Lundquist Urban Ecology Lab

Urban ecology in New York City.

Urbanization is increasing around the world and understanding the impacts that cities have on the natural world is extremely important. We aim to understand how urbanization affects biodiversity and ecological function in urban green spaces and freshwater ecosystems.

Explore our research Meet the lab

Urban ecology fieldwork in New York City

Northeastern University–NYC

About the lab

Urban ecology, spatial analysis, and undergraduate research.

The Lundquist Urban Ecology Lab is based at Northeastern University–NYC and led by Dr. Matthew J. Lundquist, Associate Teaching Professor.

Our research combines field-based biodiversity assessment with GIS, remote sensing, and computational spatial analysis. We use open-source tools and public datasets so that our methods can be reproduced and adapted by students, researchers, and conservation practitioners.

10peer-reviewed publications

13+student researchers mentored

7student co-authors

Current work

Research

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

Questions

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

Methods

Field surveys, GIS, remote sensing, graph analysis, computer vision, and reproducible open-source workflows.

Outputs

Peer-reviewed research, open-source spatial workflows, public data applications, and science education.

The Bronx River study system in New York City

Aquatic ecology

Urban rivers

Watershed urbanization can impact the richness and abundance of both predators and their prey in aquatic ecosystems. The Bronx River is greatly impacted by both. Fish in the Bronx River, including blacknose dace, alewife, and American eel, which are of conservation importance, rely on aquatic macroinvertebrates as a food source. We are exploring the impact that urbanization has on stream food webs by studying macroinvertebrate biodiversity and analyzing the gut content of Bronx River fish.

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

Using GIS software and shortest-distance algorithms (think Google Maps), we are modeling the distance insects need to travel between points in the city and green spaces while also navigating building-lined streets. We are calling these paths “bug roads” and we are using this information to identify important green spaces (shortest bug roads) and viability of locations for pollinator houses and urban bee hives throughout the five boroughs, starting with Manhattan.

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

Green spaces in cities are important for many reasons, including providing a bit of nature for city residents and providing ecosystem services that have previously been lost through the process of urbanization. A lot of attention has been given to large green areas like city parks. However, little is known about the function of micro-green spaces like tree pits for supporting biodiversity. This project aims to describe insect communities in tree pits throughout New York City and assess their potential for providing 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 have been working on ways to integrate technology into both in-person and remote classrooms. In particular, we are looking to devise ways of including big data analysis, programming, and AI tools into science classrooms.

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.

Active projects

Current research projects

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

Our green-infrastructure pipeline combines NAIP multispectral imagery with LiDAR canopy metrics, NDVI, texture filters, and building geometry to distinguish vegetated roofs from overhanging trees and characterize urban vegetation.

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

DNA barcode sequences are used to identify urban pollinator specimens and complement morphology-based identification. The active workflow processes Sanger sequence files and compares cleaned sequences against reference databases.

Sanger sequence processing
BLAST species identification
Pollinator biodiversity records

Research practice

Methods, data, and teaching

The lab combines field ecology with spatial, computational, and molecular approaches. The same methods also shape how students learn to work with ecological data.

01 · Spatial modeling

Connectivity and pathfinding

We build graph-based and least-cost path models to measure how buildings, streets, parks, and vegetation shape movement through cities. Current workflows use QGIS, GeoPandas, Shapely, rasterio, igraph, spatial indexing, and PostGIS to process datasets from dozens of 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

Analyses are developed in Python and R and include diversity metrics, multivariate ordination, spatial statistics, regression, null models, and network analysis. Docker, Git, shared data infrastructure, and scripted pipelines make large analyses 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

Ecology, conservation biology, biostatistics, and urban-ecosystem courses integrate real data and research workflows. GriffyStats and interactive web applications provide public access to statistical instruction and New York City environmental data.

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–NYC

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

Past student researchers