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Several environmental policies strive to restore impaired ecosystems and could benefit from a consistent and transparent process-codeveloped with key stakeholders-to prioritize impaired ecosystems for restoration activities. The Clean Water Act, for example, establishes reallocation mechanisms to transfer ecosystem services from sites of disturbance to compensation sites to offset aquatic resource functions that are unavoidably lost through land development. However, planning for the prioritization of compensatory mitigation areas is often hampered by decision-making processes that fall into a myopic decision frame because they are not coproduced with stakeholders. In this study, we partnered with domain experts from the North Carolina Division of Mitigation Services to codevelop a real-world decision framework to prioritize catchments by potential for the development of mitigation projects following principles of a structured decision-making process and knowledge coproduction. Following an iterative decision analysis cycle, domain experts revised foundational components of the decision framework and progressively added complexity and realism as they gained additional insights or more information became available. Through the course of facilitated in-person and remote interactions, the codevelopment of a decision framework produced three main "breakthroughs" from the perspective of the stakeholder group: (a) recognition of the problem as a multiobjective decision driven by several values in addition to biogeophysical goals (e.g., functional uplift, restoring or enhancing lost functionality of ecosystems); (b) that the decision comprises a linked and sequential planning-to-implementation process; and (c) future risk associated with land-use and climate change must be considered. We also present an interactive tool for "on-the-fly" assessment of alternatives and tradeoff analysis, allowing domain experts to quickly test, react to, and revise prioritization strategies. The decision framework described in this study is not limited to the prioritization of compensatory mitigation activities across North Carolina but rather serves as a framework to prioritize a wide range of restoration, conservation, and resource allocation activities in similar environmental contexts across the nation.

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision-making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision-making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross-literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable.Los administradores ambientales y de los recursos y los practicantes de la conservación buscan frecuentemente contribuciones científicas para informar sus decisiones. Este sector de la ciencia sólo se vuelve práctico cuando lo incentivan los órganos decisorios que consideran vías alternas de acción. Muchos dentro de la comunidad científica equiparan abordar las necesidades científicas de los actores con la ciencia práctica como resultado. Sin embargo, no son todos los esfuerzos por abordar las necesidades científicas los que resultan en ciencia práctica, lo que sugiere que el uso sinónimo de estos dos constructos (ciencia práctica como resultado y abordar las necesidades científicas) no es trivial. Esto puede ocurrir cuando personas que dejan de lado a los órganos decisorios responsables de articular un problema prioritario de manejo y de especificar cómo la información científica anticipada servirá durante el proceso de decisión transmiten dichas necesidades. Sostenemos que los actores responsables de articular estas necesidades científicas y el proceso utilizado para identificarlos son factores decisivos en la capacidad de tener ciencia práctica como resultado, con un hincapié en la importancia que tiene examinar el origen y determinación de dichas necesidades. Con el deseo de mejorar la comunicación y la alfabetización transversal entre los científicos y los órganos decisorios, identificamos las categorías de actores que pueden declarar indebidamente las necesidades científicas (p. ej.: científicos aplicados con y sin afiliación regulatoria, personas influyentes externas, órganos decisorios renuentes, agentes suplentes de los órganos decisorios y representantes de organizaciones fronterizas). También destacamos la importancia de, y el acercamiento general a, realizar análisis de las necesidades o análisis de las brechas como método para identificar las necesidades científicas prioritarias. Concluimos que las estipulaciones básicas para legitimar la ciencia práctica, como la declaración de las decisiones de interés que impulsan a las necesidades científicas y el uso de un proceso firme para identificar las brechas informativas prioritarias, no siempre se cumplen y requieren una verificación. Para mitigar estas deficiencias, formulamos algunas propuestas prácticas a consideración de los científicos aplicados, órganos decisorios, entidades de financiamiento para la investigación y organizaciones fronterizas para propiciar las condiciones que resultan en una producción científica realmente práctica.保护实践者、自然资源管理者和环境管理者常常寻求科学贡献来为决策提供信息。然而, 只有在决策者考虑替代性行动方案的情况下, 这套科学才具有可操作性。科学界的许多人将解决利益相关者的科学需求等同于提供可操作的科学, 但并非所有解决科学需求的努力都能提供可操作的科学, 表明这两个概念(提供可操作的科学和解决科学需求)的同义使用并不简单。当传递科学需求的人忽视了负责阐明优先管理问题并说明预期的科学信息将如何帮助决策过程的决策者时, 就会出现这样的情况。我们认为, 产出可操作科学的能力的决定性因素在于负责阐述科学需求的行动者和用于确定这些需求的过程, 这强调了分析科学需求的来源并进行判定的重要性。为了加强科学家和决策者之间的沟通和跨文化交流, 我们还确定了可能不能恰当阐明科学需求的行动者类型(例如, 存在及不存在监管关系的应用科学家、外部影响者、不情愿的决策者、代替决策者的代理人和边界组织代表)。我们还强调了进行需求评估或空缺分析的重要性及常用方法, 以此来确定优先的科学需求。本研究的结论是, 促进可操作科学的基本要求, 如阐明激发科学需求的利益决策以及通过稳健的过程来确定重要的信息空缺, 并不总能得到满足, 还需要进行验证。为了解决这些问题, 我们为应用科学家、决策者、研究资助机构和边界组织提出了一些实用的建议, 从而为产出真正的可操作科学创造条件。【翻译:胡怡思;审校:聂永刚】.

Challenges facing societies around the globe as they plan for and adapt to climate change are so large that usable, research-driven recommendations to inform management actions are urgently needed. We sought to understand factors that influence the variation of academic contribution and use of collaborative research on climate change. We surveyed researchers (n = 31), program-leaders (n = 5), and stakeholders (n = 81) from projects supported by a federally funded network across the United States. Our results suggest that peer-reviewed publications do not lead to use, but frequency of meetings with stakeholders significantly increased use. Overall, the factors needed for projects to have high degrees of academic contributions are distinct from those needed to be useful to stakeholders. Furthermore, leadership perceptions of use of projects were significantly different from users. Our quantitative results can inform future requests for proposals and better enable researchers using collaborative approaches to conduct science that is more often used by stakeholders., Conservation Letters, 15 (4), ISSN:1755-263X

Community occupancy models estimate species-specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates toward the community mean can mask differences among groups. Infinite-mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species-level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP-COM with different dimensions (i.e., different numbers of model parameters with species-level DP random effects) and under varying cluster differences. Because the DP-COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP-COM model to a bird data set from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community-level covariate coefficients on occupancy probability were generally unbiased with (near-) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP-COM was similar. The DP-COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP-COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP-COM, and considering the computational burden for the DP models, we recommend using the DP-COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP-COM.

Background Among the most widely anticipated climate-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution in response to changing climate conditions. In particular, a series of commonly articulated hypotheses have emerged: species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to climate change, reflecting an underlying hypothesis that species will move to cooler locations to track spatial changes in the temperature of their current range. Yet, many species are not demonstrating range shifts consistent with these hypotheses. Resolving this discrepancy and providing effective explanations for the observed variability in species’ range shifts is urgently needed to help support a range of natural resource management decisions. Here, we propose a protocol to review the body of evidence for commonly-held climate change range shift hypotheses at the species level focusing on observed latitudinal, longitudinal, elevational, and depth shifts in response to temperature and precipitation changes. We aim to answer the question: what is the impact of anthropogenic climate change (specifically changes in temperature and precipitation) on species ranges? Methods In this review protocol, we propose to conduct a systematic search of literature from internet databases and search engines in English. Articles will be screened in a two-stage process (title/abstract and full text) to evaluate whether they meet a list of eligibility criteria (e.g., presents species-level data, compares > 1 time period). Initial data coding and extraction will be completed by four reviewers and checked by a secondary reviewer from among our co-authors. We will perform a formal meta-analysis to document estimated effect size using the subset of available range-shift data expressed in distance per time (e.g., km/decade). We will also use multinomial logistic regression models to assess the probability that species are shifting in a direction that supports our hypotheses (i.e. towards higher latitudes, greater elevations, and deeper depths). We will account for study methodology as a potential source of variation.

Cultural resources in coastal parks and recreation areas are vulnerable to climate change. The US National Park Service (NPS) is facing the challenge of insufficient budget allocations for both maintenance and climate adaptation of historic structures. Research on adaptation planning for cultural resources has predominately focused on vulnerability assessments of heritage sites; however, few studies integrate multiple factors (e.g., vulnerability, cultural significance, use potential, and costs) that managers should consider when making tradeoff decisions about which cultural resources to prioritize for adaptation. Moreover, heritage sites typically include multiple types of cultural resources, and researchers have yet to examine such complex tradeoffs. This study applies the Optimal Preservation (OptiPres) Model as a decision support framework to evaluate the tradeoffs of adaptation actions among multiple types of historic structures—wooden buildings, masonry and concrete buildings, forts, and batteries—under varying budget scenarios. Results suggest that the resource values of different types of historic structures vary greatly under a range of budget scenarios, and tradeoffs have to be made among different types of historical structures to achieve optimal planning objectives. Moreover, periodic, incremental funding and partial maintenance are identified as optimal funding strategies for preservation needs of cost-intensive historic structures. Also, adaptative use of historical buildings (e.g., building occupancy) can improve the resource values when budgets are constrained. The OptiPres Model provides managers with a unique framework to inform adaptation planning efforts for a broad range of historic structures, which is transferable across coastal parks to enhance historic preservation planning under climate change.

Climate change poses great challenges for cultural resource management, particularly in coastal areas. Cultural resources, such as historic buildings, in coastal areas are vulnerable to climate impacts including inundation, deterioration, and destruction from sea-level rise and storm-related flooding and erosion. However, research that assesses the trade-offs between actions for protecting vulnerable and valuable cultural resources under budgetary constraints is limited. This study focused on developing a decision support model for managing historic buildings at Cape Lookout National Seashore. We designed the Optimal Preservation Decision Support (OptiPres) model to: (a) identify optimal, annual adaptation actions for historic buildings across a 30-year planning horizon, (b) quantify trade-offs between different actions and the timing of adaptation actions under constrained budgets, and (c) estimate the effectiveness of budget allocations on the resource value of historic buildings. Our analysis of the model suggests that: (1) funding allocation thresholds may exist for national parks to maintain the historical significance and use potential of historic buildings under climate change, (2) the quantitative assessment of trade-offs among alternative adaptation actions provides generalizable guidance for decision makers about the dynamics of their managed system, and (3) the OptiPres model can identify cost-efficient approaches to allocate funding to maintain the historical value of buildings vulnerable to the effects of climate change. Therefore, the OptiPres model, while not designed as a prescriptive decision tool, allows managers to understand the consequences of proposed adaptation actions. The OptiPres model can guide park managers to make cost-effective climate adaptation decisions for historic buildings more transparently and robustly.

Self-organization is a process of establishing and reinforcing local structures through feedbacks between internal population dynamics and external factors. In reef-building systems, substrate is collectively engineered by individuals that also occupy it and compete for space. Reefs are constrained spatially by the physical environment, and by mortality, which reduces production but exposes substrate for recruits. Reef self-organization therefore depends on efficient balancing of production and occupancy of substrate. To examine this, we develop a three-dimensional individual-based model (IBM) of oyster reef mechanics. Shell substrate is grown by individuals as valves, accumulates at the reef level, and degrades following mortality. Single restoration events and subsequent dynamics are simulated for a case study in South Carolina (USA). Variability in model processes is included on recruitment, spatial environmental constraints, and predation, over multiple independent runs and five predator community scenarios. The main goal for this study is to summarize trends in dynamics that are robust across this uncertainty, and from these generate new hypotheses and predictions for future studies. Simulation results demonstrate three phases following restoration: initial transient dynamics with considerable shell loss, followed by growth and saturation of the live population, and then saturation of settlement habitat several years later. Over half of simulations recoup initial shell losses as populations grow, while others continue in decline. The balance between population density, substrate supporting the reef, and exposed surfaces for settlement is mediated by overall population size and size structure, presence of predators, and relative amounts of live individuals and intact dead shells. The efficiency of settlement substrate production improves through time as population size structure becomes more complex, and the population of dead valves accumulates.

In recent years, researchers from interdisciplinary teams involving ecologists, economists and operations researchers collaborated to provide decision support tools to address the challenges of preserving biodiversity by optimizing the design of reserves. The goal of this paper is to further advance this area of research and provide new solutions to solve complex Spatial Conservation Planning (SCP) problems under uncertainty that consider risk preferences of decision makers. Our approach employs modern portfolio theory to address uncertainties in SCP problems, and involves two conflicting objectives: maximizing return and minimizing risk. We apply concepts from game theory such as the Nash bargaining solution to directly compute a desirable Pareto-optimal solution for the proposed bi-objective optimization formulation in natural resource management problems. We demonstrate with numerical examples that by directly computing a Nash bargaining solution, a Binary Quadratically Constrained Quadratic Program (BQCQP) can be solved. We show that our approach (implementable with commercial solvers such as CPLEX) can effectively solve the proposed BQCQP for much larger problems than previous approaches published in the ecological literature. Optimal solutions for problems with less than 400 parcels can be computed within a minute. Near optimal solutions (within at most 0.2% gap from an optimal solution) for high-dimensional problems involving up to 800 parcels can be computed within 8 h on a standard computer. We have presented a new approach to solve SCP optimization problems while considering uncertainty and risk tolerance of decision makers. Our new approach expands considerably the applicability of such SCP optimization methods to address real conservation problems.

Traditional conservation curricula and training typically emphasizes only one part of systematic decision making (i.e., the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem, (2) specifying feasible alternative actions, and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science ( i.e. , models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.

Metapopulation ecology is a field that is richer in theory than in empirical results. Many existing empirical studies use an incidence function approach based on spatial patterns and key assumptions about extinction and colonization rates. Here we recast these assumptions as hypotheses to be tested using 18 years of historic detection survey data combined with four years of data from a new monitoring program for the Lower Keys marsh rabbit. We developed a new model to estimate probabilities of local extinction and colonization in the presence of nondetection, while accounting for estimated occupancy levels of neighboring patches. We used model selection to identify important drivers of population turnover and estimate the effective neighborhood size for this system. Several key relationships related to patch size and isolation that are often assumed in metapopulation models were supported: patch size was negatively related to the probability of extinction and positively related to colonization, and estimated occupancy of neighboring patches was positively related to colonization and negatively related to extinction probabilities. This latter relationship suggested the existence of rescue effects. In our study system, we inferred that coastal patches experienced higher probabilities of extinction and colonization than interior patches. Interior patches exhibited higher occupancy probabilities and may serve as refugia, permitting colonization of coastal patches following disturbances such as hurricanes and storm surges. Our modeling approach should be useful for incorporating neighbor occupancy into future metapopulation analyses and in dealing with other historic occupancy surveys that may not include the recommended levels of sampling replication.

Context Designing effective long-term monitoring strategies is essential for managing wildlife populations. Implementing a cost-effective, practical monitoring program is especially challenging for widespread but locally rare species. Early successional habitat preferred by the New England cottontail (NEC) has become increasingly rare and fragmented, resulting in substantial declines from their peak distribution in the mid-1900s. The introduction of a possible competitor species, the eastern cottontail (EC), may also have played a role. Uncertainty surrounding how these factors have contributed to NEC declines has complicated management and necessitated development of an appropriate monitoring framework to understand possible drivers of distribution and dynamics. Aims Because estimating species abundance is costly, we designed presence–absence surveys to estimate species distributions, test assumptions about competitive interactions, and improve understanding of demographic processes for eastern cottontails (EC) and New England cottontails (NEC). The survey protocol aimed to balance long-term management objectives with practical considerations associated with monitoring a widespread but uncommon species. Modelling data arising from these observations allow for estimation of covariate relationships between species status and environmental conditions including habitat and competition. The framework also allows inference about species status at unsurveyed locations. Methods We designed a monitoring protocol to collect data across six north-eastern USA states and, using data collected from the first year of monitoring, fit a suite of single-season occupancy models to assess how abiotic and biotic factors influence NEC occurrence, correcting for imperfect detectability. Key results Models did not provide substantial support for competitive interactions between EC and NEC. NEC occurrence patterns appear to be influenced by several remotely sensed habitat covariates (land-cover classes), a habitat-suitability index, and, to a lesser degree, plot-level habitat covariates (understorey density and canopy cover). Conclusions We recommend continuing presence–absence monitoring and the development of dynamic occupancy models to provide further evidence regarding hypotheses of competitive interactions and habitat influences on the underlying dynamics of NEC occupancy. Implications State and federal agencies responsible for conserving this and other threatened species can engage with researchers in thoughtful discussions, based on management objectives, regarding appropriate monitoring design to ensure that the allocation of monitoring efforts provides useful inference on population drivers to inform management intervention.

This book highlights the growing interest in management interventions designed to enhance the resilience of social-ecological systems (SESs) such as the Jamaica Bay watershed. Effective management requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections), whether the focus is on managing biological processes or human behavior or (most likely) both. In systems characterized by many interacting components and high uncertainty, however, making even probabilistic predictions is difficult.

Estimating the age of individuals in wild populations can be of fundamental importance for answering ecological questions, modeling population demographics, and managing exploited or threatened species. Significant effort has been devoted to determining age through the use of growth annuli, secondary physical characteristics related to age, and growth models. Many species, however, either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age. Length-at-age models are well represented in the fisheries and other wildlife management literature. Many of these models overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual-specific random effects. Here, we describe hierarchical models in which growth curves vary as individual-specific stochastic processes, and we show how these models can be fit using capture-recapture data for animals of unknown age along with data for animals of known age. We combine these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. We illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models. The analysis provides the means of predicting crocodile age, given a single measurement of head length. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, reproductive maturity was estimated to be at nine years. These size benchmarks are believed to represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. The modeling approach that we present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.

Summary 1. Markov chain Monte Carlo (MCMC) is a simulation technique that has revolutionised the analysis of ecological data, allowing the fitting of complex models in a Bayesian framework. Since 2001, there have been nearly 200 papers using MCMC in publications of the Ecological Society of America and the British Ecological Society, including more than 75 in the journal Ecology and 35 in the Journal of Applied Ecology. 2. We have noted that many authors routinely ‘thin’ their simulations, discarding all but every kth sampled value; of the studies we surveyed with details on MCMC implementation, 40% reported thinning. 3. Thinning is often unnecessary and always inefficient, reducing the precision with which features of the Markov chain are summarised. The inefficiency of thinning MCMC output has been known since the early 1990’s, long before MCMC appeared in ecological publications. 4. We discuss the background and prevalence of thinning, illustrate its consequences, discuss circumstances when it might be regarded as a reasonable option and recommend against routine thinning of chains unless necessitated by computer memory limitations.

Sea level rise (SLR) projections along the coast of Florida present an enormous challenge for management and conservation over the long term. Decision makers need to recognize and adopt strategies to adapt to the potentially detrimental effects of SLR. Structured decision making (SDM) provides a rigorous framework for the management of natural resources. The aim of SDM is to identify decisions that are optimal with respect to management objectives and knowledge of the system. Most applications of SDM have assumed that the managed systems are governed by stationary processes. However, in the context of SLR it may be necessary to acknowledge that the processes underlying managed systems may be non-stationary, such that systems will be continuously changing. Therefore, SLR brings some unique considerations to the application of decision theory for natural resource management. In particular, SLR is expected to affect each of the components of SDM. For instance, management objectives may have to be reconsidered more frequently than under more stable conditions. The set of potential actions may also have to be adapted over time as conditions change. Models have to account for the non-stationarity of the modeled system processes. Each of the important sources of uncertainty in decision processes is expected to be exacerbated by SLR. We illustrate our ideas about adaptation of natural resource management to SLR by modeling a non-stationary system using a numerical example. We provide additional examples of an SDM approach for managing species that may be affected by SLR, with a focus on the endangered Florida manatee.

Reliable estimates of presence or absence of a species can provide substantial information on management questions related to distribution and habitat use but should incorporate the probability of detection to reduce bias. We surveyed for the endangered Lower Keys marsh rabbit (Sylvilagus palustris hefneri) in habitat patches on 5 Florida Key islands, USA, to estimate occupancy and detection probabilities. We derived detection probabilities using spatial replication of plots and evaluated hypotheses that patch location (coastal or interior) and patch size influence occupancy and detection. Results demonstrate that detection probability, given rabbits were present, was

The creation and use of a globally available database of DNA sequences from a standardized gene region has been proposed as a tool for species identification, assessing genetic diversity and monitoring the legal and illegal trade in wildlife species. Here, we contribute to the Barcode of Life Data System and test whether a short region of the mitochondrial cytochrome c oxidase subunit 1 (COX1) gene would reliably distinguish among a suite of commonly hunted African and South American mammal and reptile species. We used universal primers to generate reference barcode sequences of 645 bp for 23 species from five vertebrate families (Crocodilidae, Alligatoridae, Bovidae, Suidae and Cercopithecidae). Primer cocktails yielded high quality barcode sequences for 179 out of 204 samples (87.7%) from all species included in the study. For most taxa, we sequenced multiple individuals to estimate intraspecific sequence variability and document fixed diagnostic characters for species identification. Polymorphism in the COX1 fragment was generally low (mean = 0.24%), while differences between congeneric species averaged 9.77%. Both fixed character differences and tree-based maximum likelihood distance methods unambiguously identified unknown and misidentified samples with a high degree of certainty. Barcode sequences also differentiated among newly identified lineages of African crocodiles and identified unusually high levels of genetic diversity in one species of African duiker. DNA barcoding offers promise as an effective tool for monitoring poaching and commercial trade in endangered species, especially when investigating semi-processed or morphologically indistinguishable wildlife products. We discuss additional benefits of barcoding to ecology and conservation.

National Wildlife Refuges (NWRs) in the United States play an important role in the adaptation of social-ecological systems to climate change, land-use change, and other global-change processes. Coastal refuges are already experiencing threats from sea-level rise and other change processes that are largely beyond their ability to influence, while at the same time facing tighter budgets and reduced staff. We engaged in workshops with NWR managers along the U.S. Atlantic coast to understand the problems they face from global-change processes and began a multidisciplinary collaboration to use decision science to help address them. We are applying a values-focused approach to base management decisions on the resource objectives of land managers, as well as those of stakeholders who may benefit from the goods and services produced by a refuge. Two insights that emerged from our workshops were a conspicuous mismatch between the scale at which management can influence outcomes and the scale of environmental processes, and the need to consider objectives related to ecosystem goods and services that traditionally have not been explicitly considered by refuges (e.g., protection from storm surge). The broadening of objectives complicates the decision-making process, but also provides opportunities for collaboration with stakeholders who may have agendas different from those of the refuge, as well as an opportunity for addressing problems across scales. From a practical perspective, we recognized the need to (1) efficiently allocate limited staff time and budgets for short-term management of existing programs and resources under the current refuge design and (2) develop long-term priorities for acquiring or protecting new land/habitat to supplement or replace the existing refuge footprint and thus sustain refuge values as the system evolves over time. Structuring the decision-making problem in this manner facilitated a better understanding of the issues of scale and suggested that a long-term solution will require a significant reassessment of objectives to better reflect the comprehensive values of refuges to society. We discuss some future considerations to integrate these two problems into a single framework by developing novel optimization approaches for dynamic problems that account for uncertainty in future conditions.

A conceptual framework is provided for considering the threshold concept in natural resource management and conservation. We define three kinds of thresholds relevant to management and conservation. Ecological thresholds are values of system state variables at which small changes bring about substantial or specified changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process. We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

In this chapter, we demonstrate the application of the various classes of thresholds, detailed in earlier chapters and elsewhere, via an actual but simplified natural resource management case study. We intend our example to provide the reader with the ability to recognize and apply the theoretical concepts of utility, ecological and decision thresholds to management problems through a formalized decision-analytic process. Our case study concerns the management of human recreational activities in Alaska’s Denali National Park, USA, and the possible impacts of such activities on nesting Golden Eagles, Aquila chrysaetos. Managers desire to allow visitors the greatest amount of access to park lands, provided that eagle nesting-site occupancy is maintained at a level determined to be acceptable by the managers themselves. As these two management objectives are potentially at odds, we treat minimum desired occupancy level as a utility threshold which, then, serves to guide the selection of annual management alternatives in the decision process. As human disturbance is not the only factor influencing eagle occupancy, we model nesting-site dynamics as a function of both disturbance and prey availability. We incorporate uncertainty in these dynamics by considering several hypotheses, including a hypothesis that site occupancy is affected only at a threshold level of prey abundance (i.e., an ecological threshold effect). By considering competing management objectives and accounting for two forms of thresholds in the decision process, we are able to determine the optimal number of annual nesting-site restrictions that will produce the greatest long-term benefits for both eagles and humans. Setting a utility threshold of 75 occupied sites, out of a total of 90 potential nesting sites, the optimization specified a decision threshold at approximately 80 occupied sites. At the point that current occupancy falls below 80 sites, the recommended decision is to begin restricting access to humans; above this level, it is recommended that all eagle territories be opened to human recreation. We evaluated the sensitivity of the decision threshold to uncertainty in system dynamics and to management objectives (i.e., to the utility threshold).

The present study set out to evaluate cross-species amplification of 34 bovid microsatellites in six central African duikers: Cephalophus callipygus, C. monticola, C. silvicultor, C. nigrifrons, C. dorsalis and C. leucogaster. Of these loci, 16 amplified across all species and appeared polymorphic when initially tested in polyacrylamide gel electrophoresis. Twelve of these loci were subsequently assembled into three multiplex panels of four loci each. These multiplexes successfully amplified across all six duiker species in the present study and the sympatric artiodactyls Tragelaphus spekei and Hyemoschus aquaticus. The only exception was the locus BM848 that did not amplify from C. leucogaster. For species with sufficient sample sizes (C. callipygus and C. monticola), the number of alleles ranged from three to ten and four to fifteen, respectively. Three loci deviated from Hardy-Weinberg equilibrium in C. callipygus and five in C. monticola. We attribute the latter result to possibilities of local population substructuring or to an excess of homozygotes because of null alleles. These multiplex assemblies will greatly facilitate studies of individual identification, parentage analysis, population size estimation and fine-scale analyses of population genetic structure in central African artiodactyls.

The taxonomy of the African dwarf crocodile (genus Osteolaemus) has been disputed since a novel morphotype was discovered in the early 20th Century. Because this poorly-known reptile is widely hunted throughout the forests of Central and West Africa, resolving the existence and extent of taxonomic units has important management and conservation implications. Lack of molecular data from individuals of known origin and historical disagreement on diagnostic morphological characters have hindered attempts to settle one of the most important taxonomic questions in the Crocodylia. In an effort to clarify the evolutionary relationships among dwarf crocodiles, we sequenced three mitochondrial and two nuclear genes using a large sample of dwarf crocodiles from known localities across major drainage basins of forested Africa. Concordant results from Bayesian, maximum likelihood, maximum parsimony and population aggregation analytical methods support a previously recognized division of the dwarf crocodile into a Congo Basin form (O. osborni) and a West African form (Osteolaemus tetraspis), but also reveal a third diagnosable lineage from West Africa warranting recognition as an separate taxonomic unit. Corrected genetic distances between geographic regions ranged from 0.2% to 0.6% in nuclear fragments and 10.0 to 16.2% in mitochondrial COI. Population aggregation, using fixed and alternate character (nucleotide) states to cluster or divide populations, recovered 232 such molecular characters in 4286 bp of sequence data and unambiguously aggregated populations into their respective geographic clade. Several previously recognized morphological differences coincide with our molecular analysis to distinguish Congo Basin crocodiles from the Ogooue Basin and West Africa. Discrete morphological characters have not yet been documented between the latter two regions, suggesting further work is needed or molecular data may be required to recognize taxonomic divisions in cases where putative species are morphologically cryptic. This study highlights the importance of using widespread taxon sampling and a multiple evidence approach to diagnose species boundaries and reveal cryptic diversity.