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Suggested Citation:"Executive Summary." National Academies of Sciences, Engineering, and Medicine. 2020. Valuing Wildlife Crossings and Enhancements for Mitigation Credits. Washington, DC: The National Academies Press. doi: 10.17226/25731.
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Suggested Citation:"Executive Summary." National Academies of Sciences, Engineering, and Medicine. 2020. Valuing Wildlife Crossings and Enhancements for Mitigation Credits. Washington, DC: The National Academies Press. doi: 10.17226/25731.
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Page 2
Page 3
Suggested Citation:"Executive Summary." National Academies of Sciences, Engineering, and Medicine. 2020. Valuing Wildlife Crossings and Enhancements for Mitigation Credits. Washington, DC: The National Academies Press. doi: 10.17226/25731.
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Page 3

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Valuing Wildlife Crossings and Enhancements for Mitigation Credits ES-1 EXECUTIVE SUMMARY This report summarizes the activities conducted as part of National Cooperative Highway Research Program (NCHRP) 25-25, Task 117, Valuing Wildlife Crossing and Enhancements for Mitigation Credits. Mitigation crediting could provide a valuation approach that state DOTs could use to promote the construction of wildlife crossings and other enhancements to mitigate transportation project impacts. The two objectives of this research are to: • Collect and synthesize current information on valuation methods, metrics, criteria for credit development, and crediting mechanisms used by state DOTs and their partners for calculating and applying mitigation and advance mitigation credits for wildlife connectivity improvements. • Identify existing and potential quantitative methods and approaches for establishing the mitigation values of wildlife overpasses, underpasses, bridges, and culverts for habitat connectivity, and how that value is translated to mitigation credits. Research activities included identifying relevant examples and current practices for valuing wildlife connectivity mitigation by performing an online survey of 234 state DOTs and natural resources agencies and conducting telephone interviews with 13 practitioners from four state DOTs. The literature review revealed few examples of metrics used in practice to value wildlife connectivity mitigation, so the online survey sought to identify the most-experienced practitioners for telephone interviews. Based on the findings from the interviews, four case studies of wildlife connectivity mitigation, from California, Colorado, and Florida, are presented. The online survey revealed a consensus among state DOT and natural resources agency practitioners that dedicated wildlife crossings provide a direct benefit to wildlife of all sizes and a highway safety improvement to the public by reducing collisions with large animals. The survey results also showed that the development of crediting and valuation systems for wildlife crossings is in the early stages in a handful of states and the lack of regulatory requirements and processes requiring compensatory mitigation could be an impediment to developing a crediting approach. This research noted that an advance mitigation framework, as described in the Integrated Ecological Framework (NAS 2012), is an appropriate approach for state DOTs to follow when developing valuation metrics for wildlife connectivity mitigation crediting. California is the only state currently with a regulatory framework under which wildlife connectivity mitigation projects undertaken by a state DOT can establish mitigation credits. The literature review revealed many potential metrics to value wildlife connectivity. Each one could be assigned into one of four categories: (1) condition-based connectivity metrics—types of measurements based on the physical, chemical, and biological attributes of a system, such the highway footprint area within the highway crossing zone used by focal species; (2) function-based connectivity metrics—types of measurements based on wildlife habitats and ecosystem processes, such as the number of individuals of focal species crossing the highway, or the habitat quality of connected or fragmented habitat; (3) model- based connectivity metrics—types of measurements based on computer models that combine elements of function- and condition-based metrics to estimate wildlife connectivity, such as species distribution models, animal movement models, and habitat-based population viability models; and (4) avoided cost metrics—types of measurements based on the economic value of wildlife or human life and/or property, such as reductions in insurance settlements due to wildlife-vehicle collisions (WVCs). On a national level, identifying universal metrics or quantification methods for valuing wildlife connectivity mitigation appears to be infeasible, and practitioners agreed that metrics would most likely

Valuing Wildlife Crossings and Enhancements for Mitigation Credits ES-2 be ecosystem- and species-specific. Choosing appropriate metrics would depend on the life history and range(s) of the focal species and the availability of spatial data for focal species occurrences and WVCs. Also, under existing regulations, the use of credits for wildlife connectivity mitigation would most likely be focused on natural resource agency permit requirements that require state DOTs to compensate for impacts on threatened and endangered species. Practitioners interviewed generally support using function-based metrics to value mitigation credits for wildlife crossings and other connectivity enhancements. However, to quantify pre-construction versus post-construction wildlife values, function-based metrics would require extensive biological data for focal species and ecosystems. Adequate data to accurately quantify values are only available for a limited number of species and locations. Even in cases where studies have documented wildlife movement in relation to highways, the lack of comprehensive data and other confounding factors could pose a difficulty to quantifying the ecological value of a wildlife crossing or other connectivity enhancement. In contrast, using condition-based metrics to value wildlife connectivity mitigation would be more straightforward; however, they would not explicitly measure the ecological gain from the mitigation. Similarly, model-based metrics would not directly measure the ecological gain from wildlife connectivity mitigation, but they have the advantage of being transparent and repeatable. Model-based metrics could also incorporate existing ecological datasets and results from prior modeling efforts to predict ecological gain for multiple species. Both condition- and model-based metrics would serve as a proxy for performance (i.e., implementing a wildlife connectivity mitigation measure is expected to achieve its intended benefit for focal species). Lastly, many state DOTs have used avoided cost metrics (i.e., reduced WVCs) in cost-benefit models to prioritize wildlife connectivity mitigation for animals large enough to damage vehicles based on the predicted improvement in motorist safety and wildlife conservation. Because most state DOTs have roadkill data-collection protocols in place and maintain databases of WVCs, for applicable species, this avoided cost metric could be among the most practical metrics to value wildlife connectivity mitigation credits. In the absence of a market-driven mitigation banking program that guides credit costs (like the one that exists for wetland and stream mitigation bank credits), the economic impacts of WVCs could be an important metric to monetize the value of wildlife crossings or other connectivity mitigation measures. Also, State DOTs can quantify values that are intrinsic to wildlife using various non-market valuation techniques to calculate the value of animal populations that would be restored or maintained by a wildlife crossings or other connectivity enhancement, including revealed preference techniques, stated preference techniques, or techniques based on poaching fines and restitution. Only the California Department of Transportation (Caltrans) and Florida Department of Transportation (FDOT) have generated mitigation credits for wildlife crossing projects. The approach taken by Caltrans for the Laurel Curve Wildlife Habitat Connectivity Project, as discussed in section 5.1, does not directly measure the ecological gain from the wildlife crossing; rather, credits are generated based on the highway footprint within the reach where connectivity would be improved. This straightforward condition-based metric assumes that, within the zone where wildlife connectivity would be improved, increasing permeability of a larger footprint would equate to greater benefits to focal species. The Laurel Curve Project is a proof-of-concept effort that demonstrates a framework for developing credit agreements for wildlife crossing structures, and how credits generated from a wildlife crossing could be applied as mitigation for future transportation projects. FDOT has valued wildlife connectivity mitigation using the habitat connectivity scores calculated by the Florida Department of Environmental Protection’s Uniform Mitigation Assessment Methodology, which expresses credits in terms of the functional gain generated from a proposed wildlife crossing structure. As detailed section 5.2, FDOT has used this standardized

Valuing Wildlife Crossings and Enhancements for Mitigation Credits ES-3 wetland assessment methodology for valuing wildlife connectivity mitigation on several highway projects but does not have a program that allows it to apply credits to other transportation projects.

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