Population dynamics and seasonal migration patterns of Spodoptera exigua in northern China based on 11 years of monitoring data

Background

The beet armyworm, Spodoptera exigua (Hübner), is an important agricultural pest worldwide that has caused serious economic losses in the main crop-producing areas of China. To effectively monitor and control this pest, it is crucial to investigate its population dynamics and seasonal migration patterns in northern China.

Methods

In this study, we monitored the population dynamics of S. exigua using sex pheromone traps in Shenyang, Liaoning Province from 2012 to 2022, combining these data with amigration trajectory simulation approach and synoptic weather analysis.

Results

There were significant interannual and seasonal variations in the capture number of S. exigua, and the total number of S. exigua exceeded 2,000 individuals in 2018 and 2020. The highest and lowest numbers of S. exigua were trapped in September and May, accounting for 34.65% ± 6.81% and 0.11% ± 0.04% of the annual totals, respectively. The average occurrence period was 140.9 ± 9.34 days during 2012-2022. In addition, the biomass of S. exigua also increased significantly during these years. The simulated seasonal migration trajectories also revealed varying source regions in different months, primarily originated from Northeast China and East China. These unique insights into the migration patterns of S. exigua will contribute to a deeper understanding of its occurrence in northern China and provide a theoretical basis for regional monitoring, early warning, and the development of effective management strategies for long-range migratory pests.

Movement Ecology of Adult Western Corn Rootworm: Implications for Management

Movement of adult western corn rootworm, Diabrotica virgifera virgifera LeConte, is of fundamental importance to this species' population dynamics, ecology, evolution, and interactions with its environment, including cultivated cornfields. Realistic parameterization of dispersal components of models is needed to predict rates of range expansion, development, and spread of resistance to control measures and improve pest and resistance management strategies. However, a coherent understanding of western corn rootworm movement ecology has remained elusive because of conflicting evidence for both short- and long-distance lifetime dispersal, a type of dilemma observed in many species called Reid's paradox. Attempts to resolve this paradox using population genetic strategies to estimate rates of gene flow over space likewise imply greater dispersal distances than direct observations of short-range movement suggest, a dilemma called Slatkin's paradox. Based on the wide-array of available evidence, we present a conceptual model of adult western corn rootworm movement ecology under the premise it is a partially migratory species. We propose that rootworm populations consist of two behavioral phenotypes, resident and migrant. Both engage in local, appetitive flights, but only the migrant phenotype also makes non-appetitive migratory flights, resulting in observed patterns of bimodal dispersal distances and resolution of Reid's and Slatkin's paradoxes.

Comigration and interactions between two species of rice planthopper (Laodelphax striatellus and Sogatella furcifera) and natural enemies in eastern Asia

BACKGROUND

Natural enemies are important in pest control. However, control by natural enemies is hindered by the migration of rice planthoppers. Therefore, comigration and interactions between Laodelphax striatellus (Fallén) and Sogatella furcifera (Horváth) and five predator species, Chrysoperla sinica Tjeder, Harmonia axyridis (Pallas), Episyrphus balteatus, Syrphus corollae (Fab.) and Chrysopa pallens (Rambur) in eastern Asia were investigated.

RESULTS

From 2012 to 2021, the migration patterns of two rice planthoppers and five natural enemy species were monitored by suction trapping on Beihuang Island, Shandong Province, China. Both planthoppers and the five natural enemies regularly comigrated from late April to late October each year. There were significant interannual and seasonal differences in the numbers of two rice planthoppers migrating across this island. Simulated seasonal migration trajectories indicated different source areas for the two rice planthoppers, which mainly originated in northeast, north and east China. The biomass of planthoppers was significantly positively correlated with that of the ladybug H. axyridis in all migration periods, and significant differences in the ratio of rice planthoppers to natural enemies among months. A time-lag effect between seasons was obtained when natural enemies and pests comigrated.

CONCLUSION

Migration was coordinated between rice planthoppers and natural enemies in East Asia. When natural enemies and rice planthoppers comigrated, time lags between seasons were observed. The unique insights into the migration patterns will help to increase understanding of the occurrence of rice planthoppers in eastern Asia and provide an important theoretical basis for regional monitoring and management of rice planthoppers. © 2023 Society of Chemical Industry.

Dispersal inference from population genetic variation using a convolutional neural network

The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here, we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training-including population density, demographic history, habitat size, and sampling area-and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate inference of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN," a potentially valuable new tool for estimating dispersal distance in nonmodel systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.

Landscape genetics identifies barriers to Natterjack toad metapopulation dispersal

Habitat fragmentation and loss reduce population size and connectivity, which imperils populations. Functional connectivity is key for species persistence in human-modified landscapes. To inform species conservation management, we investigated spatial genetic structure, gene flow and inferred dispersal between twelve breeding sites of the Natterjack toad (Bufo calamita); regionally Red-Listed as Endangered in Ireland. Spatial genetic structure was determined using both Bayesian and non-Bayesian clustering analysis of 13 polymorphic microsatellite loci genotyping 247 individuals. We tested the influence of geographic distance, climate, habitat, geographical features, and anthropogenic pressure on pairwise genetic distances between breeding sites using Isolation-by-distance and Isolation-by-resistance based on least-cost path and circuit theory models of functional connectivity. There was clear spatial structuring with genetic distances increasing with geographic distance. Gene flow was best explained by Isolation-by-resistance models with coniferous forestry plantations, bog, marsh, moor and heath, scrub, anthropogenic presence (Human Influence Index) and rivers (riparian density) identified as habitats with high resistance to gene flow while metapopulation connectivity was enhanced by coastal habitats (beaches, sand dunes and salt marshes) and coastal grassland. Despite substantial declines in census numbers over the past 15 years and its regional status as Endangered, the Natterjack toad population in Ireland retains high genetic diversity. If declines continue, maintaining habitat connectivity to prevent genetic erosion by management of coastal grasslands, pond construction and assisted migration through translocation will be increasingly important.

Population Genomics for Insect Conservation

Insects constitute vital components of ecosystems. There is alarming evidence for global declines in insect species diversity, abundance, and biomass caused by anthropogenic drivers such as habitat degradation or loss, agricultural practices, climate change, and environmental pollution. This raises important concerns about human food security and ecosystem functionality and calls for more research to assess insect population trends and identify threatened species and the causes of declines to inform conservation strategies. Analysis of genetic diversity is a powerful tool to address these goals, but so far animal conservation genetics research has focused strongly on endangered vertebrates, devoting less attention to invertebrates, such as insects, that constitute most biodiversity. Insects' shorter generation times and larger population sizes likely necessitate different analytical methods and management strategies. The availability of high-quality reference genome assemblies enables population genomics to address several key issues. These include precise inference of past demographic fluctuations and recent declines, measurement of genetic load levels, delineation of evolutionarily significant units and cryptic species, and analysis of genetic adaptation to stressors. This enables identification of populations that are particularly vulnerable to future threats, considering their potential to adapt and evolve. We review the application of population genomics to insect conservation and the outlook for averting insect declines.

Timing and distance of natal dispersal in Asian black bears

Dispersal has important implications for population ecology and genetics of a species through redistribution of individuals. In most mammals, males leave their natal area before they reach sexual maturity, whereas females are commonly philopatric. Here, we investigate the patterns of natal dispersal in the Asian black bear (Ursus thibetanus) based on data from 550 bears (378 males, 172 females) captured or removed in Gunma and Tochigi prefectures on central Honshu Island, Japan in 2003–2018. We used genetic data and parentage analysis to investigate sex-biased differences in the distance of natal dispersal. We further investigated the age of dispersal using spatial autocorrelation analysis, that is, the change in the correlation between genetic and geographic distances in each sex and age group. Our results revealed that male dispersal distances (mean ± SE = 17.4 ± 3.5 km) were significantly farther than female distances (4.8 ± 1.7 km), and the results were not affected by years of mast failures, a prominent forage source for this population. Based on an average adult female home range radius of 1.8 km, 96% of the males and 50% of the females dispersed. In the spatial autocorrelation analysis, the changes in the relationship between genetic and geographic distances were more pronounced in males compared to females. Males seem to mostly disperse at age 3 regardless of mast productivity, and they gradually disperse far from their home range, but young and inexperienced males may return to their natal home range in years with poor food conditions. The results suggest that factors driving the dispersal process seem to be population structure-based instead of forage availability-based. In females, a significant genetic relationship was observed among all individuals in the group with a minimum age of 6 years within a distance of 2 km, which resulted in the formation of matrilineal assemblages.

A wide hybrid zone mediated by precipitation contributed to confused geographical structure of Scutiger boulengeri

Confused geographical structure of a population and mitonuclear discordance are shaped by a combination of rapid changes in population demographics and shifts in ecology. In this study, we generated a time-calibrated phylogeny of Scutiger boulengeri, an endemic Xizang alpine toad occurring in mountain streams on the Qinghai-Xizang (Tibet) Plateau (QTP). Based on three mitochondrial DNA (mtDNA) genes, eight clades were assigned to three deeply divergent lineages. Analysis of nuclear DNA (nuDNA) genes revealed three distinct clusters without geographic structure, indicating significantly high rates of gene flow. Coalescent theory framework analysis (approximate Bayesian computation model DIYABC and Migrate-N) suggested that divergence of the main intraspecific clusters was the result of hybridization after secondary contact in the Holocene around 0.59 million years ago (Ma). The ratio of mtDNA F _ST (fixation index) to nuDNA F _ST was 2.3, thus failing to show male-biased dispersal. Geographic cline analysis showed that a wide hybrid zone was initially established in southwestern China, without significant reproductive isolation but with strong introgression in S. boulengeri, suggesting high hybrid fitness. Furthermore, mtDNA genes exhibited isolation by distance (IBD) while nuDNA genes exhibited significant isolation by environment (IBE). Results suggested that mitonuclear discordance may have initially been caused by geographic isolation, followed by precipitation-mediated hybridization, producing a wide hybrid zone and geographic structure confusion of nuDNA genes in S. boulengeri. This study indicated that complicated historical processes may have led to specific genetic patterns, with a specific climate factor facilitating gene flow in the system.

Close Kin Dyads Indicate Intergenerational Dispersal and Barriers

AbstractThe movement of individuals through continuous space is typically constrained by dispersal ability and dispersal barriers. A range of approaches have been developed to investigate these. Kindisperse is a new approach that infers recent intergenerational dispersal (σ) from close kin dyads and appears particularly useful for investigating taxa that are difficult to observe individually. This study, focusing on the mosquito Aedes aegypti, shows how the same close kin data can also be used for barrier detection. We empirically demonstrate this new extension of the method using genome-wide sequence data from 266 Ae. aegypti. First, we use the spatial distribution of full-sib dyads collected within one generation to infer past movements of ovipositing female mosquitoes. These dyads indicated the relative barrier strengths of two roads and performed favorably against alternative genetic methods for detecting barriers. We then use Kindisperse to quantify recent intergenerational dispersal (σ=81.5-197.1 m generation^-1/2) from the difference in variance between the sib and the first cousin spatial distributions and, from this, estimate effective population density (ρ=833-4,864 km^-2). Dispersal estimates showed general agreement with those from mark-release-recapture studies. Barriers, σ, ρ, and neighborhood size (331-526) can inform forthcoming releases of dengue-suppressing Wolbachia bacteria into this mosquito population.

Climate influences the genetic structure and niche differentiation among populations of the olive field mouse Abrothrix olivacea (Cricetidae: Abrotrichini)

Even when environmental variation over time and space is commonly considered as an important driver of population divergence, few evaluations of intraspecific genetic variation explicitly assess whether observed structure has been caused by or is correlated with landscape heterogeneity. Several phylogeographic studies have characterized the mitochondrial diversity of Abrothrix olivacea, but none has incorporated landscape genetics analyses and ecological niche modeling, leaving a gap in the understanding of the species evolutionary history. Here, these aspects were addressed based on 186 single nucleotide polymorphisms, extracted from sequences of 801 bp of Cytb gene, gathered from 416 individuals collected at 103 localities in Argentina and Chile. Employing multivariate statistical analyses (gPCA, Mantel and Partial Mantel Tests, Procrustes Analysis, and RDA), associations between genetic differences and geographic and climatic distances were evaluated. Presence data was employed to estimate the potential geographic distribution of this species during historical and contemporary climatic scenarios, and to address differences among the climatic niches of their main mitochondrial lineages. The significant influence of landscape features in structuring mitochondrial variability was evidenced at different spatial scales, as well as the role of past climatic dynamics in driving geographic range shifts, mostly associated to Quaternary glaciations. Overall, these results suggest that throughout geographic range gene flow is unevenly influenced by climatic dissimilarity and the geographic distancing, and that studied lineages do not exhibit distributional signals of climatic niche conservatism. Additionally, genetic differentiation occurred by more complex evolutionary processes than mere disruption of gene flow or drift.

Integrating dispersal, breeding and abundance data with graph theory for the characterization and management of functional connectivity in amphibian pondscapes

CONTEXT

Robust assessment of functional connectivity in amphibian population networks is essential to address their global decline. The potential of graph theory to characterize connectivity among amphibian populations has already been confirmed, but the movement data on which modelled graphs rely are often scarce and inaccurate. While probabilistic methods that account for intraspecific variability in dispersal better reflect the biological reality of functional connectivity, they must be informed by systematically recorded individual movement data, which are difficult to obtain for secretive taxa like amphibians.

OBJECTIVES

Our aim is to assess the applied potential of probabilistic graph theory to characterize overall connectivity across amphibian pondscapes using fine-scale capture-recapture data, and to inform conservation management based on the role of ponds on functional connectivity.

METHODS

We monitored an amphibian community in a pondscape located in a Spanish "dehesa" for 2 years. Photoidentification was used to build capture histories for individuals of six species, from which dispersal kernels and population sizes were estimated to model probabilistic graphs.

RESULTS

We obtained kernels of variable robustness for six species. Node importance for connectivity varied between species, but with common patterns such as shared road crossing areas and the presence of coincident interconnected pond clusters.

CONCLUSIONS

The combination of photoidentification, capture-recapture data and graph theory allowed us to characterize functional connectivity across the pondscape of study accounting for dispersal variability and identify areas where conservation actions could be most efficient. Our results highlight the need to account for interspecific differences in the study and management of amphibian pondscapes.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10980-022-01520-x.

Dispersal patterns in Yunnan snub-nosed monkeys

Sex-biased dispersal is common in group-living animals. Due to differences in local demographic and environmental factors, sex-biased dispersal presents many irregular patterns. In this study, a habituated, individually identified Yunnan snub-nosed monkey Rhinopithecus bieti group was observed over 9 years; 192 dispersal events, including 97 male dispersal events (25 natal dispersal and 72 secondary dispersal) and 95 female dispersal events (34 natal dispersal and 61 secondary dispersal) were observed. Males and females showed different dispersal paths, dispersal ages, and dispersal patterns. Females had 2 dispersal paths, whereas males had 4 paths. In terms of age of dispersal, the male age of natal dispersal was younger than for females. Males prefer single dispersal, whereas females prefer parallel dispersal. Our study indicates that the dispersal pattern of R. bieti should be classified as a bisexual dispersal pattern. The differences in dispersal path, average age at dispersal, and dispersal path pattern indicate that Yunnan snub-nosed monkeys may still retain a loose matrilineal social system.

Non-Lethal Sampling Supports Integrative Movement Research in Freshwater Fish

Freshwater ecosystems and fishes are enormous resources for human uses and biodiversity worldwide. However, anthropogenic climate change and factors such as dams and environmental contaminants threaten these freshwater systems. One way that researchers can address conservation issues in freshwater fishes is via integrative non-lethal movement research. We review different methods for studying movement, such as with acoustic telemetry. Methods for connecting movement and physiology are then reviewed, by using non-lethal tissue biopsies to assay environmental contaminants, isotope composition, protein metabolism, and gene expression. Methods for connecting movement and genetics are reviewed as well, such as by using population genetics or quantitative genetics and genome-wide association studies. We present further considerations for collecting molecular data, the ethical foundations of non-lethal sampling, integrative approaches to research, and management decisions. Ultimately, we argue that non-lethal sampling is effective for conducting integrative, movement-oriented research in freshwater fishes. This research has the potential for addressing critical issues in freshwater systems in the future.

Evolutionary history and colonization patterns of the wing dimorphic grasshopper Dichroplus vittatus in two Argentinean biomes

Quaternary climate oscillations and modification of the environment by humans have played an important role in shaping species distribution and genetic structure of modern species. Here, population genetic parameters were inferred from the analysis of 168 individuals belonging to 11 populations of the South American grasshopper, Dichroplus vittatus, distributed in two Argentinean Biomes (Grassland and Savanna), by sequencing a 543 bp of the mitochondrial COI gene. Overall, we detected considerable haplotype diversity and low nucleotide diversity. AMOVA analyses showed a significant degree of differentiation among Biomes and between populations. Two major mitochondrial lineages can be distinguished. The haplogroup containing the most common haplotype split 17,000 years BP while the haplogroup including the second most common haplotype has a divergence date of about 11,700 years. Approximate Bayesian Computation (ABC) analyses showed that the palaeodemographic scenario that best fitted our data is consistent with a hypothesis of divergence from an ancestral population and subsequent admixture with Grassland-Savanna (South–North) direction. Our results suggest that populations located in both Biomes would derive from a single ancestral population that colonized the region after the Last Glacial Maximum and Grassland would have a more ancestral origin than Savanna. Further, our results emphasize the importance of human-mediated dispersal in the reconfiguration of genetic diversity of species with potential pest capacity.

Population genetics unveils large-scale migration dynamics and population turnover of Spodoptera exigua

BACKGROUND

Migration is a widespread phenomenon among many insect species, including herbivorous crop pests. At present, scant information exists on the long-range migration of the polyphagous armyworm, Spodoptera exigua and its underlying climatic determinants (i.e. East Asian or South Asian monsoon circulation). In this study, we employed a population genetics approach to delineate S. exigua migration patterns across multiple Asian countries.

RESULTS

Using mitochondrial cytochrome I (COI) and microsatellite markers, low-to-moderate levels of genetic diversity were detected among 101 S. exigua populations collected across China, Pakistan and Vietnam. Haplotype diversity and nucleotide diversity did not differ between years. Two spatially explicit genetic clusters were detected, an eastern and a western clade, with the former comprising populations in the East Asia monsoon area. No genetic differentiation was recorded among armyworm populations in the year-round breeding area, nor among those of the overwintering and nonoverwintering areas. Five of the most widespread mitochondrial haplotypes reflected the extensive gene flow across at a large spatial scale.

CONCLUSION

Low-to-moderate levels of genetic diversity were observed, and evidence was found for genetic clustering in certain geographical areas. Accordingly, our unique insights into S. exigua population genetics and spatiotemporal migration dynamics help to guide applied ecological studies, ecological intensification schemes or (area-wide) pest management campaigns in China and abroad. © 2021 Society of Chemical Industry.

Population genetic structure of the carrot weevil ( Listronotus oregonensis ) in North America

Population genetic studies of insect pests enhance our ability to anticipate problems in agroecosystems, such as pest outbreaks, insecticide resistance, or expansions of the host range. This study focuses on geographic distance and host plant selection as potential determinants of genetic differentiation of the carrot weevil Listronotus oregonensis, a major pest of several apiaceous crops in North America. To undertake genetic studies on this species, we assembled the first complete genome sequence for L. oregonensis. Then, we used both haplotype discrimination with mitochondrial DNA (mtDNA) and a genotyping‐by‐sequencing (GBS) approach to characterize the genetic population structure. A total of 220 individuals were sampled from 17 localities in the provinces of Québec, Ontario, Nova Scotia (Canada), and the state of Ohio (USA). Our results showed significant genetic differences between distant populations across North America, indicating that geographic distance represents an important factor of differentiation for the carrot weevil. Furthermore, the GBS analysis revealed more different clusters than COI analysis between Québec and Nova Scotia populations, suggesting a recent differentiation in the latter province. In contrast, we found no clear evidence of population structure associated with the four cultivated apiaceous plants tested (carrot, parsley, celery, and celeriac) using populations from Québec. This first characterization of the genetic structure of the carrot weevil contributes to a better understanding of the gene flow of the species and helps to adapt local pest management measures to better control this agricultural pest.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Context-dependent dispersal determines relatedness and genetic structure in a patchy amphibian population

Dispersal is a central process in ecology and evolution with far reaching consequences for the dynamics and genetics of spatially structured populations (SSPs). Individuals can adjust their decisions to disperse according to local fitness prospects, resulting in context-dependent dispersal. By determining dispersal rate, distance and direction, these individual-level decisions further modulate the demography, relatedness and genetic structure of SSPs. Here, we examined how context-dependent dispersal influences the dynamics and genetics of a great crested newt (Triturus cristatus) SSP. We collected capture-recapture data of 5564 individuals and genetic data of 950 individuals across an SSP in northern Germany. We added genetic data from six sites outside this SSP to assess genetic structure and gene flow at a regional level. Dispersal rates within the SSP were high but dispersal distances were short. Dispersal was context-dependent: individuals preferentially immigrated into high-quality ponds where breeding probabilities were higher. The studied SSP behaved like a patchy population, where subpopulations at each pond were demographically interdependent. High context-dependent dispersal led to weak but significant spatial genetic structure and relatedness within the SSP. At the regional level, a strong hierarchical genetic structure with very few first-generation migrants as well as low effective dispersal rates suggest the presence of independent demographic units. Overall, our study highlights the importance of habitat quality for driving context-dependent dispersal and therefore demography and genetic structure in SSPs. Limited capacity for long-distance dispersal seems to increase genetic structure within a population and leads to demographic isolation in anthropogenic landscapes.

Landscape-scale population connectivity in two parasitoid species associated with the spruce budworm: Testing the birdfeeder effect using genetic data

Periodic and spatially synchronous outbreaks of insect pests have dramatic consequences for boreal and sub-boreal forests. Within these multitrophic systems, parasitoids can be stabilizing agents by dispersing toward patches containing higher host density (the so-called birdfeeder effect). However, we know little about the dispersal abilities of parasitoids in continuous forested landscapes, limiting our understanding of the spatiotemporal dynamics of host-parasitoid systems, and constraining our ability to predict forest resilience in the context of global changes. In this study, we investigate the spatial genetic structure and spatial variation in genetic diversity of two important species of spruce budworm larval parasitoids during outbreaks: Apanteles fumiferanae Viereck (Braconidae) and Glypta fumiferanae (Viereck) (Ichneumonidae). Using parasitoids sampled in 2014 from 26 and 29 locations across a study area of 350,000 km² , we identified 1,012 and 992 neutral SNP loci for A. fumiferanae (N = 279 individuals) and G. fumiferanae (N = 382), respectively. Using DAPC, PCA, AMOVA, and IBD analyses, we found evidence for panmixia and high genetic connectivity for both species, matching the previously described genetic structure of the spruce budworm within the same context, suggesting similar effective dispersal during outbreaks and high parasitoid population densities between outbreaks. We also found a significant negative relationship between genetic diversity and latitude for A. fumiferanae but not for G. fumiferanae, suggesting that northern range limits may vary by species within the spruce budworm parasitoid community. These spatial dynamics should be considered when predicting future insect outbreak severities in boreal landscapes.

Dispersal in a house sparrow metapopulation: An integrative case study of genetic assignment calibrated with ecological data and pedigree information

Dispersal has a crucial role determining ecoevolutionary dynamics through both gene flow and population size regulation. However, to study dispersal and its consequences, one must distinguish immigrants from residents. Dispersers can be identified using telemetry, capture-mark-recapture (CMR) methods, or genetic assignment methods. All of these methods have disadvantages, such as high costs and substantial field efforts needed for telemetry and CMR surveys, and adequate genetic distance required in genetic assignment. In this study, we used genome-wide 200K Single Nucleotide Polymorphism data and two different genetic assignment approaches (GSI_SIM, Bayesian framework; BONE, network-based estimation) to identify the dispersers in a house sparrow (Passer domesticus) metapopulation sampled over 16 years. Our results showed higher assignment accuracy with BONE. Hence, we proceeded to diagnose potential sources of errors in the assignment results from the BONE method due to variation in levels of interpopulation genetic differentiation, intrapopulation genetic variation and sample size. We show that assignment accuracy is high even at low levels of genetic differentiation and that it increases with the proportion of a population that has been sampled. Finally, we highlight that dispersal studies integrating both ecological and genetic data provide robust assessments of the dispersal patterns in natural populations.

Molecular approaches reveal weak sibship aggregation and a high dispersal propensity in a non-native fish parasite

Inferring parameters related to the aggregation pattern of parasites and to their dispersal propensity are important for predicting their ecological consequences and evolutionary potential. Nonetheless, it is notoriously difficult to infer these parameters from wildlife parasites given the difficulty in tracking these organisms. Molecular-based inferences constitute a promising approach that has yet rarely been applied in the wild. Here, we combined several population genetic analyses including sibship reconstruction to document the genetic structure, patterns of sibship aggregation, and the dispersal dynamics of a non-native parasite of fish, the freshwater copepod ectoparasite Tracheliastes polycolpus. We collected parasites according to a hierarchical sampling design, with the sampling of all parasites from all host individuals captured in eight sites spread along an upstream-downstream river gradient. Individual multilocus genotypes were obtained from 14 microsatellite markers, and used to assign parasites to full-sib families and to investigate the genetic structure of T. polycolpus among both hosts and sampling sites. The distribution of full-sibs obtained among the sampling sites was used to estimate individual dispersal distances within families. Our results showed that T. polycolpus sibs tend to be aggregated within sites but not within host individuals. We detected important upstream-to-downstream dispersal events of T. polycolpus between sites (modal distance: 25.4 km; 95% CI [22.9, 27.7]), becoming scarcer as the geographic distance from their family core location increases. Such a dispersal pattern likely contributes to the strong isolation-by-distance observed at the river scale. We also detected some downstream-to-upstream dispersal events (modal distance: 2.6 km; 95% CI [2.2-23.3]) that likely result from movements of infected hosts. Within each site, the dispersal of free-living infective larvae among hosts likely contributes to increasing genetic diversity on hosts, possibly fostering the evolutionary potential of T. polycolpus.

Congruent Genetic and Demographic Dispersal Rates in a Natural Metapopulation at Equilibrium

Understanding the functioning of natural metapopulations at relevant spatial and temporal scales is necessary to accurately feed both theoretical eco-evolutionary models and conservation plans. One key metric to describe the dynamics of metapopulations is dispersal rate. It can be estimated with either direct field estimates of individual movements or with indirect molecular methods, but the two approaches do not necessarily match. We present a field study in a large natural metapopulation of the butterfly Boloria eunomia in Belgium surveyed over three generations using synchronized demographic and genetic datasets with the aim to characterize its genetic structure, its dispersal dynamics, and its demographic stability. By comparing the census and effective population sizes, and the estimates of dispersal rates, we found evidence of stability at several levels: constant inter-generational ranking of population sizes without drastic historical changes, stable genetic structure and geographically-influenced dispersal movements. Interestingly, contemporary dispersal estimates matched between direct field and indirect genetic assessments. We discuss the eco-evolutionary mechanisms that could explain the described stability of the metapopulation, and suggest that destabilizing agents like inter-generational fluctuations in population sizes could be controlled by a long adaptive history of the species to its dynamic local environment. We finally propose methodological avenues to further improve the match between demographic and genetic estimates of dispersal.

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.

Urbanization is associated with shifts in bumblebee body size, with cascading effects on pollination

Urbanization is a global phenomenon with major effects on species, the structure of community functional traits and ecological interactions. Body size is a key species trait linked to metabolism, life-history and dispersal as well as a major determinant of ecological networks. Here, using a well-replicated urban-rural sampling design in Central Europe, we investigate the direction of change of body size in response to urbanization in three common bumblebee species, Bombus lapidarius, Bombus pascuorum and Bombus terrestris, and potential knock-on effects on pollination service provision. We found foragers of B. terrestris to be larger in cities and the body size of all species to be positively correlated with road density (albeit at different, species-specific scales); these are expected consequences of habitat fragmentation resulting from urbanization. High ambient temperature at sampling was associated with both a small body size and an increase in variation of body size in all three species. At the community level, the community-weighted mean body size and its variation increased with urbanization. Urbanization had an indirect positive effect on pollination services through its effects not only on flower visitation rate but also on community-weighted mean body size and its variation. We discuss the eco-evolutionary implications of the effect of urbanization on body size, and the relevance of these findings for the key ecosystem service of pollination.

Quantifying the individual impact of artificial barriers in freshwaters: A standardized and absolute genetic index of fragmentation

Fragmentation by artificial barriers is an important threat to freshwater biodiversity. Mitigating the negative aftermaths of fragmentation is of crucial importance, and it is now essential for environmental managers to benefit from a precise estimate of the individual impact of weirs and dams on river connectivity. Although the indirect monitoring of fragmentation using molecular data constitutes a promising approach, it is plagued with several constraints preventing a standardized quantification of barrier effects. Indeed, observed levels of genetic differentiation GD depend on both the age of the obstacle and the effective size of the populations it separates, making comparisons of the actual barrier effect of different obstacles difficult. Here, we developed a standardized genetic index of fragmentation (F INDEX), allowing an absolute and independent assessment of the individual effects of obstacles on connectivity. The F INDEX is the standardized ratio between the observed GD between pairs of populations located on either side of an obstacle and the GD expected if this obstacle completely prevented gene flow. The expected GD is calculated from simulations taking into account two parameters: the number of generations since barrier creation and the expected heterozygosity of the populations, a proxy for effective population size. Using both simulated and empirical datasets, we explored the validity and the limits of the F INDEX. We demonstrated that it allows quantifying effects of fragmentation only from a few generations after barrier creation and provides valid comparisons among obstacles of different ages and populations (or species) of different effective sizes. The F INDEX requires a minimum amount of fieldwork and genotypic data and solves some of the difficulties inherent to the study of artificial fragmentation in rivers and potentially in other ecosystems. This makes the F INDEX promising to support the management of freshwater species affected by barriers, notably for planning and evaluating restoration programs.

Genomic variation among populations provides insight into the causes of metacommunity survival

Predators and prey interact at small spatial scales, but during their lifetime disperse at much larger spatial scales. Trophic metacommunity theory proposes that dispersal is a critical process that determines food web structure at small and large scales. The application of metacommunity theory to empirical systems remains elusive because key parameters such as dispersal and interaction strengths have been very difficult to quantify. Here we develop a novel approach that combines population genomics with mesocosm experiments to parameterize a metacommunity model. Using genotyping-by-sequencing, we characterized the dispersal kernels of a predator-prey pair living in a phytotelm metacommunity. We found that the prey dispersed up to 25 km while the predator dispersed only 350 m. We then quantified a functional response for these species using feeding trials. Even without invoking differences in the abiotic niche, our empirically parameterized simulation model produced patterns of population survival and occupancy that were consistent with past observations on the natural system. Importantly we found that these patterns were more likely to be found with simulations based on our observed values than in other regions of potential parameter space. This suggests that the observed dispersal kernels contribute to the dynamics of these species in the metacommunity.

Using spatial genetics to quantify mosquito dispersal for control programs

Background

Hundreds of millions of people get a mosquito-borne disease every year and nearly one million die. Transmission of these infections is primarily tackled through the control of mosquito vectors. The accurate quantification of mosquito dispersal is critical for the design and optimization of vector control programs, yet the measurement of dispersal using traditional mark-release-recapture (MRR) methods is logistically challenging and often unrepresentative of an insect’s true behavior. Using Aedes aegypti (a major arboviral vector) as a model and two study sites in Singapore, we show how mosquito dispersal can be characterized by the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors.

Results

Using simple oviposition traps, we captured adult female Ae. aegypti across high-rise apartment blocks and genotyped them using genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance which results from one generation of successful breeding (effective dispersal), using the distance separating full siblings and 2nd- and 3rd-degree relatives (close kin). The estimated dispersal distance kernel was exponential (Laplacian), with a mean dispersal distance (and dispersal kernel spread σ) of 45.2 m (95% CI 39.7–51.3 m), and 10% probability of a dispersal > 100 m (95% CI 92–117 m). Our genetically derived estimates matched the parametrized dispersal kernels from previous MRR experiments. If few close kin are captured, a conventional genetic isolation-by-distance analysis can be used, as it can produce σ estimates congruent with the close-kin method if effective population density is accurately estimated. Genetic patch size, estimated by spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel “tail” that influences, for example, the critical radii of release zones and the speed of Wolbachia spread in mosquito replacement programs.

Conclusions

We demonstrate that spatial genetics can provide a robust characterization of mosquito dispersal. With the decreasing cost of next-generation sequencing, the production of spatial genetic data is increasingly accessible. Given the challenges of conventional MRR methods, and the importance of quantified dispersal in operational vector control decisions, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

Genome-wide analysis of diamondback moth, Plutella xylostella L., from Brassica crops and wild host plants reveals no genetic structure in Australia

Molecular studies of population structure can reveal insight into the movement patterns of mobile insect pests in agricultural landscapes. The diamondback moth, Plutella xylostella L., a destructive pest of Brassica vegetable and oilseed crops worldwide, seasonally colonizes winter canola crops in southern Australia from alternative host plant sources. To investigate movement, we collected 59 P. xylostella populations from canola crops, Brassica vegetable and forage crops and brassicaceous wild host plants throughout southern Australia in 2014 and 2015 and genotyped 833 individuals using RAD-seq for genome-wide analysis. Despite a geographic sampling scale > 3,000 km and a statistically powerful set of 1,032 SNP markers, there was no genetic differentiation among P. xylostella populations irrespective of geographic location, host plant or sampling year, and no evidence for isolation-by-distance. Hierarchical STRUCTURE analysis at K = 2–5 showed nearly uniform ancestry in both years. Cluster analysis showed divergence of a small number of individuals at several locations, possibly reflecting an artefact of sampling related individuals. It is likely that genetic homogeneity within Australian P. xylostella largely reflects the recent colonization history of this species but is maintained through some level of present gene flow. Use of genome-wide neutral markers was uninformative for revealing the seasonal movements of P. xylostella within Australia, but may provide more insight in other global regions where the species has higher genetic diversity.

Urban Populations of Aedes aegypti (Diptera: Culicidae) From Central Argentina: Dispersal Patterns Assessed by Bayesian and Multivariate Methods

Aedes aegypti (L.), the main vector of dengue and other arboviruses, was declared eradicated from Argentina in 1964; however, in 1987, it was detected again and nowadays it occurs in most of the country territory. To understand the transmission of vector-borne diseases, knowledge of the dispersal of vector populations is essential to evaluate the risk of pathogen transmission. We conducted a population genetic analysis of Ae. aegypti in 20 neighborhoods from Córdoba, the second largest city in Argentina, using 10 microsatellite loci. High genetic differentiation and the absence of an isolation by distance pattern was found using Weir and Cockerham's θ. Bayesian and multivariate clustering analyses showed that the studied sites included individuals with high membership coefficients (Q) in their populations, individuals with membership in another cluster, and admixed individuals. Individuals with high Q in clusters different from the population in which they were collected strongly suggests that passive transport is important in shaping the Ae. aegypti dispersal pattern in Córdoba city. Knowing the genetic structure of Ae. aegypti populations and their dispersal patterns would contribute to the implementation of vector control programs.

De novo discovery of SNPs for genotyping endangered sun parakeets (Aratinga solstitialis) in Guyana

Parrots (Psittaciformes) are among the most endangered groups of birds today and remain threatened by habitat loss and exploitation for the live bird trade. Under such conditions, reliable and non-invasive monitoring techniques are crucial for successful conservation measures. In this study, we developed a panel of 86 high quality SNPs for genotyping endangered sun parakeets (Aratinga solstitialis) in Guyana, which form one of the last known breeding populations of this South American species in the wild. Genotyping was tested on different types of samples (blood, feathers, feces, beak and cloacal swabs). While blood performed best, feathers and feces also yielded reliable results and could thus be used as non-invasive sources of DNA for future population monitoring. Discriminant Analysis of Principal Components (DAPC) on genotypes revealed that Guyanese sun parakeets clustered separately from other psittacine species as well as conspecifics from a captive population. A priori known first-order kinships were also adequately detected by the SNP panel. Using a series of experimental contaminations, we found that contamination from other psittacine species and slight contamination (~ 10%) from conspecifics did not prevent successful genotyping and recognition of individuals. We show that instances of higher conspecific contamination (~ 50%) can be detected through an increased level of heterozygosity that falls outside the distribution of uncontaminated samples.

Comparative genomics approach to evolutionary process connectivity

The influence of species life history traits and historical demography on contemporary connectivity is still poorly understood. However, these factors partly determine the evolutionary responses of species to anthropogenic landscape alterations. Genetic connectivity and its evolutionary outcomes depend on a variety of spatially dependent evolutionary processes, such as population structure, local adaptation, genetic admixture, and speciation. Over the last years, population genomic studies have been interrogating these processes with increasing resolution, revealing a large diversity of species responses to spatially structured landscapes. In parallel, multispecies meta-analyses usually based on low-genome coverage data have provided fundamental insights into the ecological determinants of genetic connectivity, such as the influence of key life history traits on population structure. However, comparative studies still lack a thorough integration of macro- and micro-evolutionary scales to fully realize their potential. Here, I present how a comparative genomics framework may provide a deeper understanding of evolutionary process connectivity. This framework relies on coupling the inference of long-term demographic and selective history with an assessment of the contemporary consequences of genetic connectivity. Standardizing this approach across several species occupying the same landscape should help understand how spatial environmental heterogeneity has shaped the diversity of historical and contemporary connectivity patterns in different taxa with contrasted life history traits. I will argue that a reasonable amount of genome sequence data can be sufficient to resolve and connect complex macro- and micro-evolutionary histories. Ultimately, implementing this framework in varied taxonomic groups is expected to improve scientific guidelines for conservation and management policies.

Landscape genetics of wolverines (Gulo gulo): scale-dependent effects of bioclimatic, topographic, and anthropogenic variables

Climate change can have particularly severe consequences for high-elevation species that are well-adapted to long-lasting snow conditions within their habitats. One such species is the wolverine, Gulo gulo, with several studies showing a strong, year-round association of the species with the area defined by persistent spring snow cover. This bioclimatic niche also predicts successful dispersal paths for wolverines in the contiguous United States, where the species shows low levels of genetic exchange and low effective population size. Here, we assess the influence of additional climatic, vegetative, topographic, and anthropogenic, variables on wolverine genetic structure in this region using a multivariate, multiscale, landscape genetic approach. This approach allows us to detect landscape-genetic relationships both due to typical, small-scale genetic exchange within habitat, as well as exceptional, long-distance dispersal among habitats. Results suggest that a combination of snow depth, terrain ruggedness, and housing density, best predict gene flow in wolverines, and that the relative importance of variables is scale-dependent. Environmental variables (i.e., isolation-by-resistance, IBR) were responsible for 79% of the explained variation at small scales (i.e., up to ~230 km), and 65% at broad scales (i.e., beyond ~420 km). In contrast, a null model based on only space (i.e., isolation-by-distance, IBD) accounted only for 17% and 11% of the variation at small and broad scales, respectively. Snow depth was the most important variable for predicting genetic structures overall, and at small scales, where it contributed 43% to the variance explained. At broad spatial scales, housing density and terrain ruggedness were most important with contributions to explained variation of 55% and 25%, respectively. While the small-scale analysis most likely captures gene flow within typical wolverine habitat complexes, the broad-scale analysis reflects long-distance dispersal across areas not typically inhabited by wolverines. These findings help to refine our understanding of the processes shaping wolverine genetic structure, which is important for maintaining and improving functional connectivity among remaining wolverine populations.

Dispersal and genetic structure in a tropical small mammal, the Bornean tree shrew (Tupaia longipes), in a fragmented landscape along the Kinabatangan River, Sabah, Malaysia

Background

Constraints in migratory capabilities, such as the disruption of gene flow and genetic connectivity caused by habitat fragmentation, are known to affect genetic diversity and the long-term persistence of populations. Although negative population trends due to ongoing forest loss are widespread, the consequence of habitat fragmentation on genetic diversity, gene flow and genetic structure has rarely been investigated in Bornean small mammals. To fill this gap in knowledge, we used nuclear and mitochondrial DNA markers to assess genetic diversity, gene flow and the genetic structure in the Bornean tree shrew, Tupaia longipes, that inhabits forest fragments of the Lower Kinabatangan Wildlife Sanctuary, Sabah. Furthermore, we used these markers to assess dispersal regimes in male and female T. longipes.

Results

In addition to the Kinabatangan River, a known barrier for dispersal in tree shrews, the heterogeneous landscape along the riverbanks affected the genetic structure in this species. Specifically, while in larger connected forest fragments along the northern riverbank genetic connectivity was relatively undisturbed, patterns of genetic differentiation and the distribution of mitochondrial haplotypes in a local scale indicated reduced migration on the strongly fragmented southern riverside. Especially, oil palm plantations seem to negatively affect dispersal in T. longipes. Clear sex-biased dispersal was not detected based on relatedness, assignment tests, and haplotype diversity.

Conclusion

This study revealed the importance of landscape connectivity to maintain migration and gene flow between fragmented populations, and to ensure the long-term persistence of species in anthropogenically disturbed landscapes.

Spatio-temporal genetic tagging of a cosmopolitan planktivorous shark provides insight to gene flow, temporal variation and site-specific re-encounters

Migratory movements in response to seasonal resources often influence population structure and dynamics. Yet in mobile marine predators, population genetic consequences of such repetitious behaviour remain inaccessible without comprehensive sampling strategies. Temporal genetic sampling of seasonally recurring aggregations of planktivorous basking sharks, Cetorhinus maximus, in the Northeast Atlantic (NEA) affords an opportunity to resolve individual re-encounters at key sites with population connectivity and patterns of relatedness. Genetic tagging (19 microsatellites) revealed 18% of re-sampled individuals in the NEA demonstrated inter/multi-annual site-specific re-encounters. High genetic connectivity and migration between aggregation sites indicate the Irish Sea as an important movement corridor, with a contemporary effective population estimate (Ne) of 382 (CI = 241-830). We contrast the prevailing view of high gene flow across oceanic regions with evidence of population structure within the NEA, with early-season sharks off southwest Ireland possibly representing genetically distinct migrants. Finally, we found basking sharks surfacing together in the NEA are on average more related than expected by chance, suggesting a genetic consequence of, or a potential mechanism maintaining, site-specific re-encounters. Long-term temporal genetic monitoring is paramount in determining future viability of cosmopolitan marine species, identifying genetic units for conservation management, and for understanding aggregation structure and dynamics.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

A population genetic study of feral cats on Christmas Island

Feral and stray cats are a major threat for endemic species on Christmas Island and have been contributing to their decline. Cats were introduced to Christmas Island in 1888 and are now distributed across the whole island. We analysed the genetic population structure and diversity of feral and stray cats on Christmas Island to evaluate connectivity across the island and the possibility of discernible populations that could be targeted separately. Results indicate no differentiated population structure across the island, with cats facing no habitat obstacles to reduce their dispersal abilities across the island. We found high kin structure, suggesting individuals breeding successfully on the whole island. With the management of domestic and feral/stray cats since 2010, removal efforts targeting the whole island have successfully reduced the effective population size of feral/stray cats in the last five years. We suggest the use of various management techniques to facilitate future removal efforts, especially in areas on the island that are difficult to access.

Temporal variation in spatial genetic structure during population outbreaks: Distinguishing among different potential drivers of spatial synchrony

Spatial synchrony is a common characteristic of spatio-temporal population dynamics across many taxa. While it is known that both dispersal and spatially autocorrelated environmental variation (i.e., the Moran effect) can synchronize populations, the relative contributions of each, and how they interact, are generally unknown. Distinguishing these mechanisms and their effects on synchrony can help us to better understand spatial population dynamics, design conservation and management strategies, and predict climate change impacts. Population genetic data can be used to tease apart these two processes as the spatio-temporal genetic patterns they create are expected to be different. A challenge, however, is that genetic data are often collected at a single point in time, which may introduce context-specific bias. Spatio-temporal sampling strategies can be used to reduce bias and to improve our characterization of the drivers of spatial synchrony. Using spatio-temporal analyses of genotypic data, our objective was to identify the relative support for these two mechanisms to the spatial synchrony in population dynamics of the irruptive forest insect pest, the spruce budworm (Choristoneura fumiferana), in Quebec (Canada). AMOVA, cluster analysis, isolation by distance, and sPCA were used to characterize spatio-temporal genomic variation using 1,370 SBW larvae sampled over four years (2012-2015) and genotyped at 3,562 SNP loci. We found evidence of overall weak spatial genetic structure that decreased from 2012 to 2015 and a genetic diversity homogenization among the sites. We also found genetic evidence of a long-distance dispersal event over >140 km. These results indicate that dispersal is the key mechanism involved in driving population synchrony of the outbreak. Early intervention management strategies that aim to control source populations have the potential to be effective through limiting dispersal. However, the timing of such interventions relative to outbreak progression is likely to influence their probability of success.

Sex-biased dispersal patterns of a social passerine: complementary approaches and evidence for a role of spatial scale

Animal dispersal patterns have important implications for many biological processes, but the measurement of dispersal is challenging and often requires the use of complementary approaches. In this study, we investigated the local-scale sex-biased dispersal pattern in a social bird, the black-throated tit (Aegithalos concinnus), in central China. Spatial genetic autocorrelation analyses suggested that significant fine-scale genetic structure existed in males but not in females. Mark–recapture analyses of ringed individuals also showed that female offspring were more dispersive than male offspring, supporting genetic evidence of local female-biased dispersal. These results were contrary to a previous finding of male-biased long-distance dispersal in this species that was based on analyses of gene flow across the species range in China. This implies that the species might potentially have a scale-dependent dispersal strategy, with females frequently dispersing further than males at the local level, but with a proportion of males occasionally dispersing over long distances and contributing more to gene flow at a larger geographical scale. Long-distance dispersal by male black-throated tits might be induced by competition for resources or by unfavourable environmental conditions, warranting further investigation, but our findings increase the evidence that geographical scale is an important factor to be considered when investigating animal dispersal patterns.

The spatial scale of dispersal revealed by admixture tracts

Evaluating species dispersal across the landscape is essential to design appropriate management and conservation actions. However, technical difficulties often preclude direct measures of individual movement, while indirect genetic approaches rely on assumptions that sometimes limit their application. Here, we show that the temporal decay of admixture tracts lengths can be used to assess genetic connectivity within a population introgressed by foreign haplotypes. We present a proof-of-concept approach based on local ancestry inference in a high gene flow marine fish species, the European sea bass (Dicentrarchus labrax). Genetic admixture in the contact zone between Atlantic and Mediterranean sea bass lineages allows the introgression of Atlantic haplotype tracts within the Mediterranean Sea. Once introgressed, blocks of foreign ancestry are progressively eroded by recombination as they diffuse from the western to the eastern Mediterranean basin, providing a means to estimate dispersal. By comparing the length distributions of Atlantic tracts between two Mediterranean populations located at different distances from the contact zone, we estimated the average per-generation dispersal distance within the Mediterranean lineage to less than 50 km. Using simulations, we showed that this approach is robust to a range of demographic histories and sample sizes. Our results thus support that the length of admixture tracts can be used together with a recombination clock to estimate genetic connectivity in species for which the neutral migration-drift balance is not informative or simply does not exist.

Multiscale spatial genetic structure within and between populations of wild cherry trees in nuclear genotypes and chloroplast haplotypes

Spatial genetic structure (SGS) of plants mainly depends on the effective population size and gene dispersal. Maternally inherited loci are expected to have higher genetic differentiation between populations and more intensive SGS within populations than biparentally inherited loci because of smaller effective population sizes and fewer opportunities of gene dispersal in the maternally inherited loci. We investigated biparentally inherited nuclear genotypes and maternally inherited chloroplast haplotypes of microsatellites in 17 tree populations of three wild cherry species under different conditions of tree distribution and seed dispersal. As expected, interpopulation genetic differentiation was 6-9 times higher in chloroplast haplotypes than in nuclear genotypes. This difference indicated that pollen flow 4-7 times exceeded seed flow between populations. However, no difference between nuclear and chloroplast loci was detected in within-population SGS intensity due to their substantial variation among the populations. The SGS intensity tended to increase as trees became more aggregated, suggesting that tree aggregation biased pollen and seed dispersal distances toward shorter. The loss of effective seed dispersers, Asian black bears, did not affect the SGS intensity probably because of mitigation of the bear loss by other vertebrate dispersers and too few tree generations after the bear loss to alter SGS. The findings suggest that SGS is more variable in smaller spatial scales due to various ecological factors in local populations.

The total dispersal kernel: a review and future directions

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel.