Biomass fine‐scale variation is predictive of functional composition and diversity in grazed grassland. Issue 1 (3rd March 2023)

• Record Type: Journal Article
• Authors: Caram, Nicolas; Casalás, Felipe; Wallau, Marcelo O.; Soca, Pablo; Pillar, Valério D.; Cadenazzi, Monica; Boggiano, Pablo
• Is Part Of: Applied vegetation science. Volume 26:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-03
• Subjects: above‐ground biomass -- community‐weighted mean -- grazing -- herbage allowance -- interspecific trait variation -- intraspecific trait variation -- leaf traits -- Rao's functional diversity; Plant ecology -- Periodicals; Plant communities -- Periodicals; Plant populations -- Periodicals; Nature -- Effect of human beings on -- Periodicals; 581.705
• DOI: 10.1111/avsc.12714
• Languages: English
• ISSNs: 1402-2001

Abstract

Abstract: Questions: The adjustment of grazing pressure affects above‐ground biomass and its variation in space and time, which is a tool in grassland management for biodiversity conservation and livestock production. Here we ask to what extent the variation in above‐ground biomass at the scale of quadrats is predictive of (1) community‐weighted means (CWMs) of leaf traits and functional groups, and (2) functional diversity in grasslands. Location: Native grasslands ( Campos ) of northeastern Uruguay. Methods: Four paddocks of a replicated, randomized experiment, managed under high and low grazing pressure for 10 years, were monitored for above‐ground biomass and species composition during autumn, winter and spring of 2017 using 20 cm × 20 cm permanent quadrats. Thirteen dominant species were assessed seasonally for leaf dry matter content (LDMC), specific leaf area (SLA), leaf tensile strength (LTS), and leaf width (LW), which were used in cluster analysis to define functional groups. We computed CWMs and functional diversity at the quadrat scale, which we related to the above‐ground biomass by using linear mixed models attached to a maximum permutation test. Results: We identified four functional groups (FGs A, B, C and D), which considered the phenological seasonality of species and thus the highly intra‐functional group variability of leaf traits across seasons. Lower levels of biomass increased the dominance of species with lower LDMC and wider leaves (FG A and B), while higher levels of biomass increased species with higher LDMC and narrower leaves (FG D, represented by Nassella charruana ), and increased the functional diversity. Conclusions: Fine‐scale variation of above‐ground biomass is predictive of functional composition and diversity in grazed grasslands. Grazing management practices that create and maintain spatiotemporal heterogeneity can be used to favor the conservation of biodiversity and the functionality of native grasslands. Abstract : Fine‐scale biomass predicts diversity.