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Disturbances are ubiquitous in ecological systems, and species have evolved a range of strategies to resist or rebound following disturbance. Understanding how the presence and complementarity of regeneration traits will affect community responses to disturbance is increasingly urgent as disturbance regimes shift beyond their historical ranges of variability. We define "disturbance niche" as a species' fitness across a range of disturbance sizes and frequencies that can reflect the fundamental or realized niche, that is, whether the species occurs alone or with other species. We developed a model of intermediate complexity (i.e., a Goldilocks model) to infer the disturbance niche. We parameterized the model for subalpine forests in Yellowstone National Park (USA) adapted to infrequent stand‐replacing fires and included the three major tree‐regeneration strategies: (1) obligate seeders that rely on ex situ seeding into burned areas (non‐serotinous lodgepole pine, Pinus contorta var. latifola), (2) obligate seeders that depend on in situ seedbanks (serotinous lodgepole pine, Pinus contorta var. latifola), and (3) species that can resprout from surviving roots following fire (quaking aspen, Populus tremuloides). Our results showed which regeneration strategies increase or decrease in prevalence as fire rotation declines. Non‐serotinous pines were extirpated when fire rotation was below 50 years in a monoculture and 100 years in a mixed forest; serotinous pines were extirpated when fire rotation was below 20 years; and aspen was extirpated when fire rotation fell below 6 years. The fundamental and realized disturbance niches pinpointed the key mechanisms limiting regeneration for each strategy, namely, increasing fire size for non‐serotinous pine (ex situ seeders), decreasing fire frequency for serotinous pine (in situ seeders), and interspecific competition for aspen (resprouters). In a mixed forest, the three regeneration strategies were complementary and each dominated at different combinations of fire size and frequency. Consequently, diversity of regeneration strategies enhanced forest resilience to declining fire rotations. Despite its simplicity, our Goldilocks model produced realistic dynamics and could be readily adapted to other disturbance‐prone ecosystems to explore the generality of these results. The disturbance niche is a key concept for anticipating community resilience to changing disturbance regimes. [ABSTRACT FROM AUTHOR]

Questions: Climate extremes are predicted to become more common in many ecosystems. Climate extremes can promote and interact with disturbances, but the combined effects of climate extremes and disturbances have not been quantified in many ecosystems. In this study, we ask whether the dual impact of a climate extreme and concomitant disturbance (wildfire) has a greater affect than a climate extreme alone. Location: Tallgrass prairie in the Konza Prairie Biological Station, northeastern Kansas, USA. Methods: We quantified the response of a tallgrass prairie plant community to a 2‐year climate extreme of low growing‐season precipitation and high temperatures. In the first year of the climate extreme, a subset of plots was burned by a growing‐season wildfire. This natural experiment allowed us to compare community responses to a climate extreme with and without wildfire. Results: In plots exposed to the climate extreme but not wildfire, community structure, diversity, and composition showed minor to insignificant changes, such as a 20% reduction in grass cover and a slight increase in species diversity. Plots exposed to both the climate extreme and wildfire underwent larger changes, including an 80% reduction in grass cover, 50% increase in forb cover, and increased plant diversity. Two years after the climate extreme, structural shifts in burned plots showed little sign of recovery, indicating a potentially lasting shift in plant community structure. Conclusions: Our results suggest that community responses to climate extremes need to account for climate‐related disturbances — in this case, high temperatures, drought and wildfire. This response diverged from our expectation that heat, drought, and an additional fire would favor grasses. Although growing‐season wildfires in tallgrass prairie have been rare in recent decades, they will likely become more common with climate change, potentially leading to changes in grassland structure. [ABSTRACT FROM AUTHOR]

Abstract Many ecosystems have abruptly changed in the past and may again in the future, yet prediction and inference of mechanisms causing abrupt changes remains challenging. Critical transitions are one such mechanism, occurring when systems with alternative states cross a threshold. Such transitions are associated with a loss of resilience, often signaled by increasing variability or autocorrelation over time. However, critical transitions are difficult to distinguish from other causal mechanisms, and detection of resilience loss in sedimentary archives can be confounded by time-averaging and discontinuous sampling. Here, we simulate woodland-grassland regime shifts resulting from critical transitions and other mechanisms. We then test the diagnostic ability of two widely-used resilience indicators, standard deviation and autocorrelation time, after alterations common in sedimentary records: time averaging, discontinuous sampling, and varying sedimentation rates. Standard deviation—but not autocorrelation time—still distinguishes gradually forced critical transitions from other regime shifts when sedimentation rates are constant, and can be robust to abrupt changes in sedimentation rate. Unfortunately, shifts in standard deviation alone are rarely definitive evidence of critical transitions. Under exponential sedimentation regimes, which are common in younger upper-column sediments, neither resilience indicator is effective. Discontinuous sampling weakened the strength of resilience indicators. A demonstrative analysis of abrupt early Holocene deforestation recorded at Steel Lake, Minnesota showed signals consistent with resilience loss during early Holocene aridification. Hence, signals of resilience loss can be recovered from sedimentary archives, but efficacy varies among indicators and sedimentation regime. High-resolution and multi-proxy records remain essential to inferring causes, while process-based time series modeling such as this can be calibrated to systems of interest to explicitly test hypotheses about abrupt change causes. Highlights • Sedimentation and sampling can obscure signals of resilience loss in paleoecological records. • Standard deviation is a robust resilience indicator under most sedimentation and sampling scenarios. • Autocorrelation time is not an effective resilience indicator for sedimentary records. • Neither resilience indicator is effective when sedimentation is exponential. • Discontinuous sampling weakens or eliminates indicators of resilience loss. [ABSTRACT FROM AUTHOR]

Abrupt ecological changes are, by definition, those that occur over short periods of time relative to typical rates of change for a given ecosystem. The potential for such changes is growing due to anthropogenic pressures, which challenges the resilience of societies and ecosystems. Abrupt ecological changes are difficult to diagnose because they can arise from a variety of circumstances, including rapid changes in external drivers (e.g., climate, or resource extraction), nonlinear responses to gradual changes in drivers, and interactions among multiple drivers and disturbances. We synthesize strategies for identifying causes of abrupt ecological change and highlight instances where abrupt changes are likely. Diagnosing abrupt changes and inferring causation are increasingly important as society seek to adapt to rapid, multifaceted environmental changes. [ABSTRACT FROM AUTHOR]

Savannas are characterized by the coexistence of trees and flammable grasses. Yet, tree-grass coexistence has been labeled as paradoxical-how do these two functional groups coexist over such an extensive area, despite being generally predisposed to excluding each other? For instance, many trees develop dense canopies that limit grass growth, and many grasses facilitate frequent/intense fires, increasing tree mortality. This study revisits tree-grass coexistence with a model of hierarchical competition between pyrogenic grasses, 'forest trees' adapted to closed-canopy competition, and 'savanna trees' that are inferior competitors in closed-canopy communities, but more resistant to fire. The assumptions of this model are supported by empirical observations, including a systematic review of savanna and forest tree community composition reported here. In general, the model simulations show that when savanna trees exert weaker competitive effects on grasses, a self-reinforcing grass community is maintained, which limits forest tree expansion while still allowing savanna trees to persist (albeit as a subdominant to grasses). When savanna trees exert strong competitive effects on grasses, savanna trees cover increases initially, but as grasses decline their inhibitory effect on forest trees weakens, allowing forest trees to expand and exclude grasses and savanna trees. Rather than paradoxical, these results suggest that having weaker competitive effects on grasses may be advantageous for savanna trees, leading to greater long-term abundance and stability. We label this the 'enemy of my enemy hypothesis,' which might apply to species coexistence in communities defined by hierarchical competition or with species capable of generating strong ecological feedbacks. [ABSTRACT FROM AUTHOR]

Regime shifts are difficult-to-reverse transitions that occur when an ecosystem reorganizes around a new set of self-reinforcing feedbacks. Regime shifts are predicted to occur when the intensity of some exogenous driver variable, such as temperature, annual harvest rate, or nutrient addition rate, gradually approaches and crosses a threshold value, initiating a transition to an alternative state. However, many driver variables now change rapidly as presses or pulses, not gradually, requiring new conceptual frameworks for understanding and predicting regime shifts. We argue that identifying and controlling regime shifts in response to presses and pulses will require a greater focus on the duration, not just the intensity, of changes in driver variables. In ecosystems with slower dynamics, transitions to an alternative state can take years to decades and as a result, a driver press with an intensity capable of resulting in a regime shift over long time spans may fail to cause a regime shift when applied for shorter durations. We illustrate these ideas using simulations of local-scale alternative stable state models and preliminary evidence from long-term grazing and eutrophication experiments. The simulations also suggest that small changes in the duration of driver presses or pulses can determine whether an ecosystem recovers to its original state. These insights may extend to larger scales. In spatially extended simulations that included patchiness, spatial heterogeneity, and spatial connectivity, all patches recovered to their original state after shorter presses. However, once press duration exceeded a threshold, growing proportions of the landscape shifted to an alternative state as press duration increased. We observed similar patchy transitions in a catchment-scale experiment that reinstated frequent fires approximately halfway through a regime shift from grassland to shrubland, initiated by fire suppression. In both the local- and larger-scale models, the threshold duration needed to elicit regime shifts decreased as press intensity increased or when factors counteracting regime shifts weakened. These multiple lines of evidence suggest that conceptualizing regime shifts as an interactive function of the intensity and duration of driver changes will increase understanding of the varying effects of driver presses, pulses, and cycles on ecosystem dynamics. [ABSTRACT FROM AUTHOR]

State transitions are changes in ecosystem structure and self-reinforcing feedbacks that are initiated when an exogenous driver variable crosses a threshold. Reversing state transitions is difficult and costly. While some state transitions are relatively rapid, many take years to decades. Outside of theoretical models, very little is known about slower state transitions and how they unfold in time and space., We quantified changes in spatial variance as a mesic grassland ecosystem shifts to a shrub-dominated state, using long-term experiments and simulations that maintain grasslands with annual fires or initiate a state transition to shrub dominance by decreasing fire frequency., In the experiments, the susceptibility to state transitions varied substantially in space. In the less frequent fire treatment, some plots became shrub-dominated around year 20 and grass extirpations began in year 25, but a third of the plots were still grass-dominated in year 37. Variable rates of state transition resulted in increasing spatial variance of grass cover over time, whereas shrub cover variance decreased. In the annually burned treatment, grasses remained dominant and the spatial variance of grass cover declined., In a separate experiment, less frequent fires were maintained for 23 years and then switched to annual fires. The switch to annual fires occurred shortly after grass variance started to increase and a majority of these plots quickly returned to a grass dominated state., In simulations, spatial variance remained low and average grass cover was high under frequent fires. If fire frequency decreased below a threshold, the ecosystem transitioned to shrubland, with a transient increase in the spatial variance of grass cover during the transition between states., Synthesis. Spatial variability in the rate and susceptibility to state transitions is indicative of a system with a patchy spatial structure, high spatial heterogeneity and low connectivity between patches. Increases in spatial variance can serve as an indication that some patches have begun a state transition and that management interventions are needed to avoid widespread transitions. This is one of the first empirical examples where altering management after an increase in spatial variance prevented state transitions. [ABSTRACT FROM AUTHOR]

Winter climate is expected to change under future climate scenarios, yet the majority of winter ecology research is focused in cold-climate ecosystems. In many temperate systems, it is unclear how winter climate relates to biotic responses during the growing season. The objective of this study was to examine how winter weather relates to plant and animal communities in a variety of terrestrial ecosystems ranging from warm deserts to alpine tundra. Specifically, we examined the association between winter weather and plant phenology, plant species richness, consumer abundance, and consumer richness in 11 terrestrial ecosystems associated with the U.S. Long-Term Ecological Research ( LTER) Network. To varying degrees, winter precipitation and temperature were correlated with all biotic response variables. Bud break was tightly aligned with end of winter temperatures. For half the sites, winter weather was a better predictor of plant species richness than growing season weather. Warmer winters were correlated with lower consumer abundances in both temperate and alpine systems. Our findings suggest winter weather may have a strong influence on biotic activity during the growing season and should be considered in future studies investigating the effects of climate change on both alpine and temperate systems. [ABSTRACT FROM AUTHOR]

This review synthesizes evidence that altered fire frequency drives discontinuous ecosystem transitions from mesic grasslands to shrublands or woodlands in the Central Great Plains, USA., Long-term fire manipulations reveal that grassland to shrubland transitions are triggered when fire-free intervals increase from 1-3 years to ≥ 3-8 years, and longer fire returns (˜10 years or more) result in transitions to woodlands. Grazing and soil properties alter these fire thresholds., Grassland to shrubland transitions are abrupt and exhibit nonlinear relationships between driver and state variables. Transitions to shrublands and woodlands exhibit hysteresis, where reintroducing frequent fires does not reverse transitions in management-relevant time-scales (decades)., Nonlinear transitions and hysteresis emerge because grasses generate positive feedbacks with fire that create strong demographic barriers for shrub and tree establishment. Fire-free intervals allow shrubs and trees to reach a size sufficient to survive fire, reproduce and disrupt the fire feedback loop through competition., Synthesis. Mesic grasslands, shrublands and woodlands constitute self-reinforcing states (alternative attractors) separated by critical fire frequency thresholds. Even without major shifts in climate, altered fire frequency can produce dramatic state changes, highlighting the importance of fire for predicting future ecosystem states. Local management should focus on prevention of unwanted transitions rather than post hoc restoration. [ABSTRACT FROM AUTHOR]

Ecosystems with alternative attractors are susceptible to abrupt regime shifts that are often difficult to predict and reverse. In this study, we quantify multiple system dynamics to determine whether the transition of mesic grassland to shrubland, a widespread phenomenon, represents a linear reversible process, a nonlinear but reversible threshold process, or a transition between alternative attractors that is nonlinear and prone to hysteresis. Using a 28-yr data set with annual resolution and extensive spatial replication, we found that shrub cover is correlated with distinct thresholds of fire and C4 grass cover, resulting in temporal bimodality of shrub cover and abrupt shifts of shrub cover despite gradual changes in grass cover. These abrupt increases in shrub cover are the most rapid ever reported in grasslands, and illustrate internal thresholds that separate grasslands and shrublands. Nonlinear transitions from low to high shrub cover were also closely associated with positive feedback mechanisms that alter fire and competition (r² = 0.65), suggesting that grasslands and shrublands could show hysteresis, and by definition exist as alternative attractors. Thus, the response of this ecosystem to anthropogenic activity should tend to be rapid, nonlinear, and perhaps difficult to reverse. Regime shifts in this mesic grassland were predictable: we found that grassland and shrubland attractors were differentiated by critical thresholds of ~50-70% grass cover, 5-10% shrub cover, and a fire return interval of ~3 yr. These thresholds may provide adaptive potential for managing nonlinear behavior in socio-ecological systems in a changing environment. [ABSTRACT FROM AUTHOR]

• The accuracy of indirect LAI measurements was evaluated in dense shrub canopies. • Indirect methods were compared against direct LAI measurements. • Ceptometer was accurate in non-browsed canopies but overestimated browsed canopies. • The NEON airborne observatory platform spectral LAI underestimated LAI of canopies. • A handheld 3D scanner had high precision but underestimated large leaf area values. Leaf area index (LAI) is a key variable describing ecosystem structure and influencing the exchange of carbon, water, and energy. LAI is often evaluated with indirect methods. However, the accuracy of indirect measurements can vary with canopy structure and is not always generalizable across ecosystems. Previous research has characterized the accuracy of indirect methods for woody plants in forest ecosystems, but it is not well established for woody plants in open ecosystems—despite having large differences in canopy structure. In this study, we compared direct LAI measurements in clonal grassland shrub canopies to three indirect methods: a ceptometer, a handheld 3D scanner (processed using EXScanPro-3.6 software), and NEON's LAI product obtained from airborne hyperspectral imaging (derived from SAVI). To our knowledge, this is the first study to assess the accuracy of leaf area data in woody plants using a handheld 3D scanner and one of few studies assessing the accuracy of the National Ecological Observation Network's (NEON) Airborne Observation Platform—our source of airborne hyperspectral imaging. Data were collected in tallgrass prairie undergoing woody encroachment and three treatments: no herbivore disturbance, bison present, and simulated browsing. We found that direct LAI measurements of control and grazed C. drummondii canopies averaged ∼8.0. The ceptometer accurately estimated LAI in non-browsed canopies but overestimated LAI of browsed canopies by 38 %. One-sided leaf area of ramets measured with a handheld 3D scanner was strongly related to direct measurements (r2=0.86), but underestimated leaf area at greater values. LAI estimated from airborne spectral data underestimated LAI by 55 %. We conclude that a ceptometer was adequate for measuring LAI in dense shrub canopies when browsing was not present, the handheld 3D scanner was adequate for measuring leaf area of individual ramets, and the airborne spectral data was not suitable for estimating LAI of dense, grassland shrub canopies. [ABSTRACT FROM AUTHOR]

In restoration ecology, the transition from desired to degraded state is based solely on the composition of the aboveground plant community, whereas belowground propagules are often neglected. We developed a conceptual framework integrating seed bank dynamics into alternative stable state theory, highlighting the important relationship between aboveground and belowground composition. This integration emphasizes the role of resilience in systems that appear to have shifted to an "undesirable" state. Belowground propagules, especially soil seed and bud banks, provide buffering capacity and may serve as valuable indicators of potential resistance to state transition based on the degree of similarity between belowground and aboveground vegetation composition. Ecosystem states may have multiple components that differ in their rate of change, as well as in their capacity to promote resilience. We recommend that the application of alternative stable state theory from a management perspective should incorporate components of both above- and belowground vegetation. [ABSTRACT FROM AUTHOR]

Woody encroachment has impacted grassland ecohydrology worldwide, prompting management strategies aimed at woody vegetation removal to prevent or mitigate loss of water yield. We measured stream discharge following sustained cutting of riparian trees (2010–2020) in a native tallgrass prairie (northeastern Kansas, USA). Discharge has declined at this site since the 1980's despite a concurrent increase in precipitation. This decline has been previously attributed to increased transpiration of stream water by riparian vegetation. We used water stable isotopes (δ18O and δ2H) to determine whether riparian grasses, shrubs, and trees primarily used stream/groundwater or soil water. Additionally, we quantified the increase in riparian and non-riparian woody cover (1978–2020) and combined it with sap-flux data to estimate changes in transpirative water loss. Sustained cutting of riparian trees did not result in increased discharge. Rather than stream/groundwater, the largest proportion of water used by riparian trees (Quercus spp.) was deep soil water. Cornus drummondii (clonal woody shrub) used a higher proportion of stream water and had greater overall variability in water-use. Riparian shrub cover increased about 57% from 1978 to 2020. Over the same time period, shrub cover increased about 20% in areas outside the riparian zone, resulting in an estimated 25% increase in daily transpirative water loss. Although stream water use was less than 50% for all riparian zone species, the total increase in shrub cover on this watershed, coupled with higher transpiration rates of shrubs, suggests that these woody species—within and outside the riparian zone—are key contributors to observed declines in stream flow in this system. [ABSTRACT FROM AUTHOR]

Nitrogen (N) and phosphorus (P) are limiting nutrients for many plant communities worldwide. Foliar N and P along with leaf area are among the most important controls on photosynthesis and hence productivity. However, foliar N and P are typically assessed as species level traits, whereas productivity is often measured at the community scale. Here, we compared the community-level traits of leaf area index (LAI) to total foliar nitrogen (TFN) and total foliar phosphorus (TFP) across nearly three orders of magnitude LAI in grazed and ungrazed tallgrass prairie in north-eastern Kansas, USA. LAI was strongly correlated with both TFN and TFP across communities, and also within plant functional types (grass, forb, woody, and sedge) and grazing treatments (bison or cattle, and ungrazed). Across almost the entire range of LAI values and contrasting communities, TFN:TFP ratios indicated co-limitation by N and P in almost all communities; this may further indicate a community scale trend of an optimal N and P allocation per unit leaf area for growth. Previously, results from the arctic showed similar tight relationships between LAI:TFN, suggesting N is supplied to canopies to maximize photosynthesis per unit leaf area. This tight coupling between LAI, N, and P in tallgrass prairie suggests a process of optimal allocation of N and P, wherein LAI remains similarly constrained by N and P despite differences in species composition, grazing, and canopy density. [ABSTRACT FROM AUTHOR]

Background and aims: Determining which strategies confer a competitive advantage in variable environments with strong short-term resource fluctuations (i.e., seasonal drought and flooding) is critical for understanding ecosystem structure and function, and predicting how ecosystems will respond to global change. Here, we ask how functional traits of plant species vary in response to drought and flooding and whether trait plasticity is a better predictor of plants' cover than average functional trait values. Methods: We transplanted vegetative recruits (similar size and age) of eight common species from a moderately grazed alpine wetland in the Eastern Tibetan Plateau to a common garden where we evaluated the trait responses of these species to drought and flooding. We also measured the coverage, biomass, and height of these plant species in the field communities. Results: The leaf morphological and physiological traits of these eight species generally showed different responses to drought and flood conditions. Variation (plasticity) of leaf morphological or physiological traits rather than average values of these traits were better predictors of cover and biomass in the field community. Species with lower plasticity in leaf morphological traits had higher plasticity in leaf physiology and the higher coverage and biomass in the field community. Conclusions: Our results suggest that the ability to quickly adjust leaf physiology to changing environmental conditions provides an advantage in this ecosystem, where intra-annual rainfall variability is high and thus resource fluctuations are pulsed in time. In contrast, greater functional trait plasticity in leaf morphology was a disadvantage, possibly because the benefits of these adjustments did not outweigh their initial costs. [ABSTRACT FROM AUTHOR]

Abstracts of comments on the article "Global Resilience of Tropical Forest and Savanna to Critical Transitions," by Egbert H. Van Nes, Milena Holmgren, Marina Hirota, and Marten Scheffer that appeared in the October 14, 2011 issue of "Science" are presented.

As temperatures continue rising, the direction, magnitude, and tempo of change in disturbance‐prone forests remain unresolved. Even forests long resilient to stand‐replacing fire face uncertain futures, and efforts to project changes in forest structure and composition are sorely needed to anticipate future forest trajectories. We simulated fire (incorporating fuels feedbacks) and forest dynamics on five landscapes spanning the Greater Yellowstone Ecosystem (GYE) to ask the following questions: (1) How and where are forest landscapes likely to change with 21st‐century warming and fire activity? (2) Are future forest changes gradual or abrupt, and do forest attributes change synchronously or sequentially? (3) Can forest declines be averted by mid‐21st‐century stabilization of atmospheric greenhouse gas (GHG) concentrations? We used the spatially explicit individual‐based forest model iLand to track multiple attributes (forest extent, stand age, tree density, basal area, aboveground carbon stocks, dominant forest types, species occupancy) through 2100 for six climate scenarios. Hot‐dry climate scenarios led to more fire, but stand‐replacing fire peaked in mid‐century and then declined even as annual area burned continued to rise. Where forest cover persisted, previously dense forests were converted to sparse young woodlands. Increased aridity and fire drove a ratchet of successive abrupt declines (i.e., multiple annual landscape‐level changes ≥20%) in tree density, basal area, and extent of older (>150 yr) forests, whereas declines in carbon stocks and mean stand age were always gradual. Forest changes were asynchronous across landscapes, but declines in stand structure always preceded reductions in forest extent and carbon stocks. Forest decline was most likely in less topographically complex landscapes dominated by fire‐sensitive tree species (Picea engelmannii, Abies lasiocarpa, Pinus contorta var. latifolia) and where fire resisters (Pseudotsuga menziesii var. glauca) were not already prevalent. If current GHG emissions continue unabated (RCP 8.5) and aridity increases, a suite of forest changes would transform the GYE, with cascading effects on biodiversity and myriad ecosystem services. However, stabilizing GHG concentrations by mid‐century (RCP 4.5) would slow the ratchet, moderating fire activity and dampening the magnitude and rate of forest change. Monitoring changes in forest structure may serve as an operational early warning indicator of impending forest decline. [ABSTRACT FROM AUTHOR]

Changing climate and disturbance regimes are increasingly challenging the resilience of forest ecosystems around the globe. A powerful indicator for the loss of resilience is regeneration failure, that is, the inability of the prevailing tree species to regenerate after disturbance. Regeneration failure can result from the interplay among disturbance changes (e.g., larger and more frequent fires), altered climate conditions (e.g., increased drought), and functional traits (e.g., method of seed dispersal). This complexity makes projections of regeneration failure challenging. Here we applied a novel simulation approach assimilating data‐driven fire projections with vegetation responses from process modeling by means of deep neural networks. We (i) quantified the future probability of regeneration failure; (ii) identified spatial hotspots of regeneration failure; and (iii) assessed how current forest types differ in their ability to regenerate under future climate and fire. We focused on the Greater Yellowstone Ecosystem (2.9 × 106 ha of forest) in the Rocky Mountains of the USA, which has experienced large wildfires in the past and is expected to undergo drastic changes in climate and fire in the future. We simulated four climate scenarios until 2100 at a fine spatial grain (100 m). Both wildfire activity and unstocked forest area increased substantially throughout the 21st century in all simulated scenarios. By 2100, between 28% and 59% of the forested area failed to regenerate, indicating considerable loss of resilience. Areas disproportionally at risk occurred where fires are not constrained by topography and in valleys aligned with predominant winds. High‐elevation forest types not adapted to fire (i.e., Picea engelmannii–Abies lasiocarpa as well as non‐serotinous Pinus contorta var. latifolia forests) were especially vulnerable to regeneration failure. We conclude that changing climate and fire could exceed the resilience of forests in a substantial portion of Greater Yellowstone, with profound implications for carbon, biodiversity, and recreation. [ABSTRACT FROM AUTHOR]

Hysteresis is a fundamental characteristic of alternative stable state theory, yet evidence of hysteresis is rare. In mesic grasslands, fire frequency regulates transition from grass‐ to shrub‐dominated system states. It is uncertain, however, if increasing fire frequency can reverse shrub expansion, or if grass‐shrub dynamics exhibit hysteresis. We implemented annual burning in two infrequently burned grasslands and ceased burning in two grasslands burned annually. With annual fires, grassland composition converged on that of long‐term annually burned vegetation due to rapid recovery of grass cover, although shrubs persisted. When annual burning ceased, shrub cover increased, but community composition did not converge with a long‐term infrequently burned reference site because of stochastic and lagged dispersal by shrubs, reflecting hysteresis. Our results demonstrated that annual burning can slow, but not reverse, shrub encroachment. In addition, reversing fire frequencies resulted in hysteresis because vegetation trajectories from grassland to shrubland differed from those of shrubland to grassland. [ABSTRACT FROM AUTHOR]

Aim: Simulation models are important tools for quantifying the resilience (i.e., persistence under changed environmental conditions) of forest ecosystems to global change. We synthesized the modelling literature on forest resilience, summarizing common models and applications in resilience research, and scrutinizing the implementation of important resilience mechanisms in these models. Models applied to assess resilience are highly diverse, and our goal was to assess how well they account for important resilience mechanisms identified in experimental and empirical research. Location: Global. Time period: 1994 to 2019. Major taxa studied: Trees. Methods: We reviewed the forest resilience literature using online databases, selecting 119 simulation modelling studies for further analysis. We identified a set of resilience mechanisms from the general resilience literature and analysed models for their representation of these mechanisms. Analyses were grouped by investigated drivers (resilience to what) and responses (resilience of what), as well as by the type of model being used. Results: Models used to study forest resilience varied widely, from analytical approaches to complex landscape simulators. The most commonly addressed questions were associated with resilience of forest cover to fire. Important resilience mechanisms pertaining to regeneration, soil processes, and disturbance legacies were explicitly simulated in only 34 to 46% of the model applications. Main conclusions: We found a large gap between processes identified as underpinning forest resilience in the theoretical and empirical literature, and those represented in models used to assess forest resilience. Contemporary forest models developed for other goals may be poorly suited for studying forest resilience during an era of accelerating change. Our results highlight the need for a new wave of model development to enhance understanding of and management for resilient forests. [ABSTRACT FROM AUTHOR]

Ecologists have long studied patterns, directions and tempos of change, but there is a pressing need to extend current understanding to empirical observations of abrupt changes as climate warming accelerates. Abrupt changes in ecological systems (ACES)--changes that are fast in time or fast relative to their drivers--are ubiquitous and increasing in frequency. Powerful theoretical frameworks exist, yet applications in real-world landscapes to detect, explain and anticipate ACES have lagged. We highlight five insights emerging from empirical studies of ACES across diverse ecosystems: (i) ecological systems show ACES in some dimensions but not others; (ii) climate extremes may be more important than mean climate in generating ACES; (iii) interactions among multiple drivers often produce ACES; (iv) contingencies, such as ecological memory, frequency and sequence of disturbances, and spatial context are important; and (v) tipping points are often (but not always) associated with ACES. We suggest research priorities to advance understanding of ACES in the face of climate change. Progress in understanding ACES requires strong integration of scientific approaches (theory, observations, experiments and process-based models) and high-quality empirical data drawn from a diverse array of ecosystems. [ABSTRACT FROM AUTHOR]

Resilience has become a common goal for science-based natural resource management, particularly in the context of changing climate and disturbance regimes. Integrating varying perspectives and definitions of resilience is a complex and often unrecognized challenge to applying resilience concepts to social–ecological systems (SESs) management. Using wildfire as an example, we develop a framework to expose and separate two important dimensions of resilience: the inherent properties that maintain structure, function, or states of an SES and the human perceptions of desirable or valued components of an SES. In doing so, the framework distinguishes between value-free and human-derived, value-explicit dimensions of resilience. Four archetypal scenarios highlight that ecological resilience and human values do not always align and that recognizing and anticipating potential misalignment is critical for developing effective management goals. Our framework clarifies existing resilience theory, connects literature across disciplines, and facilitates use of the resilience concept in research and land-management applications. [ABSTRACT FROM AUTHOR]

Shrub encroachment of grasslands is a transformative ecological process by which native woody species increase in cover and frequency and replace the herbaceous community. Mechanisms of encroachment are typically assessed using temporal data or experimental manipulations, with few large spatial assessments of shrub physiology. In a mesic grassland in North America, we measured inter- and intra-annual variability in leaf δ13C in Cornus drummondii across a grassland landscape with varying fire frequency, presence of large grazers and topographic variability. This assessment of changes in individual shrub physiology is the largest spatial and temporal assessment recorded to date. Despite a doubling of annual rainfall (in 2008 versus 2011), leaf δ13C was statistically similar among and within years from 2008-11 (range of −28 to −27‰). A topography*grazing interaction was present, with higher leaf δ13C in locations that typically have more bare soil and higher sensible heat in the growing season (upland topographic positions and grazed grasslands). Leaf δ13C from slopes varied among grazing contrasts, with upland and slope leaf δ13C more similar in ungrazed locations, while slopes and lowlands were more similar in grazed locations. In 2011, canopy greenness (normalized difference vegetation index – NDVI) was assessed at the centroid of individual shrubs using high-resolution hyperspectral imagery. Canopy greenness was highest mid-summer, likely reflecting temporal periods when C assimilation rates were highest. Similar to patterns seen in leaf δ13C, NDVI was highest in locations that typically experience lowest sensible heat (lowlands and ungrazed). The ability of Cornus drummondii to decouple leaf physiological responses from climate variability and fire frequency is a likely contributor to the increase in cover and frequency of this shrub species in mesic grassland and may be generalizable to other grasslands undergoing woody encroachment. [ABSTRACT FROM AUTHOR]