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Results for “Ecological Complexity”

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At least 253 records · Page 14Linked to original sources
USGS2025

A partner-driven decision support model to inform the reintroduction of bull trout

Assessments of species reintroductions involve a series of complex decisions that include human perspectives and ecological contexts. Here, we present a reintroduction assessment involving bull trout ( Salvelinus confluentus ) using a structured decision-making process. We approached this assessment by engaging partners representing public utilities, government agencies, and Tribes with shared interests in a potential reintroduction. These individuals identified objectives, decision alternatives, and ecological scenarios that were incorporated into a co-produced simulation-based model of potential reintroduction outcomes. The model included mathematical representations of habitat availability, life history expression, and assumptions regarding constraints on potential bull trout populations. Within each recipient stream, partners chose to explore a wide range of decision alternatives and simulated scenarios affecting reintroduction success. Results suggested that 1) reintroductions using eggs or adults were most optimal, 2) adding more individuals resulted in diminishing returns, 3) access to migratory habitat could improve success, and 4) the diversity of opportunities for life history expression led to improved reintroduction opportunities. In addition, modeled scenarios indicated some recipient streams consistently produced lower abundance of reintroduced bull trout. This work contributes a novel example to a growing portfolio of reintroduction assessments that may inform future conservation for bull trout and many other species facing similar challenges.

Washington↗
USGS2011

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (∼25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Ecology↗
USGS2006

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks. ?? 2006 by the Ecological Society of America.

Ecological Applications↗
USGS2009

Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor

Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor, estimates the ecological risks associated with colonization of the United States by nine large constrictors. The nine include the world's four largest snake species (Green Anaconda, Eunectes murinus; Indian or Burmese Python, Python molurus; Northern African Python, Python sebae; and Reticulated Python, Broghammerus reticulatus), the Boa Constrictor (Boa constrictor), and four species that are ecologically or visually similar to one of the above (Southern African Python, Python natalensis; Yellow Anaconda, Eunectes notaeus; DeSchauensee's Anaconda, Eunectes deschauenseei; and Beni Anaconda, Eunectes beniensis). At present, the only probable pathway by which these species would become established in the United States is the pet trade. Although importation for the pet trade involves some risk that these animals could become established as exotic or invasive species, it does not guarantee such establishment. Federal regulators have the task of appraising the importation risks and balancing those risks against economic, social, and ecological benefits associated with the importation. The risk assessment quantifies only the ecological risks, recognizing that ecosystem processes are complex and only poorly understood. The risk assessment enumerates the types of economic impacts that may be experienced, but leaves quantification of economic costs to subsequent studies. Primary factors considered in judging the risk of establishment were: (1) history of establishment in other countries, (2) number of each species in commerce, (3) suitability of U.S. climates for each species, and (4) natural history traits, such as reproductive rate and dispersal ability, that influence the probability of establishment, spread, and impact. In addition, the risk assessment reviews all management tools for control of invasive giant constrictor populations. There is great uncertainty about many aspects of the risk assessment; the level of uncertainty is estimated separately for each risk component. Overall risk was judged to be high for five of the giant constrictors studied, and medium for the other four species. Because all nine species shared a large number of natural history traits that promote invasiveness or impede population control, none of the species was judged to be of low risk.

Open-File Report↗
USGS2017

The value of information for woodland management: Updating a state–transition model

Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.

Victoria↗
USGS2024

Characterization of the water resources of the Pamunkey River watershed in Virginia—A review of water science, management, and traditional ecological knowledge

In central Virginia, the Pamunkey Indian Tribe and Reservation are facing increasingly complex water resource issues related to quantity and quality. Documentation of surface-water, groundwater, water quality, land subsidence, sea-level rise, and river ecology issues in the Pamunkey River watershed and incorporation of traditional ecological knowledge into these research topics may improve understanding of the water resources broadly. This report summarizes the relevant traditional ecological knowledge and scientific literature to elucidate gaps in the total combined knowledge of a suite of water science topics concerning the Pamunkey River watershed. This suite of water science topics includes some of the issues that the Pamunkey Indian Tribe and Reservation are facing within the watershed: fragmentation of streams and management of streamflow, flooding, degrading water quality, groundwater extraction, relative sea-level rise, rapid changes in ecosystems, loss of ecological and biological diversity, and climate change. Gaps in total combined knowledge are pervasive throughout each of these water resource topics. Identifying these knowledge gaps can help inform future research and management strategies.

Virginia↗
USGS2016

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Ecological Modelling↗
USGS2016

Transformative environmental governance

Transformative governance is an approach to environmental governance that has the capacity to respond to, manage, and trigger regime shifts in coupled social-ecological systems (SESs) at multiple scales. The goal of transformative governance is to actively shift degraded SESs to alternative, more desirable, or more functional regimes by altering the structures and processes that define the system. Transformative governance is rooted in ecological theories to explain cross-scale dynamics in complex systems, as well as social theories of change, innovation, and technological transformation. Similar to adaptive governance, transformative governance involves a broad set of governance components, but requires additional capacity to foster new social-ecological regimes including increased risk tolerance, significant systemic investment, and restructured economies and power relations. Transformative governance has the potential to actively respond to regime shifts triggered by climate change, and thus future research should focus on identifying system drivers and leading indicators associated with social-ecological thresholds.

Annual Review of Environment and Resources↗
USGS2016

Flexible characterization of animal movement pattern using net squared displacement and a latent state model

Background Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises ( Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.

Movement Ecology↗
USGS2021

Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem

Identifying and understanding status and trends in ecological indicators motivates continual monitoring over decades. Many programs rely on probability surveys and their companion design-based estimators for status assessments (e.g. Horvitz–Thompson). Design-based estimators do not easily extend to trend estimation nor situations with observation errors. Field-based monitoring efforts inevitably have turnover of field crew members which may affect consistency and accuracy of data collection over time. Additionally, design-based estimators ignore the complexities of spatial and temporal heterogeneity in an ecological indicator and how this variability may be linked to environmental or biological dynamics. We propose monitoring programs should re-evaluate their prescribed statistical methods, consider model-based approaches and adapt their sampling designs as needed to improve inferences. The Greater Yellowstone Ecosystem, home to two of the most iconic U.S. National Parks, has experienced significant declines in whitebark pine Pinus albicaulis communities due to forest pathogens, insect outbreaks, wildland fires and drought. Whitebark pine is a keystone species found in mountainous environments throughout the Western U.S. and Canada. We assessed the design-based ratio estimator originally recommended for estimating prevalence of white pine blister rust Cronartium ribicola . We compared the design-based estimator to a model-based approach that accounts for the sampling design, imperfect detection and allows for infection probabilities to vary over space and time. Ignoring observation errors led to lower estimated prevalence of white pine blister rust in the general population. Using model-based approaches, we found that the probability of infection has increased since 2004. However, overall prevalence likely has not changed because of the mountain pine beetle Dendroctonus ponderosae -induced shift towards smaller diameter trees that have a lower probability of infection compared to their larger cohorts. Synthesis and Applications . Using a design-based approach to detect change in ecological indicators falls short because of the inability to account for observation errors or to explore environmental or biological factors explaining temporal dynamics. Inherently understanding the mechanisms leading to changes in an ecological indicator over time informs potential management actions. Our assessment underscores the need for continued evaluation and updating of a monitoring program's sampling design and analytical procedures to maintain relevancy.

Wyoming↗
USGS2023

Seven dam challenges for migratory fish: Insights from the Penobscot River

More than a century of impoundments in the Penobscot River, Maine, USA, has contributed to population declines in migratory fish in the system. A decade of change, research, and monitoring has revealed direct and indirect ways that dams have influenced the river habitat, connectivity for migratory fish, and the food web. The removal of two main-stem dams (in 2012 and 2013) and bolstering of fish passage have been part of coordinated restoration efforts in the watershed. Integral to this undertaking was support for short- and long-term monitoring and research that included physical habitat, fish passage, and broad scale ecological assessments. Herein we discuss the seven interconnected and complex ways that dams have affected the Penobscot River ecosystem, particularly for migratory fish. These include familiar influences ascribed to dams: i) impaired access to habitat, ii) injury and mortality, and iii) delays of migration. Other ecological influences are less studied and more subtle: iv) facilitation of predation, v) community shifts, and vi) demographic shifts. Lastly, dams result in vii) a loss of ecosystem services that would otherwise be intact in an unimpounded system. We draw on both direct examples from the Penobscot River and broader information to characterize how impoundments have transformed this ecosystem for more than a century. Recent dam removals and mitigation efforts have reestablished some of these ecological functions.

Maine↗
USGS2020

Ecology of influenza A viruses in wild birds and wetlands of Alaska

Alaska represents a globally important region for the ecology of avian-origin influenza A viruses (IAVs) given expansive wetlands in this region which serve as habitat for numerous hosts of IAVs that disperse among four continents during the annual cycle. Extensive sampling of wild birds for IAVs in Alaska since 1991 has greatly extended inference regarding intercontinental viral exchange between North America and East Asia and the importance of Beringian endemic species to IAV ecology within this region. Data on IAVs in aquatic birds inhabiting Alaska has also been useful for helping to establish global patterns of prevalence in wild birds and viral dispersal across the landscape. In this review, we summarize main findings from investigations of IAVs in wild birds and wetlands of Alaska with the aim of providing readers with an understanding of viral ecology within this region. More specifically, we review viral detections, evidence of IAV exposure, and genetic characterization of isolates derived from wild bird samples collected in Alaska by host taxonomy. Additionally, we provide a short overview of wetland complexes within Alaska that may be important to IAV ecology at the continental scale.

Alaska↗
USGS2023

Ecological significance of Wild Huckleberries (Vaccinium membranaceum)

Wild huckleberry ( Vaccinium globare/membranaceum complex) is a keystone species in the Pacific Northwest of the United States. The fruits are a primary food source for grizzly bears and other wildlife, as well as an important traditional and contemporary human food. Huckleberry shrubs also provide cover and nesting habitat for many animal species, including small mammals and birds. The flowers provide nectar and pollen with crucial connections between bumble bees ( Bombus species) and huckleberries. Native bee pollination is essential for successful berry development. Huckleberries flower early in the growing season and are some of the only floral resources available when bumble bee queens first emerge from hibernation and need to collect pollen and nectar for nesting. One of these species, the Western bumble bee ( Bombus occidentalis ), is in review for listing under the U.S. Endangered Species Act. Future climate change has the potential to influence huckleberry distribution, productivity, and phenology. These potential changes could have wide-ranging implications because of the economic, cultural, and ecological importance of huckleberry.

Book chapter↗
USGS2024

Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability

1. Many ecological systems dominated by stochastic dynamics can produce complex time series that inherently limit forecast accuracy. The ‘intrinsic predictability’ of these systems can be approximated by a time series complexity metric called weighted permutation entropy (WPE). While WPE is a useful metric to gauge forecast performance prior to model building, it is sensitive to noise and may be biased depending on the length of the time series. Here, we introduce a simple randomized permutation test (rWPE) to assess whether a time series is intrinsically more predictable than white noise. 2. We apply rWPE to both simulated and empirical data to assess its performance and usefulness. To do this, we simulate population dynamics under various scenarios, including a linear trend, chaotic, periodic and equilibrium dynamics. We further test this approach with observed abundance time series for 932 species across four orders of animals from the Global Population Dynamics Database. Finally, using Adélie ( Pygoscelis adeliae ) and emperor penguin ( Aptenodytes forsteri ) time series as case studies, we demonstrate the application of rWPE to multiple populations for a single species. 3. We show that rWPE can determine whether a system is significantly more predictable than white noise, even with time series as short as 10 years that show an apparent trend under biologically realistic stochasticity levels. Additionally, rWPE has statistical power close to 100% when time series are at least 30 time steps long and show chaotic or periodic dynamics. Power decreases to ~10% under equilibrium dynamics, irrespective of time series length. Among four classes of animal taxa, mammals have the highest relative frequency (28%) of time series that are both longer than 30 time steps and indistinguishable from white noise in terms of complexity, followed by insects (16%), birds (16%) and bony fishes (11%). 4. rWPE is a straightforward and useful method widely applicable to any time series, including short ones. By informing forecasters of the inherent limitations to a system's predictability, it can guide a modeller's expectations for forecast performance.

Methods in Ecology and Evolution↗
USGS2020

Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada

Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.

Montana, British Columbia↗
USGS2012

A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews

The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.

Molecular Phylogenetics and Evolution↗
USGS2018

Developing a shared understanding of the Upper Mississippi River: the foundation of an ecological resilience assessment

The Upper Mississippi River System (UMRS) is a large and complex floodplain river ecosystem that spans the jurisdictions of multiple state and federal agencies. In support of ongoing ecosystem restoration and management by this broad partnership, we are undertaking a resilience assessment of the UMRS. We describe the UMRS in the context of an ecological resilience assessment. Our description articulates the temporal and spatial extent of our assessment of the UMRS, the relevant historical context, the valued services provided by the system, and the fundamental controlling variables that determine its structure and function. An important objective of developing the system description was to determine the simplest, adequate conceptual understanding of the UMRS. We conceptualize a simplified UMRS as three interconnected subsystems: lotic channels, lentic off-channel areas, and floodplains. By identifying controlling variables within each subsystem, we have developed a shared understanding of the basic structure and function of the UMRS, which will serve as the basis for ongoing quantitative evaluations of factors that likely contribute to the resilience of the UMRS. As we undertake the subsequent elements of a resilience assessment, we anticipate our improved understanding of interactions, feedbacks, and critical thresholds will assist natural resource managers to better recognize the system’s ability to adapt to existing and new stresses.

Ecology and Society↗
USGS2018

Enhancing quantitative approaches for assessing community resilience

Scholars from many different intellectual disciplines have attempted to measure, estimate, or quantify resilience. However, there is growing concern that lack of clarity on the operationalization of the concept will limit its application. In this paper, we discuss the theory, research development and quantitative approaches in ecological and community resilience. Upon noting the lack of methods that quantify the complexities of the linked human and natural aspects of community resilience, we identify several promising approaches within the ecological resilience tradition that may be useful in filling these gaps. Further, we discuss the challenges for consolidating these approaches into a more integrated perspective for managing social-ecological systems.

Journal of Environmental Management↗