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Global environmental change is pushing many socio-environmental systems towards critical thresholds, where ecological systems’ states are on the precipice of tipping points and interventions are needed to navigate or avert impending transitions. Flickering, where a system vacillates between alternative stable states, is an early warning signal of transitions to alternative ecological regimes. However, while flickering may presage an ecological tipping point, these dynamics also pose unique challenges for human adaptation. We link an ecological model that can exhibit flickering to a model of human environmental adaptation to explore the impact of flickering on the utility of adaptive agents. When adaptive capacity is low, flickering causes wellbeing to decline disproportionately. As a result, flickering dynamics move forward the optimal timing of a transformational change that can secure wellbeing despite environmental variability. The implications of flickering on communities faced with desertification, fisheries collapse, and ecosystem change are explored as possible case studies. Flickering, driven in part by climate change and extreme events, may already be impacting communities. Our results suggest that governance interventions investing in adaptive capacity or facilitating transformational change before flickering arises could blunt the negative impact of flickering as socio-environmental systems pass through tipping points. 

Species ranges are shifting in response to climate change, but most predictions disregard food–web interactions and, in particular, if and how such interactions change through time. Predator–prey interactions could speed up species range shifts through enemy release or create lags through biotic resistance. Here, we developed a spatially explicit model of interacting species, each with a thermal niche and embedded in a size-structured food–web across a temperature gradient that was then exposed to warming. We also created counterfactual single species models to contrast and highlight the effect of trophic interactions on range shifts. We found that dynamic trophic interactions hampered species range shifts across 450 simulated food–webs with up to 200 species each over 200 years of warming. All species experiencing dynamic trophic interactions shifted more slowly than single-species models would predict. In addition, the trailing edges of larger bodied species ranges shifted especially slowly because of ecological subsidies from small shifting prey. Trophic interactions also reduced the numbers of locally novel species, novel interactions and productive species, thus maintaining historical community compositions for longer. Current forecasts ignoring dynamic food–web interactions and allometry may overestimate species' tendency to track climate change. 

Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generative models, or other supervised learning techniques. Each of these cases requires knowledge of and a method for characterizing the macro-state(s) of the system. This presents a challenge for studying novel systems where there may be little prior knowledge. Here, we present a new unsupervised method of detecting emergent behavior in complex systems, and discerning between distinct collective behaviors. We require only metrics, d (1) , d (2) , defined on the set of agents, X , which measure agents’ nearness in variables of interest. We apply the method of diffusion maps to the systems ( X , d ( i ) ) to recover efficient embeddings of their interaction networks. Comparing these geometries, we formulate a measure of similarity between two networks, called the map alignment statistic (MAS). A large MAS is evidence that the two networks are codetermined in some fashion, indicating an emergent relationship between the metrics d (1) and d (2) . Additionally, the form of the macro-scale organization is encoded in the covariances among the two sets of diffusion map components. Using these covariances we discern between different modes of collective behavior in a data-driven, unsupervised manner. This method is demonstrated on a synthetic flocking model as well as empirical fish schooling data. We show that our state classification subdivides the known behaviors of the school in a meaningful manner, leading to a finer description of the system’s behavior. 

Sexual division of labor with females as gatherers and males as hunters is a major empirical regularity of hunter-gatherer ethnography, suggesting an ancestral behavioral pattern. We present an archeological discovery and meta-analysis that challenge the man-the-hunter hypothesis. Excavations at the Andean highland site of Wilamaya Patjxa reveal a 9000-year-old human burial (WMP6) associated with a hunting toolkit of stone projectile points and animal processing tools. Osteological, proteomic, and isotopic analyses indicate that this early hunter was a young adult female who subsisted on terrestrial plants and animals. Analysis of Late Pleistocene and Early Holocene burial practices throughout the Americas situate WMP6 as the earliest and most secure hunter burial in a sample that includes 10 other females in statistical parity with early male hunter burials. The findings are consistent with nongendered labor practices in which early hunter-gatherer females were big-game hunters. 

Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s land was inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis. 

Abstract The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.