@article {905, title = {Bioclimatic velocity: The pace of species exposure to climate change}, journal = {Diversity and Distributions}, volume = {20}, year = {2014}, chapter = {169}, abstract = {

Aim

To investigate the velocity of species-specific exposure to climate change for mid- and late 21st century and develop metrics that quantify exposure to climate change over space and time.

Location

California Floristic Province, south-western USA.

Methods

Occurrences from presence/absence inventories of eight Californian endemic tree species (Pinus balfouriana [Grev.\&Balf.], Pinus coulteri [D.Don], Pinus muricata [D.Don.], Pinus sabiniana [D.Don], Quercus douglasii [Hook.\&Arn.], Quercus engelmannii [Greene], Quercus lobata [Nee] and Quercus wislizeni [A.DC.]) were used to develop eight species distribution models (SDMs) for each species with the BIOMOD platform, and this ensemble was used to construct current suitability maps and future projections based on two global circulation models in two time periods [mid-century: 2041\–2070 and late century (LC): 2071\–2100]. From the resulting current and future suitability maps, we calculated a bioclimatic velocity as the ratio of temporal gradient to spatial gradient. We developed and compared eight metrics of temporal exposure to climate change for mid- and LC for each species.

Results

The velocity of species exposure to climate change varies across species and time periods, even for similarly distributed species. We find weak support among the species analysed for higher velocities in exposure to climate change towards the end of the 21st century, coinciding with harsher conditions. The variation in the pace of exposure was greater among species than for climate projections considered.

Main conclusions

The pace of climate change exposure varies depending on period of analysis, species and the spatial extent of conservation decisions (potential ranges versus current distributions). Translating physical climatic space into a biotic climatic space helps informing conservation decisions in a given time frame. However, the influence of spatial and temporal resolution on modelled species distributions needs further consideration in order to better characterize the dynamics of exposure and species-specific velocities.

}, author = {Serra-Diaz, J.P and Franklin, J. and Ninyerola, M. and Davis, F.W. and Syphard, A.D. and Regan, H.D. and Ikegami, M.} } @article {869, title = {Modeling plant species distributions under future climates: how fine scale do climate projections need to be?}, journal = {Global Change Biology}, volume = {19}, year = {2012}, month = {11/2012}, pages = {10}, type = {primary research article}, chapter = {473}, abstract = {

Recent studies suggest that species distribution models (SDMs) based on fine-scale climate data may provide markedly different estimates of climate-change impacts than coarse-scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse-scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000-fold range of spatial scales (0.008\–16 km2). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate-data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine- and coarse-scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species\&$\#$39; range size. On average, SDMs projected onto 4 km climate data predicted 42\% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.

}, keywords = {biodiversity; California; climate change; downscaling; habitat; impacts; spatial resolution; terrain; topography}, doi = {DOI: 10.1111/gcb.12051}, url = {http://onlinelibrary.wiley.com/doi/10.1111/gcb.12051/abstract}, author = {Franklin, J. and Davis, F. W. and Ikegami, M. and Flint, L. E. and Flint, A. L. and Hannah, L.} }