Delivering the (Public) Goods: Brexit, Biodiversity, and Evidence-based Conservation
Tags: Brexit, Agriculture, UK, Conservation, Policy

Beyond the fact that the Basic Payment Scheme (BPS) will be phased out and farmers will be rewarded for delivering public goods, the details on how the UK’s future agricultural policy will actually operate are thin on the ground. This uncertainty is, understandably, causing concern in both the farming and conservation communities. With over 70% of the UK’s land area being devoted to agriculture, it is impossible to divorce farming from biodiversity conservation. However you voted, Brexit provides an opportunity to update our land-management policies and adapt them to better mitigate climate change and ecological collapse. Agri-environment schemes (AES) under the EU’s Common Agricultural Policy have been the main mechanism for providing financial support to farmers in exchange for farming in ways that supports wildlife and ecosystem services. Going forward, agri-environment schemes won’t be renewed once they expire, leaving the way open for a reevaluation of how future schemes are designed and implemented. Below I’ve outlined some of the key factors that shape the effectiveness of AES at achieving their goals.

First we should consider impact evaluation; how do we know whether a scheme is doing its job? This is a common issue in AES design. The lack of evidence for success of agri-environment schemes can be attributed to a variety of factors. In the first place, it must be acknowledged that agri-environment schemes are rarely designed to provide maximal ecological benefits at the expense of other stakeholders, but are usually designed to reconcile “a range of ecological, socio‐economic, administrative and political interests” (Buller et al. 2000 cited in Kleijn et al 2006, emphasis added). This is a practical feature of scheme design, since schemes which privilege biodiversity conservation over all other concerns are unlikely to receive much support from other stakeholders, such as farmers or politicians, and so are less likely to ever be approved.

In other cases, measuring the impact of a scheme is simply never built into the project’s design, or if it is, data are too scarce or of too poor quality to allow a thorough evaluation (Kleijn and Sutherland 2003). Many schemes never record baseline data before a scheme is put into place, meaning that there’s little way to gauge its impact (Kleijn et al. 2006).

When it is measured, the effectiveness of agri- environment schemes at achieving their goals is inconsistent across the board. Perhaps this is unsurprising given that AESs take many forms, are implemented in different ways, and have many differing goals (Ahnström et al. 2009; Carey et al. 2005). Kleijn and Sutherland’s (2003) meta-analysis helpfully concluded that while some agri-environment schemes demonstrate positive impacts, others revealed ‘no effects, negative effects, or positive effects on some species and negative effects on others’. The analysis also uncovered a positive bias towards intensively farmed areas such as non-organic arable farms, which are more frequently measured for impacts, and which tend to have lower levels of biodiversity at the start of schemes anyway (Kleijn and Sutherland 2003).

“For schemes that have no demonstrable positive effects it remains unclear whether this is because of the agri‐environmental measures being ineffective, the implementation of measures by farmers being suboptimal, the schemes being implemented in the wrong locations or a combination of these causes.” (Kleijn et al. 2006)

You don’t need to be a farmer to recognize the huge variation in farmland in the UK. Weather, geology, soil type, floral composition and human management can mean a scheme demonstrates different results even with a single farm. This makes it difficult to generalize or conduct the kinds of empirical analyses favoured by academics and policy-makers (Kleijn et al. 2006). In the same vein, something which serves as an accurate predictor in one location or scenario may not do so in another, displaying the need for contextually appropriate and evidence-based AESs rather than a generalized roll-out of schemes on a national scale (Whittingham 2006). Even more unhelpfully, this effect also be applied to different time scales, as a scheme might be found to have positive results one year, but not in the next. (Chamberlain et al. 1999).

Whittingham (2006) suggests that evaluating the success of AESs is hampered by several factors. First, the rate and density of target species varies between locations; second, habitat preference may vary between species across different regions; third, the likelihood of a species using a location in a scheme is determined at least partly by their distance from breeding individuals; and fourth, species often need multiple resources in order to breed, which means larger home ranges and with a variety of food and habitat options within them.

From a biodiversity perspective, the short length of most AESs in the UK (many require a minimum of five years) is shorter than required to restore certain species and ecosystem functions (Olff and Bakker 1991; Walker et al. 2004 cited in Kleijn et al. 2006) Similarly, a 2001 study suggested that due to the length of time that it takes for results to manifest in nature, we may simply be too early to adequately gauge the impacts of some schemes (cited in Batary et al. 2015). Potter (1998, 91, cited in Dobbs and Pretty 2008) suggested that AESs may be successful at preventing further decline in biodiversity on farms but may not serve to actually increase it.

Similarly, several studies have suggested that AESs may serve to increase the number of common farmland species, such as rooks and woodpigeons, rather than conserving or increasing vulnerable or high value species (Batary et al. 2015, 1010; Kliejn et al. 2006). This may partially be accounted for by the fact that schemes are more likely to result in increased populations of target species if they are adapted to the specific needs of these species, a system Peach et al. found in 2001 to account for a low proportion of AESs (cited in Kliejn et al. 2006).

Image: author’s own

Targeting AESs to areas of already high biodiversity value is important to maintaining their value (Whittingham 2011), so it is important to check that funding is not wasted in areas less suitable to the species that are targeted (Whittingham 2006). Such targeting measures are termed ‘zonal’ schemes in comparison to broader ‘horizontal’ schemes which fit more easily into general farm management and aim to lessen the harmful impacts of some of the more industrial farming practices (Kleijn & Sutherland 2003). It can also be useful to distinguish between schemes that apply to non-productive areas, such as field margins or hedgerows, which Garibaldi et al. termed ‘off-field practices’ (cited in Batary et al. 2015) and those that are introduced in productive or ‘on-field’ areas (Batary et al. 2015).

Feehan et al. (2005) suggest horizontal schemes may be better suited for ecosystem services and ecological processes, whilst specific biodiversity needs are better served by zonal schemes.

It must be acknowledged that not all AES areas provide equal conservation value. For example, distance between protected patches, patch size, and patch quality are all indicators of their value towards biodiversity conservation; AES locations serve little value if they are too small to provide enough resources to a species, too widely spaced to allow travel between them, or of too poor quality. They also often differ from more conventional protected areas in that they often apply to small areas of land such as hedgerows, ditches, field margins, or steep inaccessible land (Whittingham 2006). Protecting these scattered areas may be less valuable for wildlife than larger areas, which may provide more resources and shelter (Whittingham 2006). A move towards landscape-scale schemes rather than field corners and boundaries may be a more effective use of resources, although these small patches may serve as “stepping stones” helping species move between areas.

The long-term viability of many species is dependent on protecting multiple habitat at different scales (Gabriel et al. 2010). For example, an AESs may be achieving its goals at local levels but this may not be sufficient to maintain viable populations of a species across a larger region (Whittingham 2011), particularly when species require different resources over their life cycles (Gabriel et al. 2010). Conversely, landscape-scale AESs may serve as a source population from which individuals may ‘spill’ out (Gabriel et al. 2010) but success in the long-term depends on these individuals having the necessary resources and habitat to thrive once they do. While the evaluation of AESs may take place on individual field or farm scales, this is rarely the scale at which broader trends in species population are observed. (Gabriel et al. 2010).

It is now acknowledged that the landscapes surrounding and between AES areas is also a factor in determining their success, in part because intensively farmed or highly-populated areas may inhibit the spread of species into new areas (Hodge 1999, 102; Whittingham 2011; Harrison and Burgess 2000, 1120). For example, despite the fact that meadow birds are more numerous in protected areas than in farmland that is under agri environment schemes, the size of these protected areas (PAs) may be too small to sustain populations in the long-term, calling for greater investment in creating secondary habitats in farmland that can be successfully colonised (Batary et al. 2015, 1013).

The UK’s new Agriculture Bill has so far been characterised by broad statements and generalisations. Hopefully it will result in evidence-based policies that demonstrate that we have learned from past experience. However, farmers don’t operate in a vacuum; while we need to follow the science when designing a new farm agri-environment system we need to be aware that the success of a scheme isn’t determined by an academic understanding of species ecology, but by a human understanding of the economic and cultural factors that determine how they’re implemented on the ground. My next article will therefore outline the human factors that shape the uptake and success of recent agri-environment schemes.