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
Physics
Ecology, plant ecology, invasion biology, global change biology, quantitative ecology
Do forest pests and pathogens facilitate invasions of Tier 2 species?
Aiello-Lammens, M. E. & Rubbo, M. June 2026 - May 2029. NYS Department of Environmental Conservation, State. Funded. This project will focus on determining if invasions by Tier 2 invasive species are facilitated by the presence of forests pests and pathogens. Our hypothesis is that openings in the forest canopy created by pathogens/pests will provide a means for newly introduced invasive species to become established. We will identify forested locations in the Lower Hudson Valley with active infestations of Hemlock Wooly Adelgid (HWA) and Beech Lead Disease (BLD). These areas will represent a mix of infection status and/or duration. At each location we will measure a suite of environmental variables including canopy cover, soil moisture, and leaf-litter depth. We will also quantify the composition of understory and groundlayer vegetation. These data will allow us to determine if Tier 2 invasive species are establishing in these areas. These data will then be used to parameterize a model that can be used to identify potential locations of Tier 2 invasive species based on the presence of HWA and BLD and direct management efforts to prevent their expansion.
RCN-UBE: Biological and Environmental Data Education Network: Preparing Instructors to Integrate Data Science into Undergraduate Biology and Environmental Science Curricula
Aiello-Lammens, M. E., Emery, N., Supp, S., O'Donnel, K. & Broughton, L. October 2021 - September 2027. National Science Foundation, Federal. Funded. This project aims to serve the national interest by building and supporting an engaged community of college instructors trained in integrating data science skills across introductory biology and environmental science curricula. Students need foundational and repeated exposure to data science skills that are necessary for success in Science, Technology, Engineering, and Math fields and beyond. However, there are barriers to incorporating data science skills into established biology and environmental science curricula, including a knowledge gap between the skills students need and the training faculty have, curricula that are already perceived as overcrowded, confusion over what the key skills are, and a lack of confidence in teaching these skills. The BEDE (Biological and Environmental Data Education) Network will address the unmet need for data science skills and overcome barriers through professional development opportunities for biology and environmental science instructors. The BEDE Network will develop and deliver data science skills- and pedagogy-focused workshops to instructors, develop and disseminate guides for integrating these skills into biology and environmental science courses to instructors and departments, and will foster a collaborative community of educators via a combination of virtual and in-person meetings and asynchronous online interaction and resource sharing. These activities align with the NSF IUSE intention to enhance and improve undergraduate STEM education in the US to prepare students for a competitive workforce that increasingly requires data science skills.
The BEDE Network will conduct activities in four main areas: (1) convene annual network meetings, (2) develop and deliver “train the teacher” and “train the trainer” workshops, (3) design and publish a curriculum guide, and (4) establish an active and diverse community of practicing educators that are incorporating key data science skills into their undergraduate biology and/or environmental science courses. Six main data science areas will be covered in the activities (data management, data analysis, data visualization, programming, modeling, and reproducibility), with ethical frameworks applied to each to anticipate and address potential challenges that may arise during classroom activities. Each activity area will include regular assessments conducted both internally and externally including annual evaluations, pre/post surveys, and reflections. The BEDE Network will be an inclusive and diverse community drawing educators from multiple institution types, career paths, and career stages, and will be designed to last beyond the 5-year term of the RCN-UBE grant. By specifically focusing on undergraduate instructors, the BEDE Network will be able to train educators who in turn are positioned to benefit a broad population of students including STEM majors and non-majors, and from groups that are currently underrepresented in the sciences. This more inclusive group of students will learn and use data science skills in their courses that will prepare them for success in the “Big Data” world we are living in, no matter what their chosen career will be. This project is being jointly funded by the Directorate for Biological Sciences, Division of Biological Infrastructure, and the Directorate for Education and Human Resources, Division of Undergraduate Education as part of their efforts to address the challenges posed in Vision and Change in Undergraduate Biology Education: A Call to Action (http://visionandchange/finalreport/).
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 772: Thesis Preparation
ESP 792: Research 1
ESP 793: Research II
ESP 794: Cntmprry Envrnmntl Issues: Cps
LAW 802: Science for Env. Lawyers
MAT 141: Intro Stats for the Life Sci
A Brief Introduction to Species Distribution Modeling for Conservation Educators and Practitioners
Aiello-Lammens, M. E., Paz, A., Johnson, B. A., Blair, M. E. & Pearson, R. G. (2023). Lessons in Conservation. Vol 13 , pages 61-75.
Species Distribution Modeling for Conservation Educators and Practitioners
Aiello-Lammens, M. E., Anderson, R., Blair, M. E., Johnson, B. A., Kass, J., Meenan, S. I., Paz, A., Pearson, R. & Pinilla-Buitrago, G. E. (2023).
Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training
Emery, N. C., Crispo, E., Supp, S. R., Farrell, K. J., Kerkhoff, A. J., Bledsoe, E. K., O'Donnell, K. L., McCall, A. C. & Aiello-Lammens, M. E. (2021). BioScience. Vol 71 (Issue 12) , pages 1274-1287.
Dyson Professor Matthew Aiello-Lammens speaks with News12 following a retaining wall collapse in Yonkers, explaining how saturated soil and hydrostatic pressure—combined with freeze-thaw cycles—can place significant stress on retaining structures.
Environmental Studies Professor Matthew Aiello-Lammens provides an expert analysis to WHYY (part of NPR and PBS) discussing the fire risks associated with dry conditions and wind patterns following the Jones Road wildfire in New Jersey.
Environmental Science Professor Matthew Aiello-Lammens speaks with News 12 about the recent Yonkers rockslide that caused a large boulder to partially collapse a building, he notes landslides this time of year are not uncommon.