A landscape‐scale assessment of the relationship between grassland functioning, community diversity, and functional traits

Abstract

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity–productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity–insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape‐scale. Here, we provide a landscape‐scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape‐scale grassland productivity.

Ecosystem stability at the landscape scale is primarily associated with climatic history

“…Many previous investigations of stability have focused on temporal variation (e.g. van ‘t Veen et al., 2020), but here we show that different dimensions of stability are associated with different climatic factors. Preparing for temporal variation in production, therefore, will not necessarily decrease the magnitude of or provide faster recovery rates from specific perturbation events.…”

Precipitation Variability Affects Aboveground Biomass Directly and Indirectly via Plant Functional Traits in the Desert Steppe of Inner Mongolia, Northern China

“…These results are in line with those of other studies that showed that CWMs have an important consequence for ecosystem functioning along environment gradient (Diaz et al, 2007 ; Roscher et al, 2012 ; Chiang et al, 2016 ; Cadotte, 2017 ). Van'T Veen et al ( 2020 ) suggested that temperature and precipitation explained additional 22.1% of the variation in productivity, and that functional trait composition was an important predictor of grassland productivity in Switzerland grasslands. Combining previous studies, we believe that leaf functional traits (except for LT) are good response traits to precipitation change at the community level (Gross et al, 2008 ; Suding et al, 2008 ; Sterk et al, 2013 ).…”

Study of Forage Quality of Grasslands on the Southern Margin of the Pannonian Basin

“…It was found out that forage quality highly correlates with humidity, the proportion of weed and ruderal species, the proportion of sedges and stress tolerant species, and mowing. Using this approach, we confirmed that plant traits are a good predictor of grasslands productivity [18]. These are economically important habitats with high nature conservation value, providing many ecosystem services [11].…”

“…Our research studied the forage quality of grassland habitats from the ecological and functional points of view, but forage quality is also result of multiple other factors, e.g., macroclimate, management, and landscape [14,15], that are, in part, also integrated in the definition of grassland habitats [3,16,17]. We tried to establish the correlation between the forage quality and functional trait composition of grasslands since it has been established that the latter is an important predictor of grassland productivity [18].…”