Accounting for herbaceous communities in process-based models will advance our understanding of "grassy" ecosystems.

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

Richness, not evenness, varies across water availability gradients in grassy biomes on five continents.

We sought to understand the role that water availability (expressed as an aridity index) plays in determining regional and global patterns of richness and evenness, and in turn how these water availability-diversity relationships may result in different richness-evenness relationships at regional and global scales. We examined relationships between water availability, richness and evenness for eight grassy biomes spanning broad water availability gradients on five continents. Our study found that relationships between richness and water availability switched from positive for drier (South Africa, Tibet and USA) vs. negative for wetter (India) biomes, though were not significant for the remaining biomes. In contrast, only the India biome showed a significant relationship between water availability and evenness, which was negative. Globally, the richness-water availability relationship was hump-shaped, however, not significant for evenness. At the regional scale, a positive richness-evenness relationship was found for grassy biomes in India and Inner Mongolia, China. In contrast, this relationship was weakly concave-up globally. These results suggest that different, independent factors are determining patterns of species richness and evenness in grassy biomes, resulting in differing richness-evenness relationships at regional and global scales. As a consequence, richness and evenness may respond very differently across spatial gradients to anthropogenic changes, such as climate change.

Water availability dictates how plant traits predict demographic rates.

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species' drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness.

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry.

We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO2 , warming, and decreased precipitation combined because higher water-use efficiency with elevated CO2 and higher fertility with warming compensate for responses to drought. Response to elevated CO2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO2 and climate change.

Do trade-offs govern plant species' responses to different global change treatments?

Plants are subject to trade-offs among growth strategies such that adaptations for optimal growth in one condition can preclude optimal growth in another. Thus, we predicted that a plant species that responds positively to one global change treatment would be less likely than average to respond positively to another treatment, particularly for pairs of treatments that favor distinct traits. We examined plant species' abundances in 39 global change experiments manipulating two or more of the following: CO2 , nitrogen, phosphorus, water, temperature, or disturbance. Overall, the directional response of a species to one treatment was 13% more likely than expected to oppose its response to a another single-factor treatment. This tendency was detectable across the global data set, but held little predictive power for individual treatment combinations or within individual experiments. Although trade-offs in the ability to respond to different global change treatments exert discernible global effects, other forces obscure their influence in local communities.

Grazing-induced biodiversity loss impairs grassland ecosystem stability at multiple scales.

Livestock grazing is a major driver shaping grassland biodiversity, functioning and stability. Whether grazing impacts on grassland ecosystems are scale-dependent remains unclear. Here, we conducted a sheep-grazing experiment in a temperate grassland to test grazing effects on the temporal stability of productivity across scales. We found that grazing increased species stability but substantially decreased local community stability due to reduced asynchronous dynamics among species within communities. The negative effect of grazing on local community stability propagated to reduce stability at larger spatial scales. By decreasing biodiversity both within and across communities, grazing reduced biological insurance effects and hence the upscaling of stability from species to communities and further to larger spatial scales. Our study provides the first evidence for the scale dependence of grazing effects on grassland stability through biodiversity. We suggest that ecosystem management should strive to maintain biodiversity across scales to achieve sustainability of grassland ecosystem functions and services.

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.

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data-model integration.

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is a key to meeting the pressing needs of science and society in the 21st century.

Plant traits related to precipitation sensitivity of species and communities in semiarid shortgrass prairie.

Understanding how plant communities respond to temporal patterns of precipitation in water-limited ecosystems is necessary to predict interannual variation and trends in ecosystem properties, including forage production, biogeochemical cycling, and biodiversity. In North American shortgrass prairie, we measured plant abundance, functional traits related to growth rate and drought tolerance, and aboveground net primary productivity to identify: species-level responsiveness to precipitation (precipitation sensitivity Sspp ) across functional groups; Sspp relationships to continuous plant traits; and whether continuous trait-Sspp relationships scaled to the community level. Across 32 plant species, we found strong bivariate relationships of both leaf dry matter content (LDMC) and leaf osmotic potential Ψosm with Sspp . Yet, LDMC and specific leaf area were retained in the lowest Akaike information criterion multiple regression model, explaining 59% of Sspp . Most relationships between continuous traits and Sspp scaled to the community level but were often contingent on the presence/absence of particular species and/or land management at a site. Thus, plant communities in shortgrass prairie may shift towards slower growing, more stress-resistant species in drought years and/or chronically drier climate. These findings highlight the importance of both leaf economic and drought tolerance traits in determining species and community responses to altered precipitation.

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.

General destabilizing effects of eutrophication on grassland productivity at multiple spatial scales.

Eutrophication is a widespread environmental change that usually reduces the stabilizing effect of plant diversity on productivity in local communities. Whether this effect is scale dependent remains to be elucidated. Here, we determine the relationship between plant diversity and temporal stability of productivity for 243 plant communities from 42 grasslands across the globe and quantify the effect of chronic fertilization on these relationships. Unfertilized local communities with more plant species exhibit greater asynchronous dynamics among species in response to natural environmental fluctuations, resulting in greater local stability (alpha stability). Moreover, neighborhood communities that have greater spatial variation in plant species composition within sites (higher beta diversity) have greater spatial asynchrony of productivity among communities, resulting in greater stability at the larger scale (gamma stability). Importantly, fertilization consistently weakens the contribution of plant diversity to both of these stabilizing mechanisms, thus diminishing the positive effect of biodiversity on stability at differing spatial scales. Our findings suggest that preserving grassland functional stability requires conservation of plant diversity within and among ecological communities.

Drought mildly reduces plant dominance in a temperate prairie ecosystem across years.

Shifts in dominance and species reordering can occur in response to global change. However, it is not clear how altered precipitation and disturbance regimes interact to affect species composition and dominance.We explored community-level diversity and compositional similarity responses, both across and within years, to a manipulated precipitation gradient and annual clipping in a mixed-grass prairie in Oklahoma, USA. We imposed seven precipitation treatments (five water exclusion levels [-20%, -40%, -60%, -80%, and -100%], water addition [+50%], and control [0% change in precipitation]) year-round from 2016 to 2018 using fixed interception shelters. These treatments were crossed with annual clipping to mimic hay harvest.We found that community-level responses were influenced by precipitation across time. For instance, plant evenness was enhanced by extreme drought treatments, while plant richness was marginally promoted under increased precipitation.Clipping promoted species gain resulting in greater richness within each experimental year. Across years, clipping effects further reduced the precipitation effects on community-level responses (richness and evenness) at both extreme drought and added precipitation treatments. Synthesis: Our results highlight the importance of studying interactive drivers of change both within versus across time. For instance, clipping attenuated community-level responses to a gradient in precipitation, suggesting that management could buffer community-level responses to drought. However, precipitation effects were mild and likely to accentuate over time to produce further community change.

Rapid recovery of ecosystem function following extreme drought in a South African savanna grassland.

Climatic extremes, such as severe drought, are expected to increase in frequency and magnitude with climate change. Thus, identifying mechanisms of resilience is critical to predicting the vulnerability of ecosystems. An exceptional drought (

Global change effects on plant communities are magnified by time and the number of global change factors imposed.

Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity-ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously.

Ambient changes exceed treatment effects on plant species abundance in global change experiments.

The responses of species to environmental changes will determine future community composition and ecosystem function. Many syntheses of global change experiments examine the magnitude of treatment effect sizes, but we lack an understanding of how plant responses to treatments compare to ongoing changes in the unmanipulated (ambient or background) system. We used a database of long-term global change studies manipulating CO2 , nutrients, water, and temperature to answer three questions: (a) How do changes in plant species abundance in ambient plots relate to those in treated plots? (b) How does the magnitude of ambient change in species-level abundance over time relate to responsiveness to global change treatments? (c) Does the direction of species-level responses to global change treatments differ from the direction of ambient change? We estimated temporal trends in plant abundance for 791 plant species in ambient and treated plots across 16 long-term global change experiments yielding 2,116 experiment-species-treatment combinations. Surprisingly, for most species (57%) the magnitude of ambient change was greater than the magnitude of treatment effects. However, the direction of ambient change, whether a species was increasing or decreasing in abundance under ambient conditions, had no bearing on the direction of treatment effects. Although ambient communities are inherently dynamic, there is now widespread evidence that anthropogenic drivers are directionally altering plant communities in many ecosystems. Thus, global change treatment effects must be interpreted in the context of plant species trajectories that are likely driven by ongoing environmental changes.

Successional change in species composition alters climate sensitivity of grassland productivity.

Succession theory predicts altered sensitivity of ecosystem functions to disturbance (i.e., climate change) due to the temporal shift in plant community composition. However, empirical evidence in global change experiments is lacking to support this prediction. Here, we present findings from an 8-year long-term global change experiment with warming and altered precipitation manipulation (double and halved amount). First, we observed a temporal shift in species composition over 8 years, resulting in a transition from an annual C3 -dominant plant community to a perennial C4 -dominant plant community. This successional transition was independent of any experimental treatments. During the successional transition, the response of aboveground net primary productivity (ANPP) to precipitation addition magnified from neutral to +45.3%, while the response to halved precipitation attenuated substantially from -17.6% to neutral. However, warming did not affect ANPP in either state. The findings further reveal that the time-dependent climate sensitivity may be regulated by successional change in species composition, highlighting the importance of vegetation dynamics in regulating the response of ecosystem productivity to precipitation change.

Asynchrony among local communities stabilises ecosystem function of metacommunities.

Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species-level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1-315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with species' populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales.