Data from a flexible framework to assess patterns and drivers of beta diversity across spatial scales

The patterns and underlying ecological (e.g., environmental filtering) and historical (e.g., priority effects) drivers of beta diversity are scale-dependent but generally difficult to distinguish and rarely explored with a sufficiently broad range of spatial scales. We propose a general scale-explicit framework to assess and contrast the patterns and drivers of beta diversity across hierarchical spatial scales ranging from within fine-scale ecoregion-scale to among broad-scale ecoregion-scale. By applying this framework to aquatic macroinvertebrate datasets, we show that beta diversity generally increases with spatial extent. With an increasing spatial extent, beta diversity shifts from being more influenced by environmental filtering to being more influenced by recent historical factors (i.e., past beta diversity). Such recent historical effects may result from past environmental variation rather than priority effects. We also found that the small-scale and large-scale environmental dr..., , Data are compiled in different files containing the following information: 1) Presence-absence macroinvertebrate taxon dataset in the previous survey, 2) Presence-absence macroinvertebrate taxon dataset in the following survey, 3) dataset of explanatory variables., # Macroinvertebrate taxon dataset assembled two different times (past and contemporary) and explanatory data

Authors: Siwen He, Chunyan Qin, Janne Soininen; A flexible framework to assess patterns and drivers of beta diversity across spatial scales

Correspondence: Siwen He; [e-mail]

### Description of files:

1. nrsa0304\_past\_communities.csv: containing the following information: Presence-absence macroinvertebrate taxon dataset in previous (2000-2004) survey
2. nrsa0809\_contemporary\_communities.csv: containing the following information: Presence-absence macroinvertebrate taxon dataset in the following (2008-2009) survey
3. Explanatory\_variables.csv: containing nine physicochemical variables, and four landscape variables, and five spatial network variables, and four bioclimatic variables

Physicochemical variables:

* NH4 (mg/L) ammonia nitrogen
* total.P (μg/L) total phosphorus
* NO3 (mg N/L) nitrate
* pH.lab pH
* DOC (mg/L) dissolved organic carbon
* LWD.reach (volu...