Evaluating potential sources of invasive wild pigs in Ontario.

Invasive wild pigs (Sus scrofa) are considered one of the most damaging species globally, and once they become established in an area, they are notoriously difficult to eliminate. As such, identifying the potential pathways of invasion, especially in places with emerging populations, is critical for preventing new or continued invasion. Wild pigs have been reported in Ontario, Canada, in recent years. We tested four nonexclusive hypotheses about the source of wild pigs in Ontario: (a) escapees from captive sources within Ontario; (b) invasion from neighboring jurisdictions; (c) existing wild populations within Ontario; and (d) translocation and illegal release. We found that sightings of Eurasian wild boar were closer to premises with wild boar than were random locations; wild boar sightings were an average of 16.3 km (SD = 25.4 km, min = 0.2 km, n = 20) from premises with wild boar. We also found that sightings of domestic pigs were closer to domestic pig farms than expected. Sightings of wild pigs in groups of more than four animals were rare. Our results suggest that wild pigs observed in Ontario are recent escapes from captivity, recognizing that there may be established groups of wild pigs that we have not yet detected. While not common, we also received reports indicating that in the past, wild pigs have been translocated and illegally released. Other North American jurisdictions that have been successful at eliminating wild pigs have removed existing populations and changed regulations to limit future invasion, such as prohibiting possession and transport of wild boar and prohibiting hunting of wild pigs.

Predicting high-risk areas for African swine fever spread at the wild-domestic pig interface in Ontario.

The probability of disease transmission among livestock premises via spillover from wildlife vectors depends on interacting ecological, demographic, and behavioural variables. Wild pigs (Sus scrofa) act as vectors and reservoirs of many diseases, including African Swine Fever (ASF), a highly lethal and contagious viral disease that affects both wild and domestic swine. Wild pigs play a significant role in the spread of ASF in geographic locations where the disease is present. Planning and preparedness will ensure that swift action can be taken to control ASF if it is introduced into North America. We used a network to predict the highest risk areas for ASF spread in Ontario, Canada given the distribution of wild pig sightings and other risk factors for wild pig presence and movement on the landscape. We used network nodes to represent the presence of domestic pig farms in a defined area, and we weighted network edges by the probability of ASF virus movement between nodes via movement of wild pigs. Our network models predicted that central Ontario has relatively high network closeness, suggesting that this area has a relatively high risk of virus exposure. These highly connected areas tended to also have the highest domestic pig farm density within a node. Central and eastern Ontario had the highest predicted network betweenness, suggesting that these areas are important for controlling virus flow across the province. We detected 10 communities or clusters within the overall network, where nodes were highly connected locally and relatively less connected to the rest of the network. Predicting areas with a high risk of exposure to the ASF virus due to wild pig movement in Ontario will guide managers on where to focus surveillance for ASF in the wild pig population and where to heighten biosecurity within commercial and backyard pig farms, ensuring that managers are prepared to act quickly to limit spread of ASF if the virus is introduced.

Divergent estimates of herd-wide caribou calf survival: Ecological factors and methodological biases.

Population monitoring is a critical part of effective wildlife management, but methods are prone to biases that can hinder our ability to accurately track changes in populations through time. Calf survival plays an important role in ungulate population dynamics and can be monitored using telemetry and herd composition surveys. These methods, however, are susceptible to unrepresentative sampling and violations of the assumption of equal detectability, respectively. Here, we capitalized on 55 herd-wide estimates of woodland caribou (Rangifer tarandus caribou) calf survival in Newfoundland, Canada, using telemetry (n = 1,175 calves) and 249 herd-wide estimates of calf:cow ratios (C:C) using herd composition surveys to investigate these potential biases. These data included 17 herd-wide estimates replicated from both methods concurrently (n = 448 calves and n = 17 surveys) which we used to understand which processes and sampling biases contributed to disagreement between estimates of herd-wide calf survival. We used Cox proportional hazards models to determine whether estimates of calf mortality risk were biased by the date a calf was collared. We also used linear mixed-effects models to determine whether estimates of C:C ratios were biased by survey date and herd size. We found that calves collared later in the calving season had a higher mortality risk and that C:C tended to be higher for surveys conducted later in the autumn. When we used these relationships to modify estimates of herd-wide calf survival derived from telemetry and herd composition surveys concurrently, we found that formerly disparate estimates of woodland caribou calf survival now overlapped (within a 95% confidence interval) in a majority of cases. Our case study highlights the potential of under-appreciated biases to impact our understanding of population dynamics and suggests ways that managers can limit the influence of these biases in the two widely applied methods for estimating herd-wide survival.

Space use and social association in a gregarious ungulate: Testing the conspecific attraction and resource dispersion hypotheses.

Animals use a variety of proximate cues to assess habitat quality when resources vary spatiotemporally. Two nonmutually exclusive strategies to assess habitat quality involve either direct assessment of landscape features or observation of social cues from conspecifics as a form of information transfer about forage resources. The conspecific attraction hypothesis proposes that individual space use is dependent on the distribution of conspecifics rather than the location of resource patches, whereas the resource dispersion hypothesis proposes that individual space use and social association are driven by the abundance and distribution of resources. We tested the conspecific attraction and the resource dispersion hypotheses as two nonmutually exclusive hypotheses explaining social association and of adult female caribou (Rangifer tarandus). We used location data from GPS collars to estimate interannual site fidelity and networks representing home range overlap and social associations among individual caribou. We found that home range overlap and social associations were correlated with resource distribution in summer and conspecific attraction in winter. In summer, when resources were distributed relatively homogeneously, interannual site fidelity was high and home range overlap and social associations were low. Conversely, in winter when resources were distributed relatively heterogeneously, interannual site fidelity was low and home range overlap and social associations were high. As access to resources changes across seasons, caribou appear to alter social behavior and space use. In summer, caribou may use cues associated with the distribution of forage, and in winter caribou may use cues from conspecifics to access forage. Our results have broad implications for our understanding of caribou socioecology, suggesting that caribou use season-specific strategies to locate forage. Caribou populations continue to decline globally, and our finding that conspecific attraction is likely related to access to forage suggests that further fragmentation of caribou habitat could limit social association among caribou, particularly in winter when access to resources may be limited.

Emerging threat of the 21st century lightscape to global biodiversity.

Over the last century the temporal and spatial distribution of light on Earth has been drastically altered by human activity. Despite mounting evidence of detrimental effects of light pollution on organisms and their trophic interactions, the extent to which light pollution threatens biodiversity on a global scale remains unclear. We assessed the spatial extent and magnitude of light encroachment by measuring change in the extent of light using satellite imagery from 1992 to 2012 relative to species richness for terrestrial and freshwater mammals, birds, reptiles, and amphibians. The encroachment of light into previously dark areas was consistently high, often doubling, in areas of high species richness for all four groups. This pattern persisted for nocturnal groups (e.g., bats, owls, and geckos) and species considered vulnerable to extinction. Areas with high species richness and large increases in light extent were clustered within newly industrialized regions where expansion of light is likely to continue unabated unless we act to conserve remaining darkness. Implementing change at a global scale requires global public, and therefore scientific, support. Here, we offer substantial evidence that light extent is increasing where biodiversity is high, representing an emerging threat to global biodiversity requiring immediate attention.

Selection and drift influence genetic differentiation of insular Canada lynx (Lynx canadensis) on Newfoundland and Cape Breton Island.

Island populations have long been important for understanding the dynamics and mechanisms of evolution in natural systems. While genetic drift is often strong on islands due to founder events and population bottlenecks, the strength of selection can also be strong enough to counteract the effects of drift. Here, we used several analyses to identify the roles of genetic drift and selection on genetic differentiation and diversity of Canada lynx (Lynx canadensis) across eastern Canada, including the islands of Cape Breton and Newfoundland. Specifically, we assessed whether we could identify a genetic component to the observed morphological differentiation that has been reported across insular and mainland lynx. We used a dinucleotide repeat within the promoter region of a functional gene that has been linked to mammalian body size, insulin-like growth factor-1 (IGF-1). We found high genetic differentiation at neutral molecular markers but convergence of allele frequencies at the IGF-1 locus. Thus, we showed that while genetic drift has influenced the observed genetic structure of lynx at neutral molecular markers, natural selection has also played a role in the observed patterns of genetic diversity at the IGF-1 locus of insular lynx.

Does landscape connectivity shape local and global social network structure in white-tailed deer?

Intraspecific social behavior can be influenced by both intrinsic and extrinsic factors. While much research has focused on how characteristics of individuals influence their roles in social networks, we were interested in the role that landscape structure plays in animal sociality at both individual (local) and population (global) levels. We used female white-tailed deer (Odocoileus virginianus) in Illinois, USA, to investigate the potential effect of landscape on social network structure by weighting the edges of seasonal social networks with association rate (based on proximity inferred from GPS collar data). At the local level, we found that sociality among female deer in neighboring social groups (n = 36) was mainly explained by their home range overlap, with two exceptions: 1) during fawning in an area of mixed forest and grassland, deer whose home ranges had low forest connectivity were more social than expected; and 2) during the rut in an area of intensive agriculture, deer inhabiting home ranges with high amount and connectedness of agriculture were more social than expected. At the global scale, we found that deer populations (n = 7) in areas with highly connected forest-agriculture edge, a high proportion of agriculture, and a low proportion of forest tended to have higher weighted network closeness, although low sample size precluded statistical significance. This result implies that infectious disease could spread faster in deer populations inhabiting such landscapes. Our work advances the general understanding of animal social networks, demonstrating how landscape features can underlie differences in social behavior both within and among wildlife social networks.

Node-based measures of connectivity in genetic networks.

At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal.

The subtle role of climate change on population genetic structure in Canada lynx.

Anthropogenically driven climatic change is expected to reshape global patterns of species distribution and abundance. Given recent links between genetic variation and environmental patterns, climate change may similarly impact genetic population structure, but we lack information on the spatial and mechanistic underpinnings of genetic-climate associations. Here, we show that current genetic variability of Canada lynx (Lynx canadensis) is strongly correlated with a winter climate gradient (i.e. increasing snow depth and winter precipitation from west-to-east) across the Pacific-North American (PNO) to North Atlantic Oscillation (NAO) climatic systems. This relationship was stronger than isolation by distance and not explained by landscape variables or changes in abundance. Thus, these patterns suggest that individuals restricted dispersal across the climate boundary, likely in the absence of changes in habitat quality. We propose habitat imprinting on snow conditions as one possible explanation for this unusual phenomenon. Coupling historical climate data with future projections, we also found increasingly diverging snow conditions between the two climate systems. Based on genetic simulations using projected climate data (2041-2070), we predicted that this divergence could lead to a threefold increase in genetic differentiation, potentially leading to isolated east-west populations of lynx in North America. Our results imply that subtle genetic structure can be governed by current climate and that substantive genetic differentiation and related ecological divergence may arise from changing climate patterns.

The sensitivity of genetic connectivity measures to unsampled and under-sampled sites.

Landscape genetic analyses assess the influence of landscape structure on genetic differentiation. It is rarely possible to collect genetic samples from all individuals on the landscape and thus it is important to assess the sensitivity of landscape genetic analyses to the effects of unsampled and under-sampled sites. Network-based measures of genetic distance, such as conditional genetic distance (cGD), might be particularly sensitive to sampling intensity because pairwise estimates are relative to the entire network. We addressed this question by subsampling microsatellite data from two empirical datasets. We found that pairwise estimates of cGD were sensitive to both unsampled and under-sampled sites, and F(ST), D(est), and d(eucl) were more sensitive to under-sampled than unsampled sites. We found that the rank order of cGD was also sensitive to unsampled and under-sampled sites, but not enough to affect the outcome of Mantel tests for isolation by distance. We simulated isolation by resistance and found that although cGD estimates were sensitive to unsampled sites, by increasing the number of sites sampled the accuracy of conclusions drawn from landscape genetic analyses increased, a feature that is not possible with pairwise estimates of genetic differentiation such as F(ST), D(est), and d(eucl). We suggest that users of cGD assess the sensitivity of this measure by subsampling within their own network and use caution when making extrapolations beyond their sampled network.

The effect of cost surface parameterization on landscape resistance estimates.

A cost or resistance surface is a representation of a landscape's permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization.

The effect of map boundary on estimates of landscape resistance to animal movement.

BACKGROUND: Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat. METHODOLOGY/PRINCIPAL FINDINGS: We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance. CONCLUSIONS/SIGNIFICANCE: Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies.

'Futile cycle' enzymes in the flight muscles of North American bumblebees.

In the flight muscles of European bumblebees, high activities of fructose-1,6-bisphosphatase (FbPase) relative to phosphofructokinase (PFK) have suggested a thermogenic 'futile cycle' important for regional endothermy. We find generally low activities of FbPase (0.7-19.7 units g(-1) thorax) in North American Bombus species, with the exception of Bombus rufocinctus, where activity (43.1 units g(-1) thorax) is comparable with that of European congeners. These data, taken with estimates of maximal rates of heat production by cycling, do not support a significant thermogenic role for the PFK/FbPase cycle. In agreement with earlier studies, both PFK and FbPase activities were found to scale allometrically with body size (allometric exponents -0.18 and -1.33, respectively). The cycle may serve to supplement thermogenesis or amplify glycolytic flux in rest-to-flight transitions, especially in smaller bees.