An adaptive cycle resilience perspective to understand the regime shifts of social-ecological system interactions over the past two millennia in the Tarim River Basin.

Socio-ecological systems (SESs) in arid regions have experienced multiple transformations throughout history due to human activities and natural forces. However, few studies have used the resilience cycle model to explain the resilience status and determinants of SESs over the past two millennia. This study proposes the adaptive cycle resilience (ACR) perspective to investigate regime shifts of socio-ecological system interactions in the Tarim River Basin (TRB) over the past two millennia. An ACR framework combining a piecewise linear regression model (PLR), ACR theory, and physical resilience models has been built to assess and quantify socio-ecological system resilience. Key indicators such as climate variability, settlement numbers, war frequency, glacier accumulation, and oasis area changes are identified and quantified to evaluate SESs adaptability and transformability. Glacier accumulation serves as a proxy for long-term climate change, while oasis area changes reflect the direct impact of human activities and environmental feedback on ecosystem productivity. Population and war indicators provide insights into social system stability and the impact of conflicts on SESs dynamics. The findings reveal that the 7th century and 1850s are critical points of regime shifts in the ACR. 200s BC-350s AD and 700s AD-900s AD are in the forward loop (r-K) period of the ACR. 350s AD-700s AD and 900s AD-1850s AD are the adaptive resilience backward loop (Ω-α) phase. Assessing the historical socio-ecological system resilience and identifying key transition points can inform proactive measures to mitigate potential regime shifts. Combining historical data with resilience theory provides a deep understanding of the ACR of SESs and their driving factors. This enriches the theoretical understanding of SESs and offers a robust case study for future resilience assessments and scenario analyses in arid regions.

Crop booms as regime shifts.

A crop boom is a sudden, nonlinear and intense expansion of a new crop. Despite their large impacts, boom-bust dynamics are not well understood; booms are largely unpredictable and difficult to steer once they unfold. Based on the striking resemblances between land regime shifts and crop booms, we apply complex systems theory, highlighting the potential for regime shifts, to provide new insights about crop boom dynamics. We analyse qualitative and quantitative data of rubber and banana plantation expansion in two forest frontier regions of northern Laos. We show that preconditions, including previous booms, explain the occurrence (why) of booms, and triggers like policy and market changes explain their timing (when). Yet, the most important features of booms, their intensity and nonlinearity (how), strongly depended on internal self-reinforcing feedbacks. We identify built-in feedbacks (neighbourhood effects and imitation) and emergent feedbacks (land rush) and show that they were social in nature, multi-scale from plot to region and subject to thresholds. We suggest that these are regular features of booms and propose a definition and causal-mechanistic explanation of crop booms, examining the overlap between booms and regime shifts and the role of frontiers. We then identify opportunities for management interventions before, during and after booms.

Resilience assessment in complex natural systems.

Ecological resilience is the capability of an ecosystem to maintain the same structure and function and avoid crossing catastrophic tipping points (i.e. undergoing irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: (i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, (ii) it assesses resilience in relation to multiple external drivers and (iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time series of an Atlantic cod population and marine ecosystems in the North Sea and the Mediterranean Sea. We show that Cusp Resilience Assessment is a powerful method to empirically estimate resilience in support of a sustainable management of our constantly adapting ecosystems under global climate change.

A taxonomy of multiple stable states in complex ecological communities.

Natural systems are built from multiple interconnected units, making their dynamics, functioning and fragility notoriously hard to predict. A fragility scenario of particular relevance concerns so-called regime shifts: abrupt transitions from healthy to degraded ecosystem states. An explanation for these shifts is that they arise as transitions between alternative stable states, a process that is well-understood in few-species models. However, how multistability upscales with system complexity remains a debated question. Here, we identify that four different multistability regimes generically emerge in models of species-rich communities and other archetypical complex biological systems assuming random interactions. Across the studied models, each regime consistently emerges under a specific interaction scheme and leaves a distinct set of fingerprints in terms of the number of observed states, their species richness and their response to perturbations. Our results help clarify the conditions and types of multistability that can be expected to occur in complex ecological communities.

Emergent Spatial Patterns Can Indicate Upcoming Regime Shifts in a Realistic Model of Coral Community.

AbstractIncreased stress on coastal ecosystems, such as coral reefs, seagrasses, kelp forests, and other habitats, can make them shift toward degraded, often algae-dominated or barren communities. This has already occurred in many places around the world, calling for new approaches to identify where such regime shifts may be triggered. Theoretical work predicts that the spatial structure of habitat-forming species should exhibit changes prior to regime shifts, such as an increase in spatial autocorrelation. However, extending this theory to marine systems requires theoretical models connecting field-supported ecological mechanisms to data and spatial patterns at relevant scales. To do so, we built a spatially explicit model of subtropical coral communities based on experiments and long-term datasets from Rapa Nui (Easter Island, Chile), to test whether spatial indicators could signal upcoming regime shifts in coral communities. Spatial indicators anticipated degradation of coral communities following increases in frequency of bleaching events or coral mortality. However, they were generally unable to signal shifts that followed herbivore loss, a widespread and well-researched source of degradation, likely because herbivory, despite being critical for the maintenance of corals, had comparatively little effect on their self-organization. Informative trends were found under both equilibrium and nonequilibrium conditions but were determined by the type of direct neighbor interactions between corals, which remain relatively poorly documented. These inconsistencies show that while this approach is promising, its application to marine systems will require detailed information about the type of stressor and filling current gaps in our knowledge of interactions at play in coral communities.

Toward a network perspective in coastal ecosystem management.

Environmental management in coastal ecosystems has been challenged by the complex cumulative effects that occur when many small issues result in large ecological shifts. Current environmental management of these spaces focuses on identifying and limiting problematic stressors via a series of assessment techniques. Whilst there is a strong desire among managers to consider complexity in ecological responses to cumulative effects, current approaches for assessing risk focus on breaking down the issues into multiple cause and effect relationships. However, uncertainty arises when data and information for a place are limited, as is commonly the case, and this creates decision paralysis while more information is generated. Here, we discuss how ecological understanding of network interactions in coastal marine ecosystems can be used as a lens to bring together multiple lines of evidence and create actions. We list and describe four characteristics of marine ecosystem interaction networks including the possibility for; 1) indirect effects, 2) effects that emerge as stressor magnitude increases the number of network components implicated, 3) network interactions that amplify these indirect effects, and 4) feedbacks that reinforce or stabilise against indirect effects. We then link these four characteristics to three case studies of common coastal environmental issues to demonstrate how a general understanding of ecological interaction networks can enhance priorities for stressor management that can be applied even when specific data is limited.

Ecological indicators reveal historical regime shifts in the Black Sea ecosystem.

Background: The Black Sea is one of the most anthropogenically disturbed marine ecosystems in the world because of introduced species, fisheries overexploitation, nutrient enrichment via pollution through river discharge, and the impacts of climate change. It has undergone significant ecosystem transformations since the 1960s. The infamous anchovy and alien warty comb jelly Mnemiopsis leidyi shift that occurred in 1989 is the most well-known example of the drastic extent of anthropogenic disturbance in the Black Sea. Although a vast body of literature exists on the Black Sea ecosystem, a holistic look at the multidecadal changes in the Black Sea ecosystem using an ecosystem- and ecology-based approach is still lacking. Hence, this work is dedicated to filling this gap. Methods: First, a dynamic food web model of the Black Sea extending from 1960 to 1999 was established and validated against time-series data. Next, an ecological network analysis was performed to calculate the time series of synthetic ecological indicators, and a regime shift analysis was performed on the time series of indicators. Results: The model successfully replicated the regime shifts observed in the Black Sea. The results showed that the Black Sea ecosystem experienced four regime shifts and was reorganized due to effects instigated by overfishing in the 1960s, eutrophication and establishment of trophic dead-end organisms in the 1970s, and overfishing and intensifying interspecies trophic competition by the overpopulation of some r-selected organisms (i.e., jellyfish species) in the 1980s. Overall, these changes acted concomitantly to erode the structure and function of the ecosystem by manipulating the food web to reorganize itself through the introduction and selective removal of organisms and eutrophication. Basin-wide, cross-national management efforts, especially with regard to pollution and fisheries, could have prevented the undesirable changes observed in the Black Sea ecosystem and should be immediately employed for management practices in the basin to prevent such drastic ecosystem fluctuations in the future.

Microcosm experiment combined with process-based modeling reveals differential response and adaptation of aquatic primary producers to warming and agricultural run-off.

Fertilizers, pesticides and global warming are threatening freshwater aquatic ecosystems. Most of these are shallow ponds or slow-flowing streams or ditches dominated by submerged macrophytes, periphyton or phytoplankton. Regime shifts between the dominance of these primary producers can occur along a gradient of nutrient loading, possibly triggered by specific disturbances influencing their competitive interactions. However, phytoplankton dominance is less desirable due to lower biodiversity and poorer ecosystem function and services. In this study, we combined a microcosm experiment with a process-based model to test three hypotheses: 1) agricultural run-off (ARO), consisting of nitrate and a mixture of organic pesticides and copper, differentially affects primary producers and enhances the risk of regime shifts, 2) warming increases the risk of an ARO-induced regime shift to phytoplankton dominance and 3) custom-tailored process-based models support mechanistic understanding of experimental results through scenario comparison. Experimentally exposing primary producers to a gradient of nitrate and pesticides at 22°C and 26°C supported the first two hypotheses. ARO had direct negative effects on macrophytes, while phytoplankton gained from warming and indirect effects of ARO like a reduction in the competitive pressure exerted by other groups. We used the process-based model to test eight different scenarios. The best qualitative fit between modeled and observed responses was reached only when taking community adaptation and organism acclimation into account. Our results highlight the importance of considering such processes when attempting to predict the effects of multiple stressors on natural ecosystems.

Short and long-term temperature variations drive recruitment variability in marine and estuarine juvenile fishes.

Understanding the long-term effects of climatic factors on key species' recruitment is crucial to species management and conservation. Here, we analysed the recruitment variability of key species (Dicentrarchus labrax, Platichthys flesus, Solea solea, Pomatoschistus microps and Pomatoschistus minutus) in an estuary between 2003 and 2019, and related it with the prevailing local and large-scale environmental factors. Using a dynamic factor analysis (DFA), juvenile abundance data were grouped into three common trends linked to different habitat uses and life cycle characteristics, with significant effect of temperature-related variables on fish recruitment: Sea surface temperature and the Atlantic Multidecadal Oscillation. In 2010, a regime shift in the North Atlantic coincided with a shift in the common trends, particularly a decline in P. flesus and S. solea trend. This work highlights the thermophilic character of fish recruitment and the necessity to investigate key biological processes in the context of species-specific responses to climate change.

Material legacies can degrade resilience: Structure-retaining disturbances promote regime shifts on coral reefs.

Standing dead structures of habitat-forming organisms (e.g., dead trees, coral skeletons, oyster shells) killed by a disturbance are material legacies that can affect ecosystem recovery processes. Many ecosystems are subject to different types of disturbance that either remove biogenic structures or leave them intact. Here we used a mathematical model to quantify how the resilience of coral reef ecosystems may be differentially affected following structure-removing and structure-retaining disturbance events, focusing in particular on the potential for regime shifts from coral to macroalgae. We found that dead coral skeletons could substantially diminish coral resilience if they provided macroalgae refuge from herbivory, a key feedback associated with the recovery of coral populations. Our model shows that the material legacy of dead skeletons broadens the range of herbivore biomass over which coral and macroalgae states are bistable. Hence, material legacies can alter resilience by modifying the underlying relationship between a system driver (herbivory) and a state variable (coral cover).

Stable landings mask irreversible community reorganizations in an overexploited Mediterranean ecosystem.

Cumulative human pressures and climate change can induce nonlinear discontinuous dynamics in ecosystems, known as regime shifts. Regime shifts typically imply hysteresis, a lacking or delayed system response when pressures are reverted, which can frustrate restoration efforts. Here, we investigate whether the northern Adriatic Sea fish and macroinvertebrate community, as depicted by commercial fishery landings, has undergone regime shifts over the last 40 years, and the reversibility of such changes. We use a stochastic cusp model to show that, under the interactive effect of fishing pressure and water warming, the community reorganized through discontinuous changes. We found that part of the community has now reached a new stable state, implying that a recovery towards previous baselines might be impossible. Interestingly, total landings remained constant across decades, masking the low resilience of the community. Our study reveals the importance of carefully assessing regime shifts and resilience in marine ecosystems under cumulative pressures and advocates for their inclusion into management.

Spatial dynamics of a vegetation model with uptake-diffusion feedback in an arid environment.

Vegetation patterns with a variety of structures is amazing phenomena in arid or semi-arid areas, which can identify the evolution law of vegetation and are typical signals of ecosystem functions. Many achievements have been made in this respect, yet the mechanisms of uptake-diffusion feedback on the pattern structures of vegetation is not fully understood. To well reveal the influences of parameters perturbation on the pattern formation of vegetation, we give a comprehensive analysis on a vegetation-water model in the forms of reaction-diffusion equation which is posed by Zelnik et al. (Proc Natl Acad Sci 112:12,327-12,331, 2015). We obtain the exact parameters range for stationary patterns and show the dynamical behaviors near the bifurcation point based on nonlinear analysis. It is found that the model has the properties of spot, labyrinth and gap patterns. Moreover, water diffusion rate prohibits the growth of vegetation while shading parameter promotes the increase of vegetation biomass. Our results show that gradual transitions from uniform state to gap pattern can occur for suitable value of parameters which may induce the emergence of desertification.

An SIRS model with nonmonotone incidence and saturated treatment in a changing environment.

Nonmonotone incidence and saturated treatment are incorporated into an SIRS model under constant and changing environments. The nonmonotone incidence rate describes the psychological or inhibitory effect: when the number of the infected individuals exceeds a certain level, the infection function decreases. The saturated treatment function describes the effect of infected individuals being delayed for treatment due to the limitation of medical resources. In a constant environment, the model undergoes a sequence of bifurcations including backward bifurcation, degenerate Bogdanov-Takens bifurcation of codimension 3, degenerate Hopf bifurcation as the parameters vary, and the model exhibits rich dynamics such as bistability, tristability, multiple periodic orbits, and homoclinic orbits. Moreover, we provide some sufficient conditions to guarantee the global asymptotical stability of the disease-free equilibrium or the unique positive equilibrium. Our results indicate that there exist three critical values [Formula: see text] and [Formula: see text] for the treatment rate r: (i) when [Formula: see text], the disease will disappear; (ii) when [Formula: see text], the disease will persist. In a changing environment, the infective population starts along the stable disease-free state (or an endemic state) and surprisingly continues tracking the unstable disease-free state (or a limit cycle) when the system crosses a bifurcation point, and eventually tends to the stable endemic state (or the stable disease-free state). This transient tracking of the unstable disease-free state when [Formula: see text] predicts regime shifts that cause the delayed disease outbreak in a changing environment. Furthermore, the disease can disappear in advance (or belatedly) if the rate of environmental change is negative and large (or small). The transient dynamics of an infectious disease heavily depend on the initial infection number and rate or the speed of environmental change.

Temporary Allee effects among non-stationary recruitment dynamics in depleted gadid and flatfish populations.

Many considerably declined fish populations have not fully recovered despite reductions in fishing pressure. One of the possible causes of impaired recovery is the (demographic) Allee effect. To investigate whether low-abundance recruitment dynamics can switch between compensation and depensation, the latter implying the presence of the Allee effect, we analysed the stock-recruitment time series of 17 depleted cod-type and flatfish populations using a Bayesian change point model. The recruitment dynamics were represented with the sigmoidal Beverton-Holt and the Saila-Lorda stock-recruitment models, allowing the parameters of the models to shift at a priori unknown change points. Our synthesis study questions the common assumption that recruitment is stationary and compensatory and the high amount of scatteredness often present in stock-recruitment data is only due to random variation. When a moderate amount of such variation was assumed, stock-recruitment dynamics were best explained by a non-stationary model for 53% of the populations, which suggests that these populations exhibit temporal changes in the stock-recruitment relationship. For four populations, we found shifts between compensation and depensation, suggesting the presence of temporary Allee effects. However, the evidence of Allee effects was highly dependent on the priors of the stock-recruitment model parameters and the amount of random variation assumed. Nonetheless, detection of changes in low-abundance recruitment is essential in stock assessment since such changes affect the renewal ability of the population and, ultimately, its sustainable harvest limits.

Bridging Theories for Ecosystem Stability Through Structural Sensitivity Analysis of Ecological Models in Equilibrium.

Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from different angles. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitivity analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into proportional ones, while maintaining the equilibrium biomass densities and material flux rates, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the proportionalized versions, even though they describe the same biomass values and material flows. We use these findings to critically discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.

Modelling coupled human-environment complexity for the future of the biosphere: strengths, gaps and promising directions.

Humans and the environment form a single complex system where humans not only influence ecosystems but also react to them. Despite this, there are far fewer coupled human-environment system (CHES) mathematical models than models of uncoupled ecosystems. We argue that these coupled models are essential to understand the impacts of social interventions and their potential to avoid catastrophic environmental events and support sustainable trajectories on multi-decadal timescales. A brief history of CHES modelling is presented, followed by a review spanning recent CHES models of systems including forests and land use, coral reefs and fishing and climate change mitigation. The ability of CHES modelling to capture dynamic two-way feedback confers advantages, such as the ability to represent ecosystem dynamics more realistically at longer timescales, and allowing insights that cannot be generated using ecological models. We discuss examples of such key insights from recent research. However, this strength brings with it challenges of model complexity and tractability, and the need for appropriate data to parameterize and validate CHES models. Finally, we suggest opportunities for CHES models to improve human-environment sustainability in future research spanning topics such as natural disturbances, social structure, social media data, model discovery and early warning signals. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

Microclimate predicts kelp forest extinction in the face of direct and indirect marine heatwave effects.

Marine heatwaves threaten the persistence of kelp forests globally. However, the observed responses of kelp forests to these events have been highly variable on local scales. Here, we synthesize distribution data from an environmentally diverse region to examine spatial patterns of canopy kelp persistence through an unprecedented marine heatwave. We show that, although often overlooked, temperature variation occurring at fine spatial scales (i.e., a few kilometers or less) can be a critical driver of kelp forest persistence during these events. Specifically, though kelp forests nearly all persisted toward the cool outer coast, inshore areas were >3°C warmer at the surface and experienced extensive kelp loss. Although temperatures remained cool at depths below the thermocline, kelp persistence in these thermal refugia was strongly constrained by biotic interactions, specifically urchin populations that increased during the heatwave and drove transitions to urchin barrens in deeper rocky habitat. Urchins were, however, largely absent from mixed sand and cobble benthos, leading to an unexpected association between bottom substrate and kelp forest persistence at inshore sites with warm surface waters. Our findings demonstrate both that warm microclimates increase the risk of habitat loss during marine heatwaves and that biotic interactions modified by these events will modulate the capacity of cool microclimates to serve as thermal refugia.

Multiple-stressor exposure of aquatic food webs: Nitrate and warming modulate the effect of pesticides.

Shallow lakes provide essential ecological and environmental services but are exposed to multiple stressors, including agricultural runoff (ARO) and climate warming, which may act on different target receptors disrupting their normal functioning. We performed a microcosm experiment to determine the individual and combined effects of three stressors-pesticides, nitrate and climate warming-on two trophic levels representative of communities found in shallow lakes. We used three submerged macrophyte species (Myriophyllum spicatum, Potamogeton perfoliatus, Elodea nuttallii), eight benthic or pelagic microalgal species and three primary consumer species (Daphnia magna, Lymnaea stagnalis, Dreissena polymorpha) with different feeding preferences for benthic and pelagic primary producers. Eight different treatments consisted of a control, only nitrate, a pesticide cocktail, and a combination of nitrate and pesticides representing ARO, each replicated at ambient temperature and +3.5°C, mimicking climate warming. Pesticides negatively affected all functional groups except phytoplankton, which increased. Warming and nitrate modified these effects. Strong but opposite pesticide and warming effects on Myriophyllum drove the response of the total macrophyte biomass. Nitrate significantly suppressed Myriophyllum final biomass, but not overall macrophyte and microalgal biomass. Nitrate and pesticides in combination caused a macrophyte decline, and the system tipped towards phytoplankton dominance. Strong synergistic or even reversed stressor interaction effects were observed for macrophytes or periphyton. We emphasize the need for more complex community- and ecosystem-level studies incorporating multiple stressor scenarios to define safe operating spaces.

Regime transition Shapes the Composition, Assembly Processes, and Co-occurrence Pattern of Bacterioplankton Community in a Large Eutrophic Freshwater Lake.

At certain nutrient concentrations, shallow freshwater lakes are generally characterized by two contrasting ecological regimes with disparate patterns of biodiversity and biogeochemical cycles: a macrophyte-dominated regime (MDR) and a phytoplankton-dominated regime (PDR). To reveal ecological mechanisms that affect bacterioplankton along the regime shift, Illumina MiSeq sequencing of the 16S rRNA gene combined with a novel network clustering tool (Manta) were used to identify patterns of bacterioplankton community composition across the regime shift in Taihu Lake, China. Marked divergence in the composition and ecological assembly processes of bacterioplankton community was observed under the regime shift. The alpha diversity of the bacterioplankton community consistently and continuously decreased with the regime shift from MDR to PDR, while the beta diversity presents differently. Moreover, as the regime shifted from MDR to PDR, the contribution of deterministic processes (such as environmental selection) to the assembly of bacterioplankton community initially decreased and then increased again as regime shift from MDR to PDR, most likely as a consequence of differences in nutrient concentration. The topological properties, including modularity, transitivity and network diameter, of the bacterioplankton co-occurrence networks changed along the regime shift, and the co-occurrences among species changed in structure and were significantly shaped by the environmental variables along the regime transition from MDR to PDR. The divergent environmental state of the regimes with diverse nutritional status may be the most important factor that contributes to the dissimilarity of bacterioplankton community composition along the regime shift.

Large herbivores suppress liana infestation in an African savanna.

African savannas are the last stronghold of diverse large-mammal communities, and a major focus of savanna ecology is to understand how these animals affect the relative abundance of trees and grasses. However, savannas support diverse plant life-forms, and human-induced changes in large-herbivore assemblages-declining wildlife populations and their displacement by livestock-may cause unexpected shifts in plant community composition. We investigated how herbivory affects the prevalence of lianas (woody vines) and their impact on trees in an East African savanna. Although scarce (<2% of tree canopy area) and defended by toxic latex, the dominant liana, Cynanchum viminale (Apocynaceae), was eaten by 15 wild large-herbivore species and was consumed in bulk by native browsers during experimental cafeteria trials. In contrast, domesticated ungulates rarely ate lianas. When we experimentally excluded all large herbivores for periods of 8 to 17 y (simulating extirpation), liana abundance increased dramatically, with up to 75% of trees infested. Piecewise exclusion of different-sized herbivores revealed functional complementarity among size classes in suppressing lianas. Liana infestation reduced tree growth and reproduction, but herbivores quickly cleared lianas from trees after the removal of 18-y-old exclosure fences (simulating rewilding). A simple model of liana contagion showed that, without herbivores, the long-term equilibrium could be either endemic (liana-tree coexistence) or an all-liana alternative stable state. We conclude that ongoing declines of wild large-herbivore populations will disrupt the structure and functioning of many African savannas in ways that have received little attention and that may not be mitigated by replacing wildlife with livestock.