Combining Species Distribution Models and Value of Information Analysis for Spatial Allocation of Conservation Resources

Raymond, Calla

doi:10.22215/etd/2018-13226

Cited by 4 publications

(13 citation statements)

References 65 publications

(150 reference statements)

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“…We used standard VOI equations to calculate the expected number of threatened plant occurrences in each management unit with current information and the expected number found by monitoring (Raiffa & Schlaifer, ). We then accounted for the cost of purchasing each management unit for conservation, and calculated the cost‐effectiveness (expected number of occurrences protected/$ spent) of purchasing based on current knowledge, and after monitoring (Raymond et al, ). The ability to choose among multiple units fundamentally changes VOI calculations (Bennett et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…These data are accessible via GeoWarehouse (https://www2.geowarehouse.ca; 1‐866‐237‐5937) or the appropriate land registry office (https://www.ontario.ca/page/land-registry-offices-lro). We have provided all code for analysing the data as Supporting Information, as well on Zenodo https://doi.org/10.5281/zenodo.3605605 (Raymond et al, ).…”

Section: Data Availability Statementmentioning

confidence: 99%

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Combining species distribution models and value of information analysis for spatial allocation of conservation resources

Raymond

McCune

Rosner‐Katz

et al. 2020

Journal of Applied Ecology

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Managers often have incomplete information to make decisions about threatened species management, and lack the time or funding needed to obtain complete information. Value of information (VOI) analysis can assist managers in deciding whether to manage using current information or monitor to reduce uncertainty before managing. However, VOI analysis has not yet been applied to spatial allocation of monitoring resources across a landscape. Here, we demonstrate how to make the best use of data from species distribution models (SDMs) and VOI analysis to assess the value of land protection decisions for single and multiple‐species objectives across a heterogeneous landscape. Our method determines the situations where one should monitor before protecting the land, and those where one should act based on current incomplete information. Further, we prioritize land planning units based on cost‐effectiveness (expected number of occurrences protected per dollar spent) and identify properties to target for monitoring or immediate conservation. In a single species case study, we found that the optimal decision was to act based on current information when the prior probability of detecting an occurrence in a survey was low. When probability of detection was high, it was most effective to monitor the majority of units. In a multi‐species case study, monitoring was only optimal in 50% of cases, due to high inferred probability of at least one occurrence of a threatened species in many units. When compared to a simulation where units were monitored by default, using VOI to determine which units were monitored or prioritized for immediate conservation led to an increase in the expected number of occurrences protected. Synthesis and applications. Using a combination of species distribution models and value of information analysis can assist managers in efficiently distributing limited resources for protected area allocation. Our results suggest that if managers can use value of information to monitor more efficiently, it can lead to protecting a greater number of threatened species occurrences.

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Section: Methodsmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

Combining species distribution models and value of information analysis for spatial allocation of conservation resources

Raymond

McCune

Rosner‐Katz

et al. 2020

Journal of Applied Ecology

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“…They are threatened by habitat destruction due to residential and commercial development, and require site protection to avoid extinction (McCune et al, 2013). Although previous conservation efforts have led to the establishment of formal protected areas within the region (IUCN & UNEP-WCMC, 2020), challenges remain for conserving these species (Raymond et al, 2020).…”

Section: Study Areamentioning

confidence: 99%

Optimizing ecological surveys for conservation

Hanson

McCune

Chadès

et al. 2022

Journal of Applied Ecology

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Conservation decisions must be made with limited funding and incomplete information. Ecological surveys can help reduce uncertainty and, in turn, potentially lead to better management decisions. However, conducting surveys can reduce funds available for implementing management actions and, in turn, can potentially lead to worse conservation outcomes. Here we develop a value of information framework to evaluate and optimize survey plans. Our framework evaluates survey plans based on their ability to improve how likely resulting protected area systems are to secure species of interest, and accounts for survey and land acquisition costs. Using an example of eight imperilled plant species in Middlesex County (Ontario, Canada), we assessed our framework against conventional approaches for designing survey plans that involve selecting places with (i) maximal geographic coverage, (ii) diverse environmental conditions, (iii) highly uncertain information, (iv) high imperilled species richness and (v) low protected area establishment costs. We found that optimized survey plans could improve the protected area system by, on average, 57.52% (0.21 SD) (up to 105.25%) over conventional survey approaches. These optimized plans could also improve the protected area system by, on average, 19.91% (up to 32.37%) over simply prioritizing based on existing information. Survey plans designed using conventional approaches, in many cases, led to a worse protected area system than simply using existing information. Such conventional approaches performed the worst when they allocated a large percentage of the available budget to data collection. Synthesis and applications. Our findings demonstrate that conventional approaches for designing ecological surveys can impede conservation efforts by squandering funds on data that have little chance of improving decision making. Indeed, conventional approaches for designing surveys had the poorest performance under limited budgets, which are typical in real world planning exercises. We recommend that conservation practitioners carefully consider how data collection efforts can potentially improve conservation decisions, and also the costs associated with data collection. By applying the principles of value of information, our framework enables conservation practitioners to cost‐effectively collect data in places that will maximize conservation outcomes.

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“…EVPI can be used to prioritize research and monitoring around the uncertainties that “matter most,” where “mattering” is defined in terms of the utility of actions. In applied ecological contexts, EVPI has been used to (1) design monitoring programs that address stakeholder conservation concerns (Runge et al, 2011), (2) identify the switch‐point between monitoring and acting (Bennett et al, 2018), (3) spatially prioritize conservation efforts (Raymond et al, 2020), and (4) quantify the species‐persistence benefits of reducing the most important uncertainty‐species responses to threat alleviation (Nicol et al, 2019). EVPI has also been focus of reviews (Bolam et al, 2019; Canessa et al, 2015), and analytical methods also accommodate imperfect information (Nicol et al, 2019; Raiffa & Schlaifer, 1961; Williams & Johnson, 2015).…”

Section: Expected Value Of Perfect Informationmentioning

confidence: 99%

Using social values in the prioritization of research: Quantitative examples and generalizations

Falcy

2021

Ecology and Evolution

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In natural resource management contexts, good decision making includes stakeholder perceptions of the trade-offs between conservation risks and utilization rewards. Indeed, clear articulation of objectives is necessary for good decision making (Keeney, 1992).Nonetheless, many applied ecologists exclusively focus on understanding ecological systems. While reducing system uncertainty is often needed, it may not be sufficient to improve decision making. If decisions about natural resources neglect peoples' values,

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Combining Species Distribution Models and Value of Information Analysis for Spatial Allocation of Conservation Resources

Cited by 4 publications

References 65 publications

Combining species distribution models and value of information analysis for spatial allocation of conservation resources

Combining species distribution models and value of information analysis for spatial allocation of conservation resources

Optimizing ecological surveys for conservation

Using social values in the prioritization of research: Quantitative examples and generalizations

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