Mining provides resources for people but can pose risks to ecosystems that support cultural keystone species. Our synthesis reviews relevant aspects of mining operations, describes the ecology of salmonid-bearing watersheds in northwestern North America, and compiles the impacts of metal and coal extraction on salmonids and their habitat. We conservatively estimate that this region encompasses nearly 4000 past producing mines, with present-day operations ranging from small placer sites to massive open-pit projects that annually mine more than 118 million metric tons of earth. Despite impact assessments that are intended to evaluate risk and inform mitigation, mines continue to harm salmonid-bearing watersheds via pathways such as toxic contaminants, stream channel burial, and flow regime alteration. To better maintain watershed processes that benefit salmonids, we highlight key windows during the mining governance life cycle for science to guide policy by more accurately accounting for stressor complexity, cumulative effects, and future environmental change.

This paper reviews trends in the academic literature on cumulative effects assessment (CEA) of disturbance on forest ecosystems to advance research in the broader context of impact assessments. Disturbance is any distinct spatiotemporal event that disrupts the structure and composition of an ecosystem affecting resource availability. We developed a Python package to automate search term selection, write search strategies, reduce bias and improve the efficient and effective selection of articles from academic databases and grey literature. We identified 148 peer-reviewed literature published between 1986 and 2022 and conducted an inductive and deductive thematic analysis of the results. Our findings revealed that CEA studies are concentrated in the global north, with most publications from authors affiliated with government agencies in the USA and Canada. Methodological and analytical approaches are less interdisciplinary but mainly quantitative and expert-driven, involving modeling the impacts of disturbances on biophysical valued components. Furthermore, the assessment of socioeconomic valued components, including the effects of disturbance on Indigenous wellbeing connected to forests, has received less attention. Even though there is a high preference for regional assessment, challenges with data access, quality, and analysis, especially baseline data over long periods, are hampering effective CEA. Few articles examined CEA - policy/management nexus. Of the few studies, challenges such as the inadequate implementation of CEA mitigation strategies due to policy drawbacks and resource constraints, the high cost of monitoring multiple indicators, and poor connections between scenarios/modeling and management actions were paramount. Future CEA research is needed to broaden our understanding of how multiple disturbance affects forests in the global south and coupled social and ecological systems and their implications for sustainable forest management.

The Poweshiek skipperling ( Oarisma poweshiek ) is a critically endangered grassland butterfly with six populations remaining in the United States and Canada. The single Canadian population, with the largest remaining contiguous habitat, includes less than ~50 observed individuals and extirpation is potentially imminent. Captive breeding is underway and there is a need to locate suitable sites for reintroduction and habitat management. Species distribution models (SDMs) predict habitat quality and guide management decisions. Most SDMs rely on statistical validation as a surrogate metric for accuracy, with presence‐only SDMs usually reporting area under the curve (AUC). Although experts have long cautioned against relying on statistical validation alone, accuracy is rarely field‐validated. We developed a presence‐only SDM using the maximum entropy (Maxent) method to predict probability of occurrence for the Poweshiek skipperling and determine environmental covariates associated with high probability of occurrence. We collected two independent datasets to (a) calibrate our model to predict categories of habitat quality (using factor analysis) and (b) compare expected and observed habitat quality to calculate model accuracy. Statistical validation showed that we predicted presence‐absence of training data with high accuracy (AUC = 0.98). Covariates responsible for most of the variation in probability of occurrence included soil drainage, habitat patch size, and land use type. Only 0.4% of the study area was expected to represent good‐excellent habitat with the remaining 99.6% medium‐poor. Our model predicted novel habitat quality with 81% accuracy (better than chance). Poor‐medium habitat was predicted more accurately (92%) than good‐excellent habitat (54%). Our model showed better accuracy than most other field‐validated SDMs reviewed. We reiterate calls for greater field‐validation of SDMs: if we had relied on statistical validation alone, perceived accuracy of our model would be inflated. Finally, managers can use our results to reliably exclude predicted poor‐medium habitats as candidates for Poweshiek skipperling habitat management or reintroduction.

Westwood, A. R., C. Staicer, P. Sölymos, S. Haché, T. Fontaine, E. Bayne, and D. Mazerolle. 2019. Estimating the conservation value of protected areas in Maritime Canada for two species at risk: the Olive-sided Flycatcher (Contopus cooperi) and Canada Warbler (Cardellina canadensis). Avian Conservation and Ecology 14(1):16. https://doi.org/10.5751/ACE-01359-140116

Westwood, A. R., N. K. Barker, S. Grant, A. Amos, A. F. Camfield, K. Cooper, F. V. Dénes, F. Jean-Gagnon, L. McBlane, F. K. A. Schmiegelow, J. I. Simpson, S. M. Slattery, D. J. H. Sleep, S. Sliwa, J. V. Wells, and D. M. Whitaker. 2020. Toward actionable, coproduced research on boreal birds focused on building respectful partnerships. Avian Conservation and Ecology 15(1):26. https://doi.org/10.5751/ACE-01589-150126