in

Genetic analyses reveal demographic decline and population differentiation in an endangered social carnivore, Asiatic wild dog

  • 1.

    Wilcove, D. S., McLellan, C. H. & Dobson, A. P. Habitat fragmentation in the temperate zone. Conserv. Biol. 6, 237–256 (1986).

    Google Scholar 

  • 2.

    Crooks, K. R. et al. Quantification of habitat fragmentation reveals extinction risk in terrestrial mammals. Proc. Natl. Acad. Sci. USA 114, 7635–7640 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 3.

    Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2011).

    Article 

    Google Scholar 

  • 4.

    Okie, J. G. & Brown, J. H. Niches, body sizes, and the disassembly of mammal communities on the Sunda Shelf islands. Proc. Natl. Acad. Sci. USA 106, 19679–19684 (2009).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 5.

    Viveiros De Castro, E. B. & Fernandez, F. A. S. Determinants of differential extinction vulnerabilities of small mammals in Atlantic forest fragments in Brazil. Biol. Conserv. 119, 73–80 (2004).

    Article 

    Google Scholar 

  • 6.

    Feeley, K. J. & Terborgh, J. W. Direct versus indirect effects of habitat reduction on the loss of avian species from tropical forest fragments. Anim. Conserv. 11, 353–360 (2008).

    Article 

    Google Scholar 

  • 7.

    Prugh, L. R., Hodges, K. E., Sinclair, A. R. E. & Brashares, J. S. Effect of habitat area and isolation on fragmented animal populations. Proc. Natl. Acad. Sci. USA 105, 20770–20775 (2008).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 8.

    Crooks, K. R., Burdett, C. L., Theobald, D. M., Rondinini, C. & Boitani, L. Global patterns of fragmentation and connectivity of mammalian carnivore habitat. Philos. Trans. R. Soc. B Biol. Sci. 366, 2642–2651 (2011).

    Article 

    Google Scholar 

  • 9.

    Janecka, J. E. et al. Genetic differences in the response to landscape fragmentation by a habitat generalist, the bobcat, and a habitat specialist, the ocelot. Conserv. Genet. 17, 1093–1108 (2016).

    Article 

    Google Scholar 

  • 10.

    Creel, S. Four factors modifying the effect of competition on Carnivore population dynamics as illustrated by African wild dogs. Conserv. Biol. 15, 271–274 (2001).

    Article 

    Google Scholar 

  • 11.

    Crooks, K. R. Relative sensitivities of mammalian carnivores to habitat fragmentation. Conserv. Biol. 16, 488–502 (2002).

    Article 

    Google Scholar 

  • 12.

    Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343 (2014).

  • 13.

    Sanderson, C. E., Jobbins, S. E. & Alexander, K. A. With Allee effects, life for the social carnivore is complicated. Popul. Ecol. 56, 417–425 (2014).

    Article 

    Google Scholar 

  • 14.

    Kamler, J. F. et alCuon alpinusThe IUCN Red List of Threatened Species 2015: e.T5953A72477893. https://doi.org/10.2305/IUCN.UK.2015-4.RLTS.T5953A72477893.en (2015).

  • 15.

    Bashir, T., Bhattacharya, T., Poudyal, K., Roy, M. & Sathyakumar, S. Precarious status of the endangered dhole cuon alpinus in the high elevation eastern himalayan habitats of khangchendzonga biosphere reserve, Sikkim, India. Oryx 48, 125–132 (2014).

    Article 

    Google Scholar 

  • 16.

    Pal, R., Thakur, S., Arya, S., Bhattacharya, T. & Sathyakumar, S. Recent records of dhole (Cuon alpinus, Pallas 1811) in Uttarakhand, Western Himalaya, India. Mammalia 82, 614–617 (2018).

    Article 

    Google Scholar 

  • 17.

    Karanth, K. K., Nichols, J. D., UllasKaranth, K., Hines, J. E. & Christensen, N. L. The shrinking ark: Patterns of large mammal extinctions in India. Proc. R. Soc. B Biol. Sci. 277, 1971–1979 (2010).

    Article 

    Google Scholar 

  • 18.

    Keyghobadi, N. The genetic implications of habitat fragmentation for animals. Can. J. Zool. 85, 1049–1064 (2007).

    Article 

    Google Scholar 

  • 19.

    Lourenço, A., Álvarez, D., Wang, I. J. & Velo-Antón, G. Trapped within the city: Integrating demography, time since isolation and population-specific traits to assess the genetic effects of urbanization. Mol. Ecol. 26, 1498–1514 (2017).

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 20.

    Ghaskadbi, P., Habib, B. & Qureshi, Q. A whistle in the woods: An ethogram and activity budget for the dhole in central India. J. Mammal. 97, 1745–1752 (2016).

    Article 

    Google Scholar 

  • 21.

    Karanth, K. U. & Sunquist, M. E. Behavioural correlates of predation by tiger (Panthera tigiris), leopard (Panthera pardus) and dhole (Cuon alpinus) in Nagarahole, India. J. Zool. Lond. 250, 255–265 (2000).

    Article 

    Google Scholar 

  • 22.

    Johnsingh, A. J. T. Reproduction and social behaviour of the dhole, Cuon alpinus (Canidae). J. Zool. 198, 443–463 (1982).

    Article 

    Google Scholar 

  • 23.

    Ngoprasert, D. & Gale, G. A. Tiger density, dhole occupancy, and prey occupancy in the human disturbed Dong Phayayen—Khao Yai Forest Complex, Thailand. Mammal. Biol. 95, 51–58 (2019).

    Article 

    Google Scholar 

  • 24.

    Selvan, K. M., Lyngdoh, S., Habib, B. & Gopi, G. V. Population density and abundance of sympatric large carnivores in the lowland tropical evergreen forest of Indian Eastern Himalayas. Mammal. Biol. 79, 254–258 (2014).

    Article 

    Google Scholar 

  • 25.

    Jenks, K. E. et al. Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape. Raffles Bull. Zool. 63, 546–554 (2015).

    Google Scholar 

  • 26.

    Modi, S., Habib, B., Ghaskadbi, P., Nigam, P. & Mondol, S. Standardization and validation of a panel of cross-species microsatellites to individually identify the Asiatic wild dog (Cuon alpinus). PeerJ 7, e7453 (2019).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 27.

    Modi, S. et al. Noninvasive DNA-based species and sex identification of Asiatic wild dog (Cuonalpinus). J. Genet. 97, 1457–1461 (2018).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 28.

    Iyengar, A. et al. Phylogeography, genetic structure, and diversity in the dhole (Cuon alpinus). Mol. Ecol. 14, 2281–2297 (2005).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 29.

    Durbin, L., Venkataraman, A. & Hedges, S. D. J. Dhole (Cuon alpinus). In Status Survery and Conservation Action Plan. Canids: Foxes, Wolves, Jackals and Dogs (eds. Sillero-Zubiri, C., Hoffman, M. & Macdonald, D. W.) 210–219 (2004).

  • 30.

    Smith, O. & Wang, J. When can noninvasive samples provide sufficient information in conservation genetics studies?. Mol. Ecol. Resour. 14, 1011–1023 (2014).

    CAS 
    PubMed 

    Google Scholar 

  • 31.

    Godinho, R. et al. Real-time assessment of hybridization between wolves and dogs: Combining noninvasive samples with ancestry informative markers. Mol. Ecol. Resour. 15, 317–328 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 32.

    Venkataraman, A. B., Arumugam, R. & Sukumar, R. The foraging ecology of dhole (Cuon alpinus) in Mudumalai Sanctuary, southern India. J. Zool. 237, 543–561 (1995).

    Article 

    Google Scholar 

  • 33.

    Srivathsa, A., Karanth, K. U., Kumar, N. S. & Oli, M. K. Insights from distribution dynamics inform strategies to conserve a dhole Cuon alpinus metapopulation in India. Sci. Rep. 9, 1–12 (2019).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 34.

    Reddy, C. S., Sreelekshmi, S., Jha, C. S. & Dadhwal, V. K. National assessment of forest fragmentation in India: Landscape indices as measures of the effects of fragmentation and forest cover change. Ecol. Eng. 60, 453–464 (2013).

    Article 

    Google Scholar 

  • 35.

    Dutta, T., Sharma, S. & DeFries, R. Targeting restoration sites to improve connectivity in a tiger conservation landscape in India. PeerJ 6, e5587 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 36.

    Mondal, I., Habib, B., Talukdar, G. & Nigam, P. Triage of means: Options for conserving tiger corridors beyond designated protected lands in India. Front. Ecol. Evol. 4, 2–7 (2016).

    ADS 
    Article 

    Google Scholar 

  • 37.

    Lowther, A. D., Harcourt, R. G., Goldsworthy, S. D. & Stow, A. Population structure of adult female Australian sea lions is driven by fine-scale foraging site fidelity. Anim. Behav. 83, 691–701 (2012).

    Article 

    Google Scholar 

  • 38.

    Marsden, C. D. et al. Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus). Mol. Ecol. 21, 1379–1393 (2012).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 39.

    Yumnam, B. et al. Prioritizing tiger conservation through landscape genetics and habitat linkages. PLoS ONE 9 (2014).

  • 40.

    Dutta, T. et al. Fine-scale population genetic structure in a wide-ranging carnivore, the leopard (Panthera pardus fusca) in central India. Divers. Distrib. 19, 760–771 (2013).

    Article 

    Google Scholar 

  • 41.

    Thatte, P. et al. Human footprint differentially impacts genetic connectivity of four wide-ranging mammals in a fragmented landscape. Divers. Distrib. 26, 299–314 (2020).

    Article 

    Google Scholar 

  • 42.

    Slatkin M. Gene flow and population structure. Ecol. Genet. 3–17 (1994).

  • 43.

    Bhandari, A., Ghaskadbi, P., Nigam, P. & Habib, B. Dhole pack size variation: Assessing effect of Prey availability and Apex predator. Ecol. Evol. 00, 1–12 (2021).

    Google Scholar 

  • 44.

    Davies, K. F., Margules, C. R. & Lawrence, J. F. Which traits of species predict population declines in experimental forest fragments?. Ecology 81, 1450–1461 (2000).

    Article 

    Google Scholar 

  • 45.

    Bhatt, S., Biswas, S., Karanth, K., Pandav, B. & Mondol, S. Genetic analyses reveal population structure and recent decline in leopards (Panthera pardus fusca) across the Indian subcontinent. PeerJ 8, e8482 (2020).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 46.

    Mondol, S., Karanth, K. U. & Ramakrishnan, U. Why the Indian subcontinent holds the key to global tiger recovery. PLoS Genet. 5 (2009).

  • 47.

    Nijman, V. et al. Illegal wildlife trade–surveying open animal markets and online platforms to understand the poaching of wild cats. Biodiversity 20, 58–61 (2019).

    Article 

    Google Scholar 

  • 48.

    Srivathsa, A., Sharma, S., Singh, P., Punjabi, G. A. & Oli, M. K. A strategic road map for conserving the Endangered dhole Cuon alpinus in India. Mammal. Rev. 50, 399–412 (2020).

    Article 

    Google Scholar 

  • 49.

    Richards, J. F. & Elizabeth, P. F. A century of land-use change in South and Southeast Asia. In Effects of land-use change on atmospheric CO2 concentrations 15–66 (1994).

  • 50.

    Goldewijk, K. K. & Ramankutty, N. Land use changes during the past 300 years (EOLSS Publisher Co., 2009).

    Google Scholar 

  • 51.

    Sharma, S. et al. Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India. Proc. R. Soc. B Biol. Sci. 280, 14 (2013).

    Google Scholar 

  • 52.

    Rangarajan, M. Fencing the forest: Conservation and ecological change in India’s central provinces 1860–1914 (1999).

  • 53.

    Gadgil, M. Towards an ecological history of India. Econ. Pol. Wkly. 20, 1909–1911 (2011).

    Google Scholar 

  • 54.

    Bebarta, K. C. Teak; ecology, silviculture, management and profitability (International Book Distributors, 1999).

    Google Scholar 

  • 55.

    Waples, R. S. & England, P. R. Estimating contemporary effective population size on the basis of linkage disequilibrium in the face of migration. Genetics 189, 633–644 (2011).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 56.

    Frankham, R., Bradshaw, C. J. A. & Brook, B. W. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol. Conserv. 170, 56–63 (2014).

    Article 

    Google Scholar 

  • 57.

    de Manuel, M. et al. The evolutionary history of extinct and living lions. Proc. Natl. Acad. Sci. USA 117, 10927–10934 (2020).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 58.

    Creel, S. Social organization and effective population size in carnivores. Behav. Ecol. Conserv. Biol. 264–265 (1998).

  • 59.

    Lande, R. & Barrowclough, G. Effective population size, genetic variation, and their use in population. Viable Popul. Conserv. 87–123 (1987).

  • 60.

    Neel, M. C. et al. Estimation of effective population size in continuously distributed populations: There goes the neighborhood. Heredity 111, 189–199 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 61.

    Girman, D. J. et al. Patterns of population subdivision, gene flow and genetic variability in the African wild dog (Lycaon pictus). Mol. Ecol. 10, 1703–1723 (2001).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 62.

    Sacks, B. N., Mitchell, B. R., Williams, C. L. & Ernest, H. B. Coyote movements and social structure along a cryptic population genetic subdivision. Mol. Ecol. 14, 1241–1249 (2005).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 63.

    Stronen, A. V. et al. Population genetic structure of gray wolves (Canis lupus) in a marine archipelago suggests island-mainland differentiation consistent with dietary niche. BMC Ecol. 14, 1–9 (2014).

    Article 

    Google Scholar 

  • 64.

    Wolf, C. & Ripple, W. J. Range contractions of the world’s large carnivores. R. Soc. Open Sci. 4 (2017).

  • 65.

    Walston, J. et al. Bringing the tiger back from the brink-the six percent solution. PLoS Biol. 8, 6–9 (2010).

    Article 
    CAS 

    Google Scholar 

  • 66.

    Champion, H. G. & Seth, S. K. A revised survey of the forest types of India. (Manager of Publications, 1968).

  • 67.

    Biswas, S. et al. A practive faeces collection protocol for multidisciplinary research in wildlife science. Curr. Sci. 116, 1878 (2019).

    CAS 
    Article 

    Google Scholar 

  • 68.

    Hallsworth, J. E., Nomura, Y. & Iwahara, M. Ethanol-induced water stress and fungal growth. J. Ferment. Bioeng. 86, 451–456 (1998).

    CAS 
    Article 

    Google Scholar 

  • 69.

    van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).

    Article 
    CAS 

    Google Scholar 

  • 70.

    Broquet, T. & Petit, E. Quantifying genotyping errors in noninvasive population genetics. Mol. Ecol. 13, 3601–3608 (2004).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 71.

    Kalinowski, S. T., Taper, M. L. & Marshall, T. C. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16, 1099–1106 (2007).

    PubMed 
    Article 

    Google Scholar 

  • 72.

    Waits, L., Taberlet, P. & Luikart, G. Estimating the probability of identity among genotypesin natural populations: Cautions and guidelines. Mol. Ecol. 10, 249–256 (2001).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 73.

    Valière, N. GIMLET: A computer program for analysing genetic individual identification data. Mol. Ecol. Notes 2, 377–379 (2002).

    Google Scholar 

  • 74.

    Excoffier, L., Laval, G. & Schneider, S. Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evol. Bioinf. 1, 117693430500100 (2005).

  • 75.

    Pritchard, J. K. & Stephens, M. D. M. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 76.

    Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 77.

    Earl, D. A. & vonHoldt, B. M. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).

  • 78.

    Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191 (2015).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 79.

    Caye, K., Deist, T. M., Martins, H., Michel, O. & François, O. TESS3: Fast inference of spatial population structure and genome scans for selection. Mol. Ecol. Resour. 16, 540–548 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 80.

    Jombart, T. et al. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 81.

    Jombart, T. Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 82.

    Jombart, T., Devillard, S., Dufour, A. B. & Pontier, D. Revealing cryptic spatial patterns in genetic variability by a new multivariate method. Heredity 101, 92–103 (2008).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 83.

    Thioulouse, J., Chessel, D. & Champely, S. Multivariate analysis of spatial patterns: a unified approach to local and global structures. Environ. Ecol. Stat. 2, 1–14 (1995).

    Article 

    Google Scholar 

  • 84.

    Moran, P. The interpretation of statistical maps. J. R. Stat. Soc. Ser. B Stat. Methodol. 10, 243–251 (1948).

  • 85.

    Hedrick, P. W. A standardized genetic differentiation measure. Evolution 59, 1633–1638 (2005).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 86.

    Jost, L. GST and its relatives do not measure differentiation. Mol. Ecol. 17, 4015–4026 (2008).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 87.

    Keenan, K., Mcginnity, P., Cross, T. F., Crozier, W. W. & Prodöhl, P. A. DiveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol. Evol. 4, 782–788 (2013).

    Article 

    Google Scholar 

  • 88.

    Sundqvist, L., Keenan, K., Zackrisson, M., Prodöhl, P. & Kleinhans, D. Directional genetic differentiation and relative migration. Ecol. Evol. 6, 3461–3475 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 89.

    Ryman, N. & Leimar, O. GST is still a useful measure of genetic differentiation—A comment on Jost’s D. Mol. Ecol. 18, 2084–2087 (2009).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 90.

    Meirmans, P. G. & Hedrick, P. W. Assessing population structure: FST and related measures. Mol. Ecol. Resour. 11, 5–18 (2011).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 91.

    Wilson, G. A. & Rannala, B. Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163, 1177–1191 (2003).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 92.

    Faubet, P., Waples, R. S. & Gaggiotti, O. E. Evaluating the performance of a multilocus Bayesian method for the estimation of migration rates. Mol. Ecol. 16, 1149–1166 (2007).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 93.

    Do, C. et al. NeEstimator v2: Re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 94.

    Waples, R. S. & Do, C. LDNE: A program for estimating effective population size from data on linkage disequilibrium. Mol. Ecol. Resour. 8, 753–756 (2008).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 95.

    Piry, S., Luikart, G. & Cornuet, J. M. BOTTLENECK: A computer program for detecting recent reductions in the effective population size using allele frequency data. J. Hered. 90, 502–503 (1999).

    Article 

    Google Scholar 

  • 96.

    Nikolic, N. & Chevalet, C. Detecting past changes of effective population size. Evol. Appl. 7, 663–681 (2014).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 97.

    Kimura, M. & Ohta, T. Stepwise mutation model and distribution of allelic frequencies in a finite population. Proc. Natl. Acad. Sci. USA 75, 2868–2872 (1978).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    MATH 
    Article 

    Google Scholar 

  • 98.

    Ruiz-Garcia, M. et al. Determination of microsatellite DNA mutation rates, mutation models and mutation bias in four main Felidae lineages (European wild cat, F. silvestris; ocelot, Leopardus pardalis; puma, Puma concolor; jaguar, Panthera onca). In Molecular Population Genetics, Evolutionary Biology & Biological Conservation of Neotropical Carnivores. (Nova Science Publishers Inc., New York, 2013).

  • 99.

    Xu, X., Peng, M., Fang, Z. & Xu, X. The direction of microsatellite mutations is dependent upon allele length. Nat. Genet. 24, 396–399 (2000).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 


  • Source: Ecology - nature.com

    Elsa Olivetti wins 2021 MIT Bose Award for Excellence in Teaching

    Using aluminum and water to make clean hydrogen fuel — when and where it’s needed