Conservation planning when climate change projections are uncertain

Uncertainty may be inherent in predicting species responses to climate change, but that doesn’t mean those predictions have to be full of guesswork.  While many efforts to date have attempted to quantify species responses – using niche-models, various emissions scenarios, and/or incorporating dispersal probabilities, for example – there is still a large unknown involved in making maps of the future.  Kujala et al. tackle this problem of uncertainty by proposing the use of a new, proactive framework  that accounts for several types of uncertainty when creating conservation priorities.  The heart of their framework, which in this paper is illustrated by identifying conservation priorities for amphibians and reptiles in Europe, emphasizes the following:

1. Although dispersal is a major source of uncertainty, accounting for dispersal rates using any relevant published estimates, rather than a broad approach of assuming all or no dispersal, can be critical in having a more realistic process for identifying connected sites.

2. The large variation in predictions can be accounted for by giving higher priority to areas with high model agreement rather than using overall ensemble metrics such as mean across models. One of the major sources of uncertainty when assessing future climate change impacts is that different modelling techniques may give very different predictions on how species distributions are likely to change. Discounting locations with high uncertainty (high variation) in the expected future likelihood of species presence helps to make more robust conservation decisions

3. When evaluating trade-offs between conserving present versus future priority areas, it’s necessary to identify priorities beyond baseline distributions only.  Costs and benefits of dividing conservation resources between present and future can be explored through a sensitivity analysis: in the prioritization process increasing weights are given to future sites and resulting reserve configuration is compared to a solution where only present priorities are accounted for.  In this way future benefits can be maximized while simultaneously minimizing the amount of compromise necessary for present conservation.

4. There is a balance between risk aversion and risk taking when choosing between different scenarios, and this can take into account different factors such as the greatest amount of overlap between all scenarios, the lowest potential for negative outcomes, and the likelihood of positive surprises.  The best way to support decision making for climate change is to provide a transparent way of mapping trade-offs between different scenarios and weighting schemes. Decisions are always driven by values, perceptions, local goals and policies, and only very rarely would they be based on the most optimal approach (especially in conservation). Mapping trade-offs between different options  can a) help decision-makers and managers to pick the option that best suits their goals, values and willingness to take risks, but also b) quantify the cost of not choosing the most optimal plan.