Conservation macrogenetics: harnessing genetic data to meet conservation commitments.

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

Landscape Heterogeneity Explains the Genetic Differentiation of a Forest Bird across the Sino-Himalayan Mountains.

Mountains are the world's most important centers of biodiversity. The Sino-Himalayan Mountains are global biodiversity hotspot due to their extremely high species richness and endemicity. Ample research investigated the impact of the Qinghai-Tibet Plateau uplift and Quaternary glaciations in driving species diversification in plants and animals across the Sino-Himalayan Mountains. However, little is known about the role of landscape heterogeneity and other environmental features in driving diversification in this region. We utilized whole genomes and phenotypic data in combination with landscape genetic approaches to investigate population structure, demography, and genetic diversity in a forest songbird species native to the Sino-Himalayan Mountains, the red-billed leiothrix (Leiothrix lutea). We identified 5 phylogeographic clades, including 1 in the East of China, 1 in Yunnan, and 3 in Tibet, roughly consistent with differences in song and plumage coloration but incongruent with traditional subspecies boundaries. Isolation-by-resistance model best explained population differentiation within L. lutea, with extensive secondary contact after allopatric isolation leading to admixture among clades. Ecological niche modeling indicated relative stability in the extent of suitable distribution areas of the species across Quaternary glacial cycles. Our results underscore the importance of mountains in the diversification of this species, given that most of the distinct genetic clades are concentrated in a relatively small area in the Sino-Himalayan Mountain region, while a single shallow clade populates vast lower-lying areas to the east. This study highlights the crucial role of landscape heterogeneity in promoting differentiation and provides a deep genomic perspective on the mechanisms through which diversity hotspots form.

Synthesizing environmental, epidemiological and vector and parasite genetic data to assist decision making for disease elimination.

We present a framework for identifying when conditions are favourable for transmission of vector-borne diseases between communities by incorporating predicted disease prevalence mapping with landscape analysis of sociological, environmental and host/parasite genetic data. We explored the relationship between environmental features and gene flow of a filarial parasite of humans, Onchocerca volvulus, and its vector, blackflies in the genus Simulium. We generated a baseline microfilarial prevalence map from point estimates from 47 locations in the ecological transition separating the savannah and forest in Ghana, where transmission of O. volvulus persists despite onchocerciasis control efforts. We generated movement suitability maps based on environmental correlates with mitochondrial population structure of 164 parasites from 15 communities and 93 vectors from only four sampling sites, and compared these to the baseline prevalence map. Parasite genetic distance between sampling locations was significantly associated with elevation (r = .793, p = .005) and soil moisture (r = .507, p = .002), while vector genetic distance was associated with soil moisture (r = .788, p = .0417) and precipitation (r = .835, p = .0417). The correlation between baseline prevalence and parasite resistance surface maps was stronger than that between prevalence and vector resistance surface maps. The centre of the study area had high prevalence and suitability for parasite and vector gene flow, potentially contributing to persistent transmission and suggesting the importance of re-evaluating transmission zone boundaries. With suitably dense sampling, this framework can help delineate transmission zones for onchocerciasis and would be translatable to other vector-borne diseases.

Topographic barriers drive the pronounced genetic subdivision of a range-limited fossorial rodent.

Due to their limited dispersal ability, fossorial species with predominantly belowground activity usually show increased levels of population subdivision across relatively small spatial scales. This may be exacerbated in harsh mountain ecosystems, where landscape geomorphology limits species' dispersal ability and leads to small effective population sizes, making species relatively vulnerable to environmental change. To better understand the environmental drivers of species' population subdivision in remote mountain ecosystems, particularly in understudied high-elevation systems in Africa, we studied the giant root-rat (Tachyoryctes macrocephalus), a fossorial rodent confined to the afro-alpine ecosystem of the Bale Mountains in Ethiopia. Using mitochondrial and low-coverage nuclear genomes, we investigated 77 giant root-rat individuals sampled from nine localities across its entire ~1000 km2 range. Our data revealed a distinct division into a northern and southern group, with no signs of gene flow, and higher nuclear genetic diversity in the south. Landscape genetic analyses of the mitochondrial and nuclear genomes indicated that population subdivision was driven by slope and elevation differences of up to 500 m across escarpments separating the north and south, potentially reinforced by glaciation of the south during the Late Pleistocene (~42,000-16,000 years ago). Despite this landscape-scale subdivision between the north and south, weak geographic structuring of sampling localities within regions indicated gene flow across distances of at least 16 km at the local scale, suggesting high, aboveground mobility for relatively long distances. Our study highlights that despite the potential for local-scale gene flow in fossorial species, topographic barriers can result in pronounced genetic subdivision. These factors can reduce genetic variability, which should be considered when developing conservation strategies.

Effective dispersal patterns in prairie plant species across human-modified landscapes.

Effective dispersal among plant populations is dependent on vector behaviour, landscape features and availability of adequate habitats. To capture landscape feature effects on dispersal, studies must be conducted at scales reflecting single-generation dispersal events (mesoscale). Many studies are conducted at large scales where genetic differentiation is due to dispersal occurring over multiple generations, making it difficult to interpret the effects of specific landscape features on vector behaviour. Genetic structure at the mesoscale may be determined by ecological and evolutionary processes, such as the consequences of vector behaviour on patterns of gene flow. We used chloroplast haplotypes and nuclear genome SNP surveys to identify landscape features influencing seed and pollen dispersal at a mesoscale within the Rogue River Valley in southern Oregon. We evaluated biotic and abiotic vector behaviour by contrasting two annual species with differing dispersal mechanisms; Achyrachaena mollis (Asteraceae) is a self-pollinating and anemochoric species, and Plectritis congesta (Caprifoliaceae) is biotically pollinated with barochoric seeds. Using landscape genetics methods, we identified features of the study region that conduct or restrict dispersal. We found chloroplast haplotypes were indicative of historic patterns of gene flow prior to human modification of landscapes. Seed dispersal of A. mollis was best supported by models of isolation by distance, while seed-driven gene flow of P. congesta was determined by the distribution of preserved natural spaces and quality habitat. Nuclear genetic structure was driven by both pollen and seed dispersal, and both species responded to contemporary landscape changes, such as urban and agricultural conversion, and habitat availability.

Regional diversity and leaf microbiome interactions of the fungal maize pathogen Exserohilum turcicum in Switzerland: A metagenomic analysis.

The spread and adaptation of fungal plant pathogens in agroecosystems are facilitated by environmental homogeneity. Metagenomic sequencing of infected tissues allowed us to monitor eco-evolutionary dynamics and interactions between host, pathogen and plant microbiome. Exserohilum turcicum, the causal agent of northern corn leaf blight (NCLB) in maize, is distributed in multiple clonal lineages throughout Europe. To characterize regional pathogen diversity, we conducted metagenomic DNA sequencing on 241 infected leaf samples from the highly susceptible Swiss maize landrace Rheintaler Ribelmais, collected over 3 years (2016-2018) from an average of 14 agricultural farms within the Swiss Rhine Valley. All major European clonal lineages of E. turcicum were identified. Lineages differ by their mating types which indicates potential for sexual recombination and rapid evolution of new pathogen strains, although we found no evidence of recent recombination. The associated eukaryotic and prokaryotic leaf microbiome exhibited variation in taxonomic diversity between years and locations and is likely influenced by local weather conditions. A network analysis revealed distinct clusters of eukaryotic and prokaryotic taxa that correlates with the frequency of E. turcicum sequencing reads, suggesting causal interactions. Notably, the yeast genus Metschnikowia exhibited a strongly negative association with E. turcicum, supporting its known potential as biological control agent against fungal pathogens. Our findings show that metagenomic sequencing is a useful tool for analysing the role of environmental factors and potential pathogen-microbiome interactions in shaping pathogen dynamics and evolution, suggesting their potential for effective pathogen management strategies.

City divided: Unveiling family ties and genetic structuring of coyotes in Seattle.

Linear barriers pose significant challenges for wildlife gene flow, impacting species persistence, adaptation, and evolution. While numerous studies have examined the effects of linear barriers (e.g., fences and roadways) on partitioning urban and non-urban areas, understanding their influence on gene flow within cities remains limited. Here, we investigated the impact of linear barriers on coyote (Canis latrans) population structure in Seattle, Washington, where major barriers (i.e., interstate highways and bodies of water) divide the city into distinct quadrants. Just under 1000 scats were collected to obtain genetic data between January 2021 and December 2022, allowing us to identify 73 individual coyotes. Notably, private allele analysis underscored limited interbreeding among quadrants. When comparing one quadrant to each other, there were up to 16 private alleles within a single quadrant, representing nearly 22% of the population allelic diversity. Our analysis revealed weak isolation by distance, and despite being a highly mobile species, genetic structuring was apparent between quadrants even with extremely short geographic distance between individual coyotes, implying that Interstate 5 and the Ship Canal act as major barriers. This study uses coyotes as a model species for understanding urban gene flow and its consequences in cities, a crucial component for bolstering conservation of rarer species and developing wildlife friendly cities.

Spatial variation in genomic signatures of local adaptation during the cane toad invasion of Australia.

Adaptive evolution can facilitate species' range expansions across environmentally heterogeneous landscapes. However, serial founder effects can limit the efficacy of selection, and the evolution of increased dispersal during range expansions may result in gene flow swamping local adaptation. Here, we study how genetic drift, gene flow and selection interact during the cane toad's (Rhinella marina) invasion across the heterogeneous landscape of Australia. Following its introduction in 1935, the cane toad colonised eastern Australia and established several stable range edges. The ongoing, more rapid range expansion in north-central Australia has occurred concomitant with an evolved increase in dispersal capacity. Using reduced representation genomic data of Australian cane toads from the expansion front and from two areas of their established range, we test the hypothesis that high gene flow constrains local adaptation at the expansion front relative to established areas. Genetic analyses indicate the three study areas are genetically distinct but show similar levels of allelic richness, heterozygosity and inbreeding. Markedly higher gene flow or recency of colonisation at the expansion front have likely hindered local adaptation at the time of sampling, as indicated by reduced slopes of genetic-environment associations (GEAs) estimated using a novel application of geographically weighted regression that accounts for allele surfing; GEA slopes are significantly steeper in established parts of the range. Our work bolsters evidence supporting adaptation of invasive species post-introduction and adds novel evidence for differing strengths of evolutionary forces among geographic areas with different invasion histories.

Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity.

While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversity. However, even as both disciplines have come to utilize SNP data over the last decades, analytical approaches have remained for the most part focused on either broad-scale inferences of historical processes (phylogeography) or on more localized inferences about environmental and/or landscape features (landscape genetics). Here we demonstrate that an artificial intelligence model-based analytical framework can consider both deeper historical factors and landscape-level processes in an integrated analysis. We implement this framework using data collected from two Brazilian anurans, the Brazilian sibilator frog (Leptodactylus troglodytes) and granular toad (Rhinella granulosa). Our results indicate that historical demographic processes shape most the genetic variation in the sibulator frog, while landscape processes primarily influence variation in the granular toad. The machine learning framework used here allows both historical and landscape processes to be considered equally, rather than requiring researchers to make an a priori decision about which factors are important.

Geographic and seasonal variation of the for gene reveal signatures of local adaptation in Drosophila melanogaster.

In the early 1980s, the observation that Drosophila melanogaster larvae differed in their foraging behaviour laid the foundation for the work that would later lead to the discovery of the foraging gene (for) and its associated foraging phenotypes, rover and sitter. Since then, the molecular characterization of the for gene and our understanding of the mechanisms that maintain its phenotypic variants in the laboratory have progressed enormously. However, the significance and dynamics of such variation are yet to be investigated in nature. With the advent of next-generation sequencing, it is now possible to identify loci underlying the adaptation of populations in response to environmental variation. Here, I present the results of a genotype-environment association analysis that quantifies variation at the for gene among samples of D. melanogaster structured across space and time. These samples consist of published genomes of adult flies collected worldwide, and at least twice per site of collection (during spring and fall). Both an analysis of genetic differentiation based on Fs⁢t values and an analysis of population structure revealed an east-west gradient in allele frequency. This gradient may be the result of spatially varying selection driven by the seasonality of precipitation. These results support the hypothesis that different patterns of gene flow as expected under models of isolation by distance and potentially isolation by environment are driving genetic differentiation among populations. Overall, this study is essential for understanding the mechanisms underlying the evolution of foraging behaviour in D. melanogaster.

Genetic consequences of Last Glacial-Holocene changes in snowfall regime in Arnica mallotopus populations: A plant confined to heavy-snow areas of Japan.

PREMISE: Snow is an important environmental factor affecting plant distribution. Past changes in snowfall regimes may have controlled the demographies of snow-dependent plants. However, our knowledge of changes in the distribution and demographies of such plants is limited because of the lack of fossil records. METHODS: Population genetic and landscape genetic analyses were used to investigate the response of population dynamics of Arnica mallotopus (Asteraceae)-a plant confined to heavy-snow areas of Japan-to changes in snowfall regimes from the Last Glacial Period to the Holocene. RESULTS: The population genetic analysis suggested that the four geographic lineages diverged during the Last Glacial Period. The interaction between reduced snowfall and lower temperatures during this period likely triggered population isolation in separate refugia. Subpopulation differentiation in the northern group was lower than in the southern group. Our ecological niche model predicted that the current distribution was patchy in the southern region; that is, the populations were isolated by topologically flat and climatically unsuitable lowlands. The landscape genetic analysis suggested that areas with little snowfall acted as barriers to the Holocene expansion of species distribution and continued limiting gene flow between local populations. CONCLUSIONS: These findings indicate that postglacial population responses vary among regions and are controlled by environmental and geographic factors. Thus, changes in snowfall regime played a major role in shaping the distribution and genetic structure of the snow-dependent plant.

Landscape and conservation genetics of western black crested gibbons (Nomascus concolor) in China.

Despite decades of field study, very little is known about the molecular ecology of gibbons, particularly as it relates to their ability to disperse across degraded and fragmentary landscapes. The critically endangered western black crested gibbon (Nomascus concolor) has been reduced to a small, fragmented population with about 1300 individuals. In the largest population genetic study of free-ranging gibbons to date, we sampled 47 of these gibbons from 13 sites in China and generated 15 polymorphic autosomal microsatellite markers. We identify three population clusters of N. concolor in Yunnan centered in 1) the Wuliang and Ailao Mountains, 2) the Yongde Daxueshan Mountains, and 3) an isolated remnant near the border with Vietnam. Within the Wuliang Mountains, we identified four subclusters, three of which are bounded by high-altitude rhododendron forest, and one that is isolated from the main population by ~2 km of degraded forest and pasture. Least-cost path analysis and isolation by resistance modeling demonstrates that the population genetic distances among gibbons in Wuliangshan National Nature Reserve are significantly correlated with geographic paths that avoid use of high-altitude rhododendron forest in favor of evergreen broadleaf forest. Although these gibbons have likely undergone reductions in heterozygosity from recent consanguineous mating, we suggest that their active avoidance of inbreeding on the population level maintains higher than expected levels of genetic diversity. This research provides new insights into how gibbons interact with heterogeneous environments and expands our understanding of their molecular ecology and conservation genetics.

Global wind patterns shape genetic differentiation, asymmetric gene flow, and genetic diversity in trees.

Wind disperses the pollen and seeds of many plants, but little is known about whether and how it shapes large-scale landscape genetic patterns. We address this question by a synthesis and reanalysis of genetic data from more than 1,900 populations of 97 tree and shrub species around the world, using a newly developed framework for modeling long-term landscape connectivity by wind currents. We show that wind shapes three independent aspects of landscape genetics in plants with wind pollination or seed dispersal: populations linked by stronger winds are more genetically similar, populations linked by directionally imbalanced winds exhibit asymmetric gene flow ratios, and downwind populations have higher genetic diversity. For each of these distinct hypotheses, partial correlations between the respective wind and genetic metrics (controlling for distance and climate) are positive for a significant majority of wind-dispersed or wind-pollinated genetic data sets and increase significantly across functional groups expected to be increasingly influenced by wind. Together, these results indicate that the geography of both wind strength and wind direction play important roles in shaping large-scale genetic patterns across the world's forests. These findings have implications for various aspects of basic plant ecology and evolution, as well as the response of biodiversity to future global change.

A machine-learning approach to map landscape connectivity in Aedes aegypti with genetic and environmental data.

Mapping landscape connectivity is important for controlling invasive species and disease vectors. Current landscape genetics methods are often constrained by the subjectivity of creating resistance surfaces and the difficulty of working with interacting and correlated environmental variables. To overcome these constraints, we combine the advantages of a machine-learning framework and an iterative optimization process to develop a method for integrating genetic and environmental (e.g., climate, land cover, human infrastructure) data. We validate and demonstrate this method for the Aedes aegypti mosquito, an invasive species and the primary vector of dengue, yellow fever, chikungunya, and Zika. We test two contrasting metrics to approximate genetic distance and find Cavalli-Sforza-Edwards distance (CSE) performs better than linearized FST The correlation (R) between the model's predicted genetic distance and actual distance is 0.83. We produce a map of genetic connectivity for Ae. aegypti's range in North America and discuss which environmental and anthropogenic variables are most important for predicting gene flow, especially in the context of vector control.

Climate lags and genetics determine phenology in quaking aspen (Populus tremuloides).

Spatiotemporal patterns of phenology may be affected by mosaics of environmental and genetic variation. Environmental drivers may have temporally lagged impacts, but patterns and mechanisms remain poorly known. We combine multiple genomic, remotely sensed, and physically modeled datasets to determine the spatiotemporal patterns and drivers of canopy phenology in quaking aspen, a widespread clonal dioecious tree species with diploid and triploid cytotypes. We show that over 391 km2 of southwestern Colorado: greenup date, greendown date, and growing season length vary by weeks and differ across sexes, cytotypes, and genotypes; phenology has high phenotypic plasticity and heritabilities of 31-61% (interquartile range); and snowmelt date, soil moisture, and air temperature predict phenology, at temporal lags of up to 3 yr. Our study shows that lagged environmental effects are needed to explain phenological variation and that the effect of cytotype on phenology is obscured by its correlation with topography. Phenological patterns are consistent with responses to multiyear accumulation of carbon deficit or hydraulic damage.

Population dynamics in newts of the Carpathian Mountains.

Rarity, range restriction, and narrow endemism tend to carry dire and urgent conservation implications for imperilled species. What is also clear is that human-associated extinction risk factors such as urbanization and deforestation pose overwhelming threats to range-restricted species. In this issue of Molecular Ecology, Antunes et al. (2022) demonstrate that these threats can also impact widespread species. By comparing newts in the genus Lissotriton that co-occur in the same geographical region, they expose the distinctness of risks facing species with different habitat preferences. Their study emphasizes the importance of local-scale landscape genetics to reveal the nuances of population connectivity that might otherwise be missed by studying a broader spatial scale.

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.

Landscape genetics reveals contrasting patterns of connectivity in two newt species (Lissotriton montandoni and L. vulgaris).

Ecologically distinct species may respond to landscape changes in different ways. In addition to basic ecological data, the extent of the geographic range has been successfully used as an indicator of species sensitivity to anthropogenic landscapes, with widespread species usually found to be less sensitive compared to range-restricted species. In this study, we investigate connectivity patterns of two closely related but ecologically distinct newt species - the range-restricted, Lissotriton montandoni and the widespread, L. vulgaris - using genomic data, a highly replicated setting (six geographic regions per species), and tools from landscape genetics. Our results show the importance of forest for connectivity in both species, but at the same time suggest differential use of forested habitat, with L. montandoni and L. vulgaris showing the highest connectivity at forest-core and forest-edges, respectively. Anthropogenic landscapes (i.e., higher crop- or urban-cover) increased resistance in both species, but the effect was one to three orders of magnitude stronger in L. montandoni than in L. vulgaris. This result is consistent with a view of L. vulgaris as an ecological generalist. Even so, currently, the negative impact of anthropogenic landscapes is mainly seen in connectivity among L. vulgaris populations, which show significantly stronger isolation and lower effective sizes relative to L. montandoni. Overall, this study emphasizes how habitat destruction is compromising genetic connectivity not only in endemic, range-restricted species of conservation concern but also in widespread generalist species, despite their comparatively lower sensitivity to anthropogenic landscape changes.

Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study.

This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.

How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a microendemic Malagasy tree.

Understanding landscape changes is central to predicting evolutionary trajectories and defining conservation practices. While human-driven deforestation is intense throughout Madagascar, exceptions in areas such as the Loky-Manambato region (north) raise questions regarding the causes and age of forest fragmentation. The Loky-Manambato region also harbours a rich and endemic flora, whose evolutionary origin remains poorly understood. We assessed the genetic diversity of an endangered microendemic Malagasy olive species (Noronhia spinifolia Hong-Wa) to better understand the vegetation dynamics in the Loky-Manambato region and its influence on past evolutionary processes. We characterized 72 individuals sampled across eight forests through nuclear and mitochondrial restriction-associated DNA sequencing data and chloroplast microsatellites. Combined population and landscape genetics analyses indicate that N. spinifolia diversity is largely explained by the current forest cover, highlighting a long-standing habitat mosaic in the region. This sustains a major and long-term role of riparian corridors in maintaining connectivity across these antique mosaic habitats, calling for the study of organismal interactions that promote gene flow.