Drought stress constrains the productivity of terrestrial ecosystems and the distribution of plant species. To withstand drought stress, plants have evolved diverse water-use strategies. Despite the critical function of roots in whole-plant water regulation, drought strategies have been primarily studied from an aboveground perspective, and so our knowledge of how fine-root traits are related to aboveground hydraulic traits remains limited. Here, we compiled a dataset of primarily woody species comprising five aboveground plant hydraulic traits associated with water-use strategies and four fine-root traits from the root economics space (RES). We investigated how the global diversity in ecological strategies of the RES traits relates to aboveground hydraulic traits contributing to drought resistance. We found a slight trend towards acquisitive species with higher root nitrogen content and lower root tissue density having lower drought resistance in aboveground tissues. Species with thicker roots displayed a tendency towards slightly higher drought resistance than thin-rooted species. The weakness of these relationships suggests that aboveground drought adaptations are largely independent of classical axes of fine root ecological strategies, pointing to either a decoupling between aboveground and belowground responses or a stronger coordinating role for other root traits such as maximum rooting depth or root cortex fraction in hydraulic adaptation.

The realized niche captures only a fraction of the conditions in which a species can survive and reproduce, yet remains the basis for most predictions of how species respond to global change. No matter how sophisticated species distribution models have become, reliance on the realized niche biases forecasts of population persistence and range shifts. Rapid global change has turned the fundamental niche from a theoretical construct into a mission-critical objective for conservation science. Empirical tools exist to operationalize it. If we stop holding the fundamental niche to higher epistemic standards than the realized niche and treat survival and regeneration data from beyond the realized niche as genuine reflections of it, then we can advance this foundational yet surprisingly nascent research program.

Introduction Plant diversity and functional traits can improve ecosystem function in degraded plant communities, but there are gaps in our understanding of how to utilize plants to increase soil carbon (C) in the context of ecological restoration.Objectives This study explores how plants and environmental conditions interact to alter five soil C pools in restored grassland plots.Methods We seeded 35 grassland species in various combinations and subjected them to two precipitation and two land use history treatments. We assessed plant traits, species evenness, and five soil C pools across 2 years. We expected that acquisitive traits would increase microbial biomass (MBC), water-extractable organic C (WEOC), and mineral-associated organic C (MAOC) via labile tissues and root exudates, while recalcitrant tissues with opposite trait values would increase particulate organic C.Results Traits and diversity influenced several soil C pools, and relationships varied with precipitation, land use history, and year. Labile tissues had positive effects on MBC in most conditions and across multiple years, while dense roots supported MBC under wet conditions after a 1-year delay. Plant diversity positively affected MBC and MAOC in wet conditions. Land use history was the dominant predictor for all pools except the most labile (WEOC), showing that variations in plant communities and management have enduring effects on soil C.Conclusions These results demonstrate that restored plant communities contribute to soil C through disparate pathways and on various timescales, and that environmental factors mediate the relationship between plant traits and soil C following restoration.

Belowground plant trait research has predominantly focused on trade-offs in fine-root traits via the root economics space (RES). Yet, this fine-root framework captures only a fraction of the functional strategies plants employ beneath the soil surface. Here, we broaden the perspective on belowground plant functioning by integrating traits related to root system extent, clonality, and bud banks, using data from the new UNDERPLOT dataset. This integration links measurable traits to key belowground functions: resource acquisition, spatial exploration, and persistence. Our analysis shows that the fine-root economics space explains less than 5% of the variation in traits related to root system extent, clonality, and bud banks. Instead, an expanded trait analysis reveals three significant dimensions, explaining 62% of total trait variation. The third dimension represents an independent, persistence-related gradient, not captured by existing root economics frameworks. We propose that understanding belowground plant strategies requires embracing additional functional gradients. The strategy of persistence, in particular, varies significantly across growth forms and is a critical dimension of plant response to resource limitation and stress, becoming increasingly important as global change shifts disturbance regimes.

Belowground functional diversity is relevant to numerous ecosystem functions and to ecosystem resilience under global change, yet quantitative information on belowground plant traits is disparate and poorly integrated across fields of research. So far, belowground plant traits have been studied in three disparate research domains: (i) fine root traits in the context of belowground resource economics and symbioses; (ii) maximum rooting depth and lateral extent of the root system in the context of overall plant allometry and resource uptake; (iii) clonal organs and bud banks with a focus on plant and community resilience. However, there remains a major disconnection among these three fields of research. A prerequisite for linking them together is the creation of a comprehensive, curated, open-access dataset available for comprehensive analyses. Here, we compiled and harmonised such a trait dataset for 10,453 vascular plant species and 19 belowground plant traits, which we named UNDERPLOT. Based on these data, we defined two integrative indices, a Belowground Persistence Type (BPT) and a Clonal Spread Index (CSI), which are suitable trait-based indicators for predicting resistance and resilience of communities to disturbance. Further applications will increase our knowledge of the dimensionality of the belowground trait space, adding new insights into trait-environment relationships, vegetation responses to climate change and disturbance, as well as a deeper understanding of evolutionary first principles.

Understanding the drivers of plant community stability is crucial for predicting ecosystem responses to extreme drought events. In grasslands, drought resistance supports the maintenance of key functions such as above-ground primary productivity, making the identification of resistance drivers essential to guide management under climate change. Proposed factors contributing to grassland stability include multiple diversity facets, functional traits and long-term climate, but most assessments focus on temporal invariability under historical disturbance regimes, leaving mechanisms of extreme drought resistance and their variation across climatic contexts relatively underexplored. Here, we analysed data from 54 grassland sites of the International Drought Experiment to examine the resistance of above-ground net primary productivity to a short-term (i.e. 1 year) extreme drought. We investigated the relative importance and joint influence of functional composition (i.e. community-weighted means of leaf and root traits), plant diversity facets (taxonomic, functional and phylogenetic) and climate (aridity and rainfall variability) on drought resistance. We used structural equation models to disentangle direct, indirect, and moderating pathways linking these drivers to drought resistance. Long-term aridity appeared as one of the most important drivers of grassland resistance to drought, with more arid sites showing lower resistance. Moreover, aridity impacted resistance through indirect effects by shaping functional composition and plant diversity, and by moderating the influence of plant diversity and functional composition. Functional composition related to dehydration avoidance and dehydration tolerance was also positively associated with resistance, while diversity had a weaker relationship with resistance, mostly through functional and phylogenetic facets. Interannual rainfall variability also influenced resistance, with different effects in more arid versus humid and less arid sites. Synthesis. Widely studied stability drivers such as plant diversity and functional composition have only partial explanatory power for short-term drought resistance of above-ground productivity in grasslands at a global scale. The abiotic context, particularly long-term aridity, is crucial for understanding ecosystem responses to rainfall variation and can improve predictive models for advancing the study of ecosystem resistance to drought. Along with management practices that target high species diversity or specific traits, restoration and conservation practices should support vulnerable sites experiencing high aridity Compreender os fatores que determinam a estabilidade de comunidades vegetais & eacute; fundamental para prever as respostas dos ecossistemas a eventos de seca extrema. Em ecossistemas dominados por gram & iacute;neas, a resist & ecirc;ncia & agrave; seca & eacute; importante para a manuten & ccedil;& atilde;o de fun & ccedil;& otilde;es como a produtividade prim & aacute;ria a & eacute;rea. Assim, identificar os fatores que promovem essa resist & ecirc;ncia & eacute; crucial para orientar o manejo em um cen & aacute;rio de mudan & ccedil;as clim & aacute;ticas. Entre os principais determinantes da estabilidade em sistemas dominados por gram & iacute;neas est & atilde;o diferentes facetas da diversidade, atributos funcionais das esp & eacute;cies e o clima. No entanto, a maioria dos estudo foca na invariabilidade temporal sob regimes hist & oacute;ricos de dist & uacute;rbio, enquanto os mecanismos de resist & ecirc;ncia & agrave; seca extrema e a sua varia & ccedil;& atilde;o ao longo de gradientes clim & aacute;ticos permanecem relativamente pouco explorados. Neste estudo, analisamos dados de 54 s & iacute;tios do Experimento Internacional de Seca para avaliar a resist & ecirc;ncia da produtividade prim & aacute;ria l & iacute;quida a & eacute;rea a uma seca extrema de curta dura & ccedil;& atilde;o (um ano). Investigamos a import & acirc;ncia relativa e os efeitos conjuntos da composi & ccedil;& atilde;o funcional (isto & eacute;, m & eacute;dias ponderadas da comunidade de atributos funcionais de folhas e ra & iacute;zes), de diferentes facetas da diversidade de plantas (taxon & ocirc;mica, funcional e filogen & eacute;tica) e do clima (aridez e variabilidade interanual da precipita & ccedil;& atilde;o) sobre a resist & ecirc;ncia & agrave; seca. Usamos modelos de equa & ccedil;& otilde;es estruturais para discriminar os efeitos diretos, indiretos e de modera & ccedil;& atilde;o que conectam esses fatores & agrave; resist & ecirc;ncia & agrave; seca. A aridez destacou-se como um dos principais fatores geradores de resist & ecirc;ncia & agrave; seca, com locais mais & aacute;ridos apresentando menor resist & ecirc;ncia. Al & eacute;m disso, a aridez tamb & eacute;m influenciou a resist & ecirc;ncia de forma indireta, ao afetar a composi & ccedil;& atilde;o funcional e a diversidade de plantas, al & eacute;m de moderar a efeito da diversidade de plantas e da composi & ccedil;& atilde;o funcional na resist & ecirc;ncia. A composi & ccedil;& atilde;o funcional associada a estrat & eacute;gias de evita & ccedil;& atilde;o e toler & acirc;ncia & agrave; desidrata & ccedil;& atilde;o tamb & eacute;m apresentou rela & ccedil;& atilde;o positiva com a resist & ecirc;ncia, enquanto a diversidade de plantas mostrou associa & ccedil;& atilde;o mais fraca, contribuindo principalmente por meio das facetas funcionais e filogen & eacute;ticas. A variabilidade interanual da precipita & ccedil;& atilde;o tamb & eacute;m influenciou a resist & ecirc;ncia, com efeitos distintos entre locais mais & aacute;ridos e locais h & uacute;midos ou menos & aacute;ridos S & iacute;ntese. Fatores amplamente estudados como determinantes da estabilidade, como a diversidade das plantas e a composi & ccedil;& atilde;o funcional, explicam apenas parcialmente a resist & ecirc;ncia da produtividade a & eacute;rea a secas de curta dura & ccedil;& atilde;o em ecossistemas dominados por gram & iacute;n Em conjunto com pr & aacute;ticas de manejo voltados ao aumento da diversidade de esp & eacute;cies ou & agrave; promo & ccedil;& atilde;o de determinados atributos funcionais, a & ccedil;& otilde;es de restaura & ccedil;& atilde;o e conserva & ccedil;& atilde;o devem focar em & aacute;reas mais vulner & aacute;veis sob maior aridez.

Predicting which non-native plant species will become established and where is critical for conserving and managing biodiversity. Theory suggests that the mycorrhizal strategy of non-native plants may predict their establishment success. Here we combine a global dataset of 440,788 vegetation plots with data on plant native status and mycorrhizal type to assess mycorrhizal strategy of non-native plants. The mycorrhizal strategy of non-native plants varies strongly across biomes. Across grassland and desert biomes, non-native species are more frequently non-mycorrhizal than native species, whereas in other biomes non-native species are more likely to be mycorrhizal, most commonly arbuscular-mycorrhizal. Disturbance type and intensity are key predictors of mycorrhizal strategy of non-native species, as mycorrhizal species are favoured by landscape modification and non-mycorrhizal species by natural and human-caused disturbance events. Facultatively mycorrhizal species are consistently under-represented among non-native plants compared with natives, suggesting that symbiotic flexibility does not confer an advantage for non-natives as previously expected. Our study shows that non-native mycorrhizal strategy varies across biogeographical contexts and disturbance, highlighting the need for region-specific prevention and management approaches to plant species introductions.

A fundamental question in ecology is why plant communities have large trait space yet strong coordination among those traits across large scales, despite these patterns seeming contradictory. Answering this question requires quantitatively linking the geographic distribution of trait space and coordination with gross primary productivity (GPP). We leveraged an unprecedented large-scale dataset of nine leaf traits for 5718 species-site combinations with simultaneous field measurements of plant community composition in 64 naturally assembled communities to investigate trait spaces (hypervolume, quantity dimension) and trait compactness (coordination, efficiency dimension) and their influence on GPP. Trait space and compactness combined explained 72% of the variation of GPP. Interestingly, a larger trait space (more diverse trait combinations) drove higher GPP in resource-poor communities, while higher trait compactness (greater coordination of traits) determined higher GPP in resource-rich communities. Our findings provide a new perspective that natural plant communities increase both trait space and compactness to improve GPP, shedding light on the development of multidimensional functional ecology.

Drought and invasive species are threats to primary productivity in grassland ecosystems worldwide. A central challenge in ecological restoration is establishing plant communities that can withstand these abiotic and biotic stressors. We tested the efficacy of a trait-based framework for enhancing drought tolerance and invasion resistance in experimental restorations of contrasting grassland systems, a perennial mixed-grass prairie in Wyoming and annual interior grassland in California. Each experiment included four trait-based seeding treatments: drought tolerant, invasion resistant, functionally diverse, and a random control. All seeded communities were subjected to extreme precipitation reduction (-50% annual) and invasion by non-native annual grasses. We asked two questions: (1) Can we establish communities from seed that meet and maintain these desired trait-based targets? (2) Did the trait-based seeding treatments tolerate extreme precipitation reduction or resist invasion by non-native annual grasses? Based on analyses of compositional dissimilarities, we found trait-based restoration targets were more difficult to maintain in an annual-dominant grassland rather than in a perennial-dominant one, and targets composed of multiple community-weighted mean traits were more difficult to meet than targets that maximized functional diversity. In both grasslands, plant communities with drought-tolerant traits maintained growth rates under reduced precipitation, but these effects diminished after multiple years of drought and during drought release. This highlights the importance of including a diversity of strategies when restoring plant communities. Our proposed invasion-resistant traits did not consistently reduce non-native annual grass establishment, but communities with traits that conferred drought tolerance were the most effective at resisting invasion, suggesting that similar traits enhance drought tolerance and resist invasion in these grasslands. Our findings indicate that restored plant communities with high functional diversity may be able to respond to variable conditions better than communities with traits designed to meet specific restoration objectives. The results from this restoration experiment suggest that our understanding of the traits underlying drought tolerance is better than our understanding of the traits underlying invasion resistance. However, if drought tolerance enhances competitive ability in arid and semiarid grassland ecosystems, then physiological theories of resource use can be applied to enhance invasion resistance.

The proliferation of high-dimensional data in ecology and evolutionary biology raises the promise of statistical and machine learning models that are highly predictive and interpretable. However, high-dimensional data are commonly burdened with an inherent trade-off: in-sample prediction of outcomes will improve as additional variables are included in the model, but this may come at the cost of poor predictive accuracy and limited generalizability for future or unsampled observations (out-of-sample prediction). To confront this problem of overfitting, sparse models can focus on key variables by correctly placing low weight on unimportant variables. We compared nine methods to quantify their performance in variable selection and prediction using simulated data with different sample sizes, numbers of variables, and strengths of effects. Overfitting was typical for many methods and simulation scenarios. Despite this, in-sample and out-of-sample prediction converged on the true predictive target for simulations with more observations, larger causal effects, and fewer variables. Accurate variable selection to support process-based understanding will be unattainable for many realistic sampling schemes in ecology and evolution. We use our analyses to characterize data attributes for which statistical learning is possible, and illustrate how some sparse methods can achieve predictive accuracy while mitigating and learning the extent of overfitting.

Introduction Threats such as land use change and non-native plant invasion continually threaten sagebrush steppe ecosystem integrity, prompting widespread interest in habitat restoration and conservation. Unfortunately, sagebrush steppe restoration is unpredictable, making it challenging to identify management strategies that maximize species diversity, minimize invasion, and promote optimum shrub establishment, including Mountain big sagebrush (Artemisia tridentata) and Antelope bitterbrush (Purshia tridentata). Grand Teton National Park is restoring 4500 acres of degraded Smooth brome (Bromus inermis) hayfields to native sagebrush steppe and has observed poor shrub establishment and occasional native grass dominance.Objectives We established a 2 & times; 2 factorial randomized block field experiment to test the effects of seed mix design and planting method on shrub recruitment, species diversity, and composition.Methods Seed mix design differed in grass and forb proportions. Planting method included tillage and sowing combinations: no-till plots were drill-seeded, and till plots broadcast-seeded.Results A. tridentata establishment was highest in no-till plots with a drill-seeded grass-heavy seed mix, while P. tridentata establishment was highest in till plots with a broadcast-seeded grass-heavy seed mix. Species diversity and invasive species did not differ across treatments.Conclusions These results identify a key trade-off between planting methods, suggesting that landscape-scale diversity of early restoration outcomes for A. tridentata, P. tridentata, and herbaceous composition can be optimized with varied planting methods.

Humans are driving biodiversity change, which also alters community functional traits. However, how changes in the functional traits of the community alter ecosystem functions-especially belowground-remains an important gap in our understanding of the consequences of biodiversity change. We test hypotheses for how the root traits of the root economics space (composed of the collaboration and conservation gradients) are associated with proxies for ecosystem functioning across grassland and forest ecosystems in both observational and experimental datasets from 810 plant communities. First, we assessed whether community-weighted means of the root economics space traits adhered to the same trade-offs as species-level root traits. Then, we examined the relationships between community-weighted mean root traits and aboveground biomass production, root standing biomass, soil fauna biomass, soil microbial biomass, decomposition of standard and plot-specific material, ammonification, nitrification, phosphatase activity, and drought resistance. We found evidence for a community collaboration gradient but not for a community conservation gradient. Yet, links between community root traits and ecosystem functions were more common than we expected, especially for aboveground biomass, microbial biomass, and decomposition. These findings suggest that changes in species composition, which alter root trait means, will in turn affect critical ecosystem functions.

PREMISE:Relationships between flammability and drought tolerance influence vegetation dynamics during fires. A goal of the emerging subdiscipline of pyro-ecophysiology is to identify ecophysiological traits that determine live fuel flammability, but empirical studies of these relationships are rare. Furthermore, drought tolerance has been suggested as a surrogate for low flammability when choosing species to plant near houses in fire-prone areas, but this hypothesis has not been tested. METHODS:We examined links between flammability and drought tolerance for 39 woody species, compiling existing data on shoot flammability and six drought-related variables: minimum leaf water potential (Ψmin; N = 15 species), leaf turgor loss point (πtlp; N = 20), root zone water deficits (N = 19), days to plant death (N = 14), xylem embolism resistance (P50; N = 20), and wood density (WD; N = 20). RESULTS:Drought-tolerant species did not have low shoot flammability, except for a negative relationship between ignition percentage and WD, and then only for conifers. In contrast, there were significant negative relationships between four of five shoot flammability variables and either or both Ψmin and πtlp, showing that the most drought-tolerant species were also the most flammable. Ψmin and πtlp were positively associated with leaf water status, producing higher correlations with shoot flammability than other drought-response indicators. CONCLUSIONS:Pyro-ecophysiological traits, e.g. Ψmin and πtlp, are useful predictors of interspecific variation in live fuel flammability, showing how pyro-ecophysiology can provide insights into how plants might respond to a more drought- and fire-prone future.

Are non-native plants abundant because they are non-native, and have advantages over native plants, or because they possess 'fast' resource strategies, and have advantages in disturbed environments? This question is central to invasion biology but remains unanswered. We quantified the relative importance of resource strategy and biogeographic origin in 69 441 plots across the conterminous United States containing 11 280 plant species. Non-native species had faster economic traits than native species in most plant communities (77%, 86% and 82% of plots for leaf nitrogen concentration, specific leaf area, and leaf dry matter content). Non-native species also had distinct patterns of abundance, but these were not explained by their fast traits. Compared with functionally similar native species, non-native species were (1) more abundant in plains and deserts, indicating the importance of biogeographic origin, and less abundant in forested ecoregions, (2) were more abundant where co-occurring species had fast traits, for example due to disturbance, and (3) showed weaker signals of local environmental filtering. These results clarify the nature of plant invasion: Although non-native plants have consistently fast economic traits, other novel characteristics and processes likely explain their abundance and, therefore, impacts.

Aim: Beta diversity quantifies the similarity of ecological assemblages. Its increase, known as biotic homogenisation, can be a consequence of biological invasions. However, species occurrence (presence/absence) and abundance-based analyses can produce contradictory assessments of the magnitude and direction of changes in beta diversity. Previous work indicates these contradictions should be less frequent in nature than in theory, but a growing number of empirical studies report discrepancies between occurrence- and abundance-based approaches. Understanding if these discrepancies represent a few isolated cases or are systematic across a diversity of ecosystems would allow us to better understand the general patterns, mechanisms and impacts of biotic homogenisation. Location: United States. Time Period: 1963-2020. Major Taxa Studied: Vascular plants. Methods: We used a dataset of more than 70,000 vegetation survey plots to assess differences in biotic homogenisation with and without invasion using both occurrence- and abundance-based metrics of beta diversity. We estimated taxonomic biotic homogenisation by comparing beta diversity of invaded and uninvaded plots with both classes of metrics and investigated the characteristics of the non-native species pool that influenced the likelihood that these metrics disagree. Results: In 78% of plot comparisons, occurrence- and abundance-based calculations agreed in direction, and the two metrics were generally well correlated. Our empirical results are consistent with previous theory. Discrepancies between the metrics were more likely when the same non-native species was at high cover at both plots compared for beta diversity, and when these plots were spatially distant. Main Conclusions: In about 20% of cases, our calculations revealed differences in direction (homogenisation vs. differentiation) when comparing occurrence- and abundance-based metrics, indicating that the metrics are not interchangeable, especially when distances between plots are high and invader diversity is low. When data permit, combining the two approaches can offer insights into the role of invasions and extirpations in driving biotic homogenisation/differentiation.

Many recent studies have explored remote sensing approaches to facilitate non‐destructive sampling of aboveground biomass (AGB). Lidar platforms (e.g., iPhone and iPad PRO models) have recently made remote sensing technologies widely available and present an alternative to traditional approaches for estimating AGB. Lidar approaches can be completed within a fraction of the time required by many analog methods. However, it is unknown if handheld sensors are capable of accurately predicting AGB or how different modeling techniques affect prediction accuracy. Here, we collected AGB from 0.25‐m 2 plots ( N = 45) from three sites along an elevational gradient within rangelands surrounding Flagstaff, Arizona, USA. Each plot was scanned with a mobile laser scanner (MLS) and iPad before plants were clipped, dried, and weighed. We compared the capability of iPad and MLS sensors to estimate AGB via minimization of model normalized root mean square error (NRMSE). This process was performed on predictor subsets describing structural, spectral, and field‐based characteristics across a suite of modeling approaches including simple linear, stepwise, lasso, and random forest regression. We found that models developed from MLS and iPad data were equally capable of predicting AGB (NRMSE 26.6% and 29.3%, respectively) regardless of the variable subsets considered. We also found that stepwise regression regularly resulted in the lowest NRMSE. Structural variables were consistently selected during each modeling approach, while spectral variables were rarely included. Field‐based variables were important in linear regression models but were not included after variable selection within random forest models. These findings support the notion that remote sensing techniques offer a valid alternative to analog field‐based data collection methods. Together, our results demonstrate that data collected using a more widely available platform will perform similarly to a more costly option and outline a workflow for modeling AGB using remote sensing systems alone.

Despite recent advances in plant trait ecology, we identified a knowledge gap in understanding how plants strategize to cope with severe and recurrent disturbances. Here, we propose a new classification system based on three hierarchical binary attributes: woodiness, reflecting longevity of plant structures; clonality, indicating the ability to regenerate from both above- and belowground organs; and resprouting ability, referring to the ability to replace aboveground organs. This framework results in six Belowground Persistence Types (BPTs): 1, herbaceous seeder; 2, herbaceous non-clonal resprouter; 3, herbaceous clonal resprouter; 4, woody seeder; 5, woody non-clonal resprouter; and 6, woody clonal resprouter. This proposed classification system opens new avenues for research, especially concerning plant distributions in a world experiencing increasingly frequent and severe disturbance events.

Increased variability in precipitation associated with climate change creates extreme conditions of drought and deluge that can have profound effects on the abundance and composition of plant communities. Responses to these extremes likely vary across climatic gradients and depend on local plant community composition, which includes the emergent, aboveground vegetation as well as belowground seed banks. Because seed banks can both buffer the effects of environmental change and influence the future trajectories of communities, it is critical to understand seed bank responses to precipitation extremes in relation to the aboveground vegetation and how patterns vary across environmental gradients. Here we quantified the responses of aboveground and seed bank communities at five perennial grass-dominated sites across an elevational gradient to 6 years of extreme drought and deluge, by implementing experimental water exclusion and water addition treatments. Responses were stronger for drought than for deluge. Drought decreased abundance aboveground, while seed bank abundances were generally unaffected. Similarly, drought decreased richness and diversity of aboveground vegetation at intermediate elevations, without concurrent changes in seed banks. Surprisingly, the lowest and middle elevation sites showed stronger shifts in functional composition and dissimilarity in response to treatments, despite the expectation of greater buffering in seed banks in more arid environments. The relatively attenuated responses of seed bank communities to drought and deluge suggest potential for resistance and recovery, though species and functional composition may show greater responses to change particularly in more arid, lower elevation sites.