Abstract
Climate change is affecting biodiversity worldwide, but conservation responses are constrained by considerable uncertainty regarding the magnitude, rate and ecological consequences of expected climate change. Here we propose a framework to account for several sources of uncertainty in conservation prioritization. Within this framework we account for uncertainties arising from (i) species distributions that shift following climate change, (ii) basic connectivity requirements of species, (iii) alternative climate change scenarios and their impacts, (iv) in the modelling of species distributions, and (v) different levels of confidence about present and future. When future impacts of climate change are uncertain, robustness of decision-making can be improved by quantifying the risks and trade-offs associated with climate scenarios. Sensible prioritization that accounts simultaneously for the present and potential future distributions of species is achievable without overly jeopardising present-day conservation values. Doing so requires systematic treatment of uncertainties and testing of the sensitivity of results to assumptions about climate. We illustrate the proposed framework by identifying priority areas for amphibians and reptiles in Europe.
Highlights
Observed increases in global average temperatures, rise in the global average sea level and changing patterns and frequencies of extreme weather events, strongly suggest that the climate is changing according to model predictions [1]
Uncertainty due to the choice of niche model varied substantially across species (Fig. S1), between-model variation in the predicted probability of occurrences being notably larger for projected future distributions than for the baseline period
Optimizing conservation for different SRES scenarios resulted in small but significant differences, both in the conservation level achieved for species baseline distributions (Paired T-test; p,0.001 in all comparisons); as for future distributions (Paired T-test, p,0.001 in all comparisons except between B1 and B2, p = 0.054, and between B1 and A2 p = 0.082)
Summary
Observed increases in global average temperatures, rise in the global average sea level and changing patterns and frequencies of extreme weather events, strongly suggest that the climate is changing according to model predictions [1]. The discipline of systematic conservation planning has seen the development of methods for solving such non-trivial conservation resource allocation problems, factoring in predicted species range shifts by modelling expected responses of species to climate change [5,19,20,21]. An issue of concern is the uncertainty associated with both climate change and the consequent species responses [22]. This is troublesome, because decision makers might be reluctant to base their conservation decisions on highly uncertain forecasts of future impacts that require trading-off scarce resources needed for mitigation of present day threats [19,23]
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