Ecosystem service state and trends at the regional to national level: A rapid assessment

Ecological Indicators 36 (2014) 11–18

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Ecosystem service state and trends at the regional to national level: A rapid assessment Julian Helfenstein a,∗ , Felix Kienast b,1 a b

Institute of Terrestrial Ecosystems, Department of Environmental System Science, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland

a r t i c l e

i n f o

Article history: Received 13 March 2013 Received in revised form 27 June 2013 Accepted 30 June 2013 Keywords: Ecosystem service indicators Land use change Meta-analysis Agro-ecosystems Aquatic ecosystems Forest ecosystems

a b s t r a c t The concept of ecosystem services has helped rationalize humanity’s dependence on and benefits from nature, pushing the paradigm of environmental sustainability from a charity in the direction of a necessity. However, globally many ecosystem services are declining despite their eminent value for society. A prime cause of this decline is allocated to land use change. While the body of empirical research showing various consequences of land use is growing, and the ecosystem service concept has helped make trade-offs more graspable, a lucid approach that neatly summarizes the extent of land use trade-offs is still lacking. In this paper, we introduce a rapid assessment to analyze both the state and trends of selected ecosystem services associated with given land use categories. Theoretically, the assessment can be performed for any given spatial unit, but the regional to national level appears to be the most appropriate spatial resolution. Each land use-ecosystem service relationship is classified from a strong disservice to a strong service. The results are displayed in adapted flower diagrams, which legibly display information on the ecosystem services in each land use, thus clearly summarizing trade-offs associated with changing land use. We illustrate this rapid ecosystem service assessment method by applying it to three land use categories on the spatial extent of Switzerland. We found that the simple but systematic approach is more flexible than traditional mapping approaches, i.e. it allowed us to combine a variety of spatially non-explicit but highly detailed indicators with spatially explicit indicators. Also, we were able to proceed faster than with a mapping approach, where many known and unknown spatial inaccuracies may arise have allowed. This flexible incorporation of spatially explicit and non-explicit data provides high quality information on the state and trends of ecosystem services at regional to national extents. For that reason, we are convinced that the rapid assessment method has the potential to advance knowledge of ecosystem services and land use trade-offs, especially in areas with low data availability and monitoring activity. © 2013 Elsevier Ltd. All rights reserved.

1. Introduction Ecosystem services, the benefits people obtain from ecosystems, help demonstrate how humans profit from and depend on nature (Daily et al., 2009; Fisher et al., 2008). Even early, rudimentary valuation efforts made it clear that ecosystem services are of irreplaceable value for humanity (Costanza et al., 1997). However, the general condition of many ecosystem services is decreasing (MA, 2005), even though human use for them is increasing (Carpenter et al., 2009).

∗ Corresponding author. Tel.: +41 79 5696 708. E-mail addresses: [email protected] (J. Helfenstein), [email protected] (F. Kienast). 1 Tel.: +41 44 7392 366. 1470-160X/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ecolind.2013.06.031

Humanity has altered nature to increase its benefits, to maximize certain ecosystem services, a phenomenon coined land use. Kareiva et al. (2007) point out that the net effect of this “domestication” has been positive on humans. However, often societies were (and still are) not aware of the consequences of land use trade-offs. For example, it has been argued that soil loss resulting from agriculture led to the demise of various ancient civilizations (Beach et al., 2006; Judson, 1968; Montgomery, 2007). Even today, land use change often comes with unaccounted losses of carbon sequestration, regional climate and air quality regulation, pollination services, etc. (Foley et al., 2005). While the body of empirical research showing various consequences of land use is growing, and the ecosystem service concept has helped make trade-offs more graspable for management, a lucid approach that neatly summarizes the extent of trade-offs is still wanting. Different approaches have been developed to assess ecosystem services and to make the assessments readily available for

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managers. The most common method is the assessment based on mapping (Cowling et al., 2008; Haines-Young and Potschin, 2009). Prominent applications include the mapping of ecosystem services in Europe (Kienast et al., 2009; Schröter et al., 2005), California (Chan et al., 2006), globally (Naidoo et al., 2008), as well as the InVEST project (Daily et al., 2009; Nelson et al., 2009). While mapping is useful for certain objectives, mapping exercises are only as good as the spatial data available, i.e. for map overlays the layer with the lowest spatial and thematic quality determines the overall quality of the assessment. In many regions, fine-scale spatial data necessary for approximating ecosystem services across space and time is lacking (Eigenbrod et al., 2010). Also, the binary transfer assumption behind mapping approaches conveys a false sense of accuracy: it extrapolates the value of ecosystem services over a whole region, when in fact the values only stem from point observations or expert approximations of a specific habitat type (Nelson et al., 2009). Thus the use of proxies may lead to fatal error propagations (Eigenbrod et al., 2010). Lastly, because data quality and availability are unique for each assessment area, it is generally difficult to transfer inherently complex spatial assessment methods from one study area to another (Koschke et al., 2012). Efforts following the Millennium Ecosystem Assessment to create and establish a set of ecosystem service indicators have missed their goals at the continental and global level (Feld et al., 2009; Layke et al., 2012; Walpole et al., 2009). For one, there are no agreed upon global indicators. While different indicator frameworks have been suggested (Feld et al., 2010; Haines-Young and Potschin, 2010; Layke et al., 2012; Staub et al., 2011; van Oudenhoven et al., 2012), it is extremely difficult to generalize indicators broad enough to apply to diverse environments but specific enough to retain conclusiveness. Also, various ecosystem services, especially cultural ecosystem services, are still ungraspable (Harrison et al., 2010). Indicators have to find the golden middle between simplifying and expressing the original, complex processes, all while maintaining maximum possible quantifiability and transparence. In this paper we introduce a rapid method for assessing the state and trend of ecosystem services. We follow the example of Harrison et al. (2010) and evaluate the state and trends of ecosystem service capacity in our assessment area. The approach is based on a combination of spatially non-explicit but highly detailed indicators with spatially explicit indicators and lucidly illustrates land use trade-offs for decision makers. We focus our assessment on the capacity of ecosystems to provide ecosystem services, as opposed to the flux or flow of ecosystem services actually reaching society. This capacity of providing ecosystem services has been called various names, “supply” (Schröter et al., 2005), “stock” (Kienast et al., 2009; Layke et al., 2012), “potential” (Koschke et al., 2012), all of which fall into the category of biophysical assessment suggested by Cowling et al. (2008). The evaluation of the potential for landscapes to deliver ecosystem services is considered an important bridge builder between research and landscape management due to its ability to express land use trade-offs (Bastian et al., 2012; Koschke et al., 2012; Lautenbach et al., 2011).

2. Methods The objective of our assessment is to systematically approximate the state and trends of ecosystem services at large spatial scales (regional or national level). The entity of the assessment is a land use category. The core of the assessment is the evaluation of the following questions:

(1) Ecosystem service state: What is the contribution of the land use category n to the ecosystem service m (very negative −3, negative −2, slightly negative −1, no influence 0, slightly positive +1, positive +2, very positive +3)? (2) Ecosystem service trend: How is the ecosystem service state in each land use category developing over time (declining, increasing, constant, uncertain)? The value of the state and trend are determined using a systematic expert approximation. That means, first a set of indicators is established. Then, based on these indicators, experts approximate the values of interest—here the ecosystem service state and trend. Systematic expert approximations are a useful tool for providing an overview of the state of socio-ecological processes or structures where scientific knowledge is not yet at a level to allow more complex mathematical, statistically supported calculations. Applications include the (MA, 2005), the Planetary Boundaries Concept (Rockström et al., 2009), and many more (Foley et al., 2005; Haines-Young et al., 2012; Harrison et al., 2010; etc.). To illustrate the methodology behind our rapid approach for assessing the state and trends of ecosystem services in selected land use types, we applied the approach to Switzerland. 2.1. Case study region Our case study region is Switzerland. We draw on the land use categories from Swiss Statistics, which effectively divide the country into forests, agricultural areas, alpine pastures, urban areas, water bodies, glaciers, and other unproductive areas (BFS, 2012). In this assessment we evaluate forests, agricultural areas (excluding alpine pastures), and water bodies (see Table 1). The three land uses cover almost two-thirds of the country. 2.2. The assessment Based on the Common International Classification of Ecosystem Services (CICES, 2013), eight ecosystem services were defined as relevant and important to human well-being in Switzerland: provisioning services, biodiversity, water regulation, cultural services, climate regulation, soil preservation, mitigation of natural hazards, and air quality regulation. We found it more practical to use various CICES hierarchies (Table 2) then to adhere to one level. However, in their entirety, our selected ecosystem services cover all CICES classes except disease control and ones pertaining to marine ecosystems. Next we defined a set of quantifiable indicators for each ecosystem service and land use relationship. The indicators were selected based on the literature (Feld et al., 2010; Harrison et al., 2010; Layke et al., 2012; Staub et al., 2011; van Oudenhoven et al., 2012) and our own judgment. The assessment method differs from existing literature - and expert-based ecosystem service evaluations such as MA (2005), Harrison et al. (2010), and Haines-Young et al. (2012) by incorporating the concept of ecosystem dis-services. Various authors noticed that an ecosystem, land use category, or other spatial entity, aside from providing benefits to humans, may also have negative effects for human well-being (Power, 2010; Zhang et al., 2007). Agro-ecosystems, for example, often contribute to air and water pollution, emit greenhouse gases, increase erosion, and come along with biodiversity loss (Swinton et al., 2007). Considering negative effects is especially important for projects that aim at agglomerating ecosystem services from different spatial or ecological entities or demonstrating land use trade-offs. Such projects must have a mechanism whereby a positive effect on an ecosystem service may be negated on a higher agglomeration level by a negative effect in another entity. Burkhard et al. (2012) and

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Table 1 Land use categories.

a

Land use category

Area in ha (% of national land area)a

Remarks

Forests

1,272,000 (31%)

In lowlands the Common Beech (Fagus sylvatica) dominates; at higher latitudes, the European Spruce (Picea abies) is most common Compared to European forests, relatively high native tree species and low plantation percentage (Brändli, 2010)

Agricultural areas

987,000 (24%)

Encompasses crop production areas, pastures (except alpine pastures), orchards and vineyards Mostly on fertile soils at lower altitudes

Water bodies

174,000 (4%)

Aside from lakes, which make up most of the area, rivers and streams, accounting 65,000 km (Zeh et al., 2009), are also of high socio-ecological relevance

Values from the Swiss Statistics (BFS, 2012).

Nedkov and Burkhard (2012) dealt with this problem by introducing supply and demand budgets for ecosystem services. We adopt their budget assumption, that ecosystem services from one entity can be added to ecosystem services from another entity. However, in this study we do not interpret supply and demand, source or sink. Instead, we simply report the positive or negative contribution of the land use to a particular service. If the net impact of a land use category on an ecosystem service is negative, we understand an ecosystem disservice. For example, an ecosystem may have a positive contribution to air quality if it entails mechanisms for filtering out air pollutants. However, the ecosystem has a negative contribution if the emission of air pollutants from the ecosystem overweighs the cleaning effects. We classified positive as well as negative impacts on ecosystem services as strong, medium or slight. Aside from the state of the ecosystem service, the trend is also a useful feedback for management because it illustrates the effect of management decisions. It shows if past efforts to conserve an ecosystem service are effective and or reveals the (unforeseen) impact of certain actions on ecosystem services. We assume that the state of ecosystem services over time represents a line. The definition that we propose for the trend is the slope at the point “today,” smoothed for seasonal/annual fluctuations. An ecosystem service is declining (negative slope), if the expert and literary review suggest an overall degeneration of the ecosystem service for the considered land use. However, the delineation of the trend comes with considerable uncertainties; often indicators display opposing developments for the same ecosystem service. As a result, increasing or declining trends for ecosystem services were only chosen if the indicators showed a similar development or one/several indicators clearly dominated. If the indicators suggest ambivalent development, if the trend was dependent on unforeseeable socio-political policies, or if not enough evidence existed for a clear evaluation, we declared the trend as uncertain. The results of the assessment are displayed in adaptations of Foley et al.’s (2005) “flower diagrams,” which allow for a schematic and lucid exposition of ecosystem services and their trade-offs in different land use types. We emphasize the importance of displaying results in a clear, condensed but highly informative manner, which makes research products more available and legible for policy-makers and a broader audience. This is especially important in ecosystem service assessments, which are often conceived to be decision-influencing, management tools. In our “flower diagrams”, the state of each ecosystem service per broad land use category is illustrated through the length of a bar. A circle characterizes the neutral state, where an ecosystem has no measurable effect on an ecosystem service. If the ecosystem supports the ecosystem service, the bar faces outward and is either small, medium or large in size, conveying a slight, medium or strong contribution of

the ecosystem to the particular service. The same counts for disservices, except that the bar then goes inward, toward the center of the diagram. Furthermore, each bar has an indicative color that illustrates the trend. A black bar signifies that the state is declining (becoming more negative), white attributes an increase in the ecosystem service, and a stable or uncertain development is characterized through gray coloration. The bars are arranged radially like petals of a flower (hence flower diagrams). Each flower represents one land use entity, making land use trade-offs easily conveyable. 3. Results Based on the indicators in Table 2, we systematically approximated the contribution of forests, aquatic ecosystems and agro-ecosystems on the state and trends of ecosystem services. The states were classified between very negative (−3) and very positive (+3) and the trends as declining, increasing, constant, or uncertain. These values are illustrated in three flower diagrams, one for each land-use type (Figs. 1–3). Of the 24 land use ecosystem service relationships we analyzed, four are summarized below as examples. provisioning services biodiversity conservation

air quality regulation

natural hazard mitigation

water regulation

soil conservation

cultural services climate regulation

Fig. 1. State and trends of ecosystem services in forest ecosystems. The block position implies the value of the state: blocks facing outward are positive, the larger the better, while blocks facing inwards represent a negative contribution, the larger the more negative. Block coloring illustrates the trend (becoming more negative = black, improving = white, stable/uncertain = gray). Provisioning services (bold lettering) are discussed in the text. The figure shows that forests have a very positive contribution to provisioning services (position of block) and that the trend is stable/uncertain (gray color).

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Table 2 A list of the ecosystem services used and their indicators. Our defined ecosystem services correspond to the listed section/division/group as defined by CICES V4.3 (CICES, 2013). Ecosystem service

Description

Corresp. CICES SECTION/Division/Group

Selected indicators used in the present study

Forests

Water bodies

Agriculture

Fish: fish catches, fish population size, fish health, fish habitat state, fish connectivity Hydropower: potential, power generation, runoff, effects of climate change Habitat diversity: morphology, river correction, eutrophication, pollutants, river fragmentation, drift, climate change Species diversity: species number, endangered species, invasive species Genetic diversity: no available indicators found Water quality: eutrophication, micro-pollutants, other pollutants Water quantity: reserves, flows, effect of climate change Recreation, esthetics, cultural heritage, history, tourism

Crops: yield/ha; light, water, nutrient, warmth availability; disturbances, climate change Animal products: yield, feed crop, disturbances

Global climate: dissolved organic carbon, carbon fluxes Regional climate: weather, temperature, wind, fog Soil quality: not analyzed Soil quantity: not analyzed

Global climate: CO2 , CH4 , N2 O, NO emissions Micro/regional climate: not analyzed

Provisioning of goods and energy

The capacity to produce goods and energy

PROVISIONING

Timber: reserves, annual growth, impact of climate change, natural hazards, pine beetles, disease, other biotic disturbances

Biodiversity

Biological diversity at the habitat, species and genome level.

Lifecycle maintenance, habitat and gene pool protection

Habitat diversity: coarse woody debris, protected areas, effects of climate change, nitrogen deposition Species diversity: species number, endangered species, invasive species Genetic diversity: no available indicators found

Water regulation

Influence of the ecosystem on water quality and water quantity regulation.

Water conditions Liquid flows

Water quality: groundwater quality, nitrogen deposition Water quantity: above-ground runoff

Cultural services

Effect of the ecosystem on the generation of cultural values Influence on the micro and regional climate, as well as effect on the global climate (carbon cycle). Preservation of soil quality and prevention of erosion.

CULTURAL

Recreation, esthetics, cultural heritage, history, tourism

Climate regulation; Gaseous/air flows

Global climate: forest age, C emissions/sequestration Micro climate: forest micro climate

Soil formation and composition

Soil quality: chemical, physical, and biological soil fertility indicators Soil quantity: soil erosion Forest age, area of natural hazard protection forests, effect of climate change, biotic disturbances, extreme weather, avalanches, rockfall, landslides, flooding, debris flow Pollutant filtration, surface area for filtering, deciduous vs. evergreen tree composition

Climate regulation

Soil conservation

Natural hazard mitigation

Impact on the occurrence and consequences of natural hazards.

Liquid flows; mass flows; mediation of waste, toxics and other nuisances

Air quality regulation

Effect of the ecosystem on air pollutants.

Atmospheric composition

3.1. Provisioning services linked to forest ecosystems Forested areas reach maximum values for supplying provisioning services. While a large variety of potentially beneficial products are supplied by forests, and have been used historically, today timber is by far the dominating provisioning service from forests. With a timber supply of 359 m3 /ha and a yearly growth rate of 9.5 Mio m3 , Swiss forests are very productive for European standards (Brändli, 2010).

Floodplain area, river corrections, river restoration, effect of climate change

Not analyzed

Habitat diversity: intensive agriculture, homogeneity, fragmentation, extensive/organic agriculture Species diversity: species number, endangered species, invasive species Genetic diversity: crop variety, animal variety

Water quality: nutrient efficiency, pesticides, veterinary medicine, groundwater quality Water quantity: above-ground runoff Recreation, esthetics, cultural heritage, history, tourism

Soil quality: chemical, physical, and biological soil fertility indicators Soil quantity: soil erosion Soil cover, trees, landslides, flooding, debris flow

Nitrous oxide, ammonia, and soot emissions; trees

We see no clear increase or decrease in future timber production. The impact of climate change was analyzed as a main determinant of future timber production. The significant advancement of spring and increasing temperatures have already and will continue to fundamentally change forest ecosystems, putting a stress on tree species (Menzel et al., 2006; Parmesan and Yohe, 2003; Root et al., 2003; Rustad et al., 2001). While recent spatially explicit models (e.g. Hanewinkel et al., 2013) imply that forest composition will change dramatically within 50–100 years, the potentially significant lag time between site change and tree occurrence shift,

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is unpredictable, we refrain from making a definite statement on the trend of provisioning services in forests at this time.

provisioning services biodiversity conservation

air quality regulation

water regulation

natural hazard mitigation

soil conservation

cultural services climate regulation

Fig. 2. State and trends of ecosystem services in aquatic ecosystems. Biodiversity and climate regulation (bold lettering) are discussed in the text. Aquatic ecosystems have a positive contribution to biodiversity conservation and a very positive contribution to water regulation (position of blocks). The state of biodiversity is decreasing (black color) and climate regulation is stable (gray color). See figure caption 1 for more information on figure legibility.

and also changes in human preference for wood, remain uncertain (Eggers et al., 2008). Further complicating the fact, the global rise in atmospheric carbon may have a positive effect on woody biomass production (Curtis and Wang, 1998; Curtis, 1996; Jablonski et al., 2002; Medlyn et al., 1999). Biotic disturbances, including disease, pests and mammal bite damage also have an influence on timber (Brändli, 2010). Ultimately, both biotic and climatic impacts on forests are largely dependent on management decisions: depending on the forest management policy, a forest can be induced to increase or decrease its resilience to disturbances. Because the unraveling of changes across time resulting from climate change in forests are still controversial, and the development of management

provisioning services biodiversity conservation

air quality regulation

water regulation

natural hazard mitigation

soil conservation

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cultural services climate regulation

Fig. 3. State and trends of ecosystem services in agro-ecosystems. Soil conservation (bold lettering) is discussed in the text. Agro-ecosystems have a slightly negative effect on soil conservation; however, no predominant declining or increasing trend was observed for this relationship. See figure caption 1 for more information on figure legibility.

3.2. Biodiversity and climate regulation linked to aquatic ecosystems Swiss aquatic ecosystems have a diminished contribution to biodiversity conservation. Switzerland has lost 95% of its riverine floodplains (Tockner and Stanford, 2002). While 10% of fauna found in Switzerland is restricted to floodplains, 28% and 44% use it frequently or occasionally (Tockner and Stanford, 2002). Furthermore, only 54% of river and stream kilometers (35,000 km) display a natural morphology, the rest are in various states of impairment, ranging from low impairment to subterranean pipeline (Zeh et al., 2009). Fragmentation through dams (Mertens et al., 2007; Nilsson et al., 2005) and pollution through nutrient inputs (Carpenter et al., 1998; Vitousek et al., 1997) poses additional limitations to aquatic biodiversity. According to Tockner and Stanford (2002), 40% of obligate riparian species are listed as endangered in Switzerland, a clear sign that the biodiversity conservation service is not at its full potential. Despite positive trends for many biodiversity indicators, the ecosystem service is still viewed as decreasing due to the rapidly growing problem of invasive species. New legislature lays the foundation for increased rehabilitation of fragmented and structurally impaired rivers (GschG, 2011), and nitrogen and phosphor concentrations are decreasing (Binderheim-Bankay et al., 2000; Heldstab et al., 2010; Kirchhofer et al., 2007). At the same time, invasive species are taking over aquatic ecosystems and displacing native flora and fauna. As the vanguard of aquatic ecosystems in Switzerland, the Rhine River contains 90% invasive species in terms of invertebrate individuals and 95% in terms of invertebrate mass (Rey et al., 2004). Because stressed ecosystems are more vulnerable to invasive species (Colautti et al., 2006), the highly fragmented, biologically impaired aquatic ecosystems are undergoing fundamental changes in species abundance and composition, at the cost of native biodiversity. We assume that the “invasional meltdown” (Parker et al., 2006) already underway in parts of the Rhine and other forefront rivers will spread to upstream rivers and lakes. Large rivers and lakes have an effect on the local as well as the global climate. Water bodies affect air temperature, humidity and momentum (Long et al., 2007), leading to phenomena such as lake breezes that result from differing heating of terrestrial and aquatic surfaces and may influence the regional climate (Crosman and Horel, 2010). The low-friction surface of lakes also allows for higher wind speeds to develop. Furthermore, there is a correlation between areas of high fog occurrence and lake and river dominated landscapes (Bendix, 2002). As storage, conversion, emission and absorption centers of carbon, freshwater lakes play an important role in the global greenhouse effect. The annual deposition of organic carbon in lakes surpasses that of ocean sediments and is thus an important but understudied component of the global carbon cycle (Gudasz et al., 2010). The direction and magnitude of netto atmosphere-lake carbon exchange is highly variable between different lakes so that certain lakes serve as C-sinks, others as C-sources (Tranvik et al., 2009). Though dissolved organic carbon (DOC) has been measured in 7500 lakes worldwide, including 68 in Switzerland, and correlations between DOC and other parameters have been found, understanding is still limited (Sobek et al., 2007). Increasing temperatures associated with climate change alter limnological carbon cycles. The research community suggests that rising temperatures lead to more mineralization and less organic carbon burial (Gudasz et al., 2010; Tranvik et al., 2009). However, we deduce that not yet enough is known about carbon cycles in Swiss lakes to make a prediction on the trend of the ecosystem

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service. Regional climate regulatory services, on the other hand, are solely dependent on constant physical properties of water bodies such as surface area and volume, and thus believed to remain unchanged. 3.3. Soil conservation services linked to agro-ecosystems While food production is dependent on fertile soils, agriculture degrades soils by diminishing soil quality and increasing erosion. To operationalize soil fertility, physical, chemical and biological indicators have to be considered (Mäder et al., 2002). Physical soil fertility parameters—aggregate stability, bulk density, and percolation stability—fall out meagerly due to soil compaction through heavy machinery (Hamza and Anderson, 2005) and the loss of binding humus and organic material (Gadermaier et al., 2011; Six et al., 1998; Tilman et al., 2002). While fertilizer use may benefit key chemical indicators N, P, and K, other fertility indicators such as calcium may be lost as a result (Vitousek et al., 1997). Also, soil tillage reduces organic carbon (Lal, 2004; Six et al., 1998, 2000). Lastly, mycorrhizae, microbial biomass, earthworm biomass and other biological soil fertility indicators are reduced in conventional, intensive agriculture (Mäder et al., 2002). Soil erosion is also an enormous but often underestimated problem in agriculture. While experts and management have long considered 2–4 t/ha and year the acceptable threshold for soil loss (Prasuhn and Weisskopf, 2003), recent evidence shows that these thresholds are too high for many agricultural regions. On average, soil loss exceeds soil formation 10–100 fold on agricultural fields, whereas in plots with native vegetation it is in equilibrium (Montgomery, 2007). Because fine particles, important determinants of soil fertility, are the first particles to be lost when a soil becomes exposed to erosion, soil loss is a direct threat to sustainable food security (Godfray et al., 2010; Pimentel et al., 1995; Stocking, 2003). In summary, predominant agricultural methods have a clear negative effect on soil conservation. However, because erosion is comparatively low for European standards (Ledermann et al., 2010) and soil fertility could be much worse, we argue only a slightly negative contribution. We discern no definite trend for the ecosystem service ‘soil conservation’ through agro-ecosystems. Organic agriculture, which rates better on almost all physical, chemical and biological soil fertility indicators (Mäder et al., 2002), is on the rise and fertilizer use is decreasing (BLW, 2011). On the other hand, soil erosion, which is highly weather-dependent, may increase due to more extreme weather events and more precipitation in winter, when fields are fallow (Prasuhn and Weisskopf, 2003; Fuhrer et al., 2007). 4. Discussion The most common approach for assessing ecosystem services remains an assessment based on mapping (Cowling et al., 2008; Haines-Young and Potschin, 2009; Kienast et al., 2009). Mapping, however, relies on spatially available proxies and requires simplification to manageable and available indicators at e.g. a common grid size. Valuable information that is not spatially explicit cannot flow into the assessment and is therefore lost. While certain objectives unavoidably call for such a rigid mapping approach, in other cases a less rigid, rapid assessment may provide a powerful alternative. Although the rapid assessment still has a spatial component, the spatial aspects are more relaxed and information is not bound to a common scale or grid size. We argue that, compared to a rigid mapping approach, the rapid assessment presented here may include more ecosystem service indicators and has a high time and money efficiency, at the cost of some spatial information and transparency (Fig. 4). Hence our

Fig. 4. Compromise in spatial analyses. Ecosystem service assessments often have to make a compromise between spatial resolution, transparency, time and money efficiency, and ecological relevance. Compared to mapping ecosystem services, a rapid assessment may provide a good input/output ratio and high quality information on the state and trends of ecosystem services (inclusion of more parameters) at the cost of spatial information and transparency.

assessment method may provide welcome additional information, particularly for ecosystem services that are sufficiently complex, where the present state of knowledge or data availability allows only preliminary mapping at best. In such cases, the standing of literature and expert knowledge is often further, and an expert and literature based evaluation such as the one presented here may supplement the maps. Of course a rapid assessment like ours is also a simplification to a set of manageable indicators. However, we argue that it can account for more indicators. In the step from ‘what we know about ecosystems’ to ‘how we can model ecosystem services across space and time’, a lot of valuable information is lost. This may arise when not all structures and processes known to have an influence can be spatially considered—i.e. problems of data availability (Eigenbrod et al., 2010). Or information loss/skewing may occur if the mapping effort requires point or average values for ecosystem services and the indicators thereof to be extrapolated over a whole region (Nelson et al., 2009). Also, the rapid assessment method can produce ecosystem service state and trend approximations valuable for management with a low money and time investment. The meta-analysis approach only requires literature, spatially explicit and nonexplicit data, contact to experts, and ecological knowledge of the study area. For that reason, we think the method has a good time and money input/output ratio. However, because the assessment results are highly dependent on experts and literature and not produced by mathematical algorithms, the rapid assessment method lacks transparency. Although the results of our rapid assessment could easily be mapped, we advise preserving the original narrative form in order to avoid violation of mapping principles and to maintain the fine-scale character of some assessments. The following example may elucidate this statement: We can say with a certain confidence that the contribution of, for example agroecosystems on biodiversity, in Switzerland as a whole is slightly positive (+1). To map this result would mean to give all agricultural land uses a +1 throughout the whole country. This would, however, not account for the fine-scale character of some assessments, for example that agroecosystems may have an extremely positive effect on biodiversity on extensively used xeric prairies and dry meadows.

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To map these fine-scale results would be extremely difficult as long as not all xeric sites are mapped and monitored and as long as the spatial unit of analysis (here land use category) is at a coarser spatial scale than the spatial unit at which the mapped parameter may vary substantially (for biodiversity and agroecosystems, probably individual agricultural field). 5. Conclusion Our method allows an expert panel to make a structured evaluation of ecosystem services at the regional-national level. By using land use categories as the spatial entity of assessment, the results are intelligible and practical for management. The flower diagrams of each land use are designed to serve as compact but legible information carriers and awareness stimulators that lucidly illustrate land use trade-offs. In an anthropocentric world, we think it appropriate to consider land use categories (anthropocentric borders) rather than catchment areas, natural ecosystems or other natural borders as the spatial entity, basis of an ecosystem service assessment, for two reasons. For one, in many areas of the world, human behavior and its consequences has become as important of an influence on structures and processes in ecosystems as the biotic and abiotic factors defining a classical ecological zone. Secondly, using land use categories as the basis of socio-ecological assessments provides more practical and relevant information for management. Land management and political borders tend to follow anthropocentric borders, not ecological gradients. Therefore, results linked to a land use type, often under the same management jurisdiction, are practical for policy-makers. Also, a rapid assessment method may have key advantages over a mapping-approach: more indicators and higher time and money efficiency. While our assessment, like any, benefits from a high research and monitoring density, it can also be applied where spatial data is limited. For that reason, we see potential for the rapid assessment method in less developed regions of the world. In places where poor-resolution and lacking data may prevent ecosystem mapping, a panel of experts may still make a useful approximation of ecosystem service state and trends based on interviews, expert knowledge, and literature. Rapid ecosystem service assessments thus have the potential to advance understanding of land use trade-offs and ecosystem service science. Acknowledgements This paper grew out of the thesis “Ecosystem assessment Switzerland: determining the state and trends of ecosystem services in agro, aquatic and forest ecosystems “for the Swiss Federal Institute of Technology ETH. We would like to thank Dr. Peter Rotach, Prof. Rolf Kipfer, Dr. Urs Niggli, Otto Schmid, and other teachers at the Environmental Systems Science Department for the expert knowledge and advice they shared on forest, aquatic or agroecosystems. We also thank the two anonymous reviewers, who provided constructive feedback and helped us improve the text. References Bastian, O., Haase, D., Grunewald, K., 2012. Ecosystem properties, potentials and services – the EPPS conceptual framework and an urban application example. Ecol. Indicators 21, 7–16, Special issue. Beach, T., et al., 2006. Impacts of the ancient Maya on soils and soil erosion in the central Maya Lowlands. CATENA 65 (2), 166–178. Bendix, J., 2002. A satellite-based climatology of fog and low-level stratus in Germany and adjacent areas. Atmos. Res. 64, 3–18. BFS, 2012. Arealstatistik 1992/1997. Swiss Statistics, Available online: http://www.bfs.admin.ch/ (23.11.2012). Binderheim-Bankay, E., Jakob, A., Liechti, P., 2000. NADUF – Messresultate 1977–1998. Federal Office for the Environment, Bern.

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