Plant species adopt distinct ecological strategies to persist under different grazing intensities, broadly classified as resource-capturing (tolerate defoliation by capturing water, light, minerals, etc.; fast-growing) or resource-conserving (tolerate grazing by the location of the meristems, nutrient reserves, etc.; slow-growing). Understanding how these strategies—reflected in patterns of species composition and functional group distribution—respond to different grazing intensity, by residual herbage mass (HM), is essential for the sustainable use and conservation of natural ecosystems. Here, we evaluate the relative contribution of species and functional groups of grasses ( Poaceae ) in different HM levels in natural grasslands of southern Brazil. Grazed paddocks were selected in six sites in the Pampa biome and three sites in the High-altitude grasslands (Atlantic Forest biome). Over a year, three residual HM levels (low, medium, and high) were monitored monthly, and each level was sampled once in spring for species composition using three 0.25m 2 quadrats. Data were subjected to a randomization test, ordination analysis through principal coordinates, and regression analysis. Results show the presence of different plant species in different HMs in both the Pampa ( P = 0.0001) and Highland grasslands ( P = 0.0033). The Poaceae family was dominant across all sites and HM levels. Species such as Axonopus affinis, Paspalum notatum, Chaptalia runcinata, Senecio selloi, Dichanthelium sabulorum, Eupatorium christeanum , and Plantago myosurus predominated at low HM levels, associated with resource-capturing strategies, while Andropogon lateralis contributed more to higher levels of HM along with dead material, linked to resource-conserving strategies. The shift toward resource-conserving species occurred at approximately 5 800 kg DM ha −1 in the Pampa and 2 300 kg DM ha −1 in the High-Altitude grasslands. These findings highlight that grazing intensity (as indicated by HM levels) significantly alters species composition and functional strategies. Recognizing these patterns can support decision-making by aligning HM levels with desired vegetation outcomes, such as maintaining biodiversity or promoting forage resilience.
Motta et al. (Thu,) studied this question.