Project objectives

1. To define the potential distribution of selected species of conservation concern in the New Forest by carrying out habitat suitability/species distribution modelling. 2. To compare the use of different approaches for modelling potential habitat suitability (species distribution modelling) for the selected species in the New Forest. 3. To examine the potential impacts of climate change on the selected species and their habitats in the New Forest.

1.3.2. Context

The New Forest is a unique and extremely valuable landscape (see Appendix 1 for further details), which contains many species and habitats that are rare and/or threatened as a result of drivers of biodiversity loss such as habitat change, climate change, invasive alien species (and disease), and pollution, and needs to be conserved appropriately and effectively for the future.

The habitats of the New Forest include ancient pasture woodland, lowland heath, grassland, valley and seepage step mire, or fen. The unenclosed (pasture) woodlands extend to some 4,430 hectares (excluding riverine and bog woodland) and are dominated by oak (Quercus robur) and beech (Fagus sylvatica), with some trees of early 17th century origin (English Nature, 1996; Wright and Westerhoff, 2001).

The New Forest contains approximately 19,500 hectares of lowland heath, the largest area of this rare habitat remaining in the UK (New Forest National Park Authority, 2006b). The heathlands comprise a series of plant communities, including the dry heath (and associated dry grasslands), which grades into the wetter humid heath (and associated valley mires, streams, ponds, temporary pools and wet grasslands) (English Nature, 1996; Tubbs, 2001; Wright and Westerhoff, 2001).

Within the heathland mosaic, on pockets of richer soils, acid grassland can occur. The more neutral grasslands (or lawns) vary with factors such as soils, topography

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floodwater nutrient quality and grazing pressure and the species present reflect this (English Nature, 1996). The New Forest also contains ninety separate valley mires; there are no more than twenty in the rest of the English lowlands, and only a handful around the European littoral from Denmark to Spain (Tubbs, 2001). This international importance is reflected in the New Forests‘ designation as a Ramsar site (a wetland of international importance).

Monitoring of biodiversity in the New Forest is required as a result of its designation as a Special Area of Conservation (SAC) Natura 2000 site, meaning it receives strict protection under the EU Habitats Directive. In order to conserve species for the future, and monitor changes in their distributions and status, it is important to know where they currently occur and the occurrence of potentially suitable habitat.

In the New Forest, as in many other areas, and for many taxonomic groups, the need for distributional information far outstrips the resources available for collection of field data. Collecting distributional data over extensive areas is resource and time intensive (Cowley et al., 2000). Even for well-studied groups, such as butterflies, records are biased towards accessible areas (Dennis et al., 1999; Cowley et al., 2000). Despite being easily accessible and having many conservation designations, there are still many gaps in knowledge about many of the species found in the New Forest and their patterns of distribution. Chatters (2006) discusses how ‗the scale and diversity of habitats of the New Forest National Park are still not fully understood and further survey and analysis are needed to gain an adequate understanding of what the National Park contains and whether current designations are adequate. However, such habitat information is far advanced compared with the data on many individual species ... the data sets and analysis of the importance of many of these important species across the National Park are still far from adequate‘. Much of the species data are patchy and often recorded on an ad hoc basis, with biases towards easily observed species in accessible locations, in large part due to lack of time and resources.

Species distribution (or habitat suitability) modelling can be used to identify unsurveyed sites of high potential occurrence for species, so that time and resources can be directed more efficiently towards these areas. Developments in geographical

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information systems (GIS) have resulted in the potential for great increases in both the quality and quantity of habitat-level information that can be obtained and analysed (Cowley et al., 2000). This, combined with development of a range of modelling techniques (Guisan and Zimmermann, 2000), suggests that species distribution modelling offers a valuable approach for improving current knowledge of the distribution of species.

Although there are some issues and limitations in their use, species distribution models have been shown to work well in a wide range of applications (e.g. Cowley et al., 2000; Ferrier et al., 2002b; Berry et al., 2005a; Guisan and Thuiller, 2005; Elith et al., 2006; Guisan et al., 2006a; Chefaoui and Lobo, 2007; Matern et al., 2007; Sattler et al., 2007; Wollan et al., 2008). However, species distribution modelling methods have generally been applied to large spatial scales (in both extent and resolution), such as countries (Zaniewski et al., 2002; Guisan and Hofer, 2003; Sérgio et al., 2007; Thomaes et al., 2008; Lachat and Butler, 2009; Puddu et al., 2009) or large regions (Brotons et al., 2004; Santos et al., 2006; Chefaoui and Lobo, 2007; López-López et al., 2007). There have been far fewer examples of smaller scale applications built to address local conservation issues (Seoane et al., 2006), in particular at the scale of an individual protected area or landscape (but see for example Gibson et al., 2004; Seoane et al., 2006; Fei et al., 2007; Podchong et al., 2009). Although larger scale models can be used to predict coarse distributions, it is at local scales where conservation management decisions are typically taken.

In order to test the application of species distribution modelling methods to an individual protected area, this study focuses on species of high conservation value in the New Forest (as listed in the SAC management plan (Wright and Westerhoff, 2001)). This also provides the opportunity to test the application of predictive models to rare and endangered species, of which there have been relatively few studies (Engler et al., 2004; Guisan et al., 2006a; Matern et al., 2007). If models can be shown to work well for the selected species, it is anticipated that it may then be possible to apply them to other species whose distributions are less well understood. Ultimately, it is hoped that the results of these models will be useful to those trying to survey and monitor species and effectively manage the biodiversity of the New Forest. At the same time, it is hoped that the research will provide some findings of

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general relevance to the implementation of species distribution modelling approaches at the scale of individual protected areas.

In attempting to predict species‘ potential distributions (or habitat suitability) to aid conservation management, it would be naїve not to consider the impact of (future) environmental change, namely climate change, on those distributions. Climate change and the other pressures facing the New Forest are highlighted in New Forest management plans (e.g. New Forest Committee, 2003; Forestry Commission, 2007; New Forest National Park Authority, 2008), although there has been very little specific research into the impacts of climate change in the New Forest (except for an investigation into temporary pond macroinvertebrate communities (Ewald, 2008) and some general analyses undertaken for the whole of Hampshire e.g. (Berry et al., 2005a; Hossell and Rowe, 2006) and the UK (Hossell et al., 2000; Berry et al., 2007b)). Therefore, a review of the impact of climate change on the selected species and their habitats was also undertaken during this research to suggest potential impacts, using the Bayesian belief network models.