 3578-4093m
Shinkarap
3147- 3578m
Gunichawa
2730-3578m
1. Snow Partridge
Lerwa lerwa 2 with chicks
2. Dark breasted Rosefinch
Carpodacus nipalensis
2
3. Golden Eagle Aquila chrysaetos 1
4. Chough Yellow billed
Pyrrhocorax graculus
100 Aprox, 10
29
Sl. no.
English Name
Scientific Name Zhangothang
4093-4800m
Soe Yaksha Confluence 3578-4093m
Shinkarap
3147- 3578m
Gunichawa
2730-3578m
5. Grey- backed Shrike
Lanius tephronotus
6 with 5 juv. 4 with 4 juv. 3 with 2 juv. 8 with 6 juv.
6. Oriental Turtle Dove
Streptopelia orientalis
6 2 8 12
7. Ibisbill Ibidorhyncha struthersii
3 3
8. Blue Whistling Thrush
Myophonus caeruleus
1 1 1 5
9. Smoky Warbler
Phylloscopus fuligiventer
1 2
10. Dusky Warbler
Phylloscopus fuscatus
2 3 with 1 juv
11. Asian House Martin
Delichon dasypus 16 7
12. White Wagtail
Motacilla alba 3
13. Fire-tailed Sunbird
Aethopyga ignicauda
1
14. Slaty-backed Flycatcher
Ficedula hodgsonii
1 Female
15. Eurasian Cuckoo
Cuculus canorus 1
16. Black-faced Laughing thrush
Gurrulax affinis 3
17. White- winged Grosbeak
Mycerobas carnipes
4
18. Red-headed Bullfinch
Pyrrhula erythrocephala
4
19. Rufous Sibia Heterophasia capistrata
2 10 3
20. Grey-creasted Tit
Parus dichrous 5
21. Spotted nutcracker
Nucifraga caryocatactes
1
22. Rufous bellied woodpecker
Dendrocopos hyperythrus
1
23. Black Bulbul Hypsipetes leucocephalus
7 with 3 juv. 3
24. Chestnut-tailed Minla
Minla strigula 3
25. Fire-tailed Myzornis
Myzornis pyrrhoura
1
30
31
Sl. no.
English Name
Scientific Name Zhangothang
4093-4800m
Soe Yaksha Confluence 3578-4093m
Shinkarap
3147- 3578m
Gunichawa
2730-3578m
26. White- collared Blackbird
Tardus albocinctus
1 1
27. Grey-Winged Blackbird
Turdus boulboul 1M+1F
28. Green- backed Tit
Parus monticolus
2 3
29. Yellow-billed Blue Magpie
Urocissa flavirostris
1
30. Stripe throated Yuhina
Yuhina gularis 10
31. Russet sparrow
Passer rutilans 2 11
32. Rufous- vented Yuhina
Yuhina occipitalis
9
33.
White- throated Laughingthrush
Garrulax albogularis
20
34. Spotted Laughingthrush
Garrulax ocellatus
2
35 Lemon-rumped Warbler
Phylloscopus chloronotus
1
* Observations in general surroundings of transects.
a
d
b
c
e f g
Figure 19. Common Fauna: a. Yaks (Bos grunniens) >3500m; b. Blue sheep (Pseudois nayaur) 4300m; c. Himalayan Marmot (Marmota himalayana) 4300m; d. Grey Langur (Presbytis entellus) 3200m; e. Azure Sapphire (Heliophorus androcles) 3000m; f. Common Copper (Lycaena phlaeas) 3000m; g. Blue Pansy (Precis orithrya) 2600m.
32
8. Soils [ H van Noord, T. Dorji ] The soils sampled clearly reflect the influence of a highly dynamic slope environment. First, soil depth rarely exceeds 40cm. Only below 3000m a.s.l. deeper profiles were described with depths up to 85cm. Second, it has to be noted that the soils were sampled using a standard soil auger, thus limiting the possibility to sample and describe deeper profiles due to the high stoniness of the soils. The nature of the profiles suggests it is unlikely that the use of soil pits would have improved soil description significantly. The shallow soil profile development is confirmed by the abundance of A-C profiles, indicating young soils with recurrent truncation of the top soil by active slope processes (erosion, mass movement). Relatively few profiles have a B horizon development and even then not very pronounced. The organic soil profile as described by the litter (L) and fermentation layer (F) is mostly absent in the alpine soils, found only for Salix and Betula forest transects WC1 and WC2. At lower elevations the L and F layer increase markedly up to 7cm (Annex V) Soil analytical data are listed in Tables 9a, 9b. Textures are predominantly coarse ranging from gravelly sand to sandy clay loam at extremes. The top soil is consistently humic loam and , changes to sandy loam only for the lowest three transects . Because of the high content of humic acids the top soils are very dark (10YR 2/2) and characterized by abundant roots. pH values (pH H20) range from 3.85 to 7.70. The higher values above 7 for WC4, 10 and 11 are striking and may be related to carbonatic rock fragments in either the glacial deposits (WC4) or alluvial deposits originating from the Jichu Drakey glacier area, where carbonates from the Chekha and Lingshi Klippen Formations could be present. The high pH values are combined with a very high base saturation level. The low pH values of 3.8 for WC15 and WC17 could be related to the leucogranite that forms the substratum for these soils and which tends to develop in more acidic profiles. The low pH values are also combined with very low base saturation levels. CEC values on average range between 25 to 45, with some exemptions with very low CEC values (WC1, WC4, WC11 and WC16). WC1 and 4 are on very coarse glacial deposits, WC11 is on a very young alluvial deposit and WC16 is a young debris fan with coarse sandy soils. Most of the unconsolidated material in which the soils have developed is not in-situ and has been deposited by fluvial and fluvio-glacial processes, has been brought there by glacial action. Alternatively it may be a product of the combined effect of slope processes such as erosion and mass movement resulting in colluviation. The lithological composition is therefore varied with particles, stones and boulders of different rocks types present, but dominated by granites, gneisses, phyllitic quartzites and quartzites.
33
Table 9a. Soil properties Transect pHKCL pHDelta Pbray C% N% K-Av Ca_Exch Mg-Exch K-ExchWC01 5.23 0.80 2.47 2.40 1.25 76.66 4.62 0.57 0.28 WC02 4.60 0.56 4.28 14.00 0.59 182.94 20.86 2.70 0.84 WC03 4.65 0.70 2.48 5.80 0.28 42.79 6.12 0.29 0.29 WC04 7.15 0.32 1.22 1.40 0.05 35.59 6.08 0.05 0.12 WC05 * * * * * * * * * WC06 5.38 0.00 0.62 6.00 0.36 94.57 7.25 0.90 0.49 WC07 5.23 0.00 1.43 10.40 0.57 441.34 8.34 1.61 1.78 WC08 5.17 0.00 5.99 6.60 0.43 116.69 7.12 0.96 0.55 WC09 6.03 0.00 6.25 14.00 0.54 160.72 47.34 2.22 0.77 WC10 6.73 0.50 39.46 6.70 0.45 230.98 36.15 1.59 1.03 WC11 7.18 0.62 3.43 0.80 0.03 29.87 4.58 0.18 0.12 WC12 4.91 0.68 4.58 13.60 0.52 242.74 20.32 2.63 1.18 WC13 4.56 0.83 0.87 12.50 0.40 109.86 12.51 2.28 0.51 WC14 4.08 0.64 81.86 4.00 0.23 44.28 1.98 0.22 0.16 WC15 2.95 0.94 11.61 14.00 0.57 210.36 2.15 0.90 0.67 WC16 3.82 0.92 12.44 2.30 0.09 46.15 0.94 0.13 0.15 WC17 2.86 0.99 67.66 14.00 0.56 192.09 0.90 1.09 0.65 WC18 4.47 1.05 4.94 2.50 0.16 67.43 4.55 0.22 0.22 WC19 3.84 0.71 1.03 9.50 0.36 44.84 0.39 0.34 0.19 WC20 3.94 0.94 10.27 7.60 0.41 140.08 5.63 1.08 0.64 WC21 4.87 0.92 70.30 2.70 0.14 100.42 6.85 0.90 0.58 WC22 4.36 1.15 3.08 3.70 0.08 41.48 2.65 0.52 0.27 * Site not sampled due to extreme stoniness Table 9b. Soil properties Transect Na-Exch TEB CEC-Am BS-AmO Sand% Silt% Clay% BulkDensityWC01 0.03 5.50 8.73 63.02 40.00 56.30 3.70 0.68 WC02 0.09 24.49 49.01 49.94 55.90 34.10 10.00 0.31 WC03 0.04 6.74 15.22 44.25 77.80 16.50 5.70 1.05 WC04 0.03 6.28 2.87 218.59 82.00 14.10 3.90 * WC05 * * * * * * * * WC06 0.06 8.70 25.27 34.46 56.40 36.10 7.50 0.80 WC07 0.12 11.85 31.35 37.78 62.10 30.00 7.90 0.66 WC08 0.06 8.69 20.96 41.42 78.60 16.70 4.70 0.92 WC09 0.12 50.45 47.38 106.49 80.70 13.60 5.70 0.49 WC10 0.22 38.99 26.13 149.21 56.20 35.30 8.50 0.72 WC11 0.03 4.91 0.11 446.22 74.90 22.90 2.20 1.29 WC12 0.14 24.27 45.37 53.48 39.30 46.20 14.50 0.66 WC13 0.05 15.35 40.51 37.92 80.30 13.30 6.40 0.33 WC14 0.02 2.38 14.05 16.99 71.30 22.70 6.00 1.08 WC15 0.09 3.81 51.23 7.43 62.70 31.10 6.20 0.40 WC16 0.06 1.28 9.51 13.38 84.40 11.40 4.20 1.14 WC17 0.08 2.72 46.31 5.87 78.90 16.70 4.40 0.58
34
Transect Na-Exch TEB CEC-Am BS-AmO Sand% Silt% Clay% BulkDensityWC18 0.03 5.02 13.55 37.08 75.90 20.80 3.30 0.69 WC19 0.03 0.95 43.62 2.18 41.70 41.60 16.70 0.41 WC20 0.05 7.40 35.55 20.80 62.70 28.10 9.20 0.58 WC21 0.07 8.40 15.11 55.60 59.20 26.10 14.70 1.14 WC22 0.03 3.47 14.57 23.84 52.30 29.30 18.40 1.13
* Site not sampled due to extreme stoninenss
9. Plant – soil relationships Plant species, PFT richness and vegetation structure were only weakly correlated with soil properties and then mainly with soil pH. Individual Plant functional elements (PFEs) on the other hand show a much stronger relationship with soil properties with about half of the PFEs being signficantly correlated with a subset of soil elements, mainly pH (Fig. 20), P, N, CEC, Base saturation, organic carbon and total N. While the significance of these relationships is being further explored, it is with the expectation that these correlations are likely to change with the addition of survey results from Sections B and C. A linear regression of single-axis ordination scores of six key vegetation variables against single-axis ordination scores of all soil variables was statistically significant (Fig. 21). Vegetation structure contributed most to the soil ordination scores (Mean canopy height P< 0.0001; Basal area P< 0.0001; Litter depth P< 0,0001; Bryophyte cover-abundance P< 0.0001. Soil properties were poorly correlated with vegetation ordination scores, the main correlate being soil pHH20 P< 0.0001. With the exception of bryophyte cover-abundance and litter depth (P< 0.006 and P< 0,035 respectively), soil bulk density was not significantly correlated with any plant-based variable either singly or with ordination scores.
Figure 20. Soil pH and frequency of PFTs with greenstem photosynthesis (green
exernal bark cortex (ct)) across transects
35
Figure 21. Vegetation and soil relationships expressed via ordination 10. Discussion The highly dynamic nature of the alpine land forms combined with recent colluvial and fluvial processes almost certainly influences soil properties and resulting complex mosaics of vegetation types that are further modified by intensive land use especially grazing. Under these conditions but with the likely exceptions of heavily grazed meadow flats, soil bulk density has little apparent influence on plant performance. This runs counter to experience in tropical lowland ecosystems where soil-plant relationships tend to be much more stable and where bulk density is a significant determinant of both plant and animal biodiversity. The inherent dynamism of the upper Wangchhu watershed may be responsible in part for the weak correlations detected between soils and plant-based attributes. Soil pH and to a lesser extent cation exchange capacity (CEC) are among the few soil properties correlated with certain vegetation structural elements and to a much lesser degree plant species and PFT diversity. While individual PFEs exhibit stronger correlates with soil properties (e.g. Fig. 20) there are, as yet, no evident explanations for these relationships. While it is tempting to speculate about causality, caution is indicated until further data come to hand through surveys ‘B’ and ‘C’ along the Wangchhu. Initial field observations suggested slope and aspect might play a key role in determining plant diversity and vegetation structure. Apart from near-vertical (largely unsampled) slopes, this is not supported by numerical analysis that suggests such influence is secondary to primary thermal and secondary soil moisture gradients. Available annual rainfall data (‘precipitation’, Table 3) indicate the survey area lies within a low rainfall belt subject to periodic dessication. While this is reflected in the plant functional adaptation to extremes of drought and thermal stress (above-ground succuence and below-ground storage organs of numerous cryptophytes), a more accurate
36
representation of available moisture should include mist interception measurements. A consideration of elements of vegetation cover is clearly relevant to hydrological modeling as currently applied to the developing DrukDIF. While PFTs, PFEs and vegetation structure should, in principle, play a relevant part in the distribution of water within and across landscapes, it is not yet clear how these elements can be built in to process modeling of water transport in the upper Wangchhu watershed. A more enlightened framework may become evident with additional surveys further down the watershed. Tree rooting depth is one component of the DrukDIF hydrological modeling that was not measured in this section of the survey. From the few opportunities available to the team, it would seem rooting depth is closely correlated with measureable soil depth that, in turn, may be influenced by soil creep and colluvial and fluvial processes especially on unstable slopes. A notable ecological feature of the vegetation was the observed extreme range of leaf size classes where large-leaved (macrophyll) ‘megaherbs’ occurred in close proximity to exceedingy small (picophyll) leaves. The disparity in leaf sizes clearly reflects differential plant adaptation to environmental extremes via varying combinations of plant functional elements. While there is no simple ecophysiological explanation for this phenomenon other than a response to locally varying conditions of atmospheric and soil moisture, the occurrence of macrophyllous leaves on so-called ‘megaherbs’ (Fig. 11) is consistent with similar areas elsewhere in the world that are subject to extremes of temperature and moisture availability (cf. Petasites in the Greater Caucasus, Archangelica ‘forests’ in Kamchatka, Fennoscandian ‘Rheum’, Stilbocarpa in the sub-antarctic convergence and Gunnera in the South American Andes). Overall plant diversity recorded on this section of the Wangchhu watershed appears to be consistent with other observations in the Eastern Himalaya and the ‘Kanchenjunga Landscape’ (WWF and ICIMOD, 2001; Olson et al. 2001) although published accounts of plot-based records are rare. Highest alpha (within-plot) species diversity is most closely associated with conditions that appear to maximise niche-space, typically in scree slopes and meadow pastures. Under these conditions PFTs are also most diverse ranging from perennial cryptophytic (below-ground or geophytic) perennating organs to short-lived, therophytic annuals. The application of lichen-based descriptors in a survey of this kind is relatively novel. Due to their inherently complex and often cryptic life form, the inclusion of lichens in most vegetation surveys tends to be avoided by mainstream ecologists. It is a different matter in the arctic where lichens are a relatively important vegetation component as well as a significant source of mammalian food. Because of some similarities in thermal extremes with high latitudes, and following the advice of a Russian colleague5 who had already trialled VegClass in the Siberian arctic, lichens were included in the present survey. The results speak for themselves (Figs. 14-18), with lichens clearly performing equally if not better than most standard VegClass descriptors as biodiversity indicators. The degree of success may be related to wide-ranging lichen cover-abundance that tends to peak in closed canopy conifer-broadleaf forests in protected gorges between 2800-3800m (Table 7) under conditions of high ambient moisture.
5 Dr Pavel Krestov, Institute of Biology and Soil Science, Vladivostok
37
11. Conclusions As indicated in the foregoing, while the results of the statistical analyses suggest a number of immediate conclusions, experience in surveys along elevational gradients in other countries strongly suggests such conclusions be witheld until additional data have been analysed from surveys “B’ and “C”. Nonetheless, a number of findings can be made highlighted as a result of the present survey. First, as a practical test of a methodological framework referred to in the TOR, the survey methodology clearly satisfied the norms of cost-efficient survey design and implementation. Trainees quickly adapted to the rapid field recording technique and were able to record observations with a high level of repeatability, especially with respect to recording PFTs. This is reflected in Fig. 13 that shows a close correspondence between species and PFT diversity. To that extent, consolidation of previous laboratory-based training with intensive field-based experience satisfies a key element of the TOR. Second, the integration of both soil and vegetation components is a first for a survey in Bhutan. Such integration provides not only a common platform for identifying predictive relationships between biodiversity and soil nutrient availability (and thus potential agricultural productivity) but in so doing, provides a science-based approach to decision-making for adpative management. The plant-soil-landuse nexus also suggests a more meaningful input to hydrological and other process-based resource modeling than if survey data were restricted to soil or plant or landuse alone. Third, the spatially-referenced, numerical data acquired from this survey are readily transferable to the developing DrukDIF as well as other spatial analytical platforms. The generic, industry-standard format of the VegClass data also facilitates comparison with data similarly collected in other countries. While the soil data are consistent with the developing national soil database for Bhutan, the plant-based data also offer a potentially useful complement to the developing National Forest Inventory that plans to include elements of biodiversity. Finally, the current urgency surrounding the climate change debate and the related phenomenon of disappearing glaciers raises the question of establishing an effective knowledge baseline for first assessing and then monitoring change in dynamic alpine environments that, by their very nature, are highly vulnerable to climate change. Most monitoring procedures to date (e.g. for the Thorthormi glacier) focus on physical rather that biophysical reference points. By establishing a series of spatially-referenced transects on the Jichu Drakey glacier frontal moraine the team has documented fine-scale plant-based elements of biodiversity that are known to be highly sensitive to environmental change. Combined with the well documented site physical aspects, such reference points may be potentially useful for monitoring environmental change in this immediate area and possibly for similar locations elsewhere in Bhutan and the adjoining Kanchenjunga landscape.
38
12. References Alford, D., Armstrong, R. and Racoviteanu, A. (2009). Glaciers in the Himalayas: A
preliminary look at estimating runoff from glacier-covered watersheds of Nepal using area-altitude distributed models. (Powerpoint presentation; World Bank and NASA). (unpubl.) http://www.kathmandutocopenhagen.org/Richard%20Armstrong.pdf
Anthwal, A. et al. (2006). Retreat of Himalayan Glaciers – Indicator of Climate Change.. Nature and Science, 4: 53-59.
Bhargava, O.N. (Ed.) (1995). The Bhutan Himalaya : A Geological Account. GSI. 245 p. Ganesan, T.M. et al., (1974) (Quoted by Bhargava, 1995). Gansser, A. (1983) Geology of the Bhutan Himalaya. Basel [Switzerland] ; Boston :
Birkhäuser Verlag. Gillison, A.N. (2002) A generic, computer-assisted method for rapid vegetation
classification and survey:tropical and temperate case studies. Conservation Ecology, 6: 3. (http://www.ecologyandsociety.org/vol6/iss2/art3/print.pdf).
Gillison, A.N. (2009) . Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase I: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. June 5 2009. (NSSC Thimphu).
Gillison, A.N. and Brewer, K.R.W. (1985). The use of gradient-directed transects or gradsects in natural resource survey. Journal of Environmental Management, 20: 103-127.
Gillison, A.N. and Carpenter, G. (1997). A generic plant functional attribute set and grammar for dynamic vegetation description and analysis. Functional Ecology, 11: 775-783.
Gillison, A.N. and Liswanti, N. (2004) Assessing biodiversity at landscape level: the importance of environmental context. In T.P Tomich, M. van Noordwijk and D.E. Thomas, D.E. (Eds.), Environmental Services and Land Use Change: Bridging the Gap between Policy and Research in Southeast Asia. Agriculture, Ecosystems and Enviroment, 104: 75-86.
Gillison, A.N., Babu, M.M., Williams, A.C. et al., (2009). Assessing linkages between land use and biodversity: A case study from the Eastern Himalayas using low-cost, high-return survey technology. In: P.S. Low (ed.) ‘Global Change and Sustainable Development: Asia-Pacific Perspectives’ Chapter 18. Cambridge University Press (in press 2009)
Grujic, D., Hollister, L. S. and Parrish, R. R. (2002). Himalayan metamorphic core as an orogenic channel: insight from Bhutan. Earth and Planetary Science Letters, 198: 177-191.
Magurran, A.E. (2004). Measuring Biological Diversity. Blackwell publishing, Oxford. 254 p.
Norbu, C. et al. (2003). A Provisional Physiographic Zonation of Bhutan. Journal of Bhutan Studies, 8: 54-87.
Olson, D.M., Dinerstein, E.D. Wikramanayake, N.D. et al. (2001) Terrestrial Ecoregions of the World: A New Map of Life on Earth. BioScience, 51: 933-938.
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Rawat, G.S. and Wikramanayake, E.D. (2001) Eastern Himalayan broadleaf forests (IM0401). ( see Olson et al., 2001) (http://www.worldwildlife.org/wildworld/profiles/terrestrial/im/im0401_full.html.
USGS-NPS. (2003). United States Geological Survey – National Parks Service, Vegetation Mapping Program 5.0 Field methods (http://biology.usgs.gov/npsveg/fieldmethods/sect5.html)
Wangchuk, S. (2007). Maintaining ecological resilience by linking protected areas through biological corridors in Bhutan. Tropical Ecology. 48: 176-187.
Wangda, P. and Ohsawa, M. (2006). Gradational forest change along the climatically dry valle slopes of Bhutan in the midst of humid eastern Himalaya. Plant Ecology, 186: 109-128.
Wessels, K.J., Van Jaarsveld, A.S., Grimbeek, J.D. et al. (1998). An evaluation of the gradsect biological survey method. Biological Conservation, 7: 1093-1121.
WWF and ICIMOD (2001) Ecoregion-based conservation in the Eastern Himalaya: Identifying important areas for biodiversity conservation. Wikramanayake, E.D., Carpenter, C., Strand, H. and McKnight, M. (eds). World Wildlife Fund (WWF) and Center for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal Program.
ANNEX II
List of data variables recorded for each 40x5m transect
Site feature Descriptor Data type Location reference Location Alpha-numeric Date (dd-mm-year) Alpha-numeric Plot number (unique) Alpha-numeric Country Text Observer/s Observer/s by name Text Physical Latitude deg.min.sec. (GPS) Alpha-numeric Longitude deg.min.sec. (GPS) Alpha-numeric Elevation (m.a.s.l.) (aneroid or GPS) Numeric Aspect (compass. deg.) (perpendicular to plot) Numeric Slope percent (perpendicular to plot) Numeric Soil depth (cm) Numeric Soil type (US Soil taxonomy) Text Parent rock type Text Litter depth (cm) Numeric Terrain position Text Site history General description and land-use / landscape
context Text
Vegetation structure Vegetation type Text Mean canopy height (m) Numeric Crown cover percent (total) Numeric Crown cover percent (woody) Numeric Crown cover percent (non-woody) Numeric Cover-abundance (Domin) - bryophytes Numeric Cover-abundance woody plants < 2m tall Numeric Basal area (mean of 3) (m2ha-1); Numeric Furcation index (mean and cv % of 20) Numeric Profile sketch of 40x5m plot (scannable) Digital Plant taxa Family Text* Genus Text* Species Text* Botanical authority Text* If exotic (binary, presence-absence) # Numeric Plant Functional Type Plant functional elements combined
according to published rule set. Text*
Quadrat listing Unique taxa and PFTs per quadrat (for each of 8 (5x5m) quadrats) #
Numeric
Photograph Hard copy and digital image # JPEG
* Where identified, usually with voucher specimens. More detailed information available at www.cbmglobe.org
41
ANNEX III
Vascular plant species listed according to transect* (Sample page – remainder (25 pages) available on request)
Family, Genus species
WC01
WC02
WC03
WC04
WC05
WC06
WC07
WC08
WC09
WC10
WC11
WC12
WC13
WC14
WC15
WC16
WC17
WC18
WC19
WC20
WC21
WC22
Aceraceae Acer campbellii 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Aceraceae Acer caudatum 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 00 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 01 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 00 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 01 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 Aceraceae Acer pectinata 0 0 Alliaceae Allium micrantha 0 0 Anacardiaceae Rhus chinensis
0 0
Apiaceae Acronema sp09 0 0 Apiaceae Acronema tenerum
0 0
Apiaceae Angelica sikkimensis
0 0
Apiaceae Angelica sp06 0 1 Apiaceae Bupleurum sp10 0 0 Apiaceae Cortia depressa 0 0 Apiaceae Heracleum nepalense
0 0
Apiaceae Heracleum aff. nepalensis?
0 0
Apiaceae Heracleum sp31 0 0 Apiaceae Heracleum woodii
0 0
Apiaceae Parnassia sp34 0 1 Apiaceae Pleurospermum sp09
0 0
Apiaceae Selinum sp08 1 0 0 0 0 Apocynaceae Cynanchum sp38
0 0
* Presence/absence data only
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ANNEX IV
List of Plant Functional types (PFTs) recorded per transect* (Sample page only – remainder of list available on request)
PFT WC
01 WC 02
WC 03
WC04
WC05
WC06
WC07
WC08
WC09
WC10
WC11
WC 12
WC13
WC14
WC15
WC16
WC17
WC18
WC19
WC20
WC21
WC 22
pi-la-do-de-ch 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-la-do-de-ro-hc-ad 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 mi-co-do-de-ro-cr 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 na-pe-do-de-hc-ad 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 na-la-do-de-hc-ad 1 3 1 0 0 2 1 4 5 1 0 6 2 2 0 1 1 0 2 3 3 2 mi-la-do-de-hc-ad 2 0 0 0 0 0 0 0 3 1 0 3 3 7 2 1 0 3 0 2 1 1 mi-ve-do-ct-ph 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 na-pe-do-ch 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 mi-co-do-de-ro-pv-cr 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 mi-la-do-de-ch 0 1 0 0 0 1 0 0 1 0 0 1 0 2 3 3 2 2 1 1 0 0 mi-la-do-de-ct-ph 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 1 1 0 0 mi-la-do-fi-hc-ad-ep 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 na-la-do-de-ch-ad 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 pi-pe-do-ch 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-la-do-de-cr 0 1 0 1 0 2 0 0 6 1 1 0 0 1 1 2 1 2 1 0 0 1 mi-la-do-ch 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 na-la-do-ch 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 me-la-do-de-cr-ad 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 no-la-do-de-ch 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 no-ve-do-de-hc-ad 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 mi-la-do-de-ch-li 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 le-co-do-ph 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 pi-la-do-de-fi-hc-ad-ep 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 mi-la-do-de-hc-ad-ep 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 no-pe-do-ct-ph 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
*Species-weighted occurrences (i.e. number of species possessing a specific PFT)
43
ANNEX V
Overview of soil characteristics of the 22 sampled transects*
1 2 3 4 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Altitude 4055 4095 4070 4240 4340 4330 4070 4115 4050 4050 3860 3790 3615 3540 3430 3100 3050 2990 2835 2805 2665
Litter/F/H [cm]
2 L 1L 1F
- - - - - 1 L - - - 1 L 1 L 1 L 5 L 5 L 2 F
4 L 1F
3 L 3F
3 L 2 F
- -
Soil depth [cm]
30 40 30 15 40 30 30 25 20 40 25 25 20 20 20 20 30 85 10 60 55
Texture LFS FS
HL LFS
LS SL
GLS GS
HL Z/SCL
HL SCL
HSL SL
LS SL
HL SL
HL LS/FS
HL SCL
HL SL
HL SL
HL SL
HL S
HL SL
HL SL
HL SCL
HSL SL SCL
SL SCL
Profile Horizons
Ah C
Ah AB
Ah AB
Ah AC
Ah AB/BC
Ah AB/BC
Ah AB
Ah AC
Ah AB
Ah C
Ah AB
Ah AC
Ah AC
Ah AC
Ah AC
Ah AC
Ah AC
Ah B/C
Ah C
Ap AB
Ah AB
* LFS=loamy fine sand, HL = humic loam, LS = loamy sand, SL = sandy loam, G= gravelly, Z = silt, SCL = sandy clay loam
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Biodiversity Baseline Survey of the Wang Chhu Watershed Section”B” Mid-elevation zone
Andrew N. Gillison
Biodiversity specialist
Center for Biodiversity Management P.O. Box 120
Yungaburra 4884 Queensland, Australia Tel. +61-740-953224
Email: [email protected] www.cbmglobe.org
18 December 2009
1
Executive summary
1. This report deals with the second of a three-part survey of the Wang Chhu watershed. As such it is presented as an interim rather than a final report that will be delivered when the three parts are completed and the data analysed in their entirety.
2. Because of its size, the watershed was divided into three operational sections: “A” High elevation (3,000-5,000m), “B” (1,500-3,000m) and “C” 150 – 1,500m). Here we report the results of survey “B”.
3. Team structure consisted of two plant ecologists (RNR-RC, CoRRB), a soil surveyor and technical assistant (NSSC/SLMP) with a botanical technical assistant (NBC). Fieldwork was coordinated by a consulting biodiversity specialist (CBM) with prior assistance from a land management specialist from NSSC.
4. Apart from data acquisition, the survey was designed to consolidate in-field training for trainees and in the survey included a new trainee.
5. As indicated in a previous report, survey design was based on an environmental gradient-directed transect (gradsect) methodology taking into account a primary elevational (thermal) gradient from approximately 5,000m to 150m above sealevel. Other key environmental gradients included drainage, land form, land use and land cover. The gradsect provided the necessary environmental framework for vegetation survey for which a rapid survey method (VegClass) was used to record core biophysical data.
6. The team sampled 22 transects within an elevational range of 1400-4000m a.s.l.. Soil sampling was co-located at each transect. A significant intermediate section of the gradsect had to be abandoned due to heavy rain and will be included during the final survey of section ‘C”.
7. A key focus of survey ‘B” included sampling a land use intensity gradient across a slash and burn (Tseri) fallow series at Pakchikha in the Bongo Geog. Results were consistent with findings in other countries that show biological diversity peaks at intermediate levels of disturbance.
8. While it is premature to attach much reliance to statistical analyses without the inclusion of data from the final sector of the watershed, the finding of certain highly significant correlates between biotic and abiotic variables in survey “B” suggests these are worth reporting. To the extent that certain results are also consistent with those of survey “A”, some examples of potentially useful correlates are included in the report. An example of a new biodiversity indicator using estimates of lichen cover-abundance estimates (a ‘Lichen Index’) is also presented.
9. Preliminary results and proposed new activities presented at a multi-sectoral stakeholder workshop on the development of the DrukDIF received positive feedback from both government and non-government agencies.
10. In keeping with the aims of the developing DrukDIF, the biophysical data (land cover, land use, vegetation, soils, geomorphology) recorded from this survey will be located on the web portal currently under construction by UW under the guidance of Professor J. Richey.
2
List of tables Table 1. Team membership and area of expertise Table 2. Transect locations and site physical properties Table 3. Temperature and annual precipitation Table 4. Vegetation typology and land use Table 5. Summary of species, PFTs and PFC Table 6. Vegetation structural features Table 7. Cover-abundance scores of lichens Table 8a. Soil properties Table 8b. Soil properties (cont.) Annexes I Terms of Reference and description of services II List of data variables recorded for each 40x5m transect III Listing of Plant Functional Types (PFTs) and vascular plant taxa - sample page List of Figures Figure 1. Area B surveyed. Figure 2. Intensive rice farming and adjacent forest plantations, Haa area. Figure 3. Typical slash and burn (Tseri) mosaic, Bongo Geog. Figure 4. The “B” team. Survey of the mid-elevation Wang Chhu L->R : Kinga, Choki
Wangmo, Andrew Gillison, Penjor Kinley, Cheten Thinley, Dorji Gyaltshen. Figure 5. Locations sampled in survey B (circles). Some intermediate areas are to be
sampled in survey C. Figure 6a. a) Transect WC23, fir stand. Rhododendron, Rosa, Iris understorey; b)
Transect WC24, Larch with Juniper shrubs and Iris ground layer; c) Transect WC25, alpine Rhododendron, Salix shrubland; d) Transect WC26, alpine Rhododendron heath; e) Transect WC27, alpine meadow with numerous cryptophytes; f) Transect WC28, sub-alpine, conifer-broadleaf forest with Rosa and Piptanthus understorey.
Figure 6b. a) Transect WC29, Conifer-broadleaf forest with Spruce and Oak. Regen Oak understorey; b) Transect WC30, Secondary conifer-broadleaf forest, regenerating Populus, Pinus, Picea and Quercus; c) Transect WC31, Apple orchard with dense herbaceous ground layer; d) Transect WC32, secondary succession with dominant Alsinandra, dense Acanthaceae and invasive weed ground layer; e) Transect WC33, Disturbed Oak-Laurel forest, heavily cut over; f) Transect WC34, Fagaceous forest with dense shrub understorey, grazed by deer and domestic animals.
Figure 6c. a) Transect WC35, Seral Castanopsis forest with shrub understorey, cutover, grazed by deer and domestic stock; b) Transect WC36, Alnus nepalensis plantation approx 20 yr old, with some inter-planted Cryptomeria japonica, dense invasive Strobilanthes understorey; c) Transect WC37, 9-10 year slash and burn fallow, remnant tree cover; d) Transect WC38, Six year slash and burn fallow,
3
some remnant trees; e) Transect WC39, 3-4 year slash and burn fallow dominated by Artemisia vulgaris, some remnant trees; f) Transect WC40, 2-year slash and burn fallow dominated by Artemisia vulgaris and Chromolaena odorata.
Figure 6d. a) Transect WC41, 8 month fallow, previously corn and rice; b) Transect WC42, Newly planted (2 month) Buckwheat (Fagopyrum esculentum) after slash and burn; c) Transect WC 43 Grain Amaranth (Amaranthus cf. caudatus) 6 month planting in slash and burn sequence; d) Transect WC44, 3 month padi rice, sedentary agriculture (pre-harvest).
Figure 7. Correlation between plant species richness and PFT richness Figure 8. Lichen cover-abundance and plant litter depth Figure 9. Cover-abundance of bryophytes relative to all lichen groups as a predictor of
bryophyte cover-abundance. Figure 10. Ratio of total lichen cover-abundance to total plant species richness as a
predictor of richness of deciduous plant species. Figure 11. Sand % and richness of cryptophytic plants Figure 12. Silt % and richness of cryptophytic plants Figure 13. Ratio of total lichen cover-abundance to PFE richness and sand % Figure 14. Ratio of total lichen cover-abundance to PFE richness and silt % Figure 15. Plant species richness within a sequence of seral forest, forest plantation and
slash and burn fallow periods (yr = year since opening, m = months since opening).
Figure 16. Rooting depth of Pinus wallichiana, near Haa
Acronyms* CGNH CNR
Commission on Gross National Happiness College of Natural Resources, Royal University of Bhutan, Lobesa
DANIDA Danish International Development Assistance DHSVM Distributed Hydrology Soil Vegetation Model DrukDIF Bhutan Dynamic Information Framework FAO Food and Agriculture Organization, Rome FRA2000 Forest Resource Assessment 2000 (FAO) GEF Global Environment Facility GIS Geographic Information System ICIMOD International Center for Integrated Mountain Development IUCN International Union for the Conservation of Nature, Gland,
Switzerland KL Kangchenjunga Landscape MoA Ministry of Agriculture NAP National Action Plan on Land Degradation NAPA National Adaptation Plan of Action NBC National Biodiversity Centre NCD Nature Conservation Division (Dept. Forests, MoA) NEC National Environment Commission NGO Non-Government Organization NSSC National Soil Services Center PFE Plant Functional Element PFT Plant Functional Type
4
5
RGoB Royal Government of Bhutan RNR RNR-RC, CoRRB
Renewable Natural Resources (MoA oversight) Renewable Narural Resources – Council of Renewable Natural Resources Research of Bhutan
RSPN Royal Society for Protection of Nature SLMP Sustainable Land Management Project TOR Terms of Reference UNDP United Nations Development Programme UNEP United nations Environment Programme URL Unique Record Locator USGS United States Geological Survey (US Department of the Interior) USGS-NPS United States Geological Survey, National Parks Service UW University of Washington, Seattle, USA VIC Variable Infiltration Capacity Model WB The World Bank WWF Worldwide Fund for Nature * Used in this and previous DrukDIF reports Bhutanese Terms
Term Meaning Chathrim Act, rules and regulations, codes of conduct Chhu River or rivulet Chimi Representative at the National Assembly Dasho Administrative Head of a district or Dzongkhag Dzongdag Head of a district Dzongkhag District Dzongkhag Yargye Tshogchung District Development Committee Dungkhag Sub-district Dungpa Head of a sub-district Geog (chiog) Block, which is usually made up of few to several villagesGeog Yargye Tshogchung Block Development Committee Gup Head of a block Mangmi Elected representative of a geog Tseri Slash and burn cultivation Tshogpa Representative of a village, or a cluster of villages
1. Introduction This the second of three survey reports that, when combined, will provide an initial reference baseline of key data and a framework for further resource assessment of the Wang Chhu watershed as part of the developing DrukDIF. For operational reasons, because of its size, the watershed was divided into three sections: “A” High elevation (3,000-5,000m), “B” Medium elevation (1,500-3,000m) and “C” Low elevation (150 – 1,500m). This report deals with the results of survey “B”. The rationale and background to the methodology is outlined in the report on survey “A” 1. Because additional data are to be acquired from a final, low elevation survey (“C”), a detailed statistical analysis based solely on data from surveys “A” and “B’ is inappropriate in this report. Instead, broadly indicative results only are presented. A complete account of statistical and exploratory data analysis will be provided for the entire watershed when data from the three connected surveys are available. This study follows logically from earlier development in the DrukDIF2 and is consistent with the aims and targeted deliverables outlined in a following extract from a more detailed TOR (Annex I) in which the intended survey of Section “B” of the Wang Chhu watershed is described within a broader operational and environmental context. This is consistent with the general aims and is included in an introduction to the general biophysical background of the study area together with a report on soil properties. As with the alpine survey, additional data on soil properties are included. 2. Terms of reference (not included here)
1 Gillison, A.N. (2009). Biodiversity Baseline Survey of the Wang Chhu Watershed Section ”A” Alpine zone. Including report by van Noord, H. and Dorji, T. The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Upper Wang Chhu. November 11 2009. 2 Gillison, A.N. (2009) . Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase I: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. June 5 2009.
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3. Location and biophysical background to the survey area 3.1 Location The survey area in northwest Bhutan occurs within the mid section of the Wang Chhu watershed (Fig.1). The significance of the area for conservation management and the nature of land cover and land use are outlined in an earlier report for Phase I of DrukDIF dealing with a review of biodiversity in Bhutan. As with Section “A”, (the upper alpine section) the underlying topography and land form combined with thermal and precipitation gradients are closely linked with changes in land cover and vegetation types ranging from lower elevation (1400m) mixed, mainly broadleaf forests and successional vegetation types through tall closed conifer-broadleaf forest at mid-elevation to exposed higher elevation, alpine grasslands and shrublands (4025m). Sedentary agriculture (Fig. 2) and slash and burn fallow systems (Fig. 3) occupy
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the greater part of arable land. More detailed accounts of vegetation typology and related ecosystem dynamics are described in the results section of this report. While much of the area, especially the more accessible alpine grassland ecosystems, appears to be ‘pristine’, the prevailing condition is rather more representative of a state of partial equilibrium as a consequence of long periods of human occupation where, apart from climate, animal husbandry and the use of fire remain primary drivers in ecosystem performance. The area sampled (Figs. 1.,5.) is similar to other regions of the world at similar elevations that have experienced similar evolutionary pressures due to fire and the omnipresent domestic and indigenous grazing animals. Within the overall gradsect, sample sites were also located to represent a cross section of apparent land use intensity from sedentary intensive agricuture (Fig. 2) including a focal subset in slash and burn fallow sequences (Tseri) in the Bongo Geog (Fig. 3).
Figure 2. Intensive rice farming and adjacent forest plantations, Haa area.
Figure 3. Typical slash and burn (Tseri) mosaic,
Bongo Geog. 4. Team structure The multidisciplinary expertise of the survey team ( Table 1., Fig. 4) facilitated an integrated aproach to survey. While each team member contributed specific expertise in the recording of field data, the survey was designed and coordinated jointly by NSSC and CBM. Table 1. Team membership and area of expertise No. Name Institution Task/Expertise 1 Dorji Gyaltshen RNR-RC, CoRRB Plant ecologist 2 Cheten Thinley RNR-RC, CoRRB Plant ecologist 3 Kinley Penjor NSSC/SLMP Soil surveyor 4 Kinga NSC/SLMP Soil technical assistant 5 Choki Wangmo NBC Botanical technician 6 Andrew N. Gillison CBM Biodiversity specialist
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Figure 4. The “B” team. Alpine survey of the mid-elevation Wang Chhu L->R : Kinga, Choki Wangmo, Andrew Gillison, Penjor Kinley, Cheten Thinley, Dorji Gyaltshen.
5. Methodology The methodology used to record and describe vegetation, soils and land use in survey “A” 3 was applied in this survey. Because the use of Plant Functional Types and the recording of lichen cover-abundance are both relatively novel procedures in biodiversity survey, a description of their use combined with the gradsect sampling approach along environmental gradients is repeated here. As with survey “A”, in the present study, information from a variety of institutional and online sources (maps, remote sensing) and literature indicated that a thermal gradient was most likely to account for species performance and distribution, followed by soil moisture (cf. Wangda and Ohsawa, 2006) and land use practices. Sample sites were therefore located using gradsects derived according to a hierarchy of nested environmental gradients (thermal (elevation), drainage, terrain (slope, aspect), lithology, land cover and land use). Despite careful attention to these criteria, final locations were necessarily influenced by the extreme physical characteristics of the mountainous terrain. At each site we positioned a 200 m2 (40 x 5m) transect according to the standard VegClass recording procedure (Gillison, 2002), where we recorded site physical details, vegetation structure, presence of all indigenous and introduced vascular plant species and plant functional types (PFTs) (Annex II). A rule set
3 Gillison, A.N. (2009). Biodiversity Baseline Survey of the Wang Chhu Watershed Section ”A” Alpine zone. Including report by van Noord, H. and Dorji, T. The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Upper Wang Chhu. November 11 2009.
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and grammar (Gillison & Carpenter, 1997) incorporated in the VegClass software were used to construct PFTs from a generic set of 36 plant functional elements (PFEs) ( based on the plant functional attributes of Gillison, 1981). We used VegClass to generate a plant functional complexity (PFC) value as a complement to PFT richness. PFC is not a measure of functional diversity in the usual ecological sense ( cf. Magurran 2004) but is potentially useful when comparing transects where PFT richness may be identical but where PFT composition varies (Gillison, 2002). At each transect voucher specimens of each species were collected, air-dried and preserved in a portable mini-herbarium. Where field identification was incomplete, subsequent identification was provided by RSPN (R. Prabhan) following the field survey. Landuse history was documented where possible from interviews with local farmers. Within each transect, soils were described according a a standard NSSC proforma that included soil texture, color, diagnostic horizons and aggregates. An auger was used to establish soil depth at multiple locations along the transect. A composite 1 kg soil sample was taken of the topsoil and bulk density was sampled using standard 100cc rings. Standard laboratory procedures were applied to determine soil physico-chemical properties. The soil data acquired in both field and laboratory were entered in a standard NSSC format consistent with the soil database for Bhutan and the developing DrukDIF. Electronic copies of all data recorded from the survey have been lodged with NSSC. As indicated in the foregoing, in the absence of data from the completed survey of sections “A”, “B” and “C”, only very limited value can be attached to statistical analyses from any one section. For this reason only results with highly significant outcomes are displayed for interim consideration. While some are statistically highly significant, it is very likely the predictive value of certain indicators recorded here will vary with the addition of data from the final survey. Preliminary linear and non-linear regression analysis was used to explore statistical relationships between the variables recorded by VegClass, as well as lichen cover-abundance and the full range of soil properties. In the present case, only correlates with P < 0.005 were considered for potential indicator value.
6. Results 6.1 The survey gradsect: The team sampled 22 transects that, apart from accommodating a primary elevational (thermal) gradient, included a range of natural vegetation cover and a land use intensity gradients ranging from forest exploitation and sedentary agriculture to alpine grazing systems (Tables 2,3,4). Non-seasonal, heavy rain prevented sampling of an intermediate elevational range between the
Figure 5. Locations sampled in survey B (circles). Some intermediate areas are to be sampled in survey C.
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Bongo Geog and Haa (see Fig. 5). This area will be completed during the survey of section “C”. The steepness of the terrain combined with changing weather patterns also limited access to forested locations in steep gorges with near vertical slopes and rocky terrain. Nonetheless, several transects were sampled along slopes > 70%. Plant species and PFT diversity together with vegetation structural features are listed in Tables 5 and 6. All recorded PFTs and vascular plant species are tabulated in Annex III. Habitat type in each transect is displayed in Figs. 6a,b,c,d. Table 2. Transect locations and site physical properties
Transect Location Lat. S Long. E Elevn (m)
Slope%
AspectDeg.
WC23 6km below Chelela pass on Paro side 27.3715 89.3544 3392 30 80 WC24 Chelela towards Haa 27.3755 89.3171 3439 60 322 WC25 Chelela below Telecom tower 27.3825 89.3372 3942 55 80 WC26 Chelela below telecom tower 27.3826 89.3372 4025 78 90 WC27 Chelela below telecom tower 27.3823 89.3372 4024 10 152 WC28 Chelela -2km towards Haa 27.3720 89.3184 3570 35 195 WC29 Below Chelela towards Haa 27.3705 89.3171 3514 45 230 WC30 9 km towards Chelela from Haa 27.3648 89.3085 3127 55 272 WC31 4km from Haa towards Chelela 27.3708 89.2988 2908 25 247 WC32 3km to Situ from just before Chasilaka 26.9541 89.5634 1857 35 145 WC33 6km towwards Situ from Chasilaka 26.9537 89.5653 1805 60 62 WC34 Near Alaykha community school, Gedu area 26.9043 89.5884 1489 79 85 WC35 Near Alaykha School 26.9167 89.5480 1696 35 350 WC36 Near Alaykha School 26.9146 89.5434 1835 20 359 WC37 Bayme Pang, (Pakchikha, Bongo Geog) 26.9283 89.5996 1434 45 113 WC38 Zomchuthay (Pachikha, Bongo Geog) 26.9315 89.5882 1359 45 4 WC39 Zawalaktha (Pakichikha - Bongo Geog) 26.9316 89.5988 1437 65 55 WC40 Pakichikha, Bongo Geog 26.9296 89.5994 1459 35 74 WC41 Pakchikha, Bongo Geog 26.9295 89.5998 1439 50 80 WC42 Pakchikha - Bongo Geog 26.9294 89.5997 1440 38 72 WC43 Pakichikha - Bongo Geog 26.9299 89.5997 1450 35 60 WC44 Pakchikha - Bongo geog 26.9319 89.5950 1471 35 60
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Table 3. Temperature and annual precipitation*
Transect Avg temp
°C Max temp
°C Precip. mm yr-1
WC23 -4.8 20.2000 1332 WC24 -9.6 17.6000 849 WC25 -9.6 17.6000 849 WC26 -9.6 17.6000 849 WC27 -9.6 17.6000 849 WC28 -9.6 17.6000 849 WC29 -9.6 17.6000 849 WC30 -10.7 16.8000 772 WC31 -10.7 16.8000 772 WC32 4.0 24.0000 3048 WC33 4.0 24.0000 3048 WC34 5.9 25.4000 3455 WC35 3.6 23.4000 2954 WC36 3.6 23.4000 2954 WC37 5.9 25.4000 3455 WC38 5.9 25.4000 3455 WC39 5.9 25.4000 3455 WC40 5.9 25.4000 3455 WC41 5.9 25.4000 3455 WC42 5.9 25.4000 3455 WC43 5.9 25.4000 3455 WC44 5.9 25.4000 3455
* Derived from climate surface supplied by H. Greenberg UW
Table 4. Vegetation typology and land use* Transect Vegetation type and land use WC23 Fir stand with dense Rhododendron, Rosa and Iris understory. Dense
Sphagnum layer. Very disturbed forest. Logged by NRDCL. WC24 Highly disturbed Larch forest with Juniperus, shrubs and Iris groundlayer WC25 Rhododendron/ Salix shrubland. Exposed slope near ridge. Grazed. WC26 Rhododendron heath. Exposed slope near ridge. Grazed. WC27 Alpine meadow. Heavily grazed. WC28 Conifer-broadleaf forest, with Rosa and Piptanthus dominated understorey
Heavily disturbed, logged and grazed, wild boar diggings WC29 Conifer-Broadleaf forest dominated by Spruce and Oak. Heavily disturbed,
recently logged, grazed. Near road. Regeneratiing Oak understorey. Large rocks. WC30 Secondary conifer-broadleaf forest. Heavily disturbed, logged, dominated by
regenerating Populus, Piinus, Picea and Quercus WC31 Apple orchard with dense herbaceous groundlayer. Actively managed. WC32 Secondary succession with Alsinandra dominant tree. Dense Acanthaceae
and invasive weed groundlayer WC33 Disturbed Oak-Laurel forest. Patchy disturbabce, cut over, large rocks. WC34 Fagaceous forest with shrub undrerstorey. Heavily disturbed, cut over, tracks,
grazing (deer and domestic). WC35 Castanopsis forest with shrubby understorey. Disturbed, logged, near road,
grazed by deer and domestic stock WC36 Alnus nepalensis forest (plantation) with dense Strobilanthes understorey and
some planted Cryptomeria japonica WC37 9-10 year fallow. Seral shrubland following slash and burn (S/B). Many woody species including
Artemisia and Chromolaena. Remnant tree cover. WC38 Six year fallow stage. Dominated by shrubs (Artemisia, Chromolaena, Pteridium).
Some remaining trees. WC39 3-4 year shrub fallow dominated by Artemisia vulgaris. Some remnant trees. WC40 2yr seral shrubland in slash and burn cycle. Artemisia, Chromolaena WC41 Cultivation, mixed crop and non-crop species. 8 month fallow. WC42 Newly emerging buckwheat, Fagopyrum esculentum WC43 Dominantly Amaranthus (caudatus?) WC44 Dominantly padi rice with ground layer of mixed, mainly weedy species.
* See Figs. 6a,b,c,d
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Figure 6a. a) Transect WC23, fir stand. Rhododendron, Rosa, Iris understorey; b) Transect WC24, Larch with Juniper shrubs and Iris ground layer; c) Transect WC25, alpine Rhododendron, Salix shrubland; d) Transect WC26, alpine Rhododendron heath; e) Transect WC27, alpine meadow with numerous cryptophytes; f) Transect WC28, sub-alpine, conifer-broadleaf forest with Rosa and Piptanthus understorey.
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Figure 6b. a) Transect WC29, Conifer-broadleaf forest with Spruce and Oak. Regen Oak understorey; b) Transect WC30, Secondary conifer-broadleaf forest, regenerating Populus, Pinus, Picea and Quercus; c) Transect WC31, Apple orchard with dense herbaceous ground layer; d) Transect WC32, secondary succession with dominant Alsinandra, dense Acanthaceae and invasive weed ground layer; e) Transect WC33, Disturbed Oak-Laurel forest, heavily cut over; f) Transect WC34, Fagaceous forest with dense shrub understorey, grazed by deer and domestic animals.
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Figure 6c. a) Transect WC35, Seral Castanopsis forest with shrub understorey, cutover, grazed by deer and domestic stock; b) Transect WC36, Alnus nepalensis plantation approx 20 yr old, with some inter-planted Cryptomeria japonica, dense invasis Strobilanthes understorey; c) Transect WC37, 9-10 year slash and burn fallow, remnant tree cover; d) Transect WC38, Six year slash and burn fallow, some remnant trees; e) Transect WC39, 3-4 year slash and burn fallow dominated by Artemisia vulgaris, some remnant trees; f) Transect WC40, 2-year slash and burn fallow dominated by Artemisia vulgaris and Chromolaena odorata.
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Figure 6d. a) Transect WC41, 8 month fallow, previously corn and rice; b) Transect WC42, Newly planted (2 month) Buckwheat (Fagopyrum esculentum) after slash and burn; c) Transect WC 43 Grain Amaranth (Amaranthus cf. caudatus) 6 month planting in slash and burn sequence; d) Transect WC44, 3 month padi rice, sedentary agriculture (pre-harvest).
Table 5. Summary of species, PFTs and PFC
Transect Species PFTs Spp:PFT PFCWC23 37 33 1.12 220 WC24 48 38 1.26 276 WC25 36 31 1.16 234 WC26 35 24 1.46 152 WC27 27 15 1.80 60 WC28 39 34 1.15 194 WC29 39 27 1.44 166 WC30 31 24 1.29 144 WC31 58 36 1.61 228 WC32 98 72 1.36 358 WC33 52 41 1.27 222 WC34 76 58 1.31 292 WC35 54 44 1.23 280 WC36 40 30 1.33 198
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Transect Species PFTs Spp:PFT PFCWC37 81 56 1.45 294 WC38 66 44 1.50 282 WC39 59 44 1.34 232 WC40 65 44 1.48 264 WC41 57 47 1.21 230 WC42 10 10 1.00 82 WC43 38 31 1.23 146 WC44 26 22 1.18 126
Table 6. Vegetation structural features *
Transect Ht CC Tot
CC Wdy
CC Nwdy
Bryo WPlts Litt BA MFI FICV
WC23 42.00 75 65 10 8 9 15.000 31.33 34.00 139.89 WC24 15.00 95 80 15 8 7 12.000 22.67 0.00 0.00 WC25 2.50 98 95 3 9 8 15.000 2.33 100.00 0.00 WC26 0.35 98 95 3 9 6 18.000 1.33 100.00 0.00 WC27 0.02 98 0 98 0 7 3.000 0.00 0.00 0.00 WC28 30.00 90 85 5 8 7 8.000 36.00 24.00 116.80 WC29 35.00 80 75 5 7 7 12.000 22.00 39.90 125.66 WC30 4.00 95 92 3 8 5 5.000 12.67 29.50 135.80 WC31 3.50 98 35 63 1 3 2.000 6.00 89.00 17.16 WC32 10.00 98 95 3 8 7 2.000 11.33 61.00 50.36 WC33 40.00 92 75 17 6 8 0.015 34.00 51.00 54.41 WC34 30.00 99 90 9 8 8 8.000 30.00 52.30 49.54 WC35 18.00 95 92 3 8 6 3.000 24.00 55.75 57.11 WC36 19.00 99 98 1 9 5 3.000 24.67 4.50 447.21 WC37 3.00 99 90 9 8 4 5.000 2.67 63.00 73.30 WC38 2.80 99 90 9 9 5 2.500 1.00 99.00 3.11 WC39 2.50 99 95 4 9 5 2.000 1.33 100.00 0.00 WC40 2.00 99 85 14 8 3 2.000 1.00 95.50 21.07 WC41 0.40 85 10 75 1 2 0.010 0.10 93.50 21.47 WC42 0.15 75 0 75 0 0 0.000 0.00 0.00 0.00 WC43 0.60 92 10 82 2 2 0.100 0.10 99.40 2.27 WC44 1.00 90 0 90 0 1 0.000 0.00 0.00 0.00
* Ht = Mean canopy height (m); Cctot= Total canopy projective foliage cover percent; Ccwdy = projective foliage cover percent of woody plants; CCNwdy, PFC of non-woody plants; Bryo = cover-abundance of bryophytes; Wplts = cover-abundance of woody plants <2m tall; Litt = plant litter depth (cm); BA = basal area of all woody plants (m2ha-1); MFI = mean furcation index; FICV = coefficient of variation percent of FI. (See also Annex II for complete listing of site variables)
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Table 7. Cover-abundance scores of lichens
Transect Fruticose Crustose Foliose Total
WC23 8 2 6 16 WC24 8 2 8 18 WC25 6 4 7 17 WC26 2 2 4 8 WC27 1 6 4 11 WC28 9 4 7 20 WC29 9 3 7 19 WC30 7 1 5 13 WC31 1 4 1 6 WC32 2 1 3 6 WC33 2 2 2 6 WC34 2 2 1 5 WC35 0 2 0 2 WC36 2 2 1 5 WC37 1 3 3 7 WC38 0 2 0 2 WC39 0 2 1 3 WC40 0 0 0 0 WC41 0 0 0 0 WC42 0 0 0 0 WC43 0 0 0 0 WC44 0 0 0 0
6.2 Plant species and plant functional type diversity Of 1072 vascular plant species recorded during the survey, approximately 690 have been identified so far as unique species. It is anticipated this figure is likely to decrease by a further 5 percent as further indentification proceeds (NBC, RSPN). The team recorded 400 unique (species-independent) PFTs. Patterns of species and PFT richness and composition are closely related to successional stages of vegetation that, in turn, are influenced by a combination of land use type and the stability of the substrate. At the broader scale successional patterns are readily visible (Fig. 3). When species richness (diversity) is regressed against PFT richness the highly significant relationship (P< 0.0001, RSq (adj.) 0.937) (Fig. 7) provides a robust basis for predicting species richness from more readily determined PFT richness. For future assessment and monitoring purposes this may be of benefit where botanical expertise is not at hand to identify species. The highly linear response also suggests a high level of observer consistency.
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Figure 7. Plant species diversity regressed against PFT diversity 6.3 Lichens as potential biodiversity indicators As the use of lichens as biodiversity indicators is relatively novel with respect to the VegClass system, the results of the present survey are reported here as a matter of interest. With additional data from surveys of the remaining sections of the Wang Chhu watershed predictive values may change. When results from different team members were compared, observer consistency was considered adequate in estimating cover-abundance values of the three major classes of macrolichens (fruticose, crustose and foliose). See previous report for further derscription. Published accounts of lichen surveys in Bhutan and the adjacent Himalaya are relatively rare (but see Söchting, 1999; Negi and Gadgil, 2002). A ‘lichen index’ (ratio of lichen species richness to vascular plant species richness) has been developed for use in surveys at high latitudes and high elevations (cf. Mattick 1953 and P. Krestov4, pers. comm.). In such environments that are usually species-poor in lichens, a species-based index may be feasible, but this is unlikely to be the case for most surveys in species-rich tropical to sub-tropical environments. For this reason, as an alternative approach, in the present survey, an index based on the ratio of lichen cover-abundance to total vascular plant species richness was tested as a potential predictor of biodiversity. Results show only a weak correlation with plant species and PFTs but high correlation with other plant-based features such as bryophyte cover-abundance, plant litter depth and plant functional elements such as deciduousness (Figs. 8,9,10). Relationships between lichens and soil properties are described below.
4 Dr P. Krestov, Institute of Biology and Soil Science, Vladivostok.
Plant Functional Type richness
0 20 40 60 80
Pla
nt
spec
ies
rich
nes
s
0
20
40
60
80
100
012Rsq (Adj.) 0.937, P < 0.0001
Figure 7. Correlation between plant species richness and PFT richness
Plant litter depth (cm)
0 5 10 15 20
To
tal
lich
en c
ove
r-ab
un
dan
ce
-5
0
5
10
15
20
25 Rsq (adj.) 0.669, P < 0.0001
Figure 8. Lichen cover-abundance and plant litter depth
Cover-abundance all lichen groups
0 5 10 15 20 25
Co
ver-
abu
nd
an
ce b
ryo
ph
ytes
0
2
4
6
8
10 Rsq (adj.) 0.572, P < 0.0001 Figure 9. Cover-abundance of bryophytes relative to all lichen
groups as a predictor of bryophyte cover-abundance.
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Ratio of total lichen cover-abundance to total plant species richness
0.0 0.2 0.4 0.6
Dec
idu
ou
s sp
eci
es r
ich
nes
s
0
10
20
30
40
50Rsq (adj.) 0.801, P < 0.0001
Figure 10. Ratio of toal lichen cover-abundance to total plant species
richness as a predictor of richness of deciduous plant species. 7. Plant – soil relationships Soil analytical data are listed in Table 8a,b below. No single soil property is significantly correlated with vascular plant or PFT richness. On the other hand a number of PFEs are closely correlated with some soil properties (e.g. graminoid plants with exchangeable cations and soil pH) the highest correlation occurring between cryptophytes (plants with below-ground perennating organs) and plants with rosulate leaves where both are strongly positively and negatively correlated with sand% and silt% respectively (Figs. 11,12). Bryophyte cover-abundance and plant litter depth are highly correlated with exchangeable Ca, Mg and K, as well as organic C and N% and also positively and negatively correlated with sand% and silt % respectively. Basal area and cover-abundance of woody plants <2m tall are also closely correlated with exchangeable cations and soil pH. Lichens also exhibit close correlations with certain soil properties in particular exchangeable cations and soil pH. The ‘lichen index’ of total lichen cover-abundance to total plant species richness is also highly correlated with total exchangeable bases (Fig. 13 ). In addition, a ratio of total lichen cover-abundance to PFE richness (total presence – absence of PFE data in all transects) is highly correlated with several soil properties including exchangeable cations, soil pH and sand% and silt% (Fig. 14).
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Table 8a. Soil properties
Transect pHH20 pHKCL pHDelta Pbray C% N% Ca
Exch Mg
Exch K
Exch Na
Exch WC23 4.10 3.38 0.52 6.11 10.10 0.51 -1.29 0.42 0.23 0.03WC24 5.03 4.24 0.79 0.70 5.50 0.41 0.83 1.22 0.30 0.04WC25 4.75 4.04 0.70 0.21 14.20 0.63 0.31 1.41 0.40 0.06WC26 4.86 4.24 0.62 0.16 11.70 0.62 2.29 0.96 0.40 0.06WC27 4.68 4.18 0.52 0.29 9.70 0.53 -0.70 0.60 0.51 0.04WC28 4.66 4.11 0.55 0.69 7.40 0.37 -0.98 1.28 0.25 0.04WC29 4.34 3.96 0.38 0.44 7.90 0.44 -1.25 0.45 0.20 0.03WC30 5.01 4.08 0.93 0.12 3.00 0.16 -1.01 0.55 0.23 0.03WC31 5.96 4.86 1.10 0.85 2.90 0.21 4.83 1.81 1.05 0.06WC32 4.45 3.99 0.46 0.07 9.20 0.56 8.55 1.84 0.68 0.05WC33 5.15 4.55 0.60 0.05 6.70 0.49 0.49 0.46 0.33 0.03WC34 4.87 4.22 0.65 0.12 5.70 0.41 0.75 1.03 0.57 0.03WC35 5.42 4.36 1.06 0.17 4.90 0.38 2.74 1.38 0.59 0.04WC36 4.15 3.95 0.20 0.05 6.10 0.43 -0.07 0.52 0.44 0.03WC37 4.57 4.02 0.55 0.26 5.50 0.40 -0.85 0.44 0.32 0.03WC38 5.44 4.66 0.78 0.64 5.20 0.33 6.95 1.13 0.51 0.02WC39 5.52 4.69 0.83 0.44 7.40 0.52 6.48 2.73 1.22 0.07WC40 5.51 4.61 0.90 0.05 7.40 0.50 7.12 1.93 0.48 0.04WC41 5.65 4.60 1.05 0.05 5.40 0.42 5.00 1.50 0.79 0.05WC42 5.56 4.75 0.81 0.69 5.90 0.38 8.51 2.36 1.35 0.09WC43 5.53 4.66 0.87 0.06 6.70 0.12 7.85 2.03 0.62 0.05WC44 5.65 4.77 0.88 0.32 3.60 0.08 5.10 1.71 1.18 0.07
Table 8b. Soil properties
Transect TEB CEC-Am BS-AmO Sand% Silt% Clay% Bulk
Density WC23 -0.61 35.04 -1.73 47.90 35.00 17.10 1.50 WC24 2.40 27.16 8.83 48.30 37.30 14.40 1.62 WC25 2.18 47.98 4.55 65.90 23.40 10.70 1.44 WC26 3.71 33.69 11.01 59.40 26.70 13.90 1.65 WC27 0.45 26.96 1.68 76.60 13.40 10.00 1.83 WC28 0.59 24.36 2.41 47.80 34.90 17.30 1.94 WC29 -0.57 31.75 -1.78 45.00 35.70 19.30 1.84 WC30 -0.20 21.16 -0.95 34.20 36.80 29.00 1.90 WC31 7.76 15.19 51.05 35.00 42.10 22.90 2.30 WC32 11.13 27.91 39.86 40.20 35.60 24.20 1.66 WC33 1.31 37.26 3.52 27.90 39.10 33.00 1.69 WC34 2.38 21.96 10.86 46.40 31.20 22.40 1.72 WC35 4.75 23.83 19.93 32.70 41.60 25.70 1.79 WC36 0.93 26.61 3.48 27.00 48.50 24.50 1.86 WC37 -0.06 26.14 -0.25 18.20 54.60 27.20 1.90 WC38 8.62 23.78 36.22 37.20 48.40 14.40 2.09 WC39 10.51 29.42 35.71 35.40 47.30 17.30 1.74
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Transect TEB CEC-Am BS-AmO Sand% Silt% Clay% Bulk
Density WC40 9.57 29.26 32.72 38.20 44.40 17.40 1.82 WC41 7.35 25.42 28.90 28.60 62.10 9.30 1.82 WC42 12.30 29.34 41.94 19.70 55.30 25.00 1.85 WC43 10.56 32.06 32.95 23.30 57.30 19.40 1.70 WC44 8.07 22.86 35.27 20.50 50.20 29.30 1.93
Sand %
20 40 60 80
Cry
pto
ph
yte
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nes
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18Rsq (adj.) 0.680, P < 0.0001
Figure 11. Sand % and richness of cryptophytic
Silt %
10 20 30 40 50 60 70
Cry
pto
ph
yte
rich
nes
s
0
2
4
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8
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18 Rsq (adj.) 0.608, P > 0.0001
24Figure 12. Silt % and richness of cryptophytic plants
Sand %
20 40 60 80
Lic
he
n c
/a :
PF
E d
iver
sity
(p
a)
0.0
0.2
0.4
0.6
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1.0 Rsq (adj.) 0.461, P < 0.0003
Figure 13. Ratio of total lichen cover-abundance to PFE richness and sand %
Silt %
10 20 30 40 50 60 70
Lic
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/a :
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E d
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sit
y (p
a)
-0.2
0.0
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0.4
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1.0 Rsq (adj.) 0.508, P < 0.0001
Figure 14. Ratio of total lichen cover-abundance to PFE richness and silt %
25
8. Plant biodiversity, soil properties under slash and burn (Tseri)
management This section reviews results from soil analyses of the ten transects representing softwood plantation, seral oak forest and agricultural fallow sequences from 9-10 years to recent cultivation (see Table 4, Figs 6c,d). With a few exceptions, plant-based variables are generally weakly correlated with soil properties. Plant litter depth varies significantly with soil pH as does PFE richness with exchangeable bases and PFT richness with exchangeable K and Na. No significant correlation was found between species and PFT richness and soil texture including bulk density.
Figure 15. Plant species richness within a sequence of seral forest, forest plantation and slash and burn fallow periods (yr = year since opening, m = months since opening).
9. Discussion The non-seasonal weather conditions severely restricted access to a significant elevational range ( Fig. 5) and this reduced the value of subsequent analyses. The sample ‘gap’ is evident in a number of the foregoign graphs. It is intended that the area that was missed will be included in the subsequent survey of section “C” in Spring 2010. Despite this gap, the team was fortunate to include a reasonably comprehensive sample of a range of Tseri fallow sequences that included a seral Oak (Castanopsis) forest and a 20 year Alnus softwood plantation. The lack of correlation between the fallow sequences and soil properties is surprising. That soil bulk density is poorly correlated with plant-based variables overall runs counter to most findings in tropical to sub-tropical countries. This feature may be related to the physical nature of the geological substrate that is frequently dominated by fragmented and highly weathered schist. On the other hand, the finding that plant species diversity (richness)
Figure 16. Rooting depth of Pinus wallichiana, near Haa
26
peaks at a 9-10 year fallow (Fig. 16) is consistent with findings both in Bhutan (Wangda and Ohsawa, 2007; Wangda, 2008) and elsewhere and is in accord with the ‘Intermediate disturbance hypothesis’ much favoured by plant ecologists (although not without some debate). The results from this study point to the importance of certain soil properties as potentially significant ecosystem drivers. This is reflected in the relationship between plants and the level of exchangeable cations and pH, soil texture and, to a lesser extent total N% and C%. Some clear relationships between certain PFTs and PFEs and soil texture (Figs. 11,12) can be readily interpreted as a causal (adaptive) condition related to available soil moisture. Because sandy soils generally retain less moisture longer than silty soils, they are more likely to support plants where the adaptive perennating organ (such as cryptophytic, belowground storage roots and stems) is capable of surviving extended periods of soil moisture deficit. The use of macrolichen groups (Crustose, Fruticose, Foliose) as potential biodiversity indicators shows promise. Lichen sensitivity to soil texture both independently and expressed as a ratio with plant functional elements (Figs. 13,14) is clearly predictable within the context of the present survey. A causal interpretation of this relationship remains an open question (P.M. McCarthy, pers, comm.5). The application of a ‘Lichen Index’ based on cover-abundance of macrolichens and vascular plant species richness is a new development. Present indications suggest this index may be worth following in further surveys. The generic nature of the method also suggests it may have application across most global terrestrial ecosystems. The established use of lichens as indicators of atmospheric pollution also hints at their potential value in monitoring impacts due to environmental change. Tree rooting depth was estimated along road sides as opportunities permitted. While no formal quantitative estimate was attempted, it was the opinion of the team that soil depth as measured by auger at each transect was a reasonable indicator of adjacent tree rooting depth. This finding suggests that soil depth and related vegetation cover may have value as input variables in certain hydrological models such as DHSVM (Prof. J. Richey pers. comm.). If so it may provide a useful additional data dimension to the developing DrukDIF. The outcome from a workshop to discuss DrukDIF II was a useful precursor to further developments6 . The positive reaction by most participants indicated a genaeral awareness of the advantages to be gained from a carefully designed and constructed DIF. 5 Dr P.M. McCarthy Australian Biological Resources Study, Canberra. 6 See ‘DrukDIF Status Report. Working Draft, December 8, 2009. Jeffrey Richey and Andrew Gillison. Based on: DrukDIF Stakeholder Workshop and Follow-ups Thimphu, October 21st 2009 Dragon Roots Hotel.
27
10. Conclusions As indicated in the foregoing, while the results of the statistical analyses suggest a number of tentative conclusions, experience in surveys along elevational gradients in other countries strongly suggests such conclusions should be witheld until additional data have been analysed from the final survey of the lowland section of the Wang Chhu watershed. For this reason the current report remains interim rather than final. Despite the above reservations, a high level of statistically consistent relationships between certain plant and soil-based variables, (notably exchangeable cations, pH and soil texture) suggests these are likely to be supported by additional data from lower elevations (previous field reconnaissance reports refer). The TOR attached to this study require a set of recommendations for institutional responsibilities for sustainable biodiversity management and the developing DrukDIF. The outcome from the DrukDIF II workshop suggest such recommendations would be premature at this stage. The final report covering findings from the completed Wang Chhu watershed should assist in identifying areas for future work and thus indicate areas of future institutional responsibility. The data and analytical outcomes from the final watershed study will also be incorporated in the DrukDIF internet portal currently under development with the University of Washington. 11. References Gillison, A.N. (1981). Towards a functional vegetation classification. In: A.N. Gillison
and D.J.Anderson (eds.) 'Vegetation Classification in Australia', pp. 30-41. CSIRO and Aust. Natl University Press, Canberra.
Gillison, A.N. (2002) A generic, computer-assisted method for rapid vegetation classification and survey:tropical and temperate case studies. Conservation Ecology, 6: 3. (http://www.ecologyandsociety.org/vol6/iss2/art3/print.pdf).
Gillison, A.N. (2009) . Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase I: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. June 5 2009. (NSSC Thimphu).
Gillison, A.N. and Carpenter, G. (1997). A generic plant functional attribute set and grammar for dynamic vegetation description and analysis. Functional Ecology, 11: 775-783.
Magurran, A.E. (2004). Measuring Biological Diversity. Blackwell publishing, Oxford. 254 p.
Mattick, F. (1953). Lichenologische Notizen, I. Der Flechten-Koefficient und seine Bedeutung für Pflanzengeographie. Berichte Deutsche Botanische Gesellschaft, 66: 263-276.
Negi, H.R. and Gadgil, M. (2002). Cross-taxon surrogacy of biodiversity in the Indian Garhwal Himalaya. Biological Conservation, 105: 143-155.
28
29
Söchting U. (1999). Lichens of Bhutan, Biodiversity and Use. University of Copenhagen, Botanical Institute, Department of Mycology. Denmark. 30p.
Wangda, P. (2008). Preservation of agro-biodiversity landscape in a typical rural Bhutan. Preservation of Biocultural Diversity – a Global Issue, May 6-8, 2008, BOKU, Vienna.
Wangda, P. and Ohsawa, M. (2006). Gradational forest change along the climatically dry valley slopes of Bhutan in the midst of humid eastern Himalaya. Plant Ecology, 186: 109-128.
Wangda, P. and Ohsawa, M. (2007). Vegetation succession and soil recovery in the abandoned field at Tshokothangkha in Nahi, Wangdue. Bhutan Journal of Renewable Natural Resources, 3: 68-72.
ANNEX I (not included here)
ANNEX II
List of data variables recorded for each 40x5m transect
Site feature Descriptor Data type Location reference Location Alpha-numeric Date (dd-mm-year) Alpha-numeric Plot number (unique) Alpha-numeric Country Text Observer/s Observer/s by name Text Physical Latitude deg.min.sec. (GPS) Alpha-numeric Longitude deg.min.sec. (GPS) Alpha-numeric Elevation (m.a.s.l.) (aneroid or GPS) Numeric Aspect (compass. deg.) (perpendicular to plot) Numeric Slope percent (perpendicular to plot) Numeric Soil depth (cm) Numeric Soil type (US Soil taxonomy) Text Parent rock type Text Litter depth (cm) Numeric Terrain position Text Site history General description and land-use / landscape
context Text
Vegetation structure Vegetation type Text Mean canopy height (m) Numeric Crown cover percent (total) Numeric Crown cover percent (woody) Numeric Crown cover percent (non-woody) Numeric Cover-abundance (Domin) - bryophytes Numeric Cover-abundance woody plants < 2m tall Numeric Basal area (mean of 3) (m2ha-1); Numeric Furcation index (mean and cv % of 20) Numeric Profile sketch of 40x5m plot (scannable) Digital Plant taxa Family Text* Genus Text* Species Text* Botanical authority Text* If exotic (binary, presence-absence) # Numeric Plant Functional Type Plant functional elements combined
according to published rule set. Text*
Quadrat listing Unique taxa and PFTs per quadrat (for each of 8 (5x5m) quadrats) #
Numeric
Photograph Hard copy and digital image # JPEG
* Where identified, usually with voucher specimens. More detailed information available at www.cbmglobe.org
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ANNEX III
Listing of Plant Functional Types (PFTs) and vascular plant taxa - sample page
Transect PFT Family Genus Species Code WC23 le-la-do-de-fi-hc-ad Adiantaceae Pityrogramma calomelanos PITYCALO WC23 me-la-do-de-hc-ad Asteraceae Ainsliaea sp06 AINSSP06 WC23 na-la-do-de-hc-ad-ep Asteraceae Anaphalis margaritacea ANAPMARG WC23 na-la-do-hc-ad Asteraceae Anaphalis sp21 ANAPSP21 WC23 no-la-do-de-cr Asteraceae Cacalia sp11 CACASP11 WC23 no-la-do-de-ro-cr-ad Asteraceae Carpesium sp23 CARPSP23 WC23 ma-la-do-de-ro-su-cr Asteraceae Ligularia amplex LIGUAMPL WC23 na-la-do-de-ro-hc-ad Asteraceae Senecio wallichii SENEWALL WC23 na-la-do-de-ch-ep Berberidaceae Berberis sp29 BERBSP29 WC23 na-la-do-de-ch Berberidaceae Berberis sp29 BERBSP29 WC23 me-la-do-de-ch Betulaceae Betula utilis BETUUTIL WC23 na-la-do-de-ch-li Caprifoliaceae Lonicera sp14 LONISP14 WC23 pi-co-do-ph Cupressaceae Juniperus recurva JUNIRECU WC23 pi-co-do-de-fi-hc-ad-ep Davalliaceae Davallia sp17 DAVASP17 WC23 le-ve-do-de-ro-fi-hc-ad Dryopteridaceae Dryopteris clarkei DRYOCLAR WC23 mi-la-do-ch Ericaceae Rhododendron campylocarpum RHODCAMPWC23 mi-la-do-ch-ad-ep Ericaceae Rhododendron campylocarpum RHODCAMPWC23 na-ve-do-hc-ad Gentianaceae Gentiana sp09 GENTSP09 WC23 pl-ve-is-de-cr Iridaceae Iris sp05 IRISSP05 WC23 me-ve-do-de-su-pv-cr Liliaceae Clintonia udensis CLINUDEN WC23 mi-pe-do-de-cr Liliaceae Polygonatum sp15 POLYSP15 WC23 na-co-do-ph Pinaceae Abies densa ABIEDENS WC23 na-co-do-ph Pinaceae Tsuga dumosa TSUGDUMOWC23 na-ve-do-de-pv-hc-ad Poaceae Eragrostis nigra ERAGNIGR WC23 na-co-do-de-pv-hc-ad Poaceae sp34 SP34 WC23 na-la-do-de-fi-hc-ad Polypodiaceae Polypodiodes lachnopus? POLYLACH WC23 na-la-do-de-fi-hc-ad-ep Polypodiaceae Polypodium sp18 POLYSP18 WC23 mi-ve-do-de-ro-cr Primulaceae Bryocarpum himalaicum BRYOHIMA WC23 na-la-do-de-cr Ranunculaceae Thalictrum sp16 THALSP16 WC23 mi-la-do-de-hc-ad Rosaceae Fragaria nubicola FRAGNUBI WC23 na-la-do-de-ro-hc-ad Rosaceae Potentilla griffithii POTEGRIF WC23 na-la-do-de-ch Rosaceae Rosa sericea ROSASERI WC23 na-la-do-de-ph Rosaceae Rosa sericea ROSASERI WC23 mi-la-do-de-hc-ad Rosaceae Rubus fragarioides RUBUFRAG WC23 na-la-do-hc-ad Rosaceae Rubus nepalensis RUBUNEPA WC23 na-la-do-de-ch-ad Rosaceae Rubus sp40 RUBUSP40 WC23 na-la-do-de-ch-ad Rosaceae Sorbus microphylla SORBMICR WC23 na-la-do-hc-ad Scrophulariaceae sp19 SP19 WC23 na-la-do-de-su-cr Urticaceae Pilea approximata PILEAPPR WC23 me-la-do-de-su-hc-ad Euphorbia? sp25 EUPHSP25
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1
Integrated Biodiversity Survey of the Lower Wangchhu Watershed, Bhutan
13 – 23 May 2010
Andrew N. Gillison
Including: The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Middle
and Lower Wangchhu (Zones B and C) by H. van Noord
21 June 2010
2
Executive summary
1. The DrukDIF is integrating key biophysical aspects of the natural resources of Bhutan to assist policy planning and sustainable resource management. A key focus is on biodiversity, hydrology and land use. As one of the key drainage systems within Bhutan and the Eastern Himalaya the Wangchhu watershed was therefore a logical baseline for documenting and modeling ecosystem performance at the regional and landscape level. Following close discussion with national stakeholders and training of national personnel from different agencies, a comprehensive ‘landscape-based’ survey of the watershed was designed and implemented with national and international support.
2. Because of its size and extensive elevational gradient, the watershed was divided into three operational zones: “A” high elevation (3,000-5,000m), “B” mid-elevation (1,500-3,000m) and “C” lowland (200 – 1,500m). This interim report contains the results of survey “C” that for logistic and analytical reasons included mid to lower elevational sections of “B” – a total of 31 (200m2) transects. The final report for the entire watershed awaits completion of soil analyses and plant identifications.
3. Team structure consisted of a plant ecologist (RNR-RC, CoRRB), a soil surveyor, a technical assistant and a geomorphologist (NSSC/SLMP) supported by a botanist (NBC). Fieldwork was coordinated by an international biodiversity specialist (CBM) in liaison with NSSC staff. The survey provided an opportunity for advanced in-field training in survey methodology for two team members.
4. As described in previous reports, the survey employed environmental gradient-directed transect (gradsect) sampling methodology based primarily on an elevational (thermal) gradient and a subsidiary hierarchy of gradients including drainage, land form, land use and land cover. Unlike biodiversity surveys that focus mainly on species, the survey was multidisciplinary in nature, and acquired biophysical data that are consistent with modeling ecosystem dynamics and the DrukDIF. Within the overall gradsect at each transect a standard international protocol (VegClass) was used to record core biophysical data including vegetation (species, functional types, structure), soils and land use. For this survey, additional climate data (temperature, evapotranspiration, rainfall, seasonality and runoff) were supplied by the University of Washington.
5. Exploratory data analysis of the 31 transects revealed a sequence of vegetation types: 1) simply structured, managed conifer forests (2500-2700m); 2) semi-deciduous, complex conifer –broadleaf forests (2300-2500m); 3) evergreen forests (1500-2300m) 4) Deciduous Sal (Shorea robusta) dipterocarp forest (500-1500m); 5) Lowland semi-deciduous vine forest on deep soils and deciduous leguminous forest on the gravelly outwash plains of the Wangchhu (< 500m) and 6) Successional slash and burn (Tseri) cropping sequences (760-1500m). A classification based solely on lichen cover-abundance clearly identified conifer, broadleaf and successional types. The sequences of vegetation types, plant taxa
3
and functional types reflect a strong climate gradient that supported the gradsect sampling approach.
6. Preliminary statistical analyses indicate a strong predictive relationship between certain leaf-based, plant functional characteristics and climate variables. The relatively novel use of functional components in this way highlights their potential for modeling interactions between plant-based biodiversity and hydrology. As with similar surveys in other countries (Brazil, Mozambique) final data analysis of the watershed is expected to reveal close feedback relationships between biodiversity, soil and land use.
7. The survey of the Wangchhu watershed would not have been possible without the close collaboration between national and international agencies. Together with effective capacity enhancement, this has resulted in a unique set of baseline data and resource information that will contribute significantly to the DrukDIF and to decision support in policy planning and management.
_________________________________________________________________
4
Acronyms*
GNHC CNR
Gross National Happiness Commission College of Natural Resources, Royal University of Bhutan, Lobesa
DANIDA Danish International Development Assistance
DHSVM Distributed Hydrology Soil Vegetation Model
DrukDIF Bhutan Dynamic Information Framework FAO Food and Agriculture Organization, Rome GEF Global Environment Facility GIS Geographic Information System ICIMOD International Center for Integrated
Mountain Development IUCN International Union for the Conservation of
Nature, Gland, Switzerland KL Kangchenjunga Landscape MoAF Ministry of Agriculture and Forests NAP National Action Plan on Land Degradation NAPA National Adaptation Plan of Action NBC National Biodiversity Centre NCD Nature Conservation Division (Dept.
Forests, MoA) NEC National Environment Commission NGO Non-Government Organization NSSC National Soil Services Center PFC Plant Functional Complexity PFE Plant Functional Element PFT Plant Functional Type RGoB Royal Government of Bhutan RNR RNR-RC, CoRRB
Renewable Natural Resources (MoAF) Renewable Narural Resources – Council of Renewable Natural Resources Research of Bhutan
RSPN Royal Society for Protection of Nature SLMP Sustainable Land Management Project TOR Terms of Reference USGS United States Geological Survey (US
Department of the Interior) USGS-NPS United States Geological Survey, National
Parks Service UW University of Washington, Seattle, USA VIC Variable Infiltration Capacity Model WB The World Bank WWF Worldwide Fund for Nature * Used in this and previous DrukDIF reports
Bhutanese Terms*
Term Meaning Chathrim Act, rules and regulations, codes of conduct Chhu River or rivulet Chimi Representative at the National Assembly Dasho Administrative Head of a district or Dzongkhag Dzongdag Head of a district Dzongkhag District Dzongkhag Yargye Tshogchung District Development Committee Dungkhag Sub-district
Dungpa Head of a sub-district Geog (chiog) Block, which is usually made up of few to several villagesGeog Yargye Tshogchung Block Development Committee Gup Head of a block Mangmi Elected representative of a geog, second in command
after gup Tseri Slash and burn cultivation Tshogpa Representative of a village, or a cluster of villages * Used in this and previous reports
List of figures Figure 1(a) Survey team L->R, Tandin Wangdi (Botanist), A.N. Gillison (Biodiversity
specialist), Kinley Penjor (Soil Surveyor), Cheten Thinley (Plant Ecologist), (b) L->R Chador (field assistant), H. van Noord (Geomorphologist)
Figure 2. Section of map from Grujic et al. (2002) Figure 3. The lowest section of Wangchhu in Bongo geog and the apex of its alluvial fan
complex on the Indian border. Note the striking change in course from a N-S trending course to a WNW-ESE course and the change in river morphology from a predominant linear channel to a strikingly meandering flow path. The MCT is indicated with a red dotted line.
Figure 4. a). Steeply sloping gorges in the lower Wangchhu limit sampling access. b) View of the lowland outwash plains of the Wangchhu From WC55, Baikunza 881m.
Figure 5. Location of the 62 transects. Area under dotted line includes subset from Section B (13 transects) combined with Section C (18 transects) used in the preliminary numerical analysis in this report.
Figure 6. Distribution of 62 transect points along the Wangchhu watershed relative to topographical relief, National boundary (bright yellow line) and key road systems (dull yellow line) (GoogleEarth 2010) (see Figure 4 for transect labels).
5
Figure 7. Wangchhu biodiversity. (a) Terrestrial orchid Galeola lindleyana near Kemalakha 1550m (b) Rhododendron campylocarpum Chelela 2700m (c) Rhododendron cf. hodgsonii Chelela 2750m (d) Gonatanthus pumilis Baikunza 800m (e) Cyprinid fish
6
Labeo dyocheilus Wangchhu river 220m (f) Woodpecker tree 1800m Gedu (g) Paris Peacock Achillides paris Jemichhu 220 (h) L-R Common Mormon Menelaides polytes, Six-bar Swordtail Pazala eurous, Glassy Bluebottle Idaides cloanthus Cluster at 240m on cow dung, Wangchhu riverside near Alam Thang.
Figure 8. Relationship between number of species possessing the isobilateral ‘IS’ PFE per transect. Closely related to the distribution of Pine species along a thermal and rainfall seasonality gradient
Figure 9. Classification based on counts of plant genera. Group (A) Disturbed, mainly evergreen broadleaf forest with successional stages. (B) Tall evergreen broadleaf forest (C) Tseri slash and burn sequences, Pakchika area (D) Buckwheat and padi rice (E) Lower elevation Tseri at Baikunza (F) Conifer forests with some deciduous broadleaf elements.
Figure 10. Classification based on vegetation structure (Table 5). Group (A) Mixed group of highly disturbed broadleaf evergreen forest and heavily disturbed conifer forest (WC45-46). (B) Late stage Tseri sequences Pakchika and Baikunza (C) Mostly conifer forests with one Alnus plantation (WC36). (D) Early Tseri stages and recent agricultural crops.
Figure 11. Classification based on Plant Functional Elements (PFEs) weighted by number of species with each PFE attribute per transect. Group (A) Highly disturbed broadleaf (mainly fagaceous) forest (WC32,34,37) and Tseri slash and burn succession at Pakchika (Bongo geog). (B) Mixed tall broadleaf forest including Sal (deciduous Shorea robusta forest WC58). (C) Conifer forests (D) Buckwheat crop (E) Agricultural crops (Maize, Millet) and outlier (WC60) forest on outwash plains with many weedy species.
Figure 12. Classification based solely on lichen cover-abundance. Group (A) Highly disturbed broadleaf forest including Alnus plantation (B) Semi-deciduous and deciduous (Sal) broadleaf forest including late stage Tseri (WC37) (C) Conifer forests (D) Mostly Tseri successional sequences (E) Early Tseri (WC40) and agricultural crops.
List of Tables
Table 1. Team membership and area of expertise Table 2. Transect locations and site physical properties Table 3. Vegetation type and land use Table 4. Summary of species, PFTs and PFC Table 5. Vegetation structural values Table 6 Plant Functional Elements (PFEs) listed for all 18 transects in lower Wangchhu Table 7. Cover-abundance scores of lichens Table 8. Climate values for Lower Wangchhu
Annexes
I Terms of Reference II Table 1. Sample page of tentative species recorded for Zone C 18 transects Table 2. Sample page of unique Plant Functional Types (PFTs) listed in alphabectical order for Zone C
7
Table 3. List of data variables recorded for each 40x5m transect Annexes (cont.) III Photographic records of Zone C vegetation types
List of figures Figure 1. WC45 Paro side of Chelela. Managed conifer forest. Pinus wallichiana, Picea spinulosa. Pieris formosa and Quercus semecarpifolia understorey (37 spp, 24 PFT). 2688 Figure 2. WC46. Near Jyenkana, Haa valley. Managed conifer forest. Pinus wallichiana, Picea
spinulosa. Shrubby understorey of Lyonia villosa, Pieris formosa and Daphne bholua (32 spp, 23 PFT) 2705m.
Figure 3. WC47. 20 K S. of Susuna, Haa valley.Conifer forest of Pinus wallichiana with understorey of Berberis sp. Lyonia villosa and Rosa sericea. (38 spp. 29 PFT) 2634m
Figure 4. WC48. Near Nago, Haa valley. Conifer-Broadleaf forest Pinus wallichiana, Picea spinulosa, Populus ciliata with understorey of Rosa sericea, Lyonia villosa and Berberis praecipua. (41 spp., 34 PFT) 2755m.
Figure 5. WC49. 10 K. E. of Jyenkana. Mixed conifer-broadleaf forest. Pinus wallicihiana, Picea spinulosa, Tsuga dumosa, Populus ciliata, Salix spp. Understorey with Rosa sericea, Berberis praecipua Daphne bholua. (42 spp. 30 PFT) 2739m.
Figure 6. WC50. Near Jyenkana, Haa valley. Tall conifer forest Pinus wallichiana, Picea spinulosa with understorey of Quercus semecarpifolia, Berberis spp., Daphne bholua and Lyonia villosa. (35 spp. 27 PFT) 2592m
Figure 7. WC51. Near Chapcha. Mainly conifer (Pinus wallichiana) forest with Oak (Quercus lanata) and understorey of Rhododendron arboreum, Berberis praecipua, Rosa brunonia and Lyonia villosa. (44 spp. 35 PFT) 2363m.
Figure 8. WC52. Above Tashi Gatshel. Tall semi-deciduous broadleaf forest. Quercus lamellosa, Euphorbiaceae. Understorey of Viburnum sp., Daphne bholua and Symplocos aff. nepalensis. (45 spp. 37 PFT) 2221m.
Figure 9. WC53. 1 K N of Taktikoti. Tall, semi-deciduous broadleaf forest. Castanopsis sp., Quercus lamellosa, Symplocos lucida with Strobilanthes dominated understorey. Numerous ferns (46 spp. 37 PFT) 2023m.
Figure 10. WC54. 2km E. of Chasilaka. Mixed semi-deciduous broadleaf forest dominated by Castanopsis sp., Juglans regia, Acer sp., Persea fructifera, Araliaceae. Understorey with Symplocos lucida, Maytenus rufa. Numerous ferns. (47 spp. 39 PFT) 2023m
Figure 11. WC55. Baikunza. Three-year old slash and burn ‘Tseri’ at Baikunza. Artemisia vulgaris dominant. Emergent Ostodes paniculata, Mallotus philippensis, Glochidion sp. Many Dioscorea spp. (46 spp. 37 PFT) 881m.
Figure 12. WC56. Baikunza. Two month old mixed crop of Maize (Zea mays), Finger millet (Eleusine coracana) and Foxtail millet (Setaria italica) (28 spp. 24 PFT) 879m.
Figure 13. WC57. Three month old pure Maize (Zea mays) crop. Baikunza. (28 spp. 24 PFT) 767m
Figure 14. WC58. Sal (Shorea robusta) deciduous forest. Amsepho. Herbaceous understorey (Curculigo, Hedychium, Kyllinga, Dioscorea spp. Fabaceae) (46 spp. 42 PFT) 681m.
Figure 15. WC59. Tall semi-deciduous vine forest. Jemichu. Lower Wangchhu floodplain. Pterospermum sp., Adenanthera pavonina. Understorey of Murraya koenigii, Bauhinia purpurea, Mallotus philippensis, Ervatamia sp. Numerous lianes. (63 spp. 47 PFT) 222m
Figure 16. WC60. Alamthang – lower Wangchhu floodplain. Heavily grazed, dry deciduous low, weedy, forest dominated mostly by Adenathera pavonina, Bombax ceiba and Acacia sp. (23 spp. 22 PFT) 237m.
8
Figure 17. WC61. Jemi Thang. Tall mostly evergreen riparian forest dominated by Duabanga grandiflora. Understorey Maesa chisia, Clerodendrum paniculatum, Adenanthera sp., Murraya koenigii, Leea sp. Mussaenda. Numerous lianes, succulent aroids (Amorphophallus, Colocasia) (51 spp. 41 PFT) 340m.
Figure 18. WC62. Between Kemalakha and Chargarey. Tall mixed, broadleaved, mainly evergreen forest with dominant Alcimandra cathcartii, Castanopsis sp., Litsea sp. Understorey with Ardisia sp., Ostodes paniculata, Daphniphyllum, Casearia glomerata, Melastoma sp., Daphne bholua. (40 spp. 29 PFT) 1540m.
9
1. Introduction The DrukDIF is integrating key biophysical aspects of the natural resources of Bhutan to assist policy planning and sustainable resource management. A key focus is on biodiversity, hydrology and land use. As one of the key drainage systems within Bhutan and the Eastern Himalaya the Wangchhu watershed was therefore a logical baseline for documenting and modeling ecosystem performance at the regional and landscape level. Following close discussion with national stakeholders and training of national personnel from different agencies, a comprehensive ‘landscape-based’ survey of the watershed was designed and implemented with national and international support This report covers the third and final section (Zone C) of a three-part survey of the Wangchhu watershed. Zone A (2600-4600m), Zone B (1500-3000m), Zone C (220m – 2700m). The present submission is thus a logical continuation of previous reports1 2 The survey of Zone C was timed to coincide with late spring flowering and fruiting in order to improve biodiversity sampling as well as to avoid monsoonal rains. In addition to sampling the lower section of the Wangchhu watershed the survey also targeted sampling gaps in the previous survey of Zone B where lack of access was due to heavy unseasonal rain and flooding. As with previous surveys, the team collected basic data on vegetation, soils and land use history. While vegetation and key site physical data were readily analyzable following the survey, soil analyses are unlikely to be available before June 30. For that reason the present report is an interim account that deals with vegetation and land use alone. When all data are available, a final report covering the entire Wangchhu watershed (Zones A,B.C) will be submitted. 2. Terms of reference (Extract from Annex I)
Rapid Biodiversity Assessment for DrukDIF In March 2009 a Stakeholder Workshop was organized in Thimphu, Bhutan, to initiate the establishment of a Dynamic Information Framework for the natural resources of Bhutan. During this workshop it was decided that focus would be put on the Wangchu watershed area as a pilot area and that rapid biodiversity assessments would be carried out along the altitudinal gradient of the Wangchu watershed. In July 2009 a training was carried out to introduce Bhutanese biodiversity specialists in the methodology to be used for the rapid biodiversity assessments. A team of trainees set out for the first segment of the rapid biodiversity survey, section”A” in the sub-alpine zone, between 3000m to 5000m. A second survey was carried out in October 2009 for the mid-latitudes between 3000 to about 1500m, covering the
1 Gillison, A.N. (2009). Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase II: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. Wangchhu watershed, Alpine section (3000-5000m). Including report by van Noord, H. and Dorji, T. The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Upper Wang Chhu. World Bank, Sustainable Land Management Project, Bhutan. 5 Sept. 2009. 2 Gillison, A.N. (2009) Biodiversity Baseline Survey of the Wangchhu Watershed Section”B” Mid-elevation zone. World Bank, Sustainable Land Management Project, Bhutan.18 December 2009.
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section between Haa and Gedu. The preliminary results were presented during the second DrukDIF Stakeholder workshop in Thimphu, end of October 2009. The last section to be covered is the so-called Zone C, the section of warm temperate to sub-tropical forests and agricultural land downstream from Bongo towards the Indian border. A selection of trainees and team members of Zone “A” and “B” will join this survey to finalize the Wangchu rapid biodiversity assessment.
Deliverables: Following completion of Phase II input 2, the rapid natural resource baseline activities will result in the following deliverables: Phase III (29April – 7 June 2010): total 40 working days in and ex country
1. Completion of survey of Wangchhu watershed a. Liaise with NSSC/ SLMP to select a survey team made up of personnel
from stakeholder institutions including where possible, participants from the previous training workshop on ‘Aboveground Biodiversity Assessment’.
b. Identify a team leader. c. Assist team members with the design, coordination and implementation of
a survey of the remaining sector “C” of the Wangchhu watershed. d. Ensure that the survey methodology is consistent with that undertaken in
Sections “A” and “B” of the same watershed. e. To the extent that data (e.g. plant identifications) are sufficiently complete,
collate, store and analyze data from the survey of Section “C”. 2. Reporting of survey outcomes
a. As soil survey analytical data are unlikely to be available until mid-July 2010, on the conclusion of fieldwork, and while in-country, provide an interim report only on the outcome of the survey of section ‘C”.
b. Based on an analysis of available survey data for the Wangcchu watershed, prepare a presentation of the results for a workshop to be conducted for DrukDIF Phase III.
c. When all survey data are complete, prepare and submit a final report on the entire survey of the Wangchhu watershed. The report should include any issues and recommendations relative to training, and the extent to which the survey outcomes may apply to the remainder of Bhutan, focusing in particular on sustainable biodiversity and land management.
3. Data storage, security and compliance a. It is anticipated that the data collected from the survey of the Wangchhu
watershed will make a signficant contribution to the natural resource information baseline for Bhutan including DrukDIF. For that reason it will be important to ensure data are collated and stored in a format that is consistent with industry standards and complies as far as possible with developing National geospatial database standards within Bhutan.
b. Soil analytical data from the Wangchhu survey will be collected and stored according to standards already in place in NSSC. VegClass data and data summaries will be prepared in industry standard format. To ensure security, electronic copies of raw data will be maintained at NSSC, CBM and UW. Data will also be stored on DrukDIF in a format yet to be decided.
2. The team in the landscape The multidisciplinary expertise of the team ( Table 1., Figs. 1a,b) facilitated an integrated aproach to survey. While each team member contributed specific expertise in the recording of field data, the survey was designed and coordinated jointly by NSSC and CBM.
Figure 1(a) The L-R, Tandin Wangdi (Botanist), A.N. Gillison (Biodiversity specialist), Kinley Penjor (Soil Surveyor), Cheten Thinley (Plant Ecologist) (b) Chador (field assistant), H. van Noord (Geomorphologist).
Table 1. Team membership and area of expertise
No. Name Institution Task/Expertise 1 Tandin Wangdi NBC Botanist 2 Cheten Thinley RNR-RC, CoRRB Plant ecologist 3 Kinley Penjor NSSC Soil surveyor 4 Chador NSSC Driver/ field assistant 5 Hans van Noord NSSC Geomorphologist 6 Andrew N. Gillison CBM Biodiversity specialist
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a b
3. The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Middle and Lower Wangchhu (Zones B and C)
by H. van Noord 3.1 Geology Grujic et al. (2002) published the most recent simplified geological map of Bhutan with a new stratigraphic and tectonic description, (see Figure 2 below), on which the survey gradsects of Zones B and C have been indicated with a red dashed line. In essence, the survey cuts across four main geological units:
B
C
1. The MCT zone, also known as Jaishidanda, and earlier named Paro Formation. This is a complex of lower grade metamorphic rock types as quartzites, schists and marbles. 2. The Greater Himalayan Sequence, dominated by higher-grade metamorphic rock types as (garnetiferous) muscovite gneiss, also known as Thimphu Formation. 3. Lesser Himalayan Sequence, to the south of the Main Central Thrust (MCT, is the single largest structure within the Indian plate), consisting of tectonically disturbed unfossiliferous sedimentary and metasedimentary rocks like shale, sandstone, conglomerate, slate, phyllite, schist, quartzite, limestone, dolomite etc.
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Figure 2 Section of map from Grujic et al. (2002)
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4. Quaternary deposits, build up by the large alluvial fan complexes of the Bhutanese rivers into the plains, formerly known as duars. The four main geological zones are separated from each other by thrusts zones. Between the quartenary and the Lesser Himalayan Sequence one finds the Main Boundary Thrust and the MCT zone marks the transition from the Lesser Himalayan Sequence to the Greater Himalayan Sequence. The area between Paro and Haa forms part of the “Paro Window”, an opening in the Greater Himalayan Sequence through which one can see the low-grade metamorphic materials of the Paro Formation, part of the Lesser Himalayan Sequence. Important consequence of the MCT and MBT zones is that they resulted in lesser geotechnical strength of the rocks in these zones, reflected in a very high incidence of slope instability, e.g. large, active mass movement of Jumja along the Phuntsholing-Gedu highway. 3.2 Geomorphology The landscapes along the middle and lower Wangchhu transects (Fig. 2) are distinctly different from the Upper Wangchhu section, covered in Zone A. The glacial and fluvio-glacial influences, which are so evident above 3700m in Zone A, are absent at lower altitudes. The following main landscape units can be distinguished: A Haa Valley (WC24-31; WC46-50) Although glacial and peri-glacial processes have left their traces at the higher sections of Chele-La and in the Upper Haa valley, the overall landscape appears to be a broad fluvial valley, incised by the Haa Chu, with considerable infill with alluvial and debris flow deposits from a range of tribituaries. These relatively gentle fan and alluvial deposits are the key agricultural areas in the Haa valley. Towards the south the valley bottom narrows and Haa incises more (WC47-49) and bends to the East towards the confluence with Wangchhu. B Wangchhu Valley ( WC31-32; WC51-54, WC62) Downstream of the confluence of Paro Chhu and Thim Chhu at Chuzhom, the Wangchhu is incised in a deep alluvial valley. The steep valley slopes offer very little opportunity for human settlement and only a few larger settlements have developed where the valley slopes are somewhat more gentle, such as near Chapcha (WC51) and Tshimasham. These gentler slope sections have mostly been caused by large mass movement complexes. The often older slope instability has resulted in deep-seated landslides, which have been occupied by human settlement and agriculture. These gentle slope segments are also the logical sections for the road to descend to river level, as in the section between Tshimasham and Chhukha Lower Colony. C Lower Wangchhu Gorge (WC55-61) The Wangchhu is forming an impressive fluvial incision downstream of Tala dam site, with very steep valley slopes and hardly any opportunity for human habitation on the lower slopes. This gorge-like incision continues in fact all the way down to lower Bongo geog, where the gorge opens up and the Wangchhu finally is released into the Indian plains, the former Bhutanese Duars, a complex of large alluvial fans with gentle slopes towards the Brahmaputra. In a very interesting section in Lower Bongo geog, Wangchhu suddenly changes its course from a general north-south trend to a WNW-ESE course. In a very steep gorge the Wangchhu is able to form clear meanders, a feature that is almost absent in its upstream stretches. The sudden change in flow direction coincides exactly with the location of the MCT and the transition from relatively resistant and hard gneisses to the north of
Wangchhu, and the MCT, to relatively weak and unstable meta-sediments and sediments south of Wangchhu. Along the MCT, which essentially is a weakness zone, as the rocks in this transition thrust zone have been impacted by the enormous forces of the movement and shear of the tectonic units, the Wangchhu is able to make space and form meanders in the geotechnically weaker rocks, as compared to the Thimphu gneisses it was caught in for most of its North-South journey from Chuzom.
Figure 3. The lowest section of Wangchhu in Bongo geog and the apex of its alluvial fan complex on the Indian border. Note the striking change in course from a N-S trending course to a WNW-ESE course and the change in river morphology from a predominant linear channel to a strikingly meandering flow path. The MCT is indicated with a red dotted line. 3.3 References
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Grujic, D., Hollister, L. S. and Parrish, R. R. (2002). Himalayan metamorphic core as an orogenic channel: insight from Bhutan. Earth and Planetary Science Letters, 198: 177-191.
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olythetic
5. Methodology The methodology used to record and describe vegetation, soils and land use in surveys “A” and “B” was also applied in this survey. Overall sampling methodology is described in detail in previous reports3 4 as well as on the internet5. As in previous surveys the field recording system includes plant functional types (PFTs). These, together with their composite plant functional elements (PFEs) and a measure of plant functional complexity (PFC) (see Box 1) are used as a complement to species data. As indicated in the foregoing, due to unseasonal weather and local flooding, a section of the primary gradsect in Zone B could not be sampled. This section, between the lower Haa valley and Gedu was subsequently sampled in the present survey. These sample sites overlapped with those in Zone C and a number of sites previously sampled in the Pakchika area of the Bongo geog also fell within the lower elevation region (ca. 1500m). For analytical purposes they were therefore combined with the 18 transects in the present survey, making a total of 31 transects. Much of the lower Wangchhu consists of steeply sided gorges that renders access difficult and impractical. This limitation is the underlying reason for some obvious sample gaps in the thermal and elevational gradients. While the survey was timed to avoid monsoonal rains and to coincide with maximum flowering and fruiting, unexpected flooding of the Wangchhu due to unseasonal rains prevented the team from accessing an area on the northern side of the river east of the village of Bongo. Final data analysis can only be undertaken with the entire survey of 62 transects. A significant umber of species remain to be identified from voucher specimens. For this reason a numerical analysis of plant genera was undertaken instead of species. For indicative purposes, preliminary exploratory analysis of data from the 31 transects was applied to four data subsets (presence/absence of plant genera, vegetation structure, species-weighted plant functional elements (PFEs) and lichen cover-abundance). Using the PATN software package6 (Belbin 1992), a Bray-Curtis association measure was applied with a pagglomerative fusion strategy and a Beta clustering value of -0.25. Unlike the previous surveys, certain climate data were made available through the kind offices of the University of Washington, Seattle (Prof. J. Richey and staff). For each georeferenced transect these included maximum mean annual temperature, minimum temperature of the coldest month, mean annual preciptiation, cv% of precipitation over a 12 month period in 2006 (a measure of rainfall seasonality), actual evapotranspiration (mm day-1 and annual) and runoff (mm day-1 and annual). Standard Pearson correlation and linear and non-linear regression analysis (SigmaPlot v. 9.0 and Minitab v. 15) were used to explore
3 Gillison, A.N. (2009). Developing a Functional Landscape-Scale Land Cover, Biodiversity, Hydrology Modeling Framework (DrukDIF) for the SLMP areas of Bhutan. Phase II: Rapid Natural Resource Assessment Along Land Cover and Land Use Gradients. Wangchhu watershed, Alpine section (3000-5000m). Including report by van Noord, H. and Dorji, T. The Physical Base of the Survey Gradsect: Geology, geomorphology and soil development along the Upper Wang Chhu. World Bank, Sustainable Land Management Project, Bhutan. 5 Sept. 2009. 4 Gillison, A.N. (2009) Biodiversity Baseline Survey of the Wangchhu Watershed Section”B” Mid-elevation zone. World Bank, Sustainable Land Management Project, Bhutan.18 December 2009 5 www.cbmglobe.org 6 Belbin, L. (1992) P ATN Pattern Analysis Package: T echnical Reterence. Commonwealth Scientific and Industrial Research Organization, Div. Wildlife & Ecology, Canberra.
correlative relationships between these climate values and PFEs. At the time of writing, further analyses remain to be completed. All recorded vegetation data were compiled using the VegClass software package as in previous surveys. Electronic copies have been lodged with NSSC, NBC and CBM. When corrected and edited, final copies of the original data and metadata will be made available via the DrukDIF web portal managed by UW. No fauna were recorded during the survey. Pictorial records only were made of avifauna, fish and insects (butterflies).
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Box 1
Plant Functional Typology
Sustainable management of biodiversity relies on an understanding of the key factors that control the distribution and performance of species. Unfortunately there is very little in a species name that carries any useful information about how a species or plant individual adapted to environment or responds to environmental change. By classifying plants according to the way they combine certain morphological or adaptive ‘functional’ features it is possible complement species names in a way that adds important information for biodiversity management. In the VegClass system, a plant individual can be descibed as a Plant Functional Type (PFT) by combining a specific a set of Plant Functional Elements (PFEs). In this system a generic set of 36 PFEs are used via a rule set and grammar as a basis for describing a plant according to one or more of its functional leaf attributes, life-form and above-ground rooting system (Annex II Table 3). Thus an individual of the deciduous tree species Shorea robusta (Sal) might have the PFT me-co-do-de-ph that is composed of the PFEs mesophyll leaf size class, composite leaf inclination, deciduous, phanerophyte life form. Within the same species a change in any one of the PFEs (such as leaf size class) would result in a different PFE. This method confers greater sensitivity in detecting change in a species along an environmental gradient e.g. deep and shallow soils. More than one species can occur within a PFT and vice versa . Because the system is generic it can be applied uniformly to vegetation worldwide. It can facilitate informed and quantitative comparisions between geographically remote locations with, for example, environmentally similar habitats where the species may differ but where the similar PFTs are similar. When PFTs are combined with species data they can become a potentially powerful tool in identifying indicators for biodiversity and agricultural productivity. Measures of diversity are widespread in plant ecology but there are few effective measures of functional diversity. An alternative measurement of plant functional complexity (PFC) has been found especially useful as a biodiversity indicator. PFCs are calculated as a measure of the total distance of a minimum-spanning-tree of PFT distances within any one plot. The measure is useful in differentiating between two plots which, for example, may have the same number of PFTs but very different component PFEs – and thus different measures of complexity (see Table 4 ) The methodology is readily transferable. More information together with relevant publications can be found in www.cbmglobe.org
6. Site location and physical characteristics As described in the foregoing section on geomorphology, the lower part of the Wangchhu valley is bounded by steep gorges (Fig. 4a) that continue to the outwash plains near the confluence at Jimichhu, close to the Indian border (Fig. 4b). Site for the completed Wangchhu survey are labelled in Figure 5 with a topographic overview of site locations together with National boundaries and major road networks in Figure 6. Table 2 summarises geolocations, elevation, slope and aspect.
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Figure 4. a). Steeply sloping gorges in the lower Wangchhu limit sampling access. b) View of the lowland outwash plains of the Wangchhu From WC55, Baikunza 881m.
a
b
Figure 5. Location of the 62 transects. Area under dotted line includes subset from Section B (13 transects) combined with Section C (18 transects) used in the preliminary numerical analysis in this report.
18
19
Figure 6. Distribution of 62 transect points along the Wangchhu watershed relative to topographical relief, National boundary (bright yellow line) and key road systems (dull yellow line) (GoogleEarth 2010) (see Figure 5 for transect labels).
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Table 2. Transect locations and site physical properties *
Transect Location Lat. S Long. E Elevn (m)
Slope%
AspectDeg.
WC32 4km from Haa towards Chelela 26.95414 89.56335 1856 35 145 WC33 3km to Situ from just before Chasilaka 26.95366 89.56526 1819 60 62 WC34 6km towwards Situ from Chasilaka 26.90430 89.58836 1510 79 85 WC35 Near Alaykha community school, Gedu area 26.91669 89.54804 1753 35 350 WC36 Near Alaykha School 26.91457 89.54340 1805 20 359 WC37 Near Alaykha School 26.92830 89.59958 1439 45 113 WC38 Bayme Pang, (Pakchika, Bongo Geog) 26.93148 89.58818 1386 45 4 WC39 Zomchuthay (Pakchika, Bongo Geog) 26.93163 89.59877 1420 65 55 WC40 Zawalaktha (Pakichika - Bongo Geog) 26.92957 89.59944 1471 35 74 WC41 Pakichikha, Bongo geog 26.92950 89.59977 1448 50 80 WC42 Pakchikha, Bongo geog 26.99994 89.59971 1447 38 72 WC43 Pakchikha - Bongo geog 26.92993 89.59971 1447 35 60 WC44 Pakichikha =- Bongo geog [Survey B locations] 26.93192 89.59504 1477 35 60 WC45 Paro side of Chelela 27.38668 89.39790 2688 31 15 WC46 Logging road above Jyenkana, Haa valley 27.31505 89.31917 2705 90 300 WC47 20 km from Susuna towards Haa. Haa valley 27.23537 89.42417 2634 45 208 WC48 Near Nago, Haa valley 27.26270 89.36712 2755 80 220 WC49 8 km N of Jyenkana village, Haa valley 27.26021 89.32532 2739 85 128 WC50 Near Jyenkana village. Adj. bridge Haachhu 27.28857 89.30459 2592 2 254 WC51 Near Chapcha on Thimphu-Phuentsoling hwy. 27.20795 89.52826 2363 85 260 WC52 Above Tashi Gatshel. Main Phuents. hwy. 27.07189 89.57144 2221 24 203 WC53 1 km N of Taktikoti. Main Phuents. hwy 27.01668 89.56992 2023 80 330 WC54 2km E of Chasilaka 26.99739 89.58875 2023 54 8 WC55 Aewa Ganto (Baikunza). 26.79147 89.70702 881 38 294 WC56 Khapsilakha (Baikunza) 26.79209 89.70687 879 50 234 WC57 Khapsilakha (Baikunza) 26.78948 89.70251 767 3 287 WC58 Am Sepho (Between Baikunza and Jemichhu) 26.78229 89.70721 681 80 180 WC59 Jemichhu, lowest point on watershed 26.76936 89.72853 222 5 208 WC60 Alam thang 26.77463 89.71431 237 0 0 WC61 Jemi thang, near bridge crossing. Southern side. 26.80297 89.67926 340 50 30 WC62 Between Kemalakha and Chargarey. 26.78182 89.62955 1540 30 338
* Transects WC 32-44 are from Survey B. WC45-62 Survey C.
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7. Results Away from riparian flats, site recording was influenced by steepness of slope for which corrections had to be made in plot layout. For survey C, slopes ranged from 30-90% with an average of about 60%. Table 3 lists broadly descriptive vegetation types and related land use. Table 3. Vegetation type and land use
Transect Vegetation type and land use WC32 Secondary succession. Alcimandra dominant tree. Dense Strobilanthes, weeds WC33 Disturbed Oak-Laurel forest. Cut over, grazed WC34 Disturbed fagaceous forest with shrub undrerstorey. Cut over, grazed. WC35 Castanopsis forest with shrubby understorey. Cut over, grazed. WC36 Alnus nepalensis forest (plantation). Dense Strobilanthes, Cryptomeria japonica WC37 Seral shrubland following slash and burn (S/B). Remnant tree cover. WC38 Six year fallow stage. Dominated by shrubs. Some remaining trees. WC39 3-4 year shrub fallow dominated by Artemisia vulgaris. Some remnant trees. WC40 2yr seral shrubland in s/b cycle. Artemisia/ Chromolaena WC41 Cultivation, mixed crop and non-crop species. 8 month fallow. WC42 Newly emerging buckwheat, Fagopyrum esculentum WC43 Dominantly Amaranthus (caudatus?) crop WC44 Padi rice just before harvest. 3 months since planting, WC45 Managed conifer forest, Pinus wallichiana, Picea spinulosa. WC46 Managed conifer forest, shrubby understorey. Pinus wallichiana, Picea spinulosa. WC47 Pinus wallichiana forest WC48 Mixed Pinus wallichiana and broadleaf (Populus ciliata) forest. WC49 Mixed conifer broadleaf forest; Populus, Pinus, Picea, Tsuga, Oak. WC50 Tall conifer (P. wallichiana) forest with Pieris understorey. WC51 Mixed conifer/broadleaf (Pinus/Quercus) low forest. WC52 Tall broadleaf vine forest. WC53 Tall temperate broadleaf forest with Strobilanthes understorey WC54 Mixed temperate broadleaf forest. Semi-deciduous. WC55 Three year successional stage in Tseri slash and burn system. WC56 Two month old crop with Maize, Finger Millet and Foxtail Millet. WC57 Pure Maize crop. WC58 Deciduous Sal (Shorea robusta) forest. WC59 Secondary humid lowland semi-deciduous vine forest. Edge of the Douars plain. WC60 Seasonal low deciduous forest. Adenanthera, Acacia. WC61 Tall open, mixed successional forest. U’storey Chromolaena adenophorum. WC62 Tall temperate, mainly evergreen, humid broadleaf forest. For the 31 transects a total of 1113 vascular plant species was recorded. It is expected that further identification will reduce this total by about 15%. An example of species listing together with codes can be seen in Annex II, Table 1. We recorded 172 families, 463 unique genera and 481 unique PFTs. Totals of species, PFTs and a measure of Plant Functional Complexity (PFC) are listed in Table 4. Vegetation structural values are listed in Table 5. Photographs of each vegetation type can be seen in Annex III, Figures 1-18. A cross-section of biota photographed during the survey of Zone C is presented in Figure 7 below.
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Figure 7. Wangchhu biodiversity. (a) Terrestrial orchid Galeola lindleyana near Kemalakha 1550m (b) Rhododendron campylocarpum Chelela 2700m (c) Rhododendron cf. hodgsonii Chelela 2750m (d) Gonatanthus pumilis Baikunza 800m (e) Cyprinid fish Labeo dyocheilus Wangchhu river 220m (f) Woodpecker tree 1800m Gedu (g) Paris Peacock Achillides paris Jemichhu 220 (h) L-R Common Mormon Menelaides polytes, Six-bar Swordtail Pazala eurous, Glassy Bluebottle Idaides cloanthus Cluster at 240m on cow dung, Wangchhu riverside near Alam Thang.
a
g
f e
d c
b
h
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Table 4. Summary of species, PFTs and PFC
Transect Species PFTs Spp:PFT PFCWC32 98 72 1.36 358 WC33 52 41 1.27 222 WC34 76 58 1.31 292 WC35 54 44 1.23 280 WC36 40 30 1.33 198 WC37 81 56 1.45 294 WC38 66 44 1.50 282 WC39 59 44 1.34 232 WC40 65 44 1.48 264 WC41 57 47 1.21 230 WC42 10 10 1.00 82 WC43 38 31 1.23 146 WC44 26 22 1.18 126 WC45 38 24 1.58 160 WC46 32 23 1.39 144 WC47 38 29 1.31 192 WC48 41 34 1.21 230 WC49 43 30 1.43 192 WC50 35 27 1.30 192 WC51 44 35 1.26 196 WC52 46 37 1.24 238 WC53 46 37 1.24 228 WC54 47 39 1.21 226 WC55 46 37 1.24 254 WC56 28 24 1.17 162 WC57 26 24 1.08 146 WC58 46 42 1.10 268 WC59 63 47 1.34 240 WC60 23 22 1.05 172 WC61 51 41 1.24 266 WC62 40 29 1.38 158
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Table 5. Vegetation structural values *
Transect Ht CCTot CCWdy CCNwdy Bryo WPlts Litt BA MFI FICV WC32 10.00 98 95 3 8 7 2.00 11.330 61.00 50.36 WC33 40.00 92 75 17 6 8 0.01 34.000 51.00 54.41 WC34 30.00 99 90 9 8 8 8.00 30.000 52.30 49.54 WC35 18.00 95 92 3 8 6 3.00 24.000 55.75 57.11 WC36 19.00 99 98 1 9 5 3.00 24.670 4.50 447.21 WC37 3.00 99 90 9 8 4 5.00 2.670 63.00 73.30 WC38 2.80 99 90 9 9 5 2.50 1.000 99.00 3.11 WC39 2.50 99 95 4 9 5 2.00 1.330 100.00 0.00 WC40 2.00 99 85 14 8 3 2.00 1.000 95.50 21.07 WC41 0.40 85 10 75 1 2 0.01 0.100 93.50 21.47 WC42 0.15 75 0 75 0 0 0.00 0.000 0.00 0.00 WC43 0.60 92 10 82 2 2 0.10 0.100 99.40 2.27 WC44 1.00 90 0 90 0 1 0.00 0.000 0.00 0.00 WC45 19.00 90 80 10 4 8 3.00 18.67 50.90 95.60 WC46 32.00 90 85 5 7 9 5.00 26.67 57.65 84.57 WC47 17.00 85 75 10 5 6 2.50 20.67 34.75 139.85 WC48 17.00 95 90 5 6 4 3.00 20.67 30.00 156.72 WC49 30.00 95 90 5 6 8 8.00 18.67 36.00 127.26 WC50 38.00 90 85 5 6 6 0.00 36.67 14.90 244.24 WC51 18.00 85 75 10 3 6 5.00 24.67 29.75 156.76 WC52 17.00 98 95 3 7 4 10.00 36.67 54.25 49.43 WC53 20.00 98 95 3 8 8 7.00 28.67 51.50 42.39 WC54 17.00 98 95 3 7 4 7.00 30.67 46.00 59.07 WC55 1.00 99 75 24 2 9 2.00 1.00 100.00 0.00 WC56 0.80 85 5 80 1 1 0.50 0.01 0.00 0.00 WC57 1.80 90 0 90 1 0 0.20 0.00 0.00 0.00 WC58 15.00 80 75 5 5 5 5.00 31.33 34.00 57.57 WC59 13.00 98 90 8 3 8 3.00 14.67 57.95 51.58 WC60 9.00 95 80 15 2 9 2.00 10.00 46.00 74.78 WC61 15.00 98 95 3 6 9 2.00 6.67 71.65 34.27 WC62 19.00 98 96 2 7 8 1.00 19.33 49.50 69.67
* Ht = Mean canopy height (m); Cctot= Total canopy projective foliage cover percent; Ccwdy = projective
foliage cover percent of woody plants; CCNwdy, PFC of non-woody plants; Bryo = cover-abundance of bryophytes; Wplts = cover-abundance of woody plants <2m tall; Litt = plant litter depth (cm); BA = basal area of all woody plants (m2ha-1); MFI = mean furcation index; FICV = coefficient of variation percent of FI. (See also Annex II Table 3 for complete listing of site variables)
Due to the large number of unique PFTs, as with species, listing is restricted to an example in Annex II, Table 2. Species weighted PFEs (number of species per PFE in each transect) are listed in Table 6. below. Note: A maximum 36 generic PFEs (Annex II, Table 3) are used to construct PFTs as indicated in the methodological detail outlined in survey A. Again, due to size, only PFE values for the 18 transects from survey C are listed. Cover-abundance values for fruticose, crustose and foliose lichens and totals are listed in Table 7.
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Climate data as supplied by UW (H. Greenberg, M. Sonessa) are listed in Table 8. Values for ET and runoff are as used in a daily time step in the VIC (Variable Infiltration Capacity) hydrological model in use by the University of Washington. Annual ET and runoff values are being calculated separately (M. Sonessa, pers com.) for additional analyses.
Table 6 Plant Functional Elements (PFEs) listed for all 18 transects in lower Wangchhu*
P FE
WC 45
WC 46
WC 47
WC 48
WC 49
WC 50
WC 51
WC 52
WC 53
WC 54
WC 55
WC 56
WC 57
WC 58
WC 59
WC 60
WC 61
WC 62
pi 2 0 0 0 0 0 0 2 0 1 1 0 0 1 0 1 0 1 le 1 2 5 3 5 2 1 1 1 3 2 2 1 3 1 0 3 1 na 11 10 15 12 9 6 9 6 11 8 6 3 5 2 4 3 4 3 mi 20 13 11 18 22 22 22 14 4 10 10 13 9 4 11 8 10 6 no 5 6 3 6 4 7 10 15 15 16 10 8 3 10 15 3 11 7 me
1 0 4 4 3 0 2 6 14 5 14 1 5 23 27 5 16 23
pl 0 1 0 0 0 0 0 1 0 3 2 0 2 2 2 3 4 0 ma
0 0 0 0 0 0 1 1 1 1 0 1 1 1 3 0 1 0
mg
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0
ve 7 4 4 2 1 2 2 1 2 5 7 6 5 6 5 3 5 3 la 29 25 28 33 32 29 36 35 29 31 25 10 16 13 52 13 36 34 pe 0 1 0 2 1 1 0 5 4 1 3 2 1 13 2 3 9 2 co 4 2 6 6 9 5 7 5 11 10 10 10 4 14 4 4 1 2 do 37 32 36 41 41 35 44 45 46 47 44 28 26 46 63 23 51 41 is 3 0 2 2 2 2 1 1 0 0 0 0 0 0 0 0 0 0 de 1 6 19 21 28 17 29 3 3 9 9 2 0 7 5 5 6 1 ct 2 1 0 5 4 1 0 6 4 8 2 0 0 5 8 5 5 11 ac 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 ro 4 2 3 2 1 2 3 1 2 1 0 0 0 2 0 0 2 0 so 0 0 1 0 0 0 0 1 1 3 1 0 0 1 1 0 2 2 su 1 0 1 6 2 3 3 9 13 8 4 2 3 6 3 1 5 6 pv 1 1 4 2 1 3 4 3 4 3 5 7 3 9 4 2 2 1 fi 1 7 7 7 6 5 4 10 14 11 1 3 1 8 1 1 4 6 ph 4 5 2 10 5 6 2 8 7 11 3 0 0 6 10 6 6 12 ch 24 14 9 16 18 9 16 16 9 12 24 5 7 8 29 8 15 12 hc 8 11 24 16 17 19 23 18 29 23 12 16 13 28 18 8 22 15 cr 4 2 3 1 3 3 2 4 1 1 3 1 0 4 2 0 5 1 th 0 0 0 0 0 0 2 0 0 0 3 6 6 0 4 1 3 1 li 3 4 1 1 6 5 7 8 6 5 10 3 4 11 21 4 13 2 ad 10 12 23 19 21 23 29 31 36 32 17 19 14 23 20 9 29 18 ep 0 1 2 3 1 3 2 20 17 15 2 0 0 10 14 4 15 9 pa 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1
* Values are species-weighted (number of species per PFE) See Annex II Table 3 for detail. For WC32-44 values see previous report.
26
Table 7. Cover-abundance scores of lichens
Transect No. Fruticose Crustose Foliose Total WC32 2 1 3 6 WC33 2 2 2 6 WC34 2 2 1 5 WC35 0 2 0 2 WC36 2 2 1 5 WC37 1 3 3 7 WC38 0 2 0 2 WC39 0 2 1 3 WC40 0 0 0 0 WC41 0 0 0 0 WC42 0 0 0 0 WC43 0 0 0 0 WC44 0 0 0 0 WC45 6 2 4 12 WC46 4 2 7 13 WC47 6 2 6 14 WC48 2 4 5 11 WC49 1 4 3 8 WC50 3 4 6 13 WC51 4 2 5 11 WC52 1 5 1 7 WC53 0 4 1 5 WC54 0 7 1 8 WC55 0 2 0 2 WC56 0 1 0 1 WC57 0 2 0 2 WC58 0 6 2 8 WC59 0 6 1 7 WC60 0 5 0 5 WC61 0 7 2 9 WC62 0 6 1 7
In general, crustose lichen cover-abundance increases with exposure to sun and wind, while foliose and fruticose lichens increase with vegetation canopy cover. Note that Tseri group WC40-44 with zero lichen records
27
Table 8. Climate values for Lower Wangchhu*
Transect Min temp °C coldest month
Max temp °C
Precip. mm yr-1
Precip. cv%
ET mm day-1
Runoff mm yr-1
WC32 -3.1992 19.0750 3293.52 104.510 2.34772 1301.05 WC33 -3.0283 19.2365 3296.56 104.497 2.35708 1302.36 WC34 1.4797 23.3386 3407.02 104.022 2.59881 1340.88 WC35 -1.9260 20.1717 3354.03 104.264 2.39040 1344.17 WC36 -2.1350 19.9698 3353.16 104.269 2.38427 1344.26 WC37 1.2306 23.3016 3345.08 104.271 2.60311 1139.89 WC38 0.7640 22.8399 3345.37 104.274 2.57615 1188.50 WC39 1.2342 23.3150 3342.30 104.282 2.60274 1126.14 WC40 1.2252 23.3016 3343.58 104.277 2.60249 1133.20 WC41 1.2322 23.3065 3344.13 104.275 2.60300 1135.17 WC42 1.2351 23.3123 3343.31 104.278 2.60300 1130.92 WC43 1.2351 23.3123 3343.31 104.278 2.60300 1130.92 WC44 1.1418 23.2176 3344.02 104.276 2.59775 1143.70 WC45 -9.8951 15.1373 1917.83 110.957 1.64331 405.32 WC46 -10.6645 13.4266 2167.64 111.287 1.60105 511.80 WC47 -10.1287 14.0579 2372.44 108.762 1.74596 607.90 WC48 -11.8189 12.2913 2249.46 110.067 1.59174 555.93 WC49 -10.6306 13.3513 2209.71 110.978 1.64450 534.22 WC50 -10.3339 13.6739 2183.02 111.246 1.63087 522.08 WC51 -8.3086 15.3680 2791.67 106.635 1.92984 837.34 WC52 -5.6074 17.4770 3039.42 105.521 2.28056 953.59 WC53 -6.9039 15.8551 3140.34 105.114 2.18935 1014.48 WC54 -3.9844 18.5979 3197.99 104.864 2.28038 1128.81 WC55 5.0726 25.7815 3623.54 102.930 2.58431 1582.43 WC56 5.0292 25.7403 3622.96 102.933 2.58101 1582.06 WC57 5.0999 25.8108 3623.80 102.932 2.59036 1581.73 WC58 5.5472 26.2321 3629.64 102.903 2.61889 1586.64 WC59 7.4411 28.0419 3648.12 102.810 2.70600 1603.32 WC60 6.5672 27.2006 3640.88 102.847 2.67155 1596.94 WC61 4.4217 25.2283 3605.05 103.028 2.48908 1567.34 WC62 4.5389 25.6349 3569.81 103.272 2.40437 1535.34
* Supplied by H. Greenberg and M. Sonessa University of Washington Seattle
Standard statistical analyses show that the climate values listed above are not significantly correlated with species of PFT richness or PFC. On the other hand all climate values are significantly correlated with three aspects of vegetation structure (mean canopy height, basal area and bryophyte cover-abundance). Few PFTs are correlated with the climate data. When PFTs are disaggregated into their constituent PFEs there are a number of highly significant correlations between many PFEs and all four climate variables. Highest among these are plants with isobilateral leaves (photosynthetic tissue surrounding the entire leaf surface – as in many Pinus spp.) as well as deciduousness, liane richness and leaf size classes.
In the present example, (Fig. 8) the strong statistical relationship suggests that the pines Pinus wallichiana and Picea spinulosa (Pinaceae) both species with isoblateral leaves, closely follow an evapotranspiration gradient (also reflected by a high negative correlation (P< 0.0001) with temperature, rainfall and runoff and a positive correlation (P< 0.0001) with elevation and rainfall seasonality. This relationship is consistent with the known physiological characteristics of these two species that are associated with adaptation to increasing drought and rainfall seasonality.
Figure 8. Relationship between number of species possessing the isobilateral ‘IS’ PFE per transect. Closely related to the distribution of Pine species along a thermal and rainfall seasonality gradient Cluster analysis of the 31 transects applied to individual data sets of separate counts of plant genera and PFTs, vegetation structure, species-weighted PFEs and lichen cover-abundance generated a series of closely related dendrograms. While producing a number of outlying groups the classifications also indicated a general level of congruence particularly among the more mature and less disturbed forest assemblages such as those dominated by conifers. These patterns are displayed in the following figures (9,10,11,12).
The classification based on lichen cover-abundance (Fig. 12) clearly differentiates the key vegetation types and may indicate a novel approach to vegetation classifcation.
28
Figure 9. Classification based on counts of plant genera. Group (A) Disturbed, mainly evergreen broadleaf forest with successional stages. (B) Tall evergreen broadleaf forest (C) Tseri slash and burn sequences, Pakchika area (D) Buckwheat and padi rice (E) Lower elevation Tseri at Baikunza (F) Conifer forests with some deciduous broadleaf elements.
29
Figure 10. Classification based on vegetation structure (Table 5). Group (A) Mixed group of highly disturbed broadleaf evergreen forest and heavily disturbed conifer forest (WC45-46). (B) Late stage Tseri sequences Pakchika and Baikunza (C) Mostly conifer forests with one Alnus plantation (WC36). (D) Early Tseri stages and recent agricultural crops.
30
Figure 11. Classification based on Plant Functional Elements (PFEs) weighted by number of species with each PFE attribute per transect. Group (A) Highly disturbed broadleaf (mainly fagaceous) forest (WC32,34,37) and Tseri slash and burn succession at Pakchika (Bongo geog). (B) Mixed tall broadleaf forest including Sal (deciduous Shorea robusta forest WC58). (C) Conifer forests (D) Buckwheat crop (E) Agricultural crops (Maize, Millet) and outlier (WC60) forest on outwash plains with many weedy species.
31
Figure 12. Classification based solely on lichen cover-abundance. Group (A) Highly disturbed broadleaf forest including Alnus plantation (B) Semi-deciduous and deciduous (Sal) broadleaf forest including late stage Tseri (WC37) (C) Conifer forests (D) Mostly Tseri successional sequences (E) Early Tseri (WC40) and agricultural crops.
8. Discussion 8.1 Biodiversity pattern
32
As indicated by the preliminary statistical analyses, the distributional pattern of vegetation floristics, structure and functional types corresponds closely with a thermal and elevational gradient and related gradients of evapotranspiration, rainfall seasonality and runoff. While no conclusions can be drawn without a final analysis of the entire watershed survey, current trends fully support the underlying gradsect sampling strategy. It remains to be seen how these
33
patterns will be linked with soil properties and land management. To date biodiversity richness in zones B and C appears to be highest in those vegetation types impacted by intermediate levels of disturbance, thus supporting the ecologically well known ‘Intermediate Disturbance Hypothesis’. The close relationship between certain PFEs and climate variables especially runoff, has moved the outcome of this survey a step closer to identifying a quantifiable link between plant functional attributes and hydrological dynamics. The extent to which functional and other plant-based variables can contribute to hydrological modeling with VIC and DHSVM may become clearer with a final analysis of the Wangchhu watershed. Of particular ecological interest is the discovery that readily observable scores of lichen cover-abundance are of potential use as biodiversity indicators. Again, relative indicator value along the watershed will become clearer with the final analyses of the entire 62 transects. 8.2 Training and capacity enhancement The additional in-field training of two former trainees from NBC and CoRRB led to significant improvements in recording consistency. This is evident from the close statistical correlation between recorded species and PFTs (P< 0.0001). A subjective assessment of performance of these and other trainees included in the previous surveys indicates a clear capacity to design and implement similar gradient-based, integrated biodiversity surveys in Bhutan. 9. Acknowledgements The detailed preparation for this survey undertaken by the Program Director and staff of NSSC /SLMP is gratefully acknowledged. The Program Director of NBC (Dr Tashi Yangzome Dorji) and Dr Pema Wangda (RNR-RC, CoRRB) also kindly supported the survey with botanical and ecological personnel respectively. Prof. J. Richey, H. Greenberg and M. Sonessa from the University of Washington also kindly provided climate data for the numerical analyses.
Annex I (not included here)
Annex II
Table 1. Sample page of tentative species recorded for Zone C 18 transects
34
Family, Genus, Species, Code
W C 4 5
W C 4 6
W C 4 7
W C 4 8
W C 4 9
W C 5 0
W C 5 1
W C 5 2
W C 5 3
W C 5 4
W C 5 5
W C 5 6
W C 5 7
W C 5 8
W C 5 9
W C 6 0
W C 6 1
W C 6 2
Acanthaceae sp31 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Acanthaceae sp32 SP32 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Acanthaceae Strobilanthes multidens STROBMULT 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Aceraceae Acer sp44 ACERSP44 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Aceraceae Acer? sp30 ACERSP30 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Adiantaceae Monachosorum henryi MONAHENR 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 Adiantaceae Pteris biaurita? PTERBIAU 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Adiantaceae Pteris cretica PTERCRET 0 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 0 0 Amaranthaceae sp12 SP12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 Amaranthaceae Amaranthus lividus AMARLIVI 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Amaranthaceae Amaranthus sp13 AMARSP13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 Amaranthaceae Amaranthus sp39 AMARSP39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Amaranthaceae? sp28 SP28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Amaranthaceae? sp30 SP30 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Anacardiaceae Buchanania? sp11 BUCHSP11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Anacardiaceae Buchanania? sp34 BUCHSP34 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Anacardiaceae Rhus taitensis? RHUSTAIT 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 Anacardiaceae Spondias sp37 SPONSP37 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 Anacardiaceae? sp44 SP44 'ITCHY TREE' 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 Apiaceae sp14 SP14 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Apiaceae Acronema sp20 ACROSP20 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Apiaceae Heracleum sp11 HERASP11 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Apiaceae Heracleum sp35 HERASP35 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Apocynaceae sp12 SP12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Apocynaceae sp24 SP24 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Apocynaceae sp54 SP54 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Apocynaceae Ervatamia sp21 ERVASP21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Apocynaceae Parsonsia? sp18 PARSSP18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
Table 2. Sample page of unique Plant Functional Types (PFTs) listed in alphabectical order for Zone C *
PFT W C 45
W C 46
W C 47
W C 48
W C 49
W C 50
W C 51
W C 52
W C 53
W C 54
W C 55
W C 56
W C 57
W C 58
W C 59
W C 60
W C 61
W C 62
le-la-do-fi-hc-ad 1 2 1 1 0 2 0 1 1 2 1 1 1 1 0 0 1 0 me-ve-do-ch 1 0 0 0 0 0 0 0 0 0 1 0 1 2 1 0 0 0 mi-co-do-ph 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mi-la-do-ch 9 7 4 2 5 4 2 2 0 0 1 2 1 0 3 1 0 0 mi-la-do-ch-li 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mi-la-do-ct-ch 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mi-la-do-ct-ph 1 0 0 2 1 0 0 0 0 0 0 0 0 0 1 1 0 1 mi-la-do-hc-ad 1 1 2 2 0 0 0 1 1 2 0 1 2 0 1 1 2 0 mi-la-do-hc-li 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mi-la-do-ph 0 1 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 mi-la-do-ro-cr 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mi-ve-do-de-su-cr 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 mi-ve-do-hc-ad 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-co-do-ch 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-co-do-pv-hc-ad 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 na-co-is-ph 1 0 1 1 0 2 1 0 0 0 0 0 0 0 0 0 0 0 na-la-do-ch 3 0 0 3 3 0 1 0 0 1 1 0 0 0 1 1 0 0 na-la-do-ch-ad 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-la-do-ch-li 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 na-la-do-de-hc 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-la-do-hc-ad 1 1 2 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 na-la-do-ro-hc-ad 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-ve-do-pv-hc-ad 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 na-ve-do-ro-cr-ad 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 no-la-do-ch 3 3 0 0 0 0 3 1 0 3 3 0 1 1 1 0 0 1 no-la-do-ph 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 no-la-do-ro-cr 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 no-pe-do-ch-li 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 pi-ve-is-ch 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
35
* Total of 319 unique PFTs listed for transects WC45-62. Values are species-weighted (number of species with a specific PFT). For WC32-44 values see previous report.
Table 3. List of data variables recorded for each 40x5m transect
Site feature Descriptor Data type Location reference Location Alpha-numeric Date (dd-mm-year) Alpha-numeric Plot number (unique) Alpha-numeric Country Text Observer/s Observer/s by name Text Physical Latitude deg.min.sec. (GPS) Alpha-numeric Longitude deg.min.sec. (GPS) Alpha-numeric Elevation (m.a.s.l.) (aneroid or GPS) Numeric Aspect (compass. deg.) (perpendicular to plot) Numeric Slope percent (perpendicular to plot) Numeric Soil depth (cm) Numeric Soil type (US Soil taxonomy) Text Parent rock type Text Litter depth (cm) Numeric Terrain position Text Site history General description and land-use / landscape
context Text
Vegetation structure Vegetation type Text Mean canopy height (m) Numeric Crown cover percent (total) Numeric Crown cover percent (woody) Numeric Crown cover percent (non-woody) Numeric Cover-abundance (Domin) - bryophytes Numeric Cover-abundance woody plants < 2m tall Numeric Cover-abundance Fruticose lichens Numeric Cover-abundance Crustose lichens Numeric Cover-abundance Foliose lichens Numeric Basal area (mean of 3) (m2ha-1); Numeric Furcation index (mean and cv % of 20) Numeric Profile sketch of 40x5m plot (scannable) Digital Plant taxa Family Text* Genus Text* Species Text* Botanical authority Text* If exotic (binary, presence-absence) # Numeric Plant Functional Type Plant functional elements combined
according to published rule set. Text*
Quadrat listing Unique taxa and PFTs per quadrat (for each of 8 (5x5m) quadrats) #
Numeric
Photograph Hard copy and digital image # JPEG
* Where identified, usually with voucher specimens. More detailed information available at www.cbmglobe.org
36
37
Annex III
Photographic records of Zone C vegetation types
List of figures
Figure 1. WC45 Paro side of Chelela. Managed conifer forest. Pinus wallichiana, Picea spinulosa. Pieris formosa and Quercus semecarpifolia understorey (37 spp, 24 PFT). 2688
Figure 2. WC46. Near Jyenkana, Haa valley. Managed conifer forest. Pinus wallichiana, Picea spinulosa. Shrubby understorey of Lyonia villosa, Pieris formosa and Daphne bholua (32 spp, 23 PFT) 2705m.
Figure 3. WC47. 20 K S. of Susuna, Haa valley.Conifer forest of Pinus wallichiana with understorey of Berberis sp. Lyonia villosa and Rosa sericea. (38 spp. 29 PFT) 2634m
Figure 4. WC48. Near Nago, Haa valley. Conifer-Broadleaf forest Pinus wallichiana, Picea spinulosa, Populus ciliata with understorey of Rosa sericea, Lyonia villosa and Berberis praecipua. (41 spp., 34 PFT) 2755m.
Figure 5. WC49. 10 K. E. of Jyenkana. Mixed conifer-broadleaf forest. Pinus wallicihiana, Picea spinulosa, Tsuga dumosa, Populus ciliata, Salix spp. Understorey with Rosa sericea, Berberis praecipua Daphne bholua. (42 spp. 30 PFT) 2739m.
Figure 6. WC50. Near Jyenkana, Haa valley. Tall conifer forest Pinus wallichiana, Picea spinulosa with understorey of Quercus semecarpifolia, Berberis spp., Daphne bholua and Lyonia villosa. (35 spp. 27 PFT) 2592m
Figure 7. WC51. Near Chapcha. Mainly conifer (Pinus wallichiana) forest with Oak (Quercus lanata) and understorey of Rhododendron arboreum, Berberis praecipua, Rosa brunonia and Lyonia villosa. (44 spp. 35 PFT) 2363m.
Figure 8. WC52. Above Tashi Gatshel. Tall semi-deciduous broadleaf forest. Quercus lamellosa, Euphorbiaceae. Understorey of Viburnum sp., Daphne bholua and Symplocos aff. nepalensis. (45 spp. 37 PFT) 2221m.
Figure 9. WC53. 1 K N of Taktikoti. Tall, semi-deciduous broadleaf forest. Castanopsis sp., Quercus lamellosa, Symplocos lucida with Strobilanthes dominated understorey. Numerous ferns (46 spp. 37 PFT) 2023m.
Figure 10. WC54. 2km E. of Chasilaka. Mixed semi-deciduous broadleaf forest dominated by Castanopsis sp., Juglans regia, Acer sp., Persea fructifera, Araliaceae. Understorey with Symplocos lucida, Maytenus rufa. Numerous ferns. (47 spp. 39 PFT) 2023m
Figure 11. WC55. Baikunza. Three-year old slash and burn ‘Tseri’ at Baikunza. Artemisia vulgaris dominant. Emergent Ostodes paniculata, Mallotus philippensis, Glochidion sp. Many Dioscorea spp. (46 spp. 37 PFT) 881m.
Figure 12. WC56. Baikunza. Two month old mixed crop of Maize (Zea mays), Finger millet (Eleusine coracana) and Foxtail millet (Setaria italica) (28 spp. 24 PFT) 879m.
Figure 13. WC57. Three month old pure Maize (Zea mays) crop. Baikunza. (28 spp. 24 PFT) 767m Figure 14. WC58. Sal (Shorea robusta) deciduous forest. Amsepho. Herbaceous understorey (Curculigo,
Hedychium, Kyllinga, Dioscorea spp. Fabaceae) (46 spp. 42 PFT) 681m. Figure 15. WC59. Tall semi-deciduous vine forest. Jemichu. Lower Wangchhu floodplain. Pterospermum sp.,
Adenanthera pavonina. Understorey of Murraya koenigii, Bauhinia purpurea, Mallotus philippensis, Ervatamia sp. Numerous lianes. (63 spp. 47 PFT) 222m
Figure 16. WC60. Alamthang – lower Wangchhu floodplain. Heavily grazed, dry deciduous low, weedy, forest dominated mostly by Adenathera pavonina, Bombax ceiba and Acacia sp. (23 spp. 22 PFT) 237m.
Figure 17. WC61. Jemi Thang. Tall mostly evergreen riparian forest dominated by Duabanga grandiflora. Understorey Maesa chisia, Clerodendrum paniculatum, Adenanthera sp., Murraya koenigii, Leea sp. Mussaenda. Numerous lianes, succulent aroids (Amorphophallus, Colocasia) (51 spp. 41 PFT) 340m.
Figure 18. WC62. Between Kemalakha and Chargarey. Tall mixed, broadleaved, mainly evergreen forest with dominant Alcimandra cathcartii, Castanopsis sp., Litsea sp. Understorey with Ardisia sp., Ostodes paniculata, Daphniphyllum, Casearia glomerata, Melastoma sp., Daphne bholua. (40 spp. 29 PFT) 1540m.
Figure 1. WC45 Paro side of Chelela. Managed conifer forest. Pinus wallichiana, Picea spinulosa. Pieris formosa and Quercus semecarpifolia understorey (37 spp, 24 PFT). 2688m.
38
Figure 2. WC46. Near Jyenkana, Haa valley. Managed conifer forest. Pinus wallichiana, Picea spinulosa. Shrubby understorey of Lyonia villosa, Pieris formosa and Daphne bholua (32 spp, 23 PFT) 2705m.
Figure 3. WC47. 20 K S. of Susuna, Haa valley.Conifer forest of Pinus wallichiana with understorey of Berberis sp. Lyonia villosa and Rosa sericea. (38 spp. 29 PFT) 2634m.
Figure 4. WC48. Near Nago, Haa valley. Conifer-Broadleaf forest Pinus wallichiana, Picea spinulosa, Populus ciliata with understorey of Rosa sericea, Lyonia villosa and Berberis praecipua. (41 spp., 34 PFT) 2755m.
39
Figure 5. WC49. 10 K. E. of Jyenkana. Mixed conifer-broadleaf forest. Pinus wallicihiana, Picea spinulosa, Tsuga dumosa, Populus ciliata, Salix spp. Understorey with Rosa sericea, Berberis praecipua Daphne bholua. (42 spp. 30 PFT) 2739m.
Figure 6. WC50. Near Jyenkana, Haa valley. Tall conifer forest Pinus wallichiana, Picea spinulosa with understorey of Quercus semecarpifolia, Berberis spp., Daphne bholua and Lyonia villosa. (35 spp. 27 PFT) 2592m.
40
Figure 7. WC51. Near Chapcha. Mainly conifer (Pinus wallichiana) forest with Oak (Quercus lanata) and understorey of Rhododendron arboreum, Berberis praecipua, Rosa brunonia and Lyonia villosa. (44 spp. 35 PFT) 2363m.
Figure 8. WC52. Above Tashi Gatshel. Tall semi-deciduous broadleaf forest. Quercus lamellosa, Euphorbiaceae. Understorey of Viburnum sp., Daphne bholua and Symplocos aff. nepalensis. (45 spp. 37 PFT) 2221m.
41
Figure 9. WC53. 1 K N of Taktikoti. Tall, semi-deciduous broadleaf forest. Castanopsis sp., Quercus lamellosa, Symplocos lucida with Strobilanthes dominated understorey. Numerous ferns (46 spp. 37 PFT) 2023m.
Figure 10. WC54. 2km E. of Chasilaka. Mixed semi-deciduous broadleaf forest dominated by Castanopsis sp., Juglans regia, Acer sp., Persea fructifera, Araliaceae. Understorey with Symplocos lucida, Maytenus rufa. Numerous ferns. (47 spp. 39 PFT) 2023m.
42
Figure 11. WC55. Baikunza. Three-year old slash and burn ‘Tseri’ at Baikunza. Artemisia vulgaris dominant. Emergent Ostodes paniculata, Mallotus philippensis, Glochidion sp. Many Dioscorea spp. (46 spp. 37 PFT) 881m.
Figure 12. WC56. Baikunza. Two month old mixed crop of Maize (Zea mays), Finger millet (Eleusine coracana) and Foxtail millet (Setaria italica) (28 spp. 24 PFT) 879m.
43
Figure 13. WC57. Three month old pure Maize (Zea mays) crop. Baikunza. (28 spp. 24 PFT) 767m
Figure 14. WC58. Sal (Shorea robusta) deciduous forest. Amsepho. Herbaceous understorey (Curculigo, Hedychium, Kyllinga, Dioscorea spp. Fabaceae) (46 spp. 42 PFT) 681m.
44
Figure 15. WC59. Tall semi-deciduous vine forest. Jemichu. Lower Wangchhu floodplain. Pterospermum sp., Adenanthera pavonina. Understorey of Murraya koenigii, Bauhinia purpurea, Mallotus philippensis, Ervatamia sp. Numerous lianes. (63 spp. 47 PFT) 222m.
Figure 16. WC60. Alamthang – lower Wangchhu floodplain. Heavily grazed, dry deciduous low, weedy, forest dominated mostly by Adenathera pavonina, Bombax ceiba and Acacia sp. (23 spp. 22 PFT) 237m.
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Figure 17. WC61. Jemi Thang. Tall mostly evergreen riparian forest dominated by Duabanga grandiflora. Understorey Maesa chisia, Clerodendrum paniculatum, Adenanthera sp., Murraya koenigii, Leea sp. Mussaenda. Numerous lianes, succulent aroids (Amorphophallus, Colocasia) (51 spp. 41 PFT) 340m.
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Figure 18. WC62. Between Kemalakha and Chargarey. Tall mixed, broadleaved, mainly evergreen forest with dominant Alcimandra cathcartii, Castanopsis sp., Litsea sp. Understorey with Ardisia sp., Ostodes paniculata, Daphniphyllum, Casearia glomerata, Melastoma sp., Daphne bholua. (40 spp. 29 PFT) 1540m.
