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Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520–780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580–780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during ‘dry’ extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. [ABSTRACT FROM AUTHOR]

Abstract: Savanna rangelands worldwide are threatened by shrub encroachment, i.e. the increase of woody plant species at the cost of perennial grasses, causing a strong decline in the productivity of domestic livestock production. Although recent studies indicate that fire might be of great importance for semi-arid and arid savanna dynamics, it is largely not applied in the management of semi-arid rangelands especially with regard to woody plant control. We used the eco-hydrological savanna model EcoHyD to simulate the effects of different fire management strategies on semi-arid savanna vegetation and to assess their long-term suitability for semi-arid rangeland management. Simulation results show that prescribed fires, timed to kill tree seedlings prevented shrub encroachment for a broad range of livestock densities while the possible maximum long-term cattle densities on the simulated semi-arid rangeland in Namibia increased by more than 30%. However, when grazing intensity was too high, fire management failed in preventing shrub encroachment. Our findings indicate that with regard to fire management a clear distinction between mesic and more arid savannas is necessary: While the frequency of fires is of relevance for mesic savannas, we recommend a fire management focussing on the timing of fire for semi-arid and arid savannas. [Copyright &y& Elsevier]

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]