Projected loss of brown macroalgae and seagrasses with global environmental change.

Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity remain relatively unexplored. In this work, we model global shifts in one of the most important marine functional groups-ecosystem-structuring macrophytes-and predict substantial end-of-century change. By modelling the future distribution of 207 brown macroalgae and seagrass species at high temporal and spatial resolution under different climate-change projections, we estimate that by 2100, local macrophyte diversity will decline by 3-4% on average, with 17 to 22% of localities losing at least 10% of their macrophyte species. The current range of macrophytes will be eroded by 5-6%, and highly suitable macrophyte habitat will be substantially reduced globally (78-96%). Global macrophyte habitat will shift among marine regions, with a high potential for expansion in polar regions.

Marine protected areas promote stability of reef fish communities under climate warming.

Protection from direct human impacts can safeguard marine life, yet ocean warming crosses marine protected area boundaries. Here, we test whether protection offers resilience to marine heatwaves from local to network scales. We examine 71,269 timeseries of population abundances for 2269 reef fish species surveyed in 357 protected versus 747 open sites worldwide. We quantify the stability of reef fish abundance from populations to metacommunities, considering responses of species and functional diversity including thermal affinity of different trophic groups. Overall, protection mitigates adverse effects of marine heatwaves on fish abundance, community stability, asynchronous fluctuations and functional richness. We find that local stability is positively related to distance from centers of high human density only in protected areas. We provide evidence that networks of protected areas have persistent reef fish communities in warming oceans by maintaining large populations and promoting stability at different levels of biological organization.

Time-travelling pathogens and their risk to ecological communities.

Permafrost thawing and the potential 'lab leak' of ancient microorganisms generate risks of biological invasions for today's ecological communities, including threats to human health via exposure to emergent pathogens. Whether and how such 'time-travelling' invaders could establish in modern communities is unclear, and existing data are too scarce to test hypotheses. To quantify the risks of time-travelling invasions, we isolated digital virus-like pathogens from the past records of coevolved artificial life communities and studied their simulated invasion into future states of the community. We then investigated how invasions affected diversity of the free-living bacteria-like organisms (i.e., hosts) in recipient communities compared to controls where no invasion occurred (and control invasions of contemporary pathogens). Invading pathogens could often survive and continue evolving, and in a few cases (3.1%) became exceptionally dominant in the invaded community. Even so, invaders often had negligible effects on the invaded community composition; however, in a few, highly unpredictable cases (1.1%), invaders precipitated either substantial losses (up to -32%) or gains (up to +12%) in the total richness of free-living species compared to controls. Given the sheer abundance of ancient microorganisms regularly released into modern communities, such a low probability of outbreak events still presents substantial risks. Our findings therefore suggest that unpredictable threats so far confined to science fiction and conjecture could in fact be powerful drivers of ecological change.

Estimating co-extinction threats in terrestrial ecosystems.

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change-such as predicting which species will breach their thermal limits under different warming scenarios-with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.

Coextinctions dominate future vertebrate losses from climate and land use change.

Although theory identifies coextinctions as a main driver of biodiversity loss, their role at the planetary scale has yet to be estimated. We subjected a global model of interconnected terrestrial vertebrate food webs to future (2020-2100) climate and land-use changes. We predict a 17.6% (± 0.16% SE) average reduction of local vertebrate diversity globally by 2100, with coextinctions increasing the effect of primary extinctions by 184.2% (± 10.9% SE) on average under an intermediate emissions scenario. Communities will lose up to a half of ecological interactions, thus reducing trophic complexity, network connectance, and community resilience. The model reveals that the extreme toll of global change for vertebrate diversity might be of secondary importance compared to the damages to ecological network structure.

Effects of the COVID-19 lockdowns on the management of coral restoration projects.

Coral restoration initiatives are gaining significant momentum in a global effort to enhance the recovery of degraded coral reefs. However, the implementation and upkeep of coral nurseries are particularly demanding, so that unforeseen breaks in maintenance operations might jeopardize well-established projects. In the last 2 years, the COVID-19 pandemic has resulted in a temporary yet prolonged abandonment of several coral gardening infrastructures worldwide, including remote localities. Here we provide a first assessment of the potential impacts of monitoring and maintenance breakdown in a suite of coral restoration projects (based on floating rope nurseries) in Colombia, Seychelles, and Maldives. Our study comprises nine nurseries from six locations, hosting a total of 3,554 fragments belonging to three coral genera, that were left unsupervised for a period spanning from 29 to 61 weeks. Floating nursery structures experienced various levels of damage, and total fragment survival spanned from 40 to 95% among projects, with Pocillopora showing the highest survival rate in all locations present. Overall, our study shows that, under certain conditions, abandoned coral nurseries can remain functional for several months without suffering critical failure from biofouling and hydrodynamism. Still, even where gardening infrastructures were only marginally affected, the unavoidable interruptions in data collection have slowed down ongoing project progress, diminishing previous investments and reducing future funding opportunities. These results highlight the need to increase the resilience and self-sufficiency of coral restoration projects, so that the next global lockdown will not further shrink the increasing efforts to prevent coral reefs from disappearing.

A patch-dynamic metacommunity perspective on the persistence of mutualistic and antagonistic bipartite networks.

The structure of interactions between species within a community plays a key role in maintaining biodiversity. Previous studies found that the effects of these structures might vary substantially depending on interaction type, for example, a highly connected and nested architecture stabilizes mutualistic communities, while the stability of antagonistic communities is enhanced in modular and weakly connected structures. Here we show that, when network dynamics are modeled using a patch-dynamic metacommunity framework, the qualitative differences between antagonistic and mutualistic systems disappear, with nestedness and modularity interacting to promote metacommunity persistence. However, the interactive effects are significantly weaker in antagonistic metacommunities. Our model also predicts an increase in connectance, nestedness, and modularity over time in both types of interaction, except in antagonistic networks, where nestedness declines. At steady state, we find a strong negative correlation between nestedness and modularity in both mutualistic and antagonistic metacommunities. These predictions are consistent with the structural trends found in a large data set of real-world antagonistic and mutualistic communities.

Unveiling the complexity and ecological function of aquatic macrophyte-animal networks in coastal ecosystems.

Network theory offers innovative tools to explore the complex ecological mechanisms regulating species associations and interactions. Although interest in ecological networks has grown steadily during the last two decades, the application of network approaches has been unequally distributed across different study systems: while some kinds of interactions (e.g. plant-pollinator and host-parasite) have been extensively investigated, others remain relatively unexplored. Among the latter, aquatic macrophyte-animal associations in coastal environments have been largely neglected, despite their major role in littoral ecosystems. The ubiquity of macrophyte systems, their accessibility and multi-faceted ecological, economical and societal importance make macrophyte-animal systems an ideal subject for ecological network science. In fact, macrophyte-animal networks offer an aquatic counterpart to terrestrial plant-animal networks. In this review, we show how the application of network analysis to aquatic macrophyte-animal associations has the potential to broaden our understanding of how coastal ecosystems function. Network analysis can also provide a key to understanding how such ecosystems will respond to on-going and future threats from anthropogenic disturbance and environmental change. For this, we: (i) identify key issues that have limited the application of network theory and modelling to aquatic animal-macrophyte associations; (ii) illustrate through examples based on empirical data how network analysis can offer new insights on the complexity and functioning of coastal ecosystems; and (iii) provide suggestions for how to design future studies and establish this new research line into network ecology.

EU-Trees4F, a dataset on the future distribution of European tree species.

We present "EU-Trees4F", a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. "EU-Trees4F", can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking.

Ecological dependencies make remote reef fish communities most vulnerable to coral loss.

Ecosystems face both local hazards, such as over-exploitation, and global hazards, such as climate change. Since the impact of local hazards attenuates with distance from humans, local extinction risk should decrease with remoteness, making faraway areas safe havens for biodiversity. However, isolation and reduced anthropogenic disturbance may increase ecological specialization in remote communities, and hence their vulnerability to secondary effects of diversity loss propagating through networks of interacting species. We show this to be true for reef fish communities across the globe. An increase in fish-coral dependency with the distance of coral reefs from human settlements, paired with the far-reaching impacts of global hazards, increases the risk of fish species loss, counteracting the benefits of remoteness. Hotspots of fish risk from fish-coral dependency are distinct from those caused by direct human impacts, increasing the number of risk hotspots by ~30% globally. These findings might apply to other ecosystems on Earth and depict a world where no place, no matter how remote, is safe for biodiversity, calling for a reconsideration of global conservation priorities.

Congruent trophic pathways underpin global coral reef food webs.

Ecological interactions uphold ecosystem structure and functioning. However, as species richness increases, the number of possible interactions rises exponentially. More than 6,000 species of coral reef fishes exist across the world's tropical oceans, resulting in an almost innumerable array of possible trophic interactions. Distilling general patterns in these interactions across different bioregions stands to improve our understanding of the processes that govern coral reef functioning. Here, we show that across bioregions, tropical coral reef food webs exhibit a remarkable congruence in their trophic interactions. Specifically, by compiling and investigating the structure of six coral reef food webs across distinct bioregions, we show that when accounting for consumer size and resource availability, these food webs share more trophic interactions than expected by chance. In addition, coral reef food webs are dominated by dietary specialists, which makes trophic pathways vulnerable to biodiversity loss. Prey partitioning among these specialists is geographically consistent, and this pattern intensifies when weak interactions are disregarded. Our results suggest that energy flows through coral reef communities along broadly comparable trophic pathways. Yet, these critical pathways are maintained by species with narrow, specialized diets, which threatens the existence of coral reef functioning in the face of biodiversity loss.

Global tropical reef fish richness could decline by around half if corals are lost.

Reef fishes are a treasured part of marine biodiversity, and also provide needed protein for many millions of people. Although most reef fishes might survive projected increases in ocean temperatures, corals are less tolerant. A few fish species strictly depend on corals for food and shelter, suggesting that coral extinctions could lead to some secondary fish extinctions. However, secondary extinctions could extend far beyond those few coral-dependent species. Furthermore, it is yet unknown how such fish declines might vary around the world. Current coral mass mortalities led us to ask how fish communities would respond to coral loss within and across oceans. We mapped 6964 coral-reef-fish species and 119 coral genera, and then regressed reef-fish species richness against coral generic richness at the 1° scale (after controlling for biogeographic factors that drive species diversification). Consistent with small-scale studies, statistical extrapolations suggested that local fish richness across the globe would be around half its current value in a hypothetical world without coral, leading to more areas with low or intermediate fish species richness and fewer fish diversity hotspots.

Relative demographic susceptibility does not explain the extinction chronology of Sahul's megafauna.

The causes of Sahul's megafauna extinctions remain uncertain, although several interacting factors were likely responsible. To examine the relative support for hypotheses regarding plausible ecological mechanisms underlying these extinctions, we constructed the first stochastic, age-structured models for 13 extinct megafauna species from five functional/taxonomic groups, as well as 8 extant species within these groups for comparison. Perturbing specific demographic rates individually, we tested which species were more demographically susceptible to extinction, and then compared these relative sensitivities to the fossil-derived extinction chronology. Our models show that the macropodiformes were the least demographically susceptible to extinction, followed by carnivores, monotremes, vombatiform herbivores, and large birds. Five of the eight extant species were as or more susceptible than the extinct species. There was no clear relationship between extinction susceptibility and the extinction chronology for any perturbation scenario, while body mass and generation length explained much of the variation in relative risk. Our results reveal that the actual mechanisms leading to the observed extinction chronology were unlikely related to variation in demographic susceptibility per se, but were possibly driven instead by finer-scale variation in climate change and/or human prey choice and relative hunting success.

Delineating reef fish trophic guilds with global gut content data synthesis and phylogeny.

Understanding species' roles in food webs requires an accurate assessment of their trophic niche. However, it is challenging to delineate potential trophic interactions across an ecosystem, and a paucity of empirical information often leads to inconsistent definitions of trophic guilds based on expert opinion, especially when applied to hyperdiverse ecosystems. Using coral reef fishes as a model group, we show that experts disagree on the assignment of broad trophic guilds for more than 20% of species, which hampers comparability across studies. Here, we propose a quantitative, unbiased, and reproducible approach to define trophic guilds and apply recent advances in machine learning to predict probabilities of pairwise trophic interactions with high accuracy. We synthesize data from community-wide gut content analyses of tropical coral reef fishes worldwide, resulting in diet information from 13,961 individuals belonging to 615 reef fish. We then use network analysis to identify 8 trophic guilds and Bayesian phylogenetic modeling to show that trophic guilds can be predicted based on phylogeny and maximum body size. Finally, we use machine learning to test whether pairwise trophic interactions can be predicted with accuracy. Our models achieved a misclassification error of less than 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, as well as high-resolution probabilities of trophic interactions. By applying our framework to the most diverse vertebrate consumer group, we show that it can be applied to other organismal groups to advance reproducibility in trait-based ecology. Our work thus provides a viable approach to account for the complexity of predator-prey interactions in highly diverse ecosystems.

Small world in the real world: Long distance dispersal governs epidemic dynamics in agricultural landscapes.

Outbreaks of a plant disease in a landscape can be meaningfully modelled using networks with nodes representing individual crop-fields, and edges representing potential infection pathways between them. Their spatial structure, which resembles that of a regular lattice, makes such networks fairly robust against epidemics. Yet, it is well-known how the addition of a few shortcuts can turn robust regular lattices into vulnerable 'small world' networks. Although the relevance of this phenomenon has been shown theoretically for networks with nodes corresponding to individual host plants, its real-world implications at a larger scale (i.e. in networks with nodes representing crop fields or other plantations) remain elusive. Focusing on realistic spatial networks connecting olive orchards in Andalusia (Southern Spain), the world's leading olive producer, we show how even very small probabilities of long distance dispersal of infectious vectors result in a small-world effect that dramatically exacerbates a hypothetical outbreak of a disease targeting olive trees (loosely modelled on known epidemiological information on the bacterium Xylella fastidiosa, an important emerging threat for European agriculture). More specifically, we found that the probability of long distance vector dispersal has a disproportionately larger effect on epidemic dynamics compared to pathogen's intrinsic infectivity, increasing total infected area by up to one order of magnitude (in the absence of quarantine). Furthermore, even a very small probability of long distance dispersal increased the effort needed to halt a hypothetical outbreak through quarantine by about 50% in respect to scenarios modelling local/short distance pathogen's dispersal only. This highlights how identifying (and disrupting) long distance dispersal processes may be more efficacious to contain a plant disease epidemic than surveillance and intervention concentrated on local scale transmission processes.

Ecological drift and competitive interactions predict unique patterns in temporal fluctuations of population size.

Recent studies have highlighted the importance of higher-order competitive interactions in stabilizing population dynamics in multi-species communities. But how does the structure of competitive hierarchies affect population dynamics and extinction processes? We tackled this important question by using spatially explicit simulations of ecological drift (10 species in a homogeneous landscape of 64 patches) in which birth rates were influenced by interspecific competition. Specifically, we examined how transitive (linear pecking orders) and intransitive (pecking orders with loops) competitive hierarchies affected extinction rates and population dynamics in simulated communities through time. In comparison to a pure neutral model, an ecological drift model including transitive competition increased extinction rates, caused synchronous density-dependent population fluctuations, and generated a white-noise distribution of population sizes. In contrast, the drift model with intransitive competitive interactions decreased extinctions rates, caused asynchronous (compensatory) density-dependent population fluctuations, and generated a brown noise distribution of population sizes. We also explored the effect on community stability of more complex patterns of competitive interactions in which pairwise competitive relationships were assigned probabilistically. These probabilistic competition models also generated density-dependent trajectories and a brown noise distribution of population sizes. However, extinction rates and the degree of population synchrony were comparable to those observed in purely neutral communities. Collectively, our results confirm that intransitive competition has a strong and stabilizing effect on local populations in species-poor communities. This effect wanes with increasing species richness. Empirical assemblages characterized by brown spectral noise, density-dependent regulation, and asynchronous (compensatory) population fluctuations may indicate a signature of intransitive competitive interactions.

Co-extinctions annihilate planetary life during extreme environmental change.

Climate change and human activity are dooming species at an unprecedented rate via a plethora of direct and indirect, often synergic, mechanisms. Among these, primary extinctions driven by environmental change could be just the tip of an enormous extinction iceberg. As our understanding of the importance of ecological interactions in shaping ecosystem identity advances, it is becoming clearer how the disappearance of consumers following the depletion of their resources - a process known as 'co-extinction' - is more likely the major driver of biodiversity loss. Although the general relevance of co-extinctions is supported by a sound and robust theoretical background, the challenges in obtaining empirical information about ongoing (and past) co-extinction events complicate the assessment of their relative contributions to the rapid decline of species diversity even in well-known systems, let alone at the global scale. By subjecting a large set of virtual Earths to different trajectories of extreme environmental change (global heating and cooling), and by tracking species loss up to the complete annihilation of all life either accounting or not for co-extinction processes, we show how ecological dependencies amplify the direct effects of environmental change on the collapse of planetary diversity by up to ten times.