Perspectives for ecosystem management based on ecosystem resilience and ecological thresholds against multiple and stochastic disturbances

Ecosystem resilience is the inherent ability to absorb various disturbances and reorganize while undergoing state changes to maintain critical functions. When ecosystem resilience is sufficiently degraded by disturbances, ecosystem is exposed at high risk of shifting from a desirable state to an undesirable state. Ecological thresholds represent the points where even small changes in environmental conditions associated with disturbances lead to switch between ecosystem states. There is a growing body of empirical evidence for such state transitions caused by anthropogenic disturbances in a variety of ecosystems. However, fewer studies addressed the interaction of anthropogenic and natural disturbances that often force an ecosystem to cross a threshold which an anthropogenic disturbance or a natural disturbance alone would not have achieved. This fact highlights how little is known about ecosystem dynamics under uncertainties around multiple and stochastic disturbances. Here, we present two perspectives for providing a predictive scientific basis to the management and conservation of ecosystems against multiple and stochastic disturbances. The first is management of predictable anthropogenic disturbances to maintain a sufficient level of biodiversity for ensuring ecosystem resilience (i.e., resilience-based management). Several biological diversity elements appear to confer ecosystem resilience, such as functional redundancy, response diversity, a dominant species, a foundation species, or a keystone species. The greatest research challenge is to identify key elements of biodiversity conferring ecosystem resilience for each context and to examine how we can manage and conserve them. The second is the identification of ecological thresholds along existing or experimental disturbance gradients. This will facilitate the development of indicators of proximity to thresholds as well as the understanding of threshold mechanisms. The implementation of forewarning indicators will be critical particularly when resilience-based management fails. The ability to detect an ecological threshold along disturbance gradients should therefore be essential to establish a backstop for preventing the threshold from being crossed. These perspectives can take us beyond simply invoking the precautionary principle of conserving biodiversity to a predictive science that informs practical solutions to cope with uncertainties and ecological surprises in a changing world.     

陆地生态系统临界转换理论及其生态学机制研究进展

随着气候变化和人类活动对陆地生态系统双重扰动的不断加剧,越来越多的研究已经意识到生态系统结构和功能会发生难以预知的突变,并且恢复起来需要很长时间.开发判别典型生态系统临界转换的早期预警模型及理解其生态学机制成为生态学研究的热点.目前,基于跨越多个时空尺度的理论和实验研究,提出了多种预警陆地生态系统临界转换的理论框架和指...     

Plant biomes demonstrate that landscape resilience today is the lowest it has been since end‐Pleistocene megafaunal extinctions

Resilient landscapes have helped maintain terrestrial biodiversity during periods of climatic and environmental change. Identifying the tempo and mode of landscape transitions and the drivers of landscape resilience is critical to maintaining natural systems and preserving biodiversity given today's rapid climate and land use changes. However, resilient landscapes are difficult to recognize on short time scales, as perturbations are challenging to quantify and ecosystem transitions are rare. Here we analyze two components of North American landscape resilience over 20,000 years: residence time and recovery time. To evaluate landscape dynamics, we use plant biomes, preserved in the fossil pollen record, to examine how long a biome type persists at a given site (residence time) and how long it takes for the biome at that site to reestablish following a transition (recovery time). Biomes have a median residence time of only 230–460 years. Only 64% of biomes recover their original biome type, but recovery time is 140–290 years. Temperatures changing faster than 0.5°C per 500 years result in much reduced residence times. Following a transition, biodiverse biomes reestablish more quickly. Landscape resilience varies through time. Notably, short residence times and long recovery times directly preceded the end‐Pleistocene megafauna extinction, resulting in regional destabilization, and combining with more proximal human impacts to deliver a one‐two punch to megafauna species. Our work indicates that landscapes today are once again exhibiting low resilience, foreboding potential extinctions to come. Conservation strategies focused on improving both landscape and ecosystem resilience by increasing local connectivity and targeting regions with high richness and diverse landforms can mitigate these extinction risks.     

Slow recovery from perturbations as a generic indicator of a nearby catastrophic shift

The size of the basin of attraction in ecosystems with alternative stable states is often referred to as "ecological resilience." Ecosystems with a low ecological resilience may easily be tipped into an alternative basin of attraction by a stochastic event. Unfortunately, it is very difficult to measure ecological resilience in practice. Here we show that the rate of recovery from small perturbations (sometimes called "engineering resilience") is a remarkably good indicator of ecological resilience. Such recovery rates decrease as a catastrophic regime shift is approached, a phenomenon known in physics as "critical slowing down." We demonstrate the robust occurrence of critical slowing down in six ecological models and outline a possible experimental approach to quantify differences in recovery rates. In all the models we analyzed, critical slowing down becomes apparent quite far from a threshold point, suggesting that it may indeed be of practical use as an early warning signal. Despite the fact that critical slowing down could also indicate other critical transitions, such as a stable system becoming oscillatory, the robustness of the phenomenon makes it a promising indicator of loss of resilience and the risk of upcoming regime shifts in a system.     

Critical transitions in rainfall manipulation experiments on grasslands

As a result of climate and land‐use changes, grasslands have been subjected to intensifying drought regimes. Extreme droughts could interfere in the positive feedbacks between grasses and soil water content, pushing grasslands across critical thresholds of productivity and leading them to collapse. If this happens, systems may show hysteresis and costly management interventions might be necessary to restore predrought productivity. Thus, neglecting critical transitions may lead to mismanagement of grasslands and to irreversible loss of ecosystem services. Rainfall manipulation experiments constitute a powerful approach to investigate the risk of such critical transitions. However, experiments performed to date have rarely applied extreme droughts and have used resilience indices that disregard the existence of hysteresis. Here, we suggest how to incorporate critical transitions when designing rainfall manipulation experiments on grasslands and when measuring their resilience to drought. The ideas presented here have the potential to trigger a perspective shift among experimental researchers, into a new state where the existence of critical transitions will be discussed, experimentally tested, and largely considered when assessing and managing vegetation resilience to global changes.     

Local ecosystem feedbacks and critical transitions in the climate

Global and regional climate models, such as those used in IPCC assessments, are the best tools available for climate predictions. Such models typically account for large-scale land-atmosphere feedbacks. However, these models omit local vegetation-environment feedbacks that may be crucial for critical transitions in ecosystems at larger scales. In this viewpoint paper, we propose the hypothesis that, if the balance of feedbacks is positive at all scales, local vegetation-environment feedbacks may trigger a cascade of amplifying effects, propagating from local to large scale, possibly leading to critical transitions in the large-scale climate. We call for linking local ecosystem feedbacks with large-scale land-atmosphere feedbacks in global and regional climate models in order to improve climate predictions.     

Resilience indicators: prospects and limitations for early warnings of regime shifts

In the vicinity of tipping points—or more precisely bifurcation points—ecosystems recover slowly from small perturbations. Such slowness may be interpreted as a sign of low resilience in the sense that the ecosystem could easily be tipped through a critical transition into a contrasting state. Indicators of this phenomenon of ‘critical slowing down (CSD)’ include a rise in temporal correlation and variance. Such indicators of CSD can provide an early warning signal of a nearby tipping point. Or, they may offer a possibility to rank reefs, lakes or other ecosystems according to their resilience. The fact that CSD may happen across a wide range of complex ecosystems close to tipping points implies a powerful generality. However, indicators of CSD are not manifested in all cases where regime shifts occur. This is because not all regime shifts are associated with tipping points. Here, we review the exploding literature about this issue to provide guidance on what to expect and what not to expect when it comes to the CSD-based early warning signals for critical transitions.     

Slowing down in spatially patterned ecosystems at the brink of collapse

Predicting the risk of critical transitions, such as the collapse of a population, is important in order to direct management efforts. In any system that is close to a critical transition, recovery upon small perturbations becomes slow, a phenomenon known as critical slowing down. It has been suggested that such slowing down may be detected indirectly through an increase in spatial and temporal correlation and variance. Here, we tested this idea in arid ecosystems, where vegetation may collapse to desert as a result of increasing water limitation. We used three models that describe desertification but differ in the spatial vegetation patterns they produce. In all models, recovery rate upon perturbation decreased before vegetation collapsed. However, in one of the models, slowing down failed to translate into rising variance and correlation. This is caused by the regular self-organized vegetation patterns produced by this model. This finding implies an important limitation of variance and correlation as indicators of critical transitions. However, changes in such self-organized patterns themselves are a reliable indicator of an upcoming transition. Our results illustrate that while critical slowing down may be a universal phenomenon at critical transitions, its detection through indirect indicators may have limitations in particular systems.     

Asymmetric response of early warning indicators of phytoplankton transition to and from cycles

Phytoplankton populations often exhibit cycles associated with nuisance blooms of cyanobacteria and other algae that cause toxicity, odor problems, oxygen depletion, and fish kills. Models of phytoplankton blooms used for management and basic research often contain critical transitions from stable points to cycles, or vice-versa. It would be useful to know whether aquatic systems, especially water supplies, are close to a critical threshold for cycling blooms. Recent studies of resilience indicators have focused on alternate stable points, although theory suggests that indicators such as variance and autocorrelation should also rise prior to a transition from stable point to stable cycle. We investigated changes in variance and autocorrelation associated with transitions involving cycles using two models. Variance rose prior to the transition from a small-radius cycle (or point) to a larger radius cycle in all cases. In many but not all cases, autocorrelation increased prior to the transition. However, the transition from large-radius to small-radius cycles was not associated with discernible increases in variance or autocorrelation. Thus, indicators of changing resilience can be measured prior to the transition from stable to cyclic plankton dynamics. Such indicators are potentially useful in management. However, these same indicators do not provide useful signals of the reverse transition, which is often a goal of aquatic ecosystem restoration. Thus, the availability of resilience indicators for phytoplankton cycles is asymmetric: the indicators are seen for the transition to bloom–bust cycles but not for the reverse transition to a phytoplankton stable point.     

Operationalizing resilience for adaptive coral reef management under global environmental change

Cumulative pressures from global climate and ocean change combined with multiple regional and local‐scale stressors pose fundamental challenges to coral reef managers worldwide. Understanding how cumulative stressors affect coral reef vulnerability is critical for successful reef conservation now and in the future. In this review, we present the case that strategically managing for increased ecological resilience (capacity for stress resistance and recovery) can reduce coral reef vulnerability (risk of net decline) up to a point. Specifically, we propose an operational framework for identifying effective management levers to enhance resilience and support management decisions that reduce reef vulnerability. Building on a system understanding of biological and ecological processes that drive resilience of coral reefs in different environmental and socio‐economic settings, we present an Adaptive Resilience‐Based management (ARBM) framework and suggest a set of guidelines for how and where resilience can be enhanced via management interventions. We argue that press‐type stressors (pollution, sedimentation, overfishing, ocean warming and acidification) are key threats to coral reef resilience by affecting processes underpinning resistance and recovery, while pulse‐type (acute) stressors (e.g. storms, bleaching events, crown‐of‐thorns starfish outbreaks) increase the demand for resilience. We apply the framework to a set of example problems for Caribbean and Indo‐Pacific reefs. A combined strategy of active risk reduction and resilience support is needed, informed by key management objectives, knowledge of reef ecosystem processes and consideration of environmental and social drivers. As climate change and ocean acidification erode the resilience and increase the vulnerability of coral reefs globally, successful adaptive management of coral reefs will become increasingly difficult. Given limited resources, on‐the‐ground solutions are likely to focus increasingly on actions that support resilience at finer spatial scales, and that are tightly linked to ecosystem goods and services.     

Flickering as an early warning signal

Most work on generic early warning signals for critical transitions focuses on indicators of the phenomenon of critical slowing down that precedes a range of catastrophic bifurcation points. However, in highly stochastic environments, systems will tend to shift to alternative basins of attraction already far from such bifurcation points. In fact, strong perturbations (noise) may cause the system to “flicker” between the basins of attraction of the system’s alternative states. As a result, under such noisy conditions, critical slowing down is not relevant, and one would expect its related generic leading indicators to fail, signaling an impending transition. Here, we systematically explore how flickering may be detected and interpreted as a signal of an emerging alternative attractor. We show that—although the two mechanisms differ—flickering may often be reflected in rising variance, lag-1 autocorrelation and skewness in ways that resemble the effects of critical slowing down. In particular, we demonstrate how the probability distribution of a flickering system can be used to map potential alternative attractors and their resilience. Thus, while flickering systems differ in many ways from the classical image of critical transitions, changes in their dynamics may carry valuable information about upcoming major changes.     

Early warning signals also precede non‐catastrophic transitions

Synthesis The quickly expanding literature on early warning signals for critical transitions in ecosystems suggests that critical slowing down is a key phenomenon to measure the distance to a tipping point in ecosystems. Such work is broadly misinterpreted as showing that slowing down is specific to tipping points. In this contribution, we show why this is not the case. Early warning signals based on critical slowing down indicate a broader class of situations where a system becomes increasingly sensitive to perturbations. Ecosystem responses to external changes can surprise us by their abruptness and irreversibility. Models have helped identifying indicators of impending catastrophic shifts, referred to as ‘generic early warning signals’. These indicators are linked to a phenomenon known as ‘critical slowing down’ which describes the fact that the recovery rate of a system after a perturbation decreases when the system approaches a bifurcation – such as the classical fold bifurcation associated to catastrophic shifts. However, contrary to what has sometimes been suggested in the literature, a decrease in recovery rate cannot be considered as specific to approaching catastrophic shifts. Here, we analyze the behavior of early warning signals based on critical slowing down in systems approaching a range of catastrophic and non‐catastrophic situations. Our results show that slowing down generally happens in situations where a system is becoming increasingly sensitive to external perturbations, independently of whether the impeding change is catastrophic or not. These results highlight that indicators specific to catastrophic shifts are still lacking. More importantly, they also imply that in systems where we have no reason to expect catastrophic transitions, slowing down may still be used in a more general sense as a warning signal for a potential decrease in stability.     

Ecosystems off track: rate‐induced critical transitions in ecological models

Theory suggests that gradual environmental change may erode the resilience of ecosystems and increase their susceptibility to critical transitions. This notion has received a lot of attention in ecology in recent decades. An important question receiving far less attention is whether ecosystems can cope with the rapid environmental changes currently imposed. The importance of this question was recently highlighted by model studies showing that elevated rates of change may trigger critical transitions, whereas slow environmental change would not. This paper aims to provide a mechanistic understanding of these rate‐induced critical transitions to facilitate identification of rate sensitive ecosystems. Analysis of rate sensitive ecological models is challenging, but we demonstrate how rate‐induced transitions in an elementary model can still be understood. Our analyses reveal that rate‐induced transitions 1) occur if the rate of environmental change is high compared to the response rate of ecosystems, 2) are driven by rates, rather than magnitudes, of change and 3) occur once a critical rate of change is exceeded. Disentangling rate‐induced transitions from classical transitions in observations would be challenging. However, common features of rate‐sensitive models suggest that ecosystems with coupled fast–slow dynamics, exhibiting repetitive catastrophic shifts or displaying periodic spatial patterns are more likely to be rate sensitive. Our findings are supported by experimental studies showing rate‐dependent outcomes. Rate sensitivity of models suggests that the common definition of ecological resilience is not suitable for a subset of real ecosystems and that formulating limits to magnitudes of change may not always safeguard against ecosystem degradation. Synthesis Understanding and predicting ecosystem response to environmental change is one of the key challenges in ecology. Model studies have suggested that slow, gradual environmental change beyond some critical threshold can trigger so‐called critical transitions and abrupt ecosystem degradation. An important question remains however whether ecosystems can cope with the ongoing rapid anthropogenic environmental changes to which they are currently imposed. In this study we demonstrate that in some ecological models elevated rates of change can trigger critical transitions even if slow environmental change of the same magnitude would not. Such rateinduced critical transitions in models suggest that concepts like resilience and planetary boundaries may not always be sufficient to explain and prevent ecosystem degradation.     

Scaling up the diversity–resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire

Understanding the mechanisms underlying ecosystem resilience – why some systems have an irreversible response to disturbances while others recover – is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large‐scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small‐scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four‐corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local‐scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues.     

Natural regeneration as a tool for large‐scale forest restoration in the tropics: prospects and challenges

A major global effort to enable cost‐effective natural regeneration is needed to achieve ambitious forest and landscape restoration goals. Natural forest regeneration can potentially play a major role in large‐scale landscape restoration in tropical regions. Here, we focus on the conditions that favor natural regeneration within tropical forest landscapes. We illustrate cases where large‐scale natural regeneration followed forest clearing and non‐forest land use, and describe the social and ecological factors that drove these local forest transitions. The self‐organizing processes that create naturally regenerating forests and natural regeneration in planted forests promote local genetic adaptation, foster native species with known traditional uses, create spatial and temporal heterogeneity, and sustain local biodiversity and biotic interactions. These features confer greater ecosystem resilience in the face of future shocks and disturbances. We discuss economic, social, and legal issues that challenge natural regeneration in tropical landscapes. We conclude by suggesting ways to enable natural regeneration to become an effective tool for implementing large‐scale forest and landscape restoration. Major research and policy priorities include: identifying and modeling the ecological and economic conditions where natural regeneration is a viable and favorable land‐use option, developing monitoring protocols for natural regeneration that can be carried out by local communities, and developing enabling incentives, governance structures, and regulatory conditions that promote the stewardship of naturally regenerating forests. Aligning restoration goals and practices with natural regeneration can achieve the best possible outcome for achieving multiple social and environmental benefits at minimal cost.     

A new approach for rapid detection of nearby thresholds in ecosystem time series

Massive changes to ecosystems sometimes cross thresholds from which recovery can be difficult, expensive and slow. These thresholds are usually discovered in post hoc analyses long after the event occurred. Anticipating these changes prior to their occurrence could give managers a chance to intervene. Here we present a novel approach for anticipating ecosystem thresholds that combines resilience indicators with Quickest detection of change points. Unlike existing methods, the Quickest detection method is updated every time a data point arrives, and minimizes the time to detect an approaching threshold given the users’ tolerance for false alarms. The procedure accurately detected an impending regime shift in an experimentally manipulated ecosystem. An ecosystem model was used to determine if the method can detect an approaching threshold soon enough to prevent a regime shift. When the monitored variable was directly involved in the interaction that caused the regime shift, detection was quick enough to avert collapse. When the monitored variable was only indirectly linked to the critical transition, detection came too late. The procedure is useful for assessing changes in resilience as ecosystems approach thresholds. However some thresholds cannot be detected in time to prevent regime shifts, and surprises will be inevitable in ecosystem management.     

Linking variability of tree water use and growth with species resilience to environmental changes

Tree growth is an indicator of tree vitality and its temporal variability is linked to species resilience to environmental changes. Second-order statistics that quantify the cross-scale temporal variability of ecophysiological time series (statistical memory) could provide novel insights into species resilience. Species with high statistical memory in their tree growth may be more affected by disturbances, resulting in lower overall resilience and higher vulnerability to environmental changes. Here, we assessed the statistical memory, as quantified with the decay in standard deviation with increasing time scale, in tree water use and growth of co-occurring European larch Larix decidua and Norway spruce Picea abies along an elevational gradient in the Swiss Alps using measurements of stem radius changes, sap flow and tree-ring widths. Local-scale interspecific differences between the two conifers were further explored at the European scale using data from the International Tree-Ring Data Bank. Across the analysed elevational gradient, tree water use showed steeper variability decay with increasing time scale than tree growth, with no significant interspecific differences, highlighting stronger statistical memory in tree growth processes. Moreover, Norway spruce displayed slower decay in growth variability with increasing time scale (higher statistical memory) than European larch; a pattern that was also consistent at the European scale. The higher statistical memory in tree growth of Norway spruce in comparison to European larch is indicative of lower resilience of the former in comparison to the latter, and could potentially explain the occurrence of European larch at higher elevations at the Alpine treeline. Single metrics of resilience cannot often summarize the multifaceted aspects of ecosystem functioning, thus, second-order statistics that quantify the strength of statistical memory in ecophysiological time series could complement existing resilience indicators, facilitating the assessment of how environmental changes impact forest growth trajectories and ecosystem services.     

Evaluation for regional ecosystem health: methodology and research progress

The evaluation for ecosystem health is one of the hotspots in the fields of macro-ecology and ecosystem management. Conducting analysis at the regional scale is an important direction for evaluating ecosystem health. Changing the spatial scale from the local to the regional level leads to great differences in targets and methodologies for ecosystem health evaluation and creates a new direction for regional ecosystem health research. Compared with the ecosystem health at the local scale, which refers to a single ecosystem type, the regional ecosystem health focuses on the health conditions and spatial patterns of different ecosystem types. However, there has been little attention paid to this very research up to now. Based on the progress on ecosystem health studies at the regional scale, the study reported in this article aims to discuss the implications of the conception of regional ecosystem health and to put forward a methodology for evaluating the regional ecosystem health. The main results include: (1) there is a significant scaling effect on the ecosystem health analysis, and the regional level is the key scale used to focus on the correlation between spatially neighboring ecosystems in terms of ecosystem health; (2) regional ecosystem health can be defined through 4 aspects, i.e., vigor, organization, resilience, and ecosystem service functions; (3) the basic evaluation objects of the regional ecosystem health is spatial entity, which is the matrix of different ecosystem types; (4) indicator system method is the only approach to evaluate regional ecosystem health; (5) the absolute thresholds of the evaluation indicators for the regional ecosystem health do not exist; the aim of the evaluation is to discuss the temporal dynamic changes and spatial differences of health conditions rather than to ascertain whether a region is healthy or not in view of ecological sustainability; and (6) the integration of evaluation results at multispatial scales, the application of this methodology in the landscape ecology, and the utilization of geographic information systems (GIS), remote sensing (RS), and Global Positioning Systems (GPS) technologies are the main directions for further research.     

基于临界慢化模型和长时间序列叶面积指数的植被及其恢复力遥感监测研究——以三峡库区为例

基于临界慢化模型,利用长时间序列叶面积指数(GLASS LAI)数据,进行时间序列分解后,计算了LAI及其时间自相关指数作为指标,对三峡库区植被及其恢复力进行监测,通过案例模型对临界慢化模型精度进行了验证,分析了三峡库区植被及其植被恢复力的时空分布特征,探索基于临界慢化模型的植被恢复力遥感定量估算方法的适用性。结果表明：(1)2000—2018年三峡库区LAI平均值为3.4,重庆段LAI较低,湖北段LAI较高;三峡库区LAI整体呈上升趋势,重庆段LAI呈现降低趋势,显著下降区域占重庆段面积的21.75%,湖北段LAI呈现升高趋势,显著上升区域占湖北段面积的21.22%;(2)2000—2018年三峡库区重庆市北碚区、大渡口区、渝北区植被恢复力较低,宜昌市兴山县、夷陵区、点军区植被恢复力较高;(3)模型精度方面,在两个地质灾害扰动事件中案例模型结果与临界慢化模型结果呈现较高的一致性。本文对三峡库区2000—2018年的植被恢复力进行了定量估算,同时通过案例模型对临界慢化模型在恢复力监测上的有效性进行了验证,为三峡库区制定相应生态环境管理决策提供理论基础,为保障西南地区生态安全提供决策依据...     

Genetic resilience of <Emphasis Type="Italic">Daphnia</Emphasis> populations following experimental removal of introduced fish

Dramatic changes in environmental conditions or community composition may impose severe selective pressures on resident populations. These changes in the selective regime can lead to demographic bottlenecks or local extinction. The consequence of demographic contraction is often a reduction of standing genetic variation. Since the level of adaptive genetic variation in populations plays an important role in persistence and adaptive response, understanding genetic resilience and the time course for re-establishment of genetic diversity following demographic perturbations is a critical component of assessing the consequences of changing environments. The introduction of nonnative fish into historically fishless lakes is a particularly dramatic environmental change frequently contributing to demographic bottlenecks and local extinction of native populations. We examine the quantitative- and molecular-genetic recovery of two alpine populations of the zooplankton Daphnia melanica from the Sierra Nevada, California, USA. These populations were extirpated by introduced salmonids and subsequently re-established following the experimental removal of nonnative fish. We obtained data for nuclear and mitochondrial markers and conducted a common-garden experiment to assess the levels of molecular- and quantitative-genetic variation following experimental fish removal. Reestablished D. melanica populations attained levels of nuclear genetic diversity only slightly lower than surrounding fishless populations in the first year following fish removal and substantial mitochondrial and quantitative-genetic diversity within 8 years. This high level of genetic resilience was likely facilitated by multiple sources of genetic variation, including immigration from neighboring populations and hatching from a local reservoir of diapausing eggs. Our results highlight the genetic resilience of taxa with reservoirs of genetic variation in seed or egg banks.