Environmental DNA for biomonitoringJan Pawlowski1,2,3, Aurélie Bonin4, Frédéric Boyer5, Tristan Cordier1,6, Pierre Taberlet5,71 Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland2 Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland3 ID-Gene Ecodiagnostics, Geneva, Switzerland4 Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy5 Laboratoire d’Ecologie Alpine (LECA), CNRS, Université Grenoble Alpes, Grenoble, France6 NORCE Climate, NORCE Norwegian Research Centre AS, Bjerknes Centre for Climate Research, Jahnebakken 5, 5007 Bergen, Norway7 Tromsø Museum, UiT – The Arctic University of Norway, Tromsø, NorwayCorresponding [email protected] 2012, Molecular Ecology published a special issue on environmental DNA, which provided an overview of the field of eDNA research and presented a selection of papers on eDNA studies (Taberlet, Coissac, Hajibabaei, & Rieseberg, 2012). This special issue also introduced the concept of Biomonitoring 2.0, advocating for the use of DNA-based identification of taxa in biodiversity surveys and ecosystem assessment (Baird & Hajibabaei, 2012). Since then, hundreds of papers have been published covering various aspects of eDNA-based biomonitoring from single-species detection to community studies and environmental impact assessments. Numerous reviews have summarized these studies for both freshwater and marine environments (e.g. Bohmann et al., 2014; Thomsen & Willerslev, 2015).The progress made in the eDNA field during these last ten years has been spectacular (Taberlet, Bonin, Zinger, & Coissac, 2018). Although the basic concepts and workflow of DNA barcoding and metabarcoding have not changed, the technological advances in high-throughput sequencing have greatly facilitated the access to eDNA data. It has become possible to monitor biodiversity with unprecedented precision and depth. Massive environmental genomic datasets have been rapidly generated at relatively low cost. The analysis of these datasets using machine learning and other taxonomy-free approaches opened wide the doors for using new groups of bioindicators to infer ecological status (Cordier et al., 2018; Cordier, Lanzén, Apothéloz-Perret-Gentil, Stoeck, & Pawlowski, 2019; Pawlowski et al., 2018). At the same time, constant efforts to fill gaps in barcoding reference databases considerably increased the effectiveness of taxonomic identification of eDNA data (Weigand et al., 2019).Astonishingly, these rapid advances in eDNA-based technologies are rather timidly implemented in routine biomonitoring (Hering et al., 2018; Shackleton et al., 2021). Although the concept of Biomonitoring 2.0 is widely endorsed, its acceptance in practice is hampered for various reasons. There is no consensus whether eDNA-based biomonitoring should only apply to conventional bioindicators (Renovate) or should also include new bioindicators (Rebuild) or new taxonomy-free approaches (Revolutionize) (see Fig. 1). Moreover, three main steps on the roadmap from eDNA to biomonitoring are not developed equally. The main attention is given to the development and optimization of eDNA data generation and analysis. The standardization of eDNA methods and their translation into legislatory framework remain at a very early stage. One of the main issues impeding the application of eDNA-based tools concerns the lack of congruence between the results of traditional and molecular analyses (Aylagas et al., 2020). It is expected that the new method is “safe to use” only if it provides the same or almost same results as the conventional one. However, obtaining such perfect congruence is often impossible because the character of data is very different (e.g., abundance of individuals vs abundance of eDNA reads). Moreover, the eDNA “ecology” can hardly be translated directly into species ecology. There are also numerous biological and technical biases that can affect the generation and processing of eDNA data, impacting their interpretation.This special issue addresses some of these challenges by presenting the latest advances in eDNA field and discussing their strengths and limitations when applied to routine biomonitoring. The issue comprises 29 papers grouped into four sections and covering different aspects of eDNA applications. It is accompanied by an opinion paper, which clarifies the eDNA terminology in relation to its use in biomonitoring (Pawlowski, Apothéloz-Perret-Gentil, & Altermatt, 2020). The first section comprises a series of studies using new analytical tools (e.g. machine learning), new types of bioindicators and genomic data (e.g. shotgun sequencing) for the assessment of ecological status. It is followed by a section dedicated to fish eDNA, whose application in biomonitoring is the most advanced. The third section comprises papers dealing with various methodological aspects and the comparison between conventional and molecular methods. The final section presents few examples of eDNA applications for biodiversity surveys and population genetics.Novel approaches to monitor ecosystemsThe development of environmental genomics enables monitoring of microbial and meiofaunal communities that were previously inaccessible when using conventional methods. However, our knowledge of the ecology of these communities is very limited and therefore new analytic approaches are necessary to integrate them into routine bioassessment. This section begins with a review of implementation strategies for the application of environmental genomics in ecological diagnostics (Cordier et al., 2021). The authors introduce four broad categories of possible strategies, including (1) DNA-based taxonomic identification of known bioindicators, (2) taxonomy-free discovery of new bioindicators, (3) structural community metrics, and (4) functional community metrics. Each of these strategies is adapted to a particular type of data (metabarcoding, metagenomics, metatranscriptomics) and rely on different computational analyses in order to provide an assessment of the ecological status.Among the different analytical tools, machine learning seems to be the most promising way to predict the ecological status (Cordier et al., 2018, 2019). In this issue, its performance is tested in the case of the benthic diatoms index widely used in the assessment of ecological quality of rivers and streams (Apothéloz-Perret-Gentil et al., 2021). This study shows that supervised machine learning performs better than the taxonomic assignment, but its predictions are similar to those obtained using a taxonomy-free molecular assignment approach. Moreover, the efficiency of a taxonomic assignment method strongly depends on the completeness of the reference database, highlighting the need to fill in the existing gaps, particularly in the case of bioindicator taxa.The ability of de novo prokaryotic bioindicators to predict multiple anthropogenic impacts on estuarine and coastal benthic communities is demonstrated by Lanzén, Mendibil, Borja, & Alonso-Sáez (2021). The authors compare their results to the traditional macrofauna-based indices and discuss various advantages of using microbial bioindicators as they are more sensitive to different abiotic pressures. Similar conclusions were reached in the case of environmental impact assessment of marine aquaculture (Frühe et al., 2021) and the oil and gas industry (Mauffrey et al., 2021). Both studies demonstrate the effectiveness of machine learning andde novo microbial bioindicators and promote their use for benthic monitoring in marine environments.The last two papers in this series explore new directions for the further development of ecogenomic diagnostics. Broman et al. (2021) use environmental RNA (eRNA) shotgun sequencing to analyse the impact of organic enrichment on benthic micro-eukaryotic communities. Compared to eDNA metabarcoding that is used in the majority of studies, eRNA shotgun data has the advantage to overcome the potential biases of PCR amplification and to better capture the organismic response to environmental pressures by targeting predominantly active cells. Ibrahim et al. (2021) use historical eDNA metabarcoding data to analyze the impact of eutrophication on lake phytoplankton in the 20thcentury. This study demonstrates the potential of paleo-metabarcoding to characterize past biodiversity and establish reference conditions for future monitoring.Refining fish eDNA surveysThe second series of papers concerns the use of eDNA to monitor fish diversity. We focus on fish because they are among the most important groups of bioindicators and also because their study from an eDNA perspective is the most advanced (Pont et al., 2021). The barcoding reference database of common fish species in some regions is close to completeness (Knebelsberger, Dunz, Neumann, & Geiger, 2015), fish-specific markers are well defined (M. Miya et al., 2015; Valentini et al., 2016; Zhang, Zhao, & Yao, 2020) and protocols for fish eDNA sampling and processing are well established (Masaki Miya, Gotoh, & Sado, 2020; Valentini et al., 2016). Currently, considerable efforts are directed to solve the most challenging issue, which is related to quantitative fish eDNA data and its application for inferring fish indices in routine biomonitoring.Two papers address this issue by proposing different approaches to estimate fish abundance from eDNA data. Fukaya et al. (2021) use numerical hydrodynamic models to simulate the spatial and temporal distribution of fish eDNA in aquatic environments. By integrating the models to the measures of eDNA concentration, the authors obtained estimates of fish population abundance comparable to those obtained by the quantitative echo sounder method. Yates et al. (2021) improve the correlation between eDNA concentration and fish abundance by integrating allometric scaling coefficients. Such coefficients can help adjust the values of eDNA production taking in consideration density, biomass and metabolic rates characteristic to a given taxon.A better understanding of the “ecology” of fish eDNA, and particularly how its temporal and spatial distribution is shaped by abiotic and biotic factors, is the subject of the following papers. Littlefair et al. (2021) tested how seasonal variations in thermal stratification influence the distribution of fish eDNA in lakes. The authors show that eDNA distribution follows lake stratification and the thermal niche of the species, which in turn may affect its detection in certain seasons. The distribution of fish and amphibian eDNA in a lentic system was investigated experimentally by Brys et al. (2021). This study indicates high eDNA decay rates and limited dispersal, reinforcing the accuracy of eDNA-based monitoring for retrieving the spatiotemporal occupancy patterns. The advantages of using eDNA for survey of fish populations were also demonstrated by other papers in this section. McColl-Gausden et al. (2021) showed that eDNA metabarcoding is generally more sensitive than electrofishing for conducting fish surveys in freshwater streams, while Aglieri et al. (2021) demonstrate strong complementarity of eDNA-based analysis with visual and capture-based methods in the survey of coastal fish communities.Methodology and comparison with conventional methodsGeneral acceptance of molecular methods in biomonitoring requires their benchmarking against conventional morphotaxonomy-based approaches. This is commonly achieved by processing the same samples in parallel using different methods and by assessing how the molecular data fit to the results of traditional approaches, considered as a ground truth. The papers of this section compare the results of eDNA metabarcoding vs bulk DNA metabarcoding vs different morphology-based approaches. They also present and discuss the biases of molecular methods and propose solutions to improve the outcomes of molecular data generation and processing.The section begins with the three comparative studies of marine biomonitoring. Suter et al. (2021) evaluate the performance of water eDNA and bulk DNA metabarcoding in assessing the biodiversity of zooplankton in open ocean, currently monitored by using continuous plankton recorders. The study shows that both methods recover more species than morphological analyses, however, their efficiency depends on the sampling method and selected marker. They conclude that eDNA metabarcoding is very promising, but it still requires some refinement and standardization before it can be routinely used for zooplankton biomonitoring. Similar conclusions are drawn from the comparison of sediment DNA metabarcoding and macrofauna surveys applied to monitor benthic impacts of salmon farms (He et al., 2021). Although the authors found a certain coherence in relative abundance of common macrofauna bioindicators inferred from morphological and eDNA data, they observed that the correlation with organic enrichment was much stronger for meiofauna, which is not usually included in biomonitoring studies. Significant differences were also found between water eDNA samples and bulk DNA extracts from adjacent benthic communities (Antich et al., 2021). The authors concluded that water eDNA is a poor proxy for the analysis of benthic communities, although they do not exclude that the use of taxon-specific markers could improve the congruence between eDNA and bulk DNA metabarcoding data.The importance of marker selection has also been emphasized in the case of freshwater macrobenthos metabarcoding. The performance of different markers, with focus on key insect orders (Ephemeroptera, Plecoptera and Trichoptera) was tested by Ficetola et al. (2021). The authors demonstrate the complexity of the marker selection process and advocate for the use of multiple markers to cover the widest range of taxa. Combining data from different markers was shown to considerably improve the match between macrobenthic indices inferred from bulk DNA and morphotaxonomic surveys (Meyer et al., 2021). A multimarker approach was also recommended for the assessment of macroinvertebrate communities from the bulk preservative (Martins et al., 2021). Despite the importance of using multiple markers, the authors also demonstrate that the presence of heavily sclerotized exoskeleton can act as a limiting factor for the detection of some taxa.The comparison of bulk DNA vs water eDNA metabarcoding has been reported by two papers. Gleason et al. (2021) show that bulk DNA metabarcoding more accurately represents the local stream macroinvertebrate community, with water eDNA data being overwhelmed by non-metazoan sequences. The same difference was observed when comparing bulk DNA to water eDNA and morphological inventories of pond macroinvertebrates (Harper et al., 2021). However, the authors consider both approaches as complementary and suggest that they should be combined for comprehensive assessment of the invertebrate community. The importance of bulk DNA metabarcoding as a tool for the assessment of marine ecosystems is also highlighted by van de Loos and Nijland (2021). The authors review various technical biases affecting bulk DNA metabarcoding workflow and discuss possible improvements that could help overcoming these biases in the future.The analysis of water samples from five sites in the Brazilian Atlantic forest and one adjacent site in Cerrado grasslands allowed Lopes et al. (2021) to demonstrate that eDNA metabarcoding significantly improves traditional monitoring methods, confirming the presence of frog species undetected by traditional methods. For a few years, invertebrate-derived DNA (iDNA) from leech blood-meal have been used to track mammalian species (Schnell et al., 2012). Here, Drinkwater et al. (2021) apply this approach to assess differences in mammalian diversity across a gradient of forest degradation in Borneo. For monitoring elusive mammals, the iDNA method complements the more traditional and widely used camera trapping.The last two papers in this section provide examples of metabarcoding optimizations aiming at improving its effectiveness in biomonitoring surveys. Guerrieri et al. (2021) show how soil preservation methods can affect estimates of taxonomic richness and community composition. The authors propose guidelines for optimizing soil preservation conditions in agreement with the objectives and practical constraints of the research project. On the other hand, Mächler et al. (2021) address the optimization of data analysis, by investigating how stringency filtering can affect eDNA diversity estimates. The authors conclude that the use of Hill numbers can help in comparisons of eDNA datasets that strongly differ in diversity.Other perspectives for eDNA-based biomonitoringThe last three articles in this special issue present ground-breaking approaches to monitoring biodiversity. Martel et al. (2021) clearly show that eDNA surveys paired with occupancy modelling can uncover metapopulation dynamics and their drivers. Such type of information is important for monitoring endangered species distributed in metapopulations and is quite difficult to obtain via traditional inventories. Shum and Palumbi (2021) reanalyzed a published marine metabarcoding dataset concerning cobble communities found within kelp forest ecosystems. They focussed on diversity data at the intraspecific level to infer population structure and demographic trends. This type of approach greatly increases the scope and value of metabarcoding studies, also opening the way towards metaphylogeography (Turon, Antich, Palacín, Praebel, & Wangensteen, 2020). Finally, Sigsgaard et al. (2021) successfully tracked insects from cow dungs from different environments, and showed that eDNA metabarcoding represents an efficient method for assessing insect diversity, with potential for biomonitoring in relation with the relatively easy standardization of such an approach.ConclusionAs shown by the collection of papers published in this issue, potential applications of eDNA in biomonitoring are highly diverse. Their scope ranges from tracking endangered species to surveying biodiversity or assessing environmental impact. Some papers focus on integrating eDNA into existing bioindication systems, whereas others use eDNA to expand the range of bioindicators and include inconspicuous, commonly overlooked microbial and meiofaunal taxa. All these papers attest to major efforts that have been done to improve eDNA methodology at every step of the workflow from sampling to data analysis. They also contribute to better understand the biological and technical factors impacting the eDNA analyses. Yet, despite this huge new knowledge and numerous practical advantages, the implementation of eDNA in routine biomonitoring still has not taken off.It is now high time to move on and to transform the eDNA field into a truly applied science. The biodiversity crisis and global environmental changes call for an urgent modernization of the tools to monitor biodiversity and assess the ecological status of our environment. As shown by the papers published here, the eDNA methodology achieved top levels of technical and scientific excellence in many areas. Certainly, there are some biases and limitations inherent to eDNA specificity, but there is no reason to consider that the technology is less “safe to use” than the conventional morpho-taxonomic approaches. There are also actions to be taken to ensure the quality and to build confidence in eDNA analyses through standardization of technical protocols and intercalibration tests. However, in view of the substantial efforts that have been made by the scientific community and illustrated by the content of this special issue, it is reasonable to expect that the implementation of eDNA-based tools in biomonitoring will not be long in coming

A document by Jan Pawlowski. Click on the document to view its contents.

Structural variants (SVs) are large rearrangements (> 50 bp) within the genome that impact gene function and the content and structure of chromosomes. As a result, SVs are a significant source of functional genomic variation, i.e. variation at genomic regions underpinning phenotype differences, that can have large effects on individual and population fitness. While there are increasing opportunities to investigate functional genomic variation in threatened species via single nucleotide polymorphism (SNP) datasets, SVs remain understudied despite their potential influence on fitness traits of conservation interest. In this future-focused Opinion, we contend that characterizing SVs offers the conservation genomics community an exciting opportunity to complement SNP-based approaches to enhance species recovery. We also leverage the existing literature–predominantly in human health, agriculture and eco-evolutionary biology–to identify approaches for readily characterizing SVs and consider how integrating these into the conservation genomics toolbox may transform the way we manage some of the world’s most threatened species.

Over the past few decades, large-scale phylogenetic analyses of fungus-gardening ants and their symbiotic fungi have depicted strong concordance among major clades of ants and their symbiotic fungi, yet within clades, fungus sharing is somewhat widespread among unrelated ant lineages. These symbioses are thought to be explained by a diffuse coevolution model within major clades. Understanding horizontal exchange within clades has been limited by conventional genetic markers that lack both interspecific and geographic variation. To examine whether reports of horizontal exchange was indeed symbiont sharing or an issue of employing relatively uninformative molecular markers, samples of Trachymyrmex arizonensis and Trachymyrmex pomonae and their fungi were collected from native populations in Arizona and genotyped using conventional marker genes and genome-wide single nucleotide polymorphisms (SNPs). Conventional markers of the fungal symbionts generally exhibited cophylogenetic patterns that were consistent with some symbiont sharing, but most fungal clades had low support. SNP analysis, in contrast, indicated that each ant species exhibited fidelity to its own fungal subclade with only one instance of a colony growing a fungus that was otherwise associated with a different ant species. This evidence supports a pattern of codivergence between Trachymyrmex species and their fungi, and thus a diffuse coevolutionary model may not accurately predict symbiont exchange. These results suggest that fungal sharing across host species in these symbioses may be less extensive than previously thought.

The recent development of ecological studies has been fueled by the introduction of massive information based on chromosome-scale genome sequences, even for species for which genetic linkage is not accessible. This was enabled mainly by the application of Hi-C, a method for genome-wide chromosome conformation capture that was originally developed for investigating the long-range interaction of chromatins. Performing genomic scaffolding using Hi-C data is highly resource-demanding and employs elaborate laboratory steps for sample preparation. It starts with building a primary genome sequence assembly as an input, which is followed by computation for genome scaffolding using Hi-C data, requiring careful validation. This article presents technical considerations for obtaining optimal Hi-C scaffolding results and provides a test case of its application to a reptile species, the Madagascar ground gecko (Paroedura picta). Among the metrics that are frequently used for evaluating scaffolding results, we investigate the validity of the completeness assessment of chromosome-scale genome assemblies using single-copy reference orthologs, and report problems of the widely used program pipeline BUSCO.

Telomeres are protective, nucleoprotein structures at the end of chromosomes that have been associated with lifespan across taxa. However, the extent to which these associations can be attributed to absolute length versus the rate of telomere shortening prior to sampling remains unresolved. In a longitudinal study, we examined the relationship between lifespan, telomere length and the rate of telomere shortening in wild, purple-crowned fairy-wrens (Malurus coronatus coronatus). To this end, we measured telomere length using qPCR in the blood of 59 individuals sampled as nestling and 4-14 months thereafter, and in 150 individuals sampled on average three times across adulthood. We applied within-subject centering analyses to simultaneously test for associations between lifespan and average telomere length and telomere shortening. We reveal that the rate of telomere shortening in the first year of life predicted lifespan, with individuals with faster shortening rates living less long. We also report a trend for an effect of telomere length in the first year of life on lifespan, independent of telomere shortening. In contrast, in adulthood neither telomere shortening, nor telomere length predicted lifespan, despite a considerably larger data set. Our results suggest that telomere length measured very early in life (during development) and longitudinal assessments of telomere shortening during the first year of life constitute more useful biomarkers of total life expectancy than either telomere length measured after development, or telomere shortening later in adulthood.

Zooplankton play a pivotal role in sustaining the majority of marine ecosystems. The distribution patterns and diversity of zooplankton provide key information for understanding the functioning of these ecosystems. Nevertheless, due to the numerous cryptic and sibling species and the lack of diagnostic characteristics for immature developmental stages, the identification of the global-to-local patterns of zooplankton biodiversity and biogeography remains a challenge in different research fields. Here, the spatial and temporal changes in the zooplankton community from the open waters of the southern section of the Gulf of Mexico were assessed using a multilocus sequence analysis and metabarcoding approach based on the genetic information of 18S and cytochrome oxidase c subunit I (COI) genes. Additionally, a multi-scale analysis was implemented to evaluate which environmental predictors may explain the variability in the structure of the zooplankton community. Our finding suggests that the synergistic effects of oxygen, temperature, and longitude (intended as a proxy for still unexplored forces) may explain both spatial and temporal changes in the zooplankton community. Furthermore, the zooplankton distribution likely reflects the coexistence of three heterogeneous ecoregions and a bio-physical partitioning of the studied area. Finally, some taxa were either exclusive or predominant with either 18S or COI data. This may suggest that comprehensive assessments of the zooplankton community may be more accurately met by the use of multi-locus approaches.

Theory predicts that threatened species living in small populations will experience high levels of inbreeding that will increase their negative genetic load but recent work suggests that the impact of load may be minimized by purging resulting from long term population bottlenecks. Empirical studies that examine this idea using genome-wide estimates of inbreeding and genetic load in threatened species are limited. Here we use genome resequencing data to compare levels of inbreeding, levels of genetic load and population history in threatened Eastern massasauga rattlesnakes (Sistrurus catenatus) which exist in small isolated populations and closely-related yet outbred Western massasauga rattlesnakes (S. tergeminus). In terms of inbreeding, S. catenatus genomes had a greater number of ROHs of varying sizes indicating sustained inbreeding through repeated bottlenecks when compared to S. tergeminus. At the species level, outbred S. tergeminus had higher genome-wide levels of genetic load in the form of greater numbers of derived deleterious mutations compared to S. catenatus presumably due to long-term purging of deleterious mutations in S. catenatus. In contrast, mutations that escaped the “drift sieve” and were polymorphic within S. catenatus populations were more abundant and more often found in homozygote genotypes than in S. tergeminus suggesting a reduced efficiency of purifying selection in smaller S. catenatus populations. Our results support an emerging idea that the historical demography of a threatened species has a significant impact on the type of genetic load present which impacts implementation of conservation actions such as genetic rescue.

Incorporating host-pathogen(s)-environment axes into management and conservation planning is critical to preserving species in a warming climate. However, the role pathogens play in host stress resilience remains largely unexplored in wild animal populations. We experimentally characterized how independent and cumulative stressors (fisheries handling, high water temperature) and natural infections affected the health and longevity of released wild adult sockeye salmon (Oncorhynchus nerka) in British Columbia, Canada. Returning adults were collected before and after entering the Fraser River, yielding marine- and river-collected groups, respectively. Fish were exposed to a mild (seine) or severe (gill net) fishery treatment at collection, and then held in circulating freshwater tanks for up to four weeks at historical (14°C) or projected migration temperatures (18°C). Using weekly nonlethal gill biopsies and high-throughput qPCR, we quantified loads of up to 46 pathogens with host stress and immune gene expression. Marine-captured fish had less severe infections than river-captured fish, a short migration distance (100 km, 5-7 d) that produced profound infection differences. At 14°C, river-collected fish survived 1-2 weeks less than marine-collected fish. All fish held at 18°C died within 4 weeks unless they experienced minimal handling. Gene expression correlated with infections in river-collected fish, while marine-collected fish were more stressor-responsive. Cumulative stressors were detrimental regardless of infections or collection location, likely due to extreme physiological disturbance. Because river-derived infections correlated with single stressor responses, river entry likely decreases stressor resilience of adult salmon by altering both physiological status and pathogen burdens, which redirect host responses toward disease resistance.

Adaptive radiation of fishes was long thought to be possible only in lacustrine environments. Recently, several studies have shown that also riverine and stream environments provide the ecological opportunity for adaptive radiation. In this study, we report on a riverine adaptive radiation of six ecomorphs of cyprinid hillstream fishes of the genus Garra in a river located in the Ethiopian Highlands in East Africa. Garra are predominantly highly specialized algae-scrapers with a wide distribution ranging from Southeastern Asia to Western Africa. However, adaptive phenotypic diversification in mouth type, sucking disc morphology, gut length and body shape have been found among these new species in a single Ethiopian river. Moreover, we found two novel phenotypes of Garra (‘thick-lipped’ and ‘predatory’) that were not described before in this species-rich genus (>160 species). Mitochondrial and genome-wide data suggest monophyletic, intra-basin evolution of Garra phenotypic diversity with signatures of gene flow from other local populations. Although sympatric ecomorphs are genetically distinct and can be considered to being young species as suggested by genome-wide SNP data, mtDNA was unable to identify any genetic structure suggesting a recent and rapid speciation event. Furthermore, we found evidence for a hybrid origin of the novel ‘thick-lipped’ phenotype, as being the result of the hybridization of two other sympatrically occurring species. Here we highlight how, driven by ecological opportunity, an ancestral trophically highly specialized lineage is likely to have rapidly adaptively radiated in a riverine environment, and that this radiation was promoted by the evolution of novel feeding strategies.

Evidence that telomere length (TL) and dynamics can be interpreted as proxy for ‘life stress’ experienced by individuals stems largely from correlational studies. We tested for effects of an experimental increase of workload on telomere dynamics by equipping male great tits (Parus major) with a 0.9 gram backpack for a full year. In addition, we analysed associations between natural life-history variation, TL and TL dynamics. Carrying 5% extra weight for a year did not significantly accelerate telomere attrition. This agrees with our earlier finding that this experiment did not affect survival or future reproduction. Apparently, great tit males were able to compensate behaviourally or physiologically for the increase in locomotion costs we imposed. We found no cross-sectional association between reproductive success and TL, but individuals with higher reproductive success (number of recruits) lost fewer telomere base pairs in the subsequent year. We used the TRF method to measure TL, which method yields a TL distribution for each sample, and the association between reproductive success and telomere loss was more pronounced in the higher percentiles of the telomere distribution, in agreement with the higher impact of ageing on longer telomeres within individuals. Individuals with longer telomeres and less telomere shortening were more likely to survive to the next breeding season, but these patterns did not reach statistical significance. Whether successful individuals are characterized by losing fewer or more base pairs from their telomeres varies between species, and we discuss aspects of ecology and social organisation that may explain this variation.

Signatures of past changes in population size have been detected in genome-wide variation in many species. However, the causes of such demographic changes and the extent to which they are shared across co-distributed species remain poorly understood. During Pleistocene glacial maxima, many temperate European species were confined to southern refugia. While vicariance and range expansion processes associated with glacial cycles have been widely studied, little is known about the demographic history of refugial populations, and the extent and causes of demographic variation among co-distributed species. We used whole genome sequence data to reconstruct and compare demographic histories during the Quaternary for Iberian refuge populations in a single ecological guild (seven species of chalcid parasitoid wasps associated with oak cynipid galls). We find support for large changes in effective population size through the Pleistocene that coincide with major climate events. However, there is little evidence that the timing, direction and magnitude of demographic change are shared across species, suggesting that demographic histories are largely idiosyncratic even at the scale of a single glacial refugium.

Pathogen-mediated selection (PMS) is thought to maintain the high level of allelic diversity observed in the major histocompatibility complex (MHC) class II genes. A comprehensive way to demonstrate contemporary selection is to examine associations between MHC variation and individual fitness. As individual fitness is hard to measure, many studies examine associations between MHC diversity and phenotypic traits which include direct or indirect measures of adaptive immunity thought to contribute to fitness. Here, we tested associations between MHC class II variation and five representative phenotypic traits measured in August: weight, strongyle faecal egg count, and plasma IgA, IgE and IgG immunoglobulin titres against the gastrointestinal nematode parasite Teladorsagia circumcincta in a free-living population of Soay sheep. We found no association between MHC class II variation and August weight or strongyle faecal egg count. We did however find associations between MHC class II variation and immunoglobulin levels which varied with age, isotype and sex. Our results suggest associations between MHC and phenotypic traits are more likely to be found for traits more closely associated with pathogen defence than integrative traits such as body weight and highlight a useful role of MHC-antibody associations in examining selection on MHC genes.

Natural host populations differ in their susceptibility to infection by parasites, and these intra-population differences are still an incompletely understood component of host-parasite dynamics. In this study, we used controlled infection experiments with wild-caught guppies (Poecilia reticulata) and their ectoparasite Gyrodactylus turnbulli to investigate the roles of local adaptation and host genetic composition (immunogenetic and neutral) in explaining differences in susceptibility to infection. We found differences between our four study host populations that were consistent between two parasite source populations, with no indication of local adaptation by either host or parasite at two tested spatial scales. Greater host population genetic variability metrics broadly aligned with lower population mean infection intensity, with the best alignments associated with Major Histocompatibility Complex (MHC) ‘supertypes’. Controlling for intra-population differences and potential inbreeding variance, we found a significant negative relationship between individual-level functional MHC variability and infection: fish carrying more MHC supertypes experienced infections of lower severity, with limited evidence for supertype-specific effects. We conclude that population-level differences in host infection susceptibility likely reflect variation in parasite selective pressure and/or host evolutionary potential, underpinned by functional immunogenetic variation.

Early-life telomere length (TL) is associated with fitness in a range of organisms. Little is known about the genetic basis of variation in TL in wild animal populations, but to understand the evolutionary and ecological significance of TL it is important to quantify the relative importance of genetic and environmental variation in TL. In this study, we measured TL in 2746 house sparrow nestlings sampled across 20 years and used an animal model to show that there is a small heritable component of early-life TL (h2=0.04), but with a strong component of maternal inheritance. Variation in TL among individuals was mainly driven by environmental (year) variance, but also brood and parental effects. We did not find evidence for a negative genetic correlation underlying the observed negative phenotypic correlation between TL and structural body size. Thus, TL may evolve independently of body size and the negative phenotypic correlation is likely to be caused by non-genetic environmental effects. We further used genome‐wide association analysis to identify genomic regions associated with TL variation. We identified several putative genes underlying TL variation; these have been inferred to be involved in oxidative stress, cellular growth, skeletal development, cell differentiation and tumorigenesis in other species. Together, our results show that TL is a lowly heritable, polygenic trait which is strongly affected by environmental conditions in a free-living bird.

The keystone species, Pisaster ochraceus, suffered mass mortalities along the northeast Pacific Ocean from Sea Star Wasting Syndrome (SSWS) outbreaks in 2013-2016. SSWS causation is still debated, leading to concerns as to whether outbreaks will continue to impact this species. Considering the apparent link between ocean temperature and SSWS, the future of this species and intertidal communities remains uncertain. Surveys of co-occurring P. ochraceus along the central Oregon coast in 2016 allowed us to address whether variation in disease status showed genetic variation that may be associated with differences in susceptibility to SSWS. We performed restriction site-associated DNA sequencing (2bRAD-seq) to genotype ~72,000 of single nucleotide polymorphism (SNP) loci across apparently normal and wasting sea stars. Locus-specific analyses of differentiation (Fst) between disease-status groups revealed no signal of genetic differences separating the two groups. Using a multivariate approach, we observed weak separation between the groups, but identified 18 SNP loci showing highest discriminatory power between the groups and scanned the genome annotation for linked genes. A total of 34 protein-coding genes were found to be located within 15 kb (measured by linkage disequilibrium decay) of at least one of the 18 SNPs, and 30 of these genes had homologies to annotated protein databases. Our results suggest that likelihood of developing SSWS symptoms does not have a strong genetic basis. The few genomic regions highlighted had only modest levels of differentiation, but the genes associated with these regions may form the basis for functional studies aiming to understand disease progression.

Telomere DNA length is a complex trait controlled both by multiple loci and environmental factors. Even though the use of telomere DNA length measurement, as a method of assessing stress accumulation and predicting how this will influence survival, is currently being studied in numerous human cohort studies, the importance of telomere length for stress response in ecological studies remains at its infancy. Here, we investigated the telomere changes occurring in the symbiotic coral Stylophora pistillata that has experienced a continuous darkness over six months. This stress condition led to the loss of its symbionts, as what is also observed when bleaching occurs in the field at a large-scale due to climate changes and anthropogenic activities, threatening the worldwide reef ecosystem. We found that the continuous darkness condition was associated with telomere DNA length shortening and a downregulation of the expression of the telomere-associated protein Pot2. These results pave the way for future studies on the role of telomere in coral stress response and the importance of telomere dysregulation in endangered coral species.

Plants are often attacked by multiple antagonists, and traits of the attacking organisms, and their order of arrival onto hosts, may affect plant defenses. However, few studies have assessed how multiple antagonists, and varying attack order, affect plant defense or nutrition. To address this, we assessed defensive and nutritional responses of Pisum sativum plants after attack by a vector herbivore (Acrythosiphon pisum), a non-vector herbivore (Sitona lineatus), and a pathogen (Pea enation mosaic virus, PEMV). We show PEMV-infectious A. pisum induced several pathogen-specific plant defense signals, but these defenses were inhibited when S. lineatus was present in peas infected with PEMV. In contrast, feeding by S. lineatus induced anti-herbivore defense signals, but these defenses were enhanced by PEMV. Sitona lineatus also increased abundance of plant amino acids, but only when they attacked after PEMV-infectious A. pisum. Our results suggest that diverse communities of biotic antagonists alter defense and nutritional traits of plants through complex pathways that depend on the identity of attackers and their order of arrival onto hosts. Moreover, we show interactions among a group of biotic stressors can vary along a spectrum from antagonism to enhancement/synergism based on the identity and order of attackers, and these interactions are mediated by a multitude of phytohormone pathways.