A global meta-analysis of grazing effects on plant richness

Abstract A major challenge in rangeland ecology is understanding diverse responses of diversity to grazing, what factors determine these responses and what their relative importance is. Numerous site-level studies have explored grazing-diversity relations, but meta-analyses of these empirical results at a global scale are scarce. Our goals were to estimate the mean effect of grazing on plant richness and to assess the relative importance of different variables at a global scale. We conducted a global meta-analysis of 259 comparisons of plant richness in grazed vs. ungrazed sites from 96 published studies. Then, we performed analyses of subgroup, meta-regression and correlation for testing the relative roles of regional and local variables (e.g. evolutionary history of grazing, aridity, stocking rate, etc.). Globally, grazing significantly increased plant richness compared to grazing exclusion, especially in wet grasslands. The effect of evolutionary history of grazing was insignificant, which cannot support the major perception behind Milchunas-Sala-Lauenroth (MSL) model. Aridity, vegetation type, and stocking rate were three important variables that together explained 41 % of the global variation in plant richness. The roles of stocking rate and duration of grazing exclusion were revealed only when aridity and vegetation type were added to the analyses, which showed a stronger effect of stocking rate in wet areas but a stronger effect of the duration of grazing exclusion in dry areas. Changes in plant richness were significantly correlated with changes in soil carbon and nitrogen, both showing hump-shaped patterns. Our findings substantiate that scholars may improve existing theories (e.g. the MSL model, the intermediate disturbance hypothesis) through further expounding the interactions between grazing variables and aridity and vegetation type. Rangeland managers need to devise local-scale grazing strategies for conserving plant diversity according to site-specific conditions, rather than adopting a one-size-fits-all solution.