Urgent gaps in knowledge on the impacts of climate change on UK landscapes, ecosystems and species

Pam Berry, Environmental Change Institute, University of Oxford

SUMMARY: Gaps stem from lack of data, ability to model multi-species interactions across scales and to incorporate a range of drivers of change; this affects our knowledge of climate change impacts and the ability to initiate appropriate adaptation responses.

Landscapes, ecosystems and species represent an increasing hierarchy of knowledge about climate change impacts. Leaving aside the uncertainty represented by the climate scenarios themselves (Jenkins and Lowe, 2003), modelling has done much to advance our knowledge of the potential impacts of climate change on species (Berry et al., 2003; Thuiller, 2003 and Araujo et al., 2004). This has been based on mean changes in climate variables and provides no indication of the impacts of extreme events (see contribution by Harley et al., this e-conference).

Climate envelope or niche models provide important information at the broad-scale on potential species' responses, but they do not include other drivers of change or factors such as habitat availability or biological processes that affect species’ distribution at the finer scale (Pearson and Dawson, 2003). It is currently difficult to incorporate habitat availability, or even land cover as a surrogate, into niche models (Figure1; Pearson et al., 2004), especially as there are limited future scenarios; thus it must be assumed that these will remain static. This may be a reasonable assumption on short time scales (~10 years), but not when looking beyond this. Devising future habitat scenarios provides a conundrum: can habitats be modelled independently of their component species? If the answer is “No”, then multi-species, multi-trophic models need to be devised unless species’ responses can be “summed” to determine habitat response? If the answer is “Yes”, then why bother with niche models?

The future suitable climate space simulated by niche models also represents an optimistic view for species, as not only do they omit the constraints mentioned above, but also they do not incorporate the ability of species to disperse and track these changes in climate space (Opdam and Wascher, 2004). Dispersal models exist, but are difficult to parameterise for most species due to a lack of data. The MONARCH project has tested coupling niche model outputs with future land cover changes and dispersal for selected species (Figure 2; Pearson and Dawson, 2005), but overall knowledge of the likelihood of species realising their future niches, especially in fragmented landscapes, is still limited.

Ecosystems, composed of interacting species, pose similar challenges to habitats for determining climate change impacts, as species respond individualistically (Huntley, 1991). This will lead to ecosystem composition changing, possibly non-linearly in response to extreme events, and to totally new ecosystems emerging. Identification of these new ecosystems and their future service provision represent further knowledge gaps.

Landscapes are composed of many elements, both biotic and abiotic, natural and anthropogenic, and climate is one of a suite of drivers of change (not necessarily the most important) operating both directly and indirectly. The biggest knowledge gap is at this level, given difficulties in upscaling results from the lower strata of the hierarchy and downscaling those from more global models. It could be argued that this is the most important level too, as it resonates most with humans and is the appropriate scale for spatial planning.

The strategic research challenge is to devise means of integrating drivers of change, other than climate, into models so that integrated, holistic views of the future of species, ecosystems and landscapes can be provided to inform planning and policy.

References:
Araújo, M. B., Cabeza, M., Thuiller, W., Hannah, L., Williams, P. H. (2004). Would climate change drive species out of reserves? An assessment of existing reserve-selection methods. Global Change Biology 10, 1618-1626.
Berry, P. M. Dawson, T. P., Harrison, P. A., Pearson, R. G. and Butt, N. (2003). The sensitivity and vulnerability of terrestrial habitats and species in Britain and Ireland to climate change. Journal for Nature Conservation 11, 15-23.
Jenkins, G and Lowe, R. (2003). Handling uncertainties in the UKCIP02 scenarios of climate change. Hadley Centre Technical Note 44, Hadley Centre for Climate Prediction, Southampton.
Opdam, P. and Wascher, D. (2004). Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation, Biological Conservation, 117, 285-297.
Pearson, R.G. & Dawson, T.P. 2005. Long-distance plant dispersal and habitat fragmentation: identifying conservation targets for spatial landscape planning under climate change. Biological Conservation, 123, 389-401.
Pearson, R. G., Dawson, T. P. and Lui, C. (2004). Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography, 27, 285-298.
Pearson, R. G. and Dawson, T. P. (2003). Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography, 10, 361-371.
Thuiller, W. (2003). BIOMOD – optimizing predictions of species distributions and projecting potential shifts under climate change. Global Change Biology 9, 1353-1362.

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