We use this space to list published peer-review papers that cited flexsdm package. Some of the following research used flexsdm for the entire modeling protocols, others used a couple of flexsdm functions, and others just mentioned our package.

Thanks to the authors for citing our package.

2024

  1. Kougioumoutzis, K., Tsakiri, M., Kokkoris, I.P., Trigas, P., Iatrou, G., Lamari, F.N., Tzanoudakis, D., Koumoutsou, E., Dimopoulos, P., Strid, A., Panitsa, M., (2024). Assessing the vulnerability of medicinal and aromatic plants to climate and land-use changes in a Mediterranean biodiversity hotspot. Land 13, 133. https://doi.org/10.3390/land13020133

  2. Rodriguez, C.S., Rose, M.B., Velazco, S.J.E., Franklin, J., Larios, L., (2024). High potential for Brassica tournefortii spread in North American introduced range, despite highly conserved niche. Biological Invasions 26, 337–351. https://doi.org/10.1007/s10530-023-03176-3

2023

  1. Velazco, S. J. E., Brooke, M. R., De Marco Jr., P., Regan, H. M., & Franklin, J. (2023). How far can I extrapolate my species distribution model? Exploring Shape, a novel method. Ecography, e06992. https://doi.org/10.1111/ecog.06992

  2. Sillero, N., Campos, J. C., Arenas-Castro, S., & Barbosa, A. (2023). A curated list of R packages for ecological niche modelling. Ecological Modelling, 476, 110242. https://doi.org/10.1016/j.ecolmodel.2022.110242

  3. Rose, M. B., Elías Velazco, S. J., Regan, H. M., & Franklin, J. (2023). Rarity, geography, and plant exposure to global change in the California Floristic Province. Global Ecology and Biogeography, 32(2), 218-232. https://doi.org/10.1111/geb.13618

  4. Franklin, J. (2023). Species distribution modelling supports the study of past, present and future biogeographies. Journal of Biogeography, 50(9), 1533-1545. https://doi.org/10.1111/jbi.14617

  5. Amaro, G., Fidelis, E. G., Da Silva, R. S., & Marchioro, C. A. (2023). Effect of study area extent on the potential distribution of Species: A case study with models for Raoiella indica Hirst (Acari: Tenuipalpidae). Ecological Modelling, 483, 110454. https://doi.org/10.1016/j.ecolmodel.2023.110454

  6. Moura, M. R., Oliveira, G. A., Paglia, A. P., Pires, M. M., & Santos, B. A. (2023). Climate change should drive mammal defaunation in tropical dry forests. Global Change Biology, 29(24), 6931-6944. https://doi.org/10.1111/gcb.16979

  7. Da Silva, J. P., Sousa, R., Gonçalves, D. V., Miranda, R., Reis, J., Teixeira, A., Varandas, S., Lopes-Lima, M., & Filipe, A. F. (2023). Streams in the Mediterranean Region are not for mussels: Predicting extinctions and range contractions under future climate change. Science of The Total Environment, 883, 163689. https://doi.org/10.1016/j.scitotenv.2023.163689

  8. Du, Y., Jueterbock, A., Firdaus, M., Hurtado, A. Q., & Duan, D. (2023). Niche comparison and range shifts for two Kappaphycus species in the Indo-Pacific Ocean under climate change. Ecological Indicators, 154, 110900. https://doi.org/10.1016/j.ecolind.2023.110900

  9. Mathias, S., Jarvie, S., & Larcombe, M. J. (2023). Range reshuffling: Climate change, invasive species, and the case of Nothofagus forests in Aotearoa New Zealand. Diversity and Distributions, 29(11), 1402-1419. https://doi.org/10.1111/ddi.13767

  10. Petersen, W. J., & Savini, T. (2023). Lowland forest loss and climate-only species distribution models exaggerate a forest-dependent species’ vulnerability to climate change. Ecological Informatics, 78, 102327. https://doi.org/10.1016/j.ecoinf.2023.102327

  11. Kokkoris, I. P., Kougioumoutzis, K., Charalampopoulos, I., Apostolidis, E., Apostolidis, I., Strid, A., & Dimopoulos, P. (2023). Conservation Responsibility for Priority Habitats under Future Climate Conditions: A Case Study on Juniperus drupacea Forests in Greece. Land, 12(11), 1976. https://doi.org/10.3390/land12111976

  12. Wang, X., Xu, Q., & Liu, J. (2023). Determining representative pseudo-absences for invasive plant distribution modeling based on geographic similarity. Frontiers in Ecology and Evolution, 11, 1193602. https://doi.org/10.3389/fevo.2023.1193602

  13. Tytar, V., Nekrasova, O., Pupins, M., Skute, A., Kirjušina, M., Gravele, E., Mezaraupe, L., Marushchak, O., Čeirāns, A., Kozynenko, I., & Kulikova, A. A. (2023). Modeling the Distribution of the Chytrid Fungus Batrachochytrium dendrobatidis with Special Reference to Ukraine. Journal of Fungi, 9(6), 607. https://doi.org/10.3390/jof9060607

  14. Moura, M. R., Paolucci, L. N., Silva, D. P., & Santos, B. A. (2023). Pervasive impacts of climate change on the woodiness and ecological generalism of dry forest plant assemblages. Journal of Ecology, 111(8), 1762-1776. https://doi.org/10.1111/1365-2745.14139

  15. Zhang, X., Huang, Q., Liu, P., Sun, C., Papa, R. D., Sanoamuang, L., Dumont, H. J., & Han, B. (2023). Geography, ecology, and history synergistically shape across-range genetic variation in a calanoid copepod endemic to the north-eastern Oriental. Evolution, 77(2), 422-436. https://doi.org/10.1093/evolut/qpac043

2022

  1. Wen, C., Cha, J., Xu, L., Xu, H. Spatial Potential of Recreational Services in Western Hubei Region in Light of the “All-for-One Tourism” Development—A Machine Learning Approach Based on Ensemble Model. (2022) Landscape Architecture Frontiers, 10(5): 8‒31 https://doi.org/10.15302/J-LAF-1-020073