Vertebrate herbivore‐induced changes in plants and soils: linkages to ecosystem functioning in a semi‐arid steppe

Abstract

Summary1. Large grazing herbivores have been reported to determine the structure and function of grassland ecosystems. However, the ecological linkages between structure and functioning components have yet been thoroughly explored. 2. Here, we test the hypothesis of the impact of grazing on soil nematode community (e.g. structure and composition) and linkages to ecosystem functioning (e.g. soil N mineralization and ANPP) via changes in pathways of plant community, soil nutrients and soil environment using a field experiment maintained for 5 years with seven levels of grazing intensity in the Inner Mongolian grassland. 3. A structural equation model (SEM) with nematode abundances as response variables showed that plant-feeding and fungal-feeding nematodes were driven by changes in the plant community, and bacterial-feeding nematodes were affected by soil abiotic nutrients and environment, while omnivorous + carnivorous nematodes were altered by soil environment and bacterial-feeding nematodes. This indicates that the top-down control by grazing leads to bottom-up control in the soil food web. 4. We found that grazing affected the ecosystem functioning via different pathways. Grazing effects soil N mineralization by changing plant community, soil nutrients, soil environment and nematodes community structure, while it affects ANPP by altering soil N mineralization and soil environment. 5. Our findings could provide a better understanding of the responses of plants and soils to grazing and the linkages between structure and functioning of above-ground and belowground in the semi-arid steppe.

Evidence that acidification‐induced declines in plant diversity and productivity are mediated by changes in below‐ground communities and soil properties in a semi‐arid steppe

“…soil moisture, available phosphorus and extractable Ca 2+ , Mg 2+ and Na + ); (iv) N cycling (net N mineralization rate, soil NH þ 4 -N and NO À 3 -N); (v) soil microorganisms (PC1 of entire FAs, bacterial FAs, fungal FAs and the fungi/bacteria); (vi) soil nematodes (total nematode abundance, taxa richness, maturity index and PPI); and (vii) plant community (species richness and total community cover). Because variables in each functional group are often correlated, we used PCA to create multivariate functional indexes (principal components) for each functional group with multiple variables and each acidification intensity (Chen et al 2013). For each functional group with multiple variables, the first principal component (PC1), which explained 42-86% of the total variance, was used in the subsequent SEM analysis (Table S1).…”

“…We established a 3-year field experiment with seven levels of acid addition rate at a semi-arid Inner Mongolia grassland, which is part of a widely distributed grassland across the Eurasian Steppe region (Bai et al 2004;Chen et al 2013). The semi-arid Inner Mongolia grassland, together with soils of alkaline origin, enables us to test the four interrelated hypotheses that have been proposed to be the major mechanisms underpinning soil acidification-induced plant diversity loss and changes in ecosystem functioning.…”

Biotic community shifts explain the contrasting responses of microbial and root respiration to experimental soil acidification

“…Because variables in each functional group are often correlated, we used principal components analyses (PCA) to create multivariate functional indexes (principal components) for each functional group with multiple variables (Chen et al, 2013a(Chen et al, , 2013b. For each functional group with multiple variables, the first principal component (PC1), which explained 48e84% of the total variance, was used in the subsequent SEM analysis (Table S1).…”

Relationship between Soil Characteristics and Stand Structure of Robinia pseudoacacia L. and Pinus tabulaeformis Carr. Mixed Plantations in the Caijiachuan Watershed: An Application of Structural Equation Modeling

“…Due to their statistical strength and applicability, SEM approaches have been employed in a wide range of environmental and ecological studies [16][17][18][19]. For example, SEM has been applied to evaluate the effect of grazing on ecosystem processes [20,21]; the relationships between fire and edaphic factors and woody vegetation structure and composition [22]; the sensitivity of soil respiration to environmental factors [23]; the impacts of land uses on stream integrity [24]; the factors that affect plant richness in recovering forests [25,26]; the relationships associated with the decline in species richness, as natural landscapes undergo conversion to human-dominated landscapes [27]; and both the direct and indirect association of plant species richness to landscape conditions and local environmental factors [28,29]. However, to our knowledge, SEM methods have not been applied to study stand structure impacts on soil and water conservation.…”