Environmental change research is plagued by the curse of dimensionality: the number of communities at risk and the number of environmental drivers are both large. This raises the pressing question if a general understanding of ecological effects is achievable. These data show that this is indeed possible. It contains code that calculates the feasibility domain size (a proxy for coexistence) for bi- and tritrophic communities challenged by environmental change. Some of this code simply returns the output of a closed-form expressions (i.e. simple equations), while some rely on simulations that require specific packages.

The data also contain presence/absence data of macroinvertebrate taxa and water chemistry variables measured across sites (that are either severely or weakly modified by human activity, quantified via land use) at US streams. With these data, we were able to test if sites that share the same community have similar water chemistry, in other words: how tightly is a community linked to a certain water chemistry? This analysis demonstrates how to apply our theory to the analysis of field data, and lends support to effects of land use change on coexistence in natural invertebrate communities.

Full description of invertebrate data collection: https://www.science.org/doi/10.1126/sciadv.adf4896

RStudio, Version 2023.03.1+446 (2023.03.1+446).