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Where flexsdm was cited?

Source: vignettes/pkg_citation.Rmd
pkg_citation.Rmd

Here we provide a list of published peer-reviewed papers that cited flexsdm package. Some of the following research used flexsdm for the entire modeling protocol, others used a couple of flexsdm functions, and others just mentioned our package.

Cite our package as

Velazco, S.J.E., Rose, M.B., Andrade, A.F.A., Minoli, I., Franklin, J. (2022). flexsdm: An R package for supporting a comprehensive and flexible species distribution modelling workflow. Methods in Ecology and Evolution, 13(8) 1661–1669. https://doi.org/10.1111/2041-210X.13874

@article{velazco_flexsdm_2022,
    title = {flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow},
    volume = {13},
    rights = {© 2022 The Authors. Methods in Ecology and Evolution published by John Wiley \& Sons Ltd on behalf of British Ecological Society.},
    issn = {2041-210X},
    url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13874},
    doi = {10.1111/2041-210X.13874},
    pages = {1661--1669},
    number = {8},
    journaltitle = {Methods in Ecology and Evolution},
    author = {Velazco, Santiago José Elías and Rose, Miranda Brooke and de Andrade, André Felipe Alves and Minoli, Ignacio and Franklin, Janet},
    date = {2022},
    note = {\_eprint: https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13874}
}

Thanks to the authors for citing our package.

2025

  1. Rahimi, E., Ahmadzadeh, F., 2025. Investigating climate-driven corridor networks for Golden Jackal (Canis aureus) in Northern Parts of Iran. Journal of Wildlife and Biodiversity 9, 1–16. https://www.wildlife-biodiversity.com/index.php/jwb/article/view/728

  2. Kass, J.M., Smith, A.B., Warren, D.L., Vignali, S., Schmitt, S., Aiello‐Lammens, M.E., Arlé, E., Márcia Barbosa, A., Broennimann, O., Cobos, M.E. and Guéguen, M., 2025. Achieving higher standards in species distribution modeling by leveraging the diversity of available software. Ecography, 2025(2), p.e07346. https://nsojournals.onlinelibrary.wiley.com/doi/full/10.1111/ecog.07346

  3. Hesabi, A., Alavi, S.J. and Esmailzadeh, O., 2025. Evaluation of the accuracy of climatic data from the WorldClim and Chelsa databases in three northern provinces of Iran. Forest Research and Development, 11(1), pp.109-132. https://jfrd.urmia.ac.ir/article_121653.html?lang=en

  4. Withers, A.J., Croft, S., Budgey, R., Warren, D. and Johnson, N., 2025. Predicting West Nile Virus risk across Europe for the current and future conditions. bioRxiv, pp.2025-03. https://www.biorxiv.org/content/10.1101/2025.03.04.640552v1.abstract

  5. da Mota Porto, A.C. and Novaes, E., 2025. Prediction of current and future environmental suitability for Toona ciliata cultivation in Brazil. Discover Forests, 1(1), pp.1-14. https://link.springer.com/article/10.1007/s44415-025-00029-w

  6. Demir, M.A. and Kabalak, M., 2025. Predicting the suitable habitats of Alosimus marginicollis (Haag-Rutenberg, 1880)(Coleoptera: Meloidae) and evaluating its potential distribution in relation to geographical and climatic barriers. Turkish Journal of Zoology, 49(2), pp.75-91. https://journals.tubitak.gov.tr/zoology/vol49/iss2/3/

  7. Antonio, A.I., de Oliveira Junior, A.C., Villalobos, F. and Velazco, S.J.E., 2025. Environmental heterogeneity as a determinant of bee diversity patterns in the Atlantic Forest. Frontiers of Biogeography, 18, p.e142410. https://doi.org/10.21425/fob.18.142410

  8. Bayraktarov, E., Low-Choy, S., Singh, A.R., Beaumont, L.J., Williams, K.J., Baumgartner, J.B., Laffan, S.W., Vasco, D., Cosgrove, R., Wraith, J. and Antunes, J.F., 2025. EcoCommons Australia virtual laboratories with cloud computing: Meeting diverse user needs for ecological modeling and decision-making. Environmental Modelling & Software, 183, p.106255. https://www.sciencedirect.com/science/article/pii/S1364815224003165

  9. Rahimi, E. and Jung, C., 2025. Mapping co-occurrence dynamics between crops and honeybees under climate change in North America. Community Ecology, pp.1-11. https://link.springer.com/article/10.1007/s42974-025-00262-5

  10. Castillo, D.S.C. and Higa, M., 2025. Effectiveness and implications of spatial background restrictions on model performance and predictions: a special reference for Rattus species. Landscape and Ecological Engineering, pp.1-15. https://link.springer.com/article/10.1007/s11355-025-00653-w

  11. Shitara, T., Aihara, T., Momohara, A., Tsuyama, I. and Matsui, T., 2025. Are disjunct populations of Betula costata in the Japanese Archipelago glacial relict? An attempt at verification by species distribution modeling. Ecological Research. https://esj-journals.onlinelibrary.wiley.com/doi/abs/10.1111/1440-1703.12541

  12. Somerville, R., MacNeil, C. and Lee, F., 2025. Habitat suitability of Aotearoa New Zealand for the recently invaded gold clam (Corbicula fluminea). New Zealand Journal of Marine and Freshwater Research, 59(4), pp.762-779. https://www.tandfonline.com/doi/abs/10.1080/00288330.2024.2368856

  13. Porto, A.C., Santos, M.L., Lima, R.P., Filho, D.S., Souza, A.M., da Silva, J.C. and de Oliveira, A.C., 2025. Modelled potential changes in the climate-related geographic distribution of species of the Passiflora genus in Brazil. Plant Ecology & Diversity, pp.1-14. https://www.tandfonline.com/doi/abs/10.1080/17550874.2025.2505425

  14. Chartois, M., Fried, G. and Rossi, J.P., 2025. Climate and host plant availability are favourable to the establishment of Lycorma delicatula in Europe. Agricultural and Forest Entomology, 27(2), pp.316-328. https://resjournals.onlinelibrary.wiley.com/doi/abs/10.1111/afe.12665

  15. Fisher, R. J. (2025). Changes in urban landcover picks winners and losers in the non-invasive bird community. Urban Ecosystems, 28(2), 95. https://link.springer.com/article/10.1007/s11252-025-01710-w

  16. Rahimi, E. and Jung, C., 2025. Investigating the Spatial Biases and Temporal Trends in Insect Pollinator Occurrence Data on GBIF. Insects, 16(8), p.769. https://www.mdpi.com/2075-4450/16/8/769

  17. de Brito Reis, K.H., Picanço, M.M., Pereira, P.S., de Souza, H.D.D., de Sá, M.C., Amaro, G.C., da Silva, R.S., Picanço, M.C. and Sarmento, R.A., 2025. Mapping the potential distribution and invasion risk of Watermelon mosaic virus using MaxEnt ecological niche modeling. Theoretical and Applied Climatology, 156(1), p.45. https://link.springer.com/article/10.1007/s00704-024-05289-8

  18. Georgopoulou, E., Kougioumoutzis, K. and Simaiakis, S.M., 2025. The Impact of Climate and Land Use Change on Greek Centipede Biodiversity and Conservation. Land, 14, p1685. https://www.mdpi.com/2073-445X/14/8/1685

  19. Dos Santos, J.C.B., Ramos, R.S., DAS GRAÇAS Do CARMO, D.A.I.A.N.E., Picanco, M.C., Guedes, E.P., Junior, P.A.S., Sarmento, R.A., De SOUZA RIBAS, N.A.T.Á.L.I.A.X., Correa Amaro, G. and Da SILVA, R.S., 2025. Assessing the impact of climate changes on the distribution of two corn diseases: corn stunt and corn reddening. Canadian Journal of Plant Pathology, pp.1-20. https://www.tandfonline.com/doi/abs/10.1080/07060661.2025.2533964

  20. Withers, A.J., Croft, S., Budgey, R., Warren, D.A. and Johnson, N., 2025. Modelling vector and host distributions to inform potential disease risk: A case study of West Nile virus in the United Kingdom. Medical and Veterinary Entomology. https://resjournals.onlinelibrary.wiley.com/doi/abs/10.1111/mve.12825

  21. Rahimi, E. and Jung, C., 2025. Exploring Climate-Driven Mismatches Between Pollinator-Dependent Crops and Honeybees in Asia. Biology, 14(3), p.234. https://www.mdpi.com/2079-7737/14/3/234

  22. Patron-Rivero, C., Yañez-Arenas, C., Chiappa-Carrara, X., Rojas-Soto, O., Ruane, S. and Guevara, L., 2025. Ecological and biogeographic drivers of speciation in neotropical hognose pit vipers, Porthidium (Squamata, Viperidae). Zoologischer Anzeiger. https://www.sciencedirect.com/science/article/pii/S004452312500083X

  23. Ramírez‐Arce, D.G., Ochoa‐Ochoa, L.M., Lira‐Noriega, A. and Martorell, C., 2025. Reptile Diversity Patterns Under Climate and Land Use Change Scenarios in a Subtropical Montane Landscape in Mexico. Journal of Biogeography, 52(1), pp.108-121. https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.15017

  24. Gehman, C.S. and Gienger, C.M., 2025. Predicting the potential distribution of the Gila Monster and evaluating the extent of protected natural areas for conservation. Journal for Nature Conservation, 86, p.126944. https://www.sciencedirect.com/science/article/pii/S1617138125001219

  25. Lin, Y., Liu, Q., Lv, S., Huang, X., Wei, C., Li, J., Guan, Y., Pan, Y., Mi, Y., Cheng, Y. and Yang, X., 2025. Assessing the Potential Distribution of the Traditional Chinese Medicinal Plant Spatholobus suberectus in China Under Climate Change: A Biomod2 Ensemble Model-Based Study. Biology, 14(8), p.1071. https://www.mdpi.com/2079-7737/14/8/1071

  26. Kougioumoutzis, K., Kokkoris, I.P., Trigas, P., Strid, A. and Dimopoulos, P., 2025. Projected Impacts of Climate and Land Use Change on Endemic Plant Distributions in a Mediterranean Island Hotspot: The Case of Evvia (Aegean, Greece). Climate, 13(5), p.100. https://www.mdpi.com/2225-1154/13/5/100

  27. Bro-Jørgensen, J., Ikram, S., Spedding, J.V., Thomas, C.D., Snape, S., Nilsson, M. and Lazagabaster, I.A., 2025. Applying habitat suitability modelling to establish the species identity of ambiguous animal depictions in archaeology: new insights into the wild bovids of ancient Egypt. Journal of archaeological science, 179, p.106239. https://www.sciencedirect.com/science/article/pii/S0305440325000883

  28. Holcomb, K.M., Foster, E., Maes, S.E., Parise, C.M., Osikowicz, L.M., Hojgaard, A. and Eisen, R.J., 2025. Estimated density of Borrelia burgdorferi sensu stricto-infected Ixodes scapularis nymphs in the eastern United States. Parasites & Vectors, 18(1), p.350. https://link.springer.com/article/10.1186/s13071-025-06937-2

  29. Alves‐Ferreira, G., Vancine, M.H., Mota, F.M.M., Bello, C., Sobral‐Souza, T., Percequillo, A.R., Lacher Jr, T.E., Galetti, M. and Bovendorp, R.S., 2025. From Hot to Cold Spots: Climate Change is Projected to Modify Diversity Patterns of Small Mammals in a Biodiversity Hotspot. Diversity and Distributions, 31(5), p.e70026. https://onlinelibrary.wiley.com/doi/abs/10.1111/ddi.70026

  30. Holcomb, K.M., Foster, E. and Eisen, R.J., 2025. Estimating the density of questing Ixodes scapularis nymphs in the eastern United States using climate and land cover data. Ticks and Tick-borne Diseases, 16(2), p.102446. https://www.sciencedirect.com/science/article/pii/S1877959X2500010X

  31. Duyar, A., Demir, M.A. and Kabalak, M., 2025. Prediction of current and future distributions of chalcophora detrita (coleoptera: buprestidae) under climate change scenarios. Ecology and Evolution, 15(1), p.e70693. https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.70693

  32. Cheng, H., Johansen, K., Jin, B., Xu, S., Zhao, X., Han, L. and McCabe, M.F., 2025. Human footprint with machine learning identifies risks of the invasive weed Conyza sumatrensis across land-use types under climate change. Global Ecology and Conservation, p.e03657. https://www.sciencedirect.com/science/article/pii/S2351989425002586

  33. Stefanidis, A., Kougioumoutzis, K., Zografou, K., Fotiadis, G., Willemse, L., Tzortzakaki, O. and Kati, V., 2025. Distribution patterns and habitat preferences of five globally threatened and endemic montane Orthoptera (Parnassiana and Oropodisma). Ecologies, 6(1), p.5. https://www.mdpi.com/2673-4133/6/1/5

  34. Backus, G.A., Rose, M.B., Velazco, S.J., Franklin, J., Syphard, A.D. and Regan, H.M., 2025. Population Decline for Plants in the California Floristic Province: Does Demography or Geography Determine Climate Change Vulnerability?. Diversity and Distributions, 31(8), p.e70067. https://onlinelibrary.wiley.com/doi/abs/10.1111/ddi.70067

  35. Hubbard, J.A., Andrew R. Drake, D. and Mandrak, N.E., 2025. ‘Euclimatch’: an R package for climate matching with Euclidean distance metrics. Ecography, 2025(4), p.e07614. https://nsojournals.onlinelibrary.wiley.com/doi/abs/10.1111/ecog.07614

  36. Stefanidis, A., Kougioumoutzis, K., Zografou, K., Fotiadis, G., Tzortzakaki, O., Willemse, L. and Kati, V., 2025. Mitigating the extinction risk of globally threatened and endemic mountainous Orthoptera species: Parnassiana parnassica and Oropodisma parnassica. Insect Conservation and Diversity, 18(1), pp.54-68. https://resjournals.onlinelibrary.wiley.com/doi/abs/10.1111/icad.12784

  37. Noel, A., Schlaepfer, D.R., Butterfield, B.J., Swan, M.C., Norris, J., Hartwig, K., Duniway, M.C. and Bradford, J.B., 2025. Most Pinyon–Juniper Woodland Species Distributions Are Projected to Shrink Rather Than Shift Under Climate Change. Rangeland Ecology & Management, 98, pp.454-466. https://www.sciencedirect.com/science/article/pii/S1550742424001659

  38. de Oliveira Junior, A.C. and Velazco, S.J.E., 2025. adm: An R package for constructing abundance‐based species distribution models. Methods in Ecology and Evolution. https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.70074

  39. Fonteyn, W., Serra‐Diaz, J.M., Muys, B. and Van Meerbeek, K., 2025. Incorporating climatic extremes using the GEV distribution improves SDM range edge performance. Journal of Biogeography, 52(3), pp.780-791. https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.15067

  40. Harapan, T.S., Ong, L., Agung, A.P., Rafia, R., Tjong, D.H., Novarino, W. and Campos‐Arceiz, A., 2025. A Slow and Underappreciated Forest Megafauna: Food Habits, Movements, and Multiscale Habitat Preferences of Critically Endangered Sundaic Giant Tortoises (Manouria emys emys). Integrative Zoology. https://onlinelibrary.wiley.com/doi/abs/10.1111/1749-4877.12965

  41. Rossi, J.P., Battisti, A., Avtzis, D.N., Burban, C., Rahim, N., Rousselet, J., Kerdelhué, C. and İpekdal, K., 2025. Warmer and brighter winters than before: Ecological and public health challenges from the expansion of the pine processionary moth (Thaumetopoea pityocampa). Science of the Total Environment, 978, p.179470. https://www.sciencedirect.com/science/article/pii/S0048969725011076

  42. Zhang, Z., Kass, J.M., Bede‐Fazekas, Á., Mammola, S., Qu, J., Molinos, J.G., Gu, J., Huang, H., Qu, M., Yue, Y. and Qin, G., 2025. Differences in predictions of marine species distribution models based on expert maps and opportunistic occurrences. Conservation Biology, p.e70015. https://conbio.onlinelibrary.wiley.com/doi/abs/10.1111/cobi.70015

  43. Rey Pullido, K.G. and Velazco, S.J.E. On protected areas and other effective area-based conservation measures to conserve biodiversity. Exploring their contribution to Colombian snakes. Perspective in Ecology and Conservation, 23(2), pp.110-120. https://www.sciencedirect.com/science/article/pii/S2530064425000173?via%3Dihub

  44. Aidoo, O.F., Amaro, G.C., Souza, P.G.C., Picanço, M.C., Awuah‐Mensah, K.A. and Silva, R.S.D., 2025. Climate change impacts on worldwide ecological niche and invasive potential of Sternochetus mangiferae. Pest Management Science, 81(2), pp.667-677. https://scijournals.onlinelibrary.wiley.com/doi/abs/10.1002/ps.8465

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(2), 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(1), 337-351. https://doi.org/10.1007/s10530-023-03176-3

  3. Chartois, M., Fried, G. & Rossi, J.-P. (2024) Climate and host plant availability are favourable to the establishment of Lycorma delicatula in Europe. Agricultural and Forest Entomology, 1–13. Available from: https://doi.org/10.1111/afe.12665

  4. Syphard, A. D., Velazco, S. J. E., Rose, M. B., Franklin, J., & Regan, H. M. (2024). The importance of geography in forecasting future fire patterns under climate change. Proceedings of the National Academy of Sciences, 121(32), e2310076121. https://doi.org/10.1073/pnas.2310076121

  5. Rose, M. B., Velazco, S. J. E., Regan, H. M., Flint, A. L., Flint, L. E., Thorne, J. H., & Franklin, J. (2024). Uncertainty in consensus predictions of plant species’ vulnerability to climate change. Diversity and Distributions, 30(8), e13898. https://doi.org/10.1111/ddi.13898

  6. Aidoo, O.F., Amaro, G.C., Souza, P.G.C., Picanço, M.C., Awuah-Mensah, K.A. & Silva, R.S.d. (2024), Climate change impacts on worldwide ecological niche and invasive potential of Sternochetus mangiferae. Pest Management Science, https://doi.org/10.1002/ps.8465

  7. Pires, M. B., Kougioumoutzis, K., Norder, S., Dimopoulos, P., Strid, A., & Panitsa, M. (2024). The future of plant diversity within a Mediterranean endemism centre: Modelling the synergistic effects of climate and land-use change in Peloponnese, Greece. Science of The Total Environment, 947, 174622.https://doi.org/10.1016/j.scitotenv.2024.174622

  8. Noel, A., Schlaepfer, D.R., Butterfield, B.J., Swan, M.C., Norris, J., Hartwig, K., Duniway, M.C. & Bradford, J.B. (2024). Most Pinyon–Juniper Woodland Species Distributions Are Projected to Shrink Rather Than Shift Under Climate Change. Rangeland Ecology & Management, https://doi.org/10.1016/j.rama.2024.09.002

  9. Stefanidis, A., Kougioumoutzis, K., Zografou, K., Fotiadis, G., Tzortzakaki, O., Willemse, L. & Kati, V., (2024) Mitigating the extinction risk of globally threatened and endemic mountainous Orthoptera species: Parnassiana parnassica and Oropodisma parnassica. Insect Conservation and Diversity, 1–15. Available from: https://doi.org/10.1111/icad.12784

  10. Rahimi E, Jung C. (2024) A New SDM-Based Approach for Assessing Climate Change Effects on Plant–Pollinator Networks. Insects, 15(11):842. https://doi.org/10.3390/insects15110842

  11. Rahimi, E., Dong, P. & Ahmadzadeh, F. (2024). Assessing climate niche similarity between persian fallow deer (Dama mesopotamica) areas in Iran. BMC Ecology and Evolution, 24(1), 93. https://doi.org/10.1186/s12862-024-02281-8

  12. Ramírez‐Arce, D. G., Ochoa‐Ochoa, L. M., Lira‐Noriega, A., & Martorell, C. (2024). Reptile Diversity Patterns Under Climate and Land Use Change Scenarios in a Subtropical Montane Landscape in Mexico. Journal of Biogeography, https://doi.org/10.1111/jbi.15017

  13. Rahimi, E., & Jung, C. (2024). Global trends in climate suitability of bees: Ups and downs in a warming world. Insects, 15(2), 127. https://doi.org/10.3390/insects15020127

  14. Lazagabaster, I. A., Thomas, C. D., Spedding, J. V., Ikram, S., Solano‐Regadera, I., Snape, S., & Bro‐Jørgensen, J. (2024). Evaluating species distribution model predictions through time against paleozoological records. Ecology and evolution, 14(10), e70288. https://doi.org/10.1002/ece3.70288

  15. Habibi, I., Achour, H., Bounaceur, F., Benaradj, A., & Aulagnier, S. (2024). Predicting the future distribution of the Barbary ground squirrel (Atlantoxerus getulus) under climate change using niche overlap analysis and species distribution modeling. Environmental Monitoring and Assessment, 196(11), 1-18. https://doi.org/10.1007/s10661-024-13350-2

  16. Nelson, D. L., Marneweck, C. J., McShea, W. J., Shamon, H., & Jachowski, D. S. (2024). Predicted future range expansion of a small carnivore: swift fox in North America. Landscape Ecology, 39(9), 164. https://doi.org/10.1007/s10980-024-01962-5

  17. Rahimi, E., & Jung, C. (2024). A Global Estimation of Potential Climate Change Effects on Pollinator-Dependent Crops. Agricultural Research, 1-11. https://doi.org/10.1007/s40003-024-00802-x

  18. Rahimi, E., Dong, P., Ahmadzadeh, F., & Jung, C. (2024). Assessing climate change threats to biodiversity and protected areas of Iran. European Journal of Wildlife Research, 70(5), 1-11. https://doi.org/10.1007/s10344-024-01842-y

  19. He, J., Lu, L., He, H., Zhang, Z., Hao, M., Zhang, C., Zhao, X. & von Gadow, K. (2024). Estimating the dynamics of ecosystem functions under climate change in a temperate forest region. Ecological Indicators, 166, 112353. https://doi.org/10.1016/j.ecolind.2024.112353

  20. Nieto‐Lugilde, M., Nieto‐Lugilde, D., Piatkowski, B., Duffy, A.M., Robinson, S.C., Aguero, B., Schuette, S., Wilkens, R., Yavitt, J. & Shaw, A.J.(2024). Ecological differentiation and sympatry of cryptic species in the Sphagnum magellanicum complex (Bryophyta). American Journal of Botany, e16401. https://doi.org/10.1002/ajb2.16401

  21. Serra‐Diaz, J.M., Borderieux, J., Maitner, B., Boonman, C.C., Park, D., Guo, W.Y., Callebaut, A., Enquist, B.J., Svenning, J.C. & Merow, C. (2024). occTest: An integrated approach for quality control of species occurrence data. Global Ecology and Biogeography, e13847. https://doi.org/10.1111/geb.13847

  22. Bayraktarov, E., Low-Choy, S., Singh, A.R., Beaumont, L.J., Williams, K.J., Baumgartner, J., Laffan, S.W., Vasco, D., Cosgrove, R., Wraith, J. & Antunes, J.F. (2024). EcoCommons Australia Virtual Laboratories with Cloud Computing: Meeting Diverse User Needs for Ecological Modeling and Decision-making. Environmental Modelling & Software, 106255. https://doi.org/10.1016/j.envsoft.2024.106255

  23. Lamboley, Q., & Fourcade, Y. (2024). No optimal spatial filtering distance for mitigating sampling bias in ecological niche models. Journal of Biogeography, 51, 1783–1794. https://doi.org/10.1111/jbi.14854

  24. Delle Monache, D., Martino, G., Chiocchio, A., Siclari, A., Bisconti, R., Maiorano, L., & Canestrelli, D. (2024). Mapping local climates in highly heterogeneous mountain regions: Interpolation of meteorological station data vs. downscaling of macroclimate grids. Ecological Informatics, 102674. https://doi.org/10.1016/j.ecoinf.2024.102674

  25. Rahimi, E., & Jung, C. (2024). Identifying pollinator‐friendly sites within urban green spaces for sustainable urban agriculture. Journal of Sustainable Agriculture and Environment, 3(3), e12109. https://doi.org/10.1002/sae2.12109

  26. Vélez, D., & Vivallo, F. (2024). Key areas for conserving and sustainably using oil-collecting bees (Apidae: Centridini, Tapinotaspidini, Tetrapediini) in the Americas. Journal of Insect Conservation, 1-17. https://doi.org/10.1007/s10841-024-00620-0

  27. Ninsin, K.D., Souza, P.G.C., Amaro, G.C., Aidoo, O.F., Barry, E.J.D.V., da Silva, R.S., Osei-Owusu, J., Dofuor, A.K., Ablormeti, F.K., Heve, W.K. & Edusei, G., (2024). Risk of spread of the Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) in Ghana. Bulletin of Entomological Research, 1-20. https://doi.org/10.1017/S0007485324000105

  28. Buebos-Esteve, D. E., Redeña-Santos, J. C., & Dagamac, N. H. A. (2024). Ensemble modeling to identify high conservation value areas for endemic and elusive large-sized mammals of the Philippines. Journal for Nature Conservation, 126657. https://doi.org/10.1016/j.jnc.2024.126657

  29. Esparza-Orozco, A., & Lira-Noriega, A. (2024). Use of secondary diversity data to improve diversity estimates at multiple geographic scales. Biodiversity and Conservation, 1-18. https://doi.org/10.1007/s10531-024-02844-7

  30. Gandaho, S. M., Sogbohossou, E. A., & Thompson, L. J. (2024). NIMO: A graphical user interface‐based R package for species distribution modelling. Ecological Solutions and Evidence, 5(3), e12385. https://doi.org/10.1002/2688-8319.12385

  31. Kougioumoutzis, K., Constantinou, I., & Panitsa, M. (2024). Rising Temperatures, Falling Leaves: Predicting the Fate of Cyprus’s Endemic Oak under Climate and Land Use Change. Plants, 13(8), 1109. https://doi.org/10.3390/plants13081109

  32. Somerville, R., MacNeil, C., & Lee, F. (2024). Habitat suitability of Aotearoa New Zealand for the recently invaded gold clam (Corbicula fluminea). New Zealand Journal of Marine and Freshwater Research, 1-18. https://doi.org/10.1080/00288330.2024.2368856

  33. Marom, N., Peretz, A. O., Lazagabaster, I. A., Meiri, M., & Meiri, S. (2024). Water voles of Lake Hula: assessing their past, present, and future. European Journal of Wildlife Research, 70(2), 34. https://doi.org/10.1007/s10344-024-01781-8

  34. Rahimi, E., & Jung, C. (2024). A global evaluation of urban agriculture potential for pollinator‐dependent crops in major cities. Urban Agriculture & Regional Food Systems, 9(1), e20058. https://doi.org/10.1002/uar2.20058

  35. Castillo, D. S. C., & Higa, M. (2024). Strengthening ecologically based rodent management in the Philippines using maximum entropy (MaxEnt) predictions. Journal of Tropical Ecology, 40, e19. https://doi.org/10.1017/S0266467424000208

  36. Tytar, V., Kozynenko, I., & Navakatikyan, M. (2024). Modelling the distribution of the proboscis monkey (Nasalis larvatus) in Sabah (Borneo) based on remotely sensed high-resolution global cloud dynamics. Theriologia Ukrainica, 27, 103-111. http://doi.org/10.53452/TU2711

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