Reference
Brockhaus, T. and Hartmann, A. (2009). New records of Epiophlebia laidlawi Tillyard, 1921 in Bhutan with notes on its biology, ecology, distribution, zoogeography and threat status (Anisozygoptera: Epiophlebiidae). Odonatologica , 38: 203-215.
Brown J. L. (2014). SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses.Methods in Ecology and Evolution , DOI: 10.1111/2041-210X.12200.
Brown J. L., Bennett J. R. and French, C. M. (2017). SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.PeerJ 5:e4095; DOI 10.7717/peerj.4095.
Bybee, S., Cόrdoba-Aguilar, A., Duryea, M. C., Futahashi, R., Hansson, B., Lorenzo-Carballa, M. O… Wellenreuther, M. (2016). Odonata (dragonflies and damselflies) as a bridge between ecology and evolutionary genomics. Frontiers in Zoology, 13: 46. DOI 10.1186/s12983-016-0176-7.
Coxen, C. L., Frey, J. K., Carleton, S. A. and Collins, D. P. (2017). Species distribution models for a migratory bird based on citizen science and satellite tracking data. Global Ecology and Conservation , 11: 298-311. https://doi.org/10.1016/j.gecco.2017.08.001
Darwall, W., Bremerich, V., De Wever, A., Dell A. I., Freyhof, J., Gessner, M. O., … Weyl, O. (2018). The Alliance for Freshwater Life : A global call to unite efforts for freshwater biodiversity science and conservation. Aquatic Conservation: Marine and Freshwater Ecosystems , 28: 1015-1022.https://doi.org/10.1002/aqc.2958
Dorji, T. (2015). New distribution records of Epiophlebia laidlawi Tillyard, 1921 (Insecta: Odonata) in Bhutan. Journal of Threatened Taxa , 7:7668-7675.
Elith, J., Graham, C.H., Anderson, R.P., Dudík, M., Ferrier, S., Guisan, A., … Zimmermann, N.E. (2006). Novel methods improve prediction of species’ distributions from occurrence data. Ecography , 29: 129-151.
Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, Y.E. and Yates, C.J. (2011). A statistical explanation of Maxent for ecologists.Diversity and Distribution , 17: 43-57.
Fick, S. E. and Hijmans, R. J. (2017). worldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology , 37: 4302-4315. DOI: 10.1002/joc.5086
Galante, P. J., Alade, B., Muscarella, R., Jansa, S. A., Goodman, S. M. and Anderson, R. P. (2018). The challenge of modelling niches and distributions for data-poor species: a comprehensive approach to model complexity. Ecography , 41: 726-736. DOI:10.1111/ecog.02909
Gomez, V. H. F., lJff, S. D., Raes, N., Amaral, l. L.,Salomão, R. P., Coelho, L. d. S…Steege, H. t. (2018). Species distribution modelling: contrasting presence-only models with plot abundance data.Scientific Reports , 8: 1003. DOI:10.1038/s41598-017-18927-1
Guisan, A., Tingley, R., Baumgartner, J.B., Naujokaitis-Lewis, I., Sutcliffe, P.R., Tulloch, A.I.T., … Buckley, Y.M. (2013). Predicting species distributions for conservation decisions.Ecology Letters , 16: 1424–1435.
Gyeltshen, C., Tobgay, K., Gyeltshen, N., Dorji, T., and Dema, S. (2018). New species discoveries and records in Bhutan Himalaya. In M. Hartmann, M. V. L. Barclay and J. Weipert. (Eds.), Biodiversität und Naturausstattungim Himalaya / Biodiversity and Natural Heritage of the Himalaya, vol. VI (pp. 59-82). Erfurt: Naturkundemuseum Erfurt.
Kass, J. M., Vilela, B., Aiello-Lammens, M. E., Muscarella, R., Merow, C. and Anderson, R. P. (2017). WALLACE: a flexible platform for reproducible modelling of species niches and distributions built for community expansion. Methods in Ecology and Evolution , 9: 1151-1156. DOI.10.1111/2041-210x.12945.
Kramer-Schadt, S, Niedballa, J., Pilgrim, J.D., Schroder, B., Lindenborn, J., Reinfelder, V… Wilting, A. (2013). The importance of correcting for sampling bias in MaxEnt species distribution models.Diversity and Distribution , 19:1366-1379.
Lehner, B. and Grill, G. (2013). Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrological Processes, 27: 2171–2186. Data is available at www.hydrosheds.org.
Liu, C., Newell, G. and White, M. (2016). On the selection of thresholds for predicting species occurrence with presence-only data. Ecology and Evolution , 6: 337–348.
Marco Junior, P. D. and Nóbrega, C. C. (2018). Evaluating collinearity effects on species distribution models: an approach based on virtual species simulation. PLoS ONE , 13, e0202403.https://doi.org/10.1371/journal.pone.0202403
McGarvey, D.J., Menon, M., Woods, T., Tassone , S., Reese, J., Vergamini, M. and Kellogg, E. (2018). On the use of climate covariates in aquatic species distribution models: are we at risk of throwing out the baby with the bath water? Ecography , 41: 695-712.
Merow, C., Smith, M.J. and Silander, Jr J.A. (2013). A practical guide to Maxent for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography , 36:1058-1069.
Morales, N. S., Fernández, I. C., & Baca-González, V. (2017). MaxEnt’s parameter configuration and small samples: are we paying attention to recommendations? A systematic review. PeerJ5 , e3093. doi:10.7717/peerj.3093
Mukaka, M. M. (2012). Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Medical Journal , 24: 67-71.
Muscarella, R., Galante, P. J., Soley-Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M. and Anderson, R. P. (2014). ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in Ecology and Evolution , 5: 1198-1205. Doi:10.1111/2041-210X.12261.
National Biodiversity Centre. (2014). National biodiversity strategies and action plan of Bhutan 2014 . NBC, Ministry of Agriculture and Forests, Royal Government of Bhutan, Thimphu.
Norris, D. (2014). Model thresholds are more important than presence location type: understanding the distribution of lowland tapir (Tapirusterrestris ) in a continuous Atlantic forest of southeast Brazil. Tropical Conservation Science , 7: 529-547.
Pereira, D. G., Afonso, A. and Medeiros, F. M. (2015). Overview of Friedman’s test and post-hoc analysis. Communications in Statistics - Simulation and Computation , 44:10, 2636-2653, DOI: 10.1080/03610918.2014.931971
Pearson, R. G., Raxworthy, C. J., Nakamura, M., & Peterson, A. T. (2007). Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography, 34 , 102-117.
Phillips, S. J. (2017). A brief tutorial on Maxent. Available fromhttp://biodiversityinformatics.amnh.org/open_source/maxent/. Accessed on 10. 02.2018.
Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. and Blair, M. E. (2017). Opening the black box: an open-source release of Maxent.Ecography, 40: 887-893.
Phillips, S.J., Anderson, R.P. and Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling , 190: 231–259.
Phillips, S.J. and Dudík, M. (2008). Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation.Ecography , 31:161-175.
Phillips, S. J., Dudík, M., Elith, J., Graham, C. H., Lehmann, A… Ferrier, S. (2009). Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data.Ecological Applications , 19: 181-197.
Phillips, S.J., Dudík, M. and Schapire, R.E. [Internet] Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url:http://biodiversityinformatics.amnh.org/open_source/maxent/. Accessed on 12.2.2018.
Radosavljevic, A. and Anderson, R.P. (2014). Making better Maxent models of species distributions: complexity, overfitting and evaluation.Journal of Biogeography , 41:629-643.
Shcheglovitova, M. and Anderson, R. P. (2013). Estimating optimal complexity for ecological niche models: a jackknife approach for species with small sample sizes. Ecological Modelling, 269: 9-17.http://dx.doi.org/10.1016/j.ecolmodel.2013.08.011
Syfert, M. M., Smith, M. J. and Coomes, D. A. (2013). The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models. PLoS ONE , 8: e55158. Doi:10.1371/journal.pone.0055158.
Vollering, J., Halvorsen, R., Auestad, I. and Rydgren, K. (2019). Bunching up the background betters bias in species distribution models.Ecography , 42: 1717-1727. Doi:10.1111/ecog.04503
Warren, D. L. and Seifert, S. N. (2011). Ecological niche modelling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecological Applications , 21: 335-342.
Young, N., Carter, L. and Evangelista, P. (2011). A maxent model v3.3.3e tutorial (ArcGIS v10). Last modified on September 1, 2011. Natural Resources Ecology Laboratory at Colorado State University and the National Institute of Invasive Species Science. Available in http://ibis.colostate.edu/webcontent/ws/coloradoview/tutorialsdownloads/a_maxent_model_v7.pdf. Accessed on 12.1.2018.