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

Wolverines on the Move: A Multi-Scale Analysis of Forest and Landscape Factors Influencing Wolverine Occurrence in Finland

Species distributions in forest-dominated landscapes are closely tied to vegetation structure and heterogeneity, which can vary across spatial scales. As Fennoscandian wolverines recolonize their historical range in boreal forests, specific structural features linked to better resources, such as prey availability, cover, and suitable denning habitats, may promote occupancy in these areas. We studied wolverine (Gulo gulo) occurrence in mainland Finland between 2009-2010 and 2018-2022. We conducted a multi-scale analysis using wildlife and field triangle data and Multi-Source National Forest Inventory (MS-NFI) remote sensing products. We applied generalized linear mixed models (GLMMs) to assess the influence of forest and landscape variables on the probability of occurrence at two spatial scales: local (3.13 km radius) and landscape (20 km radius). Occupied and unoccupied sites were distinguished by landscape fragmentation, tree volume, tree species composition, and distance to clearcuts. Sites were more likely to become occupied when forests were less fragmented and had broadleaved trees, while the probability of occurrence decreased if the total volume of trees was high or fresh clearcuts were in close proximity. Landscape scale seems to be more relevant than local scale when studying the overall forest structure's impact on wolverine occurrence. Our findings provide new insights into the occurrence of wolverines in Finnish boreal forests and could be used to aid species conservation and forest management planning.

What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA

Modelling population connectivity is central to biodiversity conservation and often relies on resistance surfaces reflecting multi-generational gene flow. ResistanceGA (RGA) is a common optimization framework for parameterizing these surfaces by maximizing the fit between genetic distances and cost distances using maximum likelihood population effect models. As the reliability of this framework has rarely been studied, we investigated the conditions maximizing its accuracy for both prediction and interpretation of landscape features' permeability. We ran demo-genetic simulations in contrasted landscapes for species with distinct dispersal capacities and specialization levels, using corresponding reference cost scenarios. We then optimized resistance surfaces from the simulated genetic distances using RGA. First, we evaluated whether RGA identified the drivers of the genetic patterns, that is, distinguished Isolation-by-Resistance (IBR) patterns from either Isolation-by-Distance or patterns unrelated to ecological distances. We then assessed RGA predictive performance using a cross-validation method, and its ability to recover the reference cost scenarios shaping genetic structure in simulations. IBR patterns were well detected and genetic distances were predicted with great accuracy. This performance depended on the strength of the genetic structuring, sampling design and landscape structure. Matching the scale of the genetic pattern by focusing on population pairs connected through gene flow and limiting overfitting through cross-validation further enhanced inference reliability. Yet, the optimized cost values often departed from the reference values, making their interpretation and extrapolation potentially dubious. While demonstrating the value of RGA for predictive modelling, we call for caution and provide additional guidance for its optimal use.

Genetic connectivity of wolverines in western North America

Wolverine distribution contracted along the southern periphery of its range in North America during the 19th and 20th centuries due primarily to human influences. This history, along with low densities, sensitivity to climate change, and concerns about connectivity among fragmented habitats spurred the recent US federal listing of threatened status and special concern status in Canada. To help inform large scale landscape connectivity, we collected 882 genetic samples genotyped at 19 microsatellite loci. We employed multiple statistical models to assess the landscape factors (terrain complexity, human disturbance, forest configuration, and climate) associated with wolverine genetic connectivity across 2.2 million km2 of southwestern Canada and the northwestern contiguous United States. Genetic similarity (positive spatial autocorrelation) of wolverines was detected up to 555 km and a high-to-low gradient of genetic diversity occurred from north-to-south. Landscape genetics analyses confirmed that wolverine genetic connectivity has been negatively influenced by human disturbance at broad scales and positively influenced by forest cover and snow persistence at fine- and broad-scales, respectively. This information applied across large landscapes can be used to guide management actions with the goal of maintaining or restoring population connectivity.

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.

Terrain Ruggedness and Canopy Height Predict Short-Range Dispersal in the Critically Endangered Black-and-White Ruffed Lemur

Dispersal is a fundamental aspect of primates' lives and influences both population and community structuring, as well as species evolution. Primates disperse within an environmental context, where both local and intervening environmental factors affect all phases of dispersal. To date, research has primarily focused on how the intervening landscape influences primate dispersal, with few assessing the effects of local habitat characteristics. Here, we use a landscape genetics approach to examine between- and within-site environmental drivers of short-range black-and-white ruffed lemur (Varecia variegata) dispersal in the Ranomafana region of southeastern Madagascar. We identified the most influential drivers of short-range ruffed lemur dispersal as being between-site terrain ruggedness and canopy height, more so than any within-site habitat characteristic evaluated. Our results suggest that ruffed lemurs disperse through the least rugged terrain that enables them to remain within their preferred tall-canopied forest habitat. Furthermore, we noted a scale-dependent environmental effect when comparing our results to earlier landscape characteristics identified as driving long-range ruffed lemur dispersal. We found that forest structure drives short-range dispersal events, whereas forest presence facilitates long-range dispersal and multigenerational gene flow. Together, our findings highlight the importance of retaining high-quality forests and forest continuity to facilitate dispersal and maintain functional connectivity in ruffed lemurs.

Chromosomal-level reference genome assembly of the North American wolverine (Gulo gulo luscus): a resource for conservation genomics

We report a chromosomal-level genome assembly of a male North American wolverine (Gulo gulo luscus) from the Kugluktuk region of Nunavut, Canada. The genome was assembled directly from long-reads, comprising: 758 contigs with a contig N50 of 36.6 Mb; contig L50 of 20; base count of 2.39 Gb; and a near complete representation (99.98%) of the BUSCO 5.2.2 set of 9,226 genes. A presumptive chromosomal-level assembly was generated by scaffolding against two chromosomal-level Mustelidae reference genomes, the ermine and the Eurasian river otter, to derive a final scaffold N50 of 144.0 Mb and a scaffold L50 of 7. We annotated a comprehensive set of genes that have been associated with models of aggressive behavior, a trait which the wolverine is purported to have in the popular literature. To support an integrated, genomics-based wildlife management strategy at a time of environmental disruption from climate change, we annotated the principal genes of the innate immune system to provide a resource to study the wolverine's susceptibility to new infectious and parasitic diseases. As a resource, we annotated genes involved in the modality of infection by the coronaviruses, an important class of viral pathogens of growing concern as shown by the recent spillover infections by severe acute respiratory syndrome coronavirus-2 to naïve wildlife. Tabulation of heterozygous single nucleotide variants in our specimen revealed a heterozygosity level of 0.065%, indicating a relatively diverse genetic pool that would serve as a baseline for the genomics-based conservation of the wolverine, a rare cold-adapted carnivore now under threat.

Phylogenomic systematics of the spotted skunks (Carnivora, Mephitidae, Spilogale): Additional species diversity and Pleistocene climate change as a major driver of diversification

Four species of spotted skunks (Carnivora, Mephitidae, Spilogale) are currently recognized: Spilogale angustifrons, S. gracilis, S. putorius, and S. pygmaea. Understanding species boundaries within this group is critical for effective conservation given that regional populations or subspecies (e.g., S. p. interrupta) have experienced significant population declines. Further, there may be currently unrecognized diversity within this genus as some taxa (e.g., S. angustifrons) and geographic regions (e.g., Central America) never have been assessed using DNA sequence data. We analyzed species limits and diversification patterns in spotted skunks using multilocus nuclear (ultraconserved elements) and mitochondrial (whole mitogenomes and single gene analysis) data sets from broad geographic sampling representing all currently recognized species and subspecies. We found a high degree of genetic divergence among Spilogale that reflects seven distinct species and eight unique mitochondrial lineages. Initial divergence between S. pygmaea and all other Spilogale occurred in the Early Pliocene (∼ 5.0 million years ago). Subsequent diversification of the remaining Spilogale into an "eastern" and a "western" lineage occurred during the Early Pleistocene (∼1.5 million years ago). These two lineages experienced temporally coincident patterns of diversification at ∼0.66 and ∼0.35 million years ago into two and ultimately three distinct evolutionary units, respectively. Diversification was confined almost entirely within the Pleistocene during a timeframe characterized by alternating glacial-interglacial cycles, with the origin of this diversity occurring in northeastern Mexico and the southwestern United States of America. Mitochondrial-nuclear discordance was recovered across three lineages in geographic regions consistent with secondary contact, including a distinct mitochondrial lineage confined to the Sonoran Desert. Our results have direct consequences for conservation of threatened populations, or species, as well as for our understanding of the evolution of delayed implantation in this enigmatic group of small carnivores.

Do all roads lead to resistance? State road density is the main impediment to gene flow in a flagship species inhabiting a severely fragmented anthropogenic landscape

AIM

Connectivity conservation is ideally based on empirical information on how landscape heterogeneity influences species-specific movement and gene flow. Here, we present the first large-scale evaluation of landscape impacts on genetic connectivity in the European wildcat (Felis silvestris), a flagship and umbrella species for connectivity conservation across Europe.

LOCATION

The study was carried out in the core area of the distributional range of wildcats in Germany, covering about 186,000 km2 of a densely populated and highly fragmented landscape.

METHODS

We used data of 975 wildcats genotyped at 14 microsatellites and an individual-based landscape genetic framework to assess the importance of twelve landscape variables for explaining observed genetic connectivity. For this, we optimized landscape resistance surfaces for all variables and compared their relative impacts using multiple regression on distance matrices and commonality analysis.

RESULTS

Genetic connectivity was best explained by a synergistic combination of six landscape variables and isolation by distance. Of these variables, road density had by far the strongest individual impact followed by synergistic effects of agricultural lands and settlements. Subsequent analyses involving different road types revealed that the strong effect of road density was largely due to state roads, while highways and federal roads had a much smaller, and county roads only a negligible impact.

MAIN CONCLUSIONS

Our results highlight that landscape-wide genetic connectivity in wildcats across Germany is strongly shaped by the density of roads and in particular state roads, with higher densities providing larger resistance to successful dispersal. These findings have important implications for conservation planning, as measures to mitigate fragmentation effects of roads (e.g., over- or underpasses) often focus on large, federally managed transportation infrastructures. While these major roads exert local barrier effects, other road types can be more influential on overall connectivity, as they are more abundant and more widespread across the landscape.