Biodiversity conservation planning adapted to climate change

Current conservation planning defines targets for conservation sites that are based on historic references of vegetation types and local species occurrence or density (Margules et al. 1994). The long term effectiveness of such a static, site-oriented strategy is currently challenged by new scientific insight on ecosystem functioning (Gaston et al. 2006) and the unpredictability of the effects of increased perturbations caused by climate change (Mitchell and Hulme 1999). Therefore, a paradigm shift in biodiversity conservation planning is needed. Three main challenges are identified. Firstly, the exclusion of disturbances in current conservation practice ignores the nonequilibrium nature of ecosystems (Holling 1973). Disturbances are increasingly considered on the one hand the base of co-existence of species and therefore of biodiversity. On the other hand disturbances allow ecosystems to adapt to changed environmental conditions and are considered a source of renewal. Preventing disturbances to occur and restoring ecosystems to its original form, if an inadvertent disturbance did occur, results in a loss of biodiversity and adaptive capacity. Disturbances should not be perceived as undesirable, but be incorporated as an integral part of biodiversity conservation planning. Secondly, species differ in their sensitivity and response to different sources of disturbance. This is illustrated by the various responses to changing weather conditions due to climate change. The differences in the responses of species result in changing species composition of communities. Hence, the very base of current conservation policy that community types have high predictive capacity for the occurrence of target species, erodes away as climate change progresses. Instead of a focus on individual species as conservation targets for protected areas, the presence of functional diversity enabling differential responses to disturbances and enabling the continuation of ecosystem functioning should be the focus of biodiversity conservation planning. Thirdly, most existing reserves are too small to incorporate long term and large scale dynamics (Bengtsson et al. 2003). Population studies in fragmented ecosystem patterns on the landscape scale have shown dynamic patterns typical for metapopulations (Hanski & Gilpin 1991; Verboom et al. 2001; Vos et al. 2001), implying that the local occurrence of species is often unpredictable and largely dependent on characteristics of ecosystem networks at the regional scale level (Opdam & Wiens 2002; Opdam et al. 2003). Also the consequences of climate change on species ranges cannot be controlled or counteracted by local management actions. Thus the scale of the individual reserve is too small to sustain nature quality targets. Instead of local sites as the object of planning, a landscape and regional approach in biodiversity conservation planning is needed. Science has to play a key role in the paradigm shift. Science needs to provide evidence to societal partners about the effectiveness of dealing with ecosystems in a more adaptive way. Convincing cases, based on thorough science, of land use planning where biodiversity and ecosystems are considered in a more functional way are pivotal. Huge efforts are demanded before science can provide operational methods for goal setting, design and evaluation for regional planning. For example, a framework for the diagnosis of effect and response diversity should be developed. Ecosystems and ecosystem networks should be analysed for their key structures and processes and feedback mechanisms, based on such an analysis key functional groups are identified. Next the potential variation of functional groups needs to be explored and interpreted to generate a system of reference values for determining an operational framework for goal setting. We need to develop insight in the quantitative relation between the variation of functional groups, the adaptive capacity of ecosystems and ecosystem networks and the spatial characteristics. The challenge to science is not only to make this information quantitatively applicable in a spatial context, but science should also be more effective in transferring this knowledge into societal decision-making than it has been up to now. Implementing the paradigm shift is a societal learning process. Science should be part of that, and learn from practical applications just as well as practice is learning from science. A key issue in this learning process is how to deal with uncertainty. We will not be able to predict exact levels of adaptive capacity, because the nature, frequency and severity of disturbances that ecosystems will be faced with are unpredictable. Ecosystems are moving targets, with multiple potential futures that are uncertain and unpredictable (Holling and Meffe 1996). What we intend to realize with this approach is that we learn, in the end, to manage ecosystems and landscapes in such a way that they are adapted to the unpredictability and uncertainty that we face.