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Grassland biodiversity is vulnerable to land use change. How to best manage semi-natural grasslands for maintaining biodiversity is still unclear in many cases because land-use processes may depend on environmental conditions and the indirect effects of land-use on biodiversity mediated by altered abiotic and biotic factors are rarely considered. Here we evaluate the relative importance of the direct and indirect effects of grazing intensity on plant communities along an elevational gradient on a large topographic scale in the Eastern Carpathians in Ukraine. We sampled for two years 31 semi-natural grasslands exposed to cattle grazing. Within each grassland site we measured plant community properties such as the number of species, functional groups, and the proportion of species undesirable for grazing. In addition, we recorded cattle density (as a proxy for grazing intensity), soil properties (bare soil exposure, soil organic carbon, and soil pH) and densities of soil decomposers (earthworms and soil microorganisms). We used structural equation modelling to explore the direct and indirect effects of grazing intensity on plant communities along the elevation gradient. We found that cattle density decreased plant species and functional diversity but increased the proportion of undesirable species. Some of these effects were directly linked to grazing intensity (i.e., species richness), while others (i.e., functional diversity and proportion of undesirable species) were mediated via bare soil exposure. Although grazing intensity decreased with elevation, the effects of grazing on the plant community did not change along the elevation gradient. Generally, elevation had a strong positive direct effect on plant species richness as well as a negative indirect effect, mediated via altered soil acidity and decreased decomposer density. Our results indicate that plant diversity and composition are controlled by the complex interplay among grazing intensity and changing environmental conditions along an elevation gradient. Furthermore, we found lower soil pH, organic carbon and decomposer density with elevation, indicating that the effects of grazing on soil and related ecosystem functions and services in semi-natural grasslands may be more pronounced with elevation. This demonstrates that we need to account for environmental gradients when attempting to generalize effects of land-use intensity on biodiversity. [ABSTRACT FROM AUTHOR]

Biogeochemical models of vegetation dynamics could potentially be used to complement empirical studies on the effect of plant species richness. A key precondition is the simulation of species coexistence. While community scale models regularly incorporate respective processes, models at the field or landscape scale used for larger scale assessments, require additional model development. However, it is unclear how the particular process description within these models affects simulations of species performance and resulting ecosystem functions. We compare simulations of two grassland models of different complexity for monocultures and two-species mixtures in a grassland experiment in Jena, Germany. By providing an in-depth analysis of the models' process descriptions, we evaluate their ability to simulate the response of different species, their interactions and their joint performance to drought and mowing. Both models simulated similar average above-ground biomass (AGB) but showed different intra-annual variability. Generally, the models had difficulties representing a balanced species composition in multiple species mixtures and competition for space was the main driver of community composition in both models. The resulting communities were dominated by the more competitive species, while the weak competitor was only marginally present in most mixtures independent of drought and mowing. The competitive strength which we derived from the calibrated parameter sets of the species differed between the models and the agreement on which species dominate specific mixtures was mixed. While both models simulated reduced soil water content and above-ground biomass in response to drought, the strength and duration of these responses differed. Despite these differences, simulated species interactions were barely affected, and strong competitors remained dominant. Mowing had opposing effects on the competition for space in the models, which could be attributed to the different representations of plants in the two models. The models selected for the comparison are two representatives for local- and large-scale applications and use widely applied approaches for which our comparison highlighted strengths and weaknesses. To enable the investigated models (and those with similar complexity) to simulate coexistence of multiple species, niche differentiation needs to be improved. This requires a stricter separation of access to different resources and improved representation of different ecological strategies for which community scale models that are able to simulate coexistence may be an inspiration. Our approach may serve as an example for other modellers looking for ways to identify important model processes for further model development in the context of species interaction. • The model comparison showed similar biomass (AGB) with different seasonal patterns. • Competition for space was the main driver of species interaction. • Assessed grassland models have deficiencies in simulating stable coexistence. • To improve niche differentiation, incorporation of below-ground traits is needed. • Approaches from community scale models could inspire models at larger scales. [ABSTRACT FROM AUTHOR]

• Plant diversity and productivity are involved in explaining δ15N plant , δ15N soil, and δ15N soil-to-plant in North Tibet. • Precipitation is critical for driving spatial variability of δ15N plant , δ15N soil and δ15N soil-to-plant in North Tibet. • The δ15N plant and δ15N soil-to-plant indicate growth limitation shifts from P in meadows to N in desert-steppes. Nitrogen (N) cycling is a critical pathway by which producer, consumer, and decomposer interact with each other and with environmental circumstances simultaneously. The natural abundance composition of 15N/14N in plants and soils (termed as δ15N plant and δ15N soil), as well as the difference between them (δ15N soil-to-plant = δ15N plant −δ15N soil), is a useful tool for better understanding ecosystem N cycling. However, the drivers and mechanisms of ecosystem N cycling in alpine grasslands on the Tibetan Plateau are mostly unknown, especially across different grassland types at a regional scale. To fill this knowledge gap, we measured δ15N plant (200 samples of top-dominant species) and δ15N soil (85 samples of top-layer soils, 0–20 cm) at nine sites that represent zonal communities of alpine deserts, steppes, and meadows in North Tibet, and calculated the corresponding δ15N soil-to-plant. Our results showed that δ15N plant, δ15N soil, and δ15N soil-to-plant were significantly different among the three zonal grassland types (analysis of differences with non-parametric Kruskal Test, P < 0.05), with the lowest values in meadows and the highest values in deserts. Regression analyses showed that the δ15N plant , δ15N soil, and δ15N soil-to-plant decreased with the increases of growing season precipitation (GSP) and habitat aridity index (Aridity), soil organic carbon (SOC) and soil total nitrogen (STN), plant species richness, Shannon diversity index, and plant community productivity, whereas increased with the increases of accumulated active temperature (AccT) and soil total phosphorus (STP) across alpine grassland types at the regional scale. Multiple linear models with analysis of covariance (ANCOVA) confirmed GSP to be the most critical driver, which alone explained most variances of δ15N plant (56%), δ15N soil (62%), and δ15N soil-to-plant (35%). However, structural equation modeling performed better than multiple linear modeling in predicting δ15N plant (76% vs. 66%) and worse in predicting δ15N soil (79% vs. 84%) and δ15N soil-to-plant (31% vs. 46%), likely due to the exclusion of collinear predictors and the removal of non-significant influencing paths. Overall, this study has highlighted the importance to uncover the complexity of climate, soil nutrients, and vegetation properties in networking to drive the different components of ecosystem N cycling in alpine grasslands on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Abstract The biodiversity-productivity relationship is critical for better predicting ecosystem responses to climate change and human disturbance. However, it remains unclear about the effects of climate change, land use shifts, plant diversity, and their interactions on productivity partitioning above- and below-ground components in alpine grasslands on the Tibetan Plateau. To answer this question, we conducted field surveys at 33 grazed vs. fenced paired sites that are distributed across the alpine meadow, steppe, and desert-steppe zones on the northern Tibetan Plateau in early August of 2010–2013. Generalized additive models (GAMs) showed that aboveground net primary productivity (ANPP) linearly increased with growing season precipitation (GSP) while belowground net primary productivity (BNPP) decreased with growing season temperature (GST). Compared to grazed sites, short-term fencing did not alter the patterns of ANPP along climatic gradients but tended to decrease BNPP at moderate precipitation levels of 200 mm < GSP <450 mm. We also found that ANPP and BNPP linearly increased with species richness, ANPP decreased with Shannon diversity index, and BNPP did not correlate with the Shannon diversity index. Fencing did not alter the relationships between productivity components and plant diversity indices. Generalized additive mixed models furtherly confirmed that the interaction of localized plant diversity and climatic condition nonlinearly regulated productivity partitioning of alpine grasslands in this area. Finally, structural equation models (SEMs) revealed the direction and strength of causal links between biotic and abiotic variables within alpine grassland ecosystems. ANPP was controlled directly by GSP (0.53) and indirectly via species richness (0.41) and Shannon index (−0.12). In contrast, BNPP was influenced directly by GST (−0.43) and indirectly by GSP via species richness (0.05) and Shannon index (−0.02). Therefore, we recommend using a joint approach of GAMs and SEMs for better understanding mechanisms behind the relationship between biodiversity and ecosystem function under climate change and human disturbance. Highlights • Fencing did not significantly alter the plant diversity-productivity partitioning relationship. • Plant diversity and climate are interacted to influence productivity partitioning nonlinearly. • Productivity partitioning is influenced directly by climate and indirectly via plant diversity. [ABSTRACT FROM AUTHOR]

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future. • Generalized additive model revealed nonlinear climatic and anthropogenic impacts on ecosystems. • Climate change dominantly drove grassland productivity changes on the Qinghai-Tibetan Plateau. • Human impacts on grassland productivity on the Qinghai-Tibetan Plateau weakened in past decades. [ABSTRACT FROM AUTHOR]

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGBpeak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGBpeak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGBpeak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGBpeak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGBpeak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]