Ecosystem function and service quantification and valuation in aconventional winter wheat production system with DAISY modelin Denmark

Bhim Bahadur Ghaley a,b,n, John Roy Porter a,b

a Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 30, DK-2630 Taastrup, Denmarkb Copenhagen Plant Science Centre, Faculty of Science, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark

a r t i c l e i n f o

Article history:Received 10 July 2014Received in revised form1 August 2014Accepted 20 September 2014

Keywords:Soil organic matterWinter wheat productionInformed decision-makingEcosystem functionEcosystem service

a b s t r a c t

With inevitable link between ecosystem function (EF), ecosystem services (ES) and agriculturalproductivity, there is a need for quantification and valuation of EF and ES in agro-ecosystems.Management practices have significant effects on soil organic matter (SOM), affecting productivity,EF and ES provision. The objective was to quantify two EF: soil water storage and nitrogen mineralizationand three ES: food and fodder production and carbon sequestration, in a conventional winter wheatproduction system at 2.6% SOM compared to 50% lower (1.3%) and 50% higher (3.9%) SOM in Denmark byDAISY model. At 2.6% SOM, the food and fodder production was 6.49 and 6.86 t ha�1 year�1 respectivelywhereas carbon sequestration and soil water storage was 9.73 t ha�1 year�1 and 684 mm ha�1 year�1

respectively and nitrogen mineralisation was 83.58 kg ha�1 year�1. At 2.6% SOM, the two EF and threeES values were US$ 177 and US$ 2542 ha�1 year�1 respectively equivalent to US$ 96 and US$1370million year�1 respectively in Denmark. The EF and ES quantities and values were positively correlatedwith SOM content. Hence, the quantification and valuation of EF and ES provides an empirical tool foroptimising the EF and ES provision for agricultural productivity.

& 2014 Elsevier B.V. All rights reserved.

1. Introduction

Ecosystem functions (EF) are responsible for ecosystem services(ES), which are goods and services, that humans benefit from thenature and are inevitable for the well-being of human population(de Groot et al., 2010). The ES includes our basic necessities likefood, fodder and energy production (provisioning ES), watersupply and climate regulation (regulating EF), primary productionand nutrient cycling (supporting EF) and recreation and aestheticvalue (cultural ES) (Ghaley et al., 2013). The demand for ES is everincreasing due to increase in population to meet the basicnecessities of food, fodder, energy and water. The unabatedexploitation of the available natural resources to meet the food,fibre and energy demands of the growing population has degradedEF and dwindled the supply of ES (UKNEA, 2011; TEEB, 2010;Costanza et al., 1997) and the recent stock-taking reported 60%decline in global ES (MEA, 2005) in terms of degraded agriculturalland with reduced crop harvests, overfished rivers and coastlines,drastic changes in nutrient cycles etc. and hence, there is a need

for quantification and valuation of EF and resultant ES. In agro-ecosystems, the provisioning, regulating and supporting EF and EShave immense significance for production of food, fodder andenergy and management practices have significant influences on‘bundle’ of EF and ES due to trade-offs and interdependenciesamong them. Hence, management effects at field and farm scaleare determining factors for EF and the supply of ES. Managementeffects on crop productivity, EF and ES provision, can be suitablyhandled by ES model like InVEST (Goldstein et al., 2012), cropmodel like APSIM (Zhao et al., 2014) or dynamic and deterministicmodel like DAISY (Bruun and Jensen, 2002; Hansen et al., 2012).The DAISY model performance is robust across environments andmodel comparisons have proven its superiority over other models(Gjettermann et al., 2008; Palosuo et al., 2011) which provides asuitable tool to quantify and valorise EF and ES in the prominentagro-ecosystem like conventional winter wheat productionsystem. In the European Union, the conventional wheat productionis one of the most dominant practice cultivated in 23.5 million ha,constituting 41% of the total cereal acreage (57 million ha) and21.8% of total arable land (107.7 million ha) (http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/ accessed on 06.03.2014). Given the sheer wheat acreage, management regimes canhave significant influences on EF and the supply of ES. Manage-ment practices like crop rotation, inclusion of grass into rotation,

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Ecosystem Services

http://dx.doi.org/10.1016/j.ecoser.2014.09.0102212-0416/& 2014 Elsevier B.V. All rights reserved.

n Corresponding author at: Department of Plant and Environmental Sciences,Faculty of Science, University of Copenhagen, Højbakkegård Allé 30, DK-2630Taastrup, Denmark. Tel.: þ45 35 33 3570; fax: þ45 35 33 34 88.

E-mail address: bbg@life.ku.dk (B.B. Ghaley).

Ecosystem Services 10 (2014) 79–83

incorporation of catch/green manure/legume crop, residue man-agement and input of manure and fertilizer effects SOM content(Brock et al., 2011). SOM content is a measure of soil fertility as thesource of plant nutrients, food for microbes and retains moistureand changes in management practices have significant effects oncrop productivity and soil processes and thereof on EF and ESprovision (Ghaley et al., 2013). Hence, the objective of the study isto quantify two EF, viz. soil water storage (regulating EF) andnitrogen mineralization (supporting ES) and three ES, viz. food andfodder production (provisioning ES) and carbon sequestration(regulating ES) in a conventional wheat production system underthe current SOM of 2.6% compared to 50% lower (1.3% SOM) and50% higher (3.9% SOM) SOM in Denmark by the dynamic soil–plant–atmospheric DAISY model.

2. Materials and methods

2.1. Trial site description

The trial site was located at Taastrup at an experimental farm(551400N, 121180E) under the Department of Plant and Environ-mental Sciences, Faculty of Science, University of Copenhagen.A trial was set-up on winter wheat and the conventional manage-ment practices and the soil properties are provided in Table 1. Thesoil properties are based on four soil sample replicates taken to adepth of 25 cm to represent the plough layer. Sand, silt and claycontent were 78.1%, 20% and 18%, respectively. Bulk density andsoil moisture content were determined from 100 cm3 soil cores,which were weighed, dried at 801 for 72 h and re-weighed. Soilswere analysed for total carbon and total nitrogen (modified Dumasmethod) with CHNS/O analyser (Flash 2000, Thermo FisherScientific, Cambridge, UK) and soil temperature was taken with asoil thermometer.

2.2. DAISY model

DAISY is a soil–plant–atmosphere system dynamic model,which simulates plant growth and soil processes based on theinput of weather data (temperature, precipitation, global radiationand evapotranspiration), soil data (sand, silt and clay content, C:Nratio, bulk density and SOM content) and management informa-tion provided in Table 1. The model simulates water, heat, carbonand nitrogen flows in a soil–plant system at a field scale andprovides information on crop productivity, soil carbon, nutrientand water dynamics as a result of management and weatherconditions at a particular site of interest. DAISY has separate sub-models for crop growth, C and N dynamics, heat, soil water andfate of pesticide use (Abrahamsen and Hansen, 2000). In the DAISYmodel OM is the sum of added organic matter (AOM), soilmicrobial biomass (SMB) and soil organic matter (SOM) pool.AOM and SMB constitute relatively fast and slow turnover pools,whereas SOM constitutes three pools; inert (SOM3), fast (SOM2)

and slow turnover pools (SOM1) characterized by fixed C:N ratiosand first-order decomposition rate coefficients (Hansen et al.,2012).

AOM constitutes plant residues, added organic fertilizer orcompost etc; the SMB pool isresponsible for the biodegradationprocess and SOM is the recalcitrant humus fraction. Soil C and Ndynamics were modelled by assuming constant C:N ratios in eachpool (Bruun et al., 2003). The SOC pool, at the start of thesimulation period, is dependent on the management during thepre-experimental period and the model was initialized by simu-lating the pre-experimental period for 10 years before the onset ofthe experiment (Bruun and Jensen, 2002). The model inputconsisted of soil and management (Table 1) and weather data.The simulation was carried out for 10 years (growth cycles) from2003 to 2013 and same management was repeated with weatherdata of that particular year. The model outputs on grain yield(food), fodder (straw), carbon sequestration, soil water storage andnitrogen mineralisation are the mean of 10 growth cycles. Thesimulations were repeated with the same management andweather data by changing only current SOM content (2.6%) whichwas either halved (1.3% SOM) or doubled (3.9% SOM) to assessSOM effects on the two EF (soil water storage and nitrogenmineralization) and three ES (food and fodder production, carbonsequestration).

The DAISY model validation was carried out with the recordedfield data for the period (2003–2013). The simulation outputs ofthe conventional winter wheat grain yield were compared withrecorded field data and the model explained 90% of the variation(R2¼0.90), which lends credibility and robustness of the model.

2.3. Weather data

The weather data (2003–2013) was generated by LARS-WG 5(Semenov et al., 2002) based on statistical characteristics of actualsample of available weather data from Taastrup. The LARS-WG is astochastic weather generator which uses statistical model togenerate site parameters, which in turn is used to generatesynthetic daily weather data viz. mean temperature, precipitation,global radiation and evapotranspiration at a single site of interestbased on the latitude, longitude and elevation information(Semenov and Stratonovitch, 2010). Mean temperature is basedon the maximum and minimum temperature depending on thewet and dry season. Precipitation is generated on the basis of wetand dry days and global radiation is based on the empiricaldistribution of dry and wet days.

2.4. EF and ES valuation methods

The economic valuation is based on the price in base year 2013and the prices were deflated to make the ES values comparableacross different the EF and ES. The EF assessed was soil waterstorage and nitrogen mineralization and ES assessed were food

Table 1Soil characteristics and cultivation practices of the conventional wheat production trial site at Taastrup in Denmark.(Source: Ghaley et al., 2013).

Production system Bulk density (g cm�3) Soil moisture (%) N (%) SOM (%) C (%) Soil temperature (1C)

0–5 cm 5–10 cm

Soil properties 1.26 17.4 0.10 2.6 1.51 7.4 7.1Cultivationpractices

Crop residueincorporation

Ploughing Seedbedpreparation

Sowing 1st N dose(80 kg N ha�1)

2nd N dose(89 kg N ha�1)

Harvest

Timing 1st September 18thSeptember

19th September 20thSeptember

7th April 3rd May 20thAugust

B.B. Ghaley, J.R. Porter / Ecosystem Services 10 (2014) 79–8380

and fodder production and carbon sequestration. The economicvalues of the food and fodder were calculated based on theprevailing price of the grain (US$ 0.25 kg�1) and the straw (US$0.12 kg�1) in Denmark (www.farmtalonline.dk/accessed on06.03.2014). The value of soil water storage is based on the costof extraction and application of the irrigation water (US$ 20 for100 mm water) for cereal crop production (www.landrugs.info.dk/accessed on 06.03.2014). The carbon sequestration is based onabove and below-ground total biomass accumulation and 45% ofthe total biomass was considered to be carbon in cereals. Thecarbon was priced based on the prevailing price in the EuropeanUnion Emissions Trading Scheme (Kossoy and Ambrosi, 2010). Theeconomic valuation of nitrogen mineralization is based on theprevalent cost of the nitrate fertilizer kg�1 (US$ 0.48 kg�1) inDenmark.

3. Results

3.1. Physical quantification of EF and ES

The change in SOM levels had significant effects (Po0.05) onphysical quantities of food and fodder production, carbon seques-tration, soil water storage and nitrogen mineralization and theincrease in SOM had positive effects on the EF and ES provision(Table 2). At 2.6% SOM content of the trial site, the mean winterwheat food and fodder production was 6.49 t ha�1 year�1 (grainyield) and 6.86 (straw yield) t ha�1 year�1, respectively, whereasthe carbon sequestration and soil water storage was 9.73 tha�1 year�1 and 684 mm ha�1 year�1 respectively and the nitro-gen mineralisation was 83.58 kg ha�1 year�1 (Table 2). The con-ventional wheat production system constitute 39.6% (538,897 ha)of the total area under cereals (1431,677 ha) in Denmark. (http://www.statbank.dk//accessed on 07.03.2014). Accordingly, the foodand fodder production for Denmark were extrapolated to be3.50 and 3.70 million t year�1 respectively and carbon sequestra-tion and soil water storage of 5.24 million t year�1 and6840 M3 year�1 respectively and nitrogen mineralization of45.04�103 t year�1.

Compared to 2.6% SOM, at lower soil fertility of 1.3% SOM andsame management applied, the food and fodder productiondecreased by 0.34 t ha�1 year�1 and 0.36 t ha�1 year�1 respec-tively and the total production loss in Denmark was 190�103 t year�1 and 200�103 t year�1, respectively. Similarly, carbonsequestration and soil water storage decreased by 0.51 tha�1 year�1 and 17 mm ha�1 year�1 respectively, equivalent toloss of 280�103 t year�1 and 170 M3 year�1 respectively inDenmark. Nitrogen mineralization decreased by 15 kg ha�1 year�1,totalling 8.09�103 t year�1 in Denmark.

At higher soil fertility of 3.9% SOM and the same manage-ment applied, the food and fodder production increased by0.31 t ha�1 year�1 and 0.32 t ha�1 year�1 respectively compared

to 2.6% SOM and by 0.65 and 0.69 t ha�1 year�1 respectivelycompared to 1.3% SOM. The food and fodder production increasedby 160�103 t and 170�103 t year�1 respectively compared to2.6% SOM and by 350�103 t and 370�103 t year�1 respectivelycompared to 1.3% SOM. In similarity, the carbon sequestration andthe soil water storage increased by 250�103 t year�1 and140 M3 year�1 compared to 2.6% SOM and by 530�103 t year�1

and 310 M3 year�1 respectively compared to 1.3% SOM. The nitrogenmineralization increased by 14.41 kg ha�1 and 29.42 kg ha�1 year�1

compared to 2.6 and 1.3% SOM respectively, totalling 7.77�103 t year�1 and 15.85�103 t year�1, respectively, in Denmark.

3.2. Economic valuation of EF and ES

The physical quantities of EF and ES were expressed ineconomic values by using the prices prevalent in Denmark at thetime of the study and the sources of different price information areprovided in Section 2.3. At 2.6% SOM, the economic values of thetwo EF (soil water storage and nitrogen mineralized) and three ES(food, fodder, carbon sequestration) were US$ 177 ha�1 year�1

and US$ 2542 ha�1 year�1, respectively. At higher SOM content(3.9%), the economic values of two EF and three ES increased by US$ 10 ha�1 year�1 and US$ 120 ha�1 year�1 respectively comparedto 2.6% SOM. At lower SOM content of 1.3%, the economic values ofthe two EF and three ES decreased by US$ 11 ha�1 year�1 and US$134 ha�1 year�1, respectively, compared to 2.6% SOM (Table 3).

At 2.6% SOM, when extrapolated for Denmark, based on theconventional winter wheat acreage, the economic values of thetwo EF and three ES were US$ 96 million year�1 and US$ 1370million year�1, respectively. At 3.9% SOM, the two EF and three ESvalues increased by US$ 4 million year �1 and US$ 65 million -year�1, respectively, compared to 2.6% SOM. Accordingly, at 1.3%SOM, the economic values of the two EF and three ES decreasedcompared to 2.6% SOM. Hence, the economic valuation of the EFand ES was positively correlated to the SOM content.

3.3. SOM effects on soil water content

To illustrate the SOM effects on soil water storage in aparticular year during the 2003–2013 simulation periods, wesampled three different years with different precipitation regimes.SOM and soil water storage was highly correlated with high SOMretaining higher soil water depths and vice versa (Fig. 1). Irrespec-tive of precipitation regime (667–704 mm year�1) during theyears 1981, 1992 and 2003, relatively higher soil water was presentin 3.9% SOM soil compared to 1.3% and 2.6% SOM. 3.9% SOMretained 30–32 mm and 13–14 mm more soil water compared to1.3% SOM and 2.6% SOM, respectively, whereas 2.6% SOM retained17 mm more soil water compared to 1.3% SOM.

Table 2SOM effects on two EF and three ES quantities in conventional winter wheat production in Denmark.

EF and ES Units ha�1 year�1 Units Total year�1

SOM SOM

EF 1.3% 2.6% 3.9% 1.3% 2.6% 3.9%

Soil water storage mm 667 684 698 M3 6670 6840 6980N mineralisation kg ha�1 68.57 83.58 97.99 103 t 36.95 45.04 52.81ESFood t ha�1 6.14 6.49 6.79 million t 3.31 3.50 3.66Fodder t ha�1 6.50 6.86 7.18 million t 3.50 3.70 3.87Carbon sequestration t ha�1 9.21 9.73 10.19 million t 4.97 5.24 5.49

B.B. Ghaley, J.R. Porter / Ecosystem Services 10 (2014) 79–83 81

4. Discussion

4.1. SOM significance on EF and ES

The SOM has multiple benefits as a source of plant nutrients forcrop productivity, food for microbial population for nutrientcycling, retain soil moisture and have positive effects on chemical,physical and biological soil properties (Lal et al., 2007). The SOMis an indicator of soil fertility and positive correlations havebeen reported between the SOM and (a) crop productivity (Lalet al., 2007) (b) soil water availability (Bauer and Black, 1992; Pikulet al., 2007) and (c) root biomass and nitrogen cycling (Kusumoet al., 2011). Hence, there is a positive relationship between theSOM and different EF and ES provision, which are particularlysoil-based. The depletion of SOM has adverse effects on soilproductivity and on climate change by releasing carbon into theatmosphere (Lal, 2003, 2004). The management practices likeinclusion of grass into crop rotations, adoption of catch/greenmanure crops, residue management, balanced manure and ferti-lizer application and tillage intensity can have significant positiveeffects on SOM input and turn-over in the soil. The DAISY modelintegrates management, soil properties and prevalent weatherdata to assess the SOM effects on crop productivity and soilprocesses (EF and ES) and the model has been widely used toassess SOM pools under contrasting management regimes(Dewillingen, 1991; Vereecken et al., 1991). Hence, the use ofDAISY models for this study lends credibility and robustness fordetermination of different EF and ES.

4.2. Quantification and valuation of EF and ES

In this study, the investigation is based on two EF and three ES.In New Zealand in conventional wheat production system (Sandhuet al., 2008), the physical quantity and economic value of food wasreported to be 7.5 t ha�1 and US$ 1312 ha�1 (Sandhu et al., 2010),respectively, in proximity to our values in this study (6.49 t ha�1

and US$ 1622 ha�1). The New Zealand study valued fodder, carbonsequestration, soil water storage and nitrogen mineralization to beUS$ 38, 20, 54 and 66 ha�1, respectively, whereas our values weremuch higher in the range of US$823, 97, 137 and 40 ha�1,respectively. In an earlier study of a conventional wheat produc-tion systems at the same trial site, the study quantified food,fodder, carbon sequestration, soil water storage and nitrogenmineralization as 7.34 t ha�1, 5.33 t ha�1, 10 t ha�1, 283 mm and64 kg ha�1, respectively (Ghaley et al., 2013), which is in closeproximity to our findings of 6.49 t ha�1, 6.86 t ha�1, 9.73 t ha�1,137 mm and 40 kg ha�1, respectively.

The EF and ES values indicated in this study are ‘static’ (snap-shot) values to provide baseline information in the study sitewhich can be used by policy makers to assess the effects of themanagement practices on the EF and ES economic values(Crossman et al., 2013). The valuation in this study reflects onlythe two EF and three ES and do not account for the whole ‘bundle’of EF and ES provision. The valuation is broadly categorised as use(e.g. food and fodder production) and non-use (e.g. existence andintrinsic value) values and our valuations are use values and non-use values are very subjective and difficult to value. Hence, thevaluations represent minimum values and can be used for ‘valuetransfer’ method in other studies in the region for ES valuationwith similar socio-economic context.

4.3. EF and ES valuation for informed decision-making

Agriculture, forestry and other land use (AFOLU) productivityneed to be increased by 70% to meet the growing demand for thefood and fodder and energy by 2050 and at the same time, AFOLUaccounts for 24% (10–12 Gt CO2 eq year�1) of the anthropogenicGHG emissions (IPCC, 2014). Hence, there is a need to enhance thecrop productivity without adverse environmental effects. As theconventional winter wheat production is a dominant crop produc-tion system, the management practices have significant influenceson the productivity and thereof on EF and ES provision. The twoEF; soil water and nitrogen mineralisation and two ES investigatedin this study viz. food, fodder are measures of productivitywhereas the carbon sequestration is a measure for environmentalservice as a result of the production practice in place. As agro-ecosystems are both producers and consumers of ES, the produc-tion practices need to be directed towards optimisation of the EFand ES provision for enhanced productivity and the quantificationand valuation of EF and ES provides an empirical approach to valuethe suit of EF and ES due to certain management practice. We havedemonstrated in this study that different SOM levels result indifferent EF and ES values in a conventional winter wheatproduction system and this is characteristic of other crop produc-tion systems on-farm. The land managers and policy makers canuse the information for planning agri-environmental schemes atdifferent scales. Where the SOM content is being depleted due tocontinuous monoculture, the policy guidelines can be formulatedto mitigate the SOM depletion and where SOM are low, themanagement practices need to be improved to build up SOMcontent and where SOM levels are at higher range, efforts can bedirected to maintain the productivity and the resultant EF and ES.The EF and ES values can be used to assess the effects of land useand management practices, across a farm or landscape, as plan-ning tool for farmers, policy advisors and extension service

Table 3SOM effects on economic values of the two EF and three ES in a conventionalwinter wheat production in Denmark.

EF and ES ha�1 year�1 (US$) Total year�1 (million US$)

SOM SOM

EF 1.3% 2.6% 3.9% 1.3% 2.6% 3.9%

Soil water storage 133 137 140 72 74 75N mineralisation 33 40 47 18 22 25Total 166 177 187 90 96 100ESFood 1536 1622 1698 828 874 915Fodder 780 823 862 420 444 465Carbon sequestration 92 97 102 50 52 55Total 2408 2542 2662 1298 1370 1435

Fig. 1. Soil water storage (mm) at 1.3%, 2.6% and 3.9% SOM content in threecontrasting years with differing precipitation regimes at Taastrup in Denmark.

B.B. Ghaley, J.R. Porter / Ecosystem Services 10 (2014) 79–8382

(Kemkes et al., 2010; Nemec and Raudsepp-Hearne, 2013). Alter-natively, the EF and ES values can be used in integration with landfeatures to identify the location of individual and multiple EF andES or ‘hotspots’ for assessment of trade-off and synergies and tomatch the demand and supply of the EF and ES (Willemen et al.,2010; Burkhard et al., 2012). Hence, the EF and ES quantificationand valuation can be used as quantitative tools for informeddecision making at local, regional to national scale.

Acknowledgements

We appreciate the financial support from EC SmartSOIL project(Project number: 289694) for funding the field activities, labora-tory analysis and trip to 6th Annual International EcosystemService Partnership Conference at Bali in Indonesia. The manu-script is the outcome of the working group on modelling andmapping ecosystem services initiated at the conference.

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