Research
Spatial population dynamics of a grassland bird as revealed by the North American Breeding Bird Survey. Code available here.
I’m an ecologist who enjoys making sense of complex systems to advance environmental conservation. My work blends old-fashioned fieldwork with new molecular tools and data science. On the data side, I’m fond of causal modeling, Bayesian inference, bioinformatics, machine learning, and open, reproducible research practices. On the molecular side, I’m most interested in advancing our ability to monitor biodiversity using novel tools based on the DNA organisms leave behind in the environment (eDNA). More info on active research topics below…
Spatial Population Dynamics & Social-Ecological Systems
spatial population dynamics can be driven by complex interactions within human-natural systems
Spatial synchrony in North American grassland bird populations during two time periods (1968-1993 & 1994-2019). Maps colors indicate higher (red) or lower (blue) levels of local spatial synchrony, or correlated fluctuations with neighboring cells. + indicates cells with 95% credible intervals that do not overlap zero. Data: North American Breeding Bird Survey.
Much of conservation revolves around population size, which is both a spatial and dynamic phenomenon. Human activities can drive spatial population dynamics, directly or indirectly, as part of complex ‘coupled human-natural’ systems. We mapped the spatial synchrony of North American grassland bird populations to highlight regions of potential impact due to synchronous human activities (e.g., agriculture; Allen & Lockwood, Conservation Biology 2021). For one species, we dug in and attempted to quantify this social-ecological network of population drivers (Allen et al. J. Applied Ecology 2021). I’ve collaborated on 2 similar projects. One with Cornell Lab of Ornithology assessing annual-cycle spatial conservation planning in Pacific shorebirds (Donlan et al., Conservation Biology 2023). And one with the Pinsky Lab predicting range shifts of commercially important marine species using Dynamic Range Models.
Ecology of Biological Invasions
Biological invasions are costly and pose serious risks to human and ecological health.
An Acadian Flycatcher nesting in the fork of a Hemlock branch. An invasive insect, the Hemlock Woolly Adelgid, kills a preferred nesting tree and negatively alters forest structure for this species.
How do we best deploy resources to provide early detection and response to forest pests? How do disturbances caused by these organisms affect forest flora and fauna? To address the 1st question, I work with researchers in the Lockwood Lab to combine innovative terrestrial and aquatic eDNA field survey techniques with occupancy and simulation modeling to inform sampling design and survey protocols. The 2nd question formed the basis of my MS research, and I maintain an active collaboration with Dr. Terry Master (emeritus faculty, ESU) and Megan Napoli (research ecologist, Mohonk Preserve, NY) to further this work. Our studies focus on the long-term (~ 20 yr) effects of a destructive invasive insect, the Hemlock Woolly Adelgid, on songbirds within hemlock forests in the Appalachian Mountains.
Biodiversity Monitoring & Rare Species Detection
improving sampling schemes for rare and hard-to-sample wildlife is vital to effective conservation
I am interested in the special monitoring challenges posed hard-to-sample communities and rare and elusive animal species. Related to this, I am working on:
Bayesian occupancy models for the rare and elusive Black Rail in New Jersey salt marshes to inform coastal resiliency and conservation planning (Allen et al., Environmental Conservation 2023).
Improving animal survey methods using novel surface eDNA tools (similar to criminal forensic techniques). We have used this to assess biodiversity of arboreal mammals (Allen et al., Scientific Reports 2023) and forest arthropods (Allen et al. preprint) using eDNA metabarcoding. And to improve reptile detection rates using eDNA and species-specific assays (Kyle et al., Conservation Biology 2022).
Optimizing survey designs for detecting low-abundance invasive species, especially in agricultural and biosecurity applications. Model systems include Spotted Lanternfly within vineyards; khapra beetles in rice shipments; and Chinese Pond Mussel in river systems (Allen et al., Environmental DNA 2021; others in prep.).
Collaborating with researchers at Michelin Ecological Reserve, Bahia, Brazil to optimize survey design and population monitoring for a critically endangered songbird, the Bahia Tapaculo.
Grassland, Coastal, and Marine Conservation and Global Change
Coastal, Marine, and grassland ecosystems have in common a history of intense human usage and extreme vulnerability to global change stressors.
Bobolink relative abundance on two fields at Duke Farms, NJ in summer 2018. Rotational ‘conservation grazing’ will be implemented on the left field in 2020 and population responses will be evaluated. For scale, these former farm fields of heiress Dorris Duke are ~1 km long.
I recently collaborated with colleagues at Rutgers and Cornell Lab of Ornithology to construct habitat models for the rare and elusive Black Rail in New Jersey salt marshes (Allen et al., Environmental Conservation 2023) and shorebirds within the Pacific Flyway (Donlan et al., Conservation Biology 2023). I’m especially interested in integrating these models into efforts to adapt to sea level rise and help reverse population declines. I am also investigating the drivers of grassland songbird populations in agro-ecosystems from local (individual fields) to continental spatial scales (see Publications page). The goal is to shed light on potential policy and management solutions to stem population declines in this vulnerable group. Finally, I’m modelling range shifts for the Atlantic Sea Scallop - the second most valuable fishery on the US east coast behind American Lobster - under climate change using Dynamic Range Models in collaboration with Malin Pinsky’s lab.