There are a number of publications which have used BCCVL to model species distributions, and several others that have reviewed or mentioned using BCCVL. If you have a publication that you would like to add to our list, please get in touch.
BCCVL used for modelling
W. Hallgren, F. Santana, S. Low-Choy, Y. Zhao, B. Mackey (2019). Species distribution models can be highly sensitive to algorithm configuration, Ecological Modelling,408. doi.org/10.1016/j.ecolmodel.2019.108719.
Taylor, C. M., Keppel, G., Peters, S., Hopkins, G. R., & Kerr, G. D. (2018). Establishment and potential spread of the introduced spotted-thighed frog, Litoria cyclorhyncha (Ranoidea cyclorhynchus), in South Australia. Transactions of the Royal Society of South Australia, 142(1), 86-101. doi:10.1080/03721426.2018.1444911
Sumoto. S. & van Etten, E. (2017). Species distribution model of invasive alien species Acacia nilotica for Central-Eastern Indonesia using Biodiversity Climate Change Virtual Laboratory (BCCVL). https://smujo.id/td/article/view/1644
Mackey, B., Cadman, S., Rogers, N., & Hugh, S. (2017). Assessing the risk to the conservation status of temperate rainforest from exposure to mining, commercial logging, and climate change: a Tasmanian case study. Biological Conservation, 215, 19-29. https://www.sciencedirect.com/science/article/pii/S0006320717305773?via%3Dihub
Low-Choy, S., & Huijbers, C. (2017). Experimenting with Modelling via a Virtual Laboratory: Evaluating pseudo-absence strategies to refine a species distribution model. Paper presented at the 22nd International Congress on Modelling and Simulation, Hobart, Tasmania. https://www.mssanz.org.au/modsim2017/G8/lowchoy.pdf
Hallgren, W., Santana, F., Low-Choy, S., Rehn, J., & Mackey, B. (2017). Sensitivity Analysis to Configuration Option Settings in a Selection of Species Distribution Modelling Algorithms. Paper presented at the 22nd International Congress on Modelling and Simulation, Hobart, Tasmania. https://www.mssanz.org.au/modsim2017/A1/hallgren.pdf
Santana, F., Hallgren, W., Rehn, J., Chiu, L., & Holewa, H. (2017). Implementing best practices and a workflow for modelling the geospatial distribution of migratory species. Paper presented at the 22nd International Congress on Modelling and Simulation, Hobart, Tasmania. https://www.mssanz.org.au/modsim2017/C3/santana.pdf
Hallgren, W., Beaumont, L., Bowness, A., Chambers, L., Graham, E., Holewa, H., . . . Price, J. (2016). The biodiversity and climate change virtual laboratory: where ecology meets big data. Environmental Modelling & Software, 76, 182-186. https://www.sciencedirect.com/science/article/pii/S1364815215300839?via%3Dihub
BCCVL mentioned
Booth, T. H. (2018a). Species distribution modelling tools and databases to assist managing forests under climate change. Forest Ecology and Management, 430, 196-203. https://www.sciencedirect.com/science/article/pii/S0378112718310879#
Booth, T. H. (2018b). Why understanding the pioneering and continuing contributions of BIOCLIM to species distribution modelling is important. Austral Ecology. https://onlinelibrary.wiley.com/doi/abs/10.1111/aec.12628
Langenheim, N., White, M., Barton, J., & Eagleson, S. (2017). Designing with Data for Urban Resilience. In S. Geertman, A. Allan, C. Pettit, & J. Stillwell (Eds.), Planning Support Science for Smarter Urban Futures (pp. 113-133). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007%2F978-3-319-57819-4_7
Palmer, R., Dharmawardena, K., & Holewa, H. (2017). Adapting Enterprise Architecture for eScience. Paper presented at the e-Science (e-Science), 2017 IEEE 13th International Conference. https://ieeexplore.ieee.org/abstract/document/8109160/
Ramalho, C. E., Byrne, M., & Yates, C. J. (2017). A Climate-Oriented Approach to Support Decision-Making for Seed Provenance in Ecological Restoration. Frontiers in Ecology and Evolution, 5(95). doi:10.3389/fevo.2017.00095 https://www.frontiersin.org/articles/10.3389/fevo.2017.00095/full
Santana, F., Pariente, C. A. B., & Saraiva, A. M. (2017). Species Distribution Modeling with Scalability: The Case Study of P-GARP, a Parallel Genetic Algorithm for Rule-Set Production. Paper presented at the Information Reuse and Integration (IRI), 2017 IEEE International Conference. https://ieeexplore.ieee.org/abstract/document/8102933/
Wolski, M., Howard, L., & Richardson, J. (2017). The importance of tools in the data lifecycle. Digital Library Perspectives, 33(3), 235-252. doi:doi:10.1108/DLP-11-2016-0042 https://www.emeraldinsight.com/doi/full/10.1108/DLP-11-2016-0042
Booth, T. H. (2017). Assessing species climatic requirements beyond the realized niche: some lessons mainly from tree species distribution modelling. Climatic Change, 145(3), 259-271. doi:10.1007/s10584-017-2107-9 https://link.springer.com/article/10.1007/s10584-017-2107-9
Belbin, L., & Williams, K. J. (2016). Towards a national bio-environmental data facility: experiences from the Atlas of Living Australia. International Journal of Geographical Information Science, 30(1), 108-125. doi:10.1080/13658816.2015.1077962 https://www.tandfonline.com/doi/full/10.1080/13658816.2015.1077962?scroll=top&needAccess=true
La Salle, J., Williams, K. J., & Moritz, C. (2016). Biodiversity analysis in the digital era. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1702). doi:10.1098/rstb.2015.0337 http://rstb.royalsocietypublishing.org/content/371/1702/20150337