Conservation planning with uncertain climate change projections Kujala, Heini; Moilanen, Atte; Bastos Araujo, Miguel; Cabeza, Mar Published in: P L o S One DOI: 10.1371/journal.pone.0053315 Publication date: 2013 Document version Publisher's PDF, also known as Version of record Citation for published version (APA): Kujala, H., Moilanen, A., Bastos Araujo, M., & Cabeza, M. (2013). Conservation planning with uncertain climate change projections. P L o S One, 8(2), [e53315]. https://doi.org/10.1371/journal.pone.0053315 Download date: 26. Sep. 2021 Conservation Planning with Uncertain Climate Change Projections Heini Kujala1., Atte Moilanen1, Miguel B. Arau´ jo2,3,4, Mar Cabeza1*. 1 Metapopulation Research Group, Department of Biosciences, University of Helsinki, Helsinki, Finland, 2 Department of Biodiversity and Evolutionary Biology, National Museum of Natural Sciences, Consejo Superior de Investigaciones Cientı´ficas, Madrid, Spain, 3 ‘Rui Nabeiro’ Biodiversity Chair, Centro de Investigac¸a˜o em Biodiversidade e Recursos Gene´ticos, University of E´vora, E´vora, Portugal, 4 Center for Macroecology, Evolution and Climate, Department of Biology, University of Copenhagen, Copenhagen, Denmark 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. Citation: Kujala H, Moilanen A, Arau´jo MB, Cabeza M (2013) Conservation Planning with Uncertain Climate Change Projections. PLoS ONE 8(2): e53315. doi:10.1371/journal.pone.0053315 Editor: Nicolas Mouquet, CNRS, University of Montpellier II, France Received March 15, 2012; Accepted November 30, 2012; Published February 6, 2013 Copyright: ß 2013 Kujala et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: For financial support HK and AM thank the Academy of Finland Centre of Excellence Programme 2006–2011, grants 213457 and 129636 (URL: http:// www.aka.fi/en-GB/A/Centres-of-Excellence-/). HK was also funded by a Luonnonvaraisten elio¨iden kesta¨va¨nka¨yto¨n ja suojelun tutkijakoulu Graduate School fellowship (URL: http://www.helsinki.fi/luova) and by Finnish Cultural Foundation, grant SKR-00070832 (URL: http://www.skr.fi). AM acknowledges the support by the ERC-StG (European Research Council Starting Grant, URL: http://erc.europa.eu/starting-grants) project Global Environmental Decision Analysis (GEDA), grant 260393. MC and MBA were funded by the European Commission Seventh Framework Program project European RESPONSES to climate change (grant agreement number 244092, URL: http://www.responsesproject.eu/). MBA also acknowledges the Spanish Research Council (URL: http://www.csic.es/web/guest/home), the ‘Rui Nabeiro’ Biodiversity Chair (URL: http://www.catedra.uevora.pt/rui-nabeiro/), and the Danish National Research Foundation (URL: http://www.dg.dk/en/) for support of his research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: [email protected] . These authors contributed equally to this work. Introduction with respect to new threats [14,15]. But the need for a paradigm shift is being emphasized [5,16–19]. Proactive responses to Observed increases in global average temperatures, rise in the conservation challenges require the existence of reliable forecasts global average sea level and changing patterns and frequencies of and a combination of present and future conservation goals, while extreme weather events, strongly suggest that the climate is limited conservation resources entail that these goals are to be met changing according to model predictions [1]. Ecosystems are efficiently. The discipline of systematic conservation planning has already responding to such changes, with species range shifts, thus seen the development of methods for solving such non-trivial phenological changes, and changes in species’ abundances and conservation resource allocation problems, factoring in predicted community composition [1,2]. Climate change is thus recognized species range shifts by modelling expected responses of species to as a major threat to biodiversity and a big challenge to climate change [5,19–21]. Yet, an issue of concern is the conservation [3–5]. uncertainty associated with both climate change and the Protected areas are critical instruments for safeguarding consequent species responses [22]. This is particularly trouble- biodiversity. However, due to their increasing isolation in a matrix some, because decision makers might be reluctant to base their of highly modified landscapes, and the fact that they are conservation decisions on highly uncertain forecasts of future geographically fixed, present-day protected areas are unlikely to impacts that require trading-off scarce resources needed for be sufficient to accommodate and buffer climate-induced changes mitigation of present day threats [19,23]. in biota [5–7]. Changes of species composition in protected areas An inherent source of uncertainty is the fact that we can only are already being observed (e.g. [8]), and forecasts for the near make projections about the future that are conditional to our future estimate that even bigger changes could take place [9–13]. knowledge and simplified model assumptions. To understand the In the past, conservation planning has primarily focused on potential impacts of future climate change scientists have been preserving existing biodiversity pattern and has acted reactively forced to analyse responses against distinct but equally likely PLOS ONE | www.plosone.org 1 February 2013 | Volume 8 | Issue 2 | e53315 Conservation Planning with Climate Uncertainty Figure 1. A flow chart showing how species distribution maps for baseline and future are created across the different modelling techniques m, discounting the mean values (denoted by an asterix) with inter-model variability (standard deviation, see text). Connectivity maps CBj and CFj are created based on the discounted baseline and future layers, resulting in four different input maps per species j and per scenario s. Prioritization is done separately for each scenario, producing multiple results per scenario where weights given to future distributions and connectivities are varied. Trade-off curves (Fig. 5) and comparisons between scenarios (Fig. 3) are done by focusing on the top 10% priorities of each Zonation result. doi:10.1371/journal.pone.0053315.g001 scenarios of future development. Scenarios are plausible combi- be present. Ecological niche models include many assumptions nations of circumstances used to describe a future set of conditions, and limitations: They are not concerned with dispersal processes, such as the widely used SRES scenarios [24,25] that consider a the dynamics of population at the leading or retracting edge, or the wide range of possibilities for changes in population, economic potential for adaptation or species’ interactions [28] (but see e.g. growth, technological development, improvements in energy [29] and [30]). A large number of modelling approaches is efficiency, and the like. Scenario assessments are important for available, and differences in their algorithms, parameterizations policymaking, outlining a potential range of outcomes and thus and the assumptions they make regarding the data often result in influencing decisions. But despite the pressing interest in scenario variation in outputs [31,32]. Recent studies show that the probability [26,27], scenarios typically lack an associated likeli- variability in the predictions can be as high (or even higher) hood, making it difficult to assess the relative risks of particular between different niche-based models than between different adaptation policies. emission scenarios [33–36]. To cope with such inter-model Perhaps the most widely discussed aspect within the climate variation, [37] advocate the use of multiple models within an change conservation context is the uncertainty that arises from ensemble forecasting framework. This approach allows identifica- different modelling approaches when forecasting species distribu- tion of consensus among all forecasts, or consensus among subsets