DOI: 10.5061/dryad.1c59zw3sf
title: Scale-dependence of ecological assembly rules: insights from empirical datasets and joint species distribution modelling

description: 1. A comprehensive understanding of the scale-dependency of environmental
 filtering and biotic interactions influencing the local assembly of
 species is paramount to derive realistic forecasts of the future of
 biodiversity and efficiently manage ecological communities. A classical
 assumption is that environmental filters are more prevalent at larger
 scales with diminishing effects towards the finest scales where biotic
 interactions become more decisive. Recently, a refinement was proposed
 stipulating that the scale-dependency of biotic interactions should relate
 to the type of interaction. Specifically, the effect of negative
 interactions (e.g. competition) should diminish with coarsening scale,
 whereas positive interactions (i.e. facilitation) should be detected
 irrespective of the scale. 2. We use multiple vascular plant species
 datasets sampled at nested spatial scales (plot size varying from 0.04 to
 64 m2) and recently developed joint species distribution models (JSDM) to
 test the hypotheses. 3. Our analyses indicate slightly stronger
 environmental filtering with increasing plot size. While the overall
 strength of biotic interactions did not vary consistently across scales,
 we found a tendency for negative interactions to fade away with increasing
 plot size slightly more than positive interactions. Synthesis: We provide
 partial, but not unambiguous, evidence of the scale-dependency of
 ecological assembly rules. However, our correlative methodology only
 allows us to interpret the findings as indication of environmental
 filtering and biotic interactions.
description: The datasets are collected from nested plots (sizes varying from
 20 × 20 cm = 0.04 cm<sup>2</sup> to 8 × 8 m = 64
 m<sup>2</sup>) located in non-forested sites in two study
 areas. Each dataset comprises presence-absence observations of vascular
 plant species with prevalence of 0.05-0.95 at all plot sizes and spatially
 related information of the abiotic environment. Species were recorded as
 present even if only a part of aboveground vegetative growth was within
 the plot. The Alpine datasets was collected in the
 western Swiss Alps (46°23’ N, 7°5’ E). AlpineM consists of 434 sites, each
 with four nested square plots of 1, 4, 16 and 64
 m<sup>2</sup>. AlpineCM consists of 298 square sites of 4
 m<sup>2</sup>, with additional five square subplots of 20 × 20
 cm within each site The environmental variables (growing degree days,
 topographic position index, soil pH and solar radiation) for each site
 were derived from raster layers with a spatial resolution of 25 × 25
 m. The Arctic datasets were collected in mount Saana in
 northern Finland (69°2' N, 20°51' E). The plots are organized in
 21 grids of 8 m × 20 m, each grid consisting of 160 plots of 1
 m<sup>2</sup>. ArcticCM contains 12 grids with species sampled
 within plots of sizes 20 × 20, 40 × 40 and 100 × 100 cm. Under this
 design, plots of 20 and 40 cm resolutions are nested and randomly located
 inside the 100 cm-plots. ArcticM comprises all 21 grids, and 1
 m<sup>2</sup> is used as the smallest plot size, and larger
 plot sizes (4 and 16 m<sup>2</sup>) were formed by dividing
 the grids in 2 m × 2 m and 4 m × 4 m plots. Few plots of 1 and 4
 m<sup>2</sup> containing no species were removed. For arctic
 datasets, the abiotic variables (soil temperature, moisture and pH, annual
 solar radiation, and rock cover) were derived at a 1 × 1 m.
description: These datasets (partly or completely) have been used in many
 other publications from the groups ECOSPAT (University of Lausanne; led by
 Prof. Antoine Guisan) and BioGeoClimate Modelling Lab (University of
 Helsinki; led by Prof. Miska Luoto). Thus, subsets of sites and species of
 these datasets can already be found in DryAd. Sites can be connected based
 on siteID and species by their names (or abbreviations).