DOI: 10.5061/dryad.k88v330
title: Data from: Testing species assemblage predictions from stacked and joint species distribution models

description: Aim: Predicting the spatial distribution of species assemblages remains an
 important challenge in biogeography. Recently, it has been proposed to
 extend correlative species distribution models (SDMs) by taking into
 account (a) covariance between species occurrences in so-called joint
 species distribution models (JSDMs) and (b) ecological assembly rules
 within the SESAM (spatially explicit species assemblage modelling)
 framework. Yet, little guidance exists on how these approaches could be
 combined. We, thus, aim to compare the accuracy of assemblage predictions
 derived from stacked and from joint SDMs. Location: Switzerland Taxon
 Birds, tree species Methods: Based on two monitoring schemes (national
 forest inventory and Swiss breeding bird atlas), we built SDMs and JSDMs
 for tree species (at 100m resolution) and forest birds (at 1km
 resolution). We tested accuracy of species assemblage and richness
 predictions on holdout data using different stacking procedures and
 ecological assembly rules. Results Despite minor differences, results were
 consistent between birds and tree species. Cross-validated species-level
 model performance was generally higher in SDMs than JSDMs. Differences in
 species richness and assemblage predictions were larger between stacking
 procedures and ecological assembly rules than between stacked SDMs and
 JSDMs. On average, predictions were slightly better for stacked SDMs
 compared to JSDMs, probabilistic stacks outperformed binary stacks, and
 ecological assembly rules yielded best predictions. Main conclusions: When
 predicting the composition of species assemblages, the choice of stacking
 procedure and ecological assembly rule seems more decisive than
 differences in underlying model type (SDM vs. JSDM). JSDMs do not seem to
 improve community predictions compared to SDMs or improve predictions for
 rare species. Still, JSDMs may provide additional insights into community
 assembly and may help deriving hypotheses about prevailing biotic
 interactions in the system. We provide simple rules of thumb for choosing
 appropriate modelling pathways. Future studies should test these
 preliminary guidelines for other taxa and biogeographic realms as well as
 for other JSDM algorithms.
description: Data of Swiss Breeding
 BirdsBird presence-absence
 data from the Swiss breeding bird atlas at a 1x1 km resolution. [Schmid,
 H., Luder, R., Naef-Daenzer, B., Graf, R. & Zbinden, N. (1998)
 Schweizer Brutvogelatlas. Verbreitung der Brutvögel inder Schweiz und im
 Fürstentum Liechtenstein 1993-1996. Swiss Ornithological Institute,
 Sempach, Switzerland]. These data were recorded over a four-year period
 (1993-1996) in usually three visits per year (two above the treeline)
 using a simplified territory mapping approach. We only considered species
 with at least 50 presences resulting in a total number of 56 forest bird
 species in the study region. Environmental predictor variables include
 climate, topography and vegetation structure at the same resolution as the
 species data. Please refer to main article and its Online Supplementary
 Material for description of the data. Geographic coordinates were
 removed.Data_SwissBreedingBirds.csvData of Swiss National Forest InventoryTree species presence-absence data were obtained from the Swiss National Forest Inventory (NFI) . The NFI samples Switzerland on a regular grid (spacing 1.4 km), and in case the sample falls into forest it records forest characteristics in a maximal area of 50x50 m. We aggregated the NFI presence-absence data to 100x100 m plot size to match the minimum grain of available environmental data. We only considered species with at least 50 presences resulting in a total number of 63 tree and shrub species in the study region. Environmental predictor variables include climate, topography and vegetation structure at the same resolution as the species data. Please refer to main article and its Online Supplementary Material for description of the data. Geographic coordinates were removed.Data_SwissNationalForestInventory.csv