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Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change.

ABSTRACT: Landscape genetic studies typically focus on the evolutionary processes that give rise to spatial patterns that are quantified at a single point in time. Although landscape change is widely recognized as a strong driver of microevolutionary processes, few landscape genetic studies have directly evaluated the change in spatial genetic structure (SGS) over time with concurrent changes in landscape pattern. We introduce a novel approach to analyze landscape genetic data through time. We demonstrate this approach using genotyped samples (n = 569) from a large black bear (Ursus americanus) population in Michigan (USA) that were harvested during 3 years (2002, 2006, and 2010). We identified areas that were consistently occupied over this 9-year period and quantified temporal variation in SGS. Then, we evaluated alternative hypotheses about effects of changes in landscape features (e.g., deforestation or crop conversion) on fine-scale SGS among years using spatial autoregressive modeling and model selection. Relative measures of landscape change such as magnitude of landscape change (i.e., number of patches changing from suitable to unsuitable states or vice versa), and during later periods, measures of fragmentation (i.e., patch aggregation and cohesion) were associated with change in SGS. Our results stress the importance of conducting time series studies for the conservation and management of wildlife inhabiting rapidly changing landscapes.

SUBMITTER: Draheim HM

PROVIDER: S-EPMC6100183 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change.

Draheim Hope M HM Moore Jennifer A JA Fortin Marie-Josée MJ Scribner Kim T KT

Evolutionary applications 20180325 8

Landscape genetic studies typically focus on the evolutionary processes that give rise to spatial patterns that are quantified at a single point in time. Although landscape change is widely recognized as a strong driver of microevolutionary processes, few landscape genetic studies have directly evaluated the change in spatial genetic structure (SGS) over time with concurrent changes in landscape pattern. We introduce a novel approach to analyze landscape genetic data through time. We demonstrate ...[more]

PMID: 30151035

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Project description:American black bears (Ursus americanus) are seasonally polyoestrous and exhibit delayed implantation, which may allow equal and independent fertility of recurrent oestruses of a mating season. We postulated that the luteal inactivity during delayed implantation allows bears to have sequential ovulation during a polyoestrous mating season such that each oestrus of a polyoestrous female will have equivalent fertility, and pregnancy would not preclude subsequent ovulation and superfetation. Controlled mating experiments were conducted on semi-free-ranging female American black bears during three mating seasons, wherein females were bred by different male cohorts in each oestrus. Behavioural observation, vulva score ranking, genetic paternity analysis, gross morphology of ovaries and microscopic morphology of diapaused embryos were used to evaluate the fertility of each subsequent oestrus in polyoestrous females. Oestrus duration, number of successful mounts and median vulva scores were similar between first and subsequent oestruses of the season. Polyoestrus occurred in 81.3% of oestrous females, with a 9.7?±?5.5 day (mean?±?SD) inter-oestrous interval. Sequential ovulation was documented in three polyoestrous females, including one that possessed both a corpus haemorrhagicum and a developed corpus luteum. Among polyoestrous dams, four of nine embryos were conceived in the first oestrus and five of nine in the second oestrus. These results indicate that each oestrus of polyoestrous females is capable of fertility, even if the female is already pregnant from a prior oestrus. Although superfetation was not directly observed in the present study, our results strongly suggest the potential of superfetation in the American black bear and provide novel insight into the complex behavioural and physiological breeding mechanisms of bears. Given that most endangered bear species share similar reproductive traits with American black bears, captive breeding programmes could take advantage of superfetation by mating females with different males at each subsequent oestrus of the season in order to increase the genetic diversity of captive endangered bears.

Project description:Landscape genetic analyses allow detection of fine-scale spatial genetic structure (SGS) and quantification of effects of landscape features on gene flow and connectivity. Typically, analyses require generation of resistance surfaces. These surfaces characteristically take the form of a grid with cells that are coded to represent the degree to which landscape or environmental features promote or inhibit animal movement. How accurately resistance surfaces predict association between the landscape and movement is determined in large part by (a) the landscape features used, (b) the resistance values assigned to features, and (c) how accurately resistance surfaces represent landscape permeability. Our objective was to evaluate the performance of resistance surfaces generated using two publicly available land cover datasets that varied in how accurately they represent the actual landscape. We genotyped 365 individuals from a large black bear population (Ursus americanus) in the Northern Lower Peninsula (NLP) of Michigan, USA at 12 microsatellite loci, and evaluated the relationship between gene flow and landscape features using two different land cover datasets. We investigated the relative importance of land cover classification and accuracy on landscape resistance model performance. We detected local spatial genetic structure in Michigan's NLP black bears and found roads and land cover were significantly correlated with genetic distance. We observed similarities in model performance when different land cover datasets were used despite 21% dissimilarity in classification between the two land cover datasets. However, we did find the performance of land cover models to predict genetic distance was dependent on the way the land cover was defined. Models in which land cover was finely defined (i.e., eight land cover classes) outperformed models where land cover was defined more coarsely (i.e., habitat/non-habitat or forest/non-forest). Our results show that landscape genetic researchers should carefully consider how land cover classification changes inference in landscape genetic studies.

Dataset Information

Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change.

Publications

Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change.

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