Species Distribution Modelling (SDM) and Population dynamics

Briscoe, N., et al., (2019).

Understanding where species occur and how populations will likely respond to future environmental change is essential to conservation. We develop, test and apply methods for predicting species distributions and abundance. Much of our research focuses on correlative species distribution models (SDMs, also known as ecological niche or habitat models) investigating new methods, assumptions and related to biogeography. We also research models that incorporate more mechanisms, including dynamic occupancy models, spatially-explicit population models, eco-physiological or mechanistic niche models and individual-based models.We apply these methods to a broad range of taxa and problems including threatened species, invasive species, fire management and climate change.

Researchers:

Mick McCarthy, Peter Vesk, Jane Elith, Jose Lahoz-Monfort, Guruzeta Guillera-Arroita, Natalie Briscoe, David Wilkinson, Gerry Ryan, Anwar Hossain, Ian Flint, Roozbeh Valavi, August Hao, Brendan Wintle, Saras Windecker, David E. Uribe-Rivera, Alys Young, Saoirse Kelleher, Islay McDougall, Rohan Khot, Skipton Woolley

Affiliate researchers:

Nick Golding, Casey Visintin, Pia Lentini, James Camac, Reid Tingley, Alyson Stobo‐Wilson

Selected Publications:

Visintin, C., Briscoe, N., Woolley, S.N.C., Lentini, P.E., Tingley, R., Wintle, B.A. and Golding, N. 2020. steps: Software for spatially and temporally explicit population simulations. Methods in ecology and evolution, 11(4), pp.596-603.

Briscoe, N.J., Elith, J., Salguero‐Gómez, R., Lahoz‐Monfort, J.J., Camac, J.S., Giljohann, K.M., Holden, M.H., Hradsky, B.A., Kearney, M.R., McMahon, S.M. and Phillips, B.L., 2019. Forecasting species range dynamics with process‐explicit models: matching methods to applications. Ecology Letters, 22(11), pp.1940-1956.

Hradsky, B.A., Kelly, L.T., Robley, A. and Wintle, B.A., 2019. FoxNet: An individual‐based model framework to support management of an invasive predator, the red fox. Journal of Applied Ecology, 56(6), pp.1460-1470.

Valavi, R., Elith, J., Lahoz‐Monfort, J.J. and Guillera‐Arroita, G., 2019. blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models. Methods in Ecology and Evolution, 10(2), pp.225-232.

Guillera‐Arroita, G., Lahoz‐Monfort, J.J., Elith, J., Gordon, A., Kujala, H., Lentini, P.E., McCarthy, M.A., Tingley, R. and Wintle, B.A., 2015. Is my species distribution model fit for purpose? Matching data and models to applications. Global Ecology and Biogeography, 24(3), pp.276-292.

Lahoz‐Monfort, J.J., Guillera‐Arroita, G. and Wintle, B.A., 2014. Imperfect detection impacts the performance of species distribution models. Global Ecology and Biogeography, 23(4), pp.504-515.