Maintaining and restoring connectivity are key adaptation strategies for biodiversity conservation under climate change. We present a novel combination of species distribution and connectivity modeling using current and future climate regimes to prioritize connections among populations of 26 rare species in New York’s Hudson Valley. We modeled patches for each species for each time period and modeled potential connections among habitat patches by finding the least-cost path for every patch-to-patch connection. Finally, we aggregated these patches and paths to the tax parcel, commonly the primary unit of conservation action. Under future climate regimes, suitable habitat was predicted to contract or appear upslope and farther north. On average, predicted patches were nine times smaller and paths were twice as long under future climate. Parcels within the Hudson Highlands, Shawangunk Ridge, Catskill Mountains, and Harlem Valley had high species overlap, with areas upslope and northward increasing in importance over time. We envision that land managers and conservation planners can use these results to help prioritize parcel-level conservation and management and thus support biodiversity adaptation to climate change.
Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species’ risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species’ risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species’ sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species’ extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species’ extinction risk.
Few conservation projects consider climate impacts or have a process for developing adaptation strategies. To advance climate adaptation for biodiversity conservation, we tested a step-by-step approach to developing adaptation strategies with 20 projects from diverse geographies. Project teams assessed likely climate impacts using historical climate data, future climate predictions, expert input, and scientific literature. They then developed adaptation strategies that considered ecosystems and species of concern, project goals, climate impacts, and indicators of progress. Project teams identified 176 likely climate impacts and developed adaptation strategies to address 42 of these impacts. The most common impacts were to habitat quantity or quality, and to hydrologic regimes. Nearly half of expected impacts were temperature-mediated. Twelve projects indicated that the project focus, either focal ecosystems and species or project boundaries, need to change as a result of considering climate impacts. More than half of the adaptation strategies were resistance strategies aimed at preserving the status quo. The rest aimed to make ecosystems and species more resilient in the face of expected changes. All projects altered strategies in some way, either by adding new actions, or by adjusting existing actions. Habitat restoration and enactment of policies and regulations were the most frequently prescribed, though every adaptation strategy required a unique combination of actions. While the effectiveness of these adaptation strategies remains to be evaluated, the application of consistent guidance has yielded important early lessons about how, when, and how often conservation projects may need to be modified to adapt to climate change.
Climate change presents a potentially severe threat to biodiversity. Species will be required to disperse rapidly through fragmented landscapes in order to keep pace with the changing climate. An important challenge for conservation is therefore to manage landscapes so as to assist species in tracking the environmental conditions to which they are adapted. Here we develop a stochastic spatially explicit model to simulate plant dispersal across artificial fragmented landscapes. Based on certain assumptions as to the dispersal mechanism, we assess the impact that varying potential for rare long-distance dispersal (LDD) has on the ability to move over landscapes with differing spatial arrangements of suitable habitat (clumped versus fragmented). Simulations demonstrate how the relative importance of landscape structure in determining migration ability may decrease as the potential for LDD increases. Thus, if LDD is the principal mechanism by which rapid large-scale migrations are achieved, strategically planned networks of protected habitat may have a limited impact on rates of large-scale plant migrations. We relate our results to conventional principles for conservation planning and the geometric design of reserves, and demonstrate how reversal of these principles may maximise the potential for conservation under future climates. In particular, we caution against the justification of large-scale corridors on grounds of climate change since migration along corridors by standard dispersal mechanisms is unlikely to keep pace with projected change for many species. An improved understanding of the dispersal mechanisms by which species achieve rapid migrations, and the way that these processes are affected by patterns of landscape fragmentation, will be important to inform future conservation strategies.
There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate1. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change2, 3, 4, 5 based on the expectation that established assessments such as the IUCN Red List6 need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened7, 8, 9, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.