Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales

Quantifying mitochondrial heteroplasmy diversity: A computational approach

Biodiversity plays a pivotal role in sustaining ecosystem processes, encompassing diverse biological species, genetic types and the intricacies of ecosystem composition. However, the precise definition of biodiversity at the individual level remains a challenging endeavour. Hill numbers, derived from Rényi's entropy, have emerged as a popular measure of diversity, with a recent unified framework extending their application across various levels, from genetics to ecosystems. In this study, we employ a computational approach to exploring the diversity of mitochondrial heteroplasmy using real-world data. By adopting Hill numbers with q = 2, we demonstrate the feasibility of quantifying mitochondrial heteroplasmy diversity within and between individuals and populations. Furthermore, we investigate the alpha diversity of mitochondrial heteroplasmy among different species, revealing heterogeneity at multiple levels, including mitogenome components and protein-coding genes (PCGs). Our analysis explores large-scale mitochondrial heteroplasmy data in humans, examining the relationship between alpha diversity at the mitogenome components and PCGs level. Notably, we do not find a significant correlation between these two levels. Additionally, we observe significant correlations in alpha diversity between mothers and children in blood samples, exceeding the reported R2 value for allele frequency correlations. Moreover, our investigation of beta diversity and local overlay similarity demonstrates that heteroplasmy variant distributions in different tissues of children more closely resemble those of their mothers. Through systematic quantification and analysis of mitochondrial heteroplasmy diversity, this study enhances our understanding of heterogeneity at multiple levels, from individuals to populations, providing new insights into this fundamental dimension of biodiversity.

Barley Yellow Dwarf Virus Influences Its Vector's Endosymbionts but Not Its Thermotolerance

The barley yellow dwarf virus (BYDV) of cereals is thought to substantially increase the high-temperature tolerance of its aphid vector, Rhopalosiphum padi, which may enhance its transmission efficiency. This is based on experiments with North American strains of BYDV and R. padi. Here, we independently test these by measuring the temperature tolerance, via Critical Thermal Maximum (CTmax) and knockdown time, of Australian R. padi infected with a local BYDV isolate. We further consider the interaction between BYDV transmission, the primary endosymbiont of R. padi (Buchnera aphidicola), and a transinfected secondary endosymbiont (Rickettsiella viridis) which reduces the thermotolerance of other aphid species. We failed to find an increase in tolerance to high temperatures in BYDV-infected aphids or an impact of Rickettsiella on thermotolerance. However, BYDV interacted with R. padi endosymbionts in unexpected ways, suppressing the density of Buchnera and Rickettsiella. BYDV density was also fourfold higher in Rickettsiella-infected aphids. Our findings indicate that BYDV does not necessarily increase the temperature tolerance of the aphid transmission vector to increase its transmission potential, at least for the genotype combinations tested here. The interactions between BYDV and Rickettsiella suggest new ways in which aphid endosymbionts may influence how BYDV spreads, which needs further testing in a field context.

Forecasting effects of climate changes on the population genetic structure of Anacardium occidentale in the Cerrado biome, Brazil

There has been a continuous interest in understanding the patterns of genetic diversity in natural populations because of the role of intraspecific genetic diversity as the basis of all evolutionary change and thus, its potential effects on population persistence when facing environmental changes. Here, we provided the first description of genetic diversity distribution and population structure of Anacardium occidentale L. (cashew) from the Brazilian Cerrado, one of the most economically important tropical crops in the world. We applied Bayesian clustering approaches (STRUCTURE and POPS) that allow predicting the effects of future climatic changes on the population genetic structure of A. occidentale. We identified distinct genetic groups corresponding to the southwestern, central, and northern regions of the species' range. The characterized genetic clusters will disappear under future climate change scenarios, leading to a homogenization of genetic variability across the landscape. Our findings suggest a high likelihood for the loss of genetic diversity, which in turn will reduce the evolutionary potential of the species to cope with predicted future climatic changes. Results from this study may help develop management strategies to conserve the genetic diversity and structure of natural cashew populations.

Conservation macrogenetics: harnessing genetic data to meet conservation commitments

Genetic biodiversity is rapidly gaining attention in global conservation policy. However, for almost all species, conservation relevant, population-level genetic data are lacking, limiting the extent to which genetic diversity can be used for conservation policy and decision-making. Macrogenetics is an emerging discipline that explores the patterns and processes underlying population genetic composition at broad taxonomic and spatial scales by aggregating and reanalyzing thousands of published genetic datasets. Here we argue that focusing macrogenetic tools on conservation needs, or conservation macrogenetics, will enhance decision-making for conservation practice and fill key data gaps for global policy. Conservation macrogenetics provides an empirical basis for better understanding the complexity and resilience of biological systems and, thus, how anthropogenic drivers and policy decisions affect biodiversity.

Alterations of gut microbiota biodiversity and relative abundance in women with PCOS: A systematic review and meta-analysis

BACKGROUND

Numerous studies have implicated that the gut microbiota is associated with polycystic ovary syndrome (PCOS). However, a comprehensive data-based summary shown that the effects of the PCOS on the gut microbiota is minimal. We aim to assess the alterations of gut microbiota in women with PCOS.

METHODS

An electronic search of PubMed, Web of Science, Embase, Cochrane Library and Ovid was conducted for eligible studies published from inception to 28 March 2023, without any language or regional restrictions. We used Newcastle-Ottawa Quality Assessment Scale (NOS) to complete the assessment of the risk of bias and Stata 15.1 software to performed meta-analysis.

RESULTS

There were 19 human observational studies in total with 617 women with PCOS and 439 healthy individuals were identified. Compared to the control group, the Chao index (WMD -28.88, 95% CI -45.78 to -11.98, I2 = 100%), Shannon index (WMD -0.11, 95% CI -0.18 to 0.00, I2 = 92.2%); and observed operational taxonomic units (OTUs) counts (WMD - 23.48, 95% CI -34.44 to -12. 53, I2 = 99.6%) were significantly lower in women with PCOS. The relative abundance of Bacteroidaceae was significantly higher (WMD 0.12, 95% CI 0.02 to 0.22, I2 = 9.2%), however there were no statistical differences in Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, Alcaligenaceae, Bifidobacteriaceae, Clostridiaceae, Enterobacteriaceae, Lachnospiraceae, Prevotellaceae, Ruminococcaceae, Veillonellaceae, Bacteroides, Bifidobacterium, Blautia, Dialister, Escherichia-Shigella, Faecalibacterium, Lachnoclostridium, Lachnospira, Megamonas, Phascolarctobacterium, Prevotella, Roseburia, and Subdoligranulum.

CONCLUSION

We demonstrated the alpha diversity of gut microbiota and the relative abundance of Bacteroidaceae in women with PCOS are altered. The results indicates that dysbiosis may be a potential pathogenetic factor in PCOS and provided reliable information to investigate the role of gut microbiota in the development and progression of PCOS.

Global determinants of insect mitochondrial genetic diversity

Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth's biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.

Phylogenetically-conserved candidate genes unify biodiversity-ecosystem function relationships and eco-evolutionary dynamics across biological scales

The intra- and interspecific facets of biodiversity have traditionally been analysed separately, limiting our understanding of how evolution has shaped biodiversity, how biodiversity (as a whole) alters ecological dynamics and hence eco-evolutionary feedbacks at the community scale. Here, we propose using candidate genes phylogenetically-conserved across species and sustaining functional traits as an inclusive biodiversity unit transcending the intra- and interspecific boundaries. This framework merges knowledge from functional genomics and functional ecology, and we first provide guidelines and a concrete example for identifying phylogenetically-conserved candidate genes (PCCGs) within communities and for measuring biodiversity from PCCGs. We then explain how biodiversity measured at PCCGs can be linked to ecosystem functions, which unifies recent observations that both intra- and interspecific biodiversity are important for ecosystem functions. We then highlight the eco-evolutionary processes shaping PCCG diversity patterns and argue that their respective role can be inferred from concepts derived from population genetics. Finally, we explain how PCCGs may shift the field of eco-evolutionary dynamics from a focal-species approach to a more realistic focal-community approach. This framework provides a novel perspective to investigate the global ecosystem consequences of diversity loss across biological scales, and how these ecological changes further alter biodiversity evolution.

A Comparison of Entropic Diversity and Variance in the Study of Population Structure

AMOVA is a widely used approach that focuses on variance within and among strata to study the hierarchical genetic structure of populations. The recently developed Shannon Informational Diversity Translation Analysis (SIDTA) instead tackles exploration of hierarchical genetic structure using entropic allelic diversity. A mix of artificial and natural population data sets (including allopolyploids) is used to compare the performance of SIDTA (a 'q = 1' diversity measure) vs. AMOVA (a 'q = 2' measure) under different conditions. An additive allelic differentiation index based on entropic allelic diversity measuring the mean difference among populations (Ω_AP) was developed to facilitate the comparison of SIDTA with AMOVA. These analyses show that the genetic population structure seen by AMOVA is notably different in many ways from that provided by SIDTA, and the extent of this difference is greatly affected by the stability of the markers employed. Negative among group values are lacking with SIDTA but occur with AMOVA, especially with allopolyploids. To provide more focus on measuring allelic differentiation among populations, additional measures were also tested including Bray-Curtis Genetic Differentiation (BCGD) and several expected heterozygosity-based indices (e.g., G_ST, G″_ST, Jost's D, and D_EST). Corrections, such as almost unbiased estimators, that were designed to work with heterozygosity-based fixation indices (e.g., F_ST, G_ST) are problematic when applied to differentiation indices (eg., D_EST, G″_ST, G'_STH).

Enhancing the structural diversity between forest patches-A concept and real-world experiment to study biodiversity, multifunctionality and forest resilience across spatial scales

Intensification of land use by humans has led to a homogenization of landscapes and decreasing resilience of ecosystems globally due to a loss of biodiversity, including the majority of forests. Biodiversity-ecosystem functioning (BEF) research has provided compelling evidence for a positive effect of biodiversity on ecosystem functions and services at the local (α-diversity) scale, but we largely lack empirical evidence on how the loss of between-patch β-diversity affects biodiversity and multifunctionality at the landscape scale (γ-diversity). Here, we present a novel concept and experimental framework for elucidating BEF patterns at α-, β-, and γ-scales in real landscapes at a forest management-relevant scale. We examine this framework using 22 temperate broadleaf production forests, dominated by Fagus sylvatica. In 11 of these forests, we manipulated the structure between forest patches by increasing variation in canopy cover and deadwood. We hypothesized that an increase in landscape heterogeneity would enhance the β-diversity of different trophic levels, as well as the β-functionality of various ecosystem functions. We will develop a new statistical framework for BEF studies extending across scales and incorporating biodiversity measures from taxonomic to functional to phylogenetic diversity using Hill numbers. We will further expand the Hill number concept to multifunctionality allowing the decomposition of γ-multifunctionality into α- and β-components. Combining this analytic framework with our experimental data will allow us to test how an increase in between patch heterogeneity affects biodiversity and multifunctionality across spatial scales and trophic levels to help inform and improve forest resilience under climate change. Such an integrative concept for biodiversity and functionality, including spatial scales and multiple aspects of diversity and multifunctionality as well as physical and environmental structure in forests, will go far beyond the current widely applied approach in forestry to increase resilience of future forests through the manipulation of tree species composition.

Peripheral T-cell receptor repertoire dynamics in small cell lung cancer

Background

Identifying a circulating biomarker predictive of immune checkpoint inhibitor (ICI) benefit in patients with small cell lung cancer (SCLC) remains an unmet need. Characteristics of peripheral and intratumoral T-cell receptor (TCR) repertoires have been shown to predict clinical outcomes in non-small cell lung cancer (NSCLC). Recognizing a knowledge gap, we sought to characterize circulating TCR repertoires and their relationship with clinical outcomes in SCLC.

Methods

SCLC patients with limited (n=4) and extensive (n=10) stage disease were prospectively enrolled for blood collection and chart review. Targeted next-generation sequencing of TCR beta and alpha chains of peripheral blood samples was performed. Unique TCR clonotypes were defined by identical CDR3, V gene, and J gene nucleotide sequences of the beta chain and subsequently used to calculate TCR diversity indices.

Results

Patients with stable versus progressive and limited versus extensive stage disease did not demonstrate significant differences in V gene usage. Kaplan-Meier curve and log-rank analysis did not identify a statistical difference in progression-free survival (PFS) (P=0.900) or overall survival (OS) (P=0.200) between high and low on-treatment TCR diversity groups, although the high diversity group exhibited a trend toward increased OS.

Conclusions

We report the second study investigating peripheral TCR repertoire diversity in SCLC. With a limited sample size, no statistically significant associations between peripheral TCR diversity and clinical outcomes were observed, though further study is warranted.

The Dangerous Side of Being a Predator: Toxoplasma gondii and Neospora caninum in Birds of Prey

Toxoplasma gondii and Neospora caninum are apicomplexan protozoa of major concern in livestock and T. gondii is also considered one of the major threats and a public health concern. These protozoa have a wide range of intermediate hosts, including birds. The present work aimed to assess the prevalence of these cyst-forming parasites in migratory and sedentary birds of prey. The skeletal muscle and myocardium of 159 birds of prey from Central Italy, belonging to 19 species and recovered across 6 Wildlife Recovery Centers/Care structures along the Italian migratory route, were collected specifically for molecular (PCR) and for histopathological analysis to detect T. gondii and N. caninum. For the molecular analysis, genomic DNA was extracted. The DNA was tested by sequence typing, targeting GRA6, 529 bp repeated element, B1, PK1, BTUB, SAG2, alt.SAG2, and APICO genes for T. gondii and to end-point PCR targeting NC5 gene for N. caninum. Thirty-seven out of the one hundred and fifty-nine analyzed samples tested positive for T. gondii with a prevalence of 23.27% and nine for N. caninum, with a prevalence of 5.66%. Thirty-two sequences were obtained from the thirty-seven isolates of T. gondii. Among these, 26 presented alleles compatible with type I strain in 1 or more loci, 4 with type II strain and 2 consisted of atypical strains. Toxoplasma gondii genetic variability in birds of prey confirms previous findings of wildlife as reservoirs of atypical strains. Results from the histology showed few protozoal tissue cysts in skeletal muscle (n. 4) and hearts (n. 2).

Unifying approaches to Functional Marine Connectivity for improved marine resource management: the European SEA-UNICORN COST Action

Truly sustainable development in a human-altered, fragmented marine environment subject to unprecedented climate change, demands informed planning strategies in order to be successful. Beyond a simple understanding of the distribution of marine species, data describing how variations in spatio-temporal dynamics impact ecosystem functioning and the evolution of species are required. Marine Functional Connectivity (MFC) characterizes the flows of matter, genes and energy produced by organism movements and migrations across the seascape. As such, MFC determines the ecological and evolutionary interdependency of populations, and ultimately the fate of species and ecosystems. Gathering effective MFC knowledge can therefore improve predictions of the impacts of environmental change and help to refine management and conservation strategies for the seas and oceans. Gathering these data are challenging however, as access to, and survey of marine ecosystems still presents significant challenge. Over 50 European institutions currently investigate aspects of MFC using complementary methods across multiple research fields, to understand the ecology and evolution of marine species. The aim of SEA-UNICORN, a COST Action supported by COST (European Cooperation in Science and Technology), is to bring together this research effort, unite the multiple approaches to MFC, and to integrate these under a common conceptual and analytical framework. The consortium brings together a diverse group of scientists to collate existing MFC data, to identify knowledge gaps, to enhance complementarity among disciplines, and to devise common approaches to MFC. SEA-UNICORN will promote co-working between connectivity practitioners and ecosystem modelers to facilitate the incorporation of MFC data into the predictive models used to identify marine conservation priorities. Ultimately, SEA-UNICORN will forge strong forward-working links between scientists, policy-makers and stakeholders to facilitate the integration of MFC knowledge into decision support tools for marine management and environmental policies.

Bray-Curtis (AFD) differentiation in molecular ecology: Forecasting, an adjustment ( A A), and comparative performance in selection detection

Geographic genetic differentiation measures are used for purposes such as assessing genetic diversity and connectivity, and searching for signals of selection. Confirmation by unrelated measures can minimize false positives. A popular differentiation measure, Bray‐Curtis, has been used increasingly in molecular ecology, renamed AFD (hereafter called BCAFD). Critically, BCAFD is expected to be partially independent of the commonly used Hill “Q‐profile” measures. BCAFD needs scrutiny for potential biases, by examining limits on its value, and comparing simulations against expectations. BCAFD has two dependencies on within‐population (alpha) variation, undesirable for a between‐population (beta) measure. The first dependency is derived from similarity to GST and FST. The second dependency is that BCAFD cannot be larger than the highest allele proportion in either location (alpha variation), which can be overcome by data‐filtering or by a modified statistic ^AA or “Adjusted AFD”. The first dependency does not forestall applications such as assessing connectivity or selection, if we know the measure's null behavior under selective neutrality with specified conditions—which is shown in this article for ^AA, for equilibrium, and nonequilibrium, for the commonly used data type of single‐nucleotide‐polymorphisms (SNPs) in two locations. Thus, ^AA can be used in tandem with mathematically contrasting differentiation measures, with the aim of reducing false inferences. For detecting adaptive loci, the relative performance of ^AA and other measures was evaluated, showing that it is best to use two mathematically different measures simultaneously, and that ^AA is in one of the best such pairwise criteria. For any application, using ^AA, rather than BCAFD, avoids the counterintuitive limitation by maximum allele proportion within localities.

Joint analysis of microsatellites and flanking sequences enlightens complex demographic history of interspecific gene flow and vicariance in rear-edge oak populations

Inference of recent population divergence requires fast evolving markers and necessitates to differentiate shared genetic variation caused by ancestral polymorphism and gene flow. Theoretical research shows that the use of compound marker systems integrating linked polymorphisms with different mutational dynamics, such as a microsatellite and its flanking sequences, can improve estimation of population structure and inference of demographic history, especially in the case of complex population dynamics. However, empirical application in natural populations has so far been limited by lack of suitable methods for data collection. A solution comes from the development of sequence-based microsatellite genotyping which we used to study molecular variation at 36 sequenced nuclear microsatellites in seven Quercus canariensis and four Q. faginea rear-edge populations across Algeria. We aim to decipher their taxonomic relationship, past evolutionary history and recent demographic trajectory. First, we compare the estimation of population genetics parameters and simulation-based inference of demographic history from microsatellite sequence alone, flanking sequence alone or the combination of linked microsatellite and flanking sequence variation. Second, we apply random forest approximate Bayesian computation to identify which of these sequence types is most informative. Whereas analysing microsatellite variation alone indicates recent interspecific gene flow, additional information gained by integrating nucleotide variation in flanking sequences, by reducing homoplasy, suggests ancient interspecific gene flow followed by drift in isolation instead. The weight of each polymorphism in the inference also demonstrates the value of linked variations with contrasted mutation dynamic to improve estimation of both demographic and mutational parameters.

Evolving spatial conservation prioritization with intraspecific genetic data

Spatial conservation prioritization (SCP) is a planning framework used to identify new conservation areas on the basis of the spatial distribution of species, ecosystems, and their services to human societies. The ongoing accumulation of intraspecific genetic data on a variety of species offers a way to gain knowledge of intraspecific genetic diversity and to estimate several population characteristics useful in conservation, such as dispersal and population size. Here, we review how intraspecific genetic data have been integrated into SCP and highlight their potential for identifying conservation area networks that represent intraspecific genetic diversity comprehensively and that ensure the long-term persistence of biodiversity in the face of global change.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (N_e). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Ecology of sand flies (Diptera: Psychodidae, Phlebotominae) in Jajarm County, an area with high risk of cutaneous leishmaniasis, in North Khorasan, Iran

The present study was conducted to investigate the ecological aspects of sand flies in southwestern North Khorasan, in which cutaneous leishmaniasis caused by Leishmania major has been reported with the highest annual incidence in Iran. Sampling was carried out in four localities including: Khorasha (natural), Ghamiteh (natural), Jorbat (semi urban) and Brick kilns (urban), twice a month using 105 sticky paper traps from indoors and outdoors dwellings during May-December 2017. Specimens were removed from sticky papers, washed in acetone, preserved in 80% ethanol, mounted on microscopic slides by Puri’s medium, and identified using valid morphological keys. Simpson (D), richness (S), Menhinick (DMg), Margalef (DMn), Shannon-Weiner (H′), evenness (J’) were calculated for species diversity. The synanthropic index was determined for the first time in the area. Totally 517 specimens were collected, 47% in outdoors and 30.4% in human indoor dwellings and 22.6% in animal. Eight species of sand flies including 5 species of the genus Phlebotomus and 3 species of the genus Sergentomyia were identified. Phlebotomus papatasi and Sergentomyia sintoni were the most common and Eudominant species, active in all months, collected in the maximum number and percentage in September and August, respectively, and showed the highest abundance in outdoors. The synanthropic index ranged from 6.25 to 38.9 in the study area. The Shannon-Wiener index was estimated to be up to 1.4 and 1.37 in Khorasha and November, respectively, which showed the highest diversity due to maximal richness and evenness compared to other areas. High abundance of Ph. papatasi, as the main vector of cutaneous leishmaniasis, can enhance the potential risk of emerging CL in new areas, the data can be equally important when vector control measures are considered.

Information-based summary statistics for spatial genetic structure inference

The measurement of biodiversity at all levels of organisation is an essential first step to understand the ecological and evolutionary processes that drive spatial patterns of biodiversity. Ecologists have explored the use of a large range of different summary statistics and have come to the view that information-based summary statistics, and in particular so-called Hill numbers, are a useful tool to measure biodiversity. Population geneticists, on the other hand, have largely focused on summary statistics based on heterozygosity and allelic richness measures. However, recent studies proposed the adoption of information-based summary statistics in population genetics studies. Here, we performed a comprehensive assessment of the power of this family of summary statistics to inform about genetic diversity spatial patterns and we compared it with that of traditional population genetics approaches, namely measures based on allelic richness and heterozygosity. To give an unbiased evaluation, we used three machine learning methods to test the performance of different sets of summary statistics to discriminate between spatial scenarios. We defined three distinct sets, (a) one based on allelic richness measures which included the Jaccard index, (b) a set based on heterozygosity that included F_ST , and (c) a set based on Hill numbers derived from Shannon entropy, which included the recently proposed Shannon differentiation, ΔD. The results showed that the latter performed as well or, under some specific spatial scenarios, even better than the traditional population genetics measures. Interestingly, we found that a rarely or never used genetic differentiation measure based on allelic richness, Jaccard dissimilarity (J), showed the highest discriminatory power to discriminate among spatial scenarios, followed by Shannon differentiation ΔD. We concluded, therefore, that information-based measures as well as Jaccard dissimilarity, represent excellent additions to the population genetics toolkit.

Unifying approaches to Functional Marine Connectivity for improved marine resource management: the European SEA-UNICORN COST Action

Truly sustainable development in a human-altered, fragmented marine environment subject to unprecedented climate change, demands informed planning strategies in order to be successful. Beyond a simple understanding of the distribution of marine species, data describing how variations in spatio-temporal dynamics impact ecosystem functioning and the evolution of species are required. Marine Functional Connectivity (MFC) characterizes the flows of matter, genes and energy produced by organism movements and migrations across the seascape. As such, MFC determines the ecological and evolutionary interdependency of populations, and ultimately the fate of species and ecosystems. Gathering effective MFC knowledge can therefore improve predictions of the impacts of environmental change and help to refine management and conservation strategies for the seas and oceans. Gathering these data are challenging however, as access to, and survey of marine ecosystems still presents significant challenge. Over 50 European institutions currently investigate aspects of MFC using complementary methods across multiple research fields, to understand the ecology and evolution of marine species. The aim of SEA-UNICORN, a COST Action within the European Union Horizon 2020 framework programme, is to bring together this research effort, unite the multiple approaches to MFC, and to integrate these under a common conceptual and analytical framework. The consortium brings together a diverse group of scientists to collate existing MFC data, to identify knowledge gaps, to enhance complementarity among disciplines, and to devise common approaches to MFC. SEA-UNICORN will promote co-working between connectivity practitioners and ecosystem modelers to facilitate the incorporation of MFC data into the predictive models used to identify marine conservation priorities. Ultimately, SEA-UNICORN will forge strong forward-working links between scientists, policy-makers and stakeholders to facilitate the integration of MFC knowledge into decision support tools for marine management and environmental policies.

Species ecology explains the spatial components of genetic diversity in tropical reef fishes

Generating genomic data for 19 tropical reef fish species of the Western Indian Ocean, we investigate how species ecology influences genetic diversity patterns from local to regional scales. We distinguish between the α, β and γ components of genetic diversity, which we subsequently link to six ecological traits. We find that the α and γ components of genetic diversity are strongly correlated so that species with a high total regional genetic diversity display systematically high local diversity. The α and γ diversity components are negatively associated with species abundance recorded using underwater visual surveys and positively associated with body size. Pelagic larval duration is found to be negatively related to genetic β diversity supporting its role as a dispersal trait in marine fishes. Deviation from the neutral theory of molecular evolution motivates further effort to understand the processes shaping genetic diversity and ultimately the diversification of the exceptional diversity of tropical reef fishes.

Opportunities and challenges of macrogenetic studies

The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.

Coevolution between MHC class I and Antigen Processing Genes in salamanders

Proteins encoded by antigen-processing genes (APGs) provide major histocompatibility complex (MHC) class I (MHC-I) with antigenic peptides. In mammals, polymorphic multigenic MHC-I family is served by monomorphic APGs, whereas in certain nonmammalian species both MHC-I and APGs are polymorphic and coevolve within stable haplotypes. Coevolution was suggested as an ancestral gnathostome feature, presumably enabling only a single highly expressed classical MHC-I gene. In this view coevolution, while optimizing some aspects of adaptive immunity, would also limit its flexibility by preventing the expansion of classical MHC-I into a multigene family. However, some nonmammalian taxa, such as salamanders, have multiple highly expressed MHC-I genes, suggesting either that coevolution is relaxed or that it does not prevent the establishment of multigene MHC-I. To distinguish between these two alternatives, we use salamanders (30 species from 16 genera representing six families) to test, within a comparative framework, a major prediction of the coevolution hypothesis: the positive correlation between MHC-I and APG diversity. We found that MHC-I diversity explained both within-individual and species-wide diversity of two APGs, TAP1 and TAP2, supporting their coevolution with MHC-I, whereas no consistent effect was detected for the other three APGs (PSMB8, PSMB9, and TAPBP). Our results imply that although coevolution occurs in salamanders, it does not preclude the expansion of the MHC-I gene family. Contrary to the previous suggestions, nonmammalian vertebrates thus may be able to accommodate diverse selection pressures with flexibility granted by rapid expansion or contraction of the MHC-I family, while retaining the benefits of coevolution between MHC-I and TAPs.

Phenotypic plasticity can reverse the relative extent of intra- and interspecific variability across a thermal gradient

Intra- and interspecific variability can both ensure ecosystem functions. Generalizing the effects of individual and species assemblages requires understanding how much within and between species trait variation is genetically based or results from phenotypic plasticity. Phenotypic plasticity can indeed lead to rapid and important changes of trait distributions, and in turn community functionality, depending on environmental conditions, which raises a crucial question: could phenotypic plasticity modify the relative importance of intra- and interspecific variability along environmental gradients? We quantified the fundamental niche of five genotypes in monocultures for each of five ciliate species along a wide thermal gradient in standardized conditions to assess the importance of phenotypic plasticity for the level of intraspecific variability compared to differences between species. We showed that phenotypic plasticity strongly influences trait variability and reverses the relative extent of intra- and interspecific variability along the thermal gradient. Our results show that phenotypic plasticity may lead to either increase or decrease of functional trait variability along environmental gradients, making intra- and interspecific variability highly dynamic components of ecological systems.

A river runs through it: The causes, consequences, and management of intraspecific diversity in river networks

Rivers are fascinating ecosystems in which the eco-evolutionary dynamics of organisms are constrained by particular features, and biologists have developed a wealth of knowledge about freshwater biodiversity patterns. Over the last 10 years, our group used a holistic approach to contribute to this knowledge by focusing on the causes and consequences of intraspecific diversity in rivers. We conducted empirical works on temperate permanent rivers from southern France, and we broadened the scope of our findings using experiments, meta-analyses, and simulations. We demonstrated that intraspecific (genetic) diversity follows a spatial pattern (downstream increase in diversity) that is repeatable across taxa (from plants to vertebrates) and river systems. This pattern can result from interactive processes that we teased apart using appropriate simulation approaches. We further experimentally showed that intraspecific diversity matters for the functioning of river ecosystems. It indeed affects not only community dynamics, but also key ecosystem functions such as litter degradation. This means that losing intraspecific diversity in rivers can yield major ecological effects. Our work on the impact of multiple human stressors on intraspecific diversity revealed that-in the studied river systems-stocking of domestic (fish) strains strongly and consistently alters natural spatial patterns of diversity. It also highlighted the need for specific analytical tools to tease apart spurious from actual relationships in the wild. Finally, we developed original conservation strategies at the basin scale based on the systematic conservation planning framework that appeared pertinent for preserving intraspecific diversity in rivers. We identified several important research avenues that should further facilitate our understanding of patterns of local adaptation in rivers, the identification of processes sustaining intraspecific biodiversity-ecosystem function relationships, and the setting of reliable conservation plans.

Shannon diversity index: a call to replace the original Shannon's formula with unbiased estimator in the population genetics studies

BACKGROUND

The Shannon diversity index has been widely used in population genetics studies. Recently, it was proposed as a unifying measure of diversity at different levels-from genes and populations to whole species and ecosystems. The index, however, was proven to be negatively biased at small sample sizes. Modifications to the original Shannon's formula have been proposed to obtain an unbiased estimator.

METHODS

In this study, the performance of four different estimators of Shannon index-the original Shannon's formula and those of Zahl, Chao and Shen and Chao et al.-was tested on simulated microsatellite data. Both the simulation and analysis of the results were performed in the R language environment. A new R function was created for the calculation of all four indices from the genind data format.

RESULTS

Sample size dependence was detected in all the estimators analysed; however, the deviation from parametric values was substantially smaller in the derived measures than in the original Shannon's formula. Error rate was negatively associated with population heterozygosity. Comparisons among loci showed that fast-mutating loci were less affected by the error, except for the original Shannon's estimator which, in the smallest sample, was more strongly affected by loci with a higher number of alleles. The Zahl and Chao et al. estimators performed notably better than the original Shannon's formula.

CONCLUSION

The results of this study show that the original Shannon index should no longer be used as a measure of genetic diversity and should be replaced by Zahl's unbiased estimator.

Defining Individual-Level Genetic Diversity and Similarity Profiles

Classic concepts of genetic (gene) diversity (heterozygosity) such as Nei & Li’s nucleotide diversity were defined within a population context. Although variations are often measured in population context, the basic carriers of variation are individuals. Hence, measuring variations such as SNP of an individual against a reference genome, which has been ignored previously, is certainly in its own right. Indeed, similar practice has been a tradition in community ecology, where the basic unit of diversity measure is individual community sample. We propose to use Renyi’s-entropy-based Hill numbers to define individual-level genetic diversity and similarity and demonstrate the definitions with the SNP (single nucleotide polymorphism) datasets from the 1000-Genomes Project. Hill numbers, derived from Renyi’s entropy (of which Shannon’s entropy is a special case), have found widely applications including measuring the quantum information entanglement and ecological diversity. The demonstrated individual-level SNP diversity not only complements the existing population-level genetic diversity concepts, but also offers building blocks for comparative genetic analysis at higher levels. The concept of individual covers, but is not limited to, individual chromosome, region of chromosome, gene cluster(s), or whole genome. Similarly, the SNP can be replaced by other structural variants or mutation types such as indels.

City life alters the gut microbiome and stable isotope profiling of the eastern water dragon (Intellagama lesueurii)

Urbanisation is one of the most significant threats to biodiversity, due to the rapid and large-scale environmental alterations it imposes on the natural landscape. It is, therefore, imperative that we understand the consequences of and mechanisms by which, species can respond to it. In recent years, research has shown that plasticity of the gut microbiome may be an important mechanism by which animals can adapt to environmental change, yet empirical evidence of this in wild non-model species remains sparse. Using an empirical replicated study system, we show that city life alters the gut microbiome and stable isotope profiling of a wild native non-model species - the eastern water dragon (Intellagama lesueurii) in Queensland, Australia. City dragons exhibit a more diverse gut microbiome than their native habitat counterparts and show gut microbial signatures of a high fat and plant rich diet. Additionally, we also show that city dragons have elevated levels of the Nitrogen-15 isotope in their blood suggesting that a city diet, which incorporates novel anthropogenic food sources, may also be richer in protein. These results highlight the role that gut microbial plasticity plays in an animals' response to human-altered landscapes.

Holantarctic diversity varies widely among genetic loci within the gametophytically allotriploid peat moss Sphagnum × falcatulum

PREMISE OF THE STUDY

The traditional approach used in analyses of population genetic data for historical inference is to average across multiple marker loci, but averaging conflates the different evolutionary signals provided by stable vs. labile markers.

METHODS

We used a battery of microsatellites with a wide range of mutation/substitution rates, grouping them into two sets (stable and hypervariable) to provide a more nuanced reconstruction of the population genetics and evolutionary history of the allotriploid peat moss Sphagnum × falcatulum across three disjunct regions.

KEY RESULTS

Shannon diversity translation analyses show that the relative apportionment of total within-species allelic diversity (∆_WS ) within and among strata ranges widely, both between the two sets and within and among regions. The majority of diversity in the stable set was inherited directly from the ancestors of this genetically complex allopolyploid, but most of the diversity in the hypervariable set has developed post-hybrid-origin.

CONCLUSIONS

It is useful to group markers into sets having similar evolutionary lability, with each set being analyzed separately, particularly for allopolyploids. A methodology for determining how to group markers into such sets is presented, which can be applied to the requirements of other studies. Within-individual allelic diversity (Δ_WI ) should be addressed in genetic studies on allopolyploids. Allotriploid haplotypes based on a set of nine highly stable microsatellites appear to serve as a clonal-detection set for S. × falcatulum. An additive "allele-metric" diversity approach is introduced, which facilitates a direct comparison of within- and among-stratum diversity components at all levels of diversity.

Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales

Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap, we present a unifying framework for the measurement of biodiversity across hierarchical levels of organization. Our weighted, information-based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon's entropy. We investigated the numerical behaviour of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.), we applied the framework to a real data set on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics and eco-evolutionary dynamics.

Next-generation conservation genetics and biodiversity monitoring

This special issue of Evolutionary Applications consists of 10 publications investigating the use of next-generation tools and techniques in population genetic analyses and biodiversity assessment. The special issue stems from a 2016 Next Generation Genetic Monitoring Workshop, hosted by the National Institute for Mathematical and Biological Synthesis (NIMBioS) in Tennessee, USA. The improved accessibility of next-generation sequencing platforms has allowed molecular ecologists to rapidly produce large amounts of data. However, with the increased availability of new genomic markers and mathematical techniques, care is needed in selecting appropriate study designs, interpreting results in light of conservation concerns, and determining appropriate management actions. This special issue identifies key attributes of successful genetic data analyses in biodiversity evaluation and suggests ways to improve analyses and their application in current population and conservation genetics research.

Differentiation measures for conservation genetics

We compare the two main classes of measures of population structure in genetics: (i) fixation measures such as FST,GST, and θ and (ii) allelic differentiation measures such as Jost's D and entropy differentiation. These two groups of measures quantify complementary aspects of population structure, which have no necessary relationship with each other. We focus especially on empirical aspects of population structure relevant to conservation analyses. At the empirical level, the first set of measures quantify nearness to fixation, while the second set of measures quantify relative degree of allelic differentiation. The two sets of measures do not compete with each other. Fixation measures are often misinterpreted as measures of allelic differentiation in conservation applications; we give examples and theoretical explanations showing why this interpretation can mislead. This misinterpretation has led to the mistaken belief that the absolute number of migrants determines allelic differentiation between demes when mutation rate is low; we show that in the finite island model, the absolute number of migrants determines nearness to fixation, not allelic differentiation. We show that a different quantity, the factor that controls Jost's D, is a good predictor of the evolution of the actual genetic divergence between demes at equilibrium in this model. We also show that when conservation decisions require judgments about differences in genetic composition between demes, allelic differentiation measures should be used instead of fixation measures. Allelic differentiation of fast-mutating markers can be used to rank pairs or sets of demes according to their differentiation, but the allelic differentiation at coding loci of interest should be directly measured in order to judge its actual magnitude at these loci.