10.5061/DRYAD.0P2NGF233
Padullés Cubino, Josep
0000-0002-2283-5004
Masaryk University
Axmanová, Irena
Masaryk University
Lososová, Zdeňka
Masaryk University
Večeřa, Martin
Masaryk University
Bergamini, Ariel
Swiss Federal Institute for Forest, Snow and Landscape Research
Bruelheide, Helge
Martin Luther University Halle-Wittenberg
Dengler, Jürgen
Zurich University of Applied Sciences
Jandt, Ute
Martin Luther University Halle-Wittenberg
Jansen, Florian
University of Rostock
Pätsch, Ricarda
Masaryk University
Chytrý, Milan
Masaryk University
The effect of niche filtering on plant species abundance in temperate
grassland communities
Dryad
dataset
2021
Community ecology
functional trait
Neutral theory
niche differentiation
seed plants
species relative cover
Czech Science Foundation
https://ror.org/01pv73b02
19-28491X
2021-12-30T00:00:00Z
2021-12-30T00:00:00Z
en
1669601 bytes
4
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1. Niche filtering predicts that abundant species in communities have
similar traits that are suitable for the environment. However, niche
filtering can operate on distinct axes of trait variation in response to
different ecological conditions. Here, we use a trait-based approach to
infer niche filtering processes and (1) test if abundant and rare species
in grassland communities are differently positioned along distinct axes of
trait variation, (2) determine if these trait variation axes, as well as
phylogenetic and functional similarities, drive species relative abundance
(aboveground cover) within communities, and (3) explore if these
relationships vary across grassland types and macro-climatic gradients. 2.
We analysed species abundance in a set of ~2,000 vegetation plots from
temperate grasslands in Central Europe as a function of species position
along three axes of trait variation: the ‘Plant Size Spectrum’ (PSS), the
‘Leaf Economics Spectrum’ (LES), and the ‘Lifespan/Clonality Spectrum’
(LCS). We also used phylogenetic and functional similarities in the
multi-dimensional trait space as predictors of species abundance. We
compared our results among alpine, wet, mesic, and dry grasslands and
tested if the effect of the predictors on species abundance was
significant across macro-climatic gradients. 3. Compared to abundant
species, rare species in grassland communities were more commonly annual
and non-clonal, had lower stature and smaller leaves and seeds, and relied
on more acquisitive leaf economics. Our predictors significantly explained
species abundance in approximately one-third of the plots. LES was the
most important predictor across all plots, with the most prominent effect
in alpine and dry grasslands and areas with more extreme temperatures. In
contrast, in mesic and wet grasslands and grasslands located in warmer and
less seasonal regions, species abundance was best predicted by
phylogenetic similarities between species, with Poaceae species becoming
more abundant. 4. Our study explored trait-abundance relationships for
different community types across a large area and broad macro-climatic
gradients. We conclude that niche filtering, and particularly
resource-acquisition trade-offs, drives species abundance in temperate
grassland communities of Central Europe. Our findings emphasize the
interaction between local environmental conditions and plant function in
determining community assembly.
The dataset contains 3 files: 1. "metadata.xls": It contains the
necessary information to interpret the other files. 2.
"sites_x_species.csv": It contains the list of species and their
abundances in sampled vegetation plots. 3.
"sites_x_predictor.csv": It contains the macroclimatic variables
(PCA axes) in each vegetation plot, and their classification into
grassland vegetation types.