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. PeerJ , 5 , 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.