Our Faculty

Matthew Aiello-Lammens

Assistant Professor

Dyson College of Arts and Sciences

Environmental Studies and Science

  • @Pleasantville
    Room 102
Office Hours

Fall 2020

Mon 10:00am-12:00pm

Tue 3:00pm-5:00pm

Thu 8:30pm-9:30pm

Office Hours

Fall 2020

Office Hours

Fall 2020


I am a ecologist with interests in conservation biology, plant ecology, demography, community dynamics, and quantitative methods. I am also dedicated to protecting natural places and biodiversity.


PhD, Stony Brook University, Stony Brook, New York, 2014
Ecology and Evolution

BA, Columbia Univesity, New York, New York, 2003


Toomey, A. H., Alvaro, Mar\'\ia Eugenia Copa, ., Aiello-Lammens, M. E., Cossio, O. L. & Barlow, J. (2019). A question of dissemination: Assessing the practices and implications of research in tropical landscapes. Ambio. Vol 48 (Issue 1) , pages 35--47.

Szewczyk, T. M., Lee, T., Ducey, M. J., Aiello-Lammens, M. E., Bibaud, H. & Allen, J. M. (2019). Local management in a regional context: Simulations with process-based species distribution models. Ecological Modelling. Vol 413 , pages 108827.

Barry, J. M., Elbroch, L. M., Aiello-Lammens, M. E., Sarno, R. J., Seelye, L., Kusler, A., Quigley, H. B. & Grigione, M. M. (2019). Pumas as ecosystem engineers: ungulate carcasses support beetle assemblages in the Greater Yellowstone Ecosystem. Oecologia. Vol 189 (Issue 3) , pages 577--586.

Aiello-Lammens, M. E. & Silander, Jr, J. A. (2019). Statistical Methods for Modeling Traits. Handbook of Environmental and Ecological Statistics. , pages 371.

Schliep, E. M., Gelfand, A. E., Mitchell, R. M., Aiello-Lammens, M. E. & Silander, Jr, J. A. (2018). Assessing the joint behaviour of species traits as filtered by environment. Methods in Ecology and Evolution. Vol 9 (Issue 3) , pages 716--727.

Moore, T., Schlichting, C., Aiello-Lammens, M. E., Mocko, K. & Jones, C. (2018). Divergent trait and environment relationships among parallel radiations in Pelargonium (Geraniaceae): a role for evolutionary legacy?. New Phytologist. Vol 219 (Issue 2) , pages 794-807.

Moore, T. E., Bagchi, R., Aiello-Lammens, M. E. & Schlichting, C. D. (2018). Spatial autocorrelation inflates niche breadth--range size relationships. Global ecology and biogeography. Vol 27 (Issue 12) , pages 1426--1436.

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. Vol 9 (Issue 4) , pages 1151--1156.

Slingsby, J. A., Merow, C., Aiello-Lammens, M. E., Allsopp, N., Hall, S., Mollmann, H. K., Turner, R., Wilson, A. M. & Silander, J. A. (2017). Intensifying postfire weather and biological invasion drive species loss in a Mediterranean-type biodiversity hotspot. Proceedings of the National Academy of Sciences. Vol 114 (Issue 18) , pages 4697--4702.

Ariori, C., Aiello-Lammens, M. E. & Silander, Jr, J. A. (2017). Plant invasion along an urban-to-rural gradient in northeast Connecticut. Journal of Urban Ecology. Vol 3 (Issue 1) , pages jux008.

Aiello-Lammens, M. E. & Ak\ccakaya, H Resit, . (2017). Using global sensitivity analysis of demographic models for ecological impact assessment. Conservation biology. Vol 31 (Issue 1) , pages 116--125.


Aiello-Lammens, M. E. (2019, January 30). Annual NYC Restoration Practitioners Meeting. Combining Natural History Collections and Field Observations to Understand Species invasions. NYS DEC, Forest Park, Queens.

Aiello-Lammens, M. E. (2017, November 14). Downstate Recreation Conference. Do I belong here? Managing non-native invasive species. New York State Recreation and Park Society, Westchester, New York.

Aiello-Lammens, M. E. (2017, November 7). Examining Patterns and Processes of the Invasion of Frangula alnus With An Integrated Model Framework. Torrey Botanical Society, New York Botanical Garden.


Ecology, plant ecology, invasion biology, global change biology, quantitative ecology.

Grants, Sponsored Research and Contracts

RCN-UBE Incubator: The Biological and Environmental Data Education Network
Kerkhoff, A., Aiello-Lammens, M. E., Supp, S. & Echeverria-Londono, S. October 2018 - September 2020. National Science Foundation , Federal , $72,361.00. Funded. he Biological and Environmental Data Education (BEDE) project seeks to create a community of biologists and data scientists dedicated to empowering undergraduate instructors to bring data science into biology and environmental science curricula. All scientists must now, to some extent, be data scientists--they must manage, analyze, and communicate about data in the context of collaborative, reproducible research. Furthermore, future professionals will need to have data science skills to deal with urgent problems in agriculture, environmental management, and public health. However, most students in biology and environmental science graduate with little data science experience. The BEDE Network will help address this need by focusing on developing the technical skills, curricular resources, and pedagogical confidence of undergraduate instructors so that they can more intentionally include core data science skills in their classes and labs. By engaging an inclusive community of scientists and biology and environmental science educators, BEDE will develop training workshops, curricular materials, and best practices that can be adopted by educators at almost any institution and in almost any course. Biology and environmental science have been fundamentally reshaped by recent technological advances, including increased computational power, sensor technologies, publicly available software and data, and the Internet. Together with these advances, complex, multidisciplinary questions and urgent environmental and public health problems have led to changes in scientific culture and practice, with shifts toward greater collaboration, accountability, and transparency. These technological advances and cultural changes represent an educational challenge: already-full courses and curricula do not prepare students to address data-intensive problems. To assess the main opportunities and obstacles for integrating data science into biology and environmental science curricula, BEDE investigators will use a survey to gather data on faculty attitudes and expertise about it. Data from the survey will be examined at a BEDE workshop, where participants will: 1) develop Train-the-Teachers workshops based on curricular needs of survey respondents, 2) prepare a position/review paper describing barriers and opportunities to incorporating data science in biology and environmental science education; and 3) develop plans for further expansion of the Network.

Culvert Management Planning for Amphibian and Reptile Connectivity
Aiello-Lammens, M. E. & Cronin, J. June 2016 - May 2018. Hudson River Estuary Program , State , $48,520.00. Funded. Protection of ecosystems and key species within the Hudson River Estuary's watershed is one “benefit” of implementing the Hudson River Estuary Action Agenda. Natural resource management planning is a key component of protecting those ecosystems. This includes planning for protection of specific species, groups of species, and specific habitats. We propose to develop an adaptive management plan for prioritizing culvert maintenance actions to enhance connectivity of amphibian habitat, survival of amphibian species, and manage drainage during precipitation events.


New York Flora Association

Torrey Botanical Society

American Association for the Advancement of Science

Ecological Society of America[Chair of Early Career Ecologists Section]

Society for Conservation Biology


  • University Budget Committee [Committee Member]
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