Priority Threat Management for biodiversity conservation: A handbook

Carwardine, Josie; Martin, Tara G.; Firn, Jennifer; Reyes, Rocío Ponce; Nicol, Sam; Reeson, Andrew; Grantham, Hedley S.; Stratford, Danial; Kehoe, Laura; Chadès, Iadine

doi:10.1111/1365-2664.13268

Cited by 89 publications

(123 citation statements)

References 48 publications

(77 reference statements)

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“…Bennett et al, 2014;Joseph et al, 2009) and managing threats to biodiversity (e.g. Carwardine et al, 2014). Finding an exact solution to a knapsack problem can be challenging and require considerable computer resources, especially when investments and returns are strongly correlated and the number of potential actions and management units is large (Pisinger, 2005).…”

Section: Voi Across Multiple Management Units With a Limited Budgetmentioning

confidence: 99%

When to monitor and when to act: Value of information theory for multiple management units and limited budgets

Bennett

Maxwell

Martin

et al. 2018

Journal of Applied Ecology

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The question of when to monitor and when to act is fundamental to applied ecology and notoriously difficult to answer. Value of information (VOI) theory holds great promise to help answer this question for many management problems. However, VOI theory in applied ecology has only been demonstrated in single‐decision problems and has lacked explicit links between monitoring and management costs. Here, we present an extension of VOI theory for solving multi‐unit decisions of whether to monitor before managing, while explicitly accounting for monitoring costs. Our formulation helps to choose the optimal monitoring/management strategy among groups of management units (e.g. species, habitat patches) and can be used to examine the benefits of partial and repeat monitoring. To demonstrate our approach, we use case‐simulated studies of single‐species protection that must choose among potential habitat areas, and classification and management of multiple species threatened with extinction. We provide spreadsheets and code to illustrate the calculations and facilitate application. Our case studies demonstrate the utility of predicting the number of units with a given outcome for problems with probabilities of discrete states and the efficiency of having a flexible approach to manage according to monitoring outcomes. Synthesis and applications. The decision to act or gather more information can have serious consequences for management. No decision, including the decision to monitor, is risk‐free. Our multi‐unit expansion of Value of Information theory can reduce the risk in monitoring/acting decisions for many applied ecology problems. While our approach cannot account for the potential value of discovering previously unknown threats or ecological processes via monitoring programmes, it can provide quantitative guidance on whether to monitor before acting, and which monitoring/management actions are most likely to meet management objectives.

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Section: Voi Across Multiple Management Units With a Limited Budgetmentioning

confidence: 99%

When to monitor and when to act: Value of information theory for multiple management units and limited budgets

Bennett

Maxwell

Martin

et al. 2018

Journal of Applied Ecology

Self Cite

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“…Although often described as analogous to SDM, SCP is most suited to problems where options are chosen based on trade-offs among attributes that are quantified using consistent measurements across all units (Schwartz et al 2018). SCP has been used extensively to prioritize management of landscapes (e.g., Australian MPA network), species (e.g., Joseph et al 2009), and threats (Carwardine et al 2014).…”

Section: Systematic Conservation Prioritizationmentioning

confidence: 99%

Making Tough Choices: Picking the Appropriate Conservation Decision‐Making Tool

Bower

Brownscombe

Birnie‐Gauvin

et al. 2017

CONSERVATION LETTERS

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Conservation practitioners face complex challenges due to resource limitations, biological and socioeconomic trade-offs, involvement of diverse interest groups, and data deficiencies. To help address these challenges, there are a growing number of frameworks for systematic decision making. Three prominent frameworks are structured decision making, systematic conservation prioritization, and systematic reviews. These frameworks have numerous conceptual linkages, and offer rigorous and transparent solutions to conservation problems. However, they differ in their assumptions and applicability. Here, we provide guidance on how to choose among these frameworks for solving conservation problems, and how to identify less rigorous techniques when time or data availability limit options. Each framework emphasizes the need for proper problem consideration and formulation, and includes steps for monitoring and evaluation. We recommend clear and documented problem formulation, adopting structured decision-making processes, and archiving results in a global database to support conservation professionals in making evidencebased decisions in the future.

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“…2012b), prioritizing management strategies (e.g., Carwardine et al. ), risk assessments (Smith et al. ), and estimating population trends (Adams‐Hosking et al.…”

Section: Collective Intelligence In Conservationmentioning

confidence: 99%

Untapped potential of collective intelligence in conservation and environmental decision making

Vercammen

Burgman

2019

Conservation Biology

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Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade‐offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small‐group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision‐making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective‐intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision‐making research and practice.

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Priority Threat Management for biodiversity conservation: A handbook

Cited by 89 publications

References 48 publications

When to monitor and when to act: Value of information theory for multiple management units and limited budgets

When to monitor and when to act: Value of information theory for multiple management units and limited budgets

Making Tough Choices: Picking the Appropriate Conservation Decision‐Making Tool

Untapped potential of collective intelligence in conservation and environmental decision making

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