Structured decision making as a conceptual framework to identify thresholds for conservation and management

Martin, Julien; Runge, Michael C.; Nichols, James D.; Lubow, Bruce C.; Kendall, William L.

doi:10.1890/08-0255.1

Cited by 244 publications

(229 citation statements)

References 30 publications

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“…v www.esajournals.org et al 2012b); assess and mitigate for impacts, and monitor status and trends at a resolution and extent that is relevant ecologically and practically (Jones 2001, Chalfoun andMartin 2007); and provide decision support for conservation planning and policy development and for adaptive management or other structured decision making processes (Martin et al 2009). …”

Section: Discussionmentioning

confidence: 99%

Using LiDAR‐derived vegetation metrics for high‐resolution, species distribution models for conservation planning

et al. 2013

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. Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere 4(3):42. http://dx.doi.org/10.1890/ES12-000352.1Abstract. Advances in remotely sensed data for characterizing habitat have enabled development of spatially explicit predictive species distribution models (SDM) that can be essential tools for management. SDMs commonly use coarse-grain metrics, such as forest patch size or patch connectivity, over broad spatial extents. However, species distributions are likely driven in part by local, fine-grained habitat conditions. Conservation and management are often planned and applied locally, where coarse predictions may be uninformative or not sufficiently precise. We investigated the integration of high-resolution LiDAR (Light Detection and Ranging) with avian point sampling data to develop a detection-corrected occupancy model to quantify habitat-occurrence relationships for two species with different habitats: the endangered golden-cheeked warbler (Setophaga chrysoparia) and black-capped vireo (Vireo atricapilla) on a military installation in central Texas. We compared occupancy models that used only the more conventional, coarse remotely sensed metrics to models that also incorporated high-resolution LiDAR-derived metrics for vegetation height and canopy cover, to assess their use for predicting distributions. Models including LiDAR-derived vegetation height and canopy cover metrics were competitive for both species, and models without LiDAR-derived vegetation height had substantially lower model weights and explanatory strength. Area under curve estimates for the highest ranked models were high for warblers (0.864) and moderate for vireos (0.746). Using the best supported models for each species, we predicted the occurrence distribution for both species. The resulting predictions provide a decision support tool that enables assessment of the status, impacts, and mitigation of impacts to endangered species habitat on the installation due to land management and military training activities that is more standardized and accurate than current assessment approaches based on visual gestalt of habitat and expert opinion. Additionally, although previous species distribution models have been created for our focal species, most fail to match the grain and extent of most management actions or include local, fine-grained metrics that influence distributions. In contrast, we demonstrate that use of LiDAR with species occurrence data can provide precision and resolution at a scale that is relevant ecologically and to the operational scale of most conservation and management actions.

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Section: Discussionmentioning

confidence: 99%

Using LiDAR‐derived vegetation metrics for high‐resolution, species distribution models for conservation planning

et al. 2013

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“…There are a number of tools to decide which management actions are best or most likely to succeed in the presence of uncertainty. Structured decision-making and value of information analysis can be used to find the best management option and to define the direction of research most likely to illuminate critical uncertainties [87][88][89]. For example, structured decision-making might identify important gaps in our understanding of chytrid epidemiology.…”

Section: Single Strategies or A Marriage Of Methods?mentioning

confidence: 99%

Mitigating amphibian chytridiomycoses in nature

Garner

Schmidt²,

Martel

et al. 2016

Phil. Trans. R. Soc. B

128

156

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Amphibians across the planet face the threat of population decline and extirpation caused by the disease chytridiomycosis. Despite consensus that the fungal pathogens responsible for the disease are conservation issues, strategies to mitigate their impacts in the natural world are, at best, nascent. Reducing risk associated with the movement of amphibians, non-amphibian vectors and other sources of infection remains the first line of defence and a primary objective when mitigating the threat of disease in wildlife. Amphibian-associated chytridiomycete fungi and chytridiomycosis are already widespread, though, and we therefore focus on discussing options for mitigating the threats once disease emergence has occurred in wild amphibian populations. All strategies have shortcomings that need to be overcome before implementation, including stronger efforts towards understanding and addressing ethical and legal considerations. Even if these issues can be dealt with, all currently available approaches, or those under discussion, are unlikely to yield the desired conservation outcome of disease mitigation. The decision process for establishing mitigation strategies requires integrated thinking that assesses disease mitigation options critically and embeds them within more comprehensive strategies for the conservation of amphibian populations, communities and ecosystems. This article is part of the themed issue ‘Tackling emerging fungal threats to animal health, food security and ecosystem resilience’.

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“…However, the expert opinions were elicited and used in a rigorous, transparent, and logical way (Martin et al 2009). Also, it is important to recall the goal of SDM: to use currently available knowledge in a value-focused process to objectively evaluate decision options and identify the decision option with the greatest probability of achieving decision-makers' objectives.…”

Section: Appendixmentioning

confidence: 99%

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Ferguson¹,

Conroy²,

Chamblee³

et al. 2015

E&S

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ABSTRACT. Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners' objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina. Macon County has little land use regulation and a history of discordant, ineffective attempts to address land use and development. We worked with landowners to define their objectives, identify decision options for forest management, build a Bayesian decision network to predict the outcomes of decisions, and determine the optimal and least-desirable decision options. The optimal forest management options for an average, large, forested property (30 ha property with 22 ha of forest) in Macon County was crown-thinning timber harvest under the Present-Use Value program, in which enrolled property is taxed at the present-use value (growing timber for commercial harvest) rather than full market value. The least-desirable forest management actions were selling 1 ha and personal use of the forest (e.g., trails, firewood) with or without a conservation easement. Landowners reported that they enjoyed participating in the project (85%) and would reconsider what they are currently doing to manage their forest (69%). The decision that landowners initially thought would best meet their objectives did not match results from the decision network. This highlights the usefulness of SDM, which typically has been applied to decision problems involving public resources.

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Structured decision making as a conceptual framework to identify thresholds for conservation and management

Cited by 244 publications

References 30 publications

Using LiDAR‐derived vegetation metrics for high‐resolution, species distribution models for conservation planning

Using LiDAR‐derived vegetation metrics for high‐resolution, species distribution models for conservation planning

Mitigating amphibian chytridiomycoses in nature

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

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