Spatial genetic analysis reveals high connectivity of tiger (<i><scp>P</scp>anthera tigris</i>) populations in the <scp>S</scp>atpura–<scp>M</scp>aikal landscape of Central <scp>I</scp>ndia

Sharma, Sandeep; Dutta, Trishna; Maldonado, Jesús E.; Wood, Thomas O.; Panwar, Hemendra Singh; Seidensticker, John

doi:10.1002/ece3.432

Cited by 59 publications

(68 citation statements)

References 72 publications

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“…The only severe decline in tiger population reported in India in this time frame was in the past century when there was about a 50-fold decline in the countrywide tiger population, but the population has never fallen to a few individuals [43]. Also, we did not detect a genetic signature of a bottleneck in our metapopulation [17], which only appears in a population that has undergone a dramatic decline (10 -1000-fold) in effective population size to a very few remaining individuals [45,46]. A demographic decline does not necessarily result in a bottleneck, and other factors such as the duration of population decline, pre-bottleneck genetic diversity, generation time, recovery rates and gene flow rates from other populations can affect the probability of detecting a population bottleneck [47 -49].…”

Section: Popcontrasting

confidence: 56%

“…A strong signal of isolation by distance (IBD) has been shown to bias gene flow estimates [23]. However, we have previously determined that there is no evidence of IBD in this metapopulation [17].…”

Section: (C) Gene Flow Estimationmentioning

confidence: 85%

“…Further details about sampling, DNA extraction and amplification, species and individual identification, genetic diversity estimation and tests for Hardy-Weinberg equilibrium (HWE; table 1) and population subdivision (table 2) are described in Sharma et al [17].…”

Section: (B) Genotyping and Population Genetic Parametersmentioning

confidence: 99%

“…Our study explores the historical and current pattern of gene flow within a group of four global priority TCLs (TCL 50: Kanha-Phen, TCL 51: Pachmari-Satpura-Bori, TCL 52: Melghat and TCL 53: Pench) that forms a critically important metapopulation of tigers in the Central Indian Highlands of India (figure 1). This spatially heterogeneous metapopulation is large enough to sustain a viable breeding population of tigers, but the intervening matrix and corridors are under heavy human pressure [17,18]. These four TCLs were not thought to be connected with each other based on known dispersal limits of tigers and thus classified as separate demographic populations in classification of TCL [10].…”

Section: Introductionmentioning

confidence: 99%

“…We investigated and found low levels of genetic structure in the tiger metapopulation of the Satpura-Maikal landscape [17]. Analysis and comparison of historical and contemporary gene flow patterns provide information about the configuration of gene exchange and relationships among tiger populations that occupy this landscape.…”

Section: Introductionmentioning

confidence: 99%

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Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

et al. 2013

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Understanding the patterns of gene flow of an endangered species metapopulation occupying a fragmented habitat is crucial for landscape-level conservation planning and devising effective conservation strategies. Tigers (Panthera tigris) are globally endangered and their populations are highly fragmented and exist in a few isolated metapopulations across their range. We used multi-locus genotypic data from 273 individual tigers (Panthera tigris tigris) from four tiger populations of the Satpura-Maikal landscape of central India to determine whether the corridors in this landscape are functional. This 45 000 km 2 landscape contains 17% of India's tiger population and 12% of its tiger habitat. We applied Bayesian and coalescent-based analyses to estimate contemporary and historical gene flow among these populations and to infer their evolutionary history. We found that the tiger metapopulation in central India has high rates of historical and contemporary gene flow. The tests for population history reveal that tigers populated central India about 10 000 years ago. Their population subdivision began about 1000 years ago and accelerated about 200 years ago owing to habitat fragmentation, leading to four spatially separated populations. These four populations have been in migration -drift equilibrium maintained by high gene flow. We found the highest rates of contemporary gene flow in populations that are connected by forest corridors. This information is highly relevant to conservation practitioners and policy makers, because deforestation, road widening and mining are imminent threats to these corridors.

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Section: Popcontrasting

confidence: 56%

Section: (C) Gene Flow Estimationmentioning

confidence: 85%

Section: (B) Genotyping and Population Genetic Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

et al. 2013

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Connecting tiger (Panthera tigris) populations in Nepal: Identification of corridors among tiger‐bearing protected areas

Bhatt

Castley

Sims-Castley

et al. 2023

Ecology and Evolution

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Population genetics reveals high connectivity of giant panda populations across human disturbance features in key nature reserve

Qiao

Connor

Xiaogang

et al. 2019

Ecology and Evolution

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The giant panda is an example of a species that has faced extensive historical habitat fragmentation, and anthropogenic disturbance and is assumed to be isolated in numerous subpopulations with limited gene flow between them. To investigate the population size, health, and connectivity of pandas in a key habitat area, we noninvasively collected a total of 539 fresh wild giant panda fecal samples for DNA extraction within Wolong Nature Reserve, Sichuan, China. Seven validated tetra‐microsatellite markers were used to analyze each sample, and a total of 142 unique genotypes were identified. Nonspatial and spatial capture–recapture models estimated the population size of the reserve at 164 and 137 individuals (95% confidence intervals 153–175 and 115–163), respectively. Relatively high levels of genetic variation and low levels of inbreeding were estimated, indicating adequate genetic diversity. Surprisingly, no significant genetic boundaries were found within the population despite the national road G350 that bisects the reserve, which is also bordered with patches of development and agricultural land. We attribute this to high rates of migration, with four giant panda road‐crossing events confirmed within a year based on repeated captures of individuals. This likely means that giant panda populations within mountain ranges are better connected than previously thought. Increased development and tourism traffic in the area and throughout the current panda distribution pose a threat of increasing population isolation, however. Maintaining and restoring adequate habitat corridors for dispersal is thus a vital step for preserving the levels of gene flow seen in our analysis and the continued conservation of the giant panda meta‐population in both Wolong and throughout their current range.

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Spatial genetic analysis reveals high connectivity of tiger (Panthera tigris) populations in the Satpura–Maikal landscape of Central India

Cited by 59 publications

References 72 publications

Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

Connecting tiger (Panthera tigris) populations in Nepal: Identification of corridors among tiger‐bearing protected areas

Population genetics reveals high connectivity of giant panda populations across human disturbance features in key nature reserve

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