• Energy Research

Standardized sampling from many sites worldwide was used to address an important ecological problem.

AbstractTheory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities.

Biotic interaction studies have revealed a large discrepancy among experiments in target responses to the effects of neighbours, which may in part be due to both high species-specificity of plant responses and low number of target species used in experiments. Our aim was to assess facilitative responses at the community level and the role of both functional groups and ecological attributes of target species. In a sub-alpine grassland on the eastern Tibet plateau, we assessed growth responses of all species in the community to removal of a dominant shrub. We also measured changes in the main environmental variables. Species responses were analysed by functional group and in relation to their mean regional altitudinal distribution. All significant interactions were positive and affected one-third of the total species richness of the community. All functional groups were facilitated but forbs were less strongly facilitated than in the two other groups. High-alpine species were less strongly facilitated than low-sub-alpine species, but the strength of this relationship was weaker than that reported in previous work. There was evidence of a decrease in extreme temperatures below the canopy of the shrub but no variations in soil moisture. We conclude that the highly stressful conditions induced by the dry continental climate of the eastern Tibet plateau are a main driver of the exclusive dominance of positive interactions. Assessing interactive responses at the community level is likely to provide a useful tool to better understand the role of biotic interactions in community responses to environmental changes.

Abstract Predicting changes in plant diversity in response to human activities represents one of the major challenges facing ecologists and land managers striving for sustainable ecosystem management. Classical field studies have emphasized the importance of community primary productivity in regulating changes in plant species richness. However, experimental studies have yielded inconsistent empirical evidence, suggesting that primary productivity is not the sole determinant of plant diversity. Recent work has shown that more accurate predictions of changes in species diversity can be achieved by combining measures of species’ cover and height into an index of space resource utilization (SRU). While the SRU approach provides reliable predictions, it is time‐consuming and requires extensive taxonomic expertise. Ecosystem processes and plant community structure are likely driven primarily by dominant species (mass ratio effect). Within communities, it is likely that dominant and rare species have opposite contributions to overall biodiversity trends. We, therefore, suggest that better species richness predictions can be achieved by utilizing SRU assessments of only the dominant species (SRUD), as compared to SRU or biomass of the entire community. Here, we assess the ability of these measures to predict changes in plant diversity as driven by nutrient addition and herbivore exclusion. First, we tested our hypotheses by carrying out a detailed analysis in an alpine grassland that measured all species within the community. Next, we assessed the broader applicability of our approach by measuring the first three dominant species for five additional experimental grassland sites across a wide geographic and habitat range. We show that SRUD outperforms community biomass, as well as community SRU, in predicting biodiversity dynamics in response to nutrients and herbivores in an alpine grassland. Across our additional sites, SRUD yielded far better predictions of changes in species richness than community biomass, demonstrating the robustness and generalizable nature of this approach. Synthesis. The SRUD approach provides a simple, non‐destructive and more accurate means to monitor and predict the impact of global change drivers and management interventions on plant communities, thereby facilitating efforts to maintain and recover plant diversity.

AbstractThe need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot) and stand age (a). The authors of that study concluded that the length of the growing season (lgs) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re‐analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum‐likelihood model selection, independent‐effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot, both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale.

Studies of experimental grassland communities have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change. Here we analyse diversity-stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.