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.

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.

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.

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.

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.

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.

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.

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.

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.

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments.

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.

Does ecosystem sensitivity to precipitation at the site-level conform to regional-scale predictions?.

Central to understanding global C cycle dynamics is the functional relationship between precipitation and net primary production (NPP). At large spatial (regional) scales, the responsiveness of aboveground NPP (ANPP) to interannual variation in annual precipitation (AP; ANPPsens) is inversely related to site-level ANPP, coinciding with turnover of plant communities along precipitation gradients. Within ecosystems experiencing chronic alterations in water availability, plant community change will also occur with unknown consequences for ANPPsens. To examine the role plant community shifts may play in determining alterations in site-level ANPPPsens, we experimentally increased precipitation by approximately 35% for two decades in a native Central U.S. grassland. Consistent with regional models, ANPPsens decreased initially as water availability and ANPP increased. However, ANPPsens shifted back to ambient levels when mesic species increased in abundance in the plant community. Similarly, in grassland sites with distinct mesic and xeric plant communities and corresponding 50% differences in ANPP, ANPPsens did not differ over almost three decades. We conclude that responses in ANPPsens to chronic alterations in water availability within an ecosystem may not conform to regional AP-ANPP patterns, despite expected changes in ANPP and plant communities. The result is unanticipated functional resistance to climate change at the site scale.

Contrasting above- and belowground sensitivity of three Great Plains grasslands to altered rainfall regimes.

Intensification of the global hydrological cycle with atmospheric warming is expected to increase interannual variation in precipitation amount and the frequency of extreme precipitation events. Although studies in grasslands have shown sensitivity of aboveground net primary productivity (ANPP) to both precipitation amount and event size, we lack equivalent knowledge for responses of belowground net primary productivity (BNPP) and NPP. We conducted a 2-year experiment in three US Great Plains grasslands--the C4-dominated shortgrass prairie (SGP; low ANPP) and tallgrass prairie (TGP; high ANPP), and the C3-dominated northern mixed grass prairie (NMP; intermediate ANPP)--to test three predictions: (i) both ANPP and BNPP responses to increased precipitation amount would vary inversely with mean annual precipitation (MAP) and site productivity; (ii) increased numbers of extreme rainfall events during high-rainfall years would affect high and low MAP sites differently; and (iii) responses belowground would mirror those aboveground. We increased growing season precipitation by as much as 50% by augmenting natural rainfall via (i) many (11-13) small or (ii) fewer (3-5) large watering events, with the latter coinciding with naturally occurring large storms. Both ANPP and BNPP increased with water addition in the two C4 grasslands, with greater ANPP sensitivity in TGP, but greater BNPP and NPP sensitivity in SGP. ANPP and BNPP did not respond to any rainfall manipulations in the C3 -dominated NMP. Consistent with previous studies, fewer larger (extreme) rainfall events increased ANPP relative to many small events in SGP, but event size had no effect in TGP. Neither system responded consistently above- and belowground to event size; consequently, total NPP was insensitive to event size. The diversity of responses observed in these three grassland types underscores the challenge of predicting responses relevant to C cycling to forecast changes in precipitation regimes even within relatively homogeneous biomes such as grasslands.

Characterizing differences in precipitation regimes of extreme wet and dry years: implications for climate change experiments.

Climate change is intensifying the hydrologic cycle and is expected to increase the frequency of extreme wet and dry years. Beyond precipitation amount, extreme wet and dry years may differ in other ways, such as the number of precipitation events, event size, and the time between events. We assessed 1614 long-term (100 year) precipitation records from around the world to identify key attributes of precipitation regimes, besides amount, that distinguish statistically extreme wet from extreme dry years. In general, in regions where mean annual precipitation (MAP) exceeded 1000 mm, precipitation amounts in extreme wet and dry years differed from average years by ~40% and 30%, respectively. The magnitude of these deviations increased to >60% for dry years and to >150% for wet years in arid regions (MAP<500 mm). Extreme wet years were primarily distinguished from average and extreme dry years by the presence of multiple extreme (large) daily precipitation events (events >99th percentile of all events); these occurred twice as often in extreme wet years compared to average years. In contrast, these large precipitation events were rare in extreme dry years. Less important for distinguishing extreme wet from dry years were mean event size and frequency, or the number of dry days between events. However, extreme dry years were distinguished from average years by an increase in the number of dry days between events. These precipitation regime attributes consistently differed between extreme wet and dry years across 12 major terrestrial ecoregions from around the world, from deserts to the tropics. Thus, we recommend that climate change experiments and model simulations incorporate these differences in key precipitation regime attributes, as well as amount into treatments. This will allow experiments to more realistically simulate extreme precipitation years and more accurately assess the ecological consequences.

Plant community response to loss of large herbivores differs between North American and South African savanna grasslands.

Herbivory and fire shape plant community structure in grass-dominated ecosystems, but these disturbance regimes are being altered around the world. To assess the consequences of such alterations, we excluded large herbivores for seven years from mesic savanna grasslands sites burned at different frequencies in North America (Konza Prairie Biological Station, Kansas, USA) and South Africa (Kruger National Park). We hypothesized that the removal of a single grass-feeding herbivore from Konza would decrease plant community richness and shift community composition due to increased dominance by grasses. Similarly, we expected grass dominance to increase at Kruger when removing large herbivores, but because large herbivores are more diverse, targeting both grasses and forbs, at this study site, the changes due to herbivore removal would be muted. After seven years of large-herbivore exclusion, richness strongly decreased and community composition changed at Konza, whereas little change was evident at Kruger. We found that this divergence in response was largely due to differences in the traits and numbers of dominant grasses between the study sites rather than the predicted differences in herbivore assemblages. Thus, the diversity of large herbivores lost may be less important in determining plant community dynamics than the functional traits of the grasses that dominate mesic, disturbance-maintained savanna grasslands.

Loss of a large grazer impacts savanna grassland plant communities similarly in North America and South Africa.

Large herbivore grazing is a widespread disturbance in mesic savanna grasslands which increases herbaceous plant community richness and diversity. However, humans are modifying the impacts of grazing on these ecosystems by removing grazers. A more general understanding of how grazer loss will impact these ecosystems is hampered by differences in the diversity of large herbivore assemblages among savanna grasslands, which can affect the way that grazing influences plant communities. To avoid this we used two unique enclosures each containing a single, functionally similar large herbivore species. Specifically, we studied a bison (Bos bison) enclosure at Konza Prairie Biological Station, USA and an African buffalo (Syncerus caffer) enclosure in Kruger National Park, South Africa. Within these enclosures we erected exclosures in annually burned and unburned sites to determine how grazer loss would impact herbaceous plant communities, while controlling for potential fire-grazing interactions. At both sites, removal of the only grazer decreased grass and forb richness, evenness and diversity, over time. However, in Kruger these changes only occurred with burning. At both sites, changes in plant communities were driven by increased dominance with herbivore exclusion. At Konza, this was caused by increased abundance of one grass species, Andropogon gerardii, while at Kruger, three grasses, Themeda triandra, Panicum coloratum, and Digitaria eriantha increased in abundance.

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.