Predicting Biodiversity Change: Outside the Climate Envelope, Beyond the Species–area Curve

Abstract

Efforts to anticipate threats to biodiversity take the form of species richness predictions (SRPs) based on simple correlations with current climate and habitat area. We review the major approaches that have been used for SRP, species-area curves and climate envelopes, and suggest that alternative research efforts may provide more understanding and guidance for management. Extinction prediction suffers from a number of limitations related to data and the novelty of future environments. We suggest additional attention to (1) identification of variables related to biodiversity that are diagnostic and potentially more predictable than extinction, (2) constraints on species dispersal and reproduction that will determine population persistence and range shifts, including limited sources or potential immigrants for many regions, and (3) changes in biotic interactions and phenology. We suggest combinations of observational and experimental approaches within a framework available for ingesting heterogeneous data sources. Together, these recommendations amount to a shift in emphasis from prediction of extinction numbers to identification of vulnerabilities and leading indicators of change, as well as suggestions for surveillance tools needed to evaluate important variables and the experiments likely to provide most insight.

Thermophilization of adult and juvenile tree communities in the northern tropical Andes

“…For adults, TMRs were slowest in plots with soils having low P concentrations (R = −0.59; P < 0.05). Because P is one of the most important factors limiting tree growth in tropical forests (20,33), many species may be prevented from migrating into areas with low-P soils, even when climatic conditions are conducive to establishment and growth (18). This, in turn, could allow species in these areas to persist longer, even as the climate becomes unsuitable, as there will be less competitive pressure from incoming "better-suited" species.…”

“…Although most tree species in wet tropical forests are animal-dispersed (14,15), differences in the relative abundances of species with different dispersal modes could greatly affect the responses of forest communities to climate change. Furthermore, other nonclimatic factors, such as soil and other edaphic factors, can pose significant barriers to species migrations by limiting the movement of species between different habitat types (16)(17)(18). For example, the specialization of species on specific soil types or conditions (19,20) can potentially halt migrations by preventing species from moving into areas with suitable temperatures but unsuitable edaphic conditions (18,21).…”

“…Furthermore, other nonclimatic factors, such as soil and other edaphic factors, can pose significant barriers to species migrations by limiting the movement of species between different habitat types (16)(17)(18). For example, the specialization of species on specific soil types or conditions (19,20) can potentially halt migrations by preventing species from moving into areas with suitable temperatures but unsuitable edaphic conditions (18,21). Likewise, forest disturbances (anthropogenic or natural) will affect the ability of species to respond to climate change (22,23).…”

Modeling Impacts of Climate Change on Giant Panda Habitat

“…Ibáñez et al [79] point out that this approach effectively treats the realized niche as though it were the fundamental niche. Changes in climate may also affect how a species can disperse, influence reproductive capacity, and disrupt ecosystem functioning as key species move in or out of an area at varying rates [80], while the landscape mosaic and human activities may impede or facilitate migration to different degrees for different species [81].…”

Orchids distribution and bioclimatic niches as a strategy to climate change in areas of tropical dry forest in Colombia

“…Factors such as the persistence of certain species under climate change, migration speed, ecotones, immigration potential, and spatiotemporal plant-pollinator relations are excluded from predictive studies (Ibáñez 2006). Given that the current model generation does not consider factors that may increase biological realism and therefore approximation in future predictions (Urban 2015), a posteriori evaluations were proposed for the models obtained to identify where refuge areas for these plants would be in the Colombian TDF.…”