Determinants of community compositional change are equally affected by global change.

Global change is impacting plant community composition, but the mechanisms underlying these changes are unclear. Using a dataset of 58 global change experiments, we tested the five fundamental mechanisms of community change: changes in evenness and richness, reordering, species gains and losses. We found 71% of communities were impacted by global change treatments, and 88% of communities that were exposed to two or more global change drivers were impacted. Further, all mechanisms of change were equally likely to be affected by global change treatments-species losses and changes in richness were just as common as species gains and reordering. We also found no evidence of a progression of community changes, for example, reordering and changes in evenness did not precede species gains and losses. We demonstrate that all processes underlying plant community composition changes are equally affected by treatments and often occur simultaneously, necessitating a wholistic approach to quantifying community changes.

Temporal variability in production is not consistently affected by global change drivers across herbaceous-dominated ecosystems.

Understanding how global change drivers (GCDs) affect aboveground net primary production (ANPP) through time is essential to predicting the reliability and maintenance of ecosystem function and services in the future. While GCDs, such as drought, warming and elevated nutrients, are known to affect mean ANPP, less is known about how they affect inter-annual variability in ANPP. We examined 27 global change experiments located in 11 different herbaceous ecosystems that varied in both abiotic and biotic conditions, to investigate changes in the mean and temporal variability of ANPP (measured as the coefficient of variation) in response to different GCD manipulations, including resource additions, warming, and irrigation. From this comprehensive data synthesis, we found that GCD treatments increased mean ANPP. However, GCD manipulations both increased and decreased temporal variability of ANPP (24% of comparisons), with no net effect overall. These inconsistent effects on temporal variation in ANPP can, in part, be attributed to site characteristics, such as mean annual precipitation and temperature as well as plant community evenness. For example, decreases in temporal variability in ANPP with the GCD treatments occurred in wetter and warmer sites with lower plant community evenness. Further, the addition of several nutrients simultaneously increased the sensitivity of ANPP to interannual variation in precipitation. Based on this analysis, we expect that GCDs will likely affect the magnitude more than the reliability over time of ecosystem production in the future.

Negative biotic interactions drive predictions of distributions for species from a grassland community.

Understanding the factors that determine species' geographical distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritized in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships.

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.

Biodiversity and Resilience of Ecosystem Functions.

Accelerating rates of environmental change and the continued loss of global biodiversity threaten functions and services delivered by ecosystems. Much ecosystem monitoring and management is focused on the provision of ecosystem functions and services under current environmental conditions, yet this could lead to inappropriate management guidance and undervaluation of the importance of biodiversity. The maintenance of ecosystem functions and services under substantial predicted future environmental change (i.e., their 'resilience') is crucial. Here we identify a range of mechanisms underpinning the resilience of ecosystem functions across three ecological scales. Although potentially less important in the short term, biodiversity, encompassing variation from within species to across landscapes, may be crucial for the longer-term resilience of ecosystem functions and the services that they underpin.

Separating sensitivity from exposure in assessing extinction risk from climate change.

Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk.

Ecological distribution and population physiology defined by proteomics in a natural microbial community.

An important challenge in microbial ecology is developing methods that simultaneously examine the physiology of organisms at the molecular level and their ecosystem level interactions in complex natural systems. We integrated extensive proteomic, geochemical, and biological information from 28 microbial communities collected from an acid mine drainage environment and representing a range of biofilm development stages and geochemical conditions to evaluate how the physiologies of the dominant and less abundant organisms change along environmental gradients. The initial colonist dominates across all environments, but its proteome changes between two stable states as communities diversify, implying that interspecies interactions affect this organism's metabolism. Its overall physiology is robust to abiotic environmental factors, but strong correlations exist between these factors and certain subsets of proteins, possibly accounting for its wide environmental distribution. Lower abundance populations are patchier in their distribution, and proteomic data indicate that their environmental niches may be constrained by specific sets of abiotic environmental factors. This research establishes an effective strategy to investigate ecological relationships between microbial physiology and the environment for whole communities in situ.

Ecosystem responses to community disassembly.

Ecosystems around the world are experiencing unprecedented rates of extinction and species decline. The question of how community disassembly--the ongoing process of nonrandom species losses and declines--affects ecosystem functions, including those that influence persistence of other species, is addressed. The order in which species disappear from a community depends on their vulnerability to specific stressors and on traits associated with inherent susceptibility to decline. Information on species characteristics associated with vulnerability (response traits) is synthesized, and it is asked whether they are associated with characteristics that underpin significant contributions to ecosystem functioning (effect traits). Direct evidence that community disassembly affects ecosystem functioning comes from a variety of sources, ranging from documentation of long-term changes following the loss of an initial species or fragmentation of a landscape, to modeling and manipulative experiments that simulate species losses and observe their consequences. The usefulness to conservation and restoration practice of community disassembly as a concept is evaluated, and it is asked whether and how community disassembly can provide guidance about species loss order, its consequences, what each of these depends on, and whether a positive link exists between vulnerability and contribution to function--a link that would exacerbate the consequences of the ongoing extinction crisis.

Despite strong seasonal responses, soil microbial consortia are more resilient to long-term changes in rainfall than overlying grassland.

Climate change impacts on soil microbial communities could alter the structure of terrestrial ecosystems and biogeochemical cycles of the Earth. We used 16S rRNA gene microarrays to evaluate changes in the composition of grassland soil microbial communities under rainfall amendments simulating alternative climate change scenarios, and to compare these to responses of overlying plants and invertebrates. Following 5 years of rainfall manipulation, soil bacteria and archaea in plots where natural rain was supplemented differed little from ambient controls, despite profound treatment-related changes in the overlying grassland. During the sixth and seventh year, seasonal differences in bacterial and archaeal assemblages emerged among treatments, but only when watering exacerbated or alleviated periods of particularly aberrant conditions in the ambient climate. In contrast to effects on plants and invertebrates, effects on bacteria and archaea did not compound across seasons or years, indicating that soil microbial communities may be more robust than associated aboveground macroorganisms to certain alterations in climate.