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Anthropogenic activities are eroding biodiversity and its contributions to nature and people worldwide. Yet, the dual imperative to protect nature and sustain human well-being raises potential trade-offs that remain to be quantified. Using standardized fish surveys across 1,237 tropical reefs worldwide, we converted the presence and abundance data of 1,024 species into 29 fish community contributions that primarily benefit either nature or people. We show that “nature-for-nature” contributions are mostly positively correlated with total fish biomass, while “nature-for-people” contributions are more independent. Trade-offs among contributions are not the rule, with some tropical fish communities simultaneously providing high levels of different contributions. High mean contributions have been found in all tropical oceans, so sustaining healthy tropical reefs while promoting human well-being seems achievable within most countries, rather than mutually exclusive. Our framework offers an opportunity to explore different management strategies and pathways on tropical reefs between the use and the sparing of nature toward more favorable and sustainable ecological and social futures.

Analyses of genetic diversity can shed light on both the origins of biodiversity hotspots, as well as the conservation status of species that are impacted by human activities. With these objectives, we assembled a genomic dataset of 14,935 single nucleotide polymorphisms from 513 grey reef sharks (Carcharhinus amblyrhynchos) sampled across 17 locations in the tropical Indo-Pacific. We analysed geographic variation in genetic diversity, estimated ancient and contemporary effective population size (Ne) across sampling locations (using coalescent and linkage disequilibrium methods) and modelled the history of gene flow between the Coral Triangle and the Coral Sea. Genetic diversity decreased with distance away from the Coral Triangle and north-western Australia, implying that C. amblyrhynchosmay have originated in this region. Increases in Newere detected across almost all sampling locations 40,000–90,000 generations ago (approximately 0.6–1.5 mya, given an estimated generation time of 16.4 years), suggesting a range expansion around this time. More recent, secondary increases in Newere inferred for the Misool and North Great Barrier Reef sampling locations, but joint modelling did not clarify whether these were due to population growth, migration, or both. Despite the greater genetic diversity and ancient Neobserved at sites around Australia and the Coral Triangle, remote reefs around north-western New Caledonia had the highest contemporary Ne, demonstrating the importance of using multiple population size assessment methods. This study provides insight into both the past and present demographics of C. amblyrhynchosand contributes to our understanding of evolution in marine biodiversity hotspots.

Measuring socioeconomic indices at the scale of regions or countries is required in various contexts, in particular to inform public policies. The use of Deep Learning (DL) and Earth Observation (EO) data is becoming increasingly common to estimate specific variables like societal wealth. This paper presents an end-to-end framework ‘DeepWealth’ that calculates such a wealth index using open-source EO data and DL. We use a multidisciplinary approach incorporating satellite imagery, socio-economic data, and DL models. We demonstrate the effectiveness and generalizability of DeepWealth by training it on 24 African countries and deploying it in Madagascar, Brazil and Japan. Our results show that DeepWealth provides accurate and stable wealth index estimates with an R2of 0.69. It empowers computer-literate users skilled in Python and R to estimate and visualize well-being-related data. This open-source framework follows FAIR (Findable, Accessible, Interoperable, Reusable) principles, providing data, source code, metadata, and training checkpoints with its source code made available on Zenodo and GitHub. In this manner, we provide a DL framework that is reproducible and replicable.

The ocean contains unique biodiversity, provides valuable food resources and is a major sink for anthropogenic carbon. Marine protected areas (MPAs) are an effective tool for restoring ocean biodiversity and ecosystem services1,2, but at present only 2.7% of the ocean is highly protected3. This low level of ocean protection is due largely to conflicts with fisheries and other extractive uses. To address this issue, here we developed a conservation planning framework to prioritize highly protected MPAs in places that would result in multiple benefits today and in the future. We find that a substantial increase in ocean protection could have triple benefits, by protecting biodiversity, boosting the yield of fisheries and securing marine carbon stocks that are at risk from human activities. Our results show that most coastal nations contain priority areas that can contribute substantially to achieving these three objectives of biodiversity protection, food provision and carbon storage. A globally coordinated effort could be nearly twice as efficient as uncoordinated, national-level conservation planning. Our flexible prioritization framework could help to inform both national marine spatial plans4and global targets for marine conservation, food security and climate action.

Ongoing declines in the structure and function of the world’s coral reefs require novel approaches to sustain these ecosystems and the millions of people who depend on them. A presently unexplored approach that draws on theory and practice in human health and rural development is to systematically identify and learn from the ‘outliers’—places where ecosystems are substantially better (‘bright spots’) or worse (‘dark spots’) than expected, given the environmental conditions and socioeconomic drivers they are exposed to. Here we compile data from more than 2,500 reefs worldwide and develop a Bayesian hierarchical model to generate expectations of how standing stocks of reef fish biomass are related to 18 socioeconomic drivers and environmental conditions. We identify 15 bright spots and 35 dark spots among our global survey of coral reefs, defined as sites that have biomass levels more than two standard deviations from expectations. Importantly, bright spots are not simply comprised of remote areas with low fishing pressure; they include localities where human populations and use of ecosystem resources is high, potentially providing insights into how communities have successfully confronted strong drivers of change. Conversely, dark spots are not necessarily the sites with the lowest absolute biomass and even include some remote, uninhabited locations often considered near pristine. We surveyed local experts about social, institutional, and environmental conditions at these sites to reveal that bright spots are characterized by strong sociocultural institutions such as customary taboos and marine tenure, high levels of local engagement in management, high dependence on marine resources, and beneficial environmental conditions such as deep-water refuges. Alternatively, dark spots are characterized by intensive capture and storage technology and a recent history of environmental shocks. Our results suggest that investments in strengthening fisheries governance, particularly aspects such as participation and property rights, could facilitate innovative conservation actions that help communities defy expectations of global reef degradation.

Although environmental filtering has been observed to influence the biodiversity patterns of marine bacterial communities, it was restricted to the regional scale and to the species level, leaving the main drivers unknown at large biogeographic scales and higher taxonomic levels. Bacterial communities with different species compositions may nevertheless share phylogenetic lineages, and phylogenetic turnover (PT) among those communities may be surprisingly low along any biogeographic or environmental gradient. Here, we investigated the relative influence of environmental filtering and geographical distance on the PT between marine bacterial communities living more than 8000 km apart in contrasted abiotic conditions. PT was high between communities and was more structured by local environmental factors than by geographical distance, suggesting the predominance of a lineage filtering process. Strong phenotype-environment mismatches observed in the ocean may surpass high connectivity between marine microbial communities.

Our aim was to determine which of four variables (number of host species exploited by the parasite, taxonomic distinctness of these hosts, geographic range of the principal host, and year of description of this host) was the best predictor of description date of fleas. The study used previously published data on 297 flea species parasitic on 197 species of small mammals from 34 different regions of the Holarctic and one region from the Neotropics. We used both simple linear and multiple regressions to evaluate the relationships between the four predictor variables and the year of flea description, on species values as well as on phylogenetically independent contrasts. Whether or not the analyses controlled for flea phylogeny, all predictor variables correlated significantly with year of flea description when tested separately. In multiple regressions, however, the number of exploited host species was the best predictor of the date of flea description, with the geographic range of the principal host species as well as the date of its description having a lesser, though significant, influence. Overall, our results indicate that a flea species is more likely to be discovered and described early if its biological characteristics (exploitation of many host species) and those of its hosts (long-known to science, broad geographic distributions) increase its chances of being included in a collection. Because the variables we investigated only explained about 10–11% of the variation in year of description among flea species, other factors must be important, such as temporal variability in the activity of flea taxonomists.

The composition of 123 samples of needle essential oil of individual trees of Pinus nigra subsp. laricio from Corsica was investigated by GC and ¹³C-NMR. α-Pinene, manoyl oxide, germacrene-D, myrcene, (E)-caryophyllene and limonene were found to be the main constituents. The results were submitted to principal components analysis and K-means partitioning which allowed two groups of essential oils to be identified with respect to their content of α-pinene, manoyl oxide and germacrene-D. Copyright © 2001 John Wiley & Sons, Ltd.

The composition of 123 samples of needle essential oil of individual trees of Pinus nigrasubsp. lariciofrom Corsica was investigated by GC and 13C‐NMR. α‐Pinene, manoyl oxide, germacrene‐D, myrcene, (E)‐caryophyllene and limonene were found to be the main constituents. The results were submitted to principal components analysis and K‐means partitioning which allowed two groups of essential oils to be identified with respect to their content of α‐pinene, manoyl oxide and germacrene‐D. Copyright © 2001 John Wiley & Sons, Ltd.

AbstractThe abundance of a given species is usually expressed in terms of either the number of individuals per unit area or volume (i.e., density), or biomass. These two abundance metrics generate different results at both the statistical analysis level (e.g., comparison of means) and the ecological level (e.g., diversity comparisons). We seek here to unify different abundance metrics using the formula A= N(B/N)k/3where Ais the abundance of a given species, krepresents a fractional dimension, Nis the number of individuals per unit of area and Bis the biomass of the sampled species. When k= 0, Ais density and when k= 3, Ais the biomass. Avalue of k= 1 would give abundance approximately proportional to the sum of the length of individuals and k= 2 would give abundance approximately proportional to the sum of their surface areas. Metrics intermediate between density, length, area and biomass are possible using non-integer values of k.Applying this methodology to ichthyological data characterized by highly variable intraspecies biomass, we examined the effect of the abundance metric on the results of a three-factor analysis of variance (depth, season and site). In some cases, differences which could not be seen with either density or biomass could be seen with intermediate metrics. We suggest that many ecological results could be usefully evaluated in terms of the effect of the fractional dimension of sampling. In some cases, such an approach could identify the optimal metric.

The lagoon of Biguglia (northeastern Corsica) is one of a number Nature Reserve. Anthropogenic activities are increasing over its watershed however. The present study aims to examine the state of health of the lagoon with the example of two pollutants (Cd and Cu). Water samples were collected in spring and summer 1997. The trace metal fluxes between the various compartments were measured. Transfer processes from the watershed to the lagoon were also examined. The temporal evolution of Cd and Cu content is assessed on the one hand by comparing the present data with former reference work (1992). On the other hand, a 5-box model is implemented in order to reduce the complex functioning of the lagoon to a system of differential equations. With the help of a numerical resolution method, the increase of metallic concentration levels is estimated since 1992. On the basis of 1997 data, two hypotheses are compared. The hypothesis that takes into account a growing increase of anthropogenic activities on the watershed gives, by extrapolation, results that are closer to field measurements. However, even with this hypothesis, the cadmium content in the lagoon is underestimated. This may signify that for this metal the evolution of the lagoon pollution is more important than a linear increase.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03496-1.