Compositional variation in grassland plant communities

Bakker, Jonathan D. and Price, Jodi N. and Henning, Jeremiah A. and Batzer, Evan E. and Ohlert, Timothy J. and Wainwright, Claire E. and Adler, Peter B. and Alberti, Juan and Arnillas, Carlos Alberto and Biederman, Lori A. and Borer, Elizabeth T. and Brudvig, Lars A. and Buckley, Yvonne M. and Bugalho, Miguel N. and Cadotte, Marc W. and Caldeira, Maria C. and Catford, Jane A. and Chen, Qingqing and Crawley, Michael J. and Daleo, Pedro and Dickman, Chris R. and Donohue, Ian and DuPre, Mary Ellyn and Ebeling, Anne and Eisenhauer, Nico and Fay, Philip A. and Gruner, Daniel S. and Haider, Sylvia and Hautier, Yann and Jentsch, Anke and Kirkman, Kevin and Knops, Johannes M. H. and Lannes, Lucíola S. and MacDougall, Andrew S. and McCulley, Rebecca L. and Mitchell, Rachel M. and Moore, Joslin L. and Morgan, John W. and Mortensen, Brent and Olde Venterink, Harry and Peri, Pablo L. and Power, Sally A. and Prober, Suzanne M. and Roscher, Christiane and Sankaran, Mahesh and Seabloom, Eric W. and Smith, Melinda D. and Stevens, Carly and Sullivan, Lauren L. and Tedder, Michelle and Veen, G. F. (Ciska) and Virtanen, Risto and Wardle, Glenda M. (2023) Compositional variation in grassland plant communities. Ecosphere, 14 (6). ISSN 2150-8925

Abstract

Human activities are altering ecological communities around the globe. Understanding the implications of these changes requires that we consider the composition of those communities. However, composition can be summarized by many metrics which in turn are influenced by different ecological processes. For example, incidence‐based metrics strongly reflect species gains or losses, while abundance‐based metrics are minimally affected by changes in the abundance of small or uncommon species. Furthermore, metrics might be correlated with different predictors. We used a globally distributed experiment to examine variation in species composition within 60 grasslands on six continents. Each site had an identical experimental and sampling design: 24 plots × 4 years. We expressed compositional variation within each site—not across sites—using abundance‐ and incidence‐based metrics of the magnitude of dissimilarity (Bray–Curtis and Sorensen, respectively), abundance‐ and incidence‐based measures of the relative importance of replacement (balanced variation and species turnover, respectively), and species richness at two scales (per plot‐year [alpha] and per site [gamma]). Average compositional variation among all plot‐years at a site was high and similar to spatial variation among plots in the pretreatment year, but lower among years in untreated plots. For both types of metrics, most variation was due to replacement rather than nestedness. Differences among sites in overall within‐site compositional variation were related to several predictors. Environmental heterogeneity (expressed as the CV of total aboveground plant biomass in unfertilized plots of the site) was an important predictor for most metrics. Biomass production was a predictor of species turnover and of alpha diversity but not of other metrics. Continentality (measured as annual temperature range) was a strong predictor of Sorensen dissimilarity. Metrics of compositional variation are moderately correlated: knowing the magnitude of dissimilarity at a site provides little insight into whether the variation is driven by replacement processes. Overall, our understanding of compositional variation at a site is enhanced by considering multiple metrics simultaneously. Monitoring programs that explicitly incorporate these implications, both when designing sampling strategies and analyzing data, will have a stronger ability to understand the compositional variation of systems and to quantify the impacts of human activities.