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Many species, including humans exhibit a wide range of social behaviors that are crucial for the adaptation and survival of most species. Brain organization and function are shaped by genetic and environmental factors, although their precise contributions have been relatively understudied in the context of artificial selection. We used divergent lines of quail selected on their high versus low level of motivation to approach a group of conspecifics (S + and S-, respectively) to investigate the influence of genetic selection and early social environment on sociability. We observed distinct sex- and brain-region-specific expression patterns of three neuronal markers: mesotocin, and vasotocin, the avian homologues of mammalian oxytocin and vasopressin, as well as aromatase, the enzyme that converts androgens into estrogens. These markers displayed pronounced and neuroanatomically specific differences between S + and S- quail. Additionally, in a second experiment, we assessed the influence of early social environment on social skills in juvenile birds. Mixing S + and S- resulted in more S- males approaching the group without affecting the sociability of S + or other behaviors, suggesting that the early social environment may influence the results of genetic selection. In conclusion, the divergent quail lines offer a valuable model for unraveling the neuronal and behavioral mechanisms underlying social behaviors., (© 2024. The Author(s).)

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA., (© 2022. The Author(s).)

Past environmental changes are expected to have profoundly impacted diversity dynamics through time. While some previous studies showed an association between past climate changes or tectonic events and important shifts in lineage diversification, it is only recently that past environmental changes have been explicitly integrated in diversification models to test their influence on diversification rates. Here, we used a global reconstruction of tropical reef habitat dynamics during the Cenozoic and phylogenetic diversification models to test the influence of (i) major geological events, (ii) reef habitat fragmentation and (iii) reef area on the diversification of 9 major clades of tropical reef fish (Acanthuridae, Balistoidea, Carangoidea, Chaetodontidae, Haemulinae, Holocentridae, Labridae, Pomacentridae and Sparidae). The diversification models revealed a weak association between paleo-habitat changes and diversification dynamics. Specifically, the fragmentation of tropical reef habitats over the Cenozoic was found to be a driver of tropical reef fish diversification for 2 clades. However, overall, our approach did not allow the identification of striking associations between diversification dynamics and paleo-habitat fragmentation in contrast with theoretical model's predictions., (© 2021. The Author(s).)

Biodiversity monitoring delivers vital information to those making conservation decisions. Comprehensively measuring terrestrial biodiversity usually requires costly methods that can rarely be deployed at large spatial scales over multiple time periods, limiting conservation efficiency. Here we investigated the capacity of environmental DNA (eDNA) from stream water samples to survey terrestrial mammal diversity at multiple spatial scales within a large catchment. We compared biodiversity information recovered using an eDNA metabarcoding approach with data from a dense camera trap survey, as well as the sampling costs of both methods. Via the sampling of large volumes of water from the two largest streams that drained the study area, eDNA metabarcoding provided information on the presence and detection probabilities of 35 mammal taxa, 25% more than camera traps and for half the cost. While eDNA metabarcoding had limited capacity to detect felid species and provide individual-level demographic information, it is a cost-efficient method for large-scale monitoring of terrestrial mammals that can offer sufficient information to solve many conservation problems.

The chemical diversity of biologically active fungal strains from 42 Colletotrichum, isolated from leaves of the tropical palm species Astrocaryum sciophilum collected in pristine forests of French Guiana, was investigated. The collection was first classified based on protein fingerprints acquired by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) correlated with cytotoxicity. Liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HRMS/MS) data from ethyl acetate extracts were acquired and processed to generate a massive molecular network (MN) using the MetGem software. From five Colletotrichum strains producing cytotoxic specialized metabolites, we predicted the occurrence of peptide and cytochalasin analogues in four of them by MN, including a similar ion clusters in the MN algorithm provided by MetGem software. Chemoinformatics predictions were fully confirmed after isolation of three pentacyclopeptides (cyclo(Phe-Leu-Leu-Leu-Val), cyclo(Phe-Leu-Leu-Leu-Leu) and cyclo(Phe-Leu-Leu-Leu-Ile)) and two cytochalasins (cytochalasin C and cytochalasin D) exhibiting cytotoxicity at the micromolar concentration. Finally, the chemical study of the last active cytotoxic strain BSNB-0583 led to the isolation of four colletamides bearing an identical decadienamide chain.

Spatial gradients of species richness can be shaped by the interplay between historical and ecological factors. They might interact in particularly complex ways in heterogeneous mountainous landscapes with strong climatic and geological contrasts. We mapped the distribution of 171 lizard species to investigate species richness patterns for all species (171), diurnal species (101), and nocturnal species (70) separately. We related species richness with the historical (past climate change, mountain uplifting) and ecological variables (climate, topography and vegetation). We found that assemblages in the Western Zagros Mountains, north eastern and north western parts of Central Iranian Plateau have the highest number of lizard species. Among the investigated variables, annual mean temperature explained the largest variance for all species (10%) and nocturnal species (31%). For diurnal species, temperature change velocity shows strongest explained variance in observed richness pattern (26%). Together, our results reveal that areas with annual temperature of 15-20 °C, which receive 400-600 mm precipitation and experienced moderate level of climate change since the Last Glacial Maximum (LGM) have highest number of species. Documented patterns of our study provide a baseline for understanding the potential effect of ongoing climate change on lizard diversity in Iran.

Although extinctions due to climate change are still uncommon, they might surpass those caused by habitat loss or overexploitation over the next few decades. Among marine megafauna, mammals fulfill key and irreplaceable ecological roles in the ocean, and the collapse of their populations may therefore have irreversible consequences for ecosystem functioning and services. Using a trait-based approach, we assessed the vulnerability of all marine mammals to global warming under high and low greenhouse gas emission scenarios for the middle and the end of the 21 st century. We showed that the North Pacific Ocean, the Greenland Sea and the Barents Sea host the species that are most vulnerable to global warming. Future conservation plans should therefore focus on these regions, where there are long histories of overexploitation and there are high levels of current threats to marine mammals. Among the most vulnerable marine mammals were several threatened species, such as the North Pacific right whale (Eubalaena japonica) and the dugong (Dugong dugon), that displayed unique combinations of functional traits. Beyond species loss, we showed that the potential extinctions of the marine mammals that were most vulnerable to global warming might induce a disproportionate loss of functional diversity, which may have profound impacts on the future functioning of marine ecosystems worldwide.

Grasslands deliver the resources for food production and are among the most biologically diverse ecosystems. These characteristics are often in conflict as increasing yield through fertilization can lead to biodiversity loss. Thus, the challenge in grassland management is to sustain both yield and diversity. Biodiversity-ecosystem functioning experiments typically reveal a positive relationship between manipulated species diversity and productivity. In contrast, observations of the effect of increasing productivity via fertilization suggest a negative association with biodiversity. Using a mathematical model simulating species co-existence along a resource gradient, we show that trade-offs and species pool structure (size and trait distribution) determines the shape of the productivity-diversity relationship. At a constant resource level, over-yielding drives a positive relationship between biodiversity and productivity. In contrast, along a resource gradient, the shape of the productivity-diversity relationship is determined by the distribution of species along trade-off axes and often resulted in a bell-shaped relationship. In accordance to this theoretical result, we then explain the general trend of plant biodiversity loss with fertilisation in the European flora, by showing empirical evidence that trait distribution of plant species pools throughout Europe is biased toward species preferring poorer soils.

Fishing and climate change impact the demography of marine fishes, but it is generally ignored that many species are made up of genetically distinct locally adapted populations that may show idiosyncratic responses to environmental and anthropogenic pressures. Here, we track 80 years of Atlantic cod (Gadus morhua) population dynamics in West Greenland using DNA from archived otoliths in combination with fish population and niche based modeling. We document how the interacting effects of climate change and high fishing pressure lead to dramatic spatiotemporal changes in the proportions and abundance of different genetic populations, and eventually drove the cod fishery to a collapse in the early 1970s. Our results highlight the relevance of fisheries management at the level of genetic populations under future scenarios of climate change.