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 University, New York, New York, 2003
Research and Creative Works
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.
ENS 511: Plant Ecology and Conservation
ENS 610: Environmental Science I
ENS 623: Research & Statistical Methods
ENS 772: Thesis Preparation
ENS 792: Rsrch in Envrnmntl Sci I
ENS 793: Rsrch in Envrnmntl Sci II
ENS 798: Tpc: Environmental Science
ENV 100: Water, Wildlife and Windmills
ENV 110: Nature & Culture: Connections
ENV 221: Envrmntl Sci: Web of Life
ENV 498: Mentoring Seminar
ENV 499: Senior Year Exp/Environmental
EP 603: Envrnmntl Sci for Policymakers
EP 610: Cntmpry Issues in EP: Capstone
ESP 610: Prncples of Envrnmntl Sci
ESP 792: Research 1
LAW 802: Science for Env. Lawyers
MAT 141: Intro Stats for the Life Sci
Publications and Presentations
A question of dissemination: Assessing the practices and implications of research in tropical landscapes
Toomey, A. H., Alvaro, Mar\'\ia Eugenia Copa, ., Aiello-Lammens, M. E., Cossio, O. L. & Barlow, J. (2019). Ambio. Vol 48 (Issue 1) , pages 35--47.
Local management in a regional context: Simulations with process-based species distribution models
Szewczyk, T. M., Lee, T., Ducey, M. J., Aiello-Lammens, M. E., Bibaud, H. & Allen, J. M. (2019). Ecological Modelling. Vol 413 , pages 108827.
Pumas as ecosystem engineers: ungulate carcasses support beetle assemblages in the Greater Yellowstone Ecosystem
Barry, J. M., Elbroch, L. M., Aiello-Lammens, M. E., Sarno, R. J., Seelye, L., Kusler, A., Quigley, H. B. & Grigione, M. M. (2019). Oecologia. Vol 189 (Issue 3) , pages 577--586.
Statistical Methods for Modeling Traits
Aiello-Lammens, M. E. & Silander, Jr, J. A. (2019). Handbook of Environmental and Ecological Statistics. , pages 371.
Combining Natural History Collections and Field Observations to Understand Species invasions
Aiello-Lammens, M. E. (2019, January 30). Annual NYC Restoration Practitioners Meeting. NYS DEC,
Professional Contributions and Service
- 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