Abstract. We propose a framework for hypothesis-testing of stable isotope ratios in ecological studies. Statistical procedures are based on analysis of nested linear models and a residual permutation procedure (RPP) that is employed to evaluate probabilities associated with test statistics. We used simulated examples and a real data set to illustrate the utility and generality of the method. First, we developed a test for differences in centroid location and dispersion of d 13 C and d 15 N values within and among groups of isotopic data. Second, we evaluated magnitude and direction of change in centroid position (termed ''path'') of a pair of isotopic samples separated in space/time relative to paths of other paired sample sets. Third, we compared attributes of path trajectories (size, direction, and shape) over sample sets containing more than two samples to provide a quantitative description of how patterns of isotopic ratios change in response to spatial and temporal gradients. Examples are limited to the bivariate case (d 13 C-d 15 N biplots), but the statistical method can readily be applied to univariate and multivariate cases.

Climate is a critical driver of many fish populations, assemblages, and aquatic communities. However, direct observational studies of climate change impacts on North American inland fishes are rare. In this synthesis, we (1) summarize climate trends that may influence North American inland fish populations and assemblages, (2) compile 31 peer‐reviewed studies of documented climate change effects on North American inland fish populations and assemblages, and (3) highlight four case studies representing a variety of observed responses ranging from warmwater systems in the southwestern and southeastern United States to coldwater systems along the Pacific Coast and Canadian Shield. We conclude by identifying key data gaps and research needs to inform adaptive, ecosystem‐based approaches to managing North American inland fishes and fisheries in a changing climate.

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).

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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.