The interactive effects of press/pulse intensity and duration on regime shifts at multiple scales

Warming and disturbances affect Arctic-boreal vegetation resilience across northwestern North America

Rapid warming and increasing disturbances in high-latitude regions have caused extensive vegetation shifts and uncertainty in future carbon budgets. Better predictions of vegetation dynamics and functions require characterizing resilience, which indicates the capability of an ecosystem to recover from perturbations. Here, using temporal autocorrelation of remotely sensed greenness, we quantify time-varying vegetation resilience during 2000-2019 across northwestern North American Arctic-boreal ecosystems. We find that vegetation resilience significantly decreased in southern boreal forests, including forests showing greening trends, while it increased in most of the Arctic tundra. Warm and dry areas with high elevation and dense vegetation cover were among the hotspots of reduced resilience. Resilience further declined both before and after forest losses and fires, especially in southern boreal forests. These findings indicate that warming and disturbance have been altering vegetation resilience, potentially undermining the expected long-term increase of high-latitude carbon uptake under future climate.

Synthesis of recovery patterns in microbial communities across environments

BACKGROUND

Disturbances alter the diversity and composition of microbial communities. Yet a generalized empirical assessment of microbiome responses to disturbance across different environments is needed to understand the factors driving microbiome recovery, and the role of the environment in driving these patterns.

RESULTS

To this end, we combined null models with Bayesian generalized linear models to examine 86 time series of disturbed mammalian, aquatic, and soil microbiomes up to 50 days following disturbance. Overall, disturbances had the strongest effect on mammalian microbiomes, which lost taxa and later recovered their richness, but not their composition. In contrast, following disturbance, aquatic microbiomes tended away from their pre-disturbance composition over time. Surprisingly, across all environments, we found no evidence of increased compositional dispersion (i.e., variance) following disturbance, in contrast to the expectations of the Anna Karenina Principle.

CONCLUSIONS

This is the first study to systematically compare secondary successional dynamics across disturbed microbiomes, using a consistent temporal scale and modeling approach. Our findings show that the recovery of microbiomes is environment-specific, and helps to reconcile existing, environment-specific research into a unified perspective. Video Abstract.

Farming practices to enhance biodiversity across biomes: a systematic review

Intensive agriculture for food and feed production is a key driver of global biodiversity loss. It is generally assumed that more extensive practices are needed to reconcile food production with biodiversity conservation. In a literature review across biomes and for seven taxa, we retrieved 35 alternative practices (e.g. no-tillage, cover crops, organic fertilizer) from 331 studies. We found that no single practice enhanced all taxonomic groups, but that overall less intensive agricultural practices are beneficial to biodiversity. Nevertheless, often practices had no effects observed and very rarely contrasting impacts on aboveground versus belowground taxa. Species responses to practices were mostly consistent across biomes, except for fertilization. We conclude that alternative practices generally enhance biodiversity, but there is also variation in impacts depending on taxonomic group or type of practice. This suggests that a careful selection of practices is needed to secure biodiversity across taxa in future food systems worldwide.

Soil nematode assemblages respond to interacting environmental changes

Multi-factor experiments suggest that interactions among environmental changes commonly influence biodiversity and community composition. However, most field experiments manipulate only single factors. Soil food webs are critical to ecosystem health and may be particularly sensitive to interactions among environmental changes that include soil warming, eutrophication, and altered precipitation. Here, we asked how environmental changes interacted to alter soil nematode communities in a northern Chihuahuan Desert grassland. Factorial manipulations of nitrogen, winter rainfall, and nighttime warming matched predictions for regional environmental change. Warming reduced nematode diversity by 25% and genus-level richness by 32%, but declines dissipated with additional winter rain, suggesting that warming effects occurred via drying. Interactions between precipitation and nitrogen also altered nematode community composition, but only weakly affected total nematode abundance, indicating that most change involved reordering of species abundances. Specifically, under ambient precipitation, nitrogen fertilizer reduced bacterivores by 68% and herbivores by 73%, but did not affect fungivores. In contrast, under winter rain addition, nitrogen fertilization increased bacterivores by 95%, did not affect herbivores, and doubled fungivore abundance. Rain can reduce soil nitrogen availability and increase turnover in the microbial loop, potentially promoting the recovery of nematode populations overwhelmed by nitrogen eutrophication. Nematode communities were not tightly coupled to plant community composition and may instead track microbes, including biocrusts or decomposers. Our results highlight the importance of interactions among environmental change stressors for shaping the composition and function of soil food webs in drylands.

The color of environmental noise in river networks

Despite its far-reaching implications for conservation and natural resource management, little is known about the color of environmental noise, or the structure of temporal autocorrelation in random environmental variation, in streams and rivers. Here, we analyze the geography, drivers, and timescale-dependence of noise color in streamflow across the U.S. hydrography, using streamflow time series from 7504 gages. We find that daily and annual flows are dominated by red and white spectra respectively, and spatial variation in noise color is explained by a combination of geographic, hydroclimatic, and anthropogenic variables. Noise color at the daily scale is influenced by stream network position, and land use and water management explain around one third of the spatial variation in noise color irrespective of the timescale considered. Our results highlight the peculiarities of environmental variation regimes in riverine systems, and reveal a strong human fingerprint on the stochastic patterns of streamflow variation in river networks.

The two faces of Janus: Processes can be both exogenous forcings and endogenous feedbacks with wind as a case study

Janus is the Roman god of transitions. In many environments, state transitions are an important part of our understanding of ecological change. These transitions are controlled by the interactions between exogenous forcing factors and stabilizing endogenous feedbacks. Forcing factors and feedbacks are typically considered to consist of different processes. We argue that during extreme events, a process that usually forms part of a stabilizing feedback can behave as a forcing factor. And thus, like Janus, a single process can have two faces. The case explored here pertains to state change in drylands where interactions between wind erosion and vegetation form an important feedback that encourages grass-to-shrub state transitions. Wind concentrates soil resources in shrub-centered fertile islands, removes resources through loss of fines to favor deep-rooted shrubs, and abrades grasses' photosynthetic tissue, thus further favoring the shrub state that, in turn, experiences greater aeolian transport. This feedback is well documented but the potential of wind to act also as a forcing has yet to be examined. Extreme wind events have the potential to act like other drivers of state change, such as drought and grazing, to directly reduce grass cover. This study examines the responses of a grass-shrub community after two extreme wind events in 2019 caused severe deflation. We measured grass cover and root exposure due to deflation, in addition to shrub height, grass patch size, and grass greenness along 50-m transects across a wide range of grass cover. Root exposure was concentrated in the direction of erosive winds during the storms and sites with low grass cover were associated with increased root exposure and reduced greenness. We argue that differences between extreme, rare wind events and frequent, small wind events are significant enough to be differences in kind rather than differences in degree allowing extreme winds to behave as endogenous forcings and common winds to participate in an endogenous stabilizing feedback. Several types of state change in other ecological systems in are contextualized within this framework.

Combating ecosystem collapse from the tropics to the Antarctic

Globally, collapse of ecosystems-potentially irreversible change to ecosystem structure, composition and function-imperils biodiversity, human health and well-being. We examine the current state and recent trajectories of 19 ecosystems, spanning 58° of latitude across 7.7 M km² , from Australia's coral reefs to terrestrial Antarctica. Pressures from global climate change and regional human impacts, occurring as chronic 'presses' and/or acute 'pulses', drive ecosystem collapse. Ecosystem responses to 5-17 pressures were categorised as four collapse profiles-abrupt, smooth, stepped and fluctuating. The manifestation of widespread ecosystem collapse is a stark warning of the necessity to take action. We present a three-step assessment and management framework (3As Pathway Awareness, Anticipation and Action) to aid strategic and effective mitigation to alleviate further degradation to help secure our future.

Soil Seed Banks, Alternative Stable State Theory, and Ecosystem Resilience

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.

Management implications of long transients in ecological systems

The underlying biological processes that govern many ecological systems can create very long periods of transient dynamics. It is often difficult or impossible to distinguish this transient behaviour from similar dynamics that would persist indefinitely. In some cases, a shift from the transient to the long-term, stable dynamics may occur in the absence of any exogenous forces. Recognizing the possibility that the state of an ecosystem may be less stable than it appears is crucial to the long-term success of management strategies in systems with long transient periods. Here we demonstrate the importance of considering the potential of transient system behaviour for management actions across a range of ecosystem organizational scales and natural system types. Developing mechanistic models that capture essential system dynamics will be crucial for promoting system resilience and avoiding system collapses.

Phytoplankton Temporal Strategies Increase Entropy Production in a Marine Food Web Model

We develop a trait-based model founded on the hypothesis that biological systems evolve and organize to maximize entropy production by dissipating chemical and electromagnetic free energy over longer time scales than abiotic processes by implementing temporal strategies. A marine food web consisting of phytoplankton, bacteria, and consumer functional groups is used to explore how temporal strategies, or the lack thereof, change entropy production in a shallow pond that receives a continuous flow of reduced organic carbon plus inorganic nitrogen and illumination from solar radiation with diel and seasonal dynamics. Results show that a temporal strategy that employs an explicit circadian clock produces more entropy than a passive strategy that uses internal carbon storage or a balanced growth strategy that requires phytoplankton to grow with fixed stoichiometry. When the community is forced to operate at high specific growth rates near 2 d⁻¹, the optimization-guided model selects for phytoplankton ecotypes that exhibit complementary for winter versus summer environmental conditions to increase entropy production. We also present a new type of trait-based modeling where trait values are determined by maximizing entropy production rather than by random selection.

Rate of environmental change across scales in ecology

The rate of change (RoC) of environmental drivers matters: biotic and abiotic components respond differently when faced with a fast or slow change in their environment. This phenomenon occurs across spatial scales and thus levels of ecological organization. We investigated the RoC of environmental drivers in the ecological literature and examined publication trends across ecological levels, including prevalent types of evidence and drivers. Research interest in environmental driver RoC has increased over time (particularly in the last decade), however, the amount of research and type of studies were not equally distributed across levels of organization and different subfields of ecology use temporal terminology (e.g. 'abrupt' and 'gradual') differently, making it difficult to compare studies. At the level of individual organisms, evidence indicates that responses and underlying mechanisms are different when environmental driver treatments are applied at different rates, thus we propose including a time dimension into reaction norms. There is much less experimental evidence at higher levels of ecological organization (i.e. population, community, ecosystem), although theoretical work at the population level indicates the importance of RoC for evolutionary responses. We identified very few studies at the community and ecosystem levels, although existing evidence indicates that driver RoC is important at these scales and potentially could be particularly important for some processes, such as community stability and cascade effects. We recommend shifting from a categorical (e.g. abrupt versus gradual) to a quantitative and continuous (e.g. °C/h) RoC framework and explicit reporting of RoC parameters, including magnitude, duration and start and end points to ease cross-scale synthesis and alleviate ambiguity. Understanding how driver RoC affects individuals, populations, communities and ecosystems, and furthermore how these effects can feed back between levels is critical to making improved predictions about ecological responses to global change drivers. The application of a unified quantitative RoC framework for ecological studies investigating environmental driver RoC will both allow cross-scale synthesis to be accomplished more easily and has the potential for the generation of novel hypotheses.

A nucleation framework for transition between alternate states: short-circuiting barriers to ecosystem recovery

The theory of alternate stable states provides an explanation for rapid ecosystem degradation, yielding important implications for ecosystem conservation and restoration. However, utilizing this theory to initiate transitions from degraded to desired ecosystem states remains a significant challenge. Applications of the alternative stable states framework may currently be impeded by a mismatch between local‐scale driving processes and landscape‐scale emergent system transitions. We show how nucleation theory provides an elegant bridge between local‐scale positive feedback mechanisms and landscape‐scale transitions between alternate stable ecosystem states. Geometrical principles can be used to derive a critical patch radius: a spatially explicit, local description of an unstable equilibrium point. This insight can be used to derive an optimal patch size that minimizes the cost of restoration, and to provide a framework to measure the resilience of desired ecosystem states to the synergistic effects of disturbance and environmental change.

Towards a Comparative Framework of Demographic Resilience

In the current global biodiversity crisis, the development of tools to define, quantify, compare, and predict resilience is essential for understanding the responses of species to global change. However, disparate interpretations of resilience have hampered the development of a common currency to quantify and compare resilience across natural systems. Most resilience frameworks focus on upper levels of biological organization, especially ecosystems or communities, which complicates measurements of resilience using empirical data. Surprisingly, there is no quantifiable definition of resilience at the demographic level. We introduce a framework of demographic resilience that draws on existing concepts from community and population ecology, as well as an accompanying set of metrics that are comparable across species.

Climate change, ecosystems and abrupt change: science priorities

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. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

High Arctic ecosystem states: Conceptual models of vegetation change to guide long-term monitoring and research

Vegetation change has consequences for terrestrial ecosystem structure and functioning and may involve climate feedbacks. Hence, when monitoring ecosystem states and changes thereof, the vegetation is often a primary monitoring target. Here, we summarize current understanding of vegetation change in the High Arctic-the World's most rapidly warming region-in the context of ecosystem monitoring. To foster development of deployable monitoring strategies, we categorize different kinds of drivers (disturbances or stresses) of vegetation change either as pulse (i.e. drivers that occur as sudden and short events, though their effects may be long lasting) or press (i.e. drivers where change in conditions remains in place for a prolonged period, or slowly increases in pressure). To account for the great heterogeneity in vegetation responses to climate change and other drivers, we stress the need for increased use of ecosystem-specific conceptual models to guide monitoring and ecological studies in the Arctic. We discuss a conceptual model with three hypothesized alternative vegetation states characterized by mosses, herbaceous plants, and bare ground patches, respectively. We use moss-graminoid tundra of Svalbard as a case study to discuss the documented and potential impacts of different drivers on the possible transitions between those states. Our current understanding points to likely additive effects of herbivores and a warming climate, driving this ecosystem from a moss-dominated state with cool soils, shallow active layer and slow nutrient cycling to an ecosystem with warmer soil, deeper permafrost thaw, and faster nutrient cycling. Herbaceous-dominated vegetation and (patchy) bare ground would present two states in response to those drivers. Conceptual models are an operational tool to focus monitoring efforts towards management needs and identify the most pressing scientific questions. We promote greater use of conceptual models in conjunction with a state-and-transition framework in monitoring to ensure fit for purpose approaches. Defined expectations of the focal systems' responses to different drivers also facilitate linking local and regional monitoring efforts to international initiatives, such as the Circumpolar Biodiversity Monitoring Program.

Chronic but not acute saltwater intrusion leads to large release of inorganic N in a tidal freshwater marsh

Sea level rise is expected to increase inundation and saltwater intrusion into many tidal freshwater marshes and forests. Saltwater intrusion may be long-term, as with rising seas, or episodic, as with low river flow or storm surge. We applied continuous (press) and episodic (pulse) treatments of dilute seawater to replicate 2.5 × 2.5 m field plots for three years and measured soil attributes, including soil porewater, oxidation-reduction potential, soil carbon (C), and nitrogen (N) to investigate the effects of continuous and episodic saltwater intrusion and increased inundation on tidal freshwater marsh elemental cycling and soil processes. Continuous additions of dilute seawater resulted in increased porewater chloride, sulfate, sulfide, ammonium, and nitrate concentrations. Plots that received press additions also had lower soil oxidation-reduction potentials beginning in the second year. Episodic additions of dilute seawater during typical low flow conditions (Sept.-Oct.) resulted in transient increases in porewater chloride and sulfate that returned to baseline conditions once dosing ceased. Freshwater additions did not affect porewater inorganic N or soil C or N. Persistent saltwater intrusion in freshwater marshes alters the N cycle by releasing ammonium-N from sorption sites, increasing nitrification and severely reducing N storage in macrophyte biomass. Chronic saltwater intrusion, as is expected with rising seas, is likely to shift tidal freshwater marshes from a sink to a source of N whereas intermittent intrusion from drought may have no long term effect on N cycling.

A theory of pulse dynamics and disturbance in ecology

We propose four postulates as the minimum set of logical propositions necessary for a theory of pulse dynamics and disturbance in ecosystems: (1) resource dynamics characterizes the magnitude, rate, and duration of resource change caused by pulse events, including the continuing changes in resources that are the result of abiotic and biotic processes; (2) energy flux characterizes the energy flow that controls the variation in the rates of resource assimilation across ecosystems; (3) patch dynamics characterizes the distribution of resource patches over space and time, and the resulting patterns of biotic diversity, ecosystem structure, and cross-scale feedbacks of pulses processes; and (4) biotic trait diversity characterizes the evolutionary responses to pulse dynamics and, in turn, the way trait diversity affects ecosystem dynamics during and after pulse events. We apply the four postulates to an important class of pulse events, biomass-altering disturbances, and derive seven generalizations that predict disturbance magnitude, resource trajectory, rate of resource change, disturbance probability, biotic trait diversification at evolutionary scales, biotic diversity at ecological scales, and functional resilience. Ultimately, theory must define the variable combinations that result in dynamic stability, comprising resistance, recovery, and adaptation.

Spatial early warning signals for impending regime shifts: A practical framework for application in real-world landscapes

Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible 'regime shifts' that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model-based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land-managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real-world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real-world landscapes based on literature review and examples from real-world data. Major identified issues include (1) spatial heterogeneity in real-world landscapes may enhance reversibility of regime shifts and boost landscape-level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio-economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well-informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.

Basin bifurcations, oscillatory instability and rate-induced thresholds for Atlantic meridional overturning circulation in a global oceanic box model

The Atlantic meridional overturning circulation (AMOC) transports substantial amounts of heat into the North Atlantic sector, and hence is of very high importance in regional climate projections. The AMOC has been observed to show multi-stability across a range of models of different complexity. The simplest models find a bifurcation associated with the AMOC 'on' state losing stability that is a saddle node. Here, we study a physically derived global oceanic model of Wood et al. with five boxes, that is calibrated to runs of the FAMOUS coupled atmosphere-ocean general circulation model. We find the loss of stability of the 'on' state is due to a subcritical Hopf for parameters from both pre-industrial and doubled CO₂ atmospheres. This loss of stability via subcritical Hopf bifurcation has important consequences for the behaviour of the basin of attraction close to bifurcation. We consider various time-dependent profiles of freshwater forcing to the system, and find that rate-induced thresholds for tipping can appear, even for perturbations that do not cross the bifurcation. Understanding how such state transitions occur is important in determining allowable safe climate change mitigation pathways to avoid collapse of the AMOC.

Temporal clustering of extreme climate events drives a regime shift in rocky intertidal biofilms

Research on regime shifts has focused primarily on how changes in the intensity and duration of press disturbances precipitate natural systems into undesirable, alternative states. By contrast, the role of recurrent pulse perturbations, such as extreme climatic events, has been largely neglected, hindering our understanding of how historical processes regulate the onset of a regime shift. We performed field manipulations to evaluate whether combinations of extreme events of temperature and sediment deposition that differed in their degree of temporal clustering generated alternative states in rocky intertidal epilithic microphytobenthos (biofilms) on rocky shores. The likelihood of biofilms to shift from a vegetated to a bare state depended on the degree of temporal clustering of events, with biofilm biomass showing both states under a regime of non-clustered (60 d apart) perturbations while collapsing in the clustered (15 d apart) scenario. Our results indicate that time since the last perturbation can be an important predictor of collapse in systems exhibiting alternative states and that consideration of historical effects in studies of regime shifts may largely improve our understanding of ecosystem dynamics under climate change.

Evidence for 'critical slowing down' in seagrass: a stress gradient experiment at the southern limit of its range

The theory of critical slowing down, i.e. the increasing recovery times of complex systems close to tipping points, has been proposed as an early warning signal for collapse. Empirical evidence for the reality of such warning signals is still rare in ecology. We studied this on Zostera noltii intertidal seagrass meadows at their southern range limit, the Banc d'Arguin, Mauritania. We analyse the environmental covariates of recovery rates using structural equation modelling (SEM), based on an experiment in which we assessed whether recovery after disturbances (i.e. seagrass & infauna removal) depends on stress intensity (increasing with elevation) and disturbance patch size (1 m2 vs. 9 m2). The SEM analyses revealed that higher biofilm density and sediment accretion best explained seagrass recovery rates. Experimental disturbances were followed by slow rates of recovery, regrowth occurring mainly in the coolest months of the year. Macrofauna recolonisation lagged behind seagrass recovery. Overall, the recovery rate was six times slower in the high intertidal zone than in the low zone. The large disturbances in the low zone recovered faster than the small ones in the high zone. This provides empirical evidence for critical slowing down with increasing desiccation stress in an intertidal seagrass system.

Abrupt Change in Ecological Systems: Inference and Diagnosis

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.

Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods

There is considerable uncertainty in the magnitude and direction of changes in precipitation associated with climate change, and ecosystem responses are also uncertain. Multiyear periods of above- and below-average rainfall may foretell consequences of changes in rainfall regime. We compiled long-term aboveground net primary productivity (ANPP) and precipitation (PPT) data for eight North American grasslands, and quantified relationships between ANPP and PPT at each site, and in 1-3 year periods of above- and below-average rainfall for mesic, semiarid cool, and semiarid warm grassland types. Our objective was to improve understanding of ANPP dynamics associated with changing climatic conditions by contrasting PPT-ANPP relationships in above- and below-average PPT years to those that occurred during sequences of multiple above- and below-average years. We found differences in PPT-ANPP relationships in above- and below-average years compared to long-term site averages, and variation in ANPP not explained by PPT totals that likely are attributed to legacy effects. The correlation between ANPP and current- and prior-year conditions changed from year to year throughout multiyear periods, with some legacy effects declining, and new responses emerging. Thus, ANPP in a given year was influenced by sequences of conditions that varied across grassland types and climates. Most importantly, the influence of prior-year ANPP often increased with the length of multiyear periods, whereas the influence of the amount of current-year PPT declined. Although the mechanisms by which a directional change in the frequency of above- and below-average years imposes a persistent change in grassland ANPP require further investigation, our results emphasize the importance of legacy effects on productivity for sequences of above- vs. below-average years, and illustrate the utility of long-term data to examine these patterns.

Temporal heterogeneity increases with spatial heterogeneity in ecological communities

Heterogeneity is increasingly recognized as a foundational characteristic of ecological systems. Under global change, understanding temporal community heterogeneity is necessary for predicting the stability of ecosystem functions and services. Indeed, spatial heterogeneity is commonly used in alternative stable state theory as a predictor of temporal heterogeneity and therefore an early indicator of regime shifts. To evaluate whether spatial heterogeneity in species composition is predictive of temporal heterogeneity in ecological communities, we analyzed 68 community data sets spanning freshwater and terrestrial systems where measures of species abundance were replicated over space and time. Of the 68 data sets, 55 (81%) had a weak to strongly positive relationship between spatial and temporal heterogeneity, while in the remaining communities the relationship was weak to strongly negative (19%). Based on a mixed model analysis, we found a significant but weak overall positive relationship between spatial and temporal heterogeneity across all data sets combined, and within aquatic and terrestrial data sets separately. In addition, lifespan and successional stage were negatively and positively related to temporal heterogeneity, respectively. We conclude that spatial heterogeneity may be a predictor of temporal heterogeneity in ecological communities, and that this relationship may be a general property of many terrestrial and aquatic communities.