Biology subjects

Lesage, V.

Publications and source records attributed to Lesage, V..

7 recordsLinked to original sources

bioRxiv2025

Exploring contemporary and historic effective population sizes in Atlantic beluga whale populations

Ongoing global environmental changes will require animals to adapt to new conditions, as their necessary resources for survival may shift or decline. Understanding population dynamics in wildlife informs conservation strategies by providing context for genetic diversity and current population abundances. Here, we use whole genome data to reconstruct past demographic trends and estimate contemporary effective population sizes in the beluga whale (Delphinapterus leucas), an Arctic endemic species with significant cultural importance, that is an integral part of the marine ecosystem along the Canadian coast. In line with previous work, we identified six genetic populations: 1) St. Lawrence Estuary, 2) Eastern High Arctic, 3) James Bay, 4) Cumberland Sound, 5) Hudson Bay-Strait Complex and 6) Little and Great Whale Rivers. Demographic history in the deep (up to 1,000,000 years) past revealed all but the Hudson Bay-Strait Complex population declined in effective population sizes following the last glacial period. Within the last several centuries, the Eastern High Arctic and Hudson Bay-Strait Complex populations have shown evidence for an increase in effective population size and have contemporary estimates greater than 2,000. The other four populations have contemporary estimates below 400. The very low effective population size estimates in Cumberland Sound, Little and Great Whale Rivers and James Bay, as well as the high inbreeding in the St. Lawrence Estuary indicate that these populations are in need of protective measures for long-term sustainability. These results have advanced our understanding of the dynamics of beluga genetics across eastern Canada and provide valuable metrics for conservation strategies.

evolutionary biology↗

bioRxiv2024

A multistate capture-recapture model to estimate reproduction of North Atlantic right whales

The recent steep decline of critically endangered North Atlantic right whales (Eubalaena glacialis) can be attributed to high mortality combined with low reproduction. While the former is a clear result of anthro-pogenic activity, the latter involves more complexity. Evidence suggests that both short-term fluctuations in prey availability and long-term decline in health are responsible for depressed right whale calving rates. To facilitate an assessment of extinction risk, we developed a multistate capture-recapture model that estimated the probability of calving using extensive sightings data from 1990-2019. The model estimated sub-lethal effects of severe injury on calving probability, and modeled temporal variability in calving as related to indices of prey availability (Calanus spp. biomass) and an apparent regime shift. The average annual probability of calving for known-breeding females, given average prey conditions, decreased from 0.217 [0.162, 0.281] to 0.142 [0.067, 0.252] after the 2010 regime shift. The model indicated strong evidence of a relationship between calving probability and the prey index from the eastern Gulf of Maine, though this relationship effectively disappeared after 2010; moderate evidence for a relationship with prey from the southwest Gulf of St. Lawrence remained. Weak evidence of reduced calving probability due to severe injury resulted from low sample sizes, given increased mortality for individuals observed with severe injuries. The regime effect is hypothesized to be capturing a long-term decline in health due to a combination of decreasing habitat quality resulting from climate change and potentially chronic sublethal injuries (e.g., entanglements). Our reproduction model provides demographic parameter estimates that can be used in population projections for North Atlantic right whales, though uncertainty remains in the mechanisms responsible for recent declines in calving.

ecology↗

bioRxiv2023

Dealing with lipid effects and lipid-extraction biases in δ13C and δ15N isotopic studies: a solution based on 28 marine invertebrate, fish and mammal species

Lipids are naturally depleted in 13C isotope in relation to its C sources, causing a bias in {delta}13C in bulk samples that varies with lipid content. Failure to take this issue into account results in inaccurate conclusions in food web and habitat use studies. Two approaches to resolve this issue are 1) to extract lipids from samples prior to measurement, a resource-intensive process that also can alter {delta}15N or 2) estimating a lipid-free {delta}13C using one of several equations that differ in levels of sophistication and generalization across taxa. Here {delta}13C and {delta}15N were measured on bulk and lipid-extracted muscle samples of a dataset of over 2000 specimens of 28 species of marine invertebrates, fishes and mammals. Our objectives were to 1) compare the effect of lipid extraction on {delta}13C and {delta}15N across taxa; 2) compare the performance of five normalization models, overall and on subsets of species; 3) propose a model to revert lipid-extracted {delta}15N back to their bulk values; and 4) identify the most suitable approach for dealing with lipid biases in isotopic ratios. Extraction caused an uneven enrichment in {delta}13C and {delta}15N across species. Model taxonomic specificity increased estimate accuracy in both isotopes. Models from Logan et al. (2008) and McConnaughey and McRoy (1979) performed better than the other models tested. {delta}15Nbulk could be reliably estimated based on {delta}15Nlipid-extracted using a linear model. This study provides a way forward for obtaining reliable {delta}13C and {delta}15N values in muscle tissue without the costs of duplicate analyses and represents a major step toward the harmonization of datasets collected under the two different approaches.

ecology↗

bioRxiv2023

A multistate capture-recapture model to estimate cause-specific injury and mortality of North Atlantic right whales

Understanding the causes of mortality for a declining species is essential for developing effective conservation and management strategies, particularly when anthropogenic activities are the primary threat. Using a competing hazards framework allows for robust estimation of the cause-specific variation that may exist across multiple dimensions, such as time and individual. Here, we estimated cause-specific rates of severe injury and mortality for North Atlantic right whales (Eubalaena glacialis), a critically endangered species that is currently in peril due to human-caused interactions. We developed a multistate capture-recapture model that leveraged 30 years of intensive survey effort yielding sightings of individuals with injury assessments and necropsies of carcass recoveries. We examined variation in the hazard rates of severe injury and mortality due to entanglements in fishing gear and vessel strikes as explained by year and the age and reproductive status of the individual. We found strong evidence for increased rates of severe entanglement injuries after 2013 and for females with calves, with consequently higher marginal mortality. The model results also suggested that despite vessel strikes causing a lower average rate of severe injuries, the higher mortality rate conditional on injury results in significant total mortality risk, particularly for females resting from a recent calving event. Large uncertainty in the estimation of carcass recovery rate for vessel strike deaths permeated into the apportionment of mortality causes. The increased rates of North Atlantic right whale mortality in the last decade, particularly for reproducing females, puts the species at risk of severe decline. By apportioning the human-caused threats using a quantitative approach with estimation of relevant uncertainty, this work can guide development of conservation and management strategies to facilitate species recovery.

ecology↗

bioRxiv2023

Universal baleen whale microsatellite panel for individual identification and power to detect parentage

Highly polymorphic single tandem repeat loci (STR, also known as microsatellite loci) remain a familiar, cost efficient class of markers for genetic analyses in ecology, behavior and conservation. We characterize a new universal set of ten STR loci (from 28 potential candidate loci) in seven baleen whale species, which are optimized for PCR amplification in two multiplex reactions along with a Y chromosome marker for sex determination. The optimized, universal set of STR loci provides an ideal starting point for new studies in baleen whales aimed at individual-based and population genetic studies, and facilitates data sharing among research groups. Data from the new STR loci were combined with genotypes from other published STR loci to assess the power to assign parentage (paternity) using exclusion in four species: fin whales, humpback whales, blue whales and bowhead whales. We argue that parentage studies should present a power analysis to demonstrate that the specific data are sufficiently informative to assign parentage with statistical rigor.

genetics↗

bioRxiv2021

Pose-gait analysis for cetaceans with biologging tags

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations. But how best to characterize gait from tag data remains an open question. Further, the location and orientation of the tag on an animal in the field are variable and can change multiple times during deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined before a wide variety of further analyses. Currently, custom scripts that involve specific manual heuristics methods tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. The authors of this work argue that an animals gait is composed of a sequence of body poses observed by the tag, demonstrating a specific spatial pattern in the data that can be utilized for different purposes. This work presents an automated data processing pipeline (and software) that takes advantage of the common characteristics of pose and gait of the animal to 1) Identify time instances associated with occurrences of relative motion between the tag and animal; 2) Identify the relative orientation of tag wrt the animals body for a given data segment; and 3) Extract gait parameters that are invariant to pose and tag orientation. The authors included biologging tag data from bottlenose dolphins, humpback whales, and beluga whales in this work to validate and demonstrate the approach. Results show that the average relative orientation error of the tag wrt the dolphins body after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for identifying relative tag motion were 0.87 and 0.89, respectively. Examples of the resulting pose and gait analysis demonstrate the potential of this approach to enhance studies that use tag data to investigate movement and behavior. MATLAB source code and data presented in the paper were made available to the public (https://github.com/ding-z/cetacean-pose-gait-analysis.git), with suggestions related to tag data processing practices provided in this paper. The proposed analysis approach will facilitate the use of biologging tags to study cetacean locomotion and behavior.

animal behavior and cognition↗

bioRxiv2021

Extracting socio-spatial networks from photo-ID data using multilevel multinomial models

O_LIEstimating the impacts of anthropogenic disturbances requires an understanding of the habitat use patterns of individuals within a population. This is especially the case when disturbances are localized within a populations spatial range, as variation in habitat-use within a population can drastically alter the distribution of impacts. C_LIO_LIHere, we illustrate the potential for multilevel multinomial models to generate spatial networks from capture-recapture data, a common data source use in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a populations spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the populations spatial range. C_LIO_LIUsing simulations and 18 years of capture-recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, i.e., structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE. C_LIO_LISynthesis and applications. Multilevel multinomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture-recapture of individuals. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities. C_LI

ecology↗