Landscape genomics to the rescue of a tropical bee threatened by habitat loss and climate change

Biotic and abiotic stresses on honeybee health

Honeybees are the most critical pollinators providing key ecosystem services that underpin crop production and sustainable agriculture. Amidst a backdrop of rapid global change, this eusocial insect encounters a succession of stressors during nesting, foraging, and pollination. Ectoparasitic mites, together with vectored viruses, have been recognized as central biotic threats to honeybee health, while the spread of invasive giant hornets and small hive beetles also increasingly threatens colonies worldwide. Cocktails of agrochemicals, including acaricides used for mite treatment, and other pollutants of the environment have been widely documented to affect bee health in various ways. Additionally, expanding urbanization, climate change, and agricultural intensification often result in the destruction or fragmentation of flower-rich bee habitats. The anthropogenic pressures exerted by beekeeping management practices affect the natural selection and evolution of honeybees, and colony translocations facilitate alien species invasion and disease transmission. In this review, the multiple biotic and abiotic threats and their interactions that potentially undermine bee colony health are discussed, while taking into consideration the sensitivity, large foraging area, dense network among related nestmates, and social behaviors of honeybees.

Landscape quantifies the intermediate state and transition dynamics in ecological networks

Understanding the ecological mechanisms associated with the collapse and restoration is especially critical in promoting harmonious coexistence between humans and nature. So far, it remains challenging to elucidate the mechanisms of stochastic dynamical transitions for ecological systems. Using an example of plant-pollinator network, we quantified the energy landscape of ecological system. The landscape displays multiple attractors characterizing the high, low and intermediate abundance stable states. Interestingly, we detected the intermediate states under pollinator decline, and demonstrated the indispensable role of the intermediate state in state transitions. From the landscape, we define the barrier height (BH) as a global quantity to evaluate the transition feasibility. We propose that the BH can serve as a new early-warning signal (EWS) for upcoming catastrophic breakdown, which provides an earlier and more accurate warning signal than traditional metrics based on time series. Our results promote developing better management strategies to achieve environmental sustainability.

Corridor-based approach with spatial cross-validation reveals scale-dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity

Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across ~100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

Integrative population genetics and metagenomics reveals urbanization increases pathogen loads and decreases connectivity in a wild bee

As urbanization continues to increase, it is expected that two-thirds of the human population will reside in cities by 2050. Urbanization fragments and degrades natural landscapes, threatening wildlife including economically important species such as bees. In this study, we employ whole genome sequencing to characterize the population genetics, metagenome and microbiome, and environmental stressors of a common wild bee, Ceratina calcarata. Population genomic analyses revealed the presence of low genetic diversity and elevated levels of inbreeding. Through analyses of isolation by distance, resistance, and environment across urban landscapes, we found that green spaces including shrubs and scrub were the most optimal pathways for bee dispersal, and conservation efforts should focus on preserving these land traits to maintain high connectivity across sites for wild bees. Metagenomic analyses revealed landscape sites exhibiting urban heat island effects, such as high temperatures and development but low precipitation and green space, had the highest taxa alpha diversity across all domains even when isolating for potential pathogens. Notably, the integration of population and metagenomic data showed that reduced connectivity in urban areas is not only correlated with lower relatedness among individuals but is also associated with increased pathogen diversity, exposing vulnerable urban bees to more pathogens. Overall, our combined population and metagenomic approach found significant environmental variation in bee microbiomes and nutritional resources even in the absence of genetic differentiation, as well as enabled the potential early detection of stressors to bee health.

The impact of geography and climate on the population structure and local adaptation in a wild bee

Deciphering processes that contribute to genetic differentiation and divergent selection of natural populations is useful for evaluating the adaptive potential and resilience of organisms faced with various anthropogenic stressors. Insect pollinator species, including wild bees, provide critical ecosystem services but are highly susceptible to biodiversity declines. Here, we use population genomics to infer the genetic structure and test for evidence of local adaptation in an economically important native pollinator, the small carpenter bee (Ceratina calcarata). Using genome-wide SNP data (n = 8302), collected from specimens across the species' entire distribution, we evaluated population differentiation and genetic diversity and identified putative signatures of selection in the context of geographic and environmental variation. Results of the analyses of principal component and Bayesian clustering were concordant with the presence of two to three genetic clusters, associated with landscape features and inferred phylogeography of the species. All populations examined in our study demonstrated a heterozygote deficit, along with significant levels of inbreeding. We identified 250 robust outlier SNPs, corresponding to 85 annotated genes with known functional relevance to thermoregulation, photoperiod, and responses to various abiotic and biotic stressors. Taken together, these data provide evidence for local adaptation in a wild bee and highlight genetic responses of native pollinators to landscape and climate features.

Harnessing the omics revolution to address the global biodiversity crisis

Human disturbances are altering global biodiversity in unprecedented ways. We identify three fundamental challenges underpinning our understanding of global biodiversity (namely discovery, loss, and preservation), and discuss how the omics revolution (e.g. genomics, transcriptomics, proteomics, metabolomics, and meta-omics) can help address these challenges. We also discuss how omics tools can illuminate the major drivers of biodiversity loss, including invasive species, pollution, urbanization, overexploitation, and climate change, with a special focus on highly diverse tropical environments. Although omics tools are transforming the traditional toolkit of biodiversity research, their application to addressing the current biodiversity crisis remains limited and may not suffice to offset current rates of biodiversity loss. Despite technical and logistical challenges, omics tools need to be fully integrated into global biodiversity research, and better strategies are needed to improve their translation into biodiversity policy and practice. It is also important to recognize that although the omics revolution can be considered the biologist's dream, socioeconomic disparity limits their application in biodiversity research.

Environmental selection, rather than neutral processes, best explain regional patterns of diversity in a tropical rainforest fish

To conserve the high functional and genetic variation in hotspots such as tropical rainforests, it is essential to understand the forces driving and maintaining biodiversity. We asked to what extent environmental gradients and terrain structure affect morphological and genomic variation across the wet tropical distribution of an Australian rainbowfish, Melanotaenia splendida splendida. We used an integrative riverscape genomics and morphometrics framework to assess the influence of these factors on both putative adaptive and non-adaptive spatial divergence. We found that neutral genetic population structure was largely explainable by restricted gene flow among drainages. However, environmental associations revealed that ecological variables had a similar power to explain overall genetic variation, and greater power to explain body shape variation, than the included neutral covariables. Hydrological and thermal variables were the strongest environmental predictors and were correlated with traits previously linked to heritable habitat-associated dimorphism in rainbowfishes. In addition, climate-associated genetic variation was significantly associated with morphology, supporting heritability of shape variation. These results support the inference of evolved functional differences among localities, and the importance of hydroclimate in early stages of diversification. We expect that substantial evolutionary responses will be required in tropical rainforest endemics to mitigate local fitness losses due to changing climates.

Evidence for morphological and genetic structuring of Plebeia flavocincta (Apidae: Meliponini) populations in Northeast Brazil

Tropical dry forests are increasingly threatened by human activities. In Northeast Brazil, the Caatinga, an area of tropical dry forests surrounded by wetlands, is considered globally unique among these habitats. In this region, the stingless bee Plebeia flavocincta is found in a variety of environmental, ecological, and demographic conditions. We aimed to characterize P. flavocincta populations within its natural range through wing geometric morphometrics and mitochondrial DNA (mtDNA) analyses. The characterization of population variability can clarify whether the species is morphologically and genetically diverse and whether populations are morphologically and genetically structured. We analyzed 673 samples by wing morphometry and 75 by cytochrome-b assays. Our results revealed P. flavocincta is genetically and morphologically diverse and populations are morphologically and genetically structured. Despite the differentiation between the two most morphologically distant populations, we verified a large overlap of morphological variation between all populations. The genetic analysis showed that the haplotypes were geographically structured into six clusters, four of which were located in coastal areas, and the remaining two in the drier inland region. The characterization of P. flavocincta populations is an important step toward decision-making in programs for the protection, management, and sustainable use of this stingless bee in local breeding efforts.

Genotype‐environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush (Catharus guttatus), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

Effects of Climate Change on Hydrology in the Most Relevant Mining Basin in the Eastern Legal Amazon

The Itacaiúnas River basin, an important watershed for the mining sector in Brazil, has had 51% of its native forest area deforested in the last forty years. It is in the arc of deforestation of the Amazon. It has protected areas essential to local biodiversity maintenance, in addition to owning ore reserves. Here, we present the first study to assess the mean annual, seasonal, and spatialized hydrological processes, providing results on a detailed scale in the basin, including mining sites. We used five future projections of mean monthly temperature and daily precipitation as input to the MGB hydrological model to simulate how hydrological processes, such as evapotranspiration, water availability, and high flows, may change in the next 30 years. The future decrease in precipitation (−8%) and increase in temperature (10%) may strengthen the monsoon seasonal cycle and lengthen the dry month for evapotranspiration. Furthermore, some parts of the basin expect an increase in the high flows (8.1%) and a decrease in water availability (−93.6%). These results provide subsidies to develop adaptation strategies to ensure the viability of mining operations and safeguard the surrounding environment and communities.

Population genomics and phylogeography of Colletes gigas , a wild bee specialized on winter flowering plants

Diet specialization may affect the population genetic structure of pollinators by reducing gene flow and driving genetic differentiation, especially in pollen‐specialist bees. Colletes gigas is a pollen‐specialist pollinator of Camellia oleifera, one of the most important staple oil crops in China. Ca. oleifera blooms in cold climates and contains special compounds that make it an unusable pollen source to other pollinators. Thus, C. gigas undoubtedly plays a key role as the main pollinator of Ca. oleifera, with biological and economic significance. Here, we use a population genomic approach to analyze the roles of geography and climate on the genetic structure, genetic diversity, and demographic history of C. gigas. A total of 1,035,407 SNPs were identified from a 582.77 Gb dataset. Clustering and phylogenetic analyses revealed a marked genetic structure, with individuals grouped into nine local clusters. A significant isolation by distance was detected by both the Mantel test (R = .866, p = .008) and linear regression (R² = .616, p < .001). Precipitation and sunshine duration were positively and significantly (R ≥ .765, p ≤ .016) correlated with observed heterozygosity (H_o) and expected heterozygosity (H_e). These results showed that C. gigas populations had a distinct phylogeographic pattern determined by geographical distance and environmental factors (precipitation and sunshine duration). In addition, an analysis of paleogeographic dynamics indicated that C. gigas populations exhibited patterns of glacial expansion and interglacial contraction, likely resulting from post‐glacial habitat contraction and fragmentation. Our results indicated that the peculiar phylogeographic patterns in C. gigas populations may be related to their specialization under long‐term adaptation to host plants. This work improves our understanding of the population genetics in pollen‐specialist bees. The distinct genetic clusters identified in this study should be taken into consideration for the protection and utilization of this specialized crop pollinator.

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.

Large- and small-scale geographic structures affecting genetic patterns across populations of an Alpine butterfly

Understanding factors influencing patterns of genetic diversity and the population genetic structure of species is of particular importance in the current era of global climate change and habitat loss. These factors include the evolutionary history of a species as well as heterogeneity in the environment it occupies, which in turn can change across time. Most studies investigating spatio-temporal genetic patterns have focused on patterns across wide geographic areas rather than local variation, but the latter can nevertheless be important particularly in topographically complex areas. Here, we consider these issues in the Sooty Copper butterfly (Lycaena tityrus) from the European Alps, using genome-wide SNPs identified through RADseq. We found strong genetic differentiation within the Alps with four genetic clusters, indicating western, central, and eastern refuges, and a strong reduction of genetic diversity from west to east. This reduction in diversity may suggest that the southwestern refuge was the largest one in comparison to other refuges. Also, the high genetic diversity in the west may result from (a) admixture of different western refuges, (b) more recent demographic changes, or (c) introgression of lowland L. tityrus populations. At small spatial scales, populations were structured by several landscape features and especially by high mountain ridges and large river valleys. We detected 36 outlier loci likely under altitudinal selection, including several loci related to membranes and cellular processes. We suggest that efforts to preserve alpine L. tityrus should focus on the genetically diverse populations in the western Alps, and that the dolomite populations should be treated as genetically distinct management units, since they appear to be currently more threatened than others. This study demonstrates the usefulness of SNP-based approaches for understanding patterns of genetic diversity, gene flow, and selection in a region that is expected to be particularly vulnerable to climate change.

Next-Generation Sequencing and Its Impacts on Entomological Research in Ecology and Evolution

The advent of NGS-based methods has been profoundly transforming entomological research. Through continual development and improvement of different methods and sequencing platforms, NGS has promoted mass elucidation of partial or whole genetic materials associated with beneficial insects, pests (of agriculture, forestry and animal, and human health), and species of conservation concern, helping to unravel ecological and evolutionary mechanisms and characterizing survival, trophic interactions, and dispersal. It is shifting the scale of biodiversity and environmental analyses from individuals and biodiversity indicator species to the large-scale study of communities and ecosystems using bulk samples of species or a mixed "soup" of environmental DNA. As the NGS-based methods have become more affordable, complexity demystified, and specificity and sensitivity proven, their use in entomological research has spread widely. This article presents several examples on how NGS-based methods have been used in entomology to provide incentives to apply them when appropriate and to open our minds to the expected advances in entomology that are yet to come.

Bumblebee resilience to climate change, through plastic and adaptive responses

Bumblebees are ubiquitous, cold-adapted eusocial bees found worldwide from subarctic to tropical regions of the world. They are key pollinators in most temperate and boreal ecosystems, and both wild and managed populations are significant contributors to agricultural pollination services. Despite their broad ecological niche at the genus level, bumblebee species are threatened by climate change, particularly by rising average temperatures, intensifying seasonality and the increasing frequency of extreme weather events. While some temperature extremes may be offset at the individual or colony level through temperature regulation, most bumblebees are expected to exhibit specific plastic responses, selection in various key traits, and/or range contractions under even the mildest climate change. In this review, we provide an in-depth and up-to-date review on the various ways by which bumblebees overcome the threats associated with current and future global change. We use examples relevant to the fields of bumblebee physiology, morphology, behaviour, phenology, and dispersal to illustrate and discuss the contours of this new theoretical framework. Furthermore, we speculate on the extent to which adaptive responses to climate change may be influenced by bumblebees' capacity to disperse and track suitable climate conditions. Closing the knowledge gap and improving our understanding of bumblebees' adaptability or avoidance behaviour to different climatic circumstances will be necessary to improve current species climate response models. These models are essential to make correct predictions of species vulnerability in the face of future climate change and human-induced environmental changes to unfold appropriate future conservation strategies.

Conservation insights from wild bee genetic studies: Geographic differences, susceptibility to inbreeding, and signs of local adaptation

Conserving bees are critical both ecologically and economically. Genetic tools are valuable for monitoring these vital pollinators since tracking these small, fast-flying insects by traditional means is difficult. By surveying the current state of the literature, this review discusses how recent advances in landscape genetic and genomic research are elucidating how wild bees respond to anthropogenic threats. Current literature suggests that there may be geographic differences in the vulnerability of bee species to landscape changes. Populations of temperate bee species are becoming more isolated and more genetically depauperate as their landscape becomes more fragmented, but tropical bee species appear unaffected. These differences may be an artifact of historical differences in land-use, or it suggests that different management plans are needed for temperate and tropical bee species. Encouragingly, genetic studies on invasive bee species indicate that low levels of genetic diversity may not lead to rapid extinction in bees as once predicted. Additionally, next-generation sequencing has given researchers the power to identify potential genes under selection, which are likely critical to species' survival in their rapidly changing environment. While genetic studies provide insights into wild bee biology, more studies focusing on a greater phylogenetic and life-history breadth of species are needed. Therefore, caution should be taken when making broad conservation decisions based on the currently few species examined.

Urbanization reduces gene flow but not genetic diversity of stream salamander populations in the New York City metropolitan area

Natural landscape heterogeneity and barriers resulting from urbanization can reduce genetic connectivity between populations. The evolutionary, demographic, and ecological effects of reduced connectivity may lead to population isolation and ultimately extinction. Alteration to the terrestrial and aquatic environment caused by urban influence can affect gene flow, specifically for stream salamanders who depend on both landscapes for survival and reproduction. To examine how urbanization affects a relatively common stream salamander species, we compared genetic connectivity of Eurycea bislineata (northern two-lined salamander) populations within and between streams in an urban, suburban, and rural habitat around the New York City (NYC) metropolitan area. We report reduced genetic connectivity between streams within the urban landscape found to correspond with potential barriers to gene flow, that is, areas with more dense urbanization (roadways, industrial buildings, and residential housing). The suburban populations also exhibited areas of reduced connectivity correlated with areas of greater human land use and greater connectivity within a preserve protected from development. Connectivity was relatively high among neighboring rural streams, but a major roadway corresponded with genetic breaks even though the habitat contained more connected green space overall. Despite greater human disturbance across the landscape, urban and suburban salamander populations maintained comparable levels of genetic diversity to their rural counterparts. Yet small effective population size in the urban habitats yielded a high probability of loss of heterozygosity due to genetic drift in the future. In conclusion, urbanization impacted connectivity among stream salamander populations where its continual influence may eventually hinder population persistence for this native species in urban habitats.

Genetic structure across urban and agricultural landscapes reveals evidence of resource specialization and philopatry in the Eastern carpenter bee, Xylocopa virginica L

Human activity continues to impact global ecosystems, often by altering the habitat suitability, persistence, and movement of native species. It is thus critical to examine the population genetic structure of key ecosystemservice providers across human-altered landscapes to provide insight into the forces that limit wildlife persistence and movement across multiple spatial scales. While some studies have documented declines of bee pollinators as a result of human-mediated habitat alteration, others suggest that some bee species may benefit from altered land use due to increased food or nesting resource availability; however, detailed population and dispersal studies have been lacking. We investigated the population genetic structure of the Eastern carpenter bee, Xylocopa virginica, across 14 sites spanning more than 450 km, including dense urban areas and intensive agricultural habitat. X. virginica is a large bee which constructs nests in natural and human-associated wooden substrates, and is hypothesized to disperse broadly across urbanizing areas. Using 10 microsatellite loci, we detected significant genetic isolation by geographic distance and significant isolation by land use, where urban and cultivated landscapes were most conducive to gene flow. This is one of the first population genetic analyses to provide evidence of enhanced insect dispersal in human-altered areas as compared to semi-natural landscapes. We found moderate levels of regional-scale population structure across the study system (G'ST = 0.146) and substantial co-ancestry between the sampling regions, where co-ancestry patterns align with major human transportation corridors, suggesting that human-mediated movement may be influencing regional dispersal processes. Additionally, we found a signature of strong site-level philopatry where our analyses revealed significant levels of high genetic relatedness at very fine scales (<1 km), surprising given X. virginica's large body size. These results provide unique genetic evidence that insects can simultaneously exhibit substantial regional dispersal as well as high local nesting fidelity in landscapes dominated by human activity.

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

BACKGROUND

Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula.

RESULTS

IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana.

CONCLUSIONS

Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

Alternative Quantifications of Landscape Complementation to Model Gene Flow in Banded Longhorn Beetles [Typocerus v. velutinus (Olivier)]

Rapid progression of human socio-economic activities has altered the structure and function of natural landscapes. Species that rely on multiple, complementary habitat types (i.e., landscape complementation) to complete their life cycle may be especially at risk. However, such landscape complementation has received little attention in the context of landscape connectivity modeling. A previous study on flower longhorn beetles (Cerambycidae: Lepturinae) integrated landscape complementation into a continuous habitat suitability 'surface', which was then used to quantify landscape connectivity between pairs of sampling sites using gradient-surface metrics. This connectivity model was validated with molecular genetic data collected for the banded longhorn beetle (Typocerus v. velutinus) in Indiana, United States. However, this approach has not been compared to alternative models in a landscape genetics context. Here, we used a discrete land use/land cover map to calculate landscape metrics related to landscape complementation based on a patch mosaic model (PMM) as an alternative to the previously published, continuous habitat suitability model (HSM). We evaluated the HSM surface with gradient surface metrics (GSM) and with two resistance-based models (RBM) based on least cost path (LCP) and commute distance (CD), in addition to an isolation-by-distance (IBD) model based on Euclidean distance. We compared the ability of these competing models of connectivity to explain pairwise genetic distances (R ST) previously calculated from ten microsatellite genotypes of 454 beetles collected from 17 sites across Indiana, United States. Model selection with maximum likelihood population effects (MLPE) models found that GSM were most effective at explaining pairwise genetic distances as a proxy for gene flow across the landscape, followed by the landscape metrics calculated from the PMM, whereas the LCP model performed worse than both the CD and the isolation by distance model. We argue that the analysis of a continuous HSM with GSM might perform better because of their combined ability to effectively represent and quantify the continuous degree of landscape complementation (i.e., availability of complementary habitats in vicinity) found at and in-between sites, on which these beetles depend. Our findings may inform future studies that seek to model habitat connectivity in complex heterogeneous landscapes as natural habitats continue to become more fragmented in the Anthropocene.

Range-wide neutral and adaptive genetic structure of an endemic herb from Amazonian Savannas

Conserving genetic diversity in rare and narrowly distributed endemic species is essential to maintain their evolutionary potential and minimize extinction risk under future environmental change. In this study we assess neutral and adaptive genetic structure and genetic diversity in Brasilianthus carajensis (Melastomataceae), an endemic herb from Amazonian Savannas. Using RAD sequencing we identified a total of 9365 SNPs in 150 individuals collected across the species' entire distribution range. Relying on assumption-free genetic clustering methods and environmental association tests we then compared neutral with adaptive genetic structure. We found three neutral and six adaptive genetic clusters, which could be considered management units (MU) and adaptive units (AU), respectively. Pairwise genetic differentiation (F _ST) ranged between 0.024 and 0.048, and even though effective population sizes were below 100, no significant inbreeding was found in any inferred cluster. Nearly 10 % of all analysed sequences contained loci associated with temperature and precipitation, from which only 25 sequences contained annotated proteins, with some of them being very relevant for physiological processes in plants. Our findings provide a detailed insight into genetic diversity, neutral and adaptive genetic structure in a rare endemic herb, which can help guide conservation and management actions to avoid the loss of unique genetic variation.

Future scenarios of land-use-cover effects on pollination supply and demand in São Paulo State, Brazil

Abstract: Rapid land-use/land cover changes (LULCC) have led to habitat loss and fragmentation in the natural forest areas, which are mainly due to the intense and rapid expansion of urban areas and intense agricultural management. These processes are strongly threatening biodiversity maintenance and the ecosystem services provided by them. Among the ecosystem services under threat, pollination has been widely studied since this service is essential to promote food production and, therefore, human well-being. In a scenario of increasing LULCC it is crucial to understand the interplay between these changes, pollination demand by insect-dependent crops and pollinator availability to ensure these ecosystem services meet the increased demand for food production. In this study, we developed a conceptual model to disentangle the relationships between human-nature, especially LULCC, and its consequences, to the delivery of pollination service. We also presented a case study in the Brazilian São Paulo state, where we modeled the effects of predicted LULCC associated to agriculture expansion between the years 2012 and 2030 on pollinator demand by crops and pollinator supply, for fourteen economically important crops. Additionally, we systematized an expert-based Ecosystem Service matrix to estimate the influences of LULCC on the provision of pollination. Our results showed that by 2030, the demand for pollination will increase by 40% on average, while pollinator supply, estimated using suitability values for the different land-use/cover classes, will show, on average, a 3% decrease. Our results highlight the importance of considering the dialogue among stakeholders, governments, institutions, and scientists to find alternatives and strategies to promote pollinator-friendly practices and safeguard the provision of pollination services in a future under LULCC.