Climate Change

Includes data used to estimate population demographic parameters for an exemplary high-elevation amphibian species, the federally endangered Shenandoah salamander (Plethodon shenandoah). These parameters were entered into a Markov projection model which we used to forecast the future population status of the Shenandoah salamander.

Climate can have a strong influence on species distributions, and amphibians with different life histories might be affected by annual variability in precipitation in different ways. The Sierra Nevada of California, United States, experienced some of the driest and wettest years on record in the early 21st Century, with variability in annual precipitation predicted to increase with climate change. We  examined the relationship between adult occupancy dynamics of three high elevation anurans and site and annual variation in measures of winter severity, summer wetness, and cumulative drought. We further evaluated how these weather conditions affected the probability that each species would reproduce, conditional on their occurrence at a site. We found that although different aspects of weather affected the occupancy dynamics of each species differently, adult occupancy probabilities were generally stable throughout our 15-year study period. The probability of reproduction, although slightly more variable than adult occupancy, was similarly stable throughout the study. Although occurrence of the three species was resilient to recent extremes in precipitation, more detailed demographic study would inform the extent to which amphibian populations will remain resilient to increasing severity, duration, and frequency of drought and flood cycles.

Climate data allow people to examine species distributions and possible distributions. This script takes ERA5-Land climate estimates (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) for precipitation and lake temperature and processes them to create summary climate layers for use with biological organisms in lakes. This code could be modified to use a different subset of years.

These BioLake raster data provide global estimates (~10.0 x 12.4 km resolution) of twelve bioclimatic variables based on estimated lake temperature. Eleven of these twelve variables (BioLake01 - BioLake11) are estimated for each of three lake strata: lake mix (surface) layer, lake bottom, and total lake water column. These eleven variables correspond to CHELSA (Climatologies at high resolution for the earth's land surface areas) bioclimatic variables BIO1 - BIO11, except that these BioLake variables are based on lake water temperature and CHELSA BIO1 - BIO11 variables are based on air temperature. CHELSA BIO is also calculated a finer spatial resolution (~1 x 1 km). The twelfth variable (BioLake20; months with non-zero ice cover) does not correspond to any CHELSA bioclimatic variable. The data are supplied as a multi-layer raster (.grd) file in the World Mollweide projection, accompanied by a header file (.gri) with layer names.

For BioLake layer download, see https://doi.org/10.5066/P96QLN5Y