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Conservation planners often rely on heuristic indices when challenged with prioritizing potential projects under a constrained budget. This paper presents a comparative analysis of several prioritization indices (PIs) of culvert fish passage barriers, which can contribute to declines in anadromous fish populations. A federal injunction requires Washington state to restore 90% of habitat blocked by state‐owned culverts by 2030, prompting the development of numerous PIs, by various entities (i.e., counties, cities) within the injunction area. Our comparative analysis of PIs within the injunction Case Area investigates their ability to distinguish between barriers, their transferability in terms of scoring metrics, how scoring weights differ, and the preferences implied thereby. We document the use of six distinct PI methods by 10 entities and find that some PIs used many shared metrics, whereas others used a high percentage of unique metrics that would be difficult to replicate outside the entity's jurisdiction. Although habitat potential, habitat quantity, and connectivity were considered across all PIs, we found a high level of variation in terms of the metric weights. Our methods can be employed in other geographies or for other restoration PI planning efforts, and our results may facilitate the development and refinement of future PIs. [ABSTRACT FROM AUTHOR]

Fishing impacts biodiversity on multiple levels, potentially resulting in unintended feedbacks to the economic performance of the fishery over time. For example, targeting observable traits within a population can impact genetic diversity and targeting valuable species can impact biodiversity at the ecosystem level. The bioeconomic literature, however, has given little attention to the effect of fishing on population diversity, even though population diversity contributes to ecosystem services and estimates of population extinction rates are three orders of magnitude higher than species extinction rates. Here we develop a stochastic bioeconomic model that links the harvest of multiple salmon populations in a single commercial fishery to the trajectory of population diversity in a salmon stock complex. We parameterize our model with biological and economic data from the Copper River Chinook salmon fishery. We show that markets can incentivize the degradation of population diversity, reducing infra-marginal fishery rents, and increasing variability in economic returns. We also show that second-best management can conserve population diversity and improve welfare. Furthermore, depending on fishermen's time preferences, this management strategy is potentially self-financing.

Habitat restoration efforts are often conducted under limited budgets and information. Explicitly incorporating data on project costs can improve the effectiveness of restoration investments but gathering precise data for future projects is often infeasible at the planning stage. We demonstrate econometric and machine learning methods for improving the accessibility of cost information for restoration planning. Using geospatial matching methods, we combine 15 years of spatially explicit project records for over 1200 culvert fish passage barrier restoration worksites across the Pacific Northwest of the United States with data layers of hypothesized drivers of construction costs. We distinguish between two objectives in analyzing cost data: inference to identify cost drivers and prediction of future project costs. For inference, we multiple linear regression and find that the variables channel bankfull width and slope, road speed class, developed and agricultural land covers, and proximity to privately managed industrial land are associated with culvert restoration costs and may serve as strong proxies in a planning setting. For prediction, we use boosted regression trees to make out-of-sample projections of restoration costs for over 27,000 barrier culverts documented in state inventories. The distribution of these cost projections over space and across jurisdictions reveal higher, and more heterogeneous, culvert restoration costs in the Puget Sound region than in other nearby areas. Our results are directly applicable for resource managers making fish passage restoration decisions and serve as a template for the use of econometrics and machine learning to analyze costs recorded in restoration project databases in other contexts. [ABSTRACT FROM AUTHOR]