SEARCH · Search bioRxiv

Results for “Ecology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56Linked to original sources

bioRxiv2024

Host-associated genetic differentiation in the face of ongoing gene flow: ecological speciation in a pathogenic parasite of freshwater fish

Adaptation to varying environments, leading to population divergence, is one of the key processes of natural selection. However, its effectiveness amidst ongoing gene flow remains controversial. Our study explores this phenomenon by focusing on a tapeworm parasite (Ligula intestinalis), which is capable of parasitising a wide spectrum of fish species, overcoming their immunological defence and having a highly pathogenic impact. We analysed the population genetic structure, the degree of gene flow, and the level of genomic divergence between sympatrically occurring parasites from different cyprinid fish hosts. Utilising genome-wide Single Nucleotide Polymorphisms (SNPs) and transcriptome data, we investigated whether individual host species impose selection pressures on the parasite populations. Genetic clustering analyses indicated a divergence between the parasites infecting breams and those in roaches, bleaks and rudds. Historical demography modelling suggested that the most plausible scenario for this divergence is isolation with continuous gene flow. Selection analysis identified 896 SNPs under selection, exhibiting higher nucleotide diversity and genetic divergence compared to neutral loci. Transcriptome profiling corroborated these results, revealing distinct gene expression profiles for the two parasite populations. An in-depth examination of the selected SNPs and differentially expressed genes revealed specific genes and their physiological functions, as candidates for the molecular mechanisms of immune evasion and, thus, for driving ecological speciation in the parasite. This study showcases the interplay between host specificity, population demography and disruptive selection in ecological speciation. By dissecting the genomic factors at play, we gain a better understanding of the mechanisms facilitating population divergence in the presence of gene flow.

evolutionary biology↗

bioRxiv2024

A 20-year time-series of a freshwater lake reveals seasonal dynamics and environmental drivers of viral diversity, ecology, and evolution

Long-term ecological studies are powerful tools to investigate microbiomes and ecosystem change but have mostly ignored viruses. Here, we leveraged a 20-year time-series of a freshwater lake to characterize 1.3 million viral genomes over time, seasonality, and environmental factors. We identified 578 auxiliary metabolic gene (AMG) clusters representing over 150,000 AMGs, the most abundant of which, including psbA for photosynthesis, pmoC for methane oxidation, and katG for hydrogen peroxide decomposition, were consistently represented in viruses across decades and seasons. We observed positive associations and niche differentiation between virus-host pairs during seasonal change including in keystone taxa, Cyanobacteria, methanotrophs, and Nanopelagicales. Environmental constraints, specifically inorganic carbon and ammonium influenced viral abundances over time, and highlighted roles of viruses in both "top-down" and "bottom-up" interactions. Key evolutionary processes shaping gene and genome-wide selection included favored fitness genes, reduced genomic heterogeneity, and dominant sub-populations carrying specific genes. Overall, our study advances understanding of diversity, ecological dynamics, and evolutionary trajectories of viruses in Earths microbiomes and ecosystems.

microbiology↗

bioRxiv2024

traits.build: a data model, workflow and R package for building harmonised ecological trait databases

Trait databases have proliferated over the past decades, facilitating research on the ecology, evolution, and conservation of taxa across the Tree of Life. Typically, teams of independent researchers build these databases, and each must develop their own workflow and output structure. This divests research hours from downstream tasks such as trait-based analysis and interpretation and the resultant datasets are often difficult to integrate due to disparate database structures. Here we introduce the {traits.build} package, which offers a generalised workflow for building trait databases. {traits.build} contains bespoke functions for propagating metadata files, extensive tutorials, and sample configuration files, allowing researchers to efficiently build a new trait database using open source tools. In addition, the {traits.build} output structure is fully documented by a data model, ensuring the meaning of each variable and sematic relationship between variables is transparent and consistent. The data standard links to terms in previously published data standards, drawing strongly on DarwinCore and the Ecological Trait-data Standard, but also includes the ability to fully map location and context properties absent from these vocabularies., It is the first published database-building workflow that adheres to the Extensible Observation Ontology. Simultaneously developing a generalised workflow and publishing a data standard for the workflow provides {traits.build} users a straightforward pathway to build a new trait database that achieves the FAIR principles. The meaning of all variables in a {traits.build} database are already documented, allowing further integration with either other {traits.build} databases or indeed any other database with a documented data model. This follows the vision of the Open Traits Network to build trait databases whose data can be easily integrated for further analysis.

bioinformatics↗

bioRxiv2024

Metagenome-assembled genomes provide insight into the microbial taxonomy and ecology of the Buhera Soda Pans, Zimbabwe

The use of metagenomics has substantially improved our understanding of the taxonomy, phylogeny and ecology of extreme environment microbiomes. Advances in bioinformatics now permit the reconstruction of almost intact microbial genomes, called metagenome-assembled genomes (MAGs), from metagenomic sequence data, allowing for more precise cell-level taxonomic, phylogenetic and functional profiling of uncultured extremophiles. Here, we report on the recovery and characterisation of metagenome-assembled genomes from the Buhera soda pans located in eastern Zimbabwe. This ecosystem has not been studied despite its unique geochemistry and potential as a habitat for unique microorganisms. Metagenomic DNA from the soda pan was sequenced using the DNA Nanoball Sequencing (DNBSEQR) technique. Sequence analysis, done on the Knowledgebase (KBase) platform, involved quality assessment, read assembly, contig binning, and MAG extraction. The MAGs were subjected to taxonomic placement, phylogenetic profiling and functional annotation in order to establish their possible ecological roles in the soda pan ecosystem. A total of 16 bacterial MAGs of medium to high quality were recovered, all distributed among five phyla dominated by Proteobacteria and Firmicutes. Of the ten MAGs that were taxonomically classified up to genus level, five of them belonged to the halophilic/ haloalkaliphilic genera Alkalibacterium, Vibrio, Thioalkalivibrio, Cecembia and Nitrincola. Functional profiling revealed the use of diverse carbohydrate-metabolising pathways among the MAGs, with glycolysis and the pentose phosphate pathways appearing to be key pathways in this ecosystem. Several MAGs harboured both sulphur/ sulphate reduction and respiratory pathways, suggesting a possible mechanism of energy generation through sulphur/ suphate respiration. In conclusion, this study revealed a highly taxonomically and functionally diverse microbial community in the soda pans, dominated by halophilic and haloalkaliphilic bacteria.

microbiology↗

bioRxiv2024

Causality in the natural selection of the population ecological life histories of birds

Contingent life history theory explains evolution backwards by analysing the fitness consequences of tradeoffs and constraints in the evolved species of today, bypassing the essential challenge of predicting evolution forwardly by the cause and effect of natural selection. I do the latter to decompose the population ecological life histories of 11,187 species of birds. This shows how the selection of mass accounts for inter-specific variation, with 76% of the within order variance, and 72% of the between order differences, in the body mass, demography, and population ecological traits being reconciled by the response of population dynamic feedback selection to variation in net energy, mortality, and intra-specific interactive competition.

evolutionary biology↗

bioRxiv2024

Interplay between particle size and microbial ecology in the gut microbiome

Physical particles can serve as critical abiotic factors that structure the ecology of microbial communities. For non-human vertebrate gut microbiomes, fecal particle size (FPS) has been known to be shaped by chewing efficiency and diet. However, little is known about what drives FPS in the human gut. Here, we analyzed FPS by laser diffraction across a total of 76 individuals and found FPS to be strongly individualized. Surprisingly, a behavioral intervention with 41 volunteers designed to increase chewing efficiency did not impact FPS. Dietary patterns could also not be associated with FPS. Instead, we found evidence that mammalian and human gut microbiomes shaped FPS. Fecal samples from germ-free and antibiotic-treated mice exhibited increased FPS relative to colonized mice. In humans, markers of longer transit time were correlated with smaller FPS. Gut microbiota diversity and composition were also associated with FPS. Finally, ex vivo culture experiments using human fecal microbiota from distinct donors showed that differences in microbiota community composition can drive variation in particle size. Together, our results support an ecological model in which the human gut microbiome plays a key role in reducing the size of food particles during digestion, and that the microbiomes of individuals vary in this capacity. These new insights also suggest FPS in humans to be governed by processes beyond those found in other mammals and emphasize the importance of gut microbiota in shaping their own abiotic environment.

microbiology↗

bioRxiv2024

Genome-wide sweeps create fundamental ecological units in the human gut microbiome

The human gut microbiome is shaped by diverse selective forces originating from the host and associated environmental factors, and in turn profoundly influences health and disease. While the association of microbial lineages with various conditions has been shown at different levels of phylogenetic differentiation, it remains poorly understood to what extent unifying adaptive mechanisms sort microbial lineages into ecologically differentiated populations. Here we show that a pervasive mechanism differentiating bacteria in the microbiome are genome-wide selective sweeps, leading to population structure akin to global epidemics across geographically and ethnically diverse human populations. Such sweeps arise when an adaptation allows a clone to outcompete others within its niche followed by re-diversification, and manifest as clusters of closely related genomes on long branches in phylogenetic trees. This structure is revealed by excluding recombination events that mask the clonal descent of the genomes, and we find that genome-wide sweeps originate under a wide regime of recombination rates in at least 66 taxa from 25 bacterial families. Estimated ages of divergence suggest sweep clusters can spread globally within decades, and this process has occurred repeatedly throughout human history. We show, as an example, that the ecological differentiation of sweep clusters forms populations highly associated with age and colorectal cancer. Our analysis elucidates an evolutionary mechanism for the observation of stably inherited strains with differential associations and provides a theoretical foundation for analyzing adaptation among co-occurring microbial populations.

microbiology↗

bioRxiv2024

PhyloFunc: Phylogeny-informed Functional Distance as a New Ecological Metric for Metaproteomic Data Analysis

BackgroundBeta-diversity is a fundamental ecological metric for exploring dissimilarities between microbial communities. On the functional dimension, metaproteomics data can be used to quantify beta-diversity to understand how microbial community functional profiles vary under different environmental conditions. Conventional approaches to metaproteomic functional beta-diversity often treat protein functions as independent features, ignoring the evolutionary relationships among microbial taxa from which different proteins originate. A more informative functional distance metric that incorporates evolutionary relatedness is needed to better understand microbiome functional dissimilarities. ResultsHere, we introduce PhyloFunc, a novel functional beta-diversity metric that incorporates microbiome phylogeny to inform on metaproteomic functional distance. Leveraging the phylogenetic framework of weighted UniFrac distance, PhyloFunc innovatively utilizes branch lengths to weigh between-sample functional distances for each taxon, rather than differences in taxonomic abundance as in weighted UniFrac. Proof-of-concept using a simulated toy dataset and a real dataset from mouse inoculated with a synthetic gut microbiome and fed different diets show that PhyloFunc successfully captured functional compensatory effects between phylogenetically related taxa. We further tested a third dataset of complex human gut microbiomes treated with five different drugs to compare PhyloFuncs performance with other traditional distance methods. PCoA and machine learning-based classification algorithms revealed higher sensitivity of PhyloFunc in microbiome responses to paracetamol. We provide PhyloFunc as an open-source Python package (available at https://pydigger.com/pypi/PhyloFunc), enabling efficient calculation of functional beta-diversity distances between a pair of samples or the generation of a distance matrix for all samples within a dataset. ConclusionsUnlike traditional approaches that consider metaproteomics features as independent and unrelated, PhyloFunc acknowledges the role of phylogenetic context in shaping the functional landscape in metaproteomes. In particular, we report that PhyloFunc accounts for the functional compensatory effect of taxonomically related species. Its effectiveness, ecological relevance, and enhanced sensitivity in distinguishing group variations are demonstrated through the specific applications presented in this study.

bioinformatics↗

bioRxiv2024

Ecological fNIRS in mobile children: Using short separation channels to correct for systemic contamination during naturalistic neuroimaging.

AbstractO_ST_ABSSignificanceC_ST_ABSThe advances and the miniaturization in functional Near Infrared Spectroscopy (fNIRS) instrumentation offers the potential to move the classical laboratory-based cognitive neuroscience investigations into more naturalistic settings. Wearable and mobile fNIRS devices also provide a novel child-friendly means to image functional brain activity in freely moving toddlers and preschoolers. Measuring brain activity in more ecologically valid settings with fNIRS presents additional challenges, such as the increased impact of physiological interferences. One of the most popular methods to minimize such interferences is to regress out short separation channels from the long separation channels (i.e., superficial signal regression or SSR). Whilst this has been extensively investigated in adults, little is known about the impact of systemic changes on the fNIRS signals recorded in children in either classical or novel naturalistic experiments. AimWe aim to investigate if extracerebral physiological changes occur in toddlers and preschoolers, and whether SSR can help minimize these interferences. ApproachWe collected fNIRS data from 3-to-7 years olds during a conventional computerized static task and in a dynamic naturalistic task in an immersive virtual reality (VR) continuous automatic virtual environment (CAVE). ResultsOur results show that superficial signal contamination data is present in both young children as in adults. Importantly, we find that SSR helps in improving the localization of functional brain activity, both in the computerized task and, to a larger extent, in the dynamic VR task. ConclusionsFollowing from these results, we formulate suggestions to advance the field of developmental neuroimaging with fNIRS, particularly in ecological settings.

neuroscience↗

bioRxiv2024

e3SIM: epidemiological-ecological-evolutionary simulation framework for genomic epidemiology

Infectious disease dynamics are driven by the complex interplay of epidemiological, ecological, and evolutionary processes. Accurately modeling these interactions is crucial for understanding pathogen spread and informing public health strategies. However, existing simulators often fail to capture the dynamic interplay between these processes, resulting in oversimplified models that do not fully reflect real-world complexities in which the pathogens genetic evolution dynamically influences disease transmission. We introduce the epidemiological-ecological-evolutionary simulator (e3SIM), an open-source framework that concurrently models the transmission dynamics and molecular evolution of pathogens within a host population while integrating environmental factors. Using an agent-based, discrete-generation, forward-in-time approach, e3SIM incorporates compartmental models, host-population contact networks, and quantitative-trait models for pathogens. This integration allows for realistic simulations of disease spread and pathogen evolution. Key features include a modular and scalable design, flexibility in modeling various epidemiological and population-genetic complexities, incorporation of time-varying environmental factors, and a user-friendly graphical interface. We demonstrate e3SIMs capabilities through simulations of realistic outbreak scenarios with SARS-CoV-2 and Mycobacterium tuberculosis, illustrating its flexibility for studying the genomic epidemiology of diverse pathogen types.

bioinformatics↗

bioRxiv2024

Reconciling ecology and evolutionary game theory or When not to think cooperation

Evolutionary game theory (EGT)--overwhelmingly employed today for the study of cooperation in a variety of systems, from microbes to cancer and from insect to human societies--started with the seminal 1973 paper by John Maynard Smith and George Price [1], in which they probed the logic of limited war in animal conflict. If fighting was essential to get access to mates and territory, then why did fights rarely lead to serious injury? Maynard Smith and Price developed game theory to show that limited war can be selected at the individual level. Owing to the explanatory potential of this first paper, and enabled by the elegant and powerful machinery of the soon-to-be-developed replicator dynamics [2, 3], EGT took off at an accelerated pace and began to shape expectations across systems and scales. But, even as it expanded its reach from animals to microbes [4-8] and from microbes to cancer [9-11], the field did not revisit a fundamental assumption of that first paper, which subsequently got weaved into the very fabric of the framework--that individual differences in reproduction are determined only by payoff from the game (i.e. in isolation, all individuals, regardless of strategy, were assumed to have identical intrinsic growth rates). Here, we argue that this original assumption substantially limits the scope of EGT. But, because it is not explicitly presented as a caveat, predictions of EGT have been empirically tested broadly across real systems, where the intrinsic growth rates are generally not equal. That has, unsurprisingly, led to puzzling findings and contentious debates [7, 12-15]. Flagging the high potential for confusion to arise from applications of EGT to empirical systems that it is not designed to study and suggesting a way forward constitute our main motivation for this work. In the process, we reestablish a dialog with ecology that can be fruitful both ways, e.g., by providing a so-far-elusive explanation for how diverse ecological communities can assemble evolutionarily.

evolutionary biology↗

bioRxiv2024

Simulations of the infant gut microbiota suggest that complex ecological interactions regulate effects of human milk oligosaccharides on microbial mucin consumption

Intestinal mucin acts as a barrier protecting the infant gut wall against diseases such as colitis and rotavirus. In vitro experiments have shown that the gut microbiota of breastfed infants consumes less mucin than the microbiota of non-breastfed infants, but the mechanisms are incompletely understood. The main difference between human milk and most infant formulas is the presence of human milk oligosaccharides (HMOs) in human milk. We hypothesize that HMOs protect mucin by stimulating non-mucin consuming bacteria. To understand the un-derlying mechanisms we developed a computational model that describes the metabolism and ecology of the infant gut microbiota. Model simulations suggest that extracellular digestion of the HMO 2-fucosyllactose by the mucin-consumer Bifidobacterium bifidum may make this species vulnerable to competitors. The digestion products of HMOs become public goods that can be consumed by competing species such as Bacteroides vulgatus instead.Bifidobacterium longum, which does not consume mucin or produce public goods, can then become dominant, despite growing less efficiently on HMOs in monocultures than B. bifidum. In conclusion, our model simulations suggest that, through complex ecological interactions, HMOs may help lower mucin consumption by stimulating the non-mucin consumer B. longum at the expense of the mucin consumer B. bifidum.

systems biology↗

bioRxiv2024

The Acheulean niche: climate and ecology predict handaxe production in Europe

The Acheulean was the most spatially and temporally vast stone tool industry produced by early humans, persisting for >1.6 million years across three continents. Understanding how behavioral and artifactual variation in these populations relates to climate change and ecology is vital to correctly interpreting the archaeological record, especially given the major climatic and cultural fluctuations during the Pleistocene. Bifacially flaked core tools - which technologically define the tradition - are sometimes regionally and periodically absent within the Acheuleans boundaries. Biface presence is broadly associated with, but rarely formally tested against, environmental conditions. Here, we investigate biface presence/absence and climate/ecological variation at a continental scale between 726 and 130ka. Using a comprehensive sample of European sites matched to paleoenvironmental reconstructions, we demonstrate clear associations between Acheulean presence and specific environments. Acheulean habitat suitability was most strongly associated with mean winter temperatures above -5/-10{degrees}C, and precipitation of the driest month above 15 mm. Two major habitats, warm forest/woodland and shrubland, comprised the European Acheulean niche. Acheulean spatial presence was reconstructed through time: during interglacial and glacial periods it covered most of southwestern Europe, but extended along northern coastal routes during interglacials. Central and Eastern Europe always remained unsuitable. The Acheulean was excluded from areas experiencing both low winter temperatures and low summer precipitation, but reached areas including only one of those two climatic extremes, suggesting seasonal migrations to avoid the harshest seasons. These analyses explain current Acheulean site distributions in Europe and suggest strong links between handaxes, specific ecological conditions, and prehistoric demographic patterns.

evolutionary biology↗

bioRxiv2024

Building Predictive Understanding of Microbial Ecology by Bridging Microbial Growth Kinetics and Microbial Population Dynamics

Modeling microbial communities can provide predictive insights into microbial ecology, but current modeling approaches suffer from inherent limitations. In this study, a novel modeling approach was proposed to address those limitations based on the intrinsic connection between the growth kinetics of guilds and the dynamics of individual microbial populations. To implement the modeling approach, 466 samples from four full-scale activated sludge systems were retrieved from the literature. The raw samples were processed using a data transformation method that not only increased the dataset size by three times but also enabled quantification of population dynamics. Most of the 42 family-level core populations showed overall dynamics close to zero within the sampling period, explaining their resilience to environmental perturbation. Bayesian networks built with environmental factors, perturbation, historical abundance, population dynamics, and mechanistically derived microbial kinetic parameters classified the core populations into heterotrophic and autotrophic guilds. Topological data analysis was applied to identify keystone populations and their time-dependent interactions with other populations. The data-driven inferences were validated directly using the Microbial Database for Activated Sludge (MiDAS) and indirectly by predicting population abundance and community structure using artificial neural networks. The Bray-Curtis similarity between predicted and observed communities was significantly higher with microbial kinetic parameters than without parameters (0.70 vs. 0.66), demonstrating the accuracy of the modeling approach. Implemented based on engineered systems, this modeling approach can be generalized to natural systems to gain predictive understandings of microbial ecology.

microbiology↗

bioRxiv2024

Hydrocarbon Metabolism and Petroleum Seepage as Ecological and Evolutionary Drivers for Cycloclasticus

Aqueous-soluble hydrocarbons dissolve into the oceans interior and structure deep-sea microbial populations influenced by natural oil seeps and spills. n-Pentane is a seawater-soluble, volatile compound abundant in petroleum products and reservoirs and will partially partition to the deep-water column following release from the seafloor. In this study, we explore the ecology and niche partitioning of two free-living Cycloclasticus strains recovered from seawater incubations with n-pentane using and distinguish them as an open ocean variant and a seep-proximal variant, each with distinct capabilities for hydrocarbon catabolism. Comparative metagenomic analysis indicates the open ocean adapted variant encodes more general pathways for hydrocarbon consumption, including short-chain alkanes, aromatics, and long-chain alkanes, and also possesses redox versatility in the form of respiratory nitrate reduction and thiosulfate oxidation; in contrast, the seep variant specializes in short-chain alkanes and relies strictly on oxygen as the terminal electron acceptor. Both variants observed in our work were dominant ecotypes of Cycloclasticus observed during the Deepwater Horizon disaster, a conclusion supported by 16S rRNA analysis and read-recruitment of sequences from the submerged oil plume during active flow. A comparative genomic analysis of Cycloclasticus across various ecosystems suggests distinct strategies for hydrocarbon transformations among each clade. Our findings suggest Cycloclasticus is a versatile and opportunistic consumer of hydrocarbons and may have a greater role in the cycling of sulfur and nitrogen, thus contributing broad ecological impact to various ecosystems globally.

microbiology↗

bioRxiv2024

Ecological and evolutionary impacts of urbanization: applying a causal modeling framework

As the fastest-growing form of land use, urbanization drives profound environmental change that reshapes biodiversity. Studies often characterize biodiversity patterns along urban-rural gradients with statistical models that include one or more generic indices of urbanization. Such models may be useful for prediction, but they do not permit explicit tests of causal hypotheses by which urbanization mediates ecological and evolutionary processes. Here, we show how a graphical causal modeling framework with directed acyclic graphs (DAGs) can be used to design clear conceptual models and inform appropriate statistical analysis to better evaluate mechanistic hypotheses about the effects of urbanization on biodiversity. We first introduce the basic structure of DAGs and illustrate their value with simulated datasets. We then apply the framework to a case study on coat color variation in eastern gray squirrels (Sciurus carolinensis) along an urbanization gradient in Syracuse, New York, USA. We show how statistical models ungrounded in causal assumptions are difficult to interpret and can lead to misleading conclusions about mechanisms in urban ecology and evolution. In contrast, DAGs - by making causal assumptions transparent - help researchers identify appropriate control variables for statistical models to estimate the effects of interest. When applied to our case study, statistical models informed by a DAG revealed a surprising finding: although squirrel melanism was more prevalent in urban than rural populations, the prevalence of melanism was constrained by components of environmental change common to cities, namely roads, forest loss, and predator activity, contrary to expectations. Managing biodiversity in an increasingly urbanized world will require a mechanistic understanding of how urbanization impacts biodiversity patterns; graphical causal models such as DAGs can provide a powerful approach to do so.

evolutionary biology↗

bioRxiv2024

One Health in Eastern Africa: No barriers for ESBL producing E. coli transmission or independent antimicrobial resistance gene flow across ecological compartments

The One Health paradigm considers the interdependence of human, animal and environmental health. In high-income countries, limited evidence has been found from recent studies to support the importance of a One Health approach to addressing spread of antimicrobial resistance (AMR). Given AMR is a global threat, and we are all interconnected it would be important to know if closer interaction of humans with animals and the environment in low-income present a contrasting picture. We used whole genome sequencing to investigate the genomic diversity and to infer transmission of extended spectrum beta-lactamase producing Escherichia coli (ESBL-Ec) between different ecological niches (humans, animals and the environment). We found high diversity of ESBL-Ec with 172 genomic clusters and 167 sequence types identified from 2,344 genomes. Common ESBL genes, blaCTX-M-15 (67.6%) and blaCTX-M-27 (14.2%) were carried on a complex network of different plasmids, presenting multiple pathways for dissemination and revealing the high force of selection. Using fine-scale genomic clustering across multiple thresholds ranging from 0 to 20 single nucleotide polymorphisms, we found that genomes isolated from humans, animals and the environment formed overlapping clusters, indicating recent ESBL-Ec transmission and co-circulation both within and between ecological compartments. These findings demonstrate that the One Health approach is highly relevant to tackling AMR in low-income settings, and therefore critical to consider if we are to address the rise of AMR globally.

genomics↗

bioRxiv2024

Ecological and social factors lead to variation in parental care between sexes in a burying beetle

Sexual conflict over parental care represents a divergence in the evolutionary interests between males and females, consequently leading to distinct sex roles in parental care and reproductive strategies. However, whether and how various ecological and social environments influence such sex differences remains largely unclear. In the present study, using the burying beetles Nicrophorus vespilloides, we experimentally investigated the impacts of resource availability and inter- and intra-specific competition pressure on individual parental care and reproduction in males and females. We manipulated the resource availability for the breeding pairs by providing them with either large or small mouse carcasses, and constructed the presence of intra- and inter-specific competition, by introducing an additional, small pair of beetles and blowfly maggots Calliphora, respectively. We expected that males would decrease their parental care, while females would increase theirs, in response to smaller carcass. We also expected that the presence of intra- and inter-specific competition differentially affected the cares of males and females. We found that, compared to males and females breeding on large carcasses, males did not change their care, whereas females increased their care, when breeding on small carcasses. In the presence of another pair of adults, both males and females increased their parental care, whereas in the presence of blowfly maggots they both decreased their parental care. Our results showed that males and females adjust their parental care based on resource availability and competition pressure, with sex-specific differences driven by ecological and social factors. Our study sheds light on the importance of sex-specific parental care in response to various external drivers which contributes to a better understanding of the evolution of sex conflict over parental care.

animal behavior and cognition↗