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).

Ecosystem transformation can be defined as the emergence of a self‐organizing, self‐sustaining, ecological or social–ecological system that deviates from prior ecosystem structure and function. These transformations are occurring across the globe; consequently, a static view of ecosystem processes is likely no longer sufficient for managing fish, wildlife, and other species. We present a framework that encompasses three strategies for fish and wildlife managers dealing with ecosystems vulnerable to transformation. Specifically, managers can resist change and strive to maintain existing ecosystem composition, structure, and function; accept transformation when it is not feasible to resist change or when changes are deemed socially acceptable; or direct change to a future ecosystem configuration that would yield desirable outcomes. Choice of a particular option likely hinges on anticipating future change, while also acknowledging that temporal and spatial scales, recent history and current state of the system, and magnitude of change can factor into the decision. This suite of management strategies can be implemented using a structured approach of learning and adapting as ecosystems change.

Intensifying global change is propelling many ecosystems toward irreversible transformations. Natural resource managers face the complex task of conserving these important resources under unprecedented conditions and expanding uncertainty. As once familiar ecological conditions disappear, traditional management approaches that assume the future will reflect the past are becoming increasingly untenable. In the present article, we place adaptive management within the resist–accept–direct (RAD) framework to assist informed risk taking for transforming ecosystems. This approach empowers managers to use familiar techniques associated with adaptive management in the unfamiliar territory of ecosystem transformation. By providing a common lexicon, it gives decision makers agency to revisit objectives, consider new system trajectories, and discuss RAD strategies in relation to current system state and direction of change. Operationalizing RAD adaptive management requires periodic review and update of management actions and objectives; monitoring, experimentation, and pilot studies; and bet hedging to better identify and tolerate associated risks.