Science Enabled

Ellestad, P., Forest, F., Serpe, M., Novak, S. J., & Buerki, S. (2021). Harnessing large-scale biodiversity data to infer the current distribution of Vanilla planifolia (Orchidaceae). Botanical Journal of the Linnean Society. doi:10.1093/botlinnean/boab005 https://doi.org/10.1093/botlinnean/boab005

Although vanilla is one of the most popular flavours in the world, there is still uncertainty concerning the native distribution of the species that produces it, Vanilla planifolia. To circumscribe the native geographical extent of this economically important species more precisely, we propose a new…

Le Sage, E. H., Duncan, S. I., Seaborn, T., Cundiff, J., Rissler, L. J., & Crespi, E. J. (2021). Ecological adaptation drives wood frog population divergence in life history traits. Heredity. doi:10.1038/s41437-021-00409-w https://doi.org/10.1038/s41437-021-00409-w

Phenotypic variation among populations is thought to be generated from spatial heterogeneity in environments that exert selection pressures that overcome the effects of gene flow and genetic drift. Here, we tested for evidence of isolation by distance or by ecology (i.e., ecological adaptation) to g…

Seaborn, T., Goldberg, C. S., & Crespi, E. J. (2020). Drivers of distributions and niches of North American cold‐adapted amphibians: evaluating both climate and land use. Ecological Applications. doi:10.1002/eap.2236 https://doi.org/10.1002/eap.2236

Species distribution estimates are often used to understand the niche of a species; however, these are often based solely on climatic predictors. When the influences of biotic factors are ignored, erroneous inferences about range and niche may be made. We aimed to integrate climate data with a uniqu…

Li, X., Li, B., Wang, G., Zhan, X., & Holyoak, M. (2020). Deeply digging the interaction effect in multiple linear regressions using a fractional-power interaction term. MethodsX, 7, 101067. doi:10.1016/j.mex.2020.101067 https://doi.org/10.1016/j.mex.2020.101067

In multiple regression Y ~ β0 + β1X1 + β2X2 + β3X1 X2 + ɛ., the interaction term is quantified as the product of X1 and X2. We developed fractional-power interaction regression (FPIR), using βX1M X2N as the interaction term. The rationale of FPIR is that the slopes of Y-X1 regression along the X2 gr…

Deb, J. C., Forbes, G., & MacLean, D. A. (2020). Modelling the spatial distribution of selected North American woodland mammals under future climate scenarios. Mammal Review. doi:10.1111/mam.12210 https://doi.org/10.1111/mam.12210

North America has a diverse array of mammalian species. Model projections indicate significant variations in future climate conditions of North America, and the habitats of woodland mammals of this continent may be particularly sensitive to changes in climate.We report on the potential spatial distr…

Prieto-Torres, D. A., Lira-Noriega, A., & Navarro-Sigüenza, A. G. (2020). Climate change promotes species loss and uneven modification of richness patterns in the avifauna associated to Neotropical seasonally dry forests. Perspectives in Ecology and Conservation. doi:10.1016/j.pecon.2020.01.002 https://doi.org/10.1016/j.pecon.2020.01.002

We assessed the effects of global climate change as a driver of spatio-temporal biodiversity patterns in bird assemblages associated to Neotropical seasonally dry forests (NSDF). For this, we estimated the geographic distribution of 719 bird species under current and future climate (2050 and 2070) p…

Zink, R. M., Botero-Cañola, S., Martinez, H., & Herzberg, K. M. (2020). Niche modeling reveals life history shifts in birds at La Brea over the last twenty millennia. PLOS ONE, 15(1), e0227361. doi:10.1371/journal.pone.0227361 https://doi.org/10.1371/journal.pone.0227361

A species presence at a particular site can change over time, resulting in temporally dynamic species pools. Ecological niche models provide estimates of species presence at different time intervals. The avifauna of La Brea includes approximately 120 species dating to approximately 15,000 years ago.…

Liu, X., Blackburn, T. M., Song, T., Li, X., Huang, C., & Li, Y. (2019). Risks of Biological Invasion on the Belt and Road. Current Biology, 29(3), 499–505.e4. doi:10.1016/j.cub.2018.12.036 https://doi.org/10.1016/j.cub.2018.12.036

China’s Belt and Road Initiative (BRI) is an unprecedented global development program that involves nearly half of the world’s countries [1]. It not only will have economic and political influences, but also may generate multiple environmental challenges and is a focus of considerable academic and p…

Sullivan, J., Smith, M. L., Espíndola, A., Ruffley, M., Rankin, A., Tank, D., & Carstens, B. (2019). Integrating life history traits into predictive phylogeography. Molecular Ecology. doi:10.1111/mec.15029 https://doi.org/10.1111/mec.15029

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive …

Inman, R., Franklin, J., Esque, T., & Nussear, K. (2018). Spatial sampling bias in the Neotoma paleoecological archives affects species paleo-distribution models. Quaternary Science Reviews, 198, 115–125. doi:10.1016/j.quascirev.2018.08.015 https://doi.org/10.1016/j.quascirev.2018.08.015

The ability to infer paleo-distributions with limited knowledge of absence makes species distribution modeling (SDM) a useful tool for exploring paleobiogeographic questions. Spatial sampling bias is a known issue when modeling extant species. Here we quantify the spatial sampling bias in a North Am…