Compositional variation in grassland plant communities

• Autores: Bakker, Jonathan; Price, Jodi N.; Henning, Jeremiah A.; Batzer, Evan E.; Ohlert, Timothy; Wainwright, Claire E.; Adler, Peter; Alberti, Juan; Arnillas, Carlos Alberto; Biederman, Lori A.; Borer, Elizabeth; Brudvig, Lars A.; Buckley, Yvonne M.; Bugalho, Miguel N.; Cadotte, Marc W.; Caldeira, Maria C.; Catford, Jane A.; Qingqing, Chen; Crawley, Michael J.; Daleo, Pedro; Dickman, Chris R.; Donohue, Ian; DuPre, Mary Ellyn; Eisenhauer, Nico; Peri, Pablo Luis; Roscher, Christiane; Tedder, Michelle; Veen, G. F.; Virtanen, Risto; Wardle, Glenda M.
• Año de publicación: 2023
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: BRAY–CURTIS DISSIMILARITY; FERTILIZATION; SPECIES COMPOSITION; GRASSLAND
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

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.
Fil: Bakker, Jonathan. University of Washington; Estados Unidos
Fil: Price, Jodi N.. Charles Sturt University; Australia
Fil: Henning, Jeremiah A.. University of Minnesota; Estados Unidos. University of South Alabama; Estados Unidos
Fil: Batzer, Evan E.. University of California at Davis; Estados Unidos
Fil: Ohlert, Timothy. University of New Mexico; Estados Unidos
Fil: Wainwright, Claire E.. University of Washington; Estados Unidos
Fil: Adler, Peter. State University of Utah; Estados Unidos
Fil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina
Fil: Arnillas, Carlos Alberto. University of Toronto; Canadá
Fil: Biederman, Lori A.. Iowa State University; Estados Unidos
Fil: Borer, Elizabeth. University of Minnesota; Estados Unidos
Fil: Brudvig, Lars A.. Michigan State University; Estados Unidos
Fil: Buckley, Yvonne M.. Trinity College Dublin; Irlanda
Fil: Bugalho, Miguel N.. Universidade de Lisboa; Portugal
Fil: Cadotte, Marc W.. University of Toronto; Canadá
Fil: Caldeira, Maria C.. Universidade de Lisboa; Portugal
Fil: Catford, Jane A.. Kings College London (kcl);
Fil: Qingqing, Chen. Peking University; China
Fil: Crawley, Michael J.. Imperial College. London Institute Of Medical Sciences.;
Fil: Daleo, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina
Fil: Dickman, Chris R.. University of Sydney; Australia
Fil: Donohue, Ian. Trinity College Dublin; Irlanda
Fil: DuPre, Mary Ellyn. Mpg Ranch; Estados Unidos
Fil: Eisenhauer, Nico. German Centre For Integrative Biodiversity Research; Alemania. Universitat Leipzig; Alemania
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Roscher, Christiane. German Centre For Integrative Biodiversity Research; Alemania
Fil: Tedder, Michelle. University Of Kwazulu-natal; Sudáfrica
Fil: Veen, G. F.. Netherlands Institute Of Ecology; Países Bajos
Fil: Virtanen, Risto. University Of Oulu; Finlandia
Fil: Wardle, Glenda M.. The University Of Sydney; Australia