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.

Empirical evidence of widespread exaggeration bias and selective reporting in ecology.

In many scientific disciplines, common research practices have led to unreliable and exaggerated evidence about scientific phenomena. Here we describe some of these practices and quantify their pervasiveness in recent ecology publications in five popular journals. In an analysis of over 350 studies published between 2018 and 2020, we detect empirical evidence of exaggeration bias and selective reporting of statistically significant results. This evidence implies that the published effect sizes in ecology journals exaggerate the importance of the ecological relationships that they aim to quantify. An exaggerated evidence base hinders the ability of empirical ecology to reliably contribute to science, policy, and management. To increase the credibility of ecology research, we describe a set of actions that ecologists should take, including changes to scientific norms about what high-quality ecology looks like and expectations about what high-quality studies can deliver.

Multiple global change drivers show independent, not interactive effects: a long-term case study in tallgrass prairie.

Ecosystems are faced with an onslaught of co-occurring global change drivers. While frequently studied independently, the effects of multiple global change drivers have the potential to be additive, antagonistic, or synergistic. Global warming, for example, may intensify the effects of more variable precipitation regimes with warmer temperatures increasing evapotranspiration and thereby amplifying the effect of already dry soils. Here, we present the long-term effects (11 years) of altered precipitation patterns (increased intra-annual variability in the growing season) and warming (1 °C year-round) on plant community composition and aboveground net primary productivity (ANPP), a key measure of ecosystem functioning in mesic tallgrass prairie. Based on past results, we expected that increased precipitation variability and warming would have additive effects on both community composition and ANPP. Increased precipitation variability altered plant community composition and increased richness, with no effect on ANPP. In contrast, warming decreased ANPP via reduction in grass stems and biomass but had no effect on the plant community. Contrary to expectations, across all measured variables, precipitation and warming treatments had no interactive effects. While treatment interactions did not occur, each treatment did individually impact a different component of the ecosystem (i.e., community vs. function). Thus, different aspects of the ecosystem may be sensitive to different global change drivers in mesic grassland ecosystems.

Current street tree communities reflect race-based housing policy and modern attempts to remedy environmental injustice.

Humans promote and inhibit other species on the urban landscape, shaping biodiversity patterns. Institutional racism may underlie the distribution of urban species by creating disproportionate resources in space and time. Here, we examine whether present-day street tree occupancy, diversity, and composition in Baltimore, MD, USA, neighborhoods reflect their 1937 classification into grades of loan risk-from most desirable (A = green) to least desirable (D = "redlined")-using racially discriminatory criteria. We find that neighborhoods that were redlined have consistently lower street tree α-diversity and are nine times less likely to have large (old) trees occupying a viable planting site. Simultaneously, redlined neighborhoods were locations of recent tree planting activities, with a high occupancy rate of small (young) trees. However, the community composition of these young trees exhibited lower species turnover and reordering across neighborhoods compared to those in higher grades, due to heavy reliance on a single tree species. Overall, while the negative effects of redlining remain detectable in present-day street tree communities, there are clear signs of recent investment. A strategy of planting diverse tree cohorts paired with investments in site rehabilitation and maintenance may be necessary if cities wish to overcome ecological feedbacks associated with legacies of environmental injustice.

Exploring the impact of trait number and type on functional diversity metrics in real-world ecosystems.

The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work in studies that simulate communities and trait distributions show consistent sensitivity of functional richness and evenness measures to the number of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. Therefore, we propose to test how the number of traits used and the correlation between traits used in the calculation of functional diversity indices impacts the magnitude of eight functional diversity metrics in real plant communities. We will use trait data from three grassland plant communities in the US to assess the generality of our findings across ecosystems and experiments. We will determine how eight functional diversity metrics (functional richness, functional evenness, functional divergence, functional dispersion, kernel density estimation (KDE) richness, KDE evenness, KDE dispersion, Rao's Q) differ based on the number of traits used in the metric calculation and on the correlation of traits when holding the number of traits constant. Without a firm understanding of how a scientist's choices impact these metric, it will be difficult to compare results among studies with different metric parametrization and thus, limit robust conclusions about functional composition of communities across systems.

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.

Urban net primary production: Concepts, field methods, and Baltimore, Maryland, USA case study.

Given the large and increasing amount of urban, suburban, and exurban land use on Earth, there is a need to accurately assess net primary productivity (NPP) of urban ecosystems. However, the heterogeneous and dynamic urban mosaic presents challenges to the measurement of NPP, creating landscapes that may appear more similar to a savanna than to the native landscape replaced. Studies of urban biomass have tended to focus on one type of vegetation (e.g., lawns or trees). Yet a focus on the ecology of the city should include the entire urban ecosystem rather than the separate investigation of its parts. Furthermore, few studies have attempted to measure urban aboveground NPP (ANPP) using field-based methods. Most studies project growth rates from measurements of tree diameter to estimate annual ANPP or use remote sensing approaches. In addition, field-based methods for measuring NPP do not address any special considerations for adapting such field methods to urban landscapes. Frequent planting and partial or complete removal of herbaceous and woody plants can make it difficult to accurately quantify increments and losses of plant biomass throughout an urban landscape. In this study, we review how ANPP of urban landscapes can be estimated based on field measurements, highlighting the challenges specific to urban areas. We then estimated ANPP of woody and herbaceous vegetation over a 15-year period for Baltimore, MD, USA using a combination of plot-based field data and published values from the literature. Baltimore's citywide ANPP was estimated to be 355.8 g m-2 , a result that we then put into context through comparison with other North American Long-Term Ecological Research (LTER) sites and mean annual precipitation. We found our estimate of Baltimore citywide ANPP to be only approximately half as much (or less) than ANPP at forested LTER sites of the eastern United States, and more comparable to grassland, oldfield, desert, or boreal forest ANPP. We also found that Baltimore had low productivity for its level of precipitation. We conclude with a discussion of the significance of accurate assessment of primary productivity of urban ecosystems and critical future research needs.

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.

Grand challenges in biodiversity-ecosystem functioning research in the era of science-policy platforms require explicit consideration of feedbacks.

Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and-critically-the feedbacks among them.

Causal assumptions and causal inference in ecological experiments.

Causal inferences from experimental data are often justified based on treatment randomization. However, inferring causality from data also requires complementary causal assumptions, which have been formalized by scholars of causality but not widely discussed in ecology. While ecologists have recognized challenges to inferring causal relationships in experiments and developed solutions, they lack a general framework to identify and address them. We review four assumptions required to infer causality from experiments and provide design-based and statistically based solutions for when these assumptions are violated. We conclude that there is no clear demarcation between experimental and non-experimental designs. This insight can help ecologists design better experiments and remove barriers between experimental and observational scholarship in ecology.

Residential yard management and landscape cover affect urban bird community diversity across the continental USA.

Urbanization has a homogenizing effect on biodiversity and leads to communities with fewer native species and lower conservation value. However, few studies have explored whether or how land management by urban residents can ameliorate the deleterious effects of this homogenization on species composition. We tested the effects of local (land management) and neighborhood-scale (impervious surface and tree canopy cover) features on breeding bird diversity in six US metropolitan areas that differ in regional species pools and climate. We used a Bayesian multiregion community model to assess differences in species richness, functional guild richness, community turnover, population vulnerability, and public interest in each bird community in six land management types: two natural area park types (separate and adjacent to residential areas), two yard types with conservation features (wildlife-certified and water conservation) and two lawn-dominated yard types (high- and low-fertilizer application), and surrounding neighborhood-scale features. Species richness was higher in yards compared with parks; however, parks supported communities with high conservation scores while yards supported species of high public interest. Bird communities in all land management types were composed of primarily native species. Within yard types, species richness was strongly and positively associated with neighborhood-scale tree canopy cover and negatively associated with impervious surface. At a continental scale, community turnover between cities was lowest in yards and highest in parks. Within cities, however, turnover was lowest in high-fertilizer yards and highest in wildlife-certified yards and parks. Our results demonstrate that, across regions, preserving natural areas, minimizing impervious surfaces and increasing tree canopy are essential strategies to conserve regionally important species. However, yards, especially those managed for wildlife support diverse, heterogeneous bird communities with high public interest and potential to support species of conservation concern. Management approaches that include the preservation of protected parks, encourage wildlife-friendly yards and acknowledge how public interest in local birds can advance successful conservation in American residential landscapes.

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.

Municipal regulation of residential landscapes across US cities: Patterns and implications for landscape sustainability.

Local regulations on residential landscapes (yards and gardens) can facilitate or constrain ecosystem services and disservices in cities. To our knowledge, no studies have undertaken a comprehensive look at how municipalities regulate residential landscapes to achieve particular goals and to control management practices. Across six U.S. cities, we analyzed 156 municipal ordinances to examine regional patterns in local landscape regulations and their implications for sustainability. Specifically, we conducted content analysis to capture regulations aimed at: 1) goals pertaining to conservation and environmental management, aesthetics and nuisance avoidance, and health and wellbeing, and 2) management actions including vegetation maintenance, water and waste management, food production, and chemical inputs. Our results reveal significant variation in local and regional regulations. While regulatory goals stress stormwater management and nuisance avoidance, relatively few municipalities explicitly regulate residential yards to maintain property values, mitigate heat, or avoid allergens. Meanwhile, biological conservation and water quality protection are common goals, yet regulations on yard management practices (e.g., non-native plants or chemical inputs) sometimes contradict these purposes. In addition, regulations emphasizing aesthetics and the maintenance of vegetation, mowing of grass and weeds, as well as the removal of dead wood, may inhibit wildlife-friendly yards. As a whole, landscaping ordinances largely ignore tradeoffs between interacting goals and outcomes, thereby limiting their potential to support landscape sustainability. Recommendations therefore include coordinated, multiobjective planning through partnerships among planners, developers, researchers, and non-government entities at multiple scales.

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.

Climate and lawn management interact to control C4 plant distribution in residential lawns across seven U.S. cities.

In natural grasslands, C4 plant dominance increases with growing season temperatures and reflects distinct differences in plant growth rates and water use efficiencies of C3 vs. C4 photosynthetic pathways. However, in lawns, management decisions influence interactions between planted turfgrass and weed species, leading to some uncertainty about the degree of human vs. climatic controls on lawn species distributions. We measured herbaceous plant carbon isotope ratios (δ13 C, index of C3 /C4 relative abundance) and C4 cover in residential lawns across seven U.S. cities to determine how climate, lawn plant management, or interactions between climate and plant management influenced C4 lawn cover. We also calculated theoretical C4 carbon gain predicted by a plant physiological model as an index of expected C4 cover due to growing season climatic conditions in each city. Contrary to theoretical predictions, plant δ13 C and C4 cover in urban lawns were more strongly related to mean annual temperature than to growing season temperature. Wintertime temperatures influenced the distribution of C4 lawn turf plants, contrary to natural ecosystems where growing season temperatures primarily drive C4 distributions. C4 cover in lawns was greatest in the three warmest cities, due to an interaction between climate and homeowner plant management (e.g., planting C4 turf species) in these cities. The proportion of C4 lawn species was similar to the proportion of C4 species in the regional grass flora. However, the majority of C4 species were nonnative turf grasses, and not of regional origin. While temperature was a strong control on lawn species composition across the United States, cities differed as to whether these patterns were driven by cultivated lawn grasses vs. weedy species. In some cities, biotic interactions with weedy plants appeared to dominate, while in other cities, C4 plants were predominantly imported and cultivated. Elevated CO2 and temperature in cities can influence C3 /C4 competitive outcomes; however, this study provides evidence that climate and plant management dynamics influence biogeography and ecology of C3 /C4 plants in lawns. Their differing water and nutrient use efficiency may have substantial impacts on carbon, water, energy, and nutrient budgets across cities.

Demystifying dominant species.

The pattern of a few abundant species and many rarer species is a defining characteristic of communities worldwide. These abundant species are often referred to as dominant species. Yet, despite their importance, the term dominant species is poorly defined and often used to convey different information by different authors. Based on a review of historical and contemporary definitions we develop a synthetic definition of dominant species. This definition incorporates the relative local abundance of a species, its ubiquity across the landscape, and its impact on community and ecosystem properties. A meta-analysis of removal studies shows that the loss of species identified as dominant by authors can significantly impact ecosystem functioning and community structure. We recommend two metrics that can be used jointly to identify dominant species in a given community and provide a roadmap for future avenues of research on dominant species. In our review, we make the case that the identity and effects of dominant species on their environments are key to linking patterns of diversity to ecosystem function, including predicting impacts of species loss and other aspects of global change on ecosystems.

Change in dominance determines herbivore effects on plant biodiversity.

Herbivores alter plant biodiversity (species richness) in many of the world's ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis-that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity. Under this hypothesis, when herbivores reduce the abundance (biomass, cover) of dominant species (for example, because the dominant plant is palatable), additional resources become available to support new species, thereby increasing biodiversity. By contrast, if herbivores promote high dominance by increasing the abundance of herbivory-resistant, unpalatable species, then resource availability for other species decreases reducing biodiversity. We show that herbivore-induced change in dominance, independent of site productivity or precipitation (a proxy for productivity), is the best predictor of herbivore effects on biodiversity in grassland and savannah sites. Given that most herbaceous ecosystems are dominated by one or a few species, altering the competitive environment via herbivores or by other means may be an effective strategy for conserving biodiversity in grasslands and savannahs globally.