Statistical methods for analyzing ecological multinomial time series to identify environmental and biotic drivers of community change
By
Quinn Asena
Summary
This article presents statistical methods for analyzing ecological multinomial time series to disentangle the effects of environmental drivers (like temperature, rainfall, disturbance) from biotic interactions on community dynamics. It addresses the challenge of statistical inference from multivariate time series in community ecology and paleoecology, where relative abundance data across multiple species is analyzed alongside environmental variables. The paper focuses on methodological approaches to understand what drives changes in ecological communities over time.
Source
bskyStatistical methods for analyzing ecological multinomial time series to identify environmental and biotic drivers of community changebuff.lyKey quotes
· 3 pulledA common research goal in community ecology and paleoecology is to disentangle the relative effects of abiotic drivers and biotic interactions on community dynamics.
Pursuing this goal often involves analysing multi-species time series in concert with time series of possible environmental drivers such as temperature, rainfall and disturbance regimes.
Understanding the drivers of change in communities is a major goal of paleoecology and community ecology, but statistical inference from multivariate time series is challenged by relative (rather than absolute) abundance data.
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