Ecological restoration is considered an essential activity as we attempt to repair anthropogenic degradation. Yet, resources are limited and it is important that efforts focus on activities that are effective and yield successful restoration. Structured decision making (SDM) is an organized framework that is designed to incorporate differing values across stakeholders and evaluate alternatives. The SDM framework typically consists of six steps: define the decision problem, define objectives and evaluation criteria, develop alternatives, estimate consequences, evaluate trade-offs, and decide, implement, and monitor. Here, we posit that SDM is well suited for ecological restoration, yet remains underused. Specifically, tools such as stakeholder surveys, conceptual modeling, and multi-criteria decision analysis are notably useful in ecological restoration and can be applied under the SDM framework to ensure robust and transparent decision making. We illustrate the application of SDM to ecological restoration with case studies that used SDM alongside ecosystem service assessments, for species-as-risk management, and to assess action desirability across large and diverse stakeholder groups. Finally, we demonstrate how SDM is equipped to handle many of the challenges associated with ecological restoration by identifying commonalities. We contend that increased use of SDM for ecological restoration by environmental managers has the potential to yield wise use of limited resources and more effective restoration outcomes.

Global social and economic changes, alongside climate change, are affecting the operating environment for agriculture, leading to efforts to increase production and yields, typically through the use of agrochemicals like pesticides and fertilizers, expanded irrigation, and changes in seed varieties. Intensification, alongside the expansion of agriculture into new areas, has increased harvest, but has also had numerous well-known impacts on the environment, ultimately resulting in a loss of resilience and lack of sustainability in agro-ecosystems. Combined with features of agricultural systems such as the differential movement of ecosystem services, and interactions among ecosystem services driven in part by management choices, such intensification has disrupted key feedbacks in agricultural systems. These changes have tended to perpetuate the management choices that have led to efficient, productive agriculture, often at the expense of nature and the provision of important nonfood ecosystem services. Here, we explore how agriculture functions as a complex adaptive system. We assess how recent changes have interacted with agro-ecosystem features to result in a loss of resilience, and suggest key research directions to help harmonize production and ecosystem function, drawing primarily on Canadian examples. Enhancing the resilience of agricultural landscapes is critical to the long-term sustainability of agriculture in a rapidly changing world.

Calls for biodiversity conservation practice to be more evidence based are growing, and we agree evidence use in conservation practice needs improvement. However, evidence-based conservation will not be realized without improved access to evidence. In medicine, unlike in conservation, a well-established and well-funded layer of intermediary individuals and organizations engage with medical practitioners, synthesize primary research relevant to decision making, and make evidence easily accessible. These intermediaries prepare targeted evidence summaries and distribute them to practitioners faced with time-sensitive and value-laden decisions. To be effective, these intermediaries, who we refer to as evidence bridges, should identify research topics based on the priorities of practitioners; synthesize evidence; prepare and distribute easy-to-find and easy-to-use evidence summaries; and develop and maintain networks of connections with researchers and practitioners. Based on a review of the literature regarding evidence intermediaries in conservation and environmental management, as well as an anonymous questionnaire searching for such organizations, we found few intermediaries that met all these criteria. Few evidence bridges that do exist are unable to reach most conservation practitioners, which include resource managers in government and industry, conservation organizations, and farmers and other private landowners. We argue that the lack of evidence bridges from research to practitioners contributes to evidence complacency and limits the use of evidence in conservation action. Nevertheless, several existing organizations help reduce the gap between evidence and practice and could serve as a foundation for building additional components of evidence bridges in conservation. Although evidence bridges need expertise in research and evidence synthesis, they also require expertise in identifying and communicating with the community of practitioners most in need of clear and concise syntheses of evidence. Article Impact Statement: Evidence-based conservation will not be realized without improved access to evidence. We call for intermediary evidence bridges.

In a review of landscape-scale empirical studies, Fahrig (2017a) found that ecological responses to habitat fragmentation per se (fragmentation independent of habitat amount) were usually non-significant (>70% of responses) and that 76% of significant relationships were positive, with species abundance, occurrence, richness, and other response variables increasing with habitat fragmentation per se. Fahrig concluded that to date there is no empirical evidence supporting the widespread assumption that a group of small habitat patches generally has lower ecological value than large patches of the same total area. Fletcher et al. (2018) dispute this conclusion, arguing that the literature to date indicates generally negative ecological effects of habitat fragmentation per se. They base their argument largely on extrapolation from patch-scale patterns and mechanisms (effects of patch size and isolation, and edge effects) to landscape-scale effects of habitat fragmentation. We argue that such extrapolation is unreliable because: (1) it ignores other mechanisms, especially those acting at landscape scales (e.g., increased habitat diversity, spreading of risk, landscape complementation) that can counteract effects of the documented patch-scale mechanisms; and (2) extrapolation of a small-scale mechanism to a large-scale pattern is not evidence of that pattern but, rather a prediction that must be tested at the larger scale. Such tests were the subject of Fahrig's review. We find no support for Fletcher et al.'s claim that biases in Fahrig's review would alter its conclusions. We encourage further landscape-scale empirical studies of effects of habitat fragmentation per se, and research aimed at uncovering the mechanisms that underlie positive fragmentation effects.