Abstract
An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.
Highlights
All ecological projections of the impacts of climate change rely on models simulating climate change based on scenarios of anthropogenic forcing (Table 1)
We compare future species habitat distributions projected from the subset of climate change scenarios with those obtained from the full set of 27 climate change scenarios, as well as with those resulting from an arbitrary selection of just a few atmosphere-ocean general circulation models (AOGCMs)
Due to data availability when conducting this study, we worked with the forcing scenarios of the Special Report on Emissions Scenarios (SRES) [20] and the climate model simulations of the third phase of the Coupled Model Intercomparison Project (CMIP3), both used in AR4, rather than with the Representative Concentration Pathways (RCPs) and climate model simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5), used in AR5
Summary
All ecological projections of the impacts of climate change rely on models simulating climate change based on scenarios of anthropogenic forcing (Table 1). For its fifth assessment report (AR5), the Intergovernmental Panel on Climate Change (IPCC) has selected new climate model simulations carried out under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5), as well as new forcing scenarios, the Representative Concentration Pathways (RCPs). This has resulted in an impressive number of new climate change scenarios (Table 1) available to conduct climate change impact studies. Climate models (Table 1) are complex mathematical representations of the Earth’s climate system as they couple many physical processes such as atmosphere flux, ocean circulation, land surface and sea ice dynamics, snow cover, and permafrost [2]. All climate change scenarios provided by IPCC should be considered plausible and illustrative, and do not have probabilities attached to them [1]
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