C ontemporary ecosystem change driven by a suite of global anthropogenic stressors has had reverberating consequences across genetic, population, community, and ecoregional scales (Díaz et al. 2019). Fine-scale changes in phenology, morphology, abundance, gene frequencies, and distribution of populations and species (eg Staudinger et al. 2013) can scale up to system-level conversions and biome shifts (Scheffer et al. 2009). Often driven by changing climate, many of these changes are manifest in ecological and physical stresses, including invasive-plant incursions, drought, desertification, severe fire, pest outbreaks, and geographic displacement of species. Extreme ecosystem changes are occurring with increasing frequency across a range of biomes, including coral bleaching in the tropics and grassification of shrublands (Figure 1). Ecosystem changes are expected to continue across many biomes even under scenarios with aggressive reductions in greenhouse-gas emissions, with globally distributed and radical ecosystem alterations predicted under high-emission scenarios (Nolan et al. 2018;Reid et al. 2018).We define these intensive and comprehensive system changes as ecosystem transformation (ie the emergence of a selforganizing, self-sustaining ecological or socioecological system that diverges considerably and irreversibly from prior historical ecosystem structure, composition, and function; Noss 1990). Transformations include ecosystem disruptions (eg Embrey et al. 2012) and occur across a range of temporal scales -for instance, from single-event high-intensity fires (Guiterman et al. 2018) to glacial-interglacial transitions spanning many millennia (Nolan et al. 2018) -and range widely in spatial extent, from a local community to entire biomes (Thompson et al. 2021). These changes pose critical threats to ecosystem services and consequently to human health and well-being, clean air and water, food security, sanitation, and disease mitigation (Whitmee et al. 2015).

Natural resource managers worldwide face a growing challenge: Intensifying global change increasingly propels ecosystems toward irreversible ecological transformations. This nonstationarity challenges traditional conservation goals and human well-being. It also confounds a longstanding management paradigm that assumes a future that reflects the past. As once-familiar ecological conditions disappear, managers need a new approach to guide decision-making. The resist–accept–direct (RAD) framework, designed for and by managers, identifies the options managers have for responding and helps them make informed, purposeful, and strategic choices in this context. Moving beyond the diversity and complexity of myriad emerging frameworks, RAD is a simple, flexible, decision-making tool that encompasses the entire decision space for stewarding transforming ecosystems. Through shared application of a common approach, the RAD framework can help the wider natural resource management and research community build the robust, shared habits of mind necessary for a new, twenty-first-century natural resource management paradigm.

Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term ‘climate change resilience,’ frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas.

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Resource managers face mounting challenges when it comes to the implementation of climate change adaptation strategies. Novel adaptation strategies, such as managed relocation, frequently entail embracing substantial risk of unintended harm to the focal ecosystems, in an effort to alleviate serious threats to biological diversity (e.g. extinction). Assessing ecological risks associated with different adaptation strategies is consistently called for, but the process for doing so is often undefined. Here, we describe a collaboration amongst university researchers, agency scientists and resource managers to create a set of ecological risk assessment protocols for managed relocation decision support. These protocols are designed to foster a rigorous assessment of ecological risk, while simultaneously being flexible and easy to use. We describe a collaborative process through which we developed a structure for assessing risk that includes a suite of 17 risk categories aggregated into six overarching groups, which is placed within a broader decision context for managed relocation (e.g. evaluating feasibility, social acceptability). Our risk scoring includes both scaled estimates of risk and perceived confidence in those estimates. Because of differences in the importance of risk categories, we do not recommend a quantitative summary across risk areas, but suggest decision makers make decisions based on three criteria: overall confidence that a proposed action can be confidently evaluated; low overall level or risk across categories; and no single risk category that is highly likely to result in severe adverse outcomes.