Peer-reviewed

  1. Kass, J. M., Guénard, B., Jenkins, C., Dudley, K. L., Azuma, F., Fisher, B., Parr, C., Gibb, H., Longino, J. T., Ward, P. S., Chao, A., Shattuck, S., Lubertazzi, D., Weiser, M., Jetz, W., Guralnick, R., Sanders, N., Dunn, R., Economo, E. P. (2022). The global distribution of known and undiscovered ant biodiversity. Science Advances, Accepted.
  2. Andrade-Silva, J., Baccaro, F. B., Prado, L. P., Guénard, B., Warren, D. L., Kass, J. M., Economo, E. P., & Silva, R. R. (2022). A large-scale assessment of ant diversity across the Brazilian Amazon Basin: integrating geographic, ecological and morphological drivers of sampling bias. Ecography, Early View. https://doi.org/10.1111/ecog.06295
  3. Morente-López, J., Kass, J. M., Lara-Romero, C., Serra-Diaz, J. M., Soto-Correa, J. C., Anderson, R. P., & Iriondo, J. M. (2022). Linking ecological niche models and common garden experiments to predict phenotypic differentiation in stressful environments: Assessing the adaptive value of marginal populations in an alpine plant. Global Change Biology, 00, 1 – 20. https://doi.org/10.1111/gcb.16181
  4. Merow, C.; Galante, P. J; Kass, J. M; Aiello-Lammens, M. E; Babich Morrow, C.; Gerstner, B. E, et al. (2022). Operationalizing expert knowledge in species' range estimates using diverse data types. Frontiers of Biogeography. http://dx.doi.org/10.21425/F5FBG53589
  5. Peterson, A. T., Aiello-Lammens, M. E., Amatulli, G., Anderson, R. P., Cobos, M. E., Diniz-Filho, J. A. F., Escobar, L. E., Feng, X., Franklin, J., Gadelha Jr., L. M. R., Georges, D., Guéguen, M., Gueta, T., Ingenloff, K., Jarvie, S., Jiménez, L., Karger, D. N., Kass, J. M., Kearney, M. R., Loyola, R., Machado-Stredel, F., Martínez-Meyer, E., Merow, C., Mondelli, M. L., Mortara, S. B., Muscarella, R., Myers, C. E., Naimi, B., Noesgaard, D., Ondo, I., Osorio-Olvera, L., Owens, H. L., Pearson, R., Pinilla-Buitrago, G. E., Sánchez-Tapia, A., Saupe, E. E., Thuiller, W., Varela, S., Warren, D. L., Wieczorek, J., Yates, K., Zhu, G., Zuquim, G., Zurell, D. (2022). ENM2020: A free online course and set of resources on modeling species niches and distributions. Biodiversity Informatics, 17: 1-5. https://doi.org/10.17161/bi.v17i.15016
  6. Kass, J. M., Takashina, N., Friedman, N. R., Kusumoto, B., Blair, M. E. (2022). Idea paper: Improving forecasts of community composition with lightweight biodiversity monitoring across ecological and anthropogenic disturbance gradients. Ecological Research, Early View. https://doi.org/10.1111/1440-1703.12294; open-access preprint: https://doi.org/10.32942/osf.io/mxg6q
  7. Owens, H. L., Merow, C., Maitner, B., Kass, J. M., Barve, V., Guralnick, R. (2021). occCite: Tools for querying and managing large biodiversity occurrence datasets. Ecography, 44: 1228 – 125. https://doi.org/10.1111/ecog.05618
  8. Hu, Z. M., Zhang, Q. S., Zhang, J., Kass, J. M., Mammola, S., Fresia, P., Draisma, S. G. A., Assis, J., Jueterbock, A., Yokota, M., & Zhang, Z. (2021). Intraspecific genetic variation matters when predicting seagrass distribution under climate change. Molecular Ecology., 30: 3840 – 3855. https://doi.org/10.1111/mec.15996
  9. Kass, J. M., Muscarella, R., Galante, P. J., Bohl, C., Pinilla-Buitrago, G. E., Boria, R. A., Soley‐Guardia, M., & Anderson, R. P. (2021). ENMeval 2.0: redesigned for customizable and reproducible modeling of species’ niches and distributions. Methods in Ecology and Evolution, 12: 1602 – 1608. https://doi.org/10.1111/2041-210X.13628
  10. Gavrutenko, M., Gerstner, B. E., Kass. J. M., Goodman, S., & Anderson, R. P. (2021). Temporal matching of occurrence localities and forest cover data helps improve range estimates and predict climate change vulnerabilities. Global Ecology and Conservation, 27: e01569. https://doi.org/10.1016/j.gecco.2021.e01569
  11. Zhang, Z., Kass, J. M., Mammola, S., Koizumi, I., Xuecao, L., Tanaka, K., Ikeda, K., Suzuki, T., Yokota, M., & Usio, N. (2021). Lineage‐level distribution models lead to more realistic climate change predictions for a threatened crayfish. Diversity and Distributions, 27: 684 – 695. https://doi.org/10.1111/ddi.13225
  12. Kass, J. M., Meenan, S. I., Tinoco, N., Burneo, S. F., & Anderson, R. P. (2021). Improving area of occupancy estimates for parapatric species using distribution models and support vector machines. Ecological Applications, 31: e02228. https://doi.org/10.1002/eap.2228
  13. Ryo, M., Angelov, B., Mammola, S., Kass, J. M., Benito, B. M., & Hartig, F. (2021). Explainable artificial intelligence enhances the ecological interpretability of black‐box species distribution models. Ecography, 44: 199-205. https://doi.org/10.1111/ecog.05360
  14. Kass, J. M., Tingley, M. W., Tetsuya, T., Koike, F. (2020). Co-occurrence of invasive and native carnivorans affects occupancy patterns across environmental gradients. Biological Invasions, 22: 2251 – 2266. https://doi.org/10.1007/s10530-020-02254-0
  15. Kass, J. M., Anderson, R. P., Espinosa‐Lucas, A., Juárez‐Jaimes, V., Martínez‐Salas, E., Botello, F., Taverna, G., Flores-Martínez, J. J., & Sánchez‐Cordero, V. (2020). Biotic predictors with phenological information improve range estimates for migrating monarch butterflies in Mexico. Ecography, 43(3), 341-352. Editor's Choice. https://doi.org/10.1111/ecog.04886
  16. Merow, C., Maitner, B. S., Owens, H. L., Kass, J. M., Enquist, B. J., Jetz, W., & Guralnick, R. (2019). Species' range model metadata standards: RMMS. Global Ecology and Biogeography, 28(12), 1912-1924. https://doi.org/10.1111/geb.12993
  17. Bohl, C. L., Kass, J. M., & Anderson, R. P. (2019). A new null model approach to quantify performance and significance for ecological niche models of species distributions. Journal of Biogeography, 46(6), 1101-1111. _Editor's Choice_. https://doi.org/10.1111/jbi.13573
  18. Reid, B. N., Kass, J. M., Wollney, S., Jensen, E. L., Russello, M. A., Viola, E. M., Pantophlet, J., Iverson, J. B., Peery, M. Z., Raxworthy, C. J., & Naro-Maciel, E. (2019). Disentangling the genetic effects of refugial isolation and range expansion in a trans-continentally distributed species. Heredity, 122(4), 441-457. https://doi.org/10.1038/s41437-018-0135-5
  19. Kass, J. M., Vilela, B., Aiello‐Lammens, M. E., Muscarella, R., Merow, C., & Anderson, R. P. (2018). Wallace: A flexible platform for reproducible modeling of species niches and distributions built for community expansion. Methods in Ecology and Evolution, 9(4), 1151-1156. https://doi.org/10.1111/2041-210X.12945
  20. Gerstner, B. E., Kass, J. M., Kays, R., Helgen, K. M., & Anderson, R. P. (2018). Revised distributional estimates for the recently discovered olinguito (Bassaricyon neblina), with comments on natural and taxonomic history. Journal of Mammalogy, 99(2), 321-332. https://doi.org/10.1093/jmammal/gyy012
  21. Guevara, L., Gerstner, B. E., Kass, J. M., & Anderson, R. P. (2018). Toward ecologically realistic predictions of species distributions: A cross‐time example from tropical montane cloud forests. Global Change Biology, 24(4), 1511-1522. https://doi.org/10.1111/gcb.13992
  22. Muscarella, R., Galante, P. J., Soley‐Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M., & Anderson, R. P. (2014). ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in Ecology and Evolution, 5(11), 1198-1205. https://doi.org/10.1111/2041-210X.12261
  23. Klosterhaus, S., McKee, L. J., Yee, D., Kass, J. M., & Wong, A. (2014). Polychlorinated biphenyls in the exterior caulk of San Francisco Bay Area buildings, California, USA. Environment International, 66, 38-43. https://doi.org/10.1016/j.envint.2014.01.008
  24. Olson, D., DellaSala, D. A., Noss, R. F., Strittholt, J. R., Kass, J., Koopman, M. E., & Allnutt, T. F. (2012). Climate change refugia for biodiversity in the Klamath-Siskiyou ecoregion. Natural Areas Journal, 32(1), 65-74. https://doi.org/10.3375/043.032.0108

Academic Media and Blogs

Kass, J. M., Meenan, S. I., Tinoco, N., Burneo, S. F., & Anderson, R. P. (2021, January 13). Improving Area of Occupancy Estimates for Parapatric Species Using Distribution Models and Support Vector Machines. Bulletin of the Ecological Society of America, 102:e01813. https://doi.org/10.1002/bes2.1813

Kass, J. M., Juárez-Jaimes, Flores-Martínez, J. J., Sánchez-Cordero, V. (2020, June 30). New range estimates for migrating monarch butterflies in Mexico: implementing and interpreting biotic variables and future conservation applications [Blog post]. https://www.ecography.org/blog/new-range-estimates-migrating-monarch-butterflies-mexico-implementing-and-interpreting-biotic

Kass, J. M., Aiello‐Lammens, M. E., Vilela, B., Muscarella, R., Merow, C., & Anderson, R. P. (2018, March 16). Code-Based Methods and the Problem of Accessibility [Blog post]. https://methodsblog.com/2018/03/16/code-methods-accessibility/

Professional (non-academic)

Kass, J. M., Walker, J., Cayce, K., Senn, D., Williams, M. (2011). White Paper on Regional Landscape Characterization for Low Impact Development Site Suitability Analysis. Richmond, CA. San Francisco Estuary Institute. Report No.: SFEI-653.

Klosterhaus, S., Yee, D., Kass, J. M., Wong, A., McKee, L. (2011). PCBs in Caulk Project: Estimated Stock in Currently Standing Buildings in a San Francisco Bay Study Area and Releases to Stormwater during Renovation and Demolition. Richmond, CA. San Francisco Estuary Institute. Report No.: SFEI-651.