Skip to main content

Advertisement

Log in

Modeling the climate change impact on the habitat suitability and potential distribution of an economically important hill stream fish, Neolissochilus hexagonolepis, in the Ganges–Brahmaputra basin of Eastern Himalayas

  • Research Article
  • Published:
Aquatic Sciences Aims and scope Submit manuscript

Abstract

Species distribution modeling has been an expedient tool. The optimization of species distribution models for Eastern Himalayan hill stream fishes remains a substantial challenge. This study has constructed a potentially informative species distribution model for an economically important and Near Threatened hill stream fish, Neolissochilus hexagonolepis. The wild habitats of this species along the Ganges–Brahmaputra basin of the Eastern Himalayas are under enormous threat. Initially, 21 predictor variables were selected based on their ecological relevance to stream fish distribution. The maximum entropy (MaxEnt) algorithm was employed to predict the habitat suitability in current and ensemble two future scenarios considering different global circulation models of climate change. Our results suggested that seasonality in annual temperature, precipitation, terrain wetness index, and eco-regional attributes had a higher contribution to the model. The fish species seems to be distributed in freshwater rivers, streams, and headwaters of lower (elevation < 500 m) to medium (elevation < 1000 m) elevation in north-eastern states of India along with other countries of Eastern Himalayas. A potential loss of current-suitable habitats is predicted in future scenarios along the lower altitudes (500 m < elevation < 1000 m). Country-wide shifts appear significant in the analysis of variance. The maximum habitat loss is projected in the sub-Himalayan belt of India and Bangladesh. The results also indicate that this species would tend to disperse towards higher altitudes and northward. Overall, this study emphasizes preserving dispersal connectivity and identifying crucial corridors for this commercially essential cold-water fish species. The stakes of becoming climate change winners for such fish species are low, considering successful colonization to upstream habitats tracking their habitat suitability.

Graphic abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability statement

The raw data are not being submitted presently at this moment. It cannot be reproduced in any other form before the publication of the manuscript. However, it may be shared in the review/revision stage for better analytical clarity.

References

  • Abell R et al (2008) Freshwater ecoregions of the world: a new map of biogeographic units for freshwater biodiversity conservation. Bioscience 58:403–414

    Article  Google Scholar 

  • Akanda AS (2012) South Asia’s water conundrum: hydroclimatic and geopolitical asymmetry, and brewing conflicts in the Eastern Himalayas. Int J River Basin Manag 10:307–315

    Article  Google Scholar 

  • Allan JD (2004) Landscapes and riverscapes: the influence of land use on stream ecosystems. Annu Rev Ecol Evol Syst 35:257–284

    Article  Google Scholar 

  • Alle DJ, Molur S, Daniel BA (2010) The Status and Distribution of Freshwater Biodiversity in the Eastern Himalaya. IUCN, Cambridge, UK and Gland, Switzerland; Zoo Outreach Organization, Coimbatore, India

  • Araújo MB, New M (2007) Ensemble Forecasting of Species Distributions. Trends Ecol Evol 22:42–47

    Article  PubMed  Google Scholar 

  • Arunachalam M (2010) Neolissochilus hexagonolepis (errata version published in 2020). vol e.T166479A174785418. International Union for Conservation of Nature and Natural Resources. https://doi.org/10.2305/IUCN.UK.2010-4.RLTS.T166479A174785418.en

  • Austin M (2007) Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecol Model 200:1–19

    Article  Google Scholar 

  • Barbarossa V, Bosmans J, Wanders N, King H, Bierkens MF, Huijbregts MA, Schipper AM (2021) Threats of global warming to the world’s freshwater fishes. Nature Commun 12:1–10

    Article  CAS  Google Scholar 

  • Beecher HA, Dott ER, Fernau RF (1988) Fish species richness and stream order in Washington State streams. Environ Biol Fishes 22:193–209

    Article  Google Scholar 

  • Bhatt JP, Tiwari S, Pandit MK (2017) Environmental impact assessment of river valley projects in upper Teesta basin of Eastern Himalaya with special reference to fish conservation: a review. Impact Assess Proj Apprais 35:340–350

    Article  Google Scholar 

  • Bonebrake TC, Mastrandrea MD (2010) Tolerance adaptation and precipitation changes complicate latitudinal patterns of climate change impacts. Proc Natl Acad Sci 107:12581–12586

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bradie J, Leung B (2017) A quantitative synthesis of the importance of variables used in MaxEnt species distribution models. J Biogeogr 44:1344–1361

    Article  Google Scholar 

  • Brazner JC, Tanner DK, Detenbeck NE, Batterman SL, Stark SL, Jagger LA, Snarski VM (2005) Regional, watershed, and site-specific environmental influences on fish assemblage structure and function in western Lake Superior tributaries. Canadian J Fish Aquatic Sci 62:1254–1270

    Article  Google Scholar 

  • Buisson L, Blanc L, Grenouillet G (2008) Modelling stream fish species distribution in a river network: the relative effects of temperature versus physical factors. Ecol Freshw Fish 17:244–257

    Article  Google Scholar 

  • Burrows MT et al (2014) Geographical limits to species-range shifts are suggested by climate velocity. Nature 507:492–495

    Article  CAS  PubMed  Google Scholar 

  • Cayuela L et al (2009) Species distribution modeling in the tropics: problems, potentialities, and the role of biological data for effective species conservation. Trop Conserv Sci 2:319–352

    Article  Google Scholar 

  • Chen I-C, Hill JK, Ohlemüller R, Roy DB, Thomas CD (2011) Rapid range shifts of species associated with high levels of climate warming. Science 333:1024–1026

    Article  CAS  PubMed  Google Scholar 

  • Chettri N, Tsering K, Shrestha A, Sharma E (2018) Ecological vulnerability to climate change in the mountains: a case study from the Eastern Himalaya. In: Das AP, Bera S (eds) The Plant Diversity in the Himalaya Hotspot Region. M/s, Bishen Singh Mahendra Pal Singh, Dehradun, India, pp 707–721

    Google Scholar 

  • Chitale V, Behera M, Roy P (2015) Global biodiversity hotspots in India: significant yet under studied. Curr Sci 108:149–150

    Google Scholar 

  • Chucholl C (2017) Niche-based species distribution models and conservation planning for endangered freshwater crayfish in south-western Germany. Aquat Conserv Mar Freshw Ecosyst 27:698–705

    Article  Google Scholar 

  • Clarke K, Gorley R (2006) PRIMER v6: User Manual PRIMER-E Plymouth, UK

  • Comte L, Grenouillet G (2015) Distribution shifts of freshwater fish under a variable climate: comparing climatic, bioclimatic and biotic velocities. Divers Distrib 21:1014–1026

    Article  Google Scholar 

  • Crowley TJ (1983) The geologic record of climatic change. Rev Geophys 21:828–877

    Article  Google Scholar 

  • Dahlke FT, Wohlrab S, Butzin M, Pörtner H-O (2020) Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369:65–70

    Article  CAS  PubMed  Google Scholar 

  • Das B et al (2017) Review of research on fish pass facilities in india. ICAR-Central Inland Fisheries Research Institute, Barrackpore

    Google Scholar 

  • Daufresne M, Roger M, Capra H, Lamouroux N (2004) Long-term changes within the invertebrate and fish communities of the Upper Rhône River: effects of climatic factors. Glob Change Biol 10:124–140

    Article  Google Scholar 

  • Dauwalter DC, Rahel FJ (2008) Distribution modelling to guide stream fish conservation: an example using the mountain sucker in the Black Hills National Forest USA. Aquatic Conserv Marine Freshwr Ecosyst 18:1263–1276

    Article  Google Scholar 

  • Deser C, Phillips A, Bourdette V, Teng H (2012) Uncertainty in climate change projections: the role of internal variability. Climate Dynam 38:527–546

    Article  Google Scholar 

  • Domisch S, Jaehnig SC, Haase P (2011) Climate-change winners and losers: stream macroinvertebrates of a submontane region in Central Europe. Freshw Biol 56:2009–2020

    Article  Google Scholar 

  • Domisch S, Araújo MB, Bonada N, Pauls SU, Jähnig SC, Haase P (2013a) Modelling distribution in E uropean stream macroinvertebrates under future climates. Glob Change Biol 19:752–762

    Article  Google Scholar 

  • Domisch S, Kuemmerlen M, Jähnig SC, Haase P (2013b) Choice of study area and predictors affect habitat suitability projections, but not the performance of species distribution models of stream biota. Ecolog Model 257:1–10

    Article  Google Scholar 

  • Domisch S, Jähnig SC, Simaika JP, Kuemmerlen M, Stoll S (2015) Application of species distribution models in stream ecosystems: the challenges of spatial and temporal scale, environmental predictors and species occurrence data. Fundam Appl LimnolArchiv Für Hydrobiologie 186:45–61

    Article  Google Scholar 

  • Dormann CF et al (2012) Correlation and process in species distribution models: bridging a dichotomy. J Biogeogr 39:2119–2131

    Article  Google Scholar 

  • Durance I, Ormerod S (2009) Trends in water quality and discharge confound long-term warming effects on river macroinvertebrates. Freshw Biol 54:388–405

    Article  CAS  Google Scholar 

  • Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Ann Rev Ecol Evol Syst 40:677–697

    Article  Google Scholar 

  • Elith J (2000) Quantitative Methods for Modeling Species Habitat: Comparative Performance and an Application to Australian Plants. In: Ferson S, Burgman M (eds) Quantitative Methods for Conservation Biology. Springer, New York, pp 39–58. https://doi.org/10.1007/0-387-22648-6_4

  • Eschmeyer WN, Fricke R, Van der Laan R (2017) Catalog of fishes: genera, species, references. https://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp

  • Everard M, Kataria G (2010) The proposed Pancheshwar Dam, India/Nepal: A preliminary ecosystem services assessment of likely outcomes. An IES research report

  • Ferreira MT, Sousa L, Santos JM, Reino L, Oliveira J, Almeida PR, Cortes R (2007) Regional and local environmental correlates of native Iberian fish fauna. Ecol Freshw Fish 16:504–514

    Article  Google Scholar 

  • Ficke AD, Myrick CA, Hansen LJ (2007) Potential impacts of global climate change on freshwater fisheries. Rev Fish Biol Fish 17:581–613

    Article  Google Scholar 

  • Flitcroft R et al (2019) Using expressed behaviour of coho salmon (Oncorhynchus kisutch) to evaluate the vulnerability of upriver migrants under future hydrological regimes: Management implications and conservation planning. Aquatic Conserv Marine Freshwat Ecosyst 29(7):1083–1094

    Article  Google Scholar 

  • Froese R, Pauly D (2010) FishBase. University of British Columbia, Fisheries Centre

    Google Scholar 

  • Galy V, France-Lanord C, Lartiges B (2008) Loading and fate of particulate organic carbon from the Himalaya to the Ganga-Brahmaputra delta. Geochim Cosmochim Acta 72:1767–1787

    Article  CAS  Google Scholar 

  • Gama M, Crespo D, Dolbeth M, Anastácio P (2016) Predicting global habitat suitability for Corbicula fluminea using species distribution models: The importance of different environmental datasets. Ecol Model 319:163–169

    Article  Google Scholar 

  • Gebrekiros S (2016) Factors affecting stream fish community composition and habitat suitability. J Aquac Marine Biol 4:00076

    Google Scholar 

  • Gopal B, Shilpakar R, Sharma E (2010) Functions and services of wetlands in the Eastern Himalayas: impacts of climate change. International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal

  • Goswami UC, Basistha SK, Bora D, Shyamkumar K, Saikia B, Changsan K (2012) Fish diversity of North East India, inclusive of the Himalayan and Indo Burma biodiversity hotspots zones: A checklist on their taxonomic status, economic importance, geographical distribution, present status and prevailing threats. Int J Biodivers Conserv 4:592–613

    Google Scholar 

  • Graham C, Harrod C (2009) Implications of climate change for the fishes of the British Isles. J Fish Biol 74:1143–1205

    Article  CAS  PubMed  Google Scholar 

  • Grenouillet G, Buisson L, Casajus N, Lek S (2011) Ensemble modelling of species distribution: the effects of geographical and environmental ranges. Ecography 34:9–17

    Article  Google Scholar 

  • Gu W, Xu G, Huang T, Wang B (2020) The complete mitochondrial genome of Neolissochilus benasi (Cypriniformes: Cyprinidae). Mitochondrial DNA Part B 5:463–464

    Article  PubMed  PubMed Central  Google Scholar 

  • Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009

    Article  PubMed  Google Scholar 

  • Hannah L (2014) Climate change biology. Academic Press, Amsterdam

    Google Scholar 

  • Hijmans RJ, Phillips S, Leathwick J, Elith J, Hijmans MRJ (2017) Package ‘dismo.’ Circles 9:1–68

    Google Scholar 

  • Hossain MA, Lahoz-Monfort JJ, Burgman MA, Böhm M, Kujala H, Bland LM (2018) Assessing the vulnerability of freshwater crayfish to climate change. Divers Distrib 24:1830–1843

    Article  Google Scholar 

  • IUCN (2020) The IUCN Red List of Threatened Species. Version 2020–2. International Union for Conservation of Nature and Natural Resources. https://www.iucnredlist.org

  • Jackson DA, Peres-Neto PR, Olden JD (2001) What controls who is where in freshwater fish communities the roles of biotic, abiotic, and spatial factors. Canadian J Fish Aqu Sci 58:157–170

    Google Scholar 

  • Johal M (2002) Fish diversity in different habitats in the streams of lower Middle Western Himalayas. Pol J Ecol 50:45–56

    Google Scholar 

  • Jones C, Lowe J, Liddicoat S, Betts R (2009) Committed terrestrial ecosystem changes due to climate change. Nat Geosci 2:484

    Article  CAS  Google Scholar 

  • Jones MC, Dye SR, Fernandes JA, Frölicher TL, Pinnegar JK, Warren R, Cheung WW (2013) Predicting the impact of climate change on threatened species in UK waters. PLoS ONE 8:e54216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kaky E, Nolan V, Alatawi A, Gilbert F (2020) A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants. Ecolog Inform 60:101150

    Article  Google Scholar 

  • Karger DN, Zimmermann NE (2019) Climatologies at High Resolution for the Earth Land Surface Areas CHELSA V1. 2: Technical Specification. Springer Nature, London

    Google Scholar 

  • Khan M, Sinha M (2000) Status of mahseer fisheries in north and north-eastern india with a note on their conservation. J Inland Fish Soc India (India) 32:28–36

  • Kindt R (2018) Ensemble species distribution modelling with transformed suitability values. Environ Model Softw 100:136–145

    Article  Google Scholar 

  • Knouft JH, Ficklin DL (2017) The potential impacts of climate change on biodiversity in flowing freshwater systems. Ann Rev Ecol Evol Syst 48:111–133

    Article  Google Scholar 

  • Kraft NJ et al (2011) Disentangling the drivers of β diversity along latitudinal and elevational gradients. Science 333:1755–1758

    Article  CAS  PubMed  Google Scholar 

  • Kuemmerlen M, Schmalz B, Guse B, Cai Q, Fohrer N, Jähnig SC (2014) Integrating catchment properties in small scale species distribution models of stream macroinvertebrates. Ecol Model 277:77–86

    Article  Google Scholar 

  • Kwon Y-S, Bae M-J, Hwang S-J, Kim S-H, Park Y-S (2015) Predicting potential impacts of climate change on freshwater fish in Korea. Eco Inform 29:156–165

    Article  Google Scholar 

  • Lane MA, Edwards JL (2007) The global biodiversity information facility (GBIF). Systematics Association Special Volume 73:1–3

  • Langhans SD et al (2019) Combining eight research areas to foster the uptake of ecosystem-based management in fresh waters. Aquat Conserv Mar Freshwat Ecosyst 29:1161–1173

    Article  Google Scholar 

  • Laskar BA, Bhattacharjee MJ, Dhar B, Mahadani P, Kundu S, Ghosh SK (2013) The species dilemma of northeast Indian mahseer (Actinopterygii: Cyprinidae): DNA barcoding in clarifying the riddle. PLoS ONE 8:e53704

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lawler JJ, Wiersma YF, Huettmann F (2011) Using species distribution models for conservation planning and ecological forecasting. Predictive species and habitat modeling in landscape ecology. Springer, Berlin, pp 271–290

    Chapter  Google Scholar 

  • Leathwick J, Rowe D, Richardson J, Elith J, Hastie T (2005) Using multivariate adaptive regression splines to predict the distributions of New Zealand’s freshwater diadromous fish. Freshw Biol 50:2034–2052

    Article  Google Scholar 

  • Liu C, Berry PM, Dawson TP, Pearson RG (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28:385–393

    Article  Google Scholar 

  • Mahapatra B, Vinod K (2011) Reproductive biology and artificial propagation of chocolate mahseer Neolissocheilus hexagonolepis (Mc Clelland) in Meghalaya, India. Indian J Fish 58:35–40

    Google Scholar 

  • Majhi SK, Das SK, Rajkhowa D (2013) Effects of elevated water temperature on tolerance and stress in Chocolate mahseer Neolissochilus hexagonolepis: implications for habitat restoration and conservation. Curr Sci 105:379–383

  • Maloney KO, Weller DE, Michaelson DE, Ciccotto PJ (2013) Species distribution models of freshwater stream fishes in Maryland and their implications for management. Environ Model Assess 18:1–12

    Article  Google Scholar 

  • Marak BD (2019) Management and Conservation Effort on Endemic Fish (Tor putitora, Neolissochilus hexagonolepic) in West Garo Hills, Tura. University of Agriculture Technology and Sciences, Meghalaya

    Google Scholar 

  • Mbatudde M, Mwanjololo M, Kakudidi EK, Dalitz H (2012) Modelling the potential distribution of endangered P runus africana (Hookf) Kalkm. in East Africa African. J Ecol 50:393–403

    Google Scholar 

  • McClelland J (1839) Indian Cyprinidae. Asiatic Researchers 19:217–468

  • Menon S, Latif Khan M, Paul A, Peterson AT (2012) Rhododendron species in the Indian Eastern Himalayas: New approaches to understanding rare plant species distributions. Jounral of Amerocan Rhododendron SocietySpring :78–84

  • Menon AGK (2004) Threatened fishes of India and their conservation. Zoological Survey of India, Kolkata

    Google Scholar 

  • Mentges A, Blowes SA, Hodapp D, Hillebrand H, Chase JM (2021) Effects of site-selection bias on estimates of biodiversity change. Conserv Biol 35:688–698

    Article  PubMed  Google Scholar 

  • Mittermeier R et al (2004) Hotspots Revisited: Earth’s Biologically Richest and Most Endangered Terrestrial Ecoregions. Cemex, Mexico City

    Google Scholar 

  • Mukherjee A, Christman MC, Overholt WA, Cuda JP (2011) Prioritizing areas in the native range of hygrophila for surveys to collect biological control agents. Biol Control 56:254–262

    Article  Google Scholar 

  • Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GA, Kent J (2000) Biodiversity Hotspots for Conservation Priorities. Nature 403:853–858

    Article  CAS  PubMed  Google Scholar 

  • Nenzén HK, Araújo M (2011) Choice of threshold alters projections of species range shifts under climate change. Ecol Model 222:3346–3354

    Article  Google Scholar 

  • Pandit SN, Maitland BM, Pandit LK, Poesch MS, Enders EC (2017) Climate change risks, extinction debt, and conservation implications for a threatened freshwater fish: Carmine shiner (Notropis percobromus). Sci Total Environm 598:1–11

    Article  CAS  Google Scholar 

  • Panja S, Podder A, Homechaudhuri S (2020) Evaluation of Aquatic Ecological Systems through dynamics of Ichthyofaunal diversity in a Himalayan torrential river. Murti Limnologica. https://doi.org/10.1016/j.limno.2020.125779

    Article  Google Scholar 

  • Panja S, Podder A, Homechaudhuri S (2021) Understanding the impact of future climatic scenarios upon key environmental factors that determine piscine assemblage of a torrential upland river of Eastern Himalayas, India. Curr Sci 120:1471–1481. https://doi.org/10.18520/cs/v120/i9/1471-1481

    Article  CAS  Google Scholar 

  • Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37

    Article  CAS  PubMed  Google Scholar 

  • Parreira MR, Nabout JC, Tessarolo G, de Souza L-R, Teresa FB (2019) Disentangling uncertainties from niche modeling in freshwater ecosystems. Ecol Model 391:1–8

    Article  Google Scholar 

  • Pathak D, Mool P (2010) Climate change impacts on hazards in the Eastern Himalayas. International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal

  • Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371

    Article  Google Scholar 

  • Pelletier J et al (2016) Global 1-km gridded thickness of soil, regolith, and sedimentary deposit layers ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1304

  • Petr T (1999) Coldwater Fish and Fisheries in Bhutan. Food Agric Organ Fish Techn Paper 385:6–12

    Google Scholar 

  • Phillips SJ (2005) A Brief Tutorial on Maxent AT&T. Research 190:231–259

    Google Scholar 

  • Phillips SJ, Dudík M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161–175

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259

    Article  Google Scholar 

  • Platts WS (1979) Relationships among stream order, fish populations, and aquatic geomorphology in an Idaho river drainage. Fisheries 4:5–9

    Article  Google Scholar 

  • Raghavan R, Philip S, Dahanukar N, Ali A (2013) Freshwater biodiversity of India: a response to Sarkar etal. Rev Fish Biold Fisheries 23:547–554

    Article  Google Scholar 

  • Riahi K et al (2011) RCP A scenario of comparatively high greenhouse gas emissions. Clim Change 109:33

    Article  CAS  Google Scholar 

  • Roy S, Ray S, Saikia SK (2021) Indicator environmental variables in regulating the distribution patterns of small freshwater fish Amblypharyngodon mola in India and Bangladesh. Ecol Ind 120:106906. https://doi.org/10.1016/j.ecolind.2020.106906

    Article  Google Scholar 

  • Rudra K (2018) Rivers of the Tarai–Doors and Barind Tract. In: Rudra K (ed) Rivers of the Ganga-Brahmaputra-Meghna Delta: A Fluvial Account of Bengal. Geography of the Physical Environment Springer, Cham, pp 27–47. https://doi.org/10.1007/978-3-319-76544-0_3

  • Ruiz-Luna A, Hernández-Guzmán R, García-De León FJ, Ramírez-Huerta AL (2017) Potential distribution of endangered Mexican golden trout (Oncorhynchus chrysogaster) in the Rio Sinaloa and Rio Culiacan basins (Sierra Madre Occidental) based on landscape characterization and species distribution models. Environm Biol Fish 100:981–993

    Article  Google Scholar 

  • Sanderson BM, Knutti R, Caldwell P (2015) A representative democracy to reduce interdependency in a multimodel ensemble. J Clim 28:5171–5194

    Article  Google Scholar 

  • Sarma D, Jha GN (2010) Effect of Spirulina fortified diets on growth and survival of chocolate mahseer (Neolissochilus hexagonolepis). Indian J Animal Nutr 27:441–446

    Google Scholar 

  • Sarma D, Sanwal S, Jha GN, Mahanta PC (2012) Species specificity of Chocolate Mahseer (Neolissochilus hexagonolepis) and Malaysian Mahseer (Neolissochilus soroides). J Inland Fish Soc India 43:27–32

  • Sharma E, Tse-ring K, Chettri N, Shrestha A, Kathmandu N (2008) Biodiversity in the Himalayas–trends, perception and impacts of climate change. In: Proceedings of the International Mountain Biodiversity Conference. Kathmandu, Nepal

  • Sharma E, Chettri N, Tse-Ring K, Shrestha A, Jing F, Mool P, Eriksson M (2009) Climate change impacts and vulnerability in the Eastern Himalayas. ICIMOD. Kathmandu, Nepal

  • Sharma L, Ali S, Siva C, Kumar R, Barat A, Sahoo PK, Pande V (2019) Genetic diversity and population structure of the threatened chocolate mahseer (Neolissochilus hexagonolepis McClelland 1839) based on SSR markers: implications for conservation management in Northeast India. Mol Biol Rep 46:5237–5249

    Article  CAS  PubMed  Google Scholar 

  • Sharma A, Dubey VK, Johnson JA, Rawal YK, Sivakumar K (2021) Is there always space at the top? Ensemble modeling reveals climate-driven high-altitude squeeze for the vulnerable snow trout Schizothorax richardsonii in Himalaya. Ecolog Indic 120:106900

    Article  Google Scholar 

  • Sharma L et al (2019) Molecular identification and genetic diversity analysis of Chocolate mahseer (Neolissochilus hexagonolepis) populations of Northeast India, using mitochondrial DNA markers. Mitochond DNA Part A 30:397–406

    Article  CAS  Google Scholar 

  • Shrestha J (2002) Taxonomic revision of cold water fishes of Nepal. FAO Fish Techn Paper 273–288

  • Shuter B, Post J (1990) Climate, population viability, and the zoogeography of temperate fishes. Trans Am Fish Soc 119:314–336

    Article  Google Scholar 

  • Singh RB (2015) Urban development challenges, risks and resilience in asian mega cities. Springer, Japan

    Book  Google Scholar 

  • Singh A, Akhtar M (2015) Coldwater fish diversity of India and its sustainable development. UP Biodiversity Board, Lucknow

    Google Scholar 

  • Singh A, Kumar P, Ali S Ichthyofaunal Diversity of the Ganges River System in Central Himalayas, India: Conservation Status and Priorities. In: Sinha RK, Ahmed B (eds) International Symposium on River Biodiversity: Ganges-Brahmaputra-Meghna River System, Ecosystems for Life, A Bangladesh-India Initiative., New Delhi, 2014. Rivers for Life. International Union for Conservation of Nature, pp 208–214

  • Singh A (2006) Chemistry of arsenic in groundwater of Ganges–Brahmaputra river basin. Curr Sci 91:599–606

  • Smale DA, Wernberg T (2013) Extreme climatic event drives range contraction of a habitat-forming species. Proc Royal Soc B Biol Sci 280:20122829

    Article  Google Scholar 

  • Subba S, Mahaseth VK, Subba RB, Bhusal RD (2020) Monthly dynamics of reproductive indices of Neolissochilus hexagonolepis (McClelland, 1839) and their relationship with physico-chemical parameters along the mid-reaches of Tamor River, Nepal Egyptian. J Aqu Biol Fish 24:239–247

    Google Scholar 

  • Swar DB (1994) A study on the ecology of katle, Neolissochilus hexagonolepis (McClelland), in a Nepalese reservoir and river. The University of Manitoba

  • Taylor AT, Hafen T, Holley CT, González A, Long JM (2020) Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA. Ecol Evol 10:705–717

    Article  PubMed  Google Scholar 

  • Team R (2015) RStudio: integrated development for R RStudio, Boston, MA https://www.rstudio.com/

  • Team RC (2013) R: A language and environment for statistical computing

  • Tedesco PA et al (2017) A global database on freshwater fish species occurrence in drainage basins. Scientific Data 4:170141

    Article  PubMed  PubMed Central  Google Scholar 

  • Thuiller W, Georges D, Engler R, Breiner F (2014) Ensemble platform for species distribution modelling. R Package Version:3.1–64

  • Tingley MW, Koo MS, Moritz C, Rush AC, Beissinger SR (2012) The push and pull of climate change causes heterogeneous shifts in avian elevational ranges. Glob Change Biol 18:3279–3290

    Article  Google Scholar 

  • Tingley MW, Darling ES, Wilcove DS (2014) Fine-and coarse-filter conservation strategies in a time of climate change. Ann New York Acad Sci 1322:92–109

    Article  Google Scholar 

  • Tiwari PC, Tiwari A, Joshi B (2018) Urban growth in himalaya: understanding the process and options for sustainable development. J Urban Reg Stud Contemp India 4:15–27

    Google Scholar 

  • Tse-ring K, Sharma E, Chettri N, Shrestha AB (2010) Climate change vulnerability of mountain ecosystems in the Eastern Himalayas. International centre for integrated mountain development (ICIMOD), Kathmandu, Nepal

  • Van Vuuren DP et al (2011) The representative concentration pathways: an overview. Clim Change 109:5

    Article  Google Scholar 

  • Van Zuiden TM, Chen MM, Stefanoff S, Lopez L, Sharma S (2016) Projected impacts of climate change on three freshwater fishes and potential novel competitive interactions. Divers Distrib 22:603–614

    Article  Google Scholar 

  • Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE (1980) The river continuum concept Canadian. J Fish Aquat Sci 37:130–137

    Article  Google Scholar 

  • Vattakaven T, George RM, Balasubramanian D, Réjou-Méchain M, Muthusankar G, Ramesh BR, Prabhakar R (2016) India Biodiversity Portal: An integrated, interactive and participatory biodiversity informatics platform. Biodivers Data J. https://doi.org/10.3897/BDJ.4.e10279

    Article  PubMed  PubMed Central  Google Scholar 

  • Vignali SBA, Braunisch V (2020) SDMtune: Species Distribution Model Selection. R Package Version 1(1):1

    Google Scholar 

  • Walther G-R et al (2002) Ecological Responses to Recent Climate Change. Nature 416:389

    Article  CAS  PubMed  Google Scholar 

  • Warton DI, Wright ST, Wang Y (2012) Distance-based multivariate analyses confound location and dispersion effects. Methods Ecol Evol 3:89–101

    Article  Google Scholar 

  • Williams JN, Seo C, Thorne J, Nelson JK, Erwin S, O’Brien JM, Schwartz MW (2009) Using species distribution models to predict new occurrences for rare plants. Divers Distrib 15:565–576

    Article  Google Scholar 

  • WWF (2005) Ecosystem Profile: Eastern Himalayas Region WWF-US, Asia Program

  • Xiao-yong C, Jun-xing Y (2003) A Systematic Revision of ‘‘Barbodes’’ Fishes in China. Zoological Research 24:377–386

  • Yamazaki D, Ikeshima D, Sosa J, Bates PD, Allen GH, Pavelsky TM (2019) MERIT Hydro: a high-resolution global hydrography map based on latest topography dataset. Water Resour Res 55:5053–5073

    Article  Google Scholar 

  • Yousefi M et al (2019) Climate change is a major problem for biodiversity conservation: a systematic review of recent studies in Iran. Contemp Probl Ecol 12:394–403

    Article  Google Scholar 

  • Yousefi M, Ahmadi M, Nourani E, Behrooz R, Rajabizadeh M, Geniez P, Kaboli M (2015) Upward altitudinal shifts in habitat suitability of mountain vipers since the last glacial maximum. PLoS ONE 10:e038087

    Article  CAS  Google Scholar 

  • Yousefi M, Jouladeh-Roudbar A, Kafash A (2020) Using endemic freshwater fishes as proxies of their ecosystems to identify high priority rivers for conservation under climate change. Ecol Ind 112:106137

    Article  Google Scholar 

Download references

Acknowledgements

The authors of this study sincerely acknowledge DST INSPIRE-AORC for the financial support of this research (Sanction No. DST/INSPIRE Fellowship/2016/IF160059). The authors further acknowledge the Department of Zoology, the University of Calcutta, to provide the facilities and frameworks. We also thank Advarbit Creative Solutions for supporting graphical artworks. We highly appreciate the reviewers for giving valuable inputs, which has improved the content and readability of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

SP: idea formulation, data modeling, data analysis, interpretation of results, and writing manuscript. AP: data analysis, reviewing the manuscript. SH: idea formulation, interpretation of results, editing, and reviewing the manuscript.

Corresponding author

Correspondence to Sumit Homechaudhuri.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2144 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Panja, S., Podder, A. & Homechaudhuri, S. Modeling the climate change impact on the habitat suitability and potential distribution of an economically important hill stream fish, Neolissochilus hexagonolepis, in the Ganges–Brahmaputra basin of Eastern Himalayas. Aquat Sci 83, 66 (2021). https://doi.org/10.1007/s00027-021-00820-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00027-021-00820-9

Keywords

Navigation