Lundquist Urban Ecology Lab

Ecology in, of, and with New York City.

Cities are growing around the world, changing the places where people and other species live. We study what those changes mean for biodiversity and ecological processes in urban green spaces and freshwater ecosystems.

Explore our research Meet the lab

Urban ecology fieldwork in New York City

Northeastern University – New York City

About the lab

Urban ecology, spatial analysis, and undergraduate research.

The Lundquist Urban Ecology Lab is led by Dr. Matthew J. Lundquist, Associate Teaching Professor at Northeastern University – New York City.

Our research combines biodiversity fieldwork with GIS, remote sensing, and spatial analysis. Whenever possible, we use open-source tools and public data so students, researchers, and conservation practitioners can follow, reuse, and build on the work.

Collaborative research

Student researchers are integral to the lab. They help shape questions, carry out fieldwork, analyze data, develop methods, and share what we learn. Many of the lab’s papers include students as co-authors.

Current work

Research

Our research focuses on urban rivers, insect biodiversity in small green spaces, connections between pollinator habitats, and science pedagogy.

What we ask

How does urbanization alter biodiversity, food webs, habitat connectivity, and ecosystem function?

How we work

Field surveys, GIS, remote sensing, graph analysis, computer vision, and open-source research tools.

How we share it

Papers, open-source mapping tools, public data projects, and teaching materials.

The Bronx River study system in New York City

Aquatic ecology

Urban rivers

Urban development throughout a watershed can change both predators and prey in a river. In the Bronx River, fish such as blacknose dace, alewife, and American eel rely on aquatic macroinvertebrates for food. We study those invertebrate communities and the gut contents of fish to understand how city life is reshaping the river’s food web.

Study system: Bronx River watershed
Methods: Macroinvertebrate surveys, fish diet analysis, watershed GIS

Hernandez JE, Lundquist MJ (2025). Limited Diets of Eastern Blacknose Dace Within the Highly Urbanized Bronx River, New York, USA. Urban Naturalist Notes (12) N1–N7.

Aerial view of Central Park and surrounding Manhattan buildings

Photo: Dmitri Zotov / Unsplash

Urban biodiversity

Bug roads

We use GIS and pathfinding methods—something like Google Maps for insects—to estimate how pollinators might move between green spaces while navigating building-lined streets. We call these routes “bug roads.” They help us identify green spaces that may be especially important for connectivity and places where pollinator habitat could make the greatest difference.

Comparative analysis: 74 completed city datasets across six continents, with additional cities in process
Methods: LiDAR, open GIS, least-cost paths, graph connectivity

Lundquist MJ, Lovejoy PC, Fay BG, Hernandez JE, Madrid M (2025). Bug Roads: Modeling Green Space Connectivity and Pollinator Habitat in a Large City Using Open GIS Data and Tools. Ecological Applications, 35(7), e70128.

Student researcher sampling a New York City tree pit

Green infrastructure

Small green spaces

Large parks receive much of the attention in urban ecology, but smaller patches of green are everywhere. We study insects in New York City tree pits and other small green spaces to learn which species use them and how these easily overlooked habitats contribute to urban biodiversity and ecosystem services.

Habitats: Tree pits, green roofs, parks, and urban gardens
Approaches: Insect surveys, aerial imagery, LiDAR, machine vision

Lundquist MJ, Weisend MR, Kenmore HH (2022). Insect biodiversity in urban tree pit habitats. Urban Forestry & Urban Greening, 78, 127788.

Photo: Christopher Gower / Unsplash

Science education

Science pedagogy

We explore practical ways to bring data analysis, programming, and AI into science courses, whether students are working together in a classroom or learning remotely.

Courses: Ecology, conservation, biostatistics, and urban ecosystems
Tools: R, Python, interactive web applications, hybrid labs

Lundquist MJ and Aguanno A (2024). Here and there: a novel hybrid remote/in-person college-level science lab model at a small, primarily undergraduate institution. Journal of College Science Teaching (53) 205–210.

Across the lab

Projects underway

Spatial ecology

LiDAR vegetation structure and pathfinding

We classify LiDAR point clouds into low, medium, and high vegetation and use those height classes as movement-cost surfaces. The NYC analysis includes more than 74,000 paths between park pairs and measures vegetation coverage, gaps, and ecological stepping stones.

LiDAR point-cloud classification
Least-cost paths and graph networks
74,000+ NYC park-pair paths

Molecular ecology

Megachile texana genomic and microbiome analysis

We are using genomic methods and 16S rRNA sequencing to study the leafcutter bee Megachile texana and examine how bee-associated microbial communities vary across urban–rural gradients. The project connects genomic analysis with questions about urban environmental conditions and pollinator biology.

Megachile texana
16S rRNA sequencing
Genomic and microbial diversity analysis

Remote sensing

Green-roof and canopy detection

We combine NAIP multispectral imagery, LiDAR canopy measurements, NDVI, texture, and building geometry to tell vegetated roofs apart from overhanging trees and map urban vegetation more accurately.

NAIP and LiDAR processing
Computer vision and texture analysis
Interactive manual verification

Pollinator ecology

Pollinator corridor effectiveness

This project tests whether parks connected by high-quality vegetation corridors support greater pollinator richness and occurrence density. It links vegetation-path metrics with GBIF pollinator records while accounting for park area, isolation, and habitat quality.

GBIF occurrence records
Corridor quality and park connectivity
Regression and null-model analysis

Urban microclimate

Park cooling and thermal comfort

Field transects across Manhattan parks measure how air temperature, humidity, and perceived thermal comfort change from park interiors into surrounding streets. The analysis connects cooling extent with canopy cover, park size, urban form, and building height.

Temperature and humidity transects
PET and UTCI thermal-comfort metrics
LiDAR canopy and urban-form predictors

Molecular identification

DNA barcoding of urban pollinators

We use DNA barcodes alongside physical traits to identify urban pollinators. Sanger sequences are cleaned and compared with reference databases to help confirm each specimen’s identity.

Sanger sequence processing
BLAST species identification
Pollinator biodiversity records

Research practice

Methods, data, and teaching

We move between field ecology, maps, code, and molecular data. Students learn these methods by using them in the lab’s research.

01 · Spatial modeling

Connectivity and pathfinding

We build graph and least-cost path models to ask how buildings, streets, parks, and vegetation shape movement through cities. We use QGIS, GeoPandas, Shapely, rasterio, igraph, spatial indexing, and PostGIS to work across many different cities.

02 · Remote sensing

LiDAR and urban vegetation

LiDAR point clouds are classified into vegetation-height strata and combined with NAIP and satellite imagery. These data support vegetation-corridor models, park-cooling studies, canopy assessment, and computer-vision detection of green roofs.

03 · Molecular ecology

Genomics and microbial diversity

Our molecular work includes 16S rRNA analysis of bee gut microbiomes, genomic analysis of Megachile texana, and DNA barcoding of urban pollinators. Sequence-based identification complements field surveys and morphology-based taxonomy.

04 · Quantitative ecology

Statistics and reproducible computing

We work in R and Python on questions involving diversity, community composition, spatial patterns, regression, null models, and networks. Docker, Git, shared data, and scripts help us keep larger analyses organized and repeatable.

05 · Field ecology

Organisms, habitats, and microclimate

Field methods include aquatic macroinvertebrate surveys, fish gut-content analysis, pollinator sampling, riparian habitat assessment, and insect identification. New park transects connect temperature, humidity, thermal comfort, canopy cover, and surrounding urban form.

06 · Teaching and communication

Courses and public tools

Courses in ecology, conservation biology, biostatistics, and urban ecosystems use real data from research. GriffyStats and our interactive web applications make statistical lessons and New York City environmental data available beyond the classroom.

Selected publications

Recent work

2026
Croman J.R. et al. (including Lundquist, M.J.). Limno-STOICH: a comprehensive database linking the elemental stoichiometry of organisms with inland aquatic habitats. Limnology and Oceanography Letters, e70105.
2025
Lundquist, M.J., Lovejoy, P.C., Fay, B.G., Hernandez, J.E., Madrid, M. Bug Roads: Modeling Green Space Connectivity and Pollinator Habitat in a Large City Using Open GIS Data and Tools. Ecological Applications, 35(7), e70128.
2024
Shen, M. et al. (including Lundquist, M.J.). FreshLanDiv: A global database of freshwater biodiversity across different land uses. Global Ecology and Biogeography, 33, e13917.
2023
Lundquist, M.J., Scott, E.A. Patterns of aquatic insect biodiversity in the highly urbanized Bronx River, NY. Northeastern Naturalist, 30(2), 122–134.

The lab

People

Principal Investigator

Dr. Matthew J. Lundquist

Associate Teaching Professor · Northeastern University – New York City

Chair, Urban Ecosystem Ecology Section, Ecological Society of America

I am an urban ecologist whose research combines field-based biodiversity studies with GIS, remote sensing, spatial modeling, and genomic analysis. My work examines how the structure of cities affects habitat connectivity, freshwater communities, pollinators, and urban green infrastructure.

Email LinkedIn GitHub GriffyStats

Student collaborators

Student researchers are part of how the lab does science.

Students take part in fieldwork, analysis, method development, and interpretation. When their work contributes to a paper, they are included as co-authors.