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Sarah C. Elmendorf

Publications and source records attributed to Sarah C. Elmendorf.

2 recordsLinked to original sources

Divergent community trajectories with climate change across a fine-scale gradient in snow depth

Fine-scale microclimate variation due to complex topography can shape both current vegetation distributional patterns and how vegetation responds to changing climate. Topographic heterogeneity in mountains is hypothesized to mediate responses to regional climate change at the scale of metres. For alpine vegetation especially, the interplay between changing temperatures and topographically mediated variation in snow accumulation will determine the overall impact of climate change on vegetation dynamics. We combined 30 years of co-located measurements of temperature, snow and alpine plant community composition in Colorado, USA, to investigate vegetation community trajectories across a snow depth gradient. Our analysis of long-term trends in plant community composition revealed notable directional change in the alpine vegetation with warming temperatures. Furthermore, community trajectories are divergent across the snow depth gradient, with exposed parts of the landscape that experience little snow accumulation shifting towards stress-tolerant, cold- and drought-adapted communities, while snowier areas shifted towards more warm-adapted communities. Synthesis : Our findings demonstrate that fine-scale topography can mediate both the magnitude and direction of vegetation responses to climate change. We documented notable shifts in plant community composition over a 30-year period even though alpine vegetation is known for slow dynamics that often lag behind environmental change. These results suggest that the processes driving alpine plant population and community dynamics at this site are strong and highly heterogeneous across the complex topography that is characteristic of high-elevation mountain systems.

Journal of Ecology

BioTIME: A database of biodiversity time series for the Anthropocene

Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

Global Ecology and Biogeography