Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
International Journal of Biodiversity Science, Ecosystem Services & Management Vol. 6, Nos. 3–4, September–December 2010, 119–130 Impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China: a multi-scale cause–effect approach considering multiple land-use functions a,b∗ a c Masayasu Asai , Pytrik Reidsma and Shuyi Feng a b Department of Plant Sciences, Plant Production Systems Group, Wageningen University, Wageningen, The Netherlands; Department of Agriculture and Ecology, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark; College of Public Administration, Nanjing Agricultural University, Nanjing, PR China This paper aims to assess the impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China, and to identify possible conservation strategies. We used the mean species abundance (MSA) approach, building on simple cause— effect relationships between environmental drivers and biodiversity impacts at the global level. Our assessment estimated that 21% of the original species in the undisturbed ecosystem were present in 2000. We also analysed and reviewed agri- cultural pressures at different spatial scales to enable the development of conservation strategies at regional and farm levels. This analysis showed, ﬁrst, that intensive crop management is reﬂected by the amount of fertilisers applied. Policies and tech- nologies aiming to reduce environmental impacts have been ineffective. Second, the abundance of semi-natural elements was found to be low and the fragmentation high. To link agricultural pressures to the MSA approach, we propose a multi-scale cause–effect approach, which can be linked to other land uses. This approach is useful to provide a quick scan of biodiversity status and identify conservation strategies. Training farmers to use site-speciﬁc nutrient management should be stimulated. Furthermore, acknowledging multiple land-use functions will help to develop biodiversity conservation strategies that are acceptable to farmers and policymakers. Keywords: biodiversity; land-use change; multiple scales; nutrient management; landscape structure; policy options; land-use functions driver of agricultural landscape changes, that is, conver- Introduction sion of paddy ﬁeld into artiﬁcial ponds for aquaculture, Biodiversity loss is one of the main global environmental urban and rural settlements and construction lands (Xie problems. It is decreasing at an unprecedented rate and has et al. 2005; Wu et al. 2009). These changes in crop man- ethical, social and economic implications (Sala et al. 2000; agement and land use/land cover have led to pressures on Millennium Ecosystem Assessment 2005). Land-use/land- biodiversity at different spatial scales, ranging from ﬁeld to cover changes are considered major threats for biodiversity regional, in Taihu Lake Basin. conservation (Sala et al. 2000; Zebisch et al. 2004; Jackson For the assessment of impacts of agricultural land-use et al. 2007). As agricultural land occupies a large part of change on biodiversity, linking socio-economic and eco- the global land surface, its management and change are of logical processes and including temporal change at multi- major importance to reduce biodiversity loss. spatial scales is important (Dalgaard et al. 2003; Dirnböck In China, increasing agricultural production and food et al. 2008). The objective of this study is to assess the self-sufﬁciency has been a major aim of the government in impacts of agricultural intensiﬁcation on biodiversity in the last decades. In the Taihu Lake Basin, one of the most paddy agroecosystems in Taihu Lake Basin. productive areas in China, farmers have been conducting ﬂooded paddy rice (Oryza sativa) production in sum- mer, rotated with wheat (Triticum aestivum) or rapeseed Methods (Brassica napus) in winter for more than nine centuries Study area (Ellis and Wang 1997; Wu et al. 2009). The most signif- Our case study region is Taihu Lake Basin in China icant ecological changes in the history of rice cultivation (Figure 1). The basin is located in the east of China, at have likely occurred since the 1940s, as a result of popula- the mouth of the Yangtze River and between the Qiantang tion growth, the adoption of industrial technologies such as River and the Hangzhou Bay. Its total area is 36,500 chemical fertilisers, pesticides and machines and changes km , where Jiangsu Province accounts for 52.5%, Zhejiang in rural policy and its implementation (Ellis and Wang Province 33.4%, Shanghai municipality 13.5% and Anhui 1997; Wu et al. 2009). This has led to intensiﬁcation of Province 0.1%. It is a subtropical region, having an average crop management, resulting in higher crops yields to sus- temperature of 14.9–16.2 C and with the highest tempera- tain one of the most densely populated agricultural regions ◦ ◦ on earth, but also environmental side effects. Further, since tures (27.7–28.6 C) in July and the lowest (1.7–3.9 C) in the mid-1980s, economic development has been the main January. Annual precipitation is 1010–1400 mm. All study Corresponding author. Email: firstname.lastname@example.org ISSN 2151-3732 print/ISSN 2151-3740 online © 2010 Taylor & Francis DOI: 10.1080/21513732.2011.577039 http://www.infomaworld.com 120 M. Asai et al. Zhenjiang Yangtze River Changzhou Yangtze River Wuxi Shanghai Xiejia Yixing Cultivated and managed areas 31°15′N Tree cover, needle-leaved, ever Regularly flooded shrub and/or herbaceous cover Taihu Lake Water bodies Herbaceous cover, closed-open Tree cover, broadleaved, evergreen Artificial surfaces and associated areas 120°10′E Figure 1. Land-cover (GLC2000) map showing rivers, lakes and cities in the Taihu Lake Basin. sites, including cases from available literature, are located Land Cover 2000 (GLC2000) map (Bartholome et al. 2004; within the northern part of Taihu Lake Basin in Jiangsu Alkemade et al. 2009), land-use categories are deﬁned Province. The northern part is of speciﬁc interest, as it and given corresponding MSA values ranging from 5% to is dominated by cropland, and the large impact on water 100%. Besides MSA values for each deﬁned land-use type pollution in the lake has initiated policies to change agri- (LUT), Alkemade et al. (2009) identiﬁed the following cultural land use and management (Reidsma et al. 2011). environmental drivers: land-cover change, land-use inten- As the landscape is ﬂat and land cover is relatively homoge- sity, fragmentation, climate change, atmospheric nitrogen nous (Xiao et al. 2005), all study sites are representative of deposition and infrastructure development. Considering the case study region. the impacts of these drivers on biodiversity (MSA) and aggregating different LUTs to the regional scale, the eval- uated value of MSA in Jiangsu Province (half of the total area of Taihu Lake Basin is accounted for by Jiangsu) for Biodiversity assessment approaches the year 2000 was 21%. This value represents the large To assess the impact of agriculture on biodiversity, a occupation by anthropogenic land uses, as corresponding wide variety of studies have been conducted at different MSA values of different LUTs of agroforestry, low-input scales. At farm and landscape levels many studies (e.g. agriculture, intensive agriculture and build-up areas (areas Herzog et al. 2006; Billeter et al. 2008; Kleijn et al. 2009) with more than 80% of built up) are 50%, 30%, 10% and have been based on empirical species abundance data. At 5%, respectively. higher levels using cause–effect relationships is a major approach (e.g. Scholes and Biggs 2005; Reidsma et al. 2006; Weijters et al. 2009), due to the difﬁculty of observa- A multi-scale cause–effect approach tion and up-scaling from small-scale experiments to higher scales and budget limitation (Fu et al. 2007). The approach of Alkemade et al. (2009) is useful for Alkemade et al. (2009) have developed the GLOBIO3 biodiversity assessment at larger scales. The MSA value model to assess human-induced changes in biodiversity itself, however, gives little perspective for conservation at the global scale. The model is built on simple cause– strategies, especially in the case study area where the land- effect relationships between environmental drivers and cover types are quite homogeneous and the LUTs are biodiversity impacts, based on available literature using mainly anthropogenic. Farming systems in Asia, especially meta-analysis. In the model, the mean original abundance rice paddy ﬁelds, have a strong potential for a species- species relative to their abundance in undisturbed ecosys- rich environment (cf. Bignal and McCracken 1996; Pain tems (mean species abundance (MSA)) is used as the and Pienkowski 1997; Ovenden et al. 1998; Maeda 2001; indicator for biodiversity. The maximum value of MSA is Amano et al. 2008). For instance, about 2000 species of 100% and indicates an undisturbed natural situation, while plants and animals associated with rice paddy ﬁelds have 0% represents a completely transformed/destroyed ecosys- been recorded in Japan (Hidaka 1998), 645 animal species tem without any wild species left. Based on the Global were collected in the Philippines (Cohen et al. 1994), and International Journal of Biodiversity Science, Ecosystem Services & Management 121 765 species of arthropods were examined in Indonesia social) and the associated land functions (e.g. preservation (Settle et al. 1996). In Sri Lanka, 494 species of inverte- of biodiversity), and therefore the identiﬁcation of land-use brates, 103 species of vertebrates and 128 plant species functions is important for sustainable development of the were observed (Bambaradeniya et al. 2004). In general, agricultural sector and to identify conservation strategies. the semi-natural elements surrounding the managed rice After analysing and reviewing changes in these agri- ﬁelds contribute to high abundance of species (Amano cultural processes, and identifying preferences of land-use et al. 2008; Moonen and Bàrberi 2008), and extensive functions, the methodological framework is further devel- management increases biodiversity richness (Settle et al. oped, by integrating these agricultural processes at multiple 1996). Hence, to improve assessments of technological scales in the MSA approach and discussing conserva- innovations and policy options and to develop conservation tion strategies (improved nutrient management and riparian strategies, more regional/local data are required (Reidsma buffer zones) by putting biodiversity conservation in the et al. 2006, 2011). This research therefore analysed and context of other land-use functions. reviewed agricultural pressures at multi-spatial scales in the region to obtain more insight in drivers and impacts in Taihu Lake Basin. Assessing pressures on biodiversity at ﬁeld level – crop According to Firbank et al. (2008), agricultural pres- management sures on biodiversity can be characterised by three major processes, acting at different scales (albeit with interac- Rice ﬁelds are subject to many cultivation activities and tions), that can be indicated separately. These are (1) agricultural changes. Throughout the season, ﬁeld condi- the management of crops to increase their productivity, tions are changed drastically and abruptly through ﬂood- through breeding, fertiliser use, the introduction of alien ing, transplanting of seedlings, harvesting and ploughing. species and the control of competitors, predators and par- Indeed there are many pressures caused by different aspects asites; (2) the transformation of agricultural landscapes of crop management on different taxa and habitats, and into new combinations and arrangement of crops and thus their effects are very difﬁcult to separate (Firbank et al. semi-natural elements; and (3) the transformation of land 2008). between non-agricultural and agricultural habitat. By fol- In this study we focused on variability in fertiliser use lowing these three processes, land management at the as the indicator of agricultural intensity that impacts nega- ﬁeld level, landscape structure at the landscape level and tively on biodiversity. A wide variety of studies have used –1 –1 land use at the regional level, agricultural systems can be annual nitrogen input per site in kg N ha year (referred described. The advantage of this conceptual model is that it to as N input) as one of the key indicators of agricultural allows placing any agricultural system within these dimen- intensity or land-use intensity (Schmitzberger et al. 2005; sions for both the pressures on biodiversity and, separately, Dormann et al. 2007; Hendrickx et al. 2007; Billeter et al. for the biodiversity states themselves, by using indicators 2008; Kleijn et al. 2009). Schmitzberger et al. (2005) and for each process (Firbank et al. 2008). Furthermore, it Kleijn et al. (2009) used N input as a single indicator, explicitly relates to other functions of the land, as pro- because fertiliser use is generally correlated with yield and tecting biodiversity in agricultural landscapes is of major other variables characterising farming (e.g. pesticide use, importance for its provision of agroecosystem services agricultural population density, cattle density). such as climate regulation, water regulation, erosion con- Although a large number of conservation studies trol, pollination, biological control and food production showed a negative inﬂuence of increasing amounts of fer- (see more detail in Costanza et al. 1997; Daily 1997; de tiliser application on biodiversity (mainly vascular plants Groot et al. 2002). and birds) at ﬁeld level (cf. Wilson et al. 1997; Donald To explore the impacts of agricultural land-use change et al. 2001; Joyce 2001; Vickery et al. 2001; Zechmeister on biodiversity in Taihu Lake Basin in China, we ﬁrst and Moser 2001; Roschewitz et al. 2005; Herzog et al. applied the approach of Firbank et al. (2008) using data 2006), the rapid growth in China’s per hectare chemi- from literature and a household survey in paddy agricul- cal fertiliser application, from less than 10 kg around tural areas of the basin (Table 1). Although the conversion the 1960s to more than 330 kg in 2007, has contributed of natural habitats to agriculture, especially through for- signiﬁcantly to the growth in grain production (SSBC est clearance, globally has most impact on biodiversity 2007). With the objectives of sustaining or increasing farm- (the third process of Firbank et al. 2008), landscapes of ers’ proﬁts and alleviating poverty, enhancing agricultural the basin have showed little large-scale transformation production is essential (Hengsdijk et al. 2007). Thus, opti- between agricultural and natural habitats in recent decades. mising application of fertiliser, in other words, optimised Therefore we focus on changes in land management and nutrient management (Cassman et al. 1998; Pampolino landscape, reducing the number of processes to two. et al. 2007; Wang et al. 2007), is required in order to Second, the perception and preference of land-use achieve both environmental (reduce biodiversity loss) and functions among different stakeholders around the basin economic (increase production) objectives. are identiﬁed. In terms of land-use change, the variety Crop management was analysed at farm level, based of farmers’ and policymakers’ preferences largely impacts on a household survey performed in 2008, including 320 on the trade-offs among objectives (mainly economic and farms in three cities of Wuxi, Changzhou and Zhenjiang 122 M. Asai et al. Table 1. Framework of the research and overview of agricultural land-use pressures on biodiversity in northern Taihu Lake Basin. Level Main driving a b c (scale ) Location (area ) Data source Time period forces Pressures Impacts on biodiversity Land man- Northwest Household survey 2007 Intensive use of Excessive N input Direct species loss agement Basin Wuxi- in 2008 and fertiliser (+) (<1 km) Changzhou- interviews in Zhenjiang 2009 (0.5 ha) N leaching to environ- Terrestrial ecosystem ment degradation Aquatic ecosystem degradation Landscape Northwest Basin Wu et al. (2009) 1989–2002 Total output value Paddy ﬁeld loss Low availability of structure Yixing (12 sites of grain (–) semi-natural elements (1–50 km) of 0.25 km ) Non-agricultural Fragmentation Fragmentation of population (+) microhabitats Aquatic products Loss of ﬁeld margin (+) Rural construction Habitat loss in paddy ﬁeld (+) Xiejia Village Ellis et al. (2000) 1930–1994 Aquatic products Reduced share of Habitat loss in natural area (1.5 km ) (+) semi-natural elements (%) Residential areas Introduction of alien (+) species Agricultural land (–) Construction land (+) a b c Notes: Categories of scale were based on the deﬁnition of Dirnböck et al. (2008). The value 0.5 ha at ‘land management’ indicates an average production area per farm. (+) indicates that the driving force increases the value of ‘pressures’ and hence ‘impacts on biodiversity’, while (–) indicates that the force reduces. International Journal of Biodiversity Science, Ecosystem Services & Management 123 (Table 1). In northwest Taihu Lake Basin, farmers start 2008; Verburg et al. 2009), when assessing impacts of land- adopting a new fertilisation strategy to improve nutrient use change on indicators such as biodiversity. Land-use management, based on site-speciﬁc nutrient management functions can be referred to as the goods and services pro- (SSNM; Dobermann et al. 2002; Reidsma et al. 2011). vided by the land-use systems and ecosystems within the Farmers are stimulated to use, as locals call it, formula fer- landscape (Verburg et al. 2009; Paracchini et al. 2011). For tiliser. The proportions of nitrogen (N), phosphorus (P) and instance, conservation goals for biodiversity in agricultural potassium (K) in formula fertiliser are adjusted to the soil landscapes are actually linked with agroecosystem services fertility level of each farmer’s ﬁeld, and thus it is expected such carbon storage, ﬂood control, forage production, out- to result in a decreasing amount of fertiliser application due door recreation, crop pollination and water provision (Chan to more efﬁcient use of nutrients. The collected data were et al. 2006; Willemen et al. 2008; de Groot et al. 2010). used to compare fertiliser use among technologies (conven- Land cover at one location has more than one function tional nutrient management or applying formula fertilisers) (e.g. Rossing et al. 2007; Renting et al. 2009), and in the and soils (sandy, loamy or clay). last decade, multi-functional land use has become a topic of interest for policymakers concerned with rural develop- ment with increased awareness of the need for sustainable land use (Parra-Lòpez et al. 2008, 2009). Assessing pressures on biodiversity at landscape level – When land-use changes, the variety of farmers’ and transformation of the agricultural landscape policymakers’ preferences largely impacts on the trade-offs between food production as primary land use and preser- A number of studies identiﬁed positive relations between vation of biodiversity as performance of secondary use. numbers of species and area of semi-natural habitat (Bruun Therefore, in September 2009, land-use functions that are 2000; Steffan-Dewenter and Tscharntke 2001; Kremen important for sustainable development of the agricultural et al. 2002; Dormann et al. 2007; Hendrickx et al. 2007; Billeter et al. 2008). For instance, Billeter et al. (2008) sector were identiﬁed and weighted for their importance analysed the share of natural elements (% area) in 25 in the region according to different stakeholders (see more agricultural landscapes distributed across seven European detail in Reidsma et al. 2009). In total, 11 stakeholders countries (France, Belgium, the Netherlands, Germany, from 4 groups were selected. They were two ofﬁcials, four Switzerland, Czech Republic and Estonia), and concluded researchers, two local extension ofﬁcers and three local that the largest contribution to total species richness of vas- farmers. cular plants, birds and ﬁve arthropod groups comes from natural and semi-natural habitats and is directly inﬂuenced by their area in most agricultural landscapes. Further, look- Results ing at landscape structure in a broader sense, landscape Crop management fragmentation has negative impacts on habitat suitability and biodiversity (Noss 1990; Di Giulio et al. 2009). According to the extension ofﬁces in our case study area, –1 Changes in landscape structure were assessed based on recommended N application is lower than 360 kg N ha , –1 the observations of ﬁne-scale (<30 m) agricultural land- but preferably around 200 kg N ha for rice. By using for- scape transformation processes in northwest Taihu Lake mula fertiliser, a reduced N input of around 30% compared Basin: Xiejia Village of Xueyan Township, Wujing County with compound fertiliser is expected. Figure 2 however during 1930–1994 (Ellis et al. 2000) and a single ﬁeld shows the complexity of impacts of soil type and fertiliser –1 research site in Yixing County during 1989–2002 (Wu type on N input (kg ha ) and the related rice yield. There is et al. 2009). These studies stratiﬁed a village landscape into no relationship between the yields and the current N input, about 35–40 ﬁne-scale landscape components with rela- and effects of soil type and fertiliser type are not evident. tively homogeneous ecosystem processes (called ecotopes) Wang et al. (2004) reported that the optimal N applica- –1 by gathering data from aerial photography, ﬁeld surveys, tion rate is 225–270 kg N ha for rice, based on their ﬁeld local knowledge, household surveys, interviewing elder experiments in Suzhou, the east part of Taihu Lake Basin, –1 villagers and historical sources. Using the well-speciﬁed while Jing et al. (2007) suggested only 150–200 kg N ha . landscape structure at the village landscape level, the The high N input observed on the farms in the survey, up to –1 exploration of its impact on biodiversity was conducted. 1000 kg N ha (Figure 2), leads to severe N losses to the environment (e.g. Wang et al. 2004), resulting in reduced terrestrial and aquatic biodiversity. Using formula fertiliser has potential to reduce N losses, but application according Preference of land-use functions to principles of SSNM (Dobermann et al. 2002; Hu et al. In the previous sections we observed trade-offs between 2007) needs to be improved through training. Survey data food production and biodiversity, which are simultaneously reveal that around 20% of the farmers currently use dif- provided by the same land use, although there is often a ferent formula of fertilisers, but they have not reduced the negative relationship. It has been argued that there should total amounts of nutrients applied. Hence, nutrient losses to be more attention for land (use) function change instead the environment and impacts on biodiversity have not been of focussing on land-cover change (Bakker and Veldkamp reduced. 124 M. Asai et al. Clay*CF Clay*FF Loam*CF Loam*FF Sand*CF Sand*FF 0 100 200 300 400 500 600 700 800 900 1000 1100 –1 N input (kg ha ) –1 –1 Figure 2. Relationship between N input (kg ha ) and rice yield (ton ha ) in different combinations of soil type (clay, loam and sand) and fertiliser type (FF, formula fertiliser; CF, compound fertiliser). Notes: The identiﬁcation of the soil was based on what farmers indicated and can therefore differ from ofﬁcial soil data. As most soils are loamy clay, some farmers may call their soil sandy when it is only slightly sandy. Source: Household survey in 2008. Transformation of the agricultural landscape Preference of land-use functions From the ﬁne-scale observation of a typical densely pop- For Taihu Lake Basin, nine land-use functions were iden- ulated village landscape of Xiejia in Ellis et al. (2000), tiﬁed and weighted for their importance in the region by we selected the following semi-natural elements: annual researchers, government ofﬁcials, extension ofﬁcers and weeds, tall grasses, bamboo, bushes and weeds, trees farmers (Reidsma et al. 2009) (Table 2). These included (medium), trees (mature), graves, public trees, wetland three environmental (including biodiversity as an indica- crops and wetland vegetation. The share of semi-natural tor of biotic resources), three economic and three social area of the village (Ellis et al. 2000) was 5.5% in 1994, land-use functions. Although the weights of the three indicating that this percentage was relatively low as com- dimensions were similar, different stakeholders had differ- pared with the observations of Billeter et al. (2008), ent views on the importance of these functions. According ranging from 2.7% to 53%. Including ponds and canals, to researchers, the sequence should be social (36%) > semi-natural elements potentially beneﬁting aquatic bio- economic (33%) > environmental (31%); government ofﬁ- diversity, the share increases to 12.4% in 1994. In 1930, cials and local extension ofﬁcers thought that the sequence the shares were 9.2% and 14.1% with and without ponds should be economic (50% and 45%) > environmental and canals, respectively, indicating that the share of semi- (33% and 35%) > social (17% and 20%); and according to natural area has always been low and has further decreased farmers it should be environmental (37%) > social (33%) during the last century. > economic (30%). This shows that all stakeholders are At the village landscape level in Yixing County, aware of the multiple functions of agricultural land use, between 1989 and 2002 signiﬁcant declines in the propor- and that besides food production, also functions like provi- tion of village scale area covered by paddy (about –10%) sion of work and biodiversity conservation are important. and increase in built-up surface (about +1%) and aquacul- ture (about +5%) were observed. Although the percentage Discussion of increase in built-up surface was relatively small in 1989– Biodiversity conservation in Taihu Lake Basin 2002, the previous period of 1963–1989 showed about 5% The previous sections underpin that agriculture in Taihu increase of built-up surface (Wu et al. 2009). In the north- Lake Basin is intensive. As agricultural land use occu- west Taihu Lake Basin as a whole, the number of ecotope pies most of the land area, biodiversity is likely to be low, classes doubled between 1940s and 2002 (17.6 types of as reﬂected in the low MSA value of 21% in Jiangsu as ecotope to 34.7) (Ellis et al. 2009). This largely reﬂects the evaluated with the method proposed by Alkemade et al. increases in anthropogenic land uses such as houses and (2009). Conservation strategies should focus on reducing roads, implying that expansions of landscape heterogeneity impacts on biodiversity, which are considered important in as indicators of habitat fragmentation were associated with the region (last column in Table 1), they should consider increases in population density and economic development the context and they should be feasible. (Ellis et al. 2009). –1 Rice yield (ton ha ) International Journal of Biodiversity Science, Ecosystem Services & Management 125 Table 2. The comparison of average weights (%) on different land-use functions among four groups of stakeholders in the basin. Local extension Group Researcher ofﬁcer Farmer Ofﬁcial Environmental functions A 31 35 37 33 Abiotic resources 34 40 45 38 Biotic resources 36 28 32 30 Ecosystem processes 30 33 23 33 Economic functions B 33 45 30 50 Industry and services 21 20 27 25 Economic production 41 35 45 45 Physical production 38 45 28 30 Social functions C 36 20 33 17 Provision of work/livelihood 34 30 42 40 Human health 31 20 27 40 Food security 35 50 32 20 Notes: Four groups and 11 stakeholders in total were selected and interviewed in September 2009. They were two ofﬁcials, four researchers (two in social science, two in natural science), two local extension ofﬁcers and three local farmers. A is the average weight of environmen- tal, B is the average weight of economic and C is the average weight of social functions. A, B and C add up to 100%. Within a dimension, the separate functions also add up to 100%, hence the weight of ‘abiotic resources’ for sustainable development considered by researchers is 31% × 34% = 11%. According to Kleijn et al. (2009), in Europe reduc- requirements and income. Thus adopting strategies that –1 ing inputs from 75 to 0 kg N ha resulted in about the can serve multiple objectives, such as SSNM that can sus- same estimated species gain as reducing inputs from 400 tain high yields and hence income, and at the same time –1 to 60 kg N ha . In Taihu Lake Basin, without any fertilis- reduce nutrient leaching and hence water pollution, seems –1 ers, rice yields around 4.5–6.0 ton ha can be obtained to be feasible. However, from our analysis (Figure 2), the under current soil fertility conditions (Wang et al. 2004; policy stimulating farmers to use formula fertiliser was Jing et al. 2007), but considering the objectives of increas- not strong enough. This is highly required to improve ing food production and self-sufﬁciency, this is not enough. the agricultural policy in terms of informing about the Furthermore, in the long term the productivity will drop precise method, regulating the amount of N inputs or if no inputs are supplied. Moving to extensive fertiliser providing farmers with incentives to adopt the formula application is thus not feasible, which would imply that fertiliser. relatively little species gain can be obtained in agricul- Literature on landscape structures around the basin tural ﬁelds. Closely looking at the relationships in Kleijn showed that the low availability of semi-natural elements in et al. (2009), however, also shows that there is a large agricultural landscapes is a major threat factor for sustain- variability along the relationship, which is largely due ing biodiversity. Further, increasing heterogeneity of land- to local characteristics and speciﬁc management. When scape structures indicated the fragmentation of ecological farmers consider both objectives of food production and habitats as a consequence of development of anthropogenic increasing biodiversity, management may be adapted such land uses. Regarding this, another policy implemented by that it contributes to both (e.g. Feng et al. 2006). At Jiangsu Department of Agriculture from July 2007, that is, higher levels, whether reducing agricultural intensity will converting arable land along water bodies to buffer zones improve biodiversity can be argued. Although Reidsma with trees to reduce nutrient leaching, can give a win–win et al. (2006) projected that reducing agricultural intensity situation, as the trees in the buffer zones can host a vari- would lead to increased biodiversity in Europe, Glendining ety of species, while the prevention of nutrient leaching et al. (2009) showed that reducing agricultural intensity will lead to increased aquatic biodiversity (Weijters et al. may not always lead to improved sustainability or bio- 2009). A literature review by Klok et al. (2002) showed diversity conservation, as more area is needed for food that riparian buffer zones wider than 20 m can reduce N production. and P leaching by more than 80%. Maintaining the current level of food production is considered an important objective by government ofﬁcers The multi-scale cause–effect approach (Table 2). The high weights that farmers gave to envi- ronmental land-use functions compared with government The MSA approach at the global scale of Alkemade et al. ofﬁcials and extension ofﬁcers were mainly due to the (2009) lacks focus on scale issues, which are important lower importance farmers gave to food production. Food at regional level. In reality, land-use assessments based self-sufﬁciency is not an aim of farmers in the region, mainly on land-cover observations often tend to lack focus as they often have off-farm income. Farmers’ decisions on the full diversity of land uses (Bakker and Veldkamp on crop and nutrient management depend more on labour 2008; Verburg et al. 2009). Land identiﬁed as arable often 126 M. Asai et al. Agricultural land-use type: land management Option a. Fixed MSA per LUT 1. Identify agricultural land- 2. Define relationship LUT use types representing agricultural land- changes in policies and use type and farmer’s decision-making biodiversity impact Option b. Define relationship land (MSA ) LUT management indicator ‘N surplus’ with MSA + indicate where different LUTs are in the graph 3. Calculate remaining MSA based on land management: MSA = Σ (MSA RS ) lm LUT=1,n LUT LUT Agricultural land: landscape structure 4. Estimate % of semi- 5. Define ecosystem quality of 6b. Estimate impact on connectivity. semi-natural elements (MSA ) natural area (RS ) and Depends on spatial configuration and distance to sn sn and constructed area (MSA ) nature areas. constructed area (RS ) cn cn 6a. Calculate remaining MSA based on land management and landscape structure (impact of extra habitat): MSA = MSA ·(1–RS %+RS %) + MSA ·RS % – MSA ·RS % ag lm sn cn sn sn cn cn Region: land use 7. Calculate regional MSA based on land uses MSA = MSA ·RS + Σ (MSA ·RS ) region ag ag LU=1,n LU LU Figure 3. Framework showing the multi-scale cause–effect approach of our biodiversity assessment. Mean species abundance (MSA) was calculated for different land uses in the Taihu Lake Basin. Notes: RS ,RS and RS indicate the relative area size of the land-use types (LUT), agricultural land use (ag) and other land uses LUT ag LU (LU), respectively. See text for further explanation. includes multiple land uses, resulting in high landscape To link the LUTs with mean species abundance, we can heterogeneity, and different crops are associated with dif- adopt a deﬁned relationship between the land management –1 –1 ferent species. In the Netherlands, for example, 5% of indicators, N input and N surplus (in kg ha year ) with the total number of species depend on agriculture, while MSA. Crop yields are highly related to N input, and high 39% depend on semi-natural landscapes (Lahr et al. 2007). input intensity also negatively impacts biodiversity. On the Further, a number of species are speciﬁcally associated other hand, using N surplus or N losses would give more with rice ﬁelds, as reviewed above. To consider and inte- direct information on the impact of N on biodiversity. For grate the differences of MSA values for different spatial instance, Firbank et al. (2008) provided clear evidence of scales, we propose a developed methodology for more N surplus impact on plant diversity in an empirical study speciﬁc evaluation (Figure 3). from the British countryside. The advantage of using N First, agricultural LUTs should be identiﬁed at land surplus is also that it gives information on possible per- management level. Although our analysis of nutrient man- vasive impacts on both terrestrial (Smart et al. 2003) and agement did not show clear differences in terms of aquatic (Carpenter et al. 1998) biota (Firbank et al. 2008). total N input among conventional and formula fertilis- Biodiversity for LUT can be deﬁned by either (1) ﬁxing ers, nutrient management can be changed dramatically MSA per LUT based on N input and/or N surplus or (2) by adopting SSNM, aiming for lower nutrient surpluses. indicating where different LUTs are in the graph. Each Further, this speciﬁed classiﬁcation enables to consider MSA per LUT (MSA ) multiplied by the relative area LUT different LUTs based on soil type, crop rotations and size of the agricultural LUT (RS ) is then aggregated LUT other environmental and socio-economic conditions. These into one value for the entire agricultural land cover of LUTs can directly be linked with other land-use func- the region: MSA . Until now, most knowledge is avail- lm tions, such as food production (e.g. van Ittersum and able on impacts of fertiliser use, but when more insights Rabbinge 1997). become available on other indicators such as pesticide use International Journal of Biodiversity Science, Ecosystem Services & Management 127 (Geiger et al. 2010), these can be included in the relation- us to take into account pressures of land management and ship. In our case, biodiversity conservation was considered landscape structure on biodiversity. important by farmers (Table 2), but most of them do not realise that their management practices have environmen- tal impacts. With improved SSNM, it is however possible Further research to reduce fertiliser inputs and increase nutrient use efﬁ- For more speciﬁc species conservation, other biodiver- ciencies (Dobermann et al. 2002). If improved training and sity indicators can also be selected as secondary land-use education are successfully conducted, and SSNM is widely functions. Moonen and Bàrberi (2008) identiﬁed various adopted by farmers within the region, the maximum value uses of biodiversity in agroecosystems: (1) conservation of MSA can be largely increased (Asai and Tokunaga lm of species, community, habitat or overall biodiversity for 2007). intrinsic, aesthetic, traditional and cultural values; (2) bio- Second, the impact of landscape structure on the diversity for improved agroecosystem functioning, based species abundance is identiﬁed and considered in com- on deﬁnition of agroecosystem functional groups; and (3) bination with MSA to arrive at the MSA in agricul- lm ag bio-indicators for environmental monitoring of the state tural landscapes (Figure 3). Although the assessment of and resilience of agroecosystem processes, agroecosys- Alkemade et al. (2009) using a rough land-cover map cat- tem sustainability or overall biodiversity. For assessment egorised most landscape structures around the basin as of these uses, more research should be done on the ‘intensive agriculture’ with an MSA value of 10%, they importance of species occurring in agricultural areas for also consist of areas of construction and semi-natural ele- agroecosystems and for society. ments, which have a certain negative or positive impact Preferences of farmers and policymakers towards land- on biodiversity. For instance, the ﬁne-scale observation of use functions vary, leading to impacts on the trade-offs land-cover changes in Xiejia Village in 1994 found by Ellis among multiple objectives. A better understanding of the et al. (2000) identiﬁed the share of semi-natural area as land-use functions and their interactions can increase will- 5.5% or 12.4% without and with ponds and canals, respec- ingness of farmers and policymakers to preserve biodiver- tively, and 5.1% for constructed elements, although Xiejia sity in terms of implementing new environmental land-use Village locates within the category ‘intensive agriculture’ policy and adopting environmentally friendly crop man- (Figure 1). Thus the total value of MSA either decreases ag agement. The shift from primary land use to the associated (because increasing area of construction is considered as land use is deliberate and relates to new initiatives, such negative impact on MSA ) or increases (because increas- ag as the functionality of ﬁeld margins (Marshall 2002) in ing area of semi-natural elements has positive impact on terms of providing a species-rich environment (cf. Marshall MSA ). Regarding this aspect, estimating shares of semi- ag 2002; Roy et al. 2003) and environmental regulation such natural and construction areas from aerial photographs as preventing N leaching (cf. Moonen and Marshall 2001; of randomly selected sites within the agricultural land Marshall and Moonen 2002). Using and discussing this cover (Palma et al. 2007) and deﬁning ecosystem qual- multi-scale cause–effect approach can improve this under- ity of the semi-natural elements (MSA ) and constructed sn standing. elements (MSA ) are required. For a more precise esti- cn mation, also the impacts on connectivity of semi-natural elements need to be assessed, which depends on the spa- Conclusion tial conﬁguration and the distance to surrounding nature areas. In their assessment, Alkemade et al. (2009) also The main aim of this study was to assess the impacts considered fragmentation of land cover as one of the envi- of agricultural land-use changes on biodiversity in Taihu ronmental drivers. However, what we argue here is a need Lake Basin in China and to identify conservation strate- to focus on fragmentation at micro level: only a few gies, including policies and technological innovations. An semi-natural areas may lead to better connectivity of nat- assessment at the global scale using the MSA approach ural areas, which largely increases regional biodiversity. estimated that in the region around 21% of the origi- Higher MSA might be achieved by strategically placing nal species were still present (Alkemade et al. 2009). To ag semi-natural elements, assuming successful results of the give perspectives for conservation strategies at regional environmental policy implemented by Jiangsu Department and farm levels, however, more detail was required. We of Agriculture from 2007. therefore analysed and reviewed agricultural pressures at Lastly, regional MSA based on land uses is esti- multi-spatial scales (Firbank et al. 2008) in the region region mated by summing all MSA values of each land use to obtain more insights in drivers and impacts in Taihu (Figure 3). In addition, an extra factor can be added related Lake Basin. With the objective of biodiversity conserva- to the spatial conﬁguration and the lateral interactions. tion in agroecosystems in the basin, using the framework For example, a higher MSA may positively inﬂuence the of Firbank et al. (2008) showed in which directions and ag MSA of nature areas. This approach is the same as that of by which driving forces land use changed and the conse- Alkemade et al. (2009), but the estimated MSA largely quences this has had for biodiversity in Taihu Lake Basin region depends on the values of MSA and MSA , which enable during the last decades. lm ag 128 M. Asai et al. Crop management at ﬁeld level is very intensive, and References policies and technologies aiming at reducing environmen- Alkemade R, van Oorschot M, Miles L, Nellemann C, Bakkenes tal impacts have not yet had effects. Analysis of the M, ten Brink B. 2009. GLOBIO3: a framework to investi- gate options for reducing global terrestrial biodiversity loss. landscape structure showed that the abundance of semi- Ecosystems. 12(3):374–390. natural elements is low and that fragmentation is high. Amano T, Kusumoto Y, Tokuoka Y, Yamada S, Kim E-Y, These processes indicate that agriculture is very inten- Yamamoto S. 2008. Spatial and temporal variations in the use sive in the basin and that conservation strategies to protect of rice-paddy dominated landscapes by birds in Japan. Biol biodiversity will have to compete with other land-use func- Conserv. 141(6):1704–1716. Asai M, Tokunaga S. 2007. A study on integrated pest man- tions, speciﬁcally with those increasing food production agement (IPM) programs in Thailand: a case study of and maintaining food self-sufﬁciency. Saraburi province. Chiikigaku Kenkyu (Stud Reg Sci). 37(3): In order to assess and identify conservation strate- 855–866. gies, we proposed a multi-scale cause–effect approach, Bakker MM, Veldkamp A. 2008. Modelling land change: the linking agricultural pressures at different scales (Firbank issue of use and cover in wide-scale applications. J Land Use Sci. 3(4):203–213. et al. 2008) to the MSA approach (Alkemade et al. 2009). Bambaradeniya CNB, Edirisinghe JP, De Silva DN, Gunatilleke Although the availability of species data would improve CVS, Ranawana KB, Wijekoon S. 2004. Biodiversity asso- the quantiﬁcation and applicability of the approach, also ciated with an irrigated rice agro-ecosystem in Sri Lanka. when there is a lack of species data, which is the case in Biodivers Conserv. 13(9):1715–1753. many (especially developing) countries, this approach is Bartholome E, Belward A, Beuchle R, Eva H, Fritz S, Hartley A, Mayaux P, Stibig H-J. 2004. Global land cover for the useful in providing a quick scan of biodiversity and the year 2000. Brussels (Belgium): European Commission, Joint impacts of agricultural land-use changes. In this study, no Research Centre. detailed quantiﬁcations have been made, but the approach Bignal EM, McCracken DI. 1996. Low-intensity farming sys- is illustrated using the data and literature analysed in this tems in the conservation of the countryside. J Appl Ecol. 33: study. 413–424. Billeter R, Liira J, Bailey D, Bugter R, Arens P, Augenstein Appropriate conservation strategies depend on the I, Aviron S, Baudry J, Bukacek R, Burel F, et al. 2008. importance that stakeholders give to different land-use Indicators for biodiversity in agricultural landscapes: a pan- functions, in this case mainly food production and biodi- European study. J Appl Ecol. 45(1):141–150. versity conservation. In general, strategies improving both Bruun HH. 2000. Patterns of species richness in dry grassland functions can be identiﬁed. Although the farm level anal- patches in an agricultural landscape. Ecography. 23(6):641– ysis on crop management showed that despite policies Carpenter SR, Caraco NF, Correll DL, Howarth RW, Sharpley stimulating formula fertiliser, farmers have not reduced AN, Smith VH. 1998. Non-point pollution of surface fertiliser application. Thus, there is scope for improved waters with phosphorus and nitrogen. Ecol Appl. 8(3): nutrient management with lower impacts on biodiversity 559–568. by improving extension services for farmer training and Cassman KG, Peng S, Olk DC, Ladha JK, Reichardt W, Dobermann A, Singh U. 1998. Opportunities for increased enhancing diffusion of SSNM through the region. SSNM nitrogen-use efﬁciency from improved resource management should be stimulated to improve biodiversity, reduce other in irrigated rice systems. Field Crops Res. 56(1–2):7–39. environmental impacts, maintain yields and thus prevent Chan KMA, Shaw MR, Cameron DR, Underwood EC, Daily GC. natural areas being lost. Furthermore, the environmental 2006. Conservation planning for ecosystem services. PLoS policy converting arable land along water bodies to buffer Biol. 4(11):e379. Cohen JE, Schoenly K, Heong KL, Justo H, Arida G, Barrion zones with trees increases semi-natural elements surround- AT, Litsinger JA. 1994. A food web approach to evaluating ing farm ﬁelds and water bodies and enhances the ability the effect of insecticide spraying on insect pest population of agricultural landscapes to sustain their multiple land-use dynamics in a Philippine irrigated rice ecosystem. J Appl functions. Acknowledging multiple functions of land when Ecol. 31(4):747–763. developing biodiversity conservation strategies will help to Costanza R, d’Arge R, de Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill RV, Paruelo J, et al. 1997. design feasible strategies that can be adopted by farmers The value of the world’s ecosystem services and natural and policymakers. capital. Nature. 387(6630):253–260. Daily GC. 1997. Nature’s services: societal dependence on natural ecosystems. Washington (DC): Island Press. Acknowledgements Dalgaard T, Hutchings NJ, Porter JR. 2003. Agroecology, scal- This study was carried out under the Chinese case study in ing and interdisciplinarity. Agric Ecosyst Environ. 100(1): the EU-funded LUPIS (Land Use Policies and Sustainable 39–51. Development in Developing Countries) project (www.lupis.eu). de Groot RS, Alkemade R, Braat L, Hein L, Willemen L. 2010. We are grateful to Martin van Ittersum (Wageningen University), Challenges in integrating the concept of ecosystem services Shusuke Matsushita (University of Tsukuba), Tomohiro Ichinose and values in landscape planning, management and decision (Keio University) and two anonymous reviewers for their valuable making. Ecol Complex. 7(3):260–272. comments. We also thank Michel Bakkenes for providing regional de Groot RS, Wilson MA, Boumans RMJ. 2002. A typol- estimates of the MSA from the GLOBIO3 model. MA’s research ogy for the classiﬁcation, description and valuation of was funded by The Rotary Foundation, and special thanks go to ecosystem functions, goods and services. Ecol Econ. 41(3): Tsukuba-Gakuen RC and Wageningen-Bergpoort RC. 393–408. International Journal of Biodiversity Science, Ecosystem Services & Management 129 Di Giulio M, Holderegger R, Tobias S. 2009. Effects of habi- Hidaka K. 1998. Biodiversity conservation and environmentally tat and landscape fragmentation on humans and biodiver- regenerated farming system in rice paddy ﬁelds. Jpn J Ecol. sity in densely populated landscapes. J Environ Manage. 48(2):167–178. 90(10):2959–2968. Hu R, Cao J, Huang J, Peng S, Huang J, Zhong X, Zou Y, Yang Dirnböck T, Bezák P, Dullinger S, Haberl H, Lotze-Campen J, Buresh RJ. 2007. Farmer participatory testing of standard H, Mirtl M, Peterseil J, Redpath S, Singh SJ, Travis J, and modiﬁed site-speciﬁc nitrogen management for irrigated et al. 2008. Scaling issues in long-term socio-ecological rice in China. Agric Syst. 94(2):331–340. biodiversity research: a review of European cases. Vienna Jackson LE, Pascual U, Hodgkin T. 2007. Utilizing and con- (Austria): Institute of Social Ecology, IFF – Faculty for serving agrobiodiversity in agricultural landscapes. Agric Interdisciplinary Studies, Klagenfurt University. p. 100. Ecosyst Environ. 121(3):196–210. Social Ecology Working Paper No. 100. Jing Q, Bouman BAM, Hengsdijk H, Van Keulen H, Cao W. 2007. Dobermann A, Witt C, Dawe D, Abdulrachman S, Gines HC, Exploring options to combine high yields with high nitro- Nagarajan R, Satawathananont S, Son TT, Tan PS, Wang GH, gen use efﬁciencies in irrigated rice in China. Eur J Agron. et al. 2002. Site-speciﬁc nutrient management for intensive 26(2):166–177. rice cropping systems in Asia. Field Crops Res. 74(1):37–66. Joyce C. 2001. The sensitivity of a species-rich ﬂood- Donald PF, Green RE, Heath MF. 2001. Agricultural intensiﬁca- meadow plant community to fertilizer nitrogen: the Lužnice tion and the collapse of Europe’s farmland bird populations. river ﬂoodplain, Czech Republic. Plant Ecol. 155(1): Proc R Soc B. 268(1462):25–29. 47–60. Dormann CF, Schweiger O, Augenstein I, Bailey D, Billeter R, Kleijn D, Kohler F, Báldi A, Batáry P, Concepción ED, Clough Blust GD, DeFilippi R, Frenzel M, Hendrickx F, Herzog F, Y, DÃaz M, Gabriel D, Holzschuh A, Knop E, et al. 2009. On et al. 2007. Effects of landscape structure and land-use inten- the relationship between farmland biodiversity and land-use sity on similarity of plant and animal communities. Glob Ecol intensity in Europe. Proc R Soc B. 276(1658):903–909. Biogeogr. 16(6):774–787. Klok C, Römkes P, Naeff H, Arts G, Runhaar H, van Diepen Ellis EC, Li RG, Yang LZ, Cheng X. 2000. Long-term change K, Noij G. 2002. Gebiedsgerichte milieumaatregelen voor in village-scale ecosystems in China using landscape and waterkwaliteit en natuur in Noord-Brabant. Wageningen (The statistical methods. Ecol Appl. 10(4):1057–1073. Netherlands): Alterra, WUR. Ellis EC, Neerchal N, Peng K, Xiao H, Wang H, Zhuang Y, Li Kremen C, Williams NM, Thorp RW. 2002. Crop pollination from S, Wu J, Jiao J, Ouyang H, et al. 2009. Estimating long- native bees at risk from agricultural intensiﬁcation. Proc Natl term changes in China’s village landscapes. Ecosystems. Acad Sci USA. 99(26):16812–16816. 12(2):279–297. Lahr J, Lammertsma DR, Booij CJH, Jagers op Akkerhuis Ellis EC, Wang SM. 1997. Sustainable traditional agriculture in GAJM. 2007. Nederlandse biodiversiteit: hoe belangrijk is the Tai Lake Region of China. Agric Ecosyst Environ. 61(2– het agrarisch gebied? Landschap. 24(3):109–115. 3):177–193. Maeda T. 2001. Patterns of bird abundance and habitat use in rice Feng W, Pan G, Qiang S, Li R, Wei J. 2006. Inﬂuence of long- ﬁelds of the Kanto Plain, central Japan. Ecol Res. 16(3):569– term fertilization on soil seed bank diversity of a paddy soil 585. under rice/rape rotation. Biodivers Sci. 14(6):461–469. Marshall EJP. 2002. Introducing ﬁeld margin ecology in Europe. Firbank LG, Petit S, Smart S, Blain A, Fuller RJ. 2008. Assessing Agric Ecosyst Environ. 89(1–2):1–4. the impacts of agricultural intensiﬁcation on biodiversity: Marshall EJP, Moonen AC. 2002. Field margins in northern a British perspective. Philos Trans R Soc B. 363(1492): Europe: their functions and interactions with agriculture. 777–787. Agric Ecosyst Environ. 89(1–2):5–21. Fu BJ, Niu D, Yu GR, Chen LD, Ma KM, Luo Y, Lu YH, [MEA] Millennium Ecosystem Assessment. 2005. Ecosystems Zhao WW. 2007. Application of landscape ecology in long and human well-being: biodiversity synthesis. Washington term ecological research. In: Hong S-K, Nakagoshi N, (DC): World Resources Institute. Fu B, Morimoto Y, editors. Landscape ecological applica- Moonen AC, Bàrberi P. 2008. Functional biodiversity: an tions in man-inﬂuenced areas. Dordrecht (The Netherlands): agroecosystem approach. Agric Ecosyst Environ. 127(1–2): Springer. p. 33–56. 7–21. Geiger F, Bengtsson J, Berendse F, Weisser WW, Emmerson M, Moonen AC, Marshall EJP. 2001. The inﬂuence of sown margin Morales MB, Ceryngier P, Liira J, Tscharntke T, Winqvist strips, management and boundary structure on herbaceous C, et al. 2010. Persistent negative effects of pesticides on ﬁeld margin vegetation in two neighbouring farms in south- biodiversity and biological control potential on European ern England. Agric Ecosyst Environ. 86(2):187–202. farmland. Basic Appl Ecol. 11(2):97–105. Noss RF. 1990. Indicators for monitoring biodiversity: a hierar- Glendining MJ, Dailey AG, Williams AG, van Evert FK, chical approach. Conserv Biol. 4(4):355–364. Goulding KWT, Whitmore AP. 2009. Is it possible to increase Ovenden GN, Swash ARH, Smallshire D. 1998. Agri- the sustainability of arable and ruminant agriculture by reduc- environment schemes and their contribution to the conserva- ing inputs? Agric Syst. 99(2–3):117–125. tion of biodiversity in England. J Appl Ecol. 35:955–960. Hendrickx F, Maelfait J-P, Wingerden WV, Schweiger O, Pain DJ, Pienkowski MW. 1997. Farming and birds in Europe. Speelmans M, Aviron S, Augenstein I, Billeter R, Bailey San Diego (CA): Academic Press. D, Bukacek R, et al. 2007. How landscape structure, land- Palma JHN, Graves AR, Bunce RGH, Burgess PJ, de Filippi R, use intensity and habitat diversity affect components of total Keesman KJ, van Keulen H, Liagre F, Mayus M, Moreno arthropod diversity in agricultural landscapes. J Appl Ecol. G, et al. 2007. Modeling environmental beneﬁts of sil- 44(2):340–351. voarable agroforestry in Europe. Agric Ecosyst Environ. Hengsdijk H, Guanghuo W, Van den Berg MM, Jiangdi W, Wolf 119(3–4):320–334. J, Changhe L, Roetter RP, Van Keulen H. 2007. Poverty and Pampolino MF, Manguiat IJ, Ramanathan S, Gines HC, Tan PS, biodiversity trade-offs in rural development: a case study for Chi TTN, Rajendran R, Buresh RJ. 2007. Environmental Pujiang county, China. Agric Syst. 94(3):851–861. impact and economic beneﬁts of site-speciﬁc nutrient man- Herzog F, Steiner B, Bailey D, Baudry J, Billeter R, Bukácek R, agement (SSNM) in irrigated rice systems. Agric Syst. De Blust G, De Cock R, Dirksen J, Dormann CF, et al. 2006. 93(1–3):1–24. Assessing the intensity of temperate European agriculture at Paracchini ML, Pacini C, Jones MLM, Pérez-Soba M. 2011. the landscape scale. Eur J Agron. 24(2):165–181. An aggregation framework to link indicators associated with 130 M. Asai et al. multifunctional land use to the stakeholder evaluation of Smart SM, Robertson JC, Shield EJ, van de Poll HM. policy options. Ecol Indic. 11(1):71–80. 2003. Locating eutrophication effects across British vege- Parra-López C, Groot JCJ, Carmona-Torres C, Rossing tation between 1990 and 1998. Glob Change Biol. 9(12): WAH. 2008. Integrating public demands into model-based 1763–1774. design for multifunctional agriculture: an application to [SSBC] State Statistics Bureau of China. 2007. China’s statistical intensive Dutch dairy landscapes. Ecol Econ. 67(4): yearbook. Beijing (PR China): China Statistical Publishing 538–551. House. Parra-López C, Groot JCJ, Carmona-Torres C, Rossing WAH. Steffan-Dewenter I, Tscharntke T. 2001. Succession of bee com- 2009. An integrated approach for ex-ante evaluation of public munities on fallows. Ecography. 24(1):83–93. policies for sustainable agriculture at landscape level. Land van Ittersum MK, Rabbinge R. 1997. Concepts in production Use Policy. 26(4):1020–1030. ecology for analysis and quantiﬁcation of agricultural input- Reidsma P, Feng S, van Keulen H, Shi X, Qu F. 2009. D10.1 output combinations. Field Crops Res. 52(3):197–208. Description of the pre-modelling phase concluding with the Verburg PH, van de Steeg J, Veldkamp A, Willemen L. 2009. procedure for integrated impact assessment in the case study From land cover change to land function dynamics: a of China. Wageningen (The Netherlands): LUPIS EU 6th major challenge to improve land characterization. J Environ Framework Programme. Manage. 90(3):1327–1335. Reidsma P, König H, Feng S, Bezlepkina I, Nesheim I, Vickery JA, Tallowin JR, Feber RE, Asteraki EJ, Atkinson PW, Bonin M, Sghaier M, Purushothaman S, Sieber S, van Fuller RJ, Brown VK. 2001. The management of lowland Ittersum MK, et al. 2011. Methods and tools for inte- neutral grasslands in Britain: effects of agricultural prac- grated assessment of land use policies on sustainable devel- tices on birds and their food resources. J Appl Ecol. 38(3): opment in developing countries. Land Use Policy. 28(3): 647–664. 604–617. Wang DJ, Liu Q, Lin JH, Sun RJ. 2004. Optimum nitrogen Reidsma P, Tekelenburg T, van den Berg M, Alkemade R. 2006. use and reduced nitrogen loss for production of rice and Impacts of land-use change on biodiversity: an assessment wheat in the Yangtse Delta region. Environ Geochem Health. of agricultural biodiversity in the European Union. Agric 26(2):221–227. Ecosyst Environ. 114(1):86–102. Wang G, Zhang QC, Witt C, Buresh RJ. 2007. Opportunities Renting H, Rossing WAH, Groot JCJ, Van der Ploeg JD, Laurent for yield increases and environmental beneﬁts through site- C, Perraud D, Stobbelaar DJ, Van Ittersum MK. 2009. speciﬁc nutrient management in rice systems of Zhejiang Exploring multifunctional agriculture. A review of concep- province, China. Agric Syst. 94(3):801–806. tual approaches and prospects for an integrative transitional Weijters MJ, Janse JH, Alkemade R, Verhoeven JTA. 2009. framework. J Environ Manage. 90(Suppl. 2):S112–S123. Quantifying the effect of catchment land use and water Roschewitz I, Thies C, Tscharntke T. 2005. Are landscape com- nutrient concentrations on freshwater river and stream biodi- plexity and farm specialisation related to land-use intensity of versity. Aquat Conserv Mar Freshw Ecosyst. 19(1):104–112. annual crop ﬁelds? Agric Ecosyst Environ. 105(1–2):87–99. Willemen L, Verburg PH, Hein L, van Mensvoort MEF. 2008. Rossing WAH, Zander P, Josien E, Groot JCJ, Meyer BC, Spatial characterization of landscape functions. Landsc Knierim A. 2007. Integrative modelling approaches for Urban Plan. 88(1):34–43. analysis of impact of multifunctional agriculture: a review Wilson JD, Evans J, Browne SJ, Jon RK. 1997. Territory distri- for France, Germany and The Netherlands. Agric Ecosyst bution and breeding success of skylarks Alauda arvensis on Environ. 120(1):41–57. organic and intensive farmland in southern England. J Appl Roy DB, Bohan DA, Haughton AJ, Hill MO, Osborne JL, Clark Ecol. 34(6):1462–1478. SJ, Perry JN, Rothery P, Scott RJ, Brooks DR, et al. 2003. Wu J-X, Cheng X, Xiao H-S, Wang H, Yang L-Z, Ellis EC. Invertebrates and vegetation of ﬁeld margins adjacent to 2009. Agricultural landscape change in China’s Yangtze crops subject to contrasting herbicide regimes in the farm Delta, 1942–2002: a case study. Agric Ecosyst Environ. scale evaluations of genetically modiﬁed herbicide tolerant 129(4):523–533. crops. Philos Trans R Soc B. 358(1439):1879–1898. Xiao X, Boles S, Liu J, Zhuang D, Frolking S, Li C, Salas W, Sala OE, Chapin FS III, Armesto JJ, Berlow E, Bloomﬁeld Moore Iii B. 2005. Mapping paddy rice agriculture in south- J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, ern China using multi-temporal MODIS images. Remote Kinzig A, et al. 2000. Global biodiversity scenarios for the Sens Environ. 95(4):480–492. year 2100. Science. 287(5459):1770–1774. Xie Y, Mei Y, Guangjin T, Xuerong X. 2005. Socio-economic Schmitzberger I, Wrbka T, Steurer B, Aschenbrenner G, Peterseil driving forces of arable land conversion: a case study J, Zechmeister HG. 2005. How farming styles inﬂuence bio- of Wuxian City, China. Glob Environ Change. 15(3): diversity maintenance in Austrian agricultural landscapes. 238–252. Agric Ecosyst Environ. 108(3):274–290. Zebisch M, Wechsung F, Kenneweg H. 2004. Landscape response Scholes RJ, Biggs R. 2005. A biodiversity intactness index. functions for biodiversity – assessing the impact of land-use Nature. 434(7029):45–49. changes at the county level. Landsc Urban Plan. 67(1– Settle WH, Ariawan H, Astuti ET, Cahyana W, Hakim AL, 4):157–172. Hindayana D, Lestari AS. 1996. Managing tropical rice Zechmeister HG, Moser D. 2001. The inﬂuence of agricultural pests through conservation of generalist natural enemies and land-use intensity on bryophyte species richness. Biodivers alternative prey. Ecology. 77(7):1975–1988. Conserv. 10(10):1609–1625.
International Journal of Biodiversity Science, Ecosystem Services & Management – Taylor & Francis
Published: Dec 1, 2010
Keywords: biodiversity; land-use change; multiple scales; nutrient management; landscape structure; policy options; land-use functions
Access the full text.
Sign up today, get DeepDyve free for 14 days.