C.A.P.E. Fine-Scale Systematic Conservation Planning Assessment:

Technical Report

November 2008 Genevieve Q.K. Pence

Produced for

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C.A.P.E. Fine-Scale Systematic Conservation Planning Assessment:

Technical Report

November 2008 Genevieve Q.K. Pence

CITATION: Pence, Genevieve Q.K. 2008. C.A.P.E. Fine-Scale Systematic Conservation Planning Assessment: Technical Report. Produced for CapeNature as part of the GEF-funded C.A.P.E. Fine-Scale Biodiversity Planning Project. Cape Town, South Africa. CRITICAL BIODIVERSITY AREAS MAPS (PER MUNICIPALITY) AND GIS DATA AVAILABLE FROM: Biodiversity GIS (BGIS), South African National Biodiversity Institute, Tel. +27 21 799 8739 or CapeNature, Tel. +27 21 866 8000. Or on the web at: http://bgis.sanbi.org/fsp/project.asp FOR ADDITIONAL INFORMATION CONTACT: Scientific Services, CapeNature, Tel. +27 21 866 8000.

The author gratefully acknowledges the following people for their contributions: Kerry te Roller, Tracy Timmins, Therese Forsyth, Nick Helme, Nancy Job, Jeanne Nel, Kate Snaddon, Mark Thompson, Jan Vlok, Julian Conrad, all members of the FSP Task Team, and all workshop participants.

OTHER C.A.P.E. FINE-SCALE BIODIVERSITY PLANNING PRODUCTS INCLUDE: Conrad, J., and Z. Munch, 2006. Groundwater Assessment of the North-West Sandveld and Saldanha

Peninsula as an Integral Component of the Component 5.1, C.A.P.E. Fine-Scale Biodiversity Planning Project. Consultancy Report submitted by GEOSS to CapeNature. November 2006. Cape Town, South Africa.

Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Saldanha - Sandveld planning domain. Report submitted to CapeNature, November 2008, 52 pp + appendices. Cape Town, South Africa.

Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008b. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Riversdale Coastal Plain planning domain. Report submitted to CapeNature, November 2008, 71 pp + appendices. Cape Town, South Africa.

Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008c. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Upper Breede River Valley planning domain. Report submitted to CapeNature, November 2008, 32 pp + appendices. Cape Town, South Africa.

Helme, N. A. and R. Koopman. 2007. Botanical report: Fine-scale vegetation mapping in the Saldanha Peninsula. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

Helme, N. A. 2007. Botanical report: Fine-scale vegetation mapping in the Northwest Sandveld. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

Helme, N. A. 2007b. Botanical report: Fine-scale vegetation mapping of the Bokkeveld Escarpment. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

Helme, N. A. 2007c. Botanical report: Fine-scale vegetation mapping in the Upper Breede River Valley. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

Snaddon, C.D., Job, N., Nel, J., Smith-Adao, L and Day, L. 2008. C.A.P.E. fine-scale planning project: surface freshwater ecosystems. Methodology Report. Report submitted to CapeNature, November 2008, 42 pp + appendices. Cape Town, South Africa.

Thompson, M. 2007. CapeNature Fine-scale Conservation Project: Land cover classifications from SPOT 5 satellite imagery. End Users Summary Report and Metadata. Produced by GeoTerraImage (GTI) Pty Lty for CapeNature as part of the C.A.P.E. Fine-Scale Biodiversity Planning Project. October 2007. Pretoria, South Africa.

Vlok, J.H.J. and de Villiers, M.E. 2007. A vegetation map for the Riversdale Coastal Plain. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

Vromans D.C. and te Roller K.S. 2009 (in prep). The Biodiversity Sector Plan for Saldanha Bay, Bergrivier, Cederberg and Matzikama Municipalities. Supporting land-use planning and decision-making in Critical Biodiversity Areas and Ecological Support Areas for sustainable development. Produced by CapeNature as part of the C.A.P.E. Fine-scale Biodiversity Planning Project. Cape Town, South Africa.

Vromans D.C. and te Roller K.S. 2009b (in prep). The Biodiversity Sector Plan for Witzenberg, Breede Valley and Breede River Winelands Municipalities. Supporting land-use planning and decision-making in Critical Biodiversity Areas and Ecological Support Areas for sustainable development. Produced by CapeNature as part of the C.A.P.E. Fine-scale Biodiversity Planning Project. Cape Town, South Africa.

Vromans D.C. and te Roller K.S. 2009c (in prep). The Biodiversity Sector Plan for Hessequa and Mossel Bay Municipalities. Supporting land-use planning and decision-making in Critical Biodiversity Areas and Ecological Support Areas for sustainable development. Produced by CapeNature as part of the C.A.P.E. Fine-scale Biodiversity Planning Project. Cape Town, South Africa.

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TABLE OF CONTENTS INTRODUCTION .......................................................................................................................................................5

Systematic Conservation Planning ...................................................................................................................6 METHODOLOGY ......................................................................................................................................................7

Overview of the FSP Conservation Assessment ...........................................................................................7 Inputs ...................................................................................................................................................................9

Planning Domains & Product Coverages...................................................................................................9 Biodiversity Surrogates................................................................................................................................11 Biodiversity Pattern .....................................................................................................................................13

Vegetation Types .....................................................................................................................................13 Critically Endangered and Endangered Ecosystem Remnants.........................................................15 Wetland Groups ......................................................................................................................................17 River Types...............................................................................................................................................18 Indigenous Fish Species .........................................................................................................................19 Indigenous Forest Patches .....................................................................................................................19 Red Data List Plant Taxa .......................................................................................................................21 Restricted Plant Taxa ..............................................................................................................................22 Focal Animal Species ..............................................................................................................................23 Special Habitats or Features...................................................................................................................25

Biodiversity Process.....................................................................................................................................25 Coastal Corridor ......................................................................................................................................25 Significant Wetland Clusters ..................................................................................................................26 Wetland and River Buffers.....................................................................................................................26 Sub-catchments........................................................................................................................................27 Edaphic Interfaces...................................................................................................................................27 Upland-Lowland Interfaces and Gradients .........................................................................................28 Regional Corridors ..................................................................................................................................29 Key Landscape Linkages & Habitat Connectivity (fine-scale corridors) ........................................30

Status Information .......................................................................................................................................31 Landcover .................................................................................................................................................31 Protected Areas........................................................................................................................................34 Ecosystem Status .....................................................................................................................................35

Analysis ..............................................................................................................................................................37 Software.........................................................................................................................................................37 Planning Units ..............................................................................................................................................37 Initial Conditions .........................................................................................................................................39 Cost Calculations..........................................................................................................................................40 Feature Abundance......................................................................................................................................41 Targets ...........................................................................................................................................................41 Pattern within Process.................................................................................................................................45 Iterative Design ............................................................................................................................................46

CBA Map Product Development...................................................................................................................48 Establishing Map Categories ......................................................................................................................48 Stakeholder Review and Finalizing Critical Biodiversity Areas.............................................................49

SUMMARY OF RESULTS..........................................................................................................................................51 REFERENCES ..........................................................................................................................................................53

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INTRODUCTION The Fine-Scale Biodiversity Planning (FSP) project led by CapeNature in partnership with the South African National Biodiversity Institute (SANBI), is part of the C.A.P.E. (Cape Action for People and the Environment) programme and is funded through the Global Environmental Facility. The project will produce biodiversity plans for five broad conservation priority areas (North-West Sandveld, Saldanha Peninsula, Nieuwoudtville, Upper Breede River Valley and Riversdale Plain; Figure 2), covering nine local municipalities (Matzikama, Cederberg, Bergrivier, Saldanha Bay, Witzenberg, Breede Valley, Breede River Winelands, Hessequa (previously Langeberg) and Mossel Bay; Figure 3), and a portion of the Hantam Municipality, in the Cape Floristic Region.

This report addresses the conservation planning component of the Fine-Scale Biodiversity Planning (FSP) project, the purpose of which was to carry out the analysis and production of conservation plans for all nine municipalities listed above. The primary tasks included: ♦ Co-ordinating data inputs from various consultants. ♦ Deriving a systematic conservation planning method applicable in all five areas, and which

integrates freshwater and terrestrial components. ♦ Undertaking fine-scale systematic conservation planning to identify:

- Areas of biodiversity significance (vis a vis Critical Biodiversity Areas) that should be flagged for land-use planning and decision-making purposes; and

- A subset of those areas that are priorities for proactive action by conservation agencies and NGOs; particularly, a limited number of areas that should be the focus of immediate action by CapeNature’s Stewardship programme.

♦ Producing a separate Critical Biodiversity Areas Map for each municipality. Other components of the FSP project include:

• Landcover Mapping (Thompson, 2007.

• Vegetation Mapping (Helme & Koopman, 2007; Helme, 2007a, b, c.; Vlok & de Villiers, 2007)

• Freshwater Mapping & Conservation Assessment (Snaddon et al., 2008; Job et al., 2008a, b, c)

• Groundwater Mapping & Assessment (Conrad & Munch, 2006)

• Landuse Guidelines (Vorman & te Roller, 2009a, b, c) It is useful to understand that the FSP project constitutes one sub-component of the broader CAPE programme, namely Component 5.1 (the undertaking of fine-scale biodiversity planning in five priority areas), which will support the activities of Components 5.2 and 5.3 (integrating biodiversity into land-use decision-making, and increasing landowners commitment to conservation, respectively). The intention is that Components 5.2 and 5.3 will provide mechanisms and enhanced capacity for implementing fine-scale planning, both in terms of this project and beyond. Thus, the focus of the FSP project is on the technical and practical production of biodiversity planning products, not the implementation thereof. The purpose of this Report is to present the methodology used to produce the Critical Biodiversity Areas Maps for the FSP project. The actual methods used varied between planning domains depending on available data and, importantly, as we learned from, and adapted to, issues concerning scale and content. In each methodology section, the ‘best’ of these approaches is first presented and then variations or alternatives are described (see “Alternative Method or Variation” subheadings), where applicable.

The aim is for these plans to guide the implementation of conservation action, to direct land-use planning and decision-making by government bodies,

and to influence agricultural practices.

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Systematic Conservation Planning

Given the increasing number of people on the planet, and their demands on natural resources, it is essential that conservation efforts be strategic, efficient, and mainstreamed. Priority areas for both production and protection must be identified and ultimately reflected in our daily decisions surrounding land- and resource-use. Conservation planning helps direct and focus conservation action by setting clear goals and identifying the most effective places and means for protection. Because of its basis in sound biodiversity science and it’s internationally recognized principles, methodologies and techniques, systematic conservation planning (also known as systematic biodiversity planning) has become the standard approach to biodiversity planning in South Africa.1 The following excerpt from the Norms and Standards for Publishing Bioregional Plans (SANBI Draft, 2006) highlights its key characteristics:

• “The principle of representation. The plan identifies areas needed to conserve a representative sample of all biodiversity patterns [species, communities, ecosystems, etc.].

• The principle of persistence. The plan identifies areas needed to maintain ecological and evolutionary processes that allow biodiversity to persist in the long term.

• Biodiversity targets. Targets are set for biodiversity features, indicating how much of each feature is required in order to conserve a representative sample of biodiversity pattern and key ecological processes.

• Efficiency and conflict avoidance. The configuration of priority areas identified in the plan is designed to be spatially efficient (i.e. to meet biodiversity targets as efficiently as possible in terms of the amount of land required) and to avoid conflict with other land uses where these are known to exist.”

The term secured its place in the conservation biology literature in a paper titled “Systematic Conservation Planning” published in Nature in 2000 by Margules and Pressey2. They provided a general framework for systematic conservation planning, suggesting a process of six stages:

1. Compile data on the biodiversity of the planning region [identify surrogates and collate information]

2. Identify conservation goals for the planning region [formulate quantitative targets for features, set design criteria, state qualitative goals]

3. Review existing conservation areas [measure the extent to which targets have been met in existing reserves]

4. Select additional conservation areas [locate and design a system of new conservation areas to achieve remaining targets; options for doing this include reserve selection algorithms or decision-support software]

5. Implement conservation actions 6. Maintain the required values of conservation areas

The FSP project has worked and innovated within this basic systematic conservation planning framework (stages 1-4) to generate products that are: ♦ defensible – in terms of using “good” science and data, ♦ palatable – propose a well designed and not overly land-hungry network of biodiversity areas, and ♦ simple – at a glance give an indication of the places where we need to, at least, have restrictions in

place to ensure biodiversity-compatible development, versus where we can be less restrictive.

1 Department of Environmental Affairs and Tourism. 2007. Guideline regarding the Determination of Bioregions and the Preparation and Publication of Bioregional Plans. Notice 1112 of 2007. Published in terms of the National Environmental Management: Biodiversity Act, 2004 (Act No. 10 of 2004). Government Printer, Cape Town. 2 Margules, C.R., Pressey, R.L., 2000. Systematic conservation planning. Nature 405, 243–253.

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METHODOLOGY

Overview of the FSP Conservation Assessment

We followed the general framework outlined above and adhered to the principles of systematic conservation planning, yet within the technical details we innovated to address project-specific challenges, such as: ♦ working at a fine-scale (1:10 000) across a large area (4.6 million hectares and nine municipalities); ♦ working in a species-rich, spatially heterogeneous, and highly fragmented landscape; ♦ working in Critically Endangered and Endangered ecosystems which, by definition, can no longer,

or can only marginally, meet their National targets (for representing biodiversity pattern); ♦ producing an integrated plan for conserving aquatic and terrestrial biodiversity patterns and

processes; ♦ producing a product appropriate for informing site-specific decision-making and local land-use

planning (in contrast to an optimized reserve design exercise or a protected area expansion plan); and which is compatible with the legal and legislative mechanisms that will give the plans life beyond the FSP project. For example, the Publishing of Bioregional Plans, Area-Wide Planning (a tool used by the Department of Agriculture), National Biodiversity Offsets Policy, the National Listing of Threatened Ecosystems, Environmental Management Frameworks, Spatial Development Frameworks, etc.

The details of our methodology, including how we addressed these issues, are presented in the following sections. Each section outlines a key step (a through n below) within the overall conservation assessment, consisting of three broad phases (also see Figure 1 below):

1. Data inputs: collection and preparation a. Defining planning domains and product coverages b. Identifying appropriate biodiversity surrogates c. Mapping biodiversity pattern

- Vegetation types - Threatened (CR & EN) remnants - Wetland groups - River types - Indigenous fish species

- Indigenous forest patches - Red Data List plant taxa - Restricted plant taxa - Focal animal species - Special habitats or features

d. Mapping biodiversity process - Coastal corridor - Significant wetland clusters - Wetland & river buffers - Sub-catchments - Edaphic interfaces

- Upland-lowland interfaces & gradients - Regional (macro-scale) corridors - Key landscape linkages & habitat

connectivity (fine-scale corridors)

e. Collating or creating data to assess the current status of biodiversity features - Landcover (to determine current extent and location of features) - Existing protected areas (to determine the contributions thereof) - Updated Ecosystem Status information

2. Data analysis f. Defining selection units g. Determining starting conditions h. Creating cost surfaces i. Calculating feature abundance j. Setting targets k. Evaluating pattern targets within process areas l. Iterative design to meet remaining targets

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3. CBA Map Product development m. Establishing map categories n. Stakeholder review of draft Critical Biodiversity Areas

Summary of Methodology For each of the five priority areas, a planning domain was established based on ecological characteristics and administrative requirements. Each planning domain was then divided into planning units defined by summarized landcover data, wetlands, and protected areas, via eCognition software (which divides an image into objects according a set of parameters having to do with the size, shape, and characteristics of groups of pixels). Planning units averaged 10 ha in size, and ranged from about 0.10 ha to 550 ha. Features representing the broad array of biodiversity elements present in the planning domain were determined and mapped in a Geographic Information System (see list of pattern and process features above; c & d). Where possible, the abundance (amount of) each biodiversity feature in each planning unit was calculated. An overall conservation target (the desired quantity to be maintained in a natural state in the long term, based on national targets, guidelines, or regulations) was established for each feature (e.g., 24% of the original extent of the vegetation type), or an overall design objective was stated (e.g., where there are options, choose corridors which connect uplands and lowlands, follow a macroclimatic gradient, form a riverine corridor, etc.). Those planning units falling within statutory Protected Areas were noted as “Conserved” and thus their contributions to targets accounted for at the outset. All 100% urban (as per FSP landcover data) planning units were excluded from analysis. All planning units containing a feature (or a portion thereof) with a target of 100% (e.g., all rank 1 wetlands, river reaches identified in the river analysis*, known habitat for a locally endemic and threatened plant species) were “Earmarked” for inclusion as Critical Biodiversity Areas (CBAs). *A separate analysis was conducted for rivers (see Snaddon et al., 2008), using sub-catchments as planning units and including features such as river types and indigenous fish species. The results were integrated into this assessment both directly (by earmarking priority river reaches) and indirectly (by creating a cost surface to preferentially select units for meeting terrestrial targets in priority sub-catchments, as well as setting a target for each priority sub-catchment). The conservation planning support software Marxan was then used (via CLUZ interface software) to generate the best spatial solutions (i.e., most efficient selection of planning units required) for meeting all remaining conservation targets. At first, the only planning units recognized as “available” for meeting targets were those within ecological process areas. The most frequently selected of these units (as per their summed selection score) formed the foundation of the CBA network and informed the design of fine-scale corridors. In other words, at the foundation of the CBA network are sites required for meeting both pattern and process targets/objectives, as well as key landscape linkages. The final CBA network was then developed in an iterative fashion, building on the foundation, whereby Marxan was run and re-run as high-scoring units were selected to meet targets. The draft results were then presented at stakeholder workshops held for each planning domain. All stakeholder feedback was reviewed and edits made where appropriate.

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Figure 1. Overview of a typical systematic conservation planning assessment.

Inputs

Planning Domains & Product Coverages

A separate planning domain was established for each of the priority areas originally identified by CAPE3, yet not already addressed by other fine-scale planning initiatives (i.e., the Lowland Renosterveld Project, the Agulhas Plain Fine-Scale Plan, and the City of Cape Town Biodiversity Network). The planning domains were primarily defined by ecological boundaries and characteristics (e.g., threatened lowland ecosystems, river systems, and biogeography), and can also be thought of as bioregions, in terms of the NEM: Biodiversity Act (Act 10, 2004). Wherever these ecological systems stopped short of municipal boundaries, however, the planning domain was extended to encompass the entire municipality of interest. This created more useful and effective areas for products which are ultimately intended to guide land-use decision-making and resource management – regulatory functions whose geography is more political and administrative than ecological. Such “functional” planning areas are described in the Guideline regarding the Preparation and Publishing of Bioregional Plans (DEAT, Notice 1112 of 2007), which this project strove to adhere to. Note that while the assessments were focused on areas that make sense from both a biodiversity planning perspective and a land and resource management perspective, the final products were aligned to (i.e., clipped to) municipal boundaries.

3 Cape Action for People and the Environment (C.A.P.E.) Programme

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The planning domains include:

• Five CAPE priority areas (Figure 2): o Nieuwoudtville o North-West Sandveld o Saldanha Peninsula o Upper Breede River Valley o Riversdale Coastal Plain

• Nine entire local municipalities (i.e., final product coverages; Figure 3):

o Matzikama o Cederberg o Bergrivier o Saldanha Bay o Witzenberg o Breede Valley o Breede River Winelands o Hessequa (formerly Langeberg) o Mossel Bay

• A portion of : o Hantam local municipality o Swellendam local municipality o West Coast National Park and Cederberg

Wilderness Area District Management Areas

• Extent of NSBA threatened lowland vegetation types falling within priority areas and not within other conservation planning domains (Figure 4).

• Entire quaternary catchments for river systems falling within the priority areas (Figure 5)

Figure 2. C.A.P.E. broad priority areas.

Figure 3. Municipal product extents.

Figure 4. Remaining extent of relevant threatened vegetation types.

Figure 5. Relevant quaternary catchments.

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Biodiversity Surrogates

Reducing the complexity of biodiversity into a set of components that we can plan for (i.e., identifying biodiversity surrogates) is necessary, and depends on many case-specific factors – like what data are available or can be sourced, and the biotic and abiotic characteristics of the region. Although there is no universally “best” surrogate4, we felt it was imperative to follow three general rules in our selection of surrogates, in addition to considerations of data availability and suitability5:

1. to represent terrestrial, freshwater, and estuarine realms; 2. to represent a variety of spatial scales and levels of biological organization6; and 3. to develop surrogates for not only biodiversity pattern but also for persistence7, through the

inclusion of ecological processes. These guidelines are not only supported in the international literature and by global good practice8, but in lessons learned from the original (2000) C.A.P.E. conservation planning projects9. Land classes, such as vegetation types or habitat types, were identified as an effective and inexpensive region-wide biodiversity surrogate, ensuring that biodiversity pattern is sampled across the landscape. However, the physical and biological heterogeneity of land classes can be problematic, often failing to represent compositional change and rare and endangered species especially may fall through the “coarse filter” net provided by land classes (Lombard et al., 2003). Thus, the recommendation, particularly when planning at a fine scale, is to supplement land classes with point locality species data – but only if a good coverage at an appropriate scale is available. It is generally acknowledged, though, that taxon-based surrogate schemes on their own have had limited success both globally10 and locally11. The CAPE conservation plan also set the precedent for a “design for persistence” approach12 – the intention of which is to design a system of conservation areas that will continue to function ecologically

4 Margules, C.R., Pressey, R.L., 2000. Systematic conservation planning. Nature 405, 243–253. 5 Of primary importance are comprehensiveness and scale. Data must give adequate coverage of the study area and be at a useful scale (not too coarse, e.g., quarter degree square). 6 One practical recommendation is the “coarse filter” and “fine filter” approach (e.g., Noss, 1996). The premise behind the coarse-filter/fine-filter approach is that a subset of a region’s species and natural communities can represent and facilitate conservation of the whole. Identifying and protecting intact representative examples of each ecological system or community native to a region (the coarse-filter) assures conservation of a large proportion of the species, biotic interactions, and ecological processes found there. In complement, the fine-filter strategy focuses on conserving individual rare or specialized species that are likely to “slip through’ the coarse-filter or to be missed if only a few examples of each community type are protected. This is sometimes also referred to as a top-down/bottom-up approach. Groves et al. (2002), however, make the observation that this approach can be confusing with regard to the spatial scale at which various coarse and fine filter entities occur. They purport that a more useful approach may be to recognize that surrogates can be identified at a variety of levels of biological organization and spatial scales from local (fine) to regional. 7 Biodiversity conservation is guided by two inter-dependent objectives: representation and persistence. “Representation” means securing a representative example of biodiversity composition and structure, or biodiversity pattern. “Persistence” is about maintaining those ecological and evolutionary processes that underpin biodiversity distribution and variety, without which biodiversity cannot survive in the long term. From: De Villiers CC, Driver A, Brownlie S, Clark B, Day EG, Euston-Brown DIW, Helme NA, Holmes PM, Job N and Rebelo AB (2005) Fynbos Forum Ecosystem Guidelines for Environmental Assessment in the Western Cape. 8 Groves, C.R., Jensen, D.B., Valutis, L.L., Redford, K.H., Shaffer, M.L., Scott, J.M., Baumgartner, J.V., Higgins, J.V., Beck, M.W., and M.G. Anderson. 2002. Planning for Biodiversity Conservation: Putting Conservation Science into Practice. BioScience 52 (6), 499-512. 9 Conservation Planning in the Cape Floristic Region, Special Issue of Biological Conservation Volume 112, Issues 1-2, Pages 1-297 (July - August 2003). And: Driver, A., Cowling R.M., and Maze K. 2003. Planning for Living Landscapes: Perspectives and Lessons from South Africa. Washington, DC: Center for Applied Biodiversity Science at Conservation International; Cape Town: Botanical Society of South Africa. 10 Lindenmayer, D. B., Manning, A. D., Smith, P. L., Possingham, H. P., Fischer, J., Oliver, I. & McCarthy, M. A. (2002) The Focal-Species Approach and Landscape Restoration: a Critique. Conservation Biology 16 (2), 338-345. 11 Lombard A.T., Cowling, R.M., Pressey, R.L., and Rebelo, A.G. 2003. Effectiveness of land classes as surrogates for species in conservation planning for the Cape Floristic Region. Biological Conservation 112: 45-62. 12 Cowling, R.M., Pressey, R.L., Lombard, A.T., Heijnis, C.E., Richardson, D.M. & Cole, N. (1999b) Framework for a Conservation Plan for the Cape Floristic Region. IPC Report 9902, Institute for Plant Conservation, University of Cape Town.

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indefinitely, and will continue to sustain evolutionary process that result in lineage turnover. Obviously there are constraints to this approach in terms of our understanding of evolutionary processes and what it takes to sustain them, but there is also the practical constraint of how to map (or otherwise include) processes in our plans. Pressey et al. (2003) outline four groups of approaches for including ecological processes: 1. Incidentally by considering only biodiversity pattern

This may be ok for some plant-pollinator interactions and population processes of narrow endemics or species with small body sizes; but is likely to compromise processes that operate over large areas, including disturbance regimes and the dynamics underpinning the persistence of large animals.

2. Considering generic design criteria Applied in planning as preferences (e.g. larger is better) but without explicit parameters (e.g. at least 10,000 ha) to guide decisions or allow reviews of effectiveness.

3. Considering process-specific design criteria This is done by parameterizing generic design criteria, e.g., parameters of natural disturbances, spatial requirements for focal species, core of species ranges where persistence could be more likely.

4. Considering specific spatial components associated with processes These are defined by specific physical or climatic features, e.g., drought refugia, climatic refugia, areas of recent, ongoing diversification associated with ecotones, geological interfaces, etc.

Bearing all of this in mind, the FSP project commissioned the mapping of fine-scale vegetation types and wetland types (including rivers and estuaries) as land class surrogates; emphasizing the importance of representing compositional change in addition to structural and functional change when differentiating between units. In terms of species, we selected potential “focal” plant and animal taxa (see Red Data List Plant Taxa, Restricted Plant Taxa, and Animal Focal Species sections below, as well as Appendices 1-3) to plan for – based on rarity, threat, and habitat requirements which are not likely to be accommodated by land class surrogates. But because we did not have the time nor budget to collect new field data we were constrained in the final set of included species. Point locality data had to be accurate to within 500 meters, with good coverage of the entire planning domain. Mapped or modelled habitat data needed to be similarly accurate and comprehensive, and were generally either unsuitable or unavailable. Most successful was our partnership with SANBI’s (South African National Biodiversity Institute) Threatened Species Programme to improve the accuracy (to 500 meters or better) and coverage (to encompass the known global extent of each focal taxa) of plant locality data for 229 restricted and threatened taxa.

Ecological and evolutionary processes were addressed by utilizing approaches from within all four groups discussed by Pressey et al. (2003) and summarized above. For example: 1. Fine-scale processes, like pollination and faunal seed dispersal, were assumed to be accommodated

incidentally through pattern targets. 2. Two generic design criteria, or preferences, were emphasized: size (larger is better) and connectivity

(connected is better). Several slightly less generic design criteria were also formulated to help guide fine-scale corridor placement, for example: - Incorporate lateral connectivity (to ensure interconnectedness between aquatic, riparian, and

terrestrial ecosystems). - Traverse altitudinal gradients (to accommodate local-scale range shifts in the face of climate

change). - Avoid (or minimize) edaphic discontinuity across upland-lowland gradients and biogeographic

zones (abrupt soil transitions can be a barrier to plant movement). - Follow south-facing slopes when possible (they are cooler and thus likely to provide a buffer

against rising temperatures) 3. Process-specific design criteria helped define wetland clusters by considering the maximum distance

amphibians are likely to travel between wetlands.

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4. Specific spatial components associated with ecological or evolutionary processes, like edaphic interfaces as drivers of plant diversification, were included where possible.

All biodiversity pattern and process features included in the FSP assessments are discussed in more detail in the next two sections.

Biodiversity Pattern

Vegetation Types

For each planning domain a study was undertaken to produce a defensible vegetation classification system and vegetation map which would form an integral part of the conservation assessment of the area by representing the original natural extent of different vegetation types, prior to any modern transformation. The approach was essentially one of verifying, through extensive ground-truthing and the use of supporting data such as geology maps and species locality records, the Vegetation Map of South Africa (Mucina & Rutherford, 2006). Of primary importance was adjusting boundaries to be reasonably accurate at a scale of 1:10 000 (and highly accurate at 1:50 000) and adding new vegetation types where deemed necessary. In general, the national vegetation types were accepted as adequate, although new types were added when the unit was significantly different (structurally, floristically, and/or edaphically) from anything currently described in the SA Vegetation Map. The boundaries of the national units, however, were substantially incorrect in many areas13 and therefore redrawn. Unfortunately, due to time and budget constraints, the study areas were often smaller than the full extent of the planning domains, focusing on the threatened lowland portions. Therefore it was necessary to augment the fine-scale vegetation map products with the Vegetation Map of South Africa14 to produce a continuous layer of vegetation types. This required that all fine-scale vegetation types be cross-referenced to national vegetation types, and all boundaries edge-matched. The final vegetation layer was enhanced with data from several other sources as well – always retaining the more accurate of the boundaries (i.e., those mapped at a finer scale), edge-matching, and cross-referencing each unit with the most similar national type. These additional sources of vegetation type units included: west coast dune systems as mapped by Barrie Low, fine-scale wetlands for Saldanha and Sandveld as mapped by the Freshwater Consulting Group, and vegetation types at the fynbos/succulent karoo interface (in the Bokkeveld) as mapped by the Conservation Farming Project.

Additional information available

♦ Technical detail on the integration process: Appendix 4 ♦ Final integrated vegetation map product: “wc_nv_ub_integrated_vegetation” shapefile and

metadata. ♦ Vegetation reports. For detailed vegetation type descriptions and mapping methodologies see:

- Helme, N. A. and R. Koopman. 2007. Botanical report: Fine-scale vegetation mapping in the Saldanha Peninsula. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

- Helme, N. A. 2007. Botanical report: Fine-scale vegetation mapping in the Northwest Sandveld. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

- Helme, N. A. 2007b. Botanical report: Fine-scale vegetation mapping of the Bokkeveld Escarpment. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

13 Helme, N. A. and R. Koopman. 2007. Botanical report: Fine-scale vegetation mapping in the Saldanha Peninsula. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa. 14 Mucina, L. & Rutherford, M.C. (eds) 2006. The Vegetation of South Africa, Lesotho and Swaziland. Strelitzia 19. South African National Biodiversity Institute, Pretoria.

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- Helme, N. A. 2007c. Botanical report: Fine-scale vegetation mapping in the Upper Breede River Valley. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

- Vlok, J.H.J. and de Villiers, M.E. 2007. A vegetation map for the Riversdale Coastal Plain. Report for CapeNature, as part of the C.A.P.E. programme: Fine-Scale Biodiversity Planning project. Cape Town, South Africa.

- Mucina, L. & Rutherford, M.C. (eds) 2006. The Vegetation of South Africa, Lesotho and Swaziland. Strelitzia 19. South African National Biodiversity Institute, Pretoria.

Figure 6. Fine-scale vegetation maps were merged with the SA Vegetation Map (Mucina & Rutherford, 2006) to produce a continuous vegetation layer (shown) for all FSP planning domains (black outline).

Alternative Method or Variation:

For the Upper Breede River Valley and Riversdale Coastal Plain planning domains the vegetation categories were not based on the South African vegetation types of Mucina & Rutherford (2006), but rather a hierarchal classification system was used, compatible with that of the Little Karoo Vegetation Map (Vlok et al., 200515). Habitat and vegetation units were distinguished primarily on structural characteristics, as well as position in the landscape and soil type, and secondly on floristic and biogeographical distinctions. Sufficient data were not provided to integrate the Riversdale Coastal Plain Fine-Scale Vegetation Map with the SA Vegetation Map; as a result both products (and therefore sets of vegetation types) were used in the conservation assessment.

15 Vlok J.H.J., Cowling R.M., Wolf T. 2005. A vegetation map for the Little Karoo. Unpublished maps and reports for a SKEP project supported by CEPF grant no.1064410304

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Critically Endangered and Endangered Ecosystem Remnants

Threatened ecosystems (Critically Endangered (CR), Endangered (EN), and Vulnerable (VU)) may be listed by the Minister or MEC in terms of the Biodiversity Act16. Once listed, these ecosystems are subject to special precautions. For example, the transformation or removal of indigenous vegetation of any size within a CR or EN ecosystem is a listed activity17 triggering a Basic Assessment Report according to Environmental Impact Assessment regulation18. We felt it was important in a land-use decision-support product to bring to attention these specific ecosystems for which a more rigorous assessment and duty of care is legally required. Thus, all CR and EN ecosystems were included as biodiversity features. See “Status Information: Ecosystem Status” for more information about ecosystem status, how it was calculated, and our results. Once CR and EN ecosystems were identified, the remaining vegetation representing these ecosystems had to be translated into mapped features for inclusion in the assessment. An important set of issues arose during this process: because of the fine grain size (2.5m pixels) and automated processing of our landcover data, many tiny remnants of vegetation were mapped as “natural” (because their spectral characteristics matched the parameters defining natural veld) yet they do not, in effect, represent the threatened ecosystems of interest because they are too small, isolated, or degraded to be of conservation value. In some instances, for example, residential gardens, farm yards, and fence rows were classified as natural veld (see Figure 7). Thus, in order to create a useful CR and EN remnant feature layer we had to eliminate as many inappropriate areas as possible, while maintaining potentially viable remnants of CR and EN habitat. Two approaches were used, both starting with our fine-scale landcover data. Image B in Figure 7 (below) shows our natural (dark green), near-natural (medium green), and degraded (bright green) landcover classes, with SPOT 5 imagery as the background. One approach entailed setting size, condition, and connectivity thresholds for the remnants, depending on their status, and then screening the landcover for groups of cells (i.e., remnants) meeting these criteria. If Critically Endangered remnants met a size threshold of one-tenth of a hectare or greater, and a condition threshold of natural or near-natural (i.e., excluding degraded) then they would be maintained. If Endangered remnants met the same size and condition threshold, but also a connectivity threshold, then they would be maintained. The connectivity threshold selected all cells that contribute to a level of intactness of 60% or greater within a 150m radius. Put another way, any remnant that contributes to an area that is at least 60% intact over a 300m span, will be selected. This exercise was carried out on the 10m summarized landcover grids, using the “Remove Noise” function of the Grid Generalization tool, for the size filter, and Neighbourhood Statistics (mean, circle, 150 radius), with a simple MapQuery ([previous_result] >= 0.60 AsGrid) in Spatial Analyst, for the connectivity filter. The condition filter was applied first, by a selecting all natural and near-natural values (1s and 2s) from the summarized landcover and converting this to a new grid. This approach was used for the Saldanha and Sandveld planning domains. The second approach made use of our eCognition or landcover-based planning units. These units represent groups of pixels, or objects, with the same, or similar, values (i.e., summarized landcover values), according to certain scale and compactness parameters (see “Analysis: Planning Units” for

16 Section 52 of the National Environmental Management: Biodiversity Act 17 refers to activities identified by the Minister of Environmental Affairs and Tourism in terms of Section 24 and Section 24D of the NEMA which may have a detrimental effect on the environment and which may not be commenced without prior written authorization from the competent authority. These activities are listed in the Schedules contained in Government Notice R386 and R387. From: Department of Environmental Affairs and Development Planning, Chief Directorate: Environment and Land Management. NEMA Environmental Impact Assessment Regulations Guideline and Information Document Series: Guideline on the Interpretation of the Listed Activities. November 2006. 18 Published in terms of Chapter 5 of the National Environmental Management Act, 1998.

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more information). As a result, remnants generally emerge as single units or as a distinct group of units, with a minimum size of a tenth of a hectare. For each unit, we calculated what percent natural, degraded, or transformed it was. We then tested a variety of “profiles” to identify the units that best represented suitable remnants. For example, the profile that best suited the Upper Breede River Valley was: [((percent value 1>60) and (percent value 1+2 >= 90)) or ((percent values 1+2+3 >= 100) and (percent value 3 < 50%))]. Meaning that in order to be selected a planning unit had to be at least 60% natural, and greater than or equal to 90% natural plus near-natural; OR it had to be 100% natural plus near-natural plus degraded (i.e., not cultivated or transformed) and the degraded portion had to be less than 50% of the total area of the unit. An example of the results from both approaches is displayed in Figure 7 for a portion of the Riversdale Coastal Plain planning domain. Image C shows the landcover grid threshold approach and image D the planning unit profiling approach. Image B shows the original summarized landcover for comparison. Both approaches (C and D) eliminate the fence-line effect (2) and degraded veld (3). The profiling approach (D) eliminated a farmyard (5), and avoided truncating whole remnants at the mapped vegetation boundary (white line in image B, where the vegetation type above the line is Critically Endangered and Least Threatened below the line; 4). Within the degraded patch above number 3, image B, are some natural (darker green) spots; these are highlighted as CR remnants in the grid threshold approach (C) and not in the unit profiling approach (D). These spots are in fact single, or small clumps of, gum trees and not legitimate CR vegetation. On the other hand, the profiling approach does miss some apparently viable remnants (to the left of D1) that are maintained with the grid threshold approach (left of C1). Neither approach is perfect, and both involve trade-offs. We used our best judgement to select the approach most appropriate for each planning domain.

Figure 7. An example showing the results of alternative methods for generating Critically Endangered and Endangered vegetation remnants (C: landcover-derived & D: eCognition-derived), compared with SPOT5 satellite imagery (A) and natural landcover classes (B).

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Wetland Groups

A team of freshwater consultants19 undertook the fine-scale mapping, assessment, and classification of wetlands, including estuarine environments, within four priority areas (Saldanha Peninsula, NW Sandveld, Upper Breede River Valley and Riversdale Coastal Plain). They were also tasked with incorporating into their products the results of a groundwater assessment for the West Coast (NW Sandveld and Saldanha Peninsula)20. The mapping, typing, and prioritizing of wetlands was an important component of the FSP project, as wetlands have been neglected in past conservation planning exercises in these landscapes, due, primarily, to a lack of data. For example, in the Saldanha planning domain an average of 260 new wetlands were mapped in each of seven quaternary catchments, over and above existing mapped wetlands (e.g., Western Cape Sensitive Wetlands, National Wetlands Map). In addition to a paucity of mapped wetland and accompanying data, there in a bias towards the development of methods for assessing rivers, as opposed to wetlands21. South Africa’s NSBA (2004), for example, assessed terrestrial, riverine, estuarine and marine biodiversity22; and acknowledges the omission of wetlands except in a cursory manner. Neither the spatial data, nor standard methods of assessment exist. The FSP project has undoubtedly helped advance the science and practice of wetland classification and assessment in the Western Cape, and in South Africa. In order that they be included in our fine-scale assessment, wetlands were manually digitized at a scale of 1:10 000 on SPOT 5 imagery (so as to align with terrestrial vegetation and landcover features also mapped using SPOT5) by experienced wetland ecologists utilizing a variety of supplementary information for interpretation (e.g., all available GIS layers of wetlands and rivers, DWAF orthophotos, contours, DEM, vegetation, species localities). Each mapped wetland was assessed in terms of:

- wetland condition; - size; - location with regard to springs, groundwater recharge or discharge areas; - proximity to other wetlands (including rivers and estuaries); and - presence of fish or amphibian species.

Based on these criteria each wetland was given an overall rank indicating its importance relative to others of a similar type. Focus areas within the planning domains were identified and ground-truthed to improve the reliability of the product; verifying location and condition information. In terms of typing, wetlands were first grouped by Water Management Region (WMA), then by quaternary catchment. Beyond this classification level, wetlands were typed according to the National Wetlands Inventory Classification System (NWICS), using functional and structural level typing (the NWICS has not yet been developed down to the habitat unit level; see Snaddon et al., 2008 for full description of typing). In addition, wetlands were grouped into like groups, based on the NWICS typing and the broad vegetation group (from the South African Vegetation Map) in which the wetlands lie, or other appropriate descriptor of the soils or geology characterizing the ecosystem. This grouping of wetlands was an important step towards the integration of wetland features and vegetation features in our biodiversity assessment. Representation was set at the level of wetland groups.

Additional information available

♦ Freshwater Reports. More information about the freshwater component of the FSP see:

19 The Freshwater Consulting Group (FCG), in partnership with the Council for Scientific and Industrial Research (CSIR) 20 Carried out by GEOSS: Geohydrological and Spatial Solutions International (Pty) Ltd 21 Nel et al., in prep. 22 Driver, A., Maze, K., Rouget, M., Lombard, A.T., Nel, J., Turpie, J.K., Cowling, R.M., Desmet, P., Goodman, P., Harris, J., Jonas, Z., Reyers, B., Sink, K. & Strauss, T. 2005. National Spatial Biodiversity Assessment, 2004: priorities for biodiversity in conservation in South Africa. Strelitzia 17. South African National Biodiversity Institute, Pretoria.

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- Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Saldanha - Sandveld planning domain. Report submitted to CapeNature, November 2008, 52 pp + appendices. Cape Town, South Africa.

- Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008b. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Riversdale Coastal Plain planning domain. Report submitted to CapeNature, November 2008, 71 pp + appendices. Cape Town, South Africa.

- Job, N., Snaddon, C.D., Nel, J., Smith-Adao, L and Day, L. 2008c. C.A.P.E. fine-scale planning project: Aquatic ecosystems of the Upper Breede River Valley planning domain. Report submitted to CapeNature, November 2008, 32 pp + appendices. Cape Town, South Africa.

- Snaddon, C.D., Job, N., Nel, J., Smith-Adao, L and Day, L. 2008. C.A.P.E. fine-scale planning project: surface freshwater ecosystems. Methodology Report. Report submitted to CapeNature, November 2008, 42 pp + appendices. Cape Town, South Africa.

Alternative Method or Variation: No new wetland mapping was commissioned for the Nieuwoudtville/Bokkeveld planning domain. A wetlands layer was, however, compiled in order to include these important features in the biodiversity assessment. Some of the wetlands mapped for the Northwest Sandveld overlapped with the Nieuwoudtville/Bokkeveld planning domain and were thus included. In addition, all natural wetland values (1, 3, & 4) from the fine-scale landcover were extracted and converted into a shapefile (vector layer), with separate polygons representing each cluster of similar values. These polygons were subsequently filtered to only include wetlands greater than 0.25 ha. Each value cluster, or wetland type, was assigned to a “wet group” for representation purposes, and so that they could be merged with the overlapping wetlands from the Sandveld. The landcover-derived wetland groupings were based on the following: Value 1 = open water, Value 3 = vegetated wetland, Value 4 = non-vegetated wetland; and then were categorized by broad vegetation type (e.g., fynbos, karoo, renosterveld, and riverine).

River Types

The same team of freshwater consultants, lead by CSIR in the case of rivers, undertook the typing of river features, as well as an assessment thereof, within four priority areas (Saldanha Peninsula, NW Sandveld, Upper Breede River Valley, and Riversdale Coastal Plain). The river assessment followed a systematic conservation planning approach and targeted the representation and persistence of river types and indigenous fish species, using sub-catchments as planning units. The results of the river assessment were incorporated directly into the biodiversity assessment described in this document. The features used in the river assessment, as well as the integration process are described here – the full river methodology, however, is described in Snaddon et al., 2008. As with wetlands, rivers were first grouped by Water Management Region (WMA), and then by quaternary catchment. Thereafter rivers were typed according to river flow (permanent or non-permanent), DWAF Level 2 ecoregions, and finally geomorphological or longitudinal zones. This typing, which resulted in a total of 64 river types across all planning domains, was applied to the 1:500 000 DWAF rivers layer. The 1:500 000 layer was used in the river assessment and, at times, supplemented with rivers from the 1:50 000 layer. These finer-scale rivers were added mainly to increase the options of representing certain river types in intact smaller river systems, particularly where larger rivers are heavily utilized and largely degraded23. All 1:50 000 rivers and tributaries were included in the final Critical Biodiversity Area Maps as important ecological support features, with appropriate buffers and land use guidelines indicated. Alternative Method or Variation:

23 Snaddon, C.D., Job, N., Nel, J., Smith-Adao, L and Day, L. 2008. C.A.P.E. fine-scale planning project: surface freshwater ecosystems. Methodology Report. Report submitted to CapeNature, November 2008, 42 pp + appendices. Cape Town, South Africa.

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In the final Critical Biodiversity Area Maps and products for the Saldanha, Sandveld, and Upper Breede River Valley planning domains the 1:500 000 river lines were replaced with, and spatially represented by, 1:50 000 river lines and areas (from the Department of Surveys and Mapping). This was a time-consuming, manual process, but significantly improved the spatial accuracy of the final products.

Indigenous Fish Species

The Cape Floristic Region contains a high number of endemic freshwater fishes, all of which are threatened by invasive alien fish species, unsustainable water abstraction and habitat degradation. Twelve indigenous freshwater fish species were included in the biodiversity assessment through the river analysis mentioned above and further described in Snaddon et al., 2008.

Indigenous Forest Patches

Forests form the smallest, most widely distributed and most fragmented biome in southern Africa. The Forest Act (84 of 1998) prohibits the destruction of indigenous trees in any natural forest without a license, and many indigenous forest types are proposed as Listed ecosystems24 in terms of the Biodiversity Act. Unfortunately, the Vegetation Map of South Africa depicts forests at too coarse a scale (or, in some cases, is too inaccurate25; Figure 8) to be useful in the fine-scale plans, and in informing site-specific decision-making. Even in the fine-scale vegetation maps there is not necessarily forest cover everywhere forest vegetation is mapped. For example, on the Riversdale Coastal Plain many forest and thicket mosaics are mapped, with the actual forest patches occurring at a finer scale within the mosaic areas (Figure 8).

Figure 8. An example of how indigenous forest patches were dealt with in the FSP biodiversity assessment.

24 The South African Vegetation Map identifies eight forest groups and four national forest types. DWAF recognises 26 national forest types, including the four national forest types identified in the South African Vegetation Map, and a further 22 national forest types which make up the eight forest groups identified in the South African Vegetation Map. For the purpose of listing ecosystems, DWAF’s 26 national forest types have been used rather than the forest groups from the South African Vegetation Map. 25 The forest units in DWAF’s Indigenous Forest Patches Map (2004) – and, hence, in Mucina & Rutherford (2006) – on the Riversdale Coastal Plain consistently appear to be shifted about 2 kilometers to the west-northwest; see Figure7.

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Forests were thus dealt with in the following manner: All mapped forest vegetation types (SA Veg Map, FSP Veg Map, & DWAF’s Indigenous Forest Patches Map; Figure 9) were compared with the FSP landcover. Wherever the two corroborated – i.e., forest as both a landcover class and a vegetation type – the forest cover was selected, converted to a shapefile (vector format), and included as a feature in the biodiversity assessment.

Figure 9. Forest vegetation types from available map sources, shown (buffered to be visible at this scale) for the Western Cape and FSP planning domains.

Alternative Method or Variation: In the Nieuwoudtville/Bokkeveld planning domain, the botanist mapping FSP vegetation types explained that Southern Afrotemperate forest patches are typically small (<2ha) and widespread in sheltered areas; they often occur in very long and narrow patches which are practically impossible to map accurately on 1:50 000 hardcopy (SPOT 5) images (e.g., sometimes they are as narrow as a pen width). Thus, just the larger ones were mapped (see northeastern-most portion of FSP domain in Figure 8), and it was suggested that a set of rules for interpreting and extracting forests from the landcover be developed to capture smaller patches. The following rule-set was thus developed: ♦ Indigenous forest patches in this region occur on:

o slopes greater than 1:4; o above 500m in elevation; and o in areas mapped as Bokkeveld Sandstone Fynbos, Nieuwoudtville Sandstone

Renosterveld, Vanrhynsdorp Shale Renosterveld, Southern Afrotemperate Forest, and

Kobee Succulent Shrubland. ♦ In terms of landcover characteristics, indigenous forest patches within the above vegetation types:

o will not have sparse low vegetation cover;

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o will have a tall (>2m) natural shrub/tree component; o will occur in solid patches, not in a mosaic pattern; and o large stands (>1ha) of tall shrubs are not likely to be aliens.

Areas meeting these requirements were selected and converted to a shapefile (vector format) for inclusion in the Nieuwoudtville/Bokkeveld biodiversity assessment as forest features. The result is a total of 888 ha of small, disjunct forest patches on steep, generally south-facing slopes – which may be an overestimate of true forest patches, but only by picking up tall, scrubby thicket, not alien vegetation.

Red Data List Plant Taxa

As discussed in the biodiversity surrogates section above, in order to represent a variety of spatial scales and levels of biological organization, species data were investigated for inclusion. Of particular interest were threatened, rare, and restricted species – those most likely to fall through the “coarse filter” of land classes. A related issue which underscores the importance of including species is that of biodiversity targets. The National conservation target (quantified objective) for a vegetation type is a percentage of its original area, based on the species-area relationship for that system26. The target is set at the area required to accumulate 75% of the vegetation type’s full species complement. The species-area curve, however, says nothing about where species are located in the landscape; it only provides an indication of the rate at which species are likely to be accumulated27. Desmet and Cowling (2004), the original purveyors of the species-area curve approach to target-setting, make it clear that “unfortunately, rare or very patchy (habitat-specific) species, i.e., the other 25% of species not targeted, are likely to be missed.” They stress the need for at least some species point-locality data to help guide site selection. Thus, we decided to include all globally Critically Endangered (CR), Endangered (EN), Vulnerable-Range Restricted (VU-D2), and/or Rare plant species (vis a vis IUCN Red Data List), knowing that several comprehensive sources of locality information existed at a fine enough scale to be useful in our site selection, and, consequently, in site-specific land use decision-making. Two challenges, however, presented themselves: (1) South Africa’s Red Data List28 was undergoing an update and the new status information had not yet been transferred to the point data/locality records (and the old list and status information were as good as obsolete); and (2) the various sources of plant locality information had never been combined into a single layer by any of the entities hosting them, nor other projects. In order to make use of these data, then, it was necessary to update their status information and merge them together. The following sources of plant locality data were used:

o CREW’s (TSP’s Custodians of Rare and Endangered Wildlflowers project) “Rares” layer – predominantly data from herbarium specimens, with a few observation records; January 2007

o CREW’s “Specials” layer – observation records only, collected by CREW and Chris Burgers; March 2007

o A recently updated extract from PRECIS (National Herbarium Pretoria (PRE-) Computerised Information System (-CIS)); August 2007

o Protea Atlas Project data and herbarium data; March 2006 o FSP expert workshop data – observation data added by botanical experts for a subset of

‘restricted’ species (see next section), with significant overlap with Red Data List species.

26 Driver, A., Maze, K., Rouget, M., Lombard, A.T., Nel, J., Turpie, J.K., Cowling, R.M., Desmet, P., Goodman, P., Harris, J., Jonas, Z., Reyers, B., Sink, K. & Strauss, T. 2005. National Spatial Biodiversity Assessment, 2004: priorities for biodiversity in conservation in South Africa. Strelitzia 17. South African National Biodiversity Institute, Pretoria. 27 Desmet, P. and R. Cowling. 2004. Using the species–area relationship to set baseline targets for conservation. Ecology and Society 9(2): 11. 28 Lead by SANBI’s Threatened Species Programme

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We obtained the most up-to-date version of the Red List from SANBI’s Threatened Species Programme. This was in Excel format with the following attribute fields: Genus, Species, Subspecies, Variety, 2007 Global Status, Criteria, and Rarity. In order to transfer the 2007 Global Status information from this table to the plant locality data, a common Taxon Name field was required. Unfortunately, each of the six plant locality databases not only had different practices for recording a Taxon Name (e.g., Genus species, Genus species subspecies, Genus species variety, Genus species “spp” subspecies, Genus species “var” variety, Genus species [Author name], etc.), but had misspellings, double spaces, and other pervasive errors that would result in the Taxon Name not matching that in the Red List. Without an exact match, the updated status information could not be transferred to the record. A substantial amount of editing was carried out, and then three versions of each Taxon Name created (“Genus species”, “Genus species subspecies”, and “Genus species variety”). The status table was then joined successively to each of the three names in the merged locality data, and the 2007 status information copied across each time. The Genus Number and Species Number (or Genspec code) were extracted from the Threatened Species Program database and added to the locality databases where missing. Out of 303 868 locality records, 274 625 received up-to-date RDL status information (compared to zero when the data were acquired); those without had either not been assessed yet, were not due to be assessed, or bore taxonomic name changes or misspellings. Once the locality records were merged, and each taxon’s global status updated, we were able to select all of the records representing our suite of CR, EN, VU-D2, and Rare (“RDL”) taxa. Out of more than 299,000 records in the greater Cape Floristic Region29, just over 266,000 met our ‘500m or better’ accuracy criterion (~254 500 of which are Protea Atlas data), and 14,737 met our Red Data List criterion (9,038 Protea Atlas). These 14,737 records represent 905 species (or other unique taxa). A total of 4,014 qualifying records fell within the FSP planning domains, representing 401 species/taxa. Of these, 97 were Critically Endangered, 159 Endangered, 71 Vulnerable-Range Restricted, 60 additional Rares, and 14 Data Deficient but expected to be added once assessed. See Appendix 1 for the full list of RDL species included in the FSP biodiversity assessments.

Restricted Plant Taxa

For a subset of plant species with the most restricted or localized habitat requirements (at least 80% of the known global population falling within the planning domain of interest), and which are threatened or uncommon where they occur, we enlisted the help of Threatened Species Program staff and botanical experts to augment existing data. Our goal was to develop a layer of highly accurate data points representing the known, current global extent of species identified as restricted and uncommon to the threatened habitats of our planning domains. For each domain, a list of species meeting the abovementioned “restricted” criteria was developed by our resident botanical expert, Nick Helme, and circulated to others for review. The list was then given to Ilva Rogers of the Threatened Species Program who began checking PRECIS (national herbaria) and Protea Atlas records for each species, and working to improve the accuracy of the documented locations30. In particular, she added or adjusted points based on notes accompanying the record, and in conjunction with satellite imagery and/or landcover. In some cases, she also contacted the collector directly and asked for their assistance in locating the specimen more accurately. The following collectors contributed in this way: M. B. Bayer, R. Koopman, E. G. H. Oliver, J. C. Manning; L. W. Powrie, Ernst van Jaarsveld, H. Steyn, W.A.J. Pretorius, and D.A. Snijman, who also helped with some of P. Perry's specimens as they often did field work together. S. Boatright, B. Low, C. Boucher, S. Todd and D. Raimondo provided data electronically. A total of 1,724 records31 were reviewed through this process.

29 To ensure locality data were included for the full extent of vegetation types intersecting the FSP planning domains, we reviewed records within the fynbos, succulent karoo, and sub-tropical thicket biomes. 30 The accuracy of locality records has improved over time with the use of Global Positioning Systems, and data quality standards. CREW data, for example, did not need to be screened by Ilva as they are always accurate to at least 500 meters. 31 Upper Breede River Valley =525, Bokkeveld plateau = 505, Sandveld =400, Saldanha =294. This exercise was not completed for Riversdale Coastal Plain.

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As a next step, we hosted expert workshops for each domain to further improve data accuracy, but also to add observation points. For each species on our ‘restricteds’ list (Upper Breede River Valley, n=54; Bokkeveld plateau, n=122; Sandveld, n=53; Saldanha, n=71) we would: (1) confirm whether or not it should be a focal species; (2) ask if the existing points reflect the current known extent of the global population; and (3) add or adjust points (where appropriate) based on expert observation/knowledge. Specific attention was given to improving existing localities with less than 500m accuracy, so that they could meet the criteria for use in the FSP analysis. It was often the case that the species occurs in a specific habitat type, and one of the experts in attendance were able to identify the nearest appropriate or known habitat. Where appropriate or actual habitat conditions were unknown, or not present in the vicinity, the record remained unchanged. Across the four domains, we eliminated a total of 72 species from our lists of restricted focal species (original number = 301, final number = 229). Some were removed because they did not meet our criteria of being rare or threatened enough, e.g., they grow in least threatened habitats (mountains), or were considered too common where they occur (even if in a restricted range), or expert opinion was that the species would be adequately represented by planning for vegetation types. Others were removed due to data deficiencies (usually the complete lack of locality information or sufficiently accurate locality information), or taxonomic issues (typically that they are not well enough known or described or distinguishable from one another). Some 13 new species were added. During the course of the workshops, a total of 244 new expert observation localities were added, representing 91 different species; and at least 231 existing points, representing >99 species, were placed more accurately or verified based on expert input32. Experts included: Nick Helme, Rupert Koopman, Charlie Boucher, Domitilla Raimondo, Ismail Ebrahim, Garth Mortimer, and Ian Oliver. See Appendix 2 for a full list of restricted species included in the FSP biodiversity assessments.

Focal Animal Species

For reasons similar to those for including plant species, we endeavoured to include a set of focal animal species. In addition to wanting to capture unique local biodiversity – whose ecological requirements and specific habitat may not be well-served by land class surrogates (e.g., bat roosts, waterfowl congregation areas, nesting sites) – we thought focal animals may help to parameterize ecological and evolutionary processes. For example, minimum foraging habitat requirements or average territory size for area-sensitive species could help define patch size targets and/or corridor widths; the metapopulation dynamics of certain reptile and/or amphibian species could provide explicit design criteria regarding the minimum distance between, and number of, special habitat patches (e.g., koppies, isolated depressions), etc. First, we requested Andrew Turner, the curator of CapeNature’s Biodiversity Databases, extract animal locality records for our planning domains. From this information, we created a list of species known to occur in each domain, updated the status information for each taxon33, and held an in-house workshop with CapeNature Scientific Services staff to select potential focal species, learn of additional data sources, and to articulate key habitat requirements for as many focal species as possible. In the workshop, each species was briefly discussed it terms of whether or not it was a habitat specialist or had other requirements (e.g., rarity or threat) that would qualify it as a focal species – a species that would not be ‘captured’ by a plan that used land classes alone as a biodiversity surrogate. We

32 Originally, the idea was to translate all point data into “area of occupancy” data per individual population. So that instead of a point of information we would have a polygon representing the area -- and therefore the specific habitat -- in which a focal species is known to occur. This, however, would have taken considerable time and knowledge. Furthermore, point data will have the effect of selecting an entire planning unit, and because our planning units are based on landcover “objects” it is likely that entire natural patches of similar habitat will be selected anyway. 33 South African Red Data Book and IUCN information were generally up-to-date, but a new TOPS (Threatened or Protected Species) list had just been published (Department of Environmental Affairs and Tourism, Regulation 152 of 2007) and was used to update status information.

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successfully identified a number of potential focal species or guilds (e.g., grysbok; a suite of species including skinks, rain frogs and the dune mole rat, restricted to soft sands; bats; area-sensitive mammals; congregating waterfowl), and either described key habitat conditions and known locations, or were pointed towards other sources of information or experts. Out of about 550 species in the original list, approximately 50 species or guilds were identified as potential focal features (Appendix 3). The total number of locality records extracted for our planning domains was 24 826, and 4 419 for the identified focal species. Of these, 1 618 were accurate and recent enough (>1985) to be considered for use. However, 723 were for 13 fish species, which were already accounted for in the river assessment. Of the remaining 893 (representing 33 species), a substantial percentage were located on transformed lands, just over half (n=512) were for a set of 12 lizard species, and most of the other half were for larger, mobile species (e.g., grysbok, caracal, fox, leopard, honey badger, aardwolf, otter). These latter points would only be sufficiently useful for site selection if they corroborated with habitat data, which was generally unavailable. This was, however, feasible for a set of amphibian species, using the fine-scale wetland maps as a habitat informant. Thus, the following amphibian species were taken into account in the ranking and selection of wetlands, and in the selection of significant wetland clusters (see “Biodiversity Process: Significant Wetland Clusters” below): Afrana fascigula, Cape river frog Arthroleptella bicolor, Riviersonderend chirping frog Arthroleptella subvoce, Northern moss frog Breviceps gibbosus, Cape rain frog Breviceps montanus, Cape mountain rain frog Breviceps namaquensis, Namaqua rain frog Breviceps rosei, sand rain frog Bufo angusticeps, sand toad Bufo gariepensis, Karoo toad Bufo rangeri, raucous toad Bufo robinsoni, paradise toad

Cacosternum boettgeri, common caco Cacosternum capense, Cape caco Cacosternum karooicum, Karoo caco Cacosternum namaquense, Namaqua caco Capensibufo tradouwi, Tradouw mountain toad Heleophryne purcelli, Cape ghost frog Strongylopus bonaespei, banded stream frog Strongylopus fasciatus, striped stream frog Strongylopus grayii, clicking stream frog Tomopterna delalandii, Cape sand frog Xenopus laevis laevis, common platanna

While the other point data discussed above were not used in target-driven site selection for specific focal species, the locality information was used in the design phase – where decisions regarding options between specific areas could be informed by the data. Upon further investigation of other potential data, suitable accuracy (appropriate for planning at a scale of 1:10 000) was generally lacking – both in terms of localities and either expert mapped or modelled habitat data. For example, additional point data for bat roosts were extracted from the Annals of the Cape Provincial Museums publication34, but the coordinates were too coarse (nearest minute) to be included. Likewise, a database of bee data was obtained, containing 1 366 localities within the Fine-Scale Planning domains (out of 7 270 records), but were only accurate to two decimal degree decimal points (approximately 1 km), which appeared to be grid centroids. Another readily available data source was the Sensitive Lower Vertebrate Areas35, but, again, the data were too coarse to be directly taken up in the biodiversity assessment – with the exception of sites mapped for Geometric Tortoise (Psammobates geometricus). P. geometricus habitat was therefore included as a focal animal feature. Another species with spatially accurate habitat data (a single, highly important roost site) was Antarctic Tern (Sterna vittata), which was also included as a feature.

34 Herselman, J.C., and P.M. Norton. The distribution and status of bats (Mammalia: Chiroptera) in the Cape Province. In: Annals of the Cape Provincial Museums (Natural History). Volume 16, Part 4. 21st January 1985. Grahamstown, South Africa. 35 From the GIS metadata: “A digital data layer of cadastral units (properties) that have been flagged as ‘sensitive’ for lower vertebrate species (Classes: Amphibia, Reptilia and Osteichthyes). ‘Sensitive’ lower vertebrate species were defined as those that have International Union for the Conservation of Nature or Red Data Book status. Sensitive areas based on herpetofauna were defined as ‘specific habitats and/or sites and areas known to be sensitive and/or vulnerable to disturbance and habitat degradation, or which are known to support a diverse herpetofauna’ (Ernst H.W. Baard, William R. Branch, Alan C. Channing, Atherton L. de Villiers, Annelise le Roux and P. le Fras N. Mouton, unpublished).”

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New expert mapping was not undertaken for several reasons: firstly, due to time constraints and the fact that experts with the requisite knowledge of ecological and life-history requirements are limited in number, and generally focused on only a relatively small suite of species – such that acquiring taxonomically representative data would require considerable effort and multiple workshops; and also based on experience from the Cape Lowlands Renosterveld project, which reported, after having held several workshops, that expert knowledge was heavily biased towards the mountains36.

Special Habitats or Features

Certain habitats or ecological features within vegetation types have such unique characteristics that they are worthy of special attention, and were therefore included where suitable data were available. Special habitats occur at a smaller spatial scale than vegetation types, and are sometimes plant communities within vegetation types, or geological formations, or microhabitats. Most special habitats were mapped at the same time as vegetation types, by the vegetation mapper (see the FSP Vegetation Reports for complete descriptions); while others were included from existing sources (e.g., Knersvlakte quartz patches and intermediate heuweltjie/quartz veld).

Biodiversity Process

Coastal Corridor

The coastal zone supports a unique suite of habitats maintained by coast-specific processes and climatic conditions. The biodiversity of the coastal zone is influenced by dynamic processes, such as sand movement and storm events, but also stabilizing processes like the temperature-moderating effect of the ocean (which, when combined with cool on-shore winds and south-facing slopes results in fire and climate refugia). This narrow ecosystem is vital for species adapted to coastal habitats (e.g., Grant’s golden mole, coastal legless skink, pollination corridor for nectivores), extreme micro-climates (e.g., girdled lizard), and for access to littoral, estuarine, and marine environments (e.g., Cape clawless otter). Coastal development increasingly threatens these habitats and disrupts processes. The National Environmental Management: Coastal Zone Bill (B40 2007) states that “much of the rich natural heritage of our coastal zone is being squandered by overuse, degradation and inappropriate management” and thus calls for the establishment of a Coastal Buffer Zone: “(a) to protect the ecological integrity, natural character and the economic, social and aesthetic value of coastal public property; (b) to avoid increasing the incidence or severity of natural hazards in the coastal zone; (c) to protect people, property and economic activities from risks arising from dynamic coastal processes, including the risk of sea-level rise; (d) to maintain the natural functioning of the littoral active zone; (e) to maintain the productive capacity of the coastal zone by protecting the ecological integrity of the coastal environment” Spatially, the Coastal Buffer Zone generally refers to the littoral zone, plus all land within 100 meters of the high-water mark, and all non-residential, commercial, or industrial land within 1 kilometre of the high-water mark37. For simplicity as well as congruence, the FSP coastal corridor was mapped as a 1

36 von Hase, A., Rouget, M., Maze, K., and N. Helme. A Fine-Scale Conservation Plan for Cape Lowlands Renosterveld: Technical Report. September 2003. Summary Report No. CCU 2/03. Botanical Society of South Africa, Claremont. 37 More specifically, the coastal buffer zone is defined spatially as consisting of:

“Owing to extensive habitat loss on the lowlands, the achievement of most process targets – other than for processes that can be sustained in very small to small areas (5 to 1000 ha) – is no longer possible.” – Cowling, R.M., Pressey, R.L., Lombard, A.T., Heijnis, C.E., Richardson, D.M. & Cole, N. (1999b) Framework for a

Conservation Plan for the Cape Floristic Region. IPC Report 9902, Institute for Plant Conservation, University of Cape Town.

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kilometre-wide strip above the mapped coastline, and target was set for natural vegetation within the mapped coastal corridor feature (see Targets section). Where there were significant discontinuities (due to transformed sections) an alternative connection was sought further inland (e.g., a greenbelt or greenway around an urban area) during the design phase.

Significant Wetland Clusters

(From FSP Project: Surface Freshwater Ecosystems. Methodology Report. Snaddon et al., 2008.) Wetlands form stepping-stones for many taxa, including birds, reptiles, invertebrates and amphibians, as they move about the landscape. The functioning of these wetlands as stepping-stones is dependent on the permeability of the surrounding landscape matrix, which generally decreases as the landscape becomes degraded. For the FSP biodiversity assessments, we identified wetland clusters that serve potentially as ecologically viable stepping-stones. Viability was a measure of their proximity to each other, and the relatively natural condition of the surrounding landscape matrix within which the clusters are embedded. Wetland clusters were identified as follows: o All seeps and depressions were buffered by 750 m. This buffer distance is half of the maximum

viable distance between wetlands that would allow the movement of amphibian species characteristic of this planning domain across the landscape (i.e. a maximum of 1.5 km). Where these buffers incorporated more than one wetland, the proportion of natural vegetation within the wetland “cluster” was calculated using the National Land Cover 2000 [or FSP landcover data if available at the time of analysis]. Any wetland cluster with ≥ 75% natural vegetation cover was considered a significant wetland (or seep) cluster.

Wetland and River Buffers

A buffer is a strip of naturally vegetated land along a river or wetland that provides numerous benefits. It is well known that wetland and riparian buffer zones act as effective defence to sensitive freshwater ecosystems – filtering out pollutants and sediments from the surrounding landscape, helping to maintain aquatic habitat conditions, providing habitat to riparian species, and increasing the ability of wetlands to moderate flow and provide other important ecological services. The ecological processes taking place, and their related benefits, increase with increasing buffer width. For example, a minimal buffer may help control water quality by removing the majority of sediments and help maintain water temperature, but effective nitrogen removal and phosphorus control may require a larger buffer, and the provisioning of habitat for riparian species a larger buffer still. Buffers (excluding estuaries) were determined according to size and wetland integrity, as follows (from Snaddon et al, 2008; see source for more detail):

Rank: 1 2 3 4 5 6 7

Size:

>20 ha 200 150 75 50 50 32 32

5 – 20 ha 150 100 75 50 50 32 32

< 5 ha 100 75 50 50 50 32 32

- Sensitive coastal areas as defined by the ECA; - Littoral active zone consisting of unconsolidated material and dune systems; - Coastal protected areas, Admiralty reserves and any section of the seashore which are not coastal public property; - Any piece of land which was zoned for residential, commercial, industrial or multiple-use purposes which falls wholly

or partially within 100m of the high water mark; - Any area of land not zoned as residential, commercial, industrial or multiple use which falls within 1km inland of the

inland boundary of the coastal public property; - Any wetlands, lake, lagoon or dam which falls within the areas above;

- Any part of the sea shore or admiralty reserve which is not coastal public property.

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River buffer width depended on longitudinal zonation and the level of likely human pressures, as follows:

River criterion used

Buffer width (m)

Rationale

Mountain streams and upper foothills of all 1:500 000 rivers

50 These longitudinal zones generally have more confined riparian zones than lower foothills and lowland rivers; and are generally less threatened by agricultural practices.

Lower foothills and lowland rivers of all 1:500 000 rivers

100

These longitudinal zones generally have less confined riparian zones than mountain streams and upper foothills; and are generally more threatened by agricultural practices. These larger buffers are particularly important to lower the amount of crop-spray reaching the river.

All remaining 1:50 000 streams

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Longitudinal zones have not been assigned to these rivers, but these are generally the smaller upland streams corresponding to mountain streams and upper foothills. They are generally smaller rivers than those designated in the 1:500 000 rivers layer, and we assigned these the riparian buffer required under South African legislation.

A 32-metre buffer width corresponds with the buffer zone around wetlands and rivers (measured from the edge), provided in the NEMA regulations (2006), within which at least a basic assessment must be carried out before certain listed activities can take place.

Sub-catchments

Sub-quaternary catchments (referred to as “sub-catchments”) were modelled by the freshwater consulting team and used in several ways:

• as planning units in the river assessment;

• as freshwater conservation zones to which appropriate land-use guidelines will be attached, commensurate to the level of protection indicated by the water resources contained within the sub-catchment; and

• as ecological process areas. All priority sub-catchments identified in the river analysis (for meeting aquatic pattern and process targets) were treated as ecological process areas. These sub-catchments are of particular importance for water retention (yield), water cleansing, flow moderation, erosion and sedimentation mitigation, and ensuring lateral connectivity. The amount of intact natural vegetation in each catchment has direct bearing on its ability to function. Thus, in addition to targeting intact wetlands, wetland clusters, rivers, and minimum buffers, we targeted natural cover in priority sub-catchments. Sub-catchments were modelled using a combination of digital elevation data (US SRTM 90m) and the DWAF 1:500 000 rivers GIS layer. This resulted in 905 sub-catchments across the planning domains. The size of sub-quaternary catchments was variable, ranging from 20 - 287km2, and averaging 49km2. A total of 155 priority (or CBA) sub-catchments were identified.

Edaphic Interfaces

Edaphic interfaces, where different soil or bedrock types meet, can be characterized as hard or soft according to the potential for plant species to move across these boundaries (Desmet, 2004). Hard interfaces – between contrasting types (such as acid and alkaline parent material) – appear to drive ecological plant diversification, whereas soft interfaces – between similar types of parent material –

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seem to support species movement (e.g., allowing ranges to shift response to climatic change). Most recent conservation planning exercises in the Cape Floristic Region have therefore included edaphic interfaces as important ecological and evolutionary process areas. Approaches to mapping them have been similar: using boundaries between vegetation types or broad habitat units, and either classifying each unique combination on the basis of underlying parent material (Driver et al., 2003; Desmet, 2004) or only identifying juxtapositions between strongly contrasting edaphic habitats (Cole et al., 2000; Cowling et al., 1998 & 1999b; also Rouget et al., 2003 and Pressey et al., 2003). Boundaries were generally buffered by 500m on both sides to allow for inaccuracies in mapping and to provide for sections of sufficient size (patches ca. 1000 ha, 50 ha minimum). While vegetation types have typically been used to map edaphic boundaries, the evolutionary importance of edaphic interfaces has been demonstrated at a very fine scale in the quartz-patches of the Knersvlakte (A. Ellis unpublished data, Schmiedel & Jürgens 1999, and Schmiedel 2002, in Desmet 2004). We mapped “hard” edaphic interfaces at the scale of our vegetation types, but also included quartz-patches as a separate mapped feature (see “Biodiversity Pattern: Special Habitats”), and accommodated soft interfaces through design objectives (e.g., to select corridors which follow similar parent material across upland-lowland gradients and macroclimatic gradients). In order to use vegetation types to represent edaphic boundaries it was necessary to describe the soil characteristics (i.e., acid, alkaline, or neutral) and parent material (i.e., the underlying rocky type: sandstone, shale, limestone, granite, etc.) of each vegetation unit. This was done in a matrix by our vegetation mapper, Nick Helme, who also highlighted key combinations of contrasting types (e.g., sandstone + shale, deep sand + granite), and then described the resulting interface as either spatially narrow (i.e., abrupt), intermediate, broad, or mobile (e.g., dune strandveld + flats strandveld). Soil and parent material information were joined to each vegetation type (in GIS), and all polygons turned into lines with each side retaining its set of descriptors. When key combinations of contrasting types appeared in the attribute table, the particular line segment (interface) was assigned to the appropriate spatial category. Each line was then buffered according to its category, where: narrow = 150m, intermediate = 500m, broad = 1000m, and mobile =500m.

Upland-Lowland Interfaces and Gradients

The differences between uplands and lowlands drive many important ecological processes38. Besides having different elevations and associated climates, uplands and lowlands have generally derived from different parent material, with different age surfaces exposed. Thus, upland-lowland interfaces are associated with the ecological diversification of plant lineages and possibly animal lineages, as well as local-scale adjustment of species distributions to climate change. They also facilitate seasonal movements of fauna between upland and lowland habitats. Gradients are complementary to interfaces – making similar contributions to biodiversity processes – but can provide more opportunities for movement and diversification than interfaces because they connect more distant habitats across larger parts of the landscape (Pressey et al., 2003; Figure 10). Heavy transformation in the lowlands, however, has reduced opportunities for extended upland-lowland gradients. Interfaces can be seen as short gradients (Figure 10), and help to keep options open for lowland-upland biotic exchange in the face of ongoing transformation and climatic change (Rouget et al., 2003).

38 These differences are discussed in more detail in Pressey et al., 2003 and Rouget et al., 2003.

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Vegetation types were separated into upland and lowland types by Nick Helme to produce an upland-lowland surface which could be used for both interfaces and gradients (Figure 10 as an example). Due to strong edaphic differences between uplands and lowlands, and a similar method of buffering the relevant vegetation type boundaries (500m), upland-lowland interfaces corresponded to edaphic interfaces. Upland-lowland gradients were not mapped as a separate feature, rather the upland-lowland coverage and coast-to-interior gradients (see next section: Regional Corridors) were used in the design phase to place corridors across gradients while also incorporating other targeted biodiversity features and existing conservation areas.

Figure 10. An example of the spatial implications of upland-lowland interfaces (i.e., short gradients) versus whole gradients.

Regional Corridors

Corridors which operate at a regional scale, linking bioregions and following macroclimatic gradients, have been broadly identified in previous planning efforts (Figure 11) – starting most comprehensively with the CAPE conservation plan39 – and have been reinforced through the Western Cape’s provincial spatial development framework and EIA supplementation project, as well as the implementation of specific CAPE projects, notably the mega-reserve initiatives (e.g., Greater Cederberg Biodiversity Corridor, Gouritz Initiative). Our goal, then, was not to select new corridors for maintaining the geographical diversification of plant and animal lineages in relation to macroclimatic gradients and traversing biogeographic zones, but rather to scale these down to the local level where the majority of land-use decisions are made, and the ability to see regional connections most difficult.

39 Cowling, R.M., Pressey, R.L., Rouget, M., Lombard, A.T., 2003a. A conservation plan for a global biodiversity hotspot—the Cape Floristic Region, South Africa. Biological Conservation 112, 191–216.

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Figure 11. Regional-scale corridors (transformation not shown) representing coastal processes, upland macroclimatic gradients, and coast-to-interior gradients

Key Landscape Linkages & Habitat Connectivity (fine-scale corridors)

Extensive habitat loss in the Cape lowlands has resulted in a highly fragmented landscape and severely threatened vegetation types. No less than seventeen lowland vegetation types are Critically Endangered, with an average of only 18% of their original extent remaining; a further 13 are Endangered. The Cape Lowlands Renosterveld Project calculated that there are roughly 18,000 renosterveld patches remaining in a matrix of agricultural and urban land use, and that more than half of the remaining patches are smaller than a hectare40. While some vegetation types are naturally fragmented, it is not natural for the intervening landscape to be transformed, but rather to be an intact vegetation of a different type (e.g., limestone outcrops in an acid sand matrix). Because of natural variability in scale and degree of resilience, different ecosystem functions begin collapsing at different levels and intensity of fragmentation. In addition, there are lag effects, feedback loops, behavioural and other adaptations, etc. that confound the issue such that we do not have a good understanding of exactly where the critical tipping points (thresholds) are, nor robust ways of measuring fragmentation in a meaningful way. However, we do know that, generally:

- bigger is better; - corridors play a critical role; and - permeability of the landscape is important.

40 von Hase, A., Rouget, M., Maze, K., and N. Helme. A Fine-Scale Conservation Plan for Cape Lowlands Renosterveld: Technical Report. September 2003. Summary Report No. CCU 2/03. Botanical Society of South Africa, Claremont, South Africa.

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The following steps were taken to support these tenets: ♦ Different boundary length modifiers were tested to encourage the clumping of planning units into

larger patches without ostensibly compromising spatial efficiency. ♦ We also hoped to use the “clump target” feature of Marxan to establish a minimum patch size for

supporting the spatial requirements of certain processes (e.g., 500-1000 ha for regular, whole-patch fires41), but could not get the clumping feature to work. We were interested to learn that neither had other conservation planning experts from around the world (pers comm., attendees of the Advanced Marxan course at the 2007 Annual Meeting of the Society for Conservation Biology, Port Elizabeth, South Africa; led by Hugh Possingham, Matthew Watts, and Carissa Klein of The Ecology Centre, University of Queensland, St Lucia, Australia);

♦ An expert mapping exercise was undertaken to identify key landscape linkages (e.g., critical last remaining corridors between intact habitat patches; essential corridors for maintaining ecological processes between features or plant populations) in all planning domains, with the exception of Riversdale. Our expert was Nick Helme, who was suitably familiar with the planning domains having visited them extensively for vegetation mapping and other consulting work. The expert-identified landscape linkages were used in conjunction with other process layers to initially restrict the selection of pattern targets to important ecological process areas (see “Analysis: Pattern within Process”).

♦ Fine-scale corridors were manually selected throughout the landscape, based on summed scores, design criteria (next bullet), and supplementary GIS layers. This approach is discussed further in “Analysis: Iterative Design”.

♦ An overarching objective to secure topographical and habitat linkages both between and within different ecosystems, vegetation types and ecological communities was established, and design criteria were formulated to guide fine-scale corridor placement. Specifically:

- Incorporate lateral connectivity (to ensure interconnectedness between aquatic, riparian, and terrestrial ecosystems).

- Traverse altitudinal gradients (to accommodate local-scale range shifts in the face of climate change).

- Avoid (or minimize) edaphic discontinuity across upland-lowland gradients and biogeographic zones (abrupt soil transitions can be a barrier to plant movement).

- Follow south-facing slopes when possible (they are cooler and thus likely to provide a buffer against rising temperatures).

- When connections have been severed, select the most permeable path. For example, where agricultural fields bisect a potential corridor, select a route through strip fields, fallow fields, or otherwise less transformed veld.

- Connect existing protected areas, as per above design criteria.

Status Information

Landcover

Essential data for mapping the location and current extent of all biodiversity features. Each biodiversity feature included in our assessment is grounded in a real landscape with a history and a future of competing land uses. To make better decisions as we move forward, it is important to get an accurate picture of the current state of our landscapes, and an accurate indication of the location and extent of biodiversity features. Thus, the FSP invested substantial resources and effort in obtaining the most up-to-date and fine-scale landcover data available. Landcover, when combined with the vegetation map, wetland map, edaphic interface layer, or any other feature described in the previous sections, will show what remains where.

41 De Villiers CC, Driver A, Brownlie S, Clark B, Day EG, Euston-Brown DIW, Helme NA, Holmes PM, Job N and Rebelo AB (2005) Fynbos Forum Ecosystem Guidelines for Environmental Assessment in the Western Cape. Fynbos Forum, c/o Botanical Society of South Africa: Conservation Unit, Kirstenbosch, Cape Town.

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The landcover mapping process was lead by Mark Thompson of GeoTerraImage, and is described in: Thompson, 2007. Two components, however, involved close collaboration with the conservation planner: (1) the development of vegetation-specific rules for landcover interpretation, and (2) expert review workshops for the beta version of each landcover product. Prior to the FSP project, the best available landcover product for our planning domains was the 2000 National Landcover (NLC 2000), at 10-meter resolution. The NLC 2000, however, was simply not suitable for fine-scale planning and site-specific decision-making in the highly transformed and fragmented lowlands of the Western Cape. Nor was it current enough. For example, as shown in Figure 12 below, the NLC did not reflect a significant amount of coastal development (yellow in A compared to B; #s 2-4), and in some cases it overestimated the extent of cultivated lands (brown in B compared to A; #s1-3). One reason for overestimating cultivated lands is that conventional (per-pixel) spectral image classification procedures are likely to classify natural bare ground (e.g., exposed coastal sands in naturally low and sparse veld types) as cultivated land when they share the same spectral characteristics (as in 1 below). The initial (alpha) versions of our fine-scale landcover products contained this error on occasion, as well as similar misinterpretations based on spectral information alone. In response, a set of expert-defined rules for the interpretation of cover within different vegetation types was developed in collaboration with Nick Helme, our vegetation mapper. These rules provided a practical context within which to interpret spectral characteristics, based on the expected “pristine state” vegetation structure (e.g., naturally low and sparse? Likely to have a tall (>2m) shrub component? If yes, solid or as a mosaic with low shrubs? Are large stands of tall shrubs (>1ha) likely to be aliens?)

Figure 12. A comparison of (image A) the fine-scale landcover (FSP 2005) at 2.5m resolution, and (image B) National Landcover (NLC 2000) at 10m resolution. Dark green indicates natural cover, bright to light green = near-natural to degraded cover, browns = cultivation, yellow = urban, and white = natural sand exposure. See text for discussion.

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An expert workshop was held to review each alpha version (pre-vegetation rules) and beta version (post-vegetation rules) of the landcover product – to determine which was more accurate, to systematically screen for remaining errors, and to make clear recommendations regarding edits to the final version. In every case, workshop participants determined the beta version to be more accurate. Participants were also extremely helpful in identifying issues to be addressed. Some examples include:

• In all Cederberg Sandstone Fynbos vegetation (veg id 31) change 6 (bare sand/soil) to 22 (disturbed/old lands). This veg type won’t naturally have bare soil – it is a sign of disturbance, usually old lands or severe overgrazing.

• Recode the coastal bare sand (5) in the polygons digitized -- from the Olifants River north to the end of the planning domain (~7kms) and south to Strandfontein (~7kms) -- as 32 (mines: rock).

• In those portions of veg types 40, 38 and 30 that fall within the designated polygon (see N below), change all intersecting fields of 19, 20, or 21 (strip fields) to18 (cultivated fields). These are typically rows of salt bush that have been planted; so although they look like narrow strip cultivation, they are not.

• Some “rooibos” is coming out around Nieuwoudtville proper, which is incorrect. Rooibos is only grown/planted on the sandstones (with one exception that we have created a spatial mask for; see annotated ‘expert edit’ polygons), so we should use the Bokkeveld Sandstone Fynbos veg poly and buffer it outside by 250m to create a spatial mask. Any “rooibos” outside of that mask should be reclassified as cultivated fields (18); except for aforementioned exception.

• Rooibos missed/under-represented – e.g., small patches on deeper sandstones that are mixed with rocky natural bits. See spatial mask and reclassify as “rooibos”.

• Three areas need to be corrected as “fire scars” where they are classified as cultivated (i.e., change all 18, 19, 22, 36, etc. to 12 within each mask). See spatial masks and reclassify.

Once a final version of the landcover was delivered, it was used to derive two additional products: a “transformation” layer and a summarized landcover layer. A transformation layer generally defines what is unavailable for meeting conservation targets: the distinction between transformed and untransformed is therefore an important one. Irreversibly transformed habitat is fairly easy to describe and map. The cut-off point between what is restorable (i.e., reversible transformation) and what has been so severely degraded it is no longer able to recover, however, is less easy42 (Figure 13). Our ‘degraded’ land class fell into this gray area – undoubtedly containing restorable lands of conservation value and also severely degraded, unrecoverable lands of little conservation value. Field verification was not an option over the 4.25 million hectares covered by our planning domains; we therefore dealt with this in two ways: 1. When calculating ecosystem status (see ‘Status Information: Ecosystem Status’) we considered

degraded lands to be transformed. We reasoned that one of the primary purposes of ecosystem status rankings is in giving an indication of which vegetation types are experiencing significant transformation – the sooner before ecosystem functioning is irreversibly compromised the better. Thus, it is important to be precautionary and not artificially inflate the amount of remaining natural habitat by including areas that have likely already lost much of their biodiversity value or ecological functioning (i.e., degraded lands).

2. When mapping areas available for meeting conservation targets we included degraded lands, but with a substantial cost attached (see ‘Analysis: Cost Calculations’). This effectively made intact natural habitat the first choice for meeting targets, and degraded areas a secondary option. We also considered the fact that if an area is “transformed” it is often promoted as developable, and rightly so. It is in our best interests to identify such developable areas and steer development away from important biodiversity areas. In this case, by not combining degraded lands with transformed lands, we reduced the chances of vegetation that is degraded, but still of conservation value, being

42 This is discussed in Driver et al., 2003. Page 29.

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categorically interpreted as developable by land use decision-makers. Moreover, some degraded lands may not be important for biodiversity pattern, but important to processes. One role of a conservation plan is to provide this context by identify regional corridors and ecological process areas which are not discernable on the ground. Similarly, one requires a field visit for determining veld condition, which cannot be obtained from a plan.

In the summarized landcover product, each detailed class (1-47) was assigned to one of five new classes: natural, near-natural, degraded, cultivated or transformed (values 1-5, and 6 for ocean). These groupings are shown in Figure 13 below, and an example of the detailed and summarized landcover products is shown in Figure 14. The summarized landcover was used as a cost surface for applying a “naturalness” discount to planning units based on how intact they are (see “Analysis: Cost Calculations”). This naturalness discount provided a mechanism for driving the selection of planning units with a greater proportion of natural cover to degraded or cultivated cover. Put another way, 100% natural units would be chosen first for meeting targets, but restorable areas are the next best option.

Figure 13. FSP detailed landcover class groupings for the summarized landcover product.

Figure 14. Example (from Saldanha Peninsula planning domain) of the detailed (upper graphics) and summarized (lower graphic) landcover products.

Protected Areas

Despite the fact that existing protected areas in the Cape Floristic Region are biased towards the mountains43, they undoubtedly contribute towards meeting conservation targets. In recent years, too, CapeNature’s Stewardship Programme has added approximately 29,000 ha of lowland Contractual 43 Rouget, M., Richardson, D.M., Cowling, R.M., 2003a. The current configuration of protected areas in the Cape Floristic Region, South Africa—reservation bias and representation of biodiversity patterns and processes. Biological Conservation 112, 129–145.

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Nature Reserves to the protected area network (bringing the lowland total to nearly 158,000 ha). To ensure accounting of protected area contributions, our assessment thus required an up-to-date protected area map. Both logic and good practice44 dictate that only statutory or other similarly secure protected areas be treated as contributing to meeting targets for biodiversity features, while non-statutory or less secure areas represent conservation opportunities. We used CapeNature’s Western Cape Conservation Categories45 (see text box below) to inform level of security: only WCCC 1 areas were considered to contribute to targets. Both CapeNature and South African National Parks were contacted, and their latest protected area layers obtained, reviewed, and merged together.

Ecosystem Status

The South African National Biodiversity Institute (SANBI) has conducted two national assessments of the status of ecosystems (200446 and 200847). Ecosystem status is based on how much of an ecosystem’s original area remains intact relative to three thresholds (Figure 15). Thresholds are determined by best available science, and generally reflect points at which: (CR) so little natural habitat is left that not only has functioning been severely impaired, but species associated with the ecosystem

44 Driver, A., Cowling R.M., and Maze K. 2003. Planning for Living Landscapes: Perspectives and Lessons from South Africa. Washington, DC: Center for Applied Biodiversity Science at Conservation International; Cape Town: Botanical Society of South Africa. 45 Provided by Helen de Klerk, GIS Scientist, CapeNature Scientific Services 46 Driver, A., Maze, K., Rouget, M., Lombard, A.T., Nel, J., Turpie, J.K., Cowling, R.M., Desmet, P., Goodman, P., Harris, J., Jonas, Z., Reyers, B., Sink, K. & Strauss, T. 2005. National Spatial Biodiversity Assessment, 2004: priorities for biodiversity in conservation in South Africa. Strelitzia 17. South African National Biodiversity Institute, Pretoria. 47 Draft results of the 2008 national assessment provided by M. Rouget of SANBI (in file “Eco_status_v2_060408”). Our conservation assessments could not wait for the final 2008 national ecosystem status results.

Western Cape Conservation Category 1 (WCCC 1)41 Protected areas with strong legislative security.

• World Heritage Sites

• Wilderness Areas (in Provincial Nature Reserves Layer)

• National Parks

• State Forest Nature Reserves (in Provincial Nature Reserves Layer)

• Provincial Nature Reserves. Below are the different categories found within this layer: o Island Reserve o Provincial Nature Reserve o State Forest Nature Reserve o Wilderness Areas

• Marine Protected Areas

• Contractual Nature Reserves Western Cape Conservation Category 2 (WCCC 2) Protected areas with some legislative security.

• Local Authority Nature Reserves

• Mountain Catchment Areas

• Private Nature Reserves

• Natural Heritage Sites Western Cape Conservation Category 3 (WCCC 3) Properties that have little or no legislative security. These are voluntary agreements.

• Conservancies

• Biosphere Reserves

• Biodiversity Agreements and Conservation Areas

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are being lost; (EN) the loss of species is imminent and functioning is appreciably impaired; and (VU) significant amounts of habitat have been lost, impairing functioning. SANBI has decided the following with regard to habitat loss, defining ecosystems, and category thresholds: - Loss of natural habitat includes outright loss and severe degradation. - The maximum scale at which ecosystems can be listed is at the national vegetation type level. - Thresholds are:

o CR = < biodiversity target48 remaining natural; o EN = < (biodiversity target + 15% original area of vegetation type) remaining natural; o VU = < 60% of original area of vegetation type remaining natural.

Figure 15. Ecosystem status categories and thresholds, based on the amount of natural habitat remaining intact relative to an ecosystem’s original area.

During the course of the FSP project, SANBI undertook the development of criteria for listing threatened ecosystems in terms of the Biodiversity Act (Act 10 of 2004). One of the criteria is based on ecosystem status as described above – Criterion A: Loss of Natural Habitat. In response to the listing opportunity, the FSP project calculated ecosystem status at the scale of our fine-scale vegetation maps and using our fine-scale landcover to determine habitat loss. Unfortunately, however, our fine-scale ‘ecosystems’ will not be included in the initial list of threatened ecosystems – their uptake will be pursued for the next round of listing. Because our vegetation map is a more accurate reflection of actual differences in not only vegetative structure and composition, but surficial geology and other key ecological attributes, our ecosystem status product is arguably the more appropriate product for informing land-use decisions. Thus, our ecosystem status results (referred to as “local” ecosystem status) were used in the assessments (e.g., for the identification of CR and EN remnants), but should not to be confused with the published national status or list (Figure 16).

48 The biodiversity target represents the proportion of each ecosystem one would ideally like to see included in a formal protected area (NSBA, 2005). The target is generally based on a threshold that varies depending on the species richness of the ecosystem – the greater the richness, the higher the threshold. Biodiversity targets range from 16 to 36%, with the exception of indigenous forest ecosystems for which the range is 30 to100%.

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Figure 16. National ecosystem status results (as per April 2008 calculations) are shown on the left. On the right, the FSP (or local) ecosystem status results are added for the FSP project area (outlined in black).

Analysis

Software

The FSP project used Marxan49 (Version 1.8.10 and later, Marxan Optimized, Version 2.0.2) software in conjunction with Conservation Land-Use Zoning (CLUZ; Version 2) software50, which is a user-friendly interface linking Marxan, the underlying reserve selection algorithm, to ArcView GIS. CLUZ enables the easy importing, display and exporting of data, as well as interactive on-screen planning and editing. Marxan is unique to other conservation planning software (e.g., C-Plan) in that it is able to incorporate boundary cost and planning unit cost. These were key tools for influencing portfolio design. As discussed earlier, boundary cost enabled us to encourage the clumping of units into larger patches and to generally reduce scatter. Planning unit cost enabled us to favour the selection of more intact planning units, higher integrity wetlands, and terrestrial sites within priority catchments and along priority river reaches.

Planning Units

Planning units are the building blocks of an analysis; the configuration of which result in a reserve system design, protected area expansion plan, ecological infrastructure system, etc. As a unit of analysis, they are a fraction of the size of the planning domain, and form a continuous layer of regular or irregular parcels for which the abundance of each conservation feature can be calculated. Typical examples of planning units include squares, hexagons, cadastral parcels, or hydrological units. The size and shape vary with the planning context, and are generally informed by a combination of the scale of planning (i.e., global, regional, national, or local), the resolution of the datasets being used, the objective

49 Ball, I.R., and H.P. Possingham, 2000. MARXAN (V1.8.2): Marine Reserve Design Using Spatially Explicit Annealing, a Manual. Also see: Game, E. T. and H. S. Grantham. 2008. Marxan User Manual: For Marxan version 1.8.10. University of Queensland, St. Lucia, Queensland, Australia, and Pacific Marine Analysis and Research Association, Vancouver, British Columbia, Canada. And: Ardron, J. and C.J. Klein (Eds.), 2008. Marxan good practices handbook. University of Queensland, St. Lucia, Queensland, Australia, and Pacific Marine Analysis and Research Association, Vancouver, British Columbia, Canada. 50 Smith, R.J. (2004) Conservation Land-Use Zoning (CLUZ) software <http://www.mosaic-conservation.org/cluz>. Durrell Institute of Conservation and Ecology, Canterbury, UK.

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of the planning exercise, and the intended use of the outputs (e.g., general prioritization or specific plans for implementation)51. Obviously we are planning at a fine scale, with datasets at a resolution of anywhere from 1:10 0000 to 1:50 000. Our planning objectives and intended uses inspired us to think quite differently about planning unit shape though: we were challenged to develop units that made intuitive sense from a land- and water-management, planning, and decision-making perspective. As a result, our planning units are landform-based objects that average 10 hectares. In our first assessment (for the Saldanha Peninsula), we decided to run the analysis for both hexagonal units and the landform-based units. Hexagons were created using an extension called Repeating Shapes. The development of landform-based units is described in more detail below. The benefits of the landform-based units were immediately evident: they were more spatially efficient (because each unit’s content was more homogenous, rather than random), and they represented recognizable features (e.g., whole fields, wetlands, natural patches) to which management or land-use guidelines can be directly linked (Figure 17). To produce the landform-based units, we used eCognition52 software which utilizes object-oriented image analysis to extract, or segment out, homogeneous objects – groups of pixels – based on their shape and spectral characteristics. At first we segmented the SPOT imagery directly, but soon discovered several advantages to segmenting our summarized landcover instead. With a satellite image eCognition is “seeing” a wide range of hue, saturation and brightness values – often with quite subtle differences which are significant for biodiversity. Because our landcover product was developed to home in on those particular differences (and ignore less relevant ones), it was the more useful starting point for analysis. The summarized landcover was saved as an image file, such that eCognition would ‘see’ each broad class of naturalness, degradation, or transformation as a different value (Figure 17). After initial testing we decided to add wetlands as a second image for

informing segmentation. The landcover alone was not sufficient in illuminating wetlands, and it was important (primarily for efficiency in meeting targets and for linking guidelines) that they be distinguished as separate units. Each functional group of wetlands was given a unique value in the image, so that functionally different but adjacent wetlands (e.g., river channel versus floodplain) would exist as separate units. We also tried adding the protected areas layer as an image for informing further segmentation, but this had several drawbacks (including turning straight boundaries into pixellated boundaries. It was more effective (and simple) to union the protected area polygons to the

51 Ardron, J. and C.J. Klein (Eds.), 2008. Marxan good practices handbook. University of Queensland, St. Lucia, Queensland, Australia, and Pacific Marine Analysis and Research Association, Vancouver, British Columbia, Canada. 52 Definiens eCognition® Server software. Definiens. München, Germany. http://www.definiens.com/ “Technology developed by Gerd Binnig, the 1986 Nobel Laureate for Physics, and his team; it emulates human cognitive processes, extracting intelligence from digital data, such as images. The technology is context-based and identifies objects rather than simply examining individual pixels. It then makes inferences about those objects by looking at them in context.”

Figure 17. Comparison of hexagonal planning units (left) and eCognition planning units (right), displayed over summarized landcover (top) and satellite image (bottom) for the same area.

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segmentation results, and then run a cleaning process to remove slivers. For more detail about the segmentation process, parameters used, etc. refer to Appendix 5. The total number of units ranged from 30K to 125K in our different planning domains, with an average size of 10 ha – the smallest unit being a tenth of a hectare, and the largest about 400 hectares. Table 1. Number and size of planning units for each area of assessment

Planning domain # units avg. size (ha) min. size max. size

Saldanha 43 366 22 0.10 394

Sandveld 63 555 25 0.10 387

Bokkeveld 42 911 7 0.10 121

Upper Breede 126 275 7 0.10 151

Riversdale 99 184 8 0.10 146

Once the planning unit layer was complete, a ‘bound.dat’ file was created in ArcInfo in order to make use of the boundary cost function in Marxan. The bound.dat file can be created through CLUZ, but with the number of irregular planning units used in our assessment this would have taken days of processing time. For more detail on creating the bound.dat file see Appendix 6.

Initial Conditions

Before running Marxan, each planning unit had to be assigned a starting condition of either: “Excluded”, “Conserved”, “Earmarked”, or “Available”. The only sites Excluded outright were 100% urban units (or other hard transformation sites; e.g., mines); which cannot make a contribution to targets and do not belong in a portfolio of Critical Biodiversity Areas. On the other hand, formal protected areas (as described above in “Status Information: Protected Areas”) have already made a contribution towards conservation targets and must be accounted for before proceeding with the selection of additional areas. Our updated protected areas layer was used to select all planning units falling within protected areas, which were then marked as Conserved. Once noted as Conserved, Marxan automatically calculates their contributions to targets, as well as determining the balance required. The Earmarking of units is a potentially useful design tool. When a unit is Earmarked it is selected by the user for the final portfolio of sites, and treated by Marxan as if it were already Conserved: its contributions are accounted for, as well as its costs. So, like Conserved units, Earmarked sites can function as nuclei around which other units are more likely be selected, depending on the influence of the boundary length modifier (i.e., boundary cost versus planning unit cost). We Earmarked all planning units containing features with a target of 100% (listed below), with the exception of Critically Endangered and Endangered remnants, and forest patches. This is because we did not want CR and EN remnants to serve as nuclei; Earmarking them before running Marxan would effectively increase the likelihood of an adjacent degraded or cultivated unit being selected. Instead they were added after other targets had been met. Forest patches were also added at the end, as polygons derived from the FSP landcover, not as planning units. This was a more accurate (and less land-hungry) way of including 100% of forest patches. The following were initially Earmarked:

o Planning units supporting a [qualifying record for a] Restricted plant species. o Planning units supporting a [qualifying record for a] Red Data List (CR, EN, VU-D2, or

Rare) plant species; with the exception of species with more than 15 occurrences, for which targets were set (see “Analysis: Targets – RDL Taxa”).

o Planning units supporting a Rank 1 (‘must have’) wetland. o Planning units supporting mapped focal animal habitat (i.e., Geometric Tortoise and

Antarctic Tern). o Planning units corresponding to a priority river reach (i.e., a river segment selected in the

river analysis for meeting aquatic targets).

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If a planning unit was not Excluded, Conserved, or Earmarked, then it was marked as Available.

Cost Calculations

Every planning unit in Marxan has a cost. Marxan tries to meet all biodiversity constraints for minimum total cost. Hence, the cost setting can be used to favour selection of planning units in certain areas, over other areas. Our general approach was to assign a starting cost to each planning unit (110 000) and then to apply the following discounts:

• Naturalness discount: to lower the cost of selecting pristine units over degraded or transformed units.

o Tabulate area: planning unit (id) = row & landcover summary grid (value) = column o Export result to Excel to calculate the percent of each landcover value (types 1-6), in

each planning unit. o Calculate discount as: (1000 * (% nat + % ocean)) + (900* % near-natural) + (700 * %

degraded) + (100 * % cultivated). Note: % 5 = no discount. The resulting sum is the naturalness discount.

o Join this information to the planning unit theme and copy it across.

• Wetland discount: to preferentially select higher integrity wetlands when all else is equal. o Also begin with ‘tabulate area’: planning unit (id) = row & wetland theme (rank) =

column o Export result to Excel to calculate the percent of wetlands of each rank (1-6), in each

planning unit. o Join this information to the planning unit theme and copy it across. o Now select all planning units where:

� rank 6 wetlands are >33%, and set the discount to 50 (meaning 50% discount); � where rank 4 wetlands are >33%, and set discount to 33; � where rank 3 wetlands are >33%, and set discount to 50; � where rank 2 wetlands are >33%, and set discount to 66; and � where rank 1 wetlands are >33%, and set discount to 100. � It is important that it is done in this order, in case a planning unit is in/has two

wetlands with different integrity scores, the highest will dictate the discount.

• Catchment discount: to lower the cost of selecting units in priority catchments o All planning units within (‘have their center in’) priority sub-catchments receive a

further 50% discount.

• Final cost calculation: o Total cost = 110 000 minus the naturalness discount (= cost1), minus the wetland

discount (e.g., cost1 minus 33% or 50% or 60% of cost1 = cost2), all minus the catchment discount (e.g., cost2 minus 50% of cost2).

o Note: Keep a “total cost” field separate from the active “cost” field in case you want to change or experiment with different cost scenarios.

Alternative Method or Variation: In the Saldanha and Sandveld planning domains, rivers were not included in the wetlands layer and were therefore not used in the creation of planning units. In the other domains, riverine planning units existed and could be earmarked to reflect priority reaches (identified through the river assessment) as well as influence the selection of adjacent units/terrestrial sites. As an alternative, we used a river cost discount of 25% for those planning units which priority rivers reaches pass through. In the Riversdale Coastal Plain planning domain, alien vegetation was such an important issue (and confounding in terms of landcover) that an alien mapping project was commissioned. Unfortunately, only the Hessequa product was available at the time of the Riversdale assessment. This incomplete

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coverage made incorporating the data in an unbiased way difficult. We determined a reasonable approach to be the application of a cost penalty in areas of known high density aliens. Any planning units that were in (‘have their center in’) a block of high density aliens (>75%) as mapped by Conservation Support Services for the FSP project, had their cost increased by 150%.

Feature Abundance

An abundance table contains all of the information about the distribution of each feature. It is organized as a large matrix, with a unique row for each planning unit and a column for each feature. The amount (or abundance) of each feature per planning unit is recorded in the appropriate cell. We populated the abundance table in two different ways – via CLUZ for vector data (using the ‘convert theme to abundance data’ function), and manually for grids using tabulate areas (and then converting from meters to hectares in Excel and joining the results to the abundance table in CLUZ – we found this to be much faster than using the ‘import fields from table to abundance table’ function).

Targets

Targets are the amount of each feature to be achieved in the final portfolio design, and attempt to answer the question: how much is enough to ensure the long-term persistence of this feature, and, collectively, of biodiversity?

Vegetation Types

National targets have been set for vegetation types (as part of the NSBA, based on species-area curves53) and proportional representation of these national targets is called for in the Guideline regarding the Determination of Bioregions and the Preparation and Publication of Bioregional Plans54. The FSP project therefore adopted national targets as minimum representation targets; these ranged from 16 to 40% of the original extent of the vegetation type. Where our FSP vegetation types differed from national types, the target of the most floristically similar type was adopted (Appendix 7). It was important we use the NSBA targets because of the policy implications, their defensibility, and to align with SANBI's planning standards. But because of shortcomings of the [species-area relationship] approach55 it was imperative that we include species-level locality data, as well as set targets and plan for ecological processes.

Critically Endangered and Endangered Remnants

The target for CR remnants was 100% of all remnants meeting our size and condition criteria. For EN remnants the target was 100% of remnants meeting the size, condition, and connectivity criteria.

Wetland Groups

Each wetland group was assigned a target of 24% of the total area of wetlands in that group. This is based on the NSBA wetland type targets. In addition, a target of 100% was set for all Rank 1 wetlands

53 Desmet, P. and R. Cowling. 2004. Using the species–area relationship to set baseline targets for conservation. Ecology and Society 9(2): 11. 54 ‘Guideline regarding the Determination of Bioregions and the Preparation and Publication of Bioregional Plans’ published in terms of the National Environmental Management: Biodiversity Act, 2004 (Act No. 10 of 2004). Notice X of 2007. 55 In presenting the species-area relationship approach to target-setting, Desmet & Cowling (2004) point out several caveats: - Most important limitation is that is says nothing about where to meet targets, & species are not distributed randomly

across the landscape; the importance of locality information is therefore emphasized. - We do not know how well estimates reflect true species richness. - Describes accumulation of species based on single occurrence; the representation of multiple occurrences (our

conservation goal) requires more area. - Rare or patchy species are likely to be missed (i.e., the other 25%). - Assumes the landscape is untransformed (higher frag = higher target). - There was inadequate survey data of all veg types (used nearest neighbour veg type).

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– these are the best remaining examples of each wetland type (i.e., group). We used the percentage of the total area rather than original area as a target because the concept of ‘original extent’ does not apply neatly to wetlands. It would be both difficult and contentious to infer (model) where wetlands used to occur in areas where they no longer do (e.g., urban settings where they may have been filled). When mapping ‘current’ wetlands, however, and a portion is transformed (e.g., ploughed and is now in a field), but is still wet, the entire footprint was generally mapped. In this sense the ‘original’ area is reflected. Other important points:

• Wetlands are a water resource protected under the National Water Act (36 of 1998) and the Conservation of Agricultural Resources Act (43 of 1983), and have Listed Activities associated with them in terms of Environmental Impact Assessment Regulations. We did not, however, target 100% of wetlands.

• Rather, 100% of mapped wetlands will have guidelines linked to them, noting their status and relevant land use restrictions. They will be categorised as “Critical Ecological Support Areas” or “Other Ecological Support Areas” when not selected for meeting targets or otherwise qualifying as “Critical Biodiversity Areas”.

• Because wetlands were divided into planning units, it was sometimes the case that only a portion of a single wetland (e.g., a large floodplain) was selected (perhaps the target was met and no additional area needed, or maybe a portion of the floodplain was ploughed/transformed). A clear recommendation came from our stakeholder review workshops that a single wetland feature should not be split into different categories – if any portion were selected as a Critical Biodiversity Area (CBA), then the whole feature should be reflected as CBA. We have supported this recommendation and, as a result, have significantly increased the area of CBA wetlands over and above what was selected to meet targets alone. For example, the total mapped wetland area for Riversdale Coastal Plain was 47,244 ha. After running Marxan, 24,707 ha were selected for meeting wetland group targets. Once all selections were extended to whole wetland features, however, the total CBA area increased to 37,405 ha.

River Types

A target of 20% of each type in intact river systems was used. See Snaddon et al., 2008 for more detail.

Indigenous Fish Species

From Snaddon et al., 2008: The target was 2 fish sanctuaries per species, with the following noted:

• “Viable”/best populations chosen by experts;

• Wherever possible on different river systems;

• Used as anchors in the plan, then representation of river types were applied to pick up the missing pieces;

• Habitat requirements & connectivity included (e.g., mixture of mainstem & tributary habitat; upstream zones);

• Importantly, some species persist because of discontinuity.

Indigenous Forest Patches

A target of 100% of was used and applied only to mapped forest habitat (i.e., trees) not entire forest vegetation types (see Biodiversity Pattern: Indigenous Forest Patches for further explanation). This target reflects the fact that the National Forests Act (84 of 1998) protects all trees in indigenous forests.

Red Data List Plant Taxa

For CR, EN, VU-D2 and Rare species (or other unique taxa) the representation target was 100% of all occurrences documented by CREW (their ‘rares’ and ‘specials’ data, including Cape Lowlands Renosterveld Project data), or in recent herbaria (PRECIS, records >1980), or occasionally directly from the collector (in cases where the record had not yet been entered in PRECIS); AND with an

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accuracy of 500m or better. Occurrence records from the Protea Atlas were sometimes too numerous to target at 100%. We therefore set a target of 15 occurrences (with requisite accuracy) per species (based on targets established by the CAPE project), except for CR species, which retained a target of 100%. For those species with >15 occurrences we also screened the records and removed from the selection process any occurring in a degraded location (planning unit) and/or as small populations (i.e., number of plants < 10, from the ‘POP’ field in Protea Atlas database).

Restricted Plant Taxa

A target of 100% of all mapped occurrences was used. These occurrences had, at this point, already been screened to remove any of questionable status (i.e., ‘extinct’ localities versus ‘extant’).

Focal Animal Species

As discussed in the previous ‘focal animal species’ section of this report, most data were not suitable for use in the biodiversity assessment, except for general referencing. Those habitat data which were suitable were targeted as follows:

• Geometric tortoise – 100% of all planning units which are at least 60% intact and within 250m of the Geometric tortoise sites mapped in the Sensitive Lower Vertebrate Areas layer.

• Antarctic tern – 100% of all planning units which are at least 60% intact and fall within (‘have their centre in’ the expert-mapped habitat polygon (a single, critically important roost site).

• Suite of amphibian species – 100% of all planning units within significant wetland clusters which have an accurate, documented record of a focal, threatened or protected amphibian species, and which are at least 60% intact. (Note that in the Upper Breede and Riversdale planning domains, indigenous fish records were also used for targeting significant wetland clusters, due to a paucity of amphibian data. Obviously this does not imply that they are suitable amphibian habitat, but rather highlights the role they play in maintaining fish habitat: intact wetlands adjacent to rivers have a direct and positive impact on river health).

Special Habitats or Features

A target of 50% of the total mapped extent of each special habitat feature was used. This does not have an ecological basis, but was reached through experimentation. A target of 100% (and even 75%) was clearly too high: some special habitat polygons had been coarsely drawn by the vegetation mapper and therefore included bits of degraded or transformed veld; other special habitats (e.g., Knersvlakte quartz patches) had been acquired from other projects and were located in visibly transformed areas (e.g., vineyards in the Olifants River valley). A target of 25% did not capture enough special habitats.

Coastal Corridor

A target of 60% of the mapped corridor was used. The mapped corridor included everything within 1 km of the coastline (i.e., the ‘original extent’ of this ecological process area). A target of 60% therefore corresponds to a broad ‘top-down’ persistence threshold56 for function as it relates to fragmentation.

Significant Wetland Clusters

As above for ‘focal animal species’: 100% of all planning units within significant wetland clusters which have an accurate, documented record of a focal, threatened or protected amphibian or indigenous fish species, and which are at least 60% intact.

Priority Sub-catchments

Priority sub-catchments are those identified in the river analysis as required for meeting river type and indigenous fish targets, through appropriate catchment management and protection measures. All priority sub-catchments are Critical Biodiversity Areas and will have guidelines which speak to the level

56 Desmet, PG

and RM Cowling. (In prep) Targeting ecological processes in systematic conservation planning: A top down

approach.

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of protection that requires in term of restricted activities. However, it does not make sense to select the entire land area and all associated biodiversity and non-biodiversity features (i.e., towns) as CBA. Thus, in terms of terrestrial habitat within priority sub-catchments, a target of 25% was used.

Wetland and River Buffers

A target was not set for wetland and river buffers per se, but 100% of the mapped buffers (see previous ‘wetland and river buffer’ section) associated with CBA wetlands and rivers were assigned CBA Buffer status. Other buffer categories are Critical Ecological Support and Other Ecological Support. The issue of buffers was discussed at length, and different options explored. For example, we considered selecting all intact portions of buffers as CBA. Yet the non-intact (e.g., cultivated, urban) portions are just as important to manage and use appropriately. We concluded that the entire buffer needs to be portrayed as a critical management zone for maintaining the structure, ecological functions, and biological composition of the wetland or river it is associated with – this is the intent of the CBA Buffer designation.

Edaphic Interfaces

A target of 25% of the original extent (i.e., mapped extent) of each interface type (narrow, intermediate, broad, or mobile) was used.

Upland-Lowland Interfaces and Gradients

As discussed in the previous ‘upland-lowland interface and gradients’ section, no spatial component of these ecological processes was assigned a numeric target. Rather a set of design objectives encompassed the goal of representing these processes with corridors located at the upland-lowland interface, and across upland-lowland gradients. It is noted, however, that upland-lowland interfaces often correspond with edaphic interfaces, and were thus indirectly targeted.

Regional Corridors

Similarly, regional corridors were not assigned a numeric target in terms of a percentage of their mapped areas, but the goal of representing each regional corridor with at least one fine-scale corridor was an explicit one. We therefore ‘targeted’ the selection of one fine-scale corridor per regional corridor area.

Key Landscape Linkages & Habitat Connectivity (fine-scale corridors)

The following types of fine-scale corridors were ‘targeted’ (i.e., built into overall CBA design) – those which:

- incorporate lateral connectivity; - traverse altitudinal gradients; - avoid (or minimize) edaphic discontinuity across upland-lowland gradients and

biogeographic zones; - follow south-facing slopes; - connect disconnected habitats identified in our expert-mapping exercise (linkages); - connect existing protected areas; and - represent regional corridors.

There was much discussion around the spatial parameters of corridors. For example, should a minimum viable width be defined? Should we identify ‘core’ areas and corridor ‘buffers’? In the end, corridors were largely defined by the grain of the surrounding landscape and degree of transformation (Figure 18) – in highly fragmented areas, the corridors could become quite narrow and tenuous (e.g., 50 m); and in highly intact areas, quite wide (e.g., 2000 m). We generally strove for a minimum of 300 m, but where a smaller corridor existed in a threatened ecosystem or other key area – and made a contribution to pattern targets or process objectives – we felt that the physical presence of a linkage

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was of value and should not be demoted to ‘other natural vegetation’ (vis a vis final CBA map categories) simply because it was not 300 meters wide. Where habitat connectivity had already been lost, however, we took one of two approaches: ♦ For relatively short breaks in connectivity, we would look for the most permeable path and

highlight the intervening land as CBA, as long as no hard transformation was present. The interpretation is that this site, although degraded or cultivated, still potentially contributes to an ecological process and should not be put towards any more intensive land use – and ideally, it would be restored to as near to natural as possible. These short breaks in connectivity were typical of the Sandveld domain.

♦ For longer breaks in connectivity, it was not practical to, for example, highlight several kilometres of agricultural land as CBA in order to create a corridor. This was often the situation in the Riversdale Coastal Plain, particularly in the renosterveld and along the Gouritz River. Remaining patches were identified, hopefully to serve as ‘stepping-stones’, but an alternative approach is needed regarding intervening lands under production. One plausible solution is to add these lands to ‘Critical Ecological Support Areas’ – indicating, as above, that (from a biodiversity perspective) they should not be put to more intensive land-uses.

Figure 18. Example (Nieuwoudtville) of the variable scale of CBA patches (black outlines; ha) and corridor width.

Pattern within Process

Having successfully identified and mapped all biodiversity surrogates, created a transformation layer, updated protected areas, calculated ecosystem status, generated planning units, entered starting conditions, included cost data, and populated the abundance and target tables, it was finally time to run Marxan. However, after a few experimental runs to test our cost values and boundary length modifier, it became apparent that it would be useful to have some mechanism to inform design at the outset, and to reduce options in least threatened areas of the planning domain. As shown in Figure 19 for Nieuwoudtville/Bokkeveld – the most extreme example of all domains – there are many options (shades of yellow) for meeting targets across much of the landscape. Regional corridors and expert-

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mapped landscape linkages came to mind as potentially useful design informants, except that they are too coarsely mapped to be ‘hardwired’ into the plan (i.e., earmarked). We reasoned, however, that if land outside of these corridors were excluded from the analysis, then Marxan would be forced to look within the broad corridor areas to meet targets. Planning units which are able to meet both pattern targets and process or design objectives should end up with higher scores. Following this line of thought, we decided to merge all process layers together (e.g., regional corridors, expert-mapped corridors, edaphic interfaces, wetland clusters, priority sub-catchments, major river and wetland buffers, coastal corridor) and set all planning units outside of this process template as ‘excluded’ (Figure 18). We then ran Marxan for pattern targets only. The result was as hoped: constraining the area available for meeting pattern targets to mapped process areas guided us towards the most effective locations for fine-scale corridors. Those planning units selected in 100% of the runs for meeting pattern targets within the mapped process ‘landscape’ provided the foundations of our portfolio. Clearly additional areas were needed – some pattern targets, for example, were not met at all within the process areas – but we had a clear and practical starting point for an iterative design process.

Figure 19. Early results for the Bokkeveld planning domain, prior to design. Summed score refers to the number of times each planning unit was selected as part of the final solution, out of 100 runs (of 100 million iterations).

Iterative Design

As discussed above, constraining the options for meeting pattern targets to our mapped process areas, highlighted certain parts of the landscape where representation and persistence goals could both be achieved. Using Marxan’s summed solution output – which records the number of times each planning unit was selected as part of the best solution – we began ‘locking in’ (earmarking) planning units. We started with those units with a 100% selection frequency in our ‘pattern within process’ scenario, and which also met unmapped design objectives. Once the most obvious planning units were earmarked, we ran Marxan for all targets but with the previously ‘excluded’ areas now ‘available’. Based on these new results, the ‘pattern within process’ scenario results, our design criteria, and supplementary GIS layers (i.e., upland-lowland surface, fire-dependent ecosystem layer, focal animal localities, roads layer, detailed landcover) we continued to manually build our Critical Biodiversity

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Areas portfolio. Marxan was periodically run and re-run to generate new summed solution results and to check progress towards target achievement. For example, Figure 20A shows where two fairly clear corridors initially emerged based on summed scores (1), and where additional corridors later emerged (2). As fine-scale corridors and irreplaceable patches were identified and earmarked, options diminished (B and Figure 21).

Figure 20. Example of how summed solution scores informed fine-scale corridor design. See text for discussion.

It is immediately apparent from the final CBA portfolios (Figure 23) that corridors and connectivity were emphasized in the planning process. We make no apologies for the deviation from classical models for reserve design – this was not a reserve design exercise. Out of necessity the maps reflect the complexity and untidiness of many real landscapes, which do not lend themselves to the neat zonation of biosphere reserve models. For a more relevant land planning model we might, however, refer to the aggregate-with-outliers principle, which states that one should aggregate land uses (e.g., consolidate protected areas), yet maintain corridors and small patches of nature throughout developed areas57. Maintaining corridors and outliers is an essential strategy in the face of a changing climate; and the Fine-Scale Biodiversity Planning project has, for the first time over such a large area of the Cape Floristic Region, designed an ecological infrastructure to pursue this objective.

57 Forman, Richard T.T. Land mosaics: the ecology of landscapes and regions. Cambridge University Press. 1995. Cambridge, United Kingdom.

Figure 21. An example of how options (shades of yellow) diminished as corridors were designed.

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CBA Map Product Development

Establishing Map Categories

On August 21st & 22nd 2007 a workshop was held for FSP’s conservation planning technical reference group to discuss the term ‘Critical Biodiversity Area’: what we mean by it, what should be mapped, and what categories should appear on the map. Other conservation plans have, for example, had different levels of CBA (see Appendix 8). In terms of process, each biodiversity feature (or map layer) to be included in our assessment was discussed separately and placed within the proposed CBA framework, consisting of six broad categories (consistent with the Guidelines for Publishing Bioregional Plans): CBA Level 1; CBA Level 2; Other Important Biodiversity Areas/Supporting Biodiversity Areas; Other Natural Areas; Protected Areas; and Transformed Areas – although the latter two did not require discussion. The idea was to let the features help define the categories (i.e., a bottom-up approach to test the framework). The following definitions emerged: ♦ CBA 1a = Any area that is irreplaceable in terms of meeting representation/pattern targets. ♦ CBA 1b = All ‘best design’ sites in terms of meeting the balance of pattern targets. ‘Best design’

refers to their ability to also meet persistence/process objectives. ♦ CBA 2 = Any area required to meet process targets, or is ‘targeted’ for persistence objectives. This

includes any intact EN vegetation or forests not already captured in CBA 1 for pattern targets. ♦ Key Support Areas = All sites not explicitly targeted for biodiversity pattern or process, but that

support key resources (e.g., water) whose basic structure and ecological function require protection. When these categories were applied to the first set of results – for the Saldanha and Sandveld planning domains – it was immediately apparent that the CBA Level 1a and 1b, and Level 2 distinctions were significantly muddied by our ‘pattern within process’ and iterative design approaches. Pattern and process goals had become so integrated that making the distinction was not only difficult, but required Marxan be run again with just pattern targets and no process constraints in order to highlight ‘irreplaceable’ (technically not irreplaceable, but rather 100% selection frequency) units for biodiversity pattern (i.e., 1a). Our attempts to identify or redefine Level 1b were unsatisfactory. That the result was both visually and conceptually confusing was confirmed in our Stakeholder Review Workshops for Saldanha and Sandveld (see next section): the CBAs were well-received as a whole, but the distinctions between Levels 1 and 2 were not only unhelpful, the Level 1 sites had the effect of undermining the importance of Level 2 sites. The interpretation was that Level 2 sites were negotiable. We therefore eliminated the Level 1 and 2 distinctions. Also as a result of our stakeholder review workshops, as well as a follow-up aquatic work session, we decided to differentiate between aquatic and terrestrial CBAs, add a ‘CBA Buffer’ category for river and wetland buffers, and split the Key Support Area category into ‘Critical Ecological Support Areas’ and ‘Other Ecological Support Areas’. All wetlands and rivers would be shown as at least Other Ecological Support Areas, and those falling within priority sub-catchments (but not selected as CBA) would be elevated to Critical Ecological Support Areas. Buffers would correspond to the main category, but be shown as hatching so that the underlying natural and transformed portions are distinguishable. These decisions were all driven by both what they communicated visually, and a need to balance simplicity with meaningful land-use distinctions. Once the above-mentioned adjustments were made, the CBA categories seemed to work well (Figure 22). No other significant changes were made as a result of the three remaining stakeholder workshops (Nieuwoudtville, Upper Breede, and Riversdale).

Figure 22. Final CBA Map categories.

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Stakeholder Review and Finalizing Critical Biodiversity Areas

Stakeholder review workshops were held on the following dates, to review the draft CBA map products for the following planning domains and municipalities: ♦ November 13th, 2007: Saldanha Peninsula (Saldanha Bay Local Municipality) ♦ November 14th, 2007: Northwest Sandveld (Bergrivier, Cederberg, and Matzikama Local

Municipalities) ♦ May 15th, 2008: Nieuwoudtville/Bokkeveld Plateau (a portion of the Hantam Local Municipality) ♦ June 12th, 2008: Upper Breede River Valley and Riversdale Coastal Plain (Witzenberg, Breede

Valley, Breede River Winelands, Hessequa, and Mossel Bay Local Municipalities) The workshops generally consisted of introductory presentations – to the FSP project, the data, the systematic conservation planning process, and the map products – followed by a hands-on review session of the maps. A draft CBA map was printed out on an A1 sheet for each municipality and participants were asked to consider three questions:

1. Is this useful for informing site-specific land use decisions? Why? Why not? 2. In general, are the right kinds of places highlighted? 3. Are specific areas missing? Or some over-emphasized? Other comments? Please annotate the

maps with any information, ideas, concerns, etc.! Minutes are available for each workshop, along with a record of the comments received on each hardcopy map relating to the above questions. Feedback is broadly summarized as follows:

Question 1: Useful for informing site-specific land-use decisions?

There was a lot of positive feedback in response to this question. Generally everyone agreed that the maps were useful (or “very useful!”) for informing site-specific land use decision making. They emphasized that the right kinds of information were included and at a useful scale, but that land-use guidelines must accompany the maps to aid in interpretation, and GIS layers must be available. Other comments were to the affect that “this must be a living document/product” and “the maps will only be useful if curated and updated”.

Question 2: In general, are the right kinds of places highlighted?

There was agreement that, yes, the right kinds of places were selected overall. In some cases the ‘yes’ was qualified by pointing out an issue of concern. Issues emerged pertaining to: ♦ urban areas – CBAs within urban edges were questioned: Shouldn’t we concentrate development

within urban bounds and therefore not highlight CBAs? Did the prioritization factors differ inside versus outside urban edges? All parts of the landscape were treated equally. Our product does not attempt to negotiate between competing land uses – that process must take place in the development of an SDF, EMF, and other multi-sectoral planning fora – our product is a biodiversity informant for feeding into such a process. It is not the objective of these products to resolve conflicts, but rather to highlight the fact that there may be a conflict at all, and to provide better information on which to base decisions, to determine the need for ground truthing, and to encourage planning which seeks to avoid, minimize or mitigate against the loss of biodiversity. We did, however, try to design the portfolio such that, when there were options, CBAs were not selected within urban areas. The most common reason for CBAs appearing within urban areas is the presence of CR or EN vegetation – which had a target of 100%. In these cases, if the landcover erroneously classified residential yards or biodiversity-devoid open space as ‘natural’, then it would have come out as a CBA. CBA maps are in no way intended to replace site visits! It could be useful though to manually screen the landcover within all urban areas and correct any obvious errors.

♦ areas of potential or known conflict – e.g., where records of decision had already been made, or development applications were pending: What do we do about these areas? Wish we had had this information earlier! As above, when areas of conflict arise, this product is simply intended as an informant to the decision-making process. Unfortunately, if a decision has already been made there is not much that can be done. If a case arises where biodiversity offsets are under consideration, then this product could inform the location of receiving areas.

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♦ portions of wetland features – sometimes, within a single wetland feature (e.g., Hartenbos River valley bottom wetlands) there would be CBA portions separated by non-CBA portions: Shouldn’t we highlight entire systems? What do dark blue and light blue in the system indicate? As discussed in ‘Analysis: Targets - Wetland Groups’, this is a result of aquatic features/systems being broken up into multiple planning units. Sometimes not all planning units in a single system were required to meet the target (number of hectares) for that type, and thus not all were selected as CBA. As a result of further discussions around this issue (and the implications thereof, i.e., significantly over-achieving wetland targets, selecting degraded portions as CBA) we decided to assign CBA categories to entire wetlands, not different categories to different portions.

♦ design elements in the Riversdale Coastal Plain planning domain – specifically the apparent lack of corridors corresponding to those mapped for the Gouritz Initiative (GI): Gouritz River corridor, koppieveld corridors, & coastal corridor. The design phase of the Riversdale plan was still incomplete at the time of the workshop; not all process objectives had been met in the draft presented. These were later completed with the coarse-scale Gouritz data helping to inform their general location (as other regional corridor information was consistently used). However, significant transformation (e.g., a ~13 kilometre stretch along both sides of the Gouritz River, over half the 109 000ha koppieveld area) means that substantial portions of the corridors shown in the GI report and GIS files are not actually intact.

Question 3: Are specific areas missing? Or some over-emphasized? Other comments?

All specific areas identified as missing or inappropriate, or otherwise receiving comment, were captured on the hardcopy maps and documented in an addendum to the workshop minutes. Each comment was individually reviewed by the conservation planner. In general, comments can be characterized as: ♦ Specific examples of issues highlighted above in Question #2. ♦ Incorrect place names, missing labels, missing dams (accidentally not shown on the draft Breede &

Riversdale Maps). ♦ Specific examples of the confusion around CBA 1 versus CBA 2 (see ‘Establishing Map Categories’

above). ♦ Verification of important areas, known rare species occurrences, important linkages, etc. ♦ Known degraded areas or other landcover information. ♦ Places that potentially should be CBAs and that should not be CBAs.

Each comment of this type was investigated to understand why a CBA had or had not been selected. In cases where the comment indicated a site should not be a CBA, alternative options were investigated if they existed (and if the reason why it should not be a CBA was significant enough, e.g., the site had been developed since the 2005 SPOT imagery was taken). For example, if the site was not ‘earmarked’ as contributing to targets of 100%, then it was likely either selected by Marxan as an efficient option for contributing to one or more other targets, or it was selected as contributing to a process or design objective. It is important to understand that selecting alternatives is generally a less efficient approach (i.e., more sites are required to make the same contribution as the site originally selected). In the case of potentially ‘missing’ CBAs, again, the reason given for its inclusion as a CBA was considered and weighed against the alternative scenarios resulting from its inclusion or exclusion, particularly regarding the degree to which the different scenarios met targets and objectives, as well as overall efficiency.

Other general comments included: ♦ Other Ecological Support Areas – These seem to be mostly or all in riparian areas: There should be

some in terrestrial habitat, especially in cultivated landscapes to connect up fragments of CBAs. Need to have corridors through cultivated areas where tiny fragments and koppies are included as part of CBA. Yes, CESAs and OESAs are, at this point, only comprised of aquatic features. The idea of adding terrestrial habitat to these categories is certainly something to consider – particularly in the case of linking CBA fragments through cultivated areas. However, this is a substantial task over such a large planning domain, requiring careful consideration of the areas selected and also requiring a degree of ground-truthing – making it beyond the scope of the FSP project at this time. Also see ‘Analysis: Targets – Habitat Connectivity’.

♦ Where rivers/tributaries flow through cultivated lands and are categorized as ‘Other Ecological Support’, is this because system has been completely disturbed and is not functional anymore? Is there no need to intervene?

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The designation Other Ecological Support Area does not necessarily indicate that a system is completely disturbed and not functional, nor that there is no need to intervene. What it does indicate is that the feature (or system in this case) was not required to meet conservation targets, is not within a priority sub-catchment, and is of lower conservation priority than CESAs and CBAs. This means that a higher than normal (i.e., what is legally mandated; basic duty-of-care) level of protection is not required (e.g., formal protected area or significantly restrictive land-use regime), but certainly doesn’t imply no protection or intervention is needed. The guidelines attached to the final product will reflect this.

♦ How functionally viable are CBAs? Are they viewed as being functionally viable now? Again, it depends on the specific site/CBA. Also, site or individual patch viability is very difficult to define. Functionally viable in terms of what? The ecosystem services provided (e.g., pollination)? The habitat requirements of an individual plant or animal? A population of plants or animals? Which species? For the next 5 years? 50 years? 500 years? “Viability” or “functionality” will be different for each of these things. Viability at a coarser (regional or landscape or ecosystem) scale, however, is often inferred from a series of thresholds that speak to the amount of habitat required to retain the majority of species expected to occur in that particular ecosystem, or the area over which ecological processes and disturbance regimes operate. The conservation targets established for this project are based on such thresholds – from the scientific literature or expert opinion. Taken as a whole, then, the entire portfolio of CBAs is viewed as being functionally viable in terms of representing the majority of species and maintaining key ecological processes in the long-term.

SUMMARY OF RESULTS In total, the area of assessment (planning domains) cover just under 4.25 million hectares of the Western Cape Province and Cape Floristic Region. The product domains (municipalities) total 3.76 million hectares, of which Critical Biodiversity Areas amount to 1.13 million hectares, or 30% of the municipal areas – ranging from 26% in Breede River Winelands to 37% in Matzikama (Table 2). Transformed areas comprise 32%, protected areas 5% and other natural areas 33%. Table 2. Results of the systematic biodiversity assessment per municipality, in terms of amount of protected area, Critical Biodiversity Areas, areas with no natural vegetation remaining, and other areas with natural vegetation remaining.

Local Municipality

Protected Areas Critical

Biodiversity Areas No Natural Remaining

Other Natural Remaining

Total

(ha) (%) (ha) (%) (ha) (%) (ha) (%) (ha)

Matzikama 25,876 5% 203,435 37% 104,333 19% 221,564 40% 555,209

Cederberg 38,170 5% 213,706 29% 175,787 24% 306,320 42% 733,982

Bergrivier 18,299 4% 128,482 29% 245,502 56% 48,592 11% 440,876

Saldanha Bay 9,226 5% 56,480 32% 97,951 55% 13,095 7% 176,752

Witzenberg 30,063 11% 64,912 23% 78,789 28% 111,316 39% 285,080

Breede Valley 23,531 8% 94,975 32% 53,488 18% 127,339 43% 299,332 Breede River Winelands 10,883 3% 87,860 26% 69,541 21% 164,698 49% 332,982

Hessequa 22,155 4% 164,774 29% 255,169 45% 130,814 23% 572,912

Mossel Bay 12,001 6% 67,413 34% 75,656 38% 45,891 23% 200,960

Nieuwoudtville 4,789 3% 46,731 29% 30,616 19% 80,733 50% 162,868

Total: 194,994 5% 1,128,769 30% 1,186,831 32% 1,250,362 33% 3,760,956

Through a systematic conservation planning approach, we successfully identified critical areas for meeting all FSP biodiversity pattern and process targets, in less than a third of the landscape (Figure 23).

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Figure 23. Critical Biodiversity Areas identified in the FSP systematic biodiversity assessment, covering 4.25 million hectares in the Cape Floristic Region, of which CBAs comprise 1.19 million hectares.

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