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Trends in Wildlife Connectivity Science from the Biodiverse and Human-Dominated South Asia

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Journal of the Indian Institute of Science Aims and scope

Abstract

The threat of habitat fragmentation and population isolation looms large over much of biodiversity in this human-dominated epoch. Species-rich South Asia is made particularly vulnerable by its high human density and anthropogenic habitat modification. Therefore, reliably estimating wildlife connectivity and the factors underpinning it become crucial in mitigating extinction risk due to isolation. We analysed peer-reviewed literature on connectivity and corridors for terrestrial mammals in South Asia to identify trends in connectivity research. We identify key research gaps and highlight future directions that may aid efforts to robustly study connectivity. We found a significant bias towards charismatic megafauna and their habitats. Methodologically, although we observed a range of approaches reflecting some of the advances and innovations in the field, several studies lacked data on animal movement/behaviour, leading to potentially biased inferences of how species disperse through human-modified landscapes. New avenues for connectivity research, though currently under-explored in South Asia, offer alternatives to the heavily used but less-reliable habitat suitability models. We highlight the advantages of landscape genetic methods that reflect effective dispersal and are made feasible through non-invasive and increasingly more cost-effective sampling methods. We also identify important gaps or areas of focus that need to be addressed going forward, including accounting for animal movement/behaviour, human impacts and landscape change for dynamic and adaptive connectivity planning for the future.

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References

  1. Keeley ATH, et al (2019) Thirty years of connectivity conservation planning: an assessment of factors influencing plan implementation. Environ Res Lett 14(10):103001

  2. Steffen W, Grinevald J, Crutzen P, McNeill J (2011) The anthropocene: conceptual and historical perspectives. Philos Trans R Soc Math Phys Eng Sci 369:842–867

    Google Scholar 

  3. Dirzo R et al (2014) Defaunation in the Anthropocene. Science 345:401–406

    Article  CAS  Google Scholar 

  4. Brodie JF et al (2016) Connecting science, policy, and implementation for landscape-scale habitat connectivity: corridor science and policy. Conserv Biol 30:950–961

    Article  Google Scholar 

  5. Brooks TM et al (2004) Coverage provided by the global protected-area system: is it enough? Bioscience 54:1081

    Article  Google Scholar 

  6. Nayak R, et al (2020) Bits and pieces: forest fragmentation by linear intrusions in India. Land Use Policy 99(C):104619

  7. Dutta T, Sharma S, Maldonado JE, Panwar HS, Seidensticker J (2015) Genetic variation, structure, and gene flow in a sloth bear (Melursus ursinus) meta-population in the satpura-maikal landscape of Central India. PloS One 10(5):e0123384

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

    Google Scholar 

  9. Thatte P, Joshi A, Vaidyanathan S, Landguth E, Ramakrishnan U (2018) Maintaining tiger connectivity and minimizing extinction into the next century: Insights from landscape genetics and spatially-explicit simulations. Biol Conserv 218:181–191

    Article  Google Scholar 

  10. Díaz S et al (2019) Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES secretariat, Bonn, Germany

    Google Scholar 

  11. Chapron G et al (2014) Recovery of large carnivores in Europe’s modern human-dominated landscapes. Science 346:1517–1519

    Article  CAS  Google Scholar 

  12. Warrier R, Noon BR, Bailey L (2020) Agricultural lands offer seasonal habitats to tigers in a human-dominated and fragmented landscape in India. Ecosphere 11:e03080

    Article  Google Scholar 

  13. Moritz C (2002) Strategies to Protect Biological Diversity and the Evolutionary Processes That Sustain It. Syst Biol 51:238–254

    Article  Google Scholar 

  14. Keeley ATH, Beier P, Keeley BW, Fagan ME (2017) Habitat suitability is a poor proxy for landscape connectivity during dispersal and mating movements. Landsc Urban Plan 161:90–102

    Article  Google Scholar 

  15. Diniz MF, Cushman SA, Machado RB, Júnior PDM (2020) Landscape connectivity modeling from the perspective of animal dispersal. Landsc Ecol 35:41–58

    Article  Google Scholar 

  16. Zeller KA, McGarigal K, Whiteley AR (2012) Estimating landscape resistance to movement: a review. Landsc Ecol 27:777–797

    Article  Google Scholar 

  17. Fletcher RJ, Burrell NS, Reichert BE, Vasudev D, Austin JD (2016) Divergent perspectives on landscape connectivity reveal consistent effects from genes to communities. Curr Landsc Ecol Rep 1:67–79

    Article  Google Scholar 

  18. Kumar D, Scheiter S (2019) Biome diversity in South Asia - How can we improve vegetation models to understand global change impact at regional level? Sci Total Environ 671:1001–1016

    Article  CAS  Google Scholar 

  19. Nagendra H (2009) Reforestation and regrowth in the human dominated landscapes of South Asia. In: Nagendra H, Southworth J (eds) Reforesting Landscapes. Springer, New York, pp 149–174

  20. DeFries R, Pandey D (2010) Urbanization, the energy ladder and forest transitions in India’s emerging economy. Land Use Policy 27:130–138

    Article  Google Scholar 

  21. Nagendra H, Sudhira H S, Katti M, Tengo M, Schewenius M (2014) Urbanization and its impacts on land use, biodiversity and ecosystems in India. INTERdisciplina 2:169–178

  22. Narain V, Vij S (2016) Where have all the commons gone? Geoforum 68:21–24

    Article  Google Scholar 

  23. Donaldson MR, et al (2017) Taxonomic bias and international biodiversity conservation research. FACETS 1:105–113

  24. Di Marco M et al (2017) Changing trends and persisting biases in three decades of conservation science. Glob Ecol Conserv 10:32–42

    Article  Google Scholar 

  25. Tischendorf L, Fahrig L (2000) On the usage and measurement of landscape connectivity. Oikos 90:7–19

    Article  Google Scholar 

  26. Taylor P, Fahrig L, With K (2006) Landscape connectivity: a return to the basics. Conserv Biol 14:29–43

    Google Scholar 

  27. Calabrese JM, Fagan WF (2004) A comparison-shopper’s guide to connectivity metrics. Front Ecol Environ 2:529–536

    Article  Google Scholar 

  28. McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724

    Article  Google Scholar 

  29. Spear SF, Cushman SA, McRae BH (2016) Resistance surface modeling in landscape genetics. In: Balkenhol N, Cushman S, Storfer A, Waits L (eds) Landscape genetics: concepts, methods, applications. Wiley, New York, pp 129–148

  30. Beier P, Majka DR, Newell SL (2009) Uncertainty analysis of least-cost modeling for designing wildlife linkages. Ecol Appl 19:2067–2077

    Article  Google Scholar 

  31. Alexander JL, Olimb SK, Bly KL, Restani M (2016) Use of least-cost path analysis to identify potential movement corridors of swift foxes in Montana. J Mammal 97:891–898

    Article  Google Scholar 

  32. Hirzel AH, Le Lay G (2008) Habitat suitability modelling and niche theory. J Appl Ecol 45:1372–1381

    Article  Google Scholar 

  33. Ziółkowska E et al (2016) Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians. Landsc Ecol 31:1863–1882

    Article  Google Scholar 

  34. Bunn AG, Urban DL, Keitt TH (2000) Landscape connectivity: a conservation application of graph theory. J Environ Manage 59:265–278

    Article  Google Scholar 

  35. Kindlmann P, Burel F (2008) Connectivity measures: a review. Landsc Ecol 23:879–890

    Google Scholar 

  36. Godet C, Clauzel C (2021) Comparison of landscape graph modelling methods for analysing pond network connectivity. Landsc Ecol 36:735–748

    Article  Google Scholar 

  37. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evol 18:189–197

    Article  Google Scholar 

  38. Shanu S et al (2019) A graph theoretic approach for modelling tiger corridor network in Central India-Eastern Ghats landscape complex, India. Ecol Inform 50:76–85

    Article  Google Scholar 

  39. Baskaran N, Kannan G, Anbarasan U, Thapa A, Sukumar R (2013) A landscape-level assessment of Asian elephant habitat, its population and elephant-human conflict in the Anamalai hill ranges of southern Western Ghats India. Mamm Biol 78:470–481

    Article  Google Scholar 

  40. Mukherjee T, et al (2021) Adaptive spatial planning of protected area network for conserving the Himalayan brown bear. Sci Total Environ 754:142416

  41. Wegge P, Yadav SK, Lamichhane BR (2018) Are corridors good for tigers Panthera tigris but bad for people? An assessment of the Khata corridor in lowland Nepal. Oryx 52:35–45

    Article  Google Scholar 

  42. Thapa K, et al (2018) Assessment of genetic diversity, population structure, and gene flow of tigers (Panthera tigris tigris) across Nepal’s Terai Arc Landscape. PloS One 13(3):e0193495

  43. Borah J, Jena J, Yumnam B, Puia L (2016) Carnivores in corridors: estimating tiger occupancy in Kanha-Pench corridor, Madhya Pradesh India. Reg Environ Change 16:43–52

    Article  Google Scholar 

  44. Thapa A, et al (2017) Combined land cover changes and habitat occupancy to understand corridor status of Laljhadi-Mohana wildlife corridor, Nepal. Eur J Wildl Res 63:83

  45. Dutta T, Sharma S, McRae BH, Roy PS, DeFries R (2016) Connecting the dots: mapping habitat connectivity for tigers in central India. Reg Environ Change 16:53–67

    Article  Google Scholar 

  46. Joshi A, Vaidyanathan S, Mondol S, Edgaonkar A, Ramakrishnan U (2013) Connectivity of tiger (Panthera tigris) populations in the human-influenced forest Mosaic of Central India. PloS One 8(11):e77980

  47. Natesh M, et al (2017) Conservation priorities for endangered Indian tigers through a genomic lens. Sci Rep 7:9614

  48. Mondol S, Bruford MW, Ramakrishnan U (2013) Demographic loss, genetic structure and the conservation implications for Indian tigers. Proc R Soc B Biol Sci 280:20130496

  49. Dalui S. et al (2020) Fine-scale landscape genetics unveiling contemporary asymmetric movement of red panda (Ailurus fulgens) in Kangchenjunga landscape, India. Sci Rep 10:15446

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

    Article  Google Scholar 

  51. Singh SK, et al (2017) Fine-scale population genetic structure of the Bengal tiger (Panthera tigris tigris) in a human-dominated western Terai Arc Landscape, India. PloS One 12(4):e0174371

  52. Anwar M, Borah J (2019) Functional status of a wildlife corridor with reference to tiger in Terai Arc Landscape of India. Trop Ecol 60:525–531

    Article  Google Scholar 

  53. Dutta T et al (2013) Gene flow and demographic history of leopards (Panthera pardus) in the central Indian highlands. Evol Appl 6:949–959

    Article  Google Scholar 

  54. Reddy PA, et al (2012) Genetic evidence of tiger population structure and migration within an isolated and fragmented landscape in Northwest India. PloS One 7(1):e29827

  55. Sharma R et al (2011) Genetically distinct population of Bengal tiger (Panthera tigris tigris) in Terai Arc Landscape (TAL) of India. Mamm Biol 76:484–490

    Article  Google Scholar 

  56. Areendran G et al (2011) Geospatial modeling to assess elephant habitat suitability and corridors in northern Chhattisgarh India. Trop Ecol 52:275–283

    Google Scholar 

  57. Kabir M, et al (2017) Habitat suitability and movement corridors of grey wolf (Canis lupus) in Northern Pakistan. PloS One 12(11):e0187027

  58. Luikart G et al (2011) High connectivity among argali sheep from Afghanistan and adjacent countries: inferences from neutral and candidate gene microsatellites. Conserv Genet 12:921–931

    Article  Google Scholar 

  59. Kenney J, Allendorf FW, McDougal C, Smith JLD (2014) How much gene flow is needed to avoid inbreeding depression in wild tiger populations? Proc R Soc B Biol Sci 281:20133337

  60. Talukdar NR, Choudhury P, Ahmad F, Al-Razi H, Ahmed R (2020) Mapping and assessing the transboundary elephant corridor in the Patharia Hills reserve forest of Assam India. Rangel Ecol Manag 73:694–702

    Article  Google Scholar 

  61. Sharma LK, Mukherjee T, Saren PC, Chandra K (2019) Identifying suitable habitat and corridors for Indian Grey Wolf (Canis lupus pallipes) in Chotta Nagpur Plateau and Lower Gangetic Planes: a species with differential management needs. PloS One 14(4):e0215019

  62. Sarkar MS et al (2018) Multiscale statistical approach to assess habitat suitability and connectivity of common leopard (Panthera pardus) in Kailash Sacred Landscape India. Spat Stat 28:304–318

    Article  Google Scholar 

  63. Rathore CS, Dubey Y, Shrivastava A, Pathak P, Patil V (2012) Opportunities of habitat connectivity for tiger (Panthera tigris) between Kanha and Pench National Parks in Madhya Pradesh, India. PloS One 7(7):e39996

  64. Rameshan M, Roy A, Ramasamy EV (2014) Identification of potential elephant corridor between Anamalai landscape and Periyar tiger reserve, southern western Ghats: a geospatial approach. Int J Geoinform 10:41–52

    Google Scholar 

  65. Krishnamurthy R et al (2016) Multi-scale prediction of landscape resistance for tiger dispersal in central India. Landsc Ecol 31:1355–1368

    Article  Google Scholar 

  66. Hameed S, et al (2020) Identifying priority landscapes for conservation of snow leopards in Pakistan. PloS One 15(11):e0228832

  67. Gangadharan A, Vaidyanathan S, St. Clair CC (2017) Planning connectivity at multiple scales for large mammals in a human-dominated biodiversity hotspot. J Nat Conserv 36: 38–47

  68. Anitha K et al (2013) Identifying habitat connectivity for isolated populations of lion-Tailed Macaque (Macaca silenus) in Valparai Plateau, Western Ghats India. Primate Conserv 27:91–97

    Article  Google Scholar 

  69. Tobgay S, Mahavik N (2020) Potential habitat distribution of Himalayan red panda and their connectivity in Sakteng Wildlife Sanctuary Bhutan. Ecol Evol. https://doi.org/10.1002/ece3.6874

    Article  Google Scholar 

  70. Puyravaud J-P, Cushman SA, Davidar P, Madappa D (2017) Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation. Anim Conserv 20:225–234

    Article  Google Scholar 

  71. Yumnam B, et al (2014) Prioritizing tiger conservation through landscape genetics and habitat linkages. PloS One 9(11):e111207

  72. Goparaju L, Ahmad F, Sinha D (2018) Spatial analysis of wildlife habitat around Madihan forests of Mirzapur district, Uttar Pradesh in India, using geospatial technology. Folia For Pol Ser A 60:73–79

    Google Scholar 

  73. Sharma S et al (2013) Spatial genetic analysis reveals high connectivity of tiger (Panthera tigris) populations in the Satpura-Maikal landscape of Central India. Ecol Evol 3:48–60

    Article  Google Scholar 

  74. Reddy PA, Puyravaud J-P, Cushman SA, Segu H (2019) Spatial variation in the response of tiger gene flow to landscape features and limiting factors. Anim Conserv 22:472–480

    Article  Google Scholar 

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

  76. Reddy PA, Cushman SA, Srivastava A, Sarkar MS, Shivaji S (2017) Tiger abundance and gene flow in Central India are driven by disparate combinations of topography and land cover. Divers Distrib 23:863–874

    Article  Google Scholar 

  77. Thapa K, et al (2017) Tigers in the Terai: strong evidence for meta-population dynamics contributing to tiger recovery and conservation in the Terai Arc Landscape. PloS One 12(6):e0177548

  78. Singh R, Qureshi Q, Sankar K, Krausman PR, Goyal SP (2013) Use of camera traps to determine dispersal of tigers in semi-arid landscape, western India. J Arid Environ 98:105–108

    Article  Google Scholar 

  79. Kanagaraj R, Wiegand T, Kramer-Schadt S, Goyal SP (2013) Using individual-based movement models to assess inter-patch connectivity for large carnivores in fragmented landscapes. Biol Conserv 167:298–309

    Article  Google Scholar 

  80. Bagaria P, et al (2020) West to east shift in range predicted for Himalayan Langur in climate change scenario. Glob Ecol Conserv 22:e00926

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

    Article  Google Scholar 

  82. Vasudev D, Fletcher RJ (2015) Incorporating movement behavior into conservation prioritization in fragmented landscapes: an example of western hoolock gibbons in Garo Hills India. Biol Conserv 181:124–132

    Article  Google Scholar 

  83. Yadav BP, Appel A, Shrestha BP, Dahal BR, Dhaka M (2020) The fishing cat Prionailurus viverrinus (Bennet, 1833) (Mammalia: Carnivora: Felidae) in Shuklaphanta National Park Nepal. J Threat Taxa 12:17203–17212

    Article  Google Scholar 

  84. Singh SK et al (2015) Tigers of Sundarbans in India: is the population a separate conservation unit? PloS One 10(4):e0118846

  85. Shrestha B, Kindlmann P (2020) Implications of landscape genetics and connectivity of snow leopard in the Nepalese Himalayas for its conservation. Sci Rep 10:19853

  86. Kachhwaha TS (1993) Temporal and multisensor approach in forest/vegetation mapping and corridor identification for effective management of Rajaji National Park, Uttar Pradesh India. Int J Remote Sens 14:3105–3114

    Article  Google Scholar 

  87. Vasudev D, Goswami VR, Oli MK (2021) Detecting dispersal: a spatial dynamic occupancy model to reliably quantify connectivity across heterogeneous conservation landscapes. Biol Conserv 253:108874

  88. Yapa A, Ratnavira G (2015) The mammals of Sri Lanka. Field ornithology group of Sri Lanka, Department of Zoology, Colombo

  89. Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GA, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858

    Article  CAS  Google Scholar 

  90. Srinivasulu C, Srinivasulu B (2012) South Asian mammals: their diversity, distribution, and status. Springer, New York

    Book  Google Scholar 

  91. Adriaensen F et al (2003) The application of ‘least-cost’ modelling as a functional landscape model. Landsc Urban Plan 64:233–247

    Article  Google Scholar 

  92. Selonen V, Hanski IK (2006) Habitat exploration and use in dispersing juvenile flying squirrels. J Anim Ecol 75:1440–1449

    Article  Google Scholar 

  93. Mateo-Sánchez MC et al (2015) Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data. Ecosphere 6:1–16

    Article  Google Scholar 

  94. McRae BH, Beier P (2007) Circuit theory predicts gene flow in plant and animal populations. Proc Natl Acad Sci 104:19885–19890

    Article  CAS  Google Scholar 

  95. Cushman SA, McKelvey KS, Schwartz MK (2009) Use of empirically derived source-destination models to map regional conservation corridors. Conserv Biol 23:368–376

    Article  Google Scholar 

  96. Rudnick D, et al. (2012) The role of landscape connectivity in planning and implementing conservation and restoration priorities. Issues in Ecology. Report No. 16. Ecological Society of America, Washington, D.C.

  97. Kool JT, Moilanen A, Treml EA (2013) Population connectivity: recent advances and new perspectives. Landsc Ecol 28:165–185

    Article  Google Scholar 

  98. Keeley ATH et al (2018) Making habitat connectivity a reality: habitat Connectivity. Conserv Biol 32:1221–1232

    Article  Google Scholar 

  99. Arlettaz R et al (2010) From publications to public actions: when conservation biologists bridge the gap between research and implementation. Bioscience 60:835–842

    Article  Google Scholar 

  100. Wangchuk S (2007) Maintaining ecological resilience by linking protected areas through biological corridors in Bhutan. Trop Ecol 48:177

    Google Scholar 

  101. Taylor PD, Fahrig L, Henein K, Merriam G (1993) Connectivity is a vital element of landscape structure. Oikos 68:571–573

  102. Naidoo R et al (2018) Evaluating the effectiveness of local- and regional-scale wildlife corridors using quantitative metrics of functional connectivity. Biol Conserv 217:96–103

    Article  Google Scholar 

  103. Day CC, Zollner PA, Gilbert JH, McCann NP (2020) Individual-based modeling highlights the importance of mortality and landscape structure in measures of functional connectivity. Landsc Ecol 35:2191–2208

    Article  Google Scholar 

  104. Baguette M, Van Dyck H (2007) Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal. Landsc Ecol 22:1117–1129

    Article  Google Scholar 

  105. Knowlton JL, Graham CH (2010) Using behavioral landscape ecology to predict species’ responses to land-use and climate change. Biol Conserv 143:1342–1354

    Article  Google Scholar 

  106. Abrahms B et al (2017) Does wildlife resource selection accurately inform corridor conservation? J Appl Ecol 54:412–422

    Article  Google Scholar 

  107. Vasudev D, Fletcher RJ Jr, Goswami VR, Krishnadas M (2015) From dispersal constraints to landscape connectivity: lessons from species distribution modeling. Ecography 38:967–978

    Article  Google Scholar 

  108. Allen AM, Singh NJ (2016) Linking movement ecology with wildlife management and conservation. Front Ecol Evol 3:155

    Article  Google Scholar 

  109. Katzner TE, Arlettaz R (2020) Evaluating contributions of recent tracking-based animal movement ecology to conservation management. Front Ecol Evol 7:519

    Article  Google Scholar 

  110. Hebblewhite M, Haydon DT (2010) Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology. Philos Trans R Soc Lond B Biol Sci 365:2303–2312

  111. Stewart FE, Darlington S, Volpe JP, McAdie M, Fisher JT (2019) Corridors best facilitate functional connectivity across a protected area network. Sci Rep 9:1–9

    Article  Google Scholar 

  112. Wilmers CC et al (2015) The golden age of bio-logging: How animal-borne sensors are advancing the frontiers of ecology. Ecology 96:1741–1753

    Article  Google Scholar 

  113. McClune DW (2018) Joining the dots: reconstructing 3D environments and movement paths using animal-borne devices. Anim Biotele 6:1–9

    Article  Google Scholar 

  114. Fraser KC et al (2018) Tracking the conservation promise of movement ecology. Front Ecol Evol 6:150

    Article  Google Scholar 

  115. DiLeo MF, Wagner HH (2016) A landscape ecologist’s agenda for landscape genetics. Curr Landsc Ecol Rep 1:115–126

    Article  Google Scholar 

  116. Manel S, Holderegger RT (2013) 10 years of landscape genetics. Trends Ecol Evol 28:614–621

    Article  Google Scholar 

  117. Shirk AJ, Landguth EL, Cushman SA (2017) A comparison of individual-based genetic distance metrics for landscape genetics. Mol Ecol Resour 17:1308–1317

    Article  CAS  Google Scholar 

  118. Zeller KA et al (2018) Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data. Divers Distrib 24:868–879

    Article  Google Scholar 

  119. Peterman WE et al (2019) A comparison of popular approaches to optimize landscape resistance surfaces. Landsc Ecol 34:2197–2208

    Article  Google Scholar 

  120. Brodie JF et al (2015) Evaluating multispecies landscape connectivity in a threatened tropical mammal community. Conserv Biol 29:122–132

    Article  Google Scholar 

  121. Gangadharan A, Vaidyanathan S, Clair CCS (2016) Categorizing species by niche characteristics can clarify conservation planning in rapidly-developing landscapes. Anim Conserv 19(5):451–461

  122. Keller D, Holderegger R, van Strien MJ, Bolliger J (2015) How to make landscape genetics beneficial for conservation management? Conserv Genet 16:503–512

    Article  Google Scholar 

  123. Richardson JL, Brady SP, Wang IJ, Spear SF (2016) Navigating the pitfalls and promise of landscape genetics. Mol Ecol 25:849–863

  124. Dudaniec RY et al (2016) Dealing with uncertainty in landscape genetic resistance models: a case of three co-occurring marsupials. Mol Ecol 25:470–486

    Article  Google Scholar 

  125. Engler JO, Balkenhol N, Filz KJ, Habel JC, Rödder D (2014) Comparative landscape genetics of three closely related sympatric hesperid butterflies with diverging ecological traits. PloS One 9(9):e106526

  126. Marrotte RR et al (2017) Multi-species genetic connectivity in a terrestrial habitat network. Mov Ecol 5:1–11

    Article  Google Scholar 

  127. Early R, Thomas CD (2007) Multispecies conservation planning: identifying landscapes for the conservation of viable populations using local and continental species priorities. J Appl Ecol 44:253–262

    Article  Google Scholar 

  128. Magris RA, Treml EA, Pressey RL, Weeks R (2016) Integrating multiple species connectivity and habitat quality into conservation planning for coral reefs. Ecography 39:649–664

    Article  Google Scholar 

  129. Marrec R et al (2020) Conceptual framework and uncertainty analysis for large-scale, species-agnostic modelling of landscape connectivity across Alberta, Canada. Sci Rep 10:1–14

    Article  CAS  Google Scholar 

  130. Costanza JK, Terando AJ (2019) Landscape connectivity planning for adaptation to future climate and land-use change. Curr Landsc Ecol Rep 4:1–13

    Article  Google Scholar 

  131. Gregory R, Failing L, Higgins P (2006) Adaptive management and environmental decision making: a case study application to water use planning. Ecol Econ 58:434–447

    Article  Google Scholar 

  132. Zeller KA, Lewsion R, Fletcher RJ, Tulbure MG, Jennings MK (2020) Understanding the importance of dynamic landscape connectivity. Land 9:303

    Article  Google Scholar 

  133. Osipova L et al (2019) Using step-selection functions to model landscape connectivity for African elephants: accounting for variability across individuals and seasons. Anim Conserv 22:35–48

    Article  Google Scholar 

  134. Ghoddousi A et al (2021) Anthropogenic resistance: accounting for human behavior in wildlife connectivity planning. One Earth 4:39–48

    Article  Google Scholar 

  135. Thekaekara T, Thornton TF (2016) Ethnic diversity and human-elephant conflict in South India. In: Locke P, Buckingham J (eds) Conflict, negotiation, and coexistence: rethinking human-elephant relations in South Asia, 1st edn. Oxford University Press, New Delhi, pp 300–330

  136. Inskip C, Carter N, Riley S, Roberts T, MacMillan D (2016) Toward human-carnivore coexistence: understanding tolerance for tigers in Bangladesh. PloS One 11(1):e0145913

  137. Bhatia S, Redpath SM, Suryawanshi K, Mishra C (2020) Beyond conflict: exploring the spectrum of human–wildlife interactions and their underlying mechanisms. Oryx 54:621–628

    Article  Google Scholar 

  138. Lewis M (2003) Inventing global ecology: tracking the biodiversity ideal in India, 1945–1997. vol. 5. Orient Longman, Hyderabad

  139. Bhagwat S (ed) (2018) Conservation and development in India: reimagining wilderness. Routledge, Abingdon

    Google Scholar 

  140. Carter NH, Linnell JD (2016) Co-adaptation is key to coexisting with large carnivores. Trends Ecol Evol 31:575–578

    Article  Google Scholar 

  141. Srinivasaiah N, Kumar V, Vaidyanathan S, Sukumar R, Sinha A (2019) All-Male groups in Asian elephants: a novel, adaptive social strategy in increasingly anthropogenic landscapes of southern India. Sci Rep 9:1–11

    Article  CAS  Google Scholar 

  142. Majgaonkar I, et al (2019) Land-sharing potential of large carnivores in human-modified landscapes of western India. Conserv Sci Practi 1(5):e34

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Acknowledgements

We would like to thank Pranav Chanchani and Jared Margulies for their informal comments, as well as two anonymous reviewers whose extensive feedback significantly improved the manuscript. We also thank Mansi Monga for data management work during this review to classify a subset of the papers with appropriate tags. Finally, the Coalition for Wildlife Corridors for playing a key role in bringing some of us together to work on this review.

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Thatte, P., Tyagi, A., Neelakantan, A. et al. Trends in Wildlife Connectivity Science from the Biodiverse and Human-Dominated South Asia. J Indian Inst Sci 101, 177–193 (2021). https://doi.org/10.1007/s41745-021-00240-6

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  • DOI: https://doi.org/10.1007/s41745-021-00240-6

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