Current Science

Open Access Open Access  Restricted Access Subscription Access

Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment


Affiliations
1 Department of Botany, North-Eastern Hill University, Shillong 793 022, India
2 Department of Botany, University of Kashmir, Srinagar 190 006, India
3 Department of Botany, Tripura University, Suryamaninagar, Agartala 799 022, India
4 G.B. Pant National Institute of Himalayan Environment and Sustainable Development, Himachal Unit, Mohal-Kullu 175 101, India
5 Department of Botany, Sikkim University, Gangtok 737 102, India
6 Department of Basic Science and Social Science, School of Technology, North-Eastern Hill University, Shillong 793 022, India
 

Categorization of species under different threat classes is a pre-requisite for planning, management and monitoring of any species conservation programme. However, data availability, particularly at the population level, has been a major bottleneck in the correct categorization of threatened species. Till date, threat assessments have been mostly based on expert opinion and/or herbarium records. The availability of primary data on distribution of species and their p opulation attributes is limited in India because of inadequate field survey, which has been ascribed to resource constraints and inaccessibility. In this study, we demonstrate that ecological niche modelling (ENM) can be an economical and effective tool to guide surveys overcoming the above two constraints leading to the discovery of new populations of threatened species. Such data lead to improved threat assessment and more accurate categorization. We selected 14 threatened plants comprising 5 trees (Acer hookeri Miq., Bhesa robusta (Roxb.) Ding Hou, Gynocardia odorata Roxb., Ilex venulosa Hook. f. and Lagerstroemia minuticarpa Debb. ex P.C. Kanjilal), 8 herbs (Angelica glauca Edgew., Aquilegia nivalis Falc. ex Jackson, Artemisia amygdalina DC., Begonia satrapis C.B. Clarke, Corydalis cashmeriana Royle, Dactylorhiza hatagirea (D. Don) Soo, Podophyllum hexandrum Royle, and Rheum australe D. Don), and 1 pteridophyte (Angiopteris evecta (Forst.) Hoffm.) having distribution range in North East India, Eastern and Western Himalaya, and Jammu and Kashmir. The study was carried out between 2012 and 2016. ENM-based survey led to the discovery and characterization of 348 new populations. The data so obtained helped in assigning conservation status to 10 species, which earlier were never classified due to data deficiency. Using the new population and distribution data of the remaining four species, only one was confirmed regarding its existing status and two species were classified as ‘Critically endangered’ instead of the present classification as ‘Endangered’. The fourth species was classified as ‘Critically endangered’ against the earlier category of ‘Least concerned’.

Keywords

Niche Modelling, Population Characterization, Threatened Plants, Threat Assessment.
User
Notifications
Font Size

  • Master, L. L., Assessing threats and setting priorities for conservation. Conserv. Biol., 1991, 5(4), 559–563.

  • Mace, G. M. and Lande, R., Assessing extinction threats: toward a reevaluation of IUCN threatened species categories. Conserv. Biol., 1991, 5(2), 148–157.

  • Moran, D. and Kanemoto, K., Identifying species threat hotspots from global supply chains. Nature Ecol. Evol., 2017, 1, 0023.

  • Schemske, D. W., Husband, B. C., Ruckelshaus, M. H., Goodwillie, C., Parker, I. M. and Bishop, J. G., Evaluating approaches to the conservation of rare and endangered plants. Ecology, 1994, 75(3), 584–606.

  • Hortal, J., de Bello, F., Diniz-Filho, J. A. F., Lewinsohn, T. M., Lobo, J. M. and Ladle, R. J., Seven shortfalls that beset large-scale knowledge of biodiversity. Annu. Rev. Ecol., Evol. Syst., 2015, 46, 523–549.

  • Margules, C. R. and Pressey, R. L., Systematic conservation planning. Nature, 2000, 405(6783), 243–253.

  • Elzinga, C. L., Salzer, D. W., Willoughby, J. W. and Gibbs, J. P., Monitoring Plant and Animal Populations: A Handbook for Field Viologists, John Wiley, Oxford, 2009.

  • Vollmar, A., Macklin, J. A. and Ford, L., Natural history specimen digitization: challenges and concerns. Biodiver. Inform., 2010, 7(2), 93–112.

  • Otegui, J., Arino, A. H., Encinas, M. A. and Pando, F., Assessing the primary data hosted by the Spanish node of the Global Biodiversity Information Facility (GBIF). PLOS ONE, 2013, 8(1), e55144.

  • Williams, J. N., Seo, C., Thorne, J., Nelson, J. K., Erwin, S., O’Brien, J. M. and Schwartz, M. W., Using species distribution models to predict new occurrences for rare plants Divers. Distrib., 2009, 15(4), 565–576.

  • Kumar, S. and Stohlgren, T. J., Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. J. Ecol. Nat. Environ., 2009, 1(4), 094–098.

  • Menon, S., Choudhury, B. I., Khan, M. L. and Peterson, A. T., Ecological niche modeling and local knowledge predict new populations of Gymnocladus assamicus a critically endangered tree species. Endanger. Species Res., 2010, 11, 175–181.

  • Adhikari, D., Barik, S. K. and Upadhaya, K., Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India. Ecol. Eng., 2012, 40, 37–43.

  • Elith, J. and Leathwick, J. R., Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol., Evol., Syst., 2009, 40(1), 677.

  • Peterson, A. T., Soberón, J. and Sánchez-Cordero, V., Conservatism of ecological niches in evolutionary time. Science, 1999, 285(5431), 1265–1267.

  • Balakrishnan, N. P., Flora of Jowai, Meghalaya Vol. I and II, Botanical Survey of India, Howrah, 1981–1983.

  • Deb, D. B., The Flora of Tripura State, Today and Tomorrows’ Printers and Publishers, New Delhi, 1981, vol. I.

  • Hajra, P. K., Verma, D. M. and Giri, G. S., Materials for the Flora of Arunachal Pradesh, Botanical Survey of India, 1996.

  • Haridasan, K. and Rao, R. R., Forest Flora of Meghalaya, Dehradun, 1985.

  • Hooker, J. D., JD 1872–1897. The Flora of British India, Bishen Singh Mahendra Pal Singh, Dehra Dun, India, 1973, vols 1–7.

  • Nayar, M. P. and Sastry, A. R. K., Red Data Book of Indian Plants, Botanical Survey of India, Calcutta, 1987, vol. I.

  • Nayar, M. P. and Sastry, A. R. K., Red Data Book of Indian Plants, Botanical Survey of India, Calcutta, 1988, vol. II.

  • Nayar, M. P., Sastry, A. R. K., Red Data Book of Indian Plants, Botanical Survey of India, Calcutta, 1990, vol. III.

  • Jain, S. K. and Rao, R. R., Assessment of threatened plants of India. In Seminar on Threatened Plants of India (1981: Dehra Dun), Botanical Survey of India, 1983.

  • Joseph, J., Flora of Nongpoh and vicinity: east Khasi Hills District, Meghalaya. Meghalaya Forest Department, Meghalaya, iv, 376, 86.

  • Kanjilal, V. N., Kanjilal, P. C., Das, A., De, R. N. and Bor, N. L., Flora of Assam, 5 Vols, Government Press, Shillong, 1934–1940.

  • Kataki, S. K.. Orchids of Meghalaya, Forest Department, Government of Meghalaya, Shillong, 1986, p. 258.

  • Peterson, A. T., and Nakazawa, Y., Environmental datasets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri. Global Ecol. Biogeogr., 2008, 17(1), 135–144.

  • Dilts, T. E., Weisberg, P. J., Dencker, C. M. and Chambers, J. C., Functionally relevant climate variables for arid lands: a climatic water deficit approach for modelling desert shrub distributions. J. Biogeogr., 2015, 42(10), 1986–1997.

  • Jetz, W., Cavender-Bares, J., Pavlick, R., Schimel, D., Davis, F. W., Asner, G. P. and Schaepman, M. E., Monitoring plant functional diversity from space. Nature Plants, 2016, 2, 16024.

  • Trabucco, A., and Zomer, R. J., Global Aridity Index (GlobalAridity) and Global Potential Evapo-Transpiration (Global-PET) Geospatial Database. CGIAR Consortium for Spatial Information. published online, available from the CGIAR-CSI GeoPortal at: http://www.cgiar-csi.org/data/global-aridity-and-pet-database

  • Hirosawa, Y., Marsh, S. E. and Kliman, D. H., Application of standardized principal component analysis to land-cover characterization using multitemporal AVHRR data. Remote Sensing Environ., 1996, 58(3), 267–281.

  • Giovanelli, J. G., de Siqueira, M. F., Haddad, C. F. and Alexandrino, J., Modeling a spatially restricted distribution in the Neotropics: how the size of calibration area affects the performance of five presence-only methods. Ecol. Model., 2010, 221(2), 215–224.

  • Barve, N. et al., The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecol. Model., 2011, 222(11), 1810–1819.

  • Phillips, S. J., Anderson, R. P. and Schapire, R. E., Maximum entropy modeling of species geographic distributions. Ecol. Model., 2006, 190(3), 231–259.

  • Merow, C., Smith, M. J. and Silander, J. A., A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography, 2013, 36(10), 1058–1069.

  • Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J., A statistical explanation of MaxEnt for ecologists. Divers. Distrib., 2011, 17(1), 43–57.

  • Thuiller, W., Richardson, D. M., Pyšek, P., Midgley, G. F., Hughes, G. O. and Rouget, M., Niche‐based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Global Change Biol., 2005, 11(12), 2234–2250.

  • Lobo, J. M., Jiménez‐Valverde, A. and Real, R., AUC: a misleading measure of the performance of predictive distribution models. Global Ecol. Biogeogr., 2008, 17(2), 145–151.

  • Peterson, A. T., Papeş, M. and Soberón, J., Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Model., 2008, 213(1), 63–72.

  • IUCN Red List Categories and Criteria: Version 3.1, ICUN, Gland, Switzerland, UK, 2012, 2nd edn, pp. iv + 32.

  • Moat, J.. Conservation assessment tools extension for ArcView 3.x, version 1.2. GIS Unit, Royal Botanic Gardens, Kew, 2007; available at: http://www.rbgkew.org.uk/gis/cats

  • Adhikari, D., Tiwary, R. and Barik, S. K., Modelling hotspots for invasive alien plants in India. PLOS ONE, 2015, 10(7), e0134665.


Abstract Views: 502

PDF Views: 150




  • Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment

Abstract Views: 502  |  PDF Views: 150

Authors

D. Adhikari
Department of Botany, North-Eastern Hill University, Shillong 793 022, India
Z. Reshi
Department of Botany, University of Kashmir, Srinagar 190 006, India
B. K. Datta
Department of Botany, Tripura University, Suryamaninagar, Agartala 799 022, India
S. S. Samant
G.B. Pant National Institute of Himalayan Environment and Sustainable Development, Himachal Unit, Mohal-Kullu 175 101, India
A. Chettri
Department of Botany, Sikkim University, Gangtok 737 102, India
K. Upadhaya
Department of Basic Science and Social Science, School of Technology, North-Eastern Hill University, Shillong 793 022, India
M. A. Shah
Department of Botany, University of Kashmir, Srinagar 190 006, India
P. P. Singh
Department of Botany, North-Eastern Hill University, Shillong 793 022, India
R. Tiwary
Department of Botany, North-Eastern Hill University, Shillong 793 022, India
K. Majumdar
Department of Botany, Tripura University, Suryamaninagar, Agartala 799 022, India
A. Pradhan
Department of Botany, Sikkim University, Gangtok 737 102, India
M. L. Thakur
G.B. Pant National Institute of Himalayan Environment and Sustainable Development, Himachal Unit, Mohal-Kullu 175 101, India
N. Salam
Department of Botany, University of Kashmir, Srinagar 190 006, India
Z. Zahoor
Department of Botany, University of Kashmir, Srinagar 190 006, India
S. H. Mir
Department of Botany, University of Kashmir, Srinagar 190 006, India
Z. A. Kaloo
Department of Botany, University of Kashmir, Srinagar 190 006, India
S. K. Barik
Department of Botany, North-Eastern Hill University, Shillong 793 022, India

Abstract


Categorization of species under different threat classes is a pre-requisite for planning, management and monitoring of any species conservation programme. However, data availability, particularly at the population level, has been a major bottleneck in the correct categorization of threatened species. Till date, threat assessments have been mostly based on expert opinion and/or herbarium records. The availability of primary data on distribution of species and their p opulation attributes is limited in India because of inadequate field survey, which has been ascribed to resource constraints and inaccessibility. In this study, we demonstrate that ecological niche modelling (ENM) can be an economical and effective tool to guide surveys overcoming the above two constraints leading to the discovery of new populations of threatened species. Such data lead to improved threat assessment and more accurate categorization. We selected 14 threatened plants comprising 5 trees (Acer hookeri Miq., Bhesa robusta (Roxb.) Ding Hou, Gynocardia odorata Roxb., Ilex venulosa Hook. f. and Lagerstroemia minuticarpa Debb. ex P.C. Kanjilal), 8 herbs (Angelica glauca Edgew., Aquilegia nivalis Falc. ex Jackson, Artemisia amygdalina DC., Begonia satrapis C.B. Clarke, Corydalis cashmeriana Royle, Dactylorhiza hatagirea (D. Don) Soo, Podophyllum hexandrum Royle, and Rheum australe D. Don), and 1 pteridophyte (Angiopteris evecta (Forst.) Hoffm.) having distribution range in North East India, Eastern and Western Himalaya, and Jammu and Kashmir. The study was carried out between 2012 and 2016. ENM-based survey led to the discovery and characterization of 348 new populations. The data so obtained helped in assigning conservation status to 10 species, which earlier were never classified due to data deficiency. Using the new population and distribution data of the remaining four species, only one was confirmed regarding its existing status and two species were classified as ‘Critically endangered’ instead of the present classification as ‘Endangered’. The fourth species was classified as ‘Critically endangered’ against the earlier category of ‘Least concerned’.

Keywords


Niche Modelling, Population Characterization, Threatened Plants, Threat Assessment.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi03%2F519-531