• agri-environment schemes;
  • climate change;
  • conservation;
  • corridors;
  • farmland;
  • fragmentation;
  • habitat connectivity;
  • invasive species;
  • matrix habitat


  1. Top of page
  2. Summary
  3. Introduction
  4. Agri-environment schemes
  5. Acknowledgements
  6. References
  • 1
    The spread and intensification of agriculture are recognized as two of the most important global threats to wildlife. There are clear links between agricultural change and declines in biodiversity across a wide range of agricultural systems, and convincing evidence that reversing these changes leads to a recovery in wildlife populations.
  • 2
    Nearly 4 billion euros are now paid annually through agri-environment schemes (AES) to farmers in Europe and North America to make environmental improvements to their land. Where appropriately designed and targeted, these schemes have proved successful in reversing declines in farmland wildlife populations.
  • 3
    We argue that insights gained from island biogeography and metapopulation theory, and from theoretical and empirical assessments of landscape connectivity suggest that AES may carry substantial wider benefits, which so far have not been considered in the design and deployment of such schemes. ‘Softening’ agricultural land could offset some of the negative impacts on biodiversity of the loss and fragmentation of non-agricultural habitats; could allow species to adapt to climate change; could slow the spread of alien and invasive species; and could contribute positively to the coherence of key biodiversity and protected area networks. Indeed, AES might represent the only viable way to counter these threats.
  • 4
    We outline a number of ways in which these wider benefits could be taken account of in the design of AES and suggest a number of characteristics of the species most likely to benefit from them.
  • 5
    Synthesis and applications. Agri-environment schemes might bring significant environmental benefits to habitats other than farmland by restoring the agricultural matrix that separates them. Theoretical and empirical research suggests that matrix restoration improves a number of ecosystem functions. Where they are available, AES might therefore represent a viable mechanism for addressing a range of pandemic environmental problems such as global climate change. Little consideration has so far been given to these wider conservation applications in the design, deployment and monitoring of AES.


  1. Top of page
  2. Summary
  3. Introduction
  4. Agri-environment schemes
  5. Acknowledgements
  6. References

Agricultural land currently occupies approximately 38% of the planet's land surface, or around half its habitable area (Clay 2004). The modification and management of landscapes to produce food or other agricultural commodities for human consumption represents one of the most severe and widespread threats to global biodiversity (BirdLife International 2004; Foley et al. 2005). The distribution of agricultural land is a better predictor of wildlife threat status than the distribution of people (Scharlemann, Balmford & Green 2005). A projected doubling in food demand over the next 50 years means that urgent measures need to be developed to ensure sustainability and protect ecosystem services (Foley et al. 2005).

Agriculture impacts on biodiversity in two main ways. The first is through the clearance of pristine habitats for new planting, with the accompanying pressures of fragmentation of remaining habitats, pollution and disturbance. The area of agriculture in the developing world (particularly in South America and subSaharan Africa) may increase by more than 30% by 2050 (Tilman et al. 2001), occupying a new area approximately equal to that of all the planet's remaining rainforests (Mayaux, Achard & Malingreau 1998). In the developed world, on the other hand, agricultural area is predicted to fall (Rounsevell et al. 2005). The second driver of biodiversity decline is the intensification of existing agricultural systems, aimed at increasing crop yields per unit area. This has contributed more to increasing overall productivity of most commodities over the last 30 years than the planting of new land. While the global agricultural area increased by less than 8% between 1972 and 1992, global agricultural productivity more than doubled over the same period (UN Food and Agriculture Organization;,Rome,Italy,accessed23/01/06).

Direct comparisons of the relative impacts on wildlife of agricultural expansion and intensification are difficult. The loss of pristine habitats to agriculture might have an effect disproportional to its area, as there is a tendency for agricultural spread to be greater in regions of the planet with particularly high biodiversity (Scharlemann, Green & Balmford 2004). Crops such as oil palm, soybean and rubber are expanding greatly in areas of high and threatened biodiversity, leaving little of conservation value in their wake (Clay 2004; Aratrakorn, Thunhikorn & Donald 2006). Two common and possibly general patterns have been described following the conversion of pristine habitats to agriculture: a decline in species richness, and the replacement of species of high conservation concern with species of lower conservation threat status (Waltert, Mardiastuti & Mühlenberg 2004; Aratrakorn, Thunhikorn & Donald 2006). These patterns conform to the process of ‘biotic homogenization’ predicted by McKinney & Lockwood (1999). Conversion of pristine habitats to agriculture might have reduced the planet's carrying capacity for birds by 20–25% since pre-agricultural times (Gaston, Blackburn & Goldewijk 2003). Agricultural intensification also consistently results in losses of biodiversity. Many crops are grown across a gradient from low-input, low-yield systems through to systems where yield is maximized through the removal of competitors, the use of pesticides and fertilizers, increased mechanization, improved husbandry and the development of higher yielding cultivars (Clay 2004). In certain systems, the transition from low-intensity to high-intensity production can have a more severe impact on biodiversity than the conversion of pristine habitats to low-intensity agricultural systems (Donald 2004).

Birds have been widely used as indicators of agricultural environments, and increases in agricultural intensity have been linked with severe declines in farmland bird populations in Europe (Donald, Green & Heath 2001; Gregory et al. 2005), North America (Murphy 2003; Brennan & Kuvlesky 2005), Africa (Söderström, Kiema & Reid 2003) and Asia (Semwal et al. 2004). Similar effects have been documented in other taxa (Smith, Jennings & Harris 2005). The evidence linking agricultural intensification to biodiversity loss appears conclusive, although the causal and demographic mechanisms differ between species (Newton 2004).

Agri-environment schemes

  1. Top of page
  2. Summary
  3. Introduction
  4. Agri-environment schemes
  5. Acknowledgements
  6. References

Recognition of the severe ecological and environmental impacts of agricultural intensification, and their agronomic implications (Clergue et al. 2005), has led to the development of initiatives (here referred to as agri-environment schemes; AES) that provide state support to farmers for making environmental improvements to their land. These schemes aim to repair some of the environmental damage caused by agricultural intensification and ensure the future sustainability of agriculture, so measures are generally directed towards the wildlife and ecosystem services (such as soil and water protection) of farmed land. Because they are expensive and may result in reduced yields, AES are currently limited to richer countries, where agricultural intensification has generally been greatest. They include a wide range of measures available through the Common Agricultural Policy (CAP) in the European Union (EU) and through the US Department of Agriculture (Natural Resources Conservation Service) in the USA. Typical measures include the creation and restoration of field margins (filter strips), ponds, woodland and other non-farmed components of agricultural systems, support for traditional farming systems and the use of native species, grassland restoration and the provision of feeding and other resources for farmland wildlife. A number of prescriptions currently available through AES in England are given in Table 1. In the USA, the Conservation Reserve Program (CRP) provides expertise and funding to allow agricultural landowners to undertake a range of nature conservation and soil protection measures on their land. The scheme costs around 1·5 billion euros annually, substantially more than the budget of the US Fish and Wildlife Service, and has agreements on over 14 million hectares of farmland. Within the EU, Regulation 1257/1997 obliges member states to introduce AES, although uptake by farmers is voluntary. The various schemes are designed and implemented at a national level, resulting in a patchwork of different schemes that between them cover around 20% of EU farmland. The total cost of these schemes to the EU is more than 1·6 billion euros annually, added to which are further state funds provided unilaterally. In Europe, recent changes in the way subsidies are paid make adoption of these schemes financially advantageous. Two deployment strategies have evolved. Some schemes have adopted a ‘broad and shallow’ approach, offering relatively simple, low-cost management options over a very wide area. An alternative ‘narrow and deep’ approach offers more targeted, possibly higher maintenance, management options to fewer farmers.

Table 1.  Management prescriptions in Environmental Stewardship (England's revised AES) and some of the resources they provide that could soften intensively managed agricultural matrices. Adapted from Vickery et al. (2004)
Resource provided Management prescriptionAerial insectsGround/foliar invertebratesAquatic invertebratesSoil-dwelling invertebratesPollen/nectar sourceSeed/fruit sourceRefuge habitat
Hedgerow planting/restoration**   **
Ditch management/restoration* **  *
Pond and scrape creation/restoration* **  *
Water level management   *   
Grass strip/margin creation in arable fields *    *
Uncropped margin creation in arable fields    ** 
Reduced pesticide/fertilizer inputs*** ** 
Wild bird seed mix *   * 
Pollen/nectar mix**  *  
Winter stubbles     * 
Summer fallows***    

It is difficult to assess the success of AES because monitoring of their impact has generally been poor (Kleijn & Sutherland 2003). Some have demonstrably failed to meet their environmental objectives (Kleijn et al. 2001; Berendse et al. 2004). However, when appropriately designed and targeted (Evans, Armstrong-Brown & Grice 2002), such schemes are capable of providing measurable benefits to wildlife populations over wide geographical areas (Reynolds et al. 1994; Johnson & Igl 1995; Aebischer, Green & Evans 2000; Peach et al. 2001; Bradbury et al. 2004; Kleijn et al. 2004; Swetnam et al. 2004; Cunningham 2005). Nearly 75% of CRP participants reported increases in wildlife populations after joining the scheme (, accessed 23/01/06). AES currently represent the only realistic mechanism by which to achieve 2010 targets to reduce biodiversity loss across huge areas of agricultural land (Vickery et al. 2004).

The wider benefits of AES

AES have been designed and implemented primarily to benefit the physical environments and species of agricultural habitats. However, insights from island biogeography and metapopulation theory and from theoretical and empirical assessments of landscape connectivity suggest that they may have far wider ecological impacts.

theoretical background

A consistent by-product of the spread and intensification of agriculture has been the fragmentation and isolation of natural habitats within an increasingly hostile matrix. Fragmentation causes major ecosystem perturbation, and its effects are eclectic, leading to changes in species composition, community structure, population dynamics, behaviour, breeding success, individual fitness and a range of ecological and ecosystem processes (Laurance et al. 2002; Fahrig 2003; Opdam & Wascher 2004). These effects appear particularly severe when the matrix between fragments is formed by agricultural land (Aberg et al. 1995; Bayne & Hobson 1997; Joly et al. 2001).

The potential threats of fragmentation were recognized from theories developed by MacArthur & Wilson (1967) to explain patterns of species richness and turnover on oceanic islands. It was soon realized that at least some of this new theory might also apply to isolated patches of habitat on the mainland (Diamond 1975; May 1975), leading to the evolution of metapopulation theory (Hanski & Gilpin 1991). Theory quickly filtered through into conservation practice, and wildlife corridors and stepping-stones became recognized as potential ways of reducing fragmentation effects. Corridors are now widely used in conservation practice at a range of spatial scales from tens of metres to hundreds of kilometres. Plans are underway to create habitat corridors on national, international and continental scales, and landscape-scale conservation is starting to replace the protection of isolated patches as a key conservation objective at wide spatial scales (Bennett 1999; Henry et al. 1999; Bennett 2004; Jongman, Kulvik & Kristiansen 2004; Opdam & Wascher 2004). There are currently more than 150 landscape-scale or regional networks in place or under development globally (Bennett 2004).

However, a number of reviews have concluded that there is little evidence that corridors increase functional connectivity (Hobbs 1992; Dawson 1994; Wiens 1995; Beier & Noss 1998; Donald 2005). Others have gone further, and suggested that corridors carry risks that might actually outweigh their advantages (Simberloff & Cox 1987; Earn, Levin & Rohani 2000; Pienimaki & Leppakoski 2004). Artificially increasing connectivity might influence metapopulation structure in complex and possibly undesirable ways (Altizer, Harvell & Friedle 2003; Cale 2003). In the absence of conclusive evidence of the functional benefits of corridors, the costs of establishing them need to be compared critically against the costs and potential benefits of alternative conservation approaches (Simberloff et al. 1992).

These equivocal conclusions suggest that island biogeography theory provides only a crude approximation to patterns in mainland situations (McCoy 1982; Gascon & Lovejoy 1998; Opdam & Wiens 2002), largely because the permeability of the matrix is likely to be higher in mainland than oceanic island situations (Brotons, Mönkkönen & Martin 2003; Antongiovanni & Metzger 2005; Bender & Fahrig 2005). In addition, island theory considers the matrix to be internally homogeneous, a situation rarely encountered in mainland situations (Revilla et al. 2004). Ironically, the poor fit of classical island biogeography theory to mainland contexts makes this a useful model for assessing the effects of improving matrix habitats, as isolation can now be viewed not only in terms of distance but also the quality of the matrix habitat. This has theoretical support, and the models of Malanson (2003) and Bender & Fahrig (2005) suggest that dispersal and patch colonization rates are related to the structure of the matrix. Empirical evidence of the importance of matrix permeability to patch colonization rates comes from studies of both vertebrates (Verbeylen et al. 2003) and invertebrates (Chardon, Adriaensen & Matthysen 2003). There is an emerging consensus that communities in fragments, even very large fragments, are profoundly influenced by the quality of the surrounding matrix (Gascon & Lovejoy 1998; Fahrig 2001; Brotons, Mönkkönen & Martin 2003; Jules & Shahani 2003; Lomolino & Smith 2003; Rodewald 2003; Carroll et al. 2004; Gray, Smith & Layva 2004; Murphy & Lovett-Doust 2004; Fischer et al. 2005; Wethered & Lawes 2005). The negative effects of isolation are reduced as the quality of the matrix increases (Carroll et al. 2004). Enhancing the matrix increases its permeability to potential colonists, reducing extinction rates in habitat fragments (Marzluff & Ewing 2001; Ricketts 2001; Antongiovanni & Metzger 2005; Berry et al. 2005). Increased permeability in improved matrix habitats may result from a greater likelihood to attempt a crossing, increased mean step length and better directionality (Schooley & Wiens 2004; Ross, Matter & Roland 2005). Matrix restoration may also enhance the connectivity function of existing corridors and stepping-stones (Baum et al. 2004; Revilla et al. 2004), improve feeding opportunities for organisms in fragments (Tubelis, Lindenmayer & Cowling 2004), promote genetic variation (Berry et al. 2005) and reduce edge and small area effects (Rodewald 2003). Changes in matrix quality may have profound effects on species’ interactions within islands (Cantrell, Cosner & Fagan 1998). A fundamental point is that landscape-scale distributional patterns can result from just small-scale behavioural responses by individual organisms (Levey et al. 2005).

practical applications

In many areas of Europe and North America, areas of high biodiversity exist as fragments of formerly larger areas within a matrix of intensive agriculture. The theoretical background to the problems of isolation and poor connectivity, and the availability in the form of AES of a mechanism to alter matrix habitats over vast areas, suggests a number of practical applications. We identify three interrelated pandemic threats to biodiversity, likely to be particularly severe in intensively managed, monocultural and poorly connected agricultural landscapes (Roschewitz, Thies & Tscharntke 2005), to which the widespread but carefully targeted deployment of AES could offer at least partial solutions.

Habitat loss, fragmentation and reduced network coherence

Fragmentation effects have been identified in habitat islands in agricultural matrices in Europe and North America (Nupp & Swihart 2000; Jacquemyn, Butaye & Hermy 2003). AES that improve matrix quality by ‘softening’ agriculture could play an important role in reducing fragmentation effects in isolated habitat patches, and represent the most viable delivery mechanism for landscape-scale ecological restoration (Smallshire, Robertson & Thompson 2004; Vickery et al. 2004). For example, the models of Sutcliffe et al. (2003) of movement between habitat patches by butterflies across a farmland matrix suggested that restoring field margins to grassy banks (an option already available in a number of AES) would lead to increased rates of interpatch movement. Protected area networks, and other sites of key importance to biodiversity (such as BirdLife International's Important Bird Areas; BirdLife International 2004), can be viewed as very large islands in a mixed matrix. Even at such large spatial scales, improving the matrix can have demonstrable effects. For example, a study of large predatory mammals in North American parks concluded that if matrix quality were to decline, the area of the parks would need to increase greatly if populations were to persist (Carroll et al. 2004). Simulation models suggest that improving the quality of the matrix can offset the increased extinction risk caused by losses of island habitat of up to 60% (Fahrig 2001). While a number of studies have been designed to compare permeability of structurally very different matrix types (Lindenmayer et al. 2001), we are not aware of any that compare agricultural matrices of differing intensity (although see Gray, Smith & Layva 2004; Fischer et al. 2005).

Little consideration has been given to the existing distribution of non-farmed habitats in the design, implementation and monitoring of AES. However, AES provide a number of resources that might soften intensive agricultural matrices (Table 1). Greater awareness and further research might lead to the development of an integrated strategy whereby the design and implementation of AES consider not only the benefits to agricultural ecosystems but also the less visible and tractable benefits to off-farm wildlife. The Ecological Main Structure (Ecologische Hoofdstructuur; EHS) initiative in the Netherlands has already started to link isolated wildlife habitats together by reducing the intensity of the agricultural matrix that connects them.

The groups that benefit most from matrix restoration are likely to be those with intermediate powers of dispersal, such as reptiles, amphibia, mammals and some invertebrates (Berger 2004; Burel et al. 2004; Driscoll 2004; Berry et al. 2005). Organisms with very low rates of dispersal, such as some invertebrates, plants and trees, may not benefit from an enhanced matrix that has the high temporal heterogeneity of land under agricultural management (Baudry et al. 2003; Matlack & Monde 2004). Some characteristics of species likely to benefit most from matrix restoration are listed in Table 2. Even species incapable of entering matrix habitats stand to benefit from the enhanced biodiversity within habitat islands that matrix restoration is likely to bring.

Table 2.  Some characteristics of species likely to benefit most from matrix restoration (adapted from Henle et al. 2004; Donald 2005)
 1.Species with high habitat/climate envelope specificity, or species whose climate envelopes are predicted to move most; these species’ ranges are likely to change most and their transitional and final ranges are likely to be smallest (Hobbs & Hopkins 1991)
 2.Species with poor dispersal powers relative to the gaps between fragments; these are likely to be less able to occupy new sites than species with high dispersal powers (Gaston & Blackburn 2002)
 3.Species with low survival or persistence in hostile matrix habitats
 4.Species with high habitat specificity; their transitional and final ranges are likely to contain little of the right habitat (Julliard, Jiguet & Couvet 2004) and they may be less able to cross matrix habitats
 5.Species occupying habitats that are already highly fragmented
 6.Species occupying habitats that are particularly vulnerable to climate change; in western Europe these include native pinewoods, calcareous grassland, mesotrophic lakes and riverine and wetland ecosystems (van Ierland et al. 2001)
 7.Species that are limited to higher latitudes and altitudes; their ranges are likely to become smaller and more fragmented under climate change
 8.Species with seasonally variable food requirements; these may require specific combinations of habitats and the ability to move between them
 9.Species with small or widely fluctuating populations; increasing connectivity might be more effective at preventing the extinction of small populations than larger ones (Henle et al. 2004)
10.Species requiring moist or wet soil habitats; wet habitats of ecological importance are likely to become more fragmented under climate change (Naden & Watts 2001)
11.Larger species, species at higher trophic levels, species that require large areas of habitat and habitat interior species; these generally require larger areas of habitat, necessitating more movement between patches (van Dorp & Opdam 1987; Soulé & Gilpin 1991)
12.Species dependent on climax, rather than seral, habitats; these tend to have lower fecundity, dispersal ability and tolerance to fragmentation (Travis & Dytham 1999; Opdam & Wascher 2004)
13.Species with relatively small brain size; these are less adaptable to environmental change and do less well in hostile matrices (Schultz et al. 2005)
14.Species showing other traits, including low reproductive output, low tolerance of disturbance, low survival in matrix habitats and highly social behaviour, that make them particularly sensitive to fragmentation (Hudgens & Haddad 2003; Henle et al. 2004)
Climate change

Current estimates predict a global rise in temperature of between 1·4 and 5·8 °C within the next century (IPCC 2001). This is likely to have profound impacts on wildlife; indeed, the effects of global climate change on plants and animals are already detectable (Parmesan & Yohe 2003). Global climate change is expected to cause the extinction of many species (Thomas et al. 2004) yet relatively little has been done to develop strategies for helping wildlife to adapt to predicted changes (Hulme 2005). Perhaps the most profound effect of climate change will be a redistribution of species’ ranges as they track moving climate envelopes; such changes have already been observed and appear to follow patterns predicted by climate envelope models (Walther, Berger & Sykes 2005). Their ability to survive this transition may depend on the availability of suitable habitats within their transitional and final ranges and their ability to reach them. This in turn may depend largely on landscape structure, and the potentially synergistic effects of landscape structure and climate change are likely to be important, although currently poorly understood, determinants of future ranges (Honnay et al. 2002; Opdam & Wascher 2004; Hulme 2005). In regions where intensive agriculture has isolated natural habitats in a hostile matrix, the ability of species to move across a landscape in a series of colonizations and extinctions may be reduced (Honnay et al. 2002; Higgins, Lavorel & Revilla 2003). In landscapes in which the existing degree of fragmentation still permits persistence, the shift of species’ ranges may be retarded but not blocked, whereas species will be incapable of crossing landscapes in which fragmentation has reduced the carrying capacity below that necessary to sustain a metapopulation (Opdam & Wascher 2004). For example, Warren et al. (2001) showed that the predicted range expansion of butterflies in the UK proceeded more slowly in heavily fragmented environments, and concluded that the negative effect of fragmentation outweighed the positive effects of warmer climate. The potential of increasing habitat connectivity at landscape scales to help reduce the negative effects of climate change on wildlife was first proposed in the 1980s (Peters & Darling 1985) and has been discussed several times since (Dawson 1994; Chen, Zhang & Li 2003; Hulme 2005). Creating or maintaining corridors of natural habitat are unlikely to be the best way of delivering this connectivity for many species (Donald 2005), especially those with poor dispersal (Hulme 2005), although if they were to be deployed for this purpose simultaneously improving matrix quality would improve their function (Baum et al. 2004). Matrix restoration could, however, do much to improve habitat connectivity (Baudry et al. 2003) and delivery mechanisms for this already exist in AES and other agricultural support instruments.

The potential of AES to tackle problems such as climate change has not been generally considered in the design and deployment of such schemes. Climate envelope models are now available for many species, predicting the future distributions of species’ ranges under different climate change scenarios. These models also allow prediction of those species or groups likely to be most affected by shifting climate envelopes (Thuiller, Lavorel & Araujo 2005). Any strategy developed to help species to adapt to climate change by targeting AES could use such models to identify where species’ intermediate or final predicted ranges coincide with areas of low matrix quality and low habitat availability. The taxa that might benefit most from such an approach are likely to exhibit some or many of the characteristics listed in Table 2.

The spread of aliens and invasives

One of the arguments levelled against increasing habitat connectivity through providing artificial corridors is that they may benefit alien and invasive species more than the species they were intended to help (Panetta 1991; Pienimaki & Leppakoski 2004). This might be a particular problem in deploying corridors to help species adapt to climate change, as one of the predicted effects of climate change is an increase in invasive species (Hulme 2003). This suggests a further benefit to the approach of increasing landscape connectivity through improving matrix quality using delivery systems such as AES. Such a strategy would reduce the increased risks of biological invasion associated with climate change, because habitats with more biodiverse matrices are less prone to invasion (With et al. 2002; Seabloom et al. 2003; Bakker & Wilson 2004). The restoration of matrix habitats could therefore act as a filter, constraining invasive species while allowing the spread of native species (Bakker & Wilson 2004). Even where invasive species are already established, habitat restoration can reduce their numbers (Price & Weltzin 2003). Such an approach would benefit agriculture as well as wildlife, as many invasive species, particularly those predicted to arrive in Europe following climate change, are serious crop pests.

practical considerations

AES currently represent the only mechanism to deliver large-scale ecological restoration to vast areas of agricultural land in Europe and North America. So far, such schemes have concentrated largely on restoring biota and protecting natural resources in agricultural habitats. We argue that a greater appreciation and better understanding of the potential effects of agricultural change on biota occupying non-farmland habitats might have profound implications for conservation planning. This would, however, require a restructuring of the way that AES are designed and targeted. Experience shows that for AES to have measurable impacts on farmland biota, they need to be very precisely designed and targeted. This makes it almost inevitable that the optimal AES for protecting farmland biota will differ in spatial or temporal deployment, or in land management options, from the optimal AES for mitigating the effects of, for example, climate change. Furthermore, the optimal AES for helping species adapt to climate change is likely to differ between landscapes, agricultural types and target taxa. This uncertainty means that it is likely that, for the near future, AES will continue to have as their main aim the enhancement of agricultural ecosystems. However, the opportunity exists to examine the effects of these schemes on adjacent habitats to indicate the suitability of AES to tackle wider environmental problems. It may be that existing AES deployment strategies can be easily adjusted to integrate, for example, predictions from climate change models or the existing spatial arrangement of non-farmed habitats, an approach already underway in the Netherlands. Further research is clearly needed to assess the magnitude and generality of these wider potential benefits of AES, and to determine patterns of agricultural matrix use by non-farmland species (Jules & Shahani 2003), before specific prescriptions can be developed. Nevertheless, it may be possible to use existing knowledge of the resources provided by AES prescriptions (Table 1) and characteristics of species likely to respond positively to matrix restoration (Table 2) to predict which non-farmland species might be most in need of matrix restoration, which resources they are likely to need in the matrix habitat and which existing AES prescriptions would provide them. Even such crude analyses might be of value in guiding AES deployment.

AES could have a significant role to play in reducing extinction rates predicted to occur from a number of pandemic threats to biodiversity, such as climate change, fragmentation, habitat destruction, biological invasion and the isolation of key biodiversity areas. This echoes Sutherland's (2004) call for an alternative approach that places the issues of farmland biodiversity within a wider range of environmental benefits. Further consideration should be given to these wider implications in the design, deployment and monitoring of AES, and the ecological improvement of agriculture more generally recognized as a potential mechanism to reduce other, non-agricultural, global threats to biodiversity.


  1. Top of page
  2. Summary
  3. Introduction
  4. Agri-environment schemes
  5. Acknowledgements
  6. References

For help and useful comments on previous drafts, we thank Sue Armstrong-Brown, Fiona Sanderson, Richard Bradbury, David Gibbons, Debbie Pain, Maiken Winter, David Kleijn, Harry Huyton, Giovanna Pisano, Tim Benton, Juliet Vickery and the editor.


  1. Top of page
  2. Summary
  3. Introduction
  4. Agri-environment schemes
  5. Acknowledgements
  6. References