DOI: 10.5061/dryad.zcrjdfnfc
title: Cross-scale drivers of woody plant species commonness and rarity in the Brazilian drylands

description: Aim: Locally abundant species are typically widespread, while locally
 scarce species are geographically restricted – the so-called
 abundance-occupancy relationships (AORs). AORs help explain the drivers of
 species rarity and community assembly, but little is known about how
 variation around such relationships is driven by species traits and
 niche-based processes, particularly in tropical woody plants. We tested
 the hypothesis that AORs in tropical dryland woody plants are positive and
 mediated by niche and functional traits along environmental gradients.
 Location: The Caatinga dry forest and Cerrado savannah, Brazil. Methods:
 We aggregated abundance and occurrence data into grid-cells representing
 local (10-km) to landscape scales (50-km). We calculated species mean
 relative abundance at occupied grid-cells (local abundance) and the
 proportion of grid-cells occupied (occupancy), and estimated their niche
 breadth and marginality along multivariate environmental gradients.
 Results: AORs were positive but weak at different scales in both regions
 due to some locally abundant but geographically restricted species, with
 most species being both locally and geographically rare. Cross-species
 variation in local abundance was largely unpredictable, but occupancy was
 strongly driven by niche and functional traits, with a prominent negative
 effect of niche marginality. Geographically restricted species were
 associated with rare habitats, such as wetter and less intensively used
 habitats. Large seeds and abiotic dispersal favoured occupancy in Caatinga
 at small and large spatial scales, respectively, whereas species with
 conservative leaves were more widespread across scales in Cerrado. Main
 conclusions: Woody plants in dry tropical biotas exhibit weak AORs, likely
 related to low habitat availability and dispersal limitation. Caatinga and
 Cerrado emerge as environmentally structured at multiple spatial scales,
 with several habitat-specialist rare species bearing specific regenerative
 and resource-use traits and relying on conditions threatened by climate
 change and land-use intensification. Examining AORs through the lens of
 niche, functional traits and spatial scales enables mapping patterns and
 drivers of species commonness and rarity, enhancing understanding of
 species assembly and providing tools for biodiversity conservation.
description: We first compiled a dataset of woody plant (i.e., sub-shrubs,
 shrubs, and trees) abundance within 330 plots, 121 across Caatinga dry
 forests and 209 across Cerrado savannahs (solid dots in Fig. 1).  Plots
 differed in size and stem diameter cut-offs (see Table S1, for further
 sampling details in each region), covering 122,326 plant individuals in
 Caatinga and 385,884 in Cerrado. Most of the plot data were extracted from
 the Neotropical Tree Communities database (TreeCo; Lima et al., 2020) plus
 our own data as described elsewhere (Ribeiro et al., 2015; Rito et al.,
 2017). To assess macroecological patterns from
 relatively local to landscape scales, while also reducing
 pseudo-replication issues caused by nearby plots, we aggregated abundance
 data into spatial grid-cells of different sizes (10, 20, 30, 40, and 50
 km) over the Caatinga and Cerrado regions (see an example of 50-km grid
 scale in Fig. 1). To avoid species with poorly known distributions/niches,
 only species occurring in at least three grid-cells were considered in
 further analyses. We also excluded palms, as they are frequently planted
 by locals in our focal regions. Finally, we filtered species for which
 functional trait data were available, which resulted in 135 and 417 woody
 plant species in the Caatinga and Cerrado regions, respectively, with 66
 species occurring in both regions. However, all individuals recorded
 across plots (i.e., including palms and poorly sampled species) were
 considered in estimates of species mean relative local abundances (see
 below). To accurately estimate species occupancy
 patterns, we additionally compiled georeferenced occurrence data for each
 selected plant species from the plot dataset (see above) by using the
 Botanical Information and Ecology Network - ‘BIEN’ R package (Maitner et
 al., 2017). Valid records were checked using the ‘CoordinateCleaner’ R
 package (Zizka et al., 2019). Synonyms and minor misspellings on specific
 epithets were double-checked using the ‘flora’ R package (Carvalho 2016),
 which follows the Brazilian Flora 2020 nomenclature (Brazil Flora Group
 2019). After the data compilation, cleaning,
 spatializing, and filtering steps, we calculated the local abundance and
 regional occupancy of each selected species, at each grid-cell scale in
 each biogeographic region. Local abundance was calculated as the mean
 relative abundance of a species across grid-cells at which it was
 present(hereafter, local abundance), whereas occupancy is defined as the
 proportion of grid-cells occupied by any given species by collapsing
 plot-based data and individual occurrences. We overlaid
 the spatial grid-cells on global maps of key climate, soil, topographic
 and land-use variables. Environmental variables were then averaged within
 grid-cells to measure species’ niche attributes (see below). For
 peripheral grid-cells straddling the boundaries between biogeographic
 regions, averaged environmental variables only considered the area
 representing each region. To describe species niches,
 two key measures were adopted: niche marginality and niche breadth, based
 on the outlying mean index (OMI) analysis (Dolédec et al., 2000),
 calculated using the niche function, both in the ‘ade4’ R package (Chessel
 et al., 2012).
description: The dataset includes (1) woody plant species abundance data from
 sample plots aggregated by grid-cells of different spatial resolution, (2)
 occurrence data for selected species, (3) spatial coordinates of the
 centroids of studied grid-cells, (4) environmental variables averaged by
 grid-cells, and (5) summary of local abundance, occupancy, functional
 traits and niche attributes of selected species.