Data from: SRUD: a simple non-destructive method for accurate quantification of plant diversity dynamics

1. Predicting changes in plant diversity in response to human activities
represents one of the major challenges facing ecologists and land managers
striving for sustainable ecosystem management. Classical field studies
have emphasized the importance of community primary productivity in
regulating changes in plant species richness. However, experimental
studies have yielded inconsistent empirical evidence, suggesting that
primary productivity is not the sole determinant of plant diversity.
Recent work has shown that more accurate predictions of changes in species
diversity can be achieved by combining measures of species' cover and
height into an index of Space Resource Utilization (SRU). While the SRU
approach provides reliable predictions, it is time-consuming and requires
extensive taxonomic expertise. Ecosystem processes and plant community
structure are likely driven primarily by dominant species (mass-ratio
effect). Within communities, it is likely that dominant and rare species
have opposite contributions to overall biodiversity trends. We therefore
suggest that better species richness predictions can be achieved by
utilizing SRU assessments of only the dominant species (SRUD), as compared
to SRU or biomass of the entire community. 2. Here, we assess the ability
of these measures to predict changes in plant diversity as driven by
nutrient addition and herbivore exclusion. First, we tested our hypotheses
by carrying out a detailed analysis in an alpine grassland that measured
all species within the community. Next, we assessed the broader
applicability of our approach by measuring the first three dominant
species for five additional experimental grassland sites across a wide
geographic and habitat range. 3. We show that SRUD outperforms community
biomass, as well as community SRU, in predicting biodiversity dynamics in
response to nutrients and herbivores in an alpine grassland. Across our
additional sites, SRUD yielded far better predictions of changes in
species richness than community biomass, demonstrating the robustness and
generalizable nature of this approach. 4. Synthesis. The SRUD approach
provides a simple, non-destructive and more accurate means to monitor and
predict the impact of global change drivers and management interventions
on plant communities, thereby facilitating efforts to maintain and recover
plant diversity.