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Geology topics

Michael C. Runge

Publications and source records attributed to Michael C. Runge.

At least 109 records · Page 6Linked to original sources
USGS2017

New interventions are needed to save coral reefs

Since 2014, coral reefs worldwide have been subjected to the most extensive, prolonged and damaging heat wave in recorded history1. Large sections of Australia’s Great Barrier Reef (GBR) bleached in response to heat stress in 2016 and 2017 — the first back-to-back event on record. Such severe coral bleaching results in widespread loss of reef habitat and biodiversity. Globally, we are facing catastrophic decline of these ecosystems, which sustain services valued at around $US 10 trillion per year2, are home to over a million species3, and feed and support the livelihoods of hundreds of millions of people4. Model predictions indicate that mass coral bleaching could become the new norm by 2050 (ref. 5). Critically, even if global warming can be kept within 1.5⁰C above preindustrial levels, shallow tropical seas would warm at least 0.4°C in coming decades, triggering frequent bleaching of the most sensitive habitat-forming coral species6. This outlook poses a time-critical decision challenge for management and conservation. Existing conservation approaches, despite innovative governance arrangements7, could simply become insufficient to protect coral reefs under any expected climate future. Thus, for coral reefs to remain resilient and their services sustained, we argue that new and potentially riskier interventions must be implemented alongside conventional management efforts and strong action to curb global warming. We build the case for this strategy below.

Nature Ecology & Evolution↗
USGS2017

Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach

Every year, migratory species undertake seasonal movements along different pathways between discrete regions and habitats. The ability to assess the relative demographic contributions of these different habitats and pathways to the species’ overall population dynamics is critical for understanding the ecology of migratory species, and also has practical applications for management and conservation. Metrics for assessing habitat contributions have been well-developed for metapopulations, but an equivalent metric is not currently available for migratory populations. Here, we develop a framework for estimating the demographic contributions of the discrete habitats and pathways used by migratory species throughout the annual cycle by estimating the per capita contribution of cohorts using these locations. Our framework accounts for seasonal movements between multiple breeding and non-breeding habitats and for both resident and migratory cohorts. We illustrate our framework using a hypothetical migratory network of four habitats, which allows us to better understand how variations in habitat quality affect per capita contributions. Results indicate that per capita contributions for any habitat or pathway are dependent on habitat-specific survival probabilities in all other areas used as part of the migratory circuit, and that contribution metrics are spatially linked (e.g. reduced survival in one habitat also decreases the contribution metric for other habitats). Our framework expands existing theory on the dynamics of spatiotemporally structured populations by developing a generalized approach to estimate the habitat- and pathway-specific contributions of species migrating between multiple breeding and multiple non-breeding habitats for a range of life histories or migratory strategies. Most importantly, it provides a means of prioritizing conservation efforts towards those migratory pathways and habitats that are most critical for the population viability of migratory species.

Ecography↗
USGS2017

Decision support frameworks and tools for conservation

The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

Conservation Letters↗
USGS2017

Essential information: Uncertainty and optimal control of Ebola outbreaks

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Proceedings of the National Academy of Sciences of↗
USGS2017

Two-step adaptive management for choosing between two management actions

Adaptive management is widely advocated to improve environmental management. Derivations of optimal strategies for adaptive management, however, tend to be case specific and time consuming. In contrast, managers might seek relatively simple guidance, such as insight into when a new potential management action should be considered, and how much effort should be expended on trialing such an action. We constructed a two-time-step scenario where a manager is choosing between two possible management actions. The manager has a total budget that can be split between a learning phase and an implementation phase. We use this scenario to investigate when and how much a manager should invest in learning about the management actions available. The optimal investment in learning can be understood intuitively by accounting for the expected value of sample information, the benefits that accrue during learning, the direct costs of learning, and the opportunity costs of learning. We find that the optimal proportion of the budget to spend on learning is characterized by several critical thresholds that mark a jump from spending a large proportion of the budget on learning to spending nothing. For example, as sampling variance increases, it is optimal to spend a larger proportion of the budget on learning, up to a point: if the sampling variance passes a critical threshold, it is no longer beneficial to invest in learning. Similar thresholds are observed as a function of the total budget and the difference in the expected performance of the two actions. We illustrate how this model can be applied using a case study of choosing between alternative rearing diets for hihi, an endangered New Zealand passerine. Although the model presented is a simplified scenario, we believe it is relevant to many management situations. Managers often have relatively short time horizons for management, and might be reluctant to consider further investment in learning and monitoring beyond collecting data from a single time period.

Ecological Applications↗
USGS2017

Evaluation of harvest and information needs for North American sea ducks

Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini ). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider ( Somateria mollissima dresseri ), eastern and western populations of black scoter ( Melanitta americana ) and surf scoter ( M . perspicillata ), and continental populations of white-winged scoter ( M . fusca ) and long-tailed duck ( Clangula hyemalis ). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth ( r max ), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5–7% and 19–26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22–68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demographic parameters to prioritize information needs. We found that uncertainty in overall fecundity had more influence on comparisons of allowable and observed harvest than adult survival or observed harvest for all species except long-tailed duck. Although adult survival was characterized by less uncertainty than individual components of fecundity, it was identified as a high priority information need given the sensitivity of growth rate and allowable harvest to this parameter. Uncertainty about population size was influential in the comparison of observed and allowable harvest for 5 of the 6 populations where it factored into the assessment. While this assessment highlights a high degree of uncertainty in allowable harvest, it provides a framework for integration of improved data from future research and monitoring. It could also serve as the basis for harvest strategy development as management objectives and regulatory alternatives are specified by the management community.

PLoS ONE↗
USGS2017

Status and threats analysis for the Florida manatee ( Trichechus manatus latirostris ), 2016

Trichechus manatus (West Indian manatee), especially T. m. latirostris , the Florida subspecies, has been the focus of conservation efforts and extensive research since its listing under the Endangered Species Act of 1973. To determine the status of, and severity of threats to, the Florida manatee, a comprehensive revision and update of the manatee Core Biological Model was completed and used to perform a population viability analysis for the Florida manatee. The probability of the Florida manatee population falling below 500 adults on either the Gulf or East coast within the next 100 years was estimated to be 0.42 percent. This risk of quasi-extinction is low because the estimated adult survival rates are high, the current population size is greater than 2,500 on each coast, and the estimated carrying capacity for manatees is much larger than the current abundance estimates in all four regions of Florida. Three threats contribute in roughly equal measures to the risk of quasi-extinction: watercraft-related mortality, red-tide mortality, and loss of warm-water habitat. Only an increase in watercraft-related mortality has the potential to substantially increase the risk of quasi-extinction at the statewide or coastal level. Expected losses of warm-water habitat are likely to cause a major change in the distribution of the population from the regions where manatees rely heavily on power plant effluents for warmth in winter (Southwest and Atlantic regions) to the regions where manatees primarily use natural springs in winter (Northwest and Upper St. Johns regions). The chances are nearly 50 percent that manatee populations in the Southwest and Atlantic regions will decrease from their 2011 levels by at least 30 percent over the next century. A large number of scenarios were examined to explore the possible effects of potential emerging threats, and in most of them, the risk of quasi-extinction at the coastal scale within 100 years did not rise above 1 percent. The four exceptions are scenarios in which the rate of watercraft-related mortality increases, carrying capacity is only a fraction of the current estimates, a new chronic source of mortality emerges, or multiple threats emerge in concert. Even in these scenarios, however, the risk of falling below 500 adults on either the East coast or the Gulf coast within 100 years from 2011 is less than 10 percent. High adult survival provides the population with strong resilience to a variety of current and future threats. On the basis of these analyses, we conclude that if these threats continue to be managed effectively, manatees are likely to persist on both coasts of Florida and remain an integral part of the coastal Florida ecosystem through the 21st century. If vigilance in management is reduced, however, the scenarios in which manatees could face risk of decline become more likely.

Florida↗
USGS2017

Harvesting wildlife affected by climate change: a modelling and management approach for polar bears

The conservation of many wildlife species requires understanding the demographic effects of climate change, including interactions between climate change and harvest, which can provide cultural, nutritional or economic value to humans. We present a demographic model that is based on the polar bear Ursus maritimus life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity ( K ). Using this model, we develop a state-dependent management framework to calculate a harvest level that (i) maintains a population above its maximum net productivity level (MNPL; the population size that produces the greatest net increment in abundance) relative to a changing K , and (ii) has a limited negative effect on population persistence. Our density-dependent relationships suggest that MNPL for polar bears occurs at approximately 0·69 (95% CI = 0·63–0·74) of K . Population growth rate at MNPL was approximately 0·82 (95% CI = 0·79–0·84) of the maximum intrinsic growth rate, suggesting relatively strong compensation for human-caused mortality. Our findings indicate that it is possible to minimize the demographic risks of harvest under climate change, including the risk that harvest will accelerate population declines driven by loss of the polar bear's sea-ice habitat. This requires that (i) the harvest rate – which could be 0 in some situations – accounts for a population's intrinsic growth rate, (ii) the harvest rate accounts for the quality of population data (e.g. lower harvest when uncertainty is large), and (iii) the harvest level is obtained by multiplying the harvest rate by an updated estimate of population size. Environmental variability, the sex and age of removed animals and risk tolerance can also affect the harvest rate. Synthesis and applications . We present a coupled modelling and management approach for wildlife that accounts for climate change and can be used to balance trade-offs among multiple conservation goals. In our example application to polar bears experiencing sea-ice loss, the goals are to maintain population viability while providing continued opportunities for subsistence harvest. Our approach may be relevant to other species for which near-term management is focused on human factors that directly influence population dynamics within the broader context of climate-induced habitat degradation.

Journal of Applied Ecology↗
USGS2017

Value of information analysis as a decision support tool for biosecurity

This chapter demonstrates the economic concept of ‘value of information’(VOI), and how biosecurity managers can use VOI analysis to decide whether or not to reduce uncertainty by collecting additional information through monitoring, experimentation, or some other form of research. We first explore how some uncertainties may be scientifically interesting to resolve, but ultimately irrelevant to decision-making. We then develop a prototype model where a manager must choose between eradication or containment of an infestation. Eradication is more cost-effective for smaller infestations, but once the extent reaches a certain size it becomes more cost-effective to contain. When choosing between eradication and containment, how much does knowing the extent of the infestation more exactly improve the outcome of the decision? We calculate the expected value of perfect information (EVPI) about the extent, which provides an upper limit for the value of reducing uncertainty. We then illustrate the approach using the example of red imported fire ant management in south-east Queensland. We calculate the EVPI for three different uncertain variables: the extent of the infestation, the sensitivity (true positive rate) of remote sensing, and the efficacy of baiting.

Book chapter↗
USGS2017

Experts correctly describe demography associated with historical decline of the endangered Indiana bat, but not recent period of stationarity

Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat ( Myotis sodalis ) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.

PeerJ↗
USGS2017

Allowable take of a population of red-winged blackbirds in the northern Great Plains

Red-winged blackbirds ( Agelaius phoeniceus ) are protected under the Migratory Bird Treaty Act (MBTA), which has provisions against take. Blackbirds may be taken legally without a Federal permit, however, under an existing Depredation Order (50 CFR 21.43), which allows for take of blackbirds that are in the process of doing, or about to do, agricultural damage. Modeling the effect of take on blackbird population allows us to balance the conservation protections of the MBTA with the protection of agricultural interests. A quantitative framework based on harvest theory, demography, and population status has been used to assess the allowable take of a number of species of birds under the MBTA. In this chapter, we calculate allowable levels of take for two populations of red-winged blackbirds in the northern Great Plains from estimates of intrinsic growth rate and population size.

Book chapter↗
USGS2016

Cross-seasonal effects on waterfowl productivity: Implications under climate change

Previous efforts to relate winter-ground precipitation to subsequent reproductive success as measured by the ratio of juveniles to adults in the autumn failed to account for increased vulnerability of juvenile ducks to hunting and uncertainty in the estimated age ratio. Neglecting increased juvenile vulnerability will positively bias the mean productivity estimate, and neglecting increased vulnerability and estimation uncertainty will positively bias the year-to-year variance in productivity because raw age ratios are the product of sampling variation, the year-specific vulnerability, and year-specific reproductive success. Therefore, we estimated the effects of cumulative winter precipitation in the California Central Valley and the Mississippi Alluvial Valley on pintail ( Anas acuta ) and mallard ( Anas platyrhnchos ) reproduction, respectively, using hierarchical Bayesian methods to correct for sampling bias in productivity estimates and observation error in covariates. We applied the model to a hunter-collected parts survey implemented by the United States Fish and Wildlife Service and band recoveries reported to the United States Geological Survey Bird Banding Laboratory using data from 1961 to 2013. We compared our results to previous estimates that used simple linear regression on uncorrected age ratios from a smaller subset of years in pintail (1961–1985). Like previous analyses, we found large and consistent effects of population size and wetland conditions in prairie Canada on mallard productivity, and large effects of population size and mean latitude of the observed breeding population on pintail productivity. Unlike previous analyses, we report a large amount of uncertainty in the estimated effects of wintering-ground precipitation on pintail and mallard productivity, with considerable uncertainty in the sign of the estimated main effect, although the posterior medians of precipitation effects were consistent with past studies. We found more consistent estimates in the sign of an interaction effect between population size and precipitation, suggesting that wintering-ground precipitation has a larger effect in years of high population size, especially for pintail. When we used the estimated effects in a population model to derive a sustainable harvest and population size projection (i.e., a yield curve), there was considerable uncertainty in the effect of increased or decreased wintering-ground precipitation on sustainable harvest potential and population size. These results suggest that the mechanism of cross-seasonal effects between winter habitat and reproduction in ducks occurs through a reduction in the strength of density dependence in years of above-average wintering-ground precipitation. We suggest additional investigation of the underlying mechanisms and that habitat managers and decision-makers consider the level of uncertainty in these estimates when attempting to integrate habitat management and harvest management decisions. Collection of annual data on the status of wintering-ground habitat in a rigorous sampling framework would likely be the most direct way to improve understanding of mechanisms and inform management.

Journal of Wildlife Management↗
USGS2016

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty 1 , 2 . Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies 3 . Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

Nature Climate Change↗
USGS2016

Decision analysis to support development of the Glen Canyon Dam long-term experimental and management plan

The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, National Park Service, and Argonne National Laboratory, completed a decision analysis to use in the evaluation of alternatives in the Environmental Impact Statement concerning the long-term management of water releases from Glen Canyon Dam and associated management activities. Two primary decision analysis methods, multicriteria decision analysis and the expected value of information, were used to evaluate the alternative strategies against the resource goals and to evaluate the influence of uncertainty. A total of 18 performance metrics associated with 8 out of 12 resource goals (fundamental objectives) were developed by the Bureau of Reclamation and National Park Service in partnership with subject-matter teams composed of Federal, State, tribal, and private experts. A total of 19 long-term strategies associated with 7 alternatives were developed by the Bureau of Reclamation, National Park Service, Argonne National Laboratory, U.S. Geological Survey, and Cooperating Agencies. The 19 long-term strategies were evaluated against the 18 performance metrics using a series of coupled simulation models, taking into account the effects of several important sources of uncertainty. A total of 27 Federal, State, tribal, and nongovernmental agencies were invited by the Assistant Secretary of Interior to participate in a swing-weighting exercise to understand the range of perspectives about how to place relative value on the resource goals and performance metrics; 14 of the 27 chose to participate. The results of the swing-weighting exercise were combined with the evaluation of the alternatives to complete a multicriteria decision analysis. The effects of uncertainty on the ranking of long-term strategies were evaluated through calculation of the value of information. The alternatives and their long-term strategies differed across performance metrics, producing unavoidable tradeoffs; thus, there was no long-term strategy that was dominated by another across all performance metrics. When the performance of each alternative was weighted across performance metrics, three alternatives (B, D, and G) were top-ranked depending on the set of weights proposed: Alternative B was favored by those stakeholders that placed a high value on hydropower; Alternative G was favored by those stakeholders that placed a high value on the restoration of natural processes, like beachbuilding and natural vegetation; and Alternative D was favored by the remaining stakeholders. Surprisingly, these rankings were not sensitive to the critical uncertainties that were evaluated; that is, the choice of a preferred long-term strategy was sensitive to the value-based judgment about how to place relative weight on the resource goals but was not sensitive to the uncertainties in the system dynamics that were evaluated in this analysis. The one area of uncertainty that did slightly affect the ranking of alternatives was the long-term pattern of hydrological input; because of this sensitivity, some attention to the possible effects of climate change is warranted. The results of the decision analysis are meant to serve as only one of many sources of information that can be used to evaluate the alternatives proposed in the Environmental Impact Statement. These results only focus on those resource goals for which quantitative performance metrics could be formulated and evaluated; there are other important aspects of the resource goals that also need to be considered. Not all the stakeholders who were invited to participate in the decision analysis chose to do so; thus, the Bureau of Reclamation, National Park Service, and U.S. Department of Interior may want to consider other input.

Arizona↗
USGS2016

Expert elicitation of population-level effects of disturbance

Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales ( Eubalaena glacialis ). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.

Book chapter↗
USGS2016

Decision-making for foot-and-mouth disease control: Objectives matter

Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.

Epidemics↗
USGS2015

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Conservation Biology↗