Contributions of human cultures to biodiversity and ecosystem conservation.

The expansion of globalized industrial societies is causing global warming, ecosystem degradation, and species and language extinctions worldwide. Mainstream conservation efforts still focus on nature protection strategies to revert this crisis, often overlooking the essential roles of Indigenous Peoples and Local Communities (IP&LC) in protecting biodiversity and ecosystems globally. Here we assess the scientific literature to identify relationships between biodiversity (including ecosystem diversity) and cultural diversity, and investigate how these connections may affect conservation outcomes in tropical lowland South America. Our assessment reveals a network of interactions and feedbacks between biodiversity and diverse IP&LC, suggesting interconnectedness and interdependencies from which multiple benefits to nature and societies emerge. We illustrate our findings with five case studies of successful conservation models, described as consolidated or promising 'social-ecological hope spots', that show how engagement with IP&LC of various cultures may be the best hope for biodiversity and ecosystem conservation, particularly when aligned with science and technology. In light of these five inspiring cases, we argue that conservation science and policies need to recognize that protecting and promoting both biological and cultural diversities can provide additional co-benefits and solutions to maintain ecosystems resilient in the face of global changes.

Critical transitions in the Amazon forest system.

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1-3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

Targeted rainfall enhancement as an objective of forestation.

Forestation efforts are accelerating across the globe in the fight against global climate change, in order to restore biodiversity, and to improve local livelihoods. Yet, so far the non-local effects of forestation on rainfall have largely remained a blind spot. Here we build upon emerging work to propose that targeted rainfall enhancement may also be considered in the prioritization of forestation. We show that the tools to achieve this are rapidly becoming available, but we also identify drawbacks and discuss which further developments are still needed to realize robust assessments of the rainfall effects of forestation in the face of climate change. Forestation programs may then mitigate not only global climate change itself but also its adverse effects in the form of drying.

Network motifs shape distinct functioning of Earth's moisture recycling hubs.

Earth's hydrological cycle critically depends on the atmospheric moisture flows connecting evaporation to precipitation. Here we convert a decade of reanalysis-based moisture simulations into a high-resolution global directed network of spatial moisture provisions. We reveal global and local network structures that offer a new view of the global hydrological cycle. We identify four terrestrial moisture recycling hubs: the Amazon Basin, the Congo Rainforest, South Asia and the Indonesian Archipelago. Network motifs reveal contrasting functioning of these regions, where the Amazon strongly relies on directed connections (feed-forward loops) for moisture redistribution and the other hubs on reciprocal moisture connections (zero loops and neighboring loops). We conclude that Earth's moisture recycling hubs are characterized by specific topologies shaping heterogeneous effects of land-use changes and climatic warming on precipitation patterns.

Exceeding 1.5°C global warming could trigger multiple climate tipping points.

Climate tipping points occur when change in a part of the climate system becomes self-perpetuating beyond a warming threshold, leading to substantial Earth system impacts. Synthesizing paleoclimate, observational, and model-based studies, we provide a revised shortlist of global "core" tipping elements and regional "impact" tipping elements and their temperature thresholds. Current global warming of ~1.1°C above preindustrial temperatures already lies within the lower end of some tipping point uncertainty ranges. Several tipping points may be triggered in the Paris Agreement range of 1.5 to <2°C global warming, with many more likely at the 2 to 3°C of warming expected on current policy trajectories. This strengthens the evidence base for urgent action to mitigate climate change and to develop improved tipping point risk assessment, early warning capability, and adaptation strategies.

Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest.

Tipping elements are nonlinear subsystems of the Earth system that have the potential to abruptly shift to another state if environmental change occurs close to a critical threshold with large consequences for human societies and ecosystems. Among these tipping elements may be the Amazon rainforest, which has been undergoing intensive anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations from climatological rainfall regimes may cause local forest collapse that cascades through the coupled forest-climate system. We develop a conceptual dynamic network model to isolate and uncover the role of atmospheric moisture recycling in such tipping cascades. We account for heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, a future climate characterized by permanent drought conditions could trigger a transition to an open canopy state particularly in the southern Amazon. The loss of atmospheric moisture recycling contributes to one-third of the tipping events. Thus, by exceeding local thresholds in forest adaptive capacity, local climate change impacts may propagate to other regions of the Amazon basin, causing a risk of forest shifts even in regions where critical thresholds have not been crossed locally.

Feedback in tropical forests of the Anthropocene.

Tropical forests are complex systems containing myriad interactions and feedbacks with their biotic and abiotic environments, but as the world changes fast, the future of these ecosystems becomes increasingly uncertain. In particular, global stressors may unbalance the feedbacks that stabilize tropical forests, allowing other feedbacks to propel undesired changes in the whole ecosystem. Here, we review the scientific literature across various fields, compiling known interactions of tropical forests with their environment, including the global climate, rainfall, aerosols, fire, soils, fauna, and human activities. We identify 170 individual interactions among 32 elements that we present as a global tropical forest network, including countless feedback loops that may emerge from different combinations of interactions. We illustrate our findings with three cases involving urgent sustainability issues: (1) wildfires in wetlands of South America; (2) forest encroachment in African savanna landscapes; and (3) synergistic threats to the peatland forests of Borneo. Our findings reveal an unexplored world of feedbacks that shape the dynamics of tropical forests. The interactions and feedbacks identified here can guide future qualitative and quantitative research on the complexities of tropical forests, allowing societies to manage the nonlinear responses of these ecosystems in the Anthropocene.

Effects of land-use change in the Amazon on precipitation are likely underestimated.

The Amazon forest enhances precipitation levels regionally as trees take up water from the soil and release it back into the atmosphere through transpiration. Therefore, land-use changes in the Amazon affect precipitation patterns but to what extent remains unclear. Recent studies used hydrological and atmospheric models to estimate the contribution of tree transpiration to precipitation but assumed that precipitation decreases proportionally to the transpired portion of atmospheric moisture. Here, we relaxed this assumption by, first, relating observed hourly precipitation levels to atmospheric column water vapor in a relatively flat study area encompassing a large part of the Amazon. We found that the effect of column water vapor on hourly precipitation was strongly nonlinear, showing a steep increase in precipitation above a column water vapor content of around 60 mm. Next, we used published atmospheric trajectories of moisture from tree transpiration across the whole Amazon to estimate the transpiration component in column water vapor in our study area. Finally, we estimated precipitation reductions for column water vapor levels without this transpired moisture, given the nonlinear relationship we found. Although loss of tree transpiration from the Amazon causes a 13% drop in column water vapor, we found that it could result in a 55%-70% decrease in precipitation annually. Consequences of this nonlinearity might be twofold: although the effects of deforestation may be underestimated, it also implies that forest restoration may be more effective for precipitation enhancement than previously assumed.

Forests buffer against variations in precipitation.

Atmospheric moisture recycling effectively increases the amount of usable water over land as the water can undergo multiple precipitation-evapotranspiration cycles. Differences in land cover and climate regulate the evapotranspiration flux. Forests can have deep roots that access groundwater facilitating transpiration throughout the dry season independent of precipitation. This stable transpiration buffers the forest against precipitation variability. However, it is not known whether the buffering effect, already modeled for tropical forests, is common to all forests globally. Here we apply a state-of-the-art Lagrangian moisture tracking model (UTrack) to study whether forest land cover in the upwind precipitationshed can lead to a reduction in monthly precipitation variability downwind. We found a significant buffering effect of forests in the precipitation variability of 10 out of 14 biomes globally. On average, if 50% of precipitation originates from forest, then we find a reduction in the coefficient of variation of monthly precipitation of 60%. We also observed that a high fraction of precipitation from non-forest land sources tends to have the opposite effect, that is, no buffering effect. The average variation of monthly precipitation was 69% higher in areas where 50% of precipitation originates from non-forest land sources in the precipitationshed. Our results emphasize the importance of land cover composition in the precipitationshed to buffer precipitation variability downwind, in particular forest cover. Understanding the influence of land cover in a precipitationshed on atmospheric moisture transport is key for evaluating an area's water-climate regulatory ecosystem services and may become increasingly important due to continued changes in land cover and climate change.

Hysteresis of tropical forests in the 21st century.

Tropical forests modify the conditions they depend on through feedbacks at different spatial scales. These feedbacks shape the hysteresis (history-dependence) of tropical forests, thus controlling their resilience to deforestation and response to climate change. Here, we determine the emergent hysteresis from local-scale tipping points and regional-scale forest-rainfall feedbacks across the tropics under the recent climate and a severe climate-change scenario. By integrating remote sensing, a global hydrological model, and detailed atmospheric moisture tracking simulations, we find that forest-rainfall feedback expands the geographic range of possible forest distributions, especially in the Amazon. The Amazon forest could partially recover from complete deforestation, but may lose that resilience later this century. The Congo forest currently lacks resilience, but is predicted to gain it under climate change, whereas forests in Australasia are resilient under both current and future climates. Our results show how tropical forests shape their own distributions and create the climatic conditions that enable them.

How motifs condition critical thresholds for tipping cascades in complex networks: Linking micro- to macro-scales.

In this study, we investigate how specific micro-interaction structures (motifs) affect the occurrence of tipping cascades on networks of stylized tipping elements. We compare the properties of cascades in Erdos-Rényi networks and an exemplary moisture recycling network of the Amazon rainforest. Within these networks, decisive small-scale motifs are the feed forward loop, the secondary feed forward loop, the zero loop, and the neighboring loop. Of all motifs, the feed forward loop motif stands out in tipping cascades since it decreases the critical coupling strength necessary to initiate a cascade more than the other motifs. We find that for this motif, the reduction of critical coupling strength is 11% less than the critical coupling of a pair of tipping elements. For highly connected networks, our analysis reveals that coupled feed forward loops coincide with a strong 90% decrease in the critical coupling strength. For the highly clustered moisture recycling network in the Amazon, we observe regions of a very high motif occurrence for each of the four investigated motifs, suggesting that these regions are more vulnerable. The occurrence of motifs is found to be one order of magnitude higher than in a random Erdos-Rényi network. This emphasizes the importance of local interaction structures for the emergence of global cascades and the stability of the network as a whole.

Dynamics of tipping cascades on complex networks.

Tipping points occur in diverse systems in various disciplines such as ecology, climate science, economy, and engineering. Tipping points are critical thresholds in system parameters or state variables at which a tiny perturbation can lead to a qualitative change of the system. Many systems with tipping points can be modeled as networks of coupled multistable subsystems, e.g., coupled patches of vegetation, connected lakes, interacting climate tipping elements, and multiscale infrastructure systems. In such networks, tipping events in one subsystem are able to induce tipping cascades via domino effects. Here, we investigate the effects of network topology on the occurrence of such cascades. Numerical cascade simulations with a conceptual dynamical model for tipping points are conducted on Erdos-Rényi, Watts-Strogatz, and Barabási-Albert networks. Additionally, we generate more realistic networks using data from moisture-recycling simulations of the Amazon rainforest and compare the results to those obtained for the model networks. We furthermore use a directed configuration model and a stochastic block model which preserve certain topological properties of the Amazon network to understand which of these properties are responsible for its increased vulnerability. We find that clustering and spatial organization increase the vulnerability of networks and can lead to tipping of the whole network. These results could be useful to evaluate which systems are vulnerable or robust due to their network topology and might help us to design or manage systems accordingly.

Resilience of tropical tree cover: The roles of climate, fire, and herbivory.

Fires and herbivores shape tropical vegetation structure, but their effects on the stability of tree cover in different climates remain elusive. Here, we integrate empirical and theoretical approaches to determine the effects of climate on fire- and herbivore-driven forest-savanna shifts. We analyzed time series of remotely sensed tree cover and fire observations with estimates of herbivore pressure across the tropics to quantify the fire-tree cover and herbivore-tree cover feedbacks along climatic gradients. From these empirical results, we developed a spatially explicit, stochastic fire-vegetation model that accounts for herbivore pressure. We find emergent alternative stable states in tree cover with hysteresis across rainfall conditions. Whereas the herbivore-tree cover feedback can maintain low tree cover below 1,100 mm mean annual rainfall, the fire-tree cover feedback can maintain low tree cover at higher rainfall levels. Interestingly, the rainfall range where fire-driven alternative vegetation states can be found depends strongly on rainfall variability. Both higher seasonal and interannual variability in rainfall increase fire frequency, but only seasonality expands the distribution of fire-maintained savannas into wetter climates. The strength of the fire-tree cover feedback depends on the spatial configuration of tree cover: Landscapes with clustered low tree-cover areas are more susceptible to cross a tipping point of fire-driven forest loss than landscapes with scattered deforested patches. Our study shows how feedbacks involving fire, herbivores, and the spatial structure of tree cover explain the resilience of tree cover across climates.

Fire forbids fifty-fifty forest.

Recent studies have interpreted patterns of remotely sensed tree cover as evidence that forest with intermediate tree cover might be unstable in the tropics, as it will tip into either a closed forest or a more open savanna state. Here we show that across all continents the frequency of wildfires rises sharply as tree cover falls below ~40%. Using a simple empirical model, we hypothesize that the steepness of this pattern causes intermediate tree cover (30‒60%) to be unstable for a broad range of assumptions on tree growth and fire-driven mortality. We show that across all continents, observed frequency distributions of tropical tree cover are consistent with this hypothesis. We argue that percolation of fire through an open landscape may explain the remarkably universal rise of fire frequency around a critical tree cover, but we show that simple percolation models cannot predict the actual threshold quantitatively. The fire-driven instability of intermediate states implies that tree cover will not change smoothly with climate or other stressors and shifts between closed forest and a state of low tree cover will likely tend to be relatively sharp and difficult to reverse.

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks.

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation-atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10-13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.

Remotely sensed canopy height reveals three pantropical ecosystem states.

Although canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite-borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest-savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500  and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna-like sparse tree cover that have a forest-like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

What Do You Mean, 'Tipping Point'?

Over the past 10 years the use of the term 'tipping point' in the scientific literature has exploded. It was originally used loosely as a metaphor for the phenomenon that, beyond a certain threshold, runaway change propels a system to a new state. Although several specific mathematical definitions have since been proposed, we argue that these are too narrow and that it is better to retain the original definition.