About

James S. Clark is the Nicholas Distinguished Professor of Environmental Science at Duke University, with appointments in the Nicholas School of the Environment, the Department of Biology, and the Division of Earth and Ocean Sciences. His research lab focuses on understanding disturbance and climate controls on ecosystem dynamics through long-term experiments and monitoring studies. Clark has made significant contributions to ecological science, particularly in barrier beach dynamics, climate change, and fire studies, earning recognition from the Ecological Society of America with awards such as the William Skinner Cooper Award and the George Mercer Award. He is a Fellow of the Ecological Society of America, a member of the National Academy of Sciences, and the American Academy of Arts and Sciences. Clark has led comprehensive scientific assessments, authored over 250 scientific articles and four books, and served on numerous editorial boards and advisory panels, including testifying before Congress on ecological issues.

Research topics

• Biology
• Ecology
• Mathematics
• Climatology
• Geography
• Sociology
• Geology
• Genetics
• Environmental science
• Physical geography
• Economic geography
• Demography
• Zoology
• Environmental resource management
• Statistics
• Evolutionary biology

Selected publications

• Impact of waves on phytoplankton activity on the Northwest European Shelf: insights from observations and km-scale coupled models

  Ocean science · 2026-02-02 · 1 citations

  articleOpen access

  Abstract. The spring bloom is an annual event in temperate regions of the North Atlantic Ocean where the abundance of photosynthetic plankton increases dramatically. The timing and intensity of the spring bloom is dependent on underlying physical conditions that control ocean stratification and mixing. Although surface waves can be an important source of turbulent kinetic energy to the surface mixed layer, they have seldom been considered explicitly in studies of bloom formation. Here, we investigate the role of surface waves in bloom formation using a combination of satellite observations and numerical models. Satellite observations show a positive correlation between wave activity and chlorophyll concentration in the Northwest European shelf (May–September). In the deeper Northeast Atlantic, increased wave activity correlates with lower chlorophyll during periods of high phytoplankton activity (March-May) and higher chlorophyll when activity is low (below 54° N, July–September). We use a first-of-its-kind, km-scale, two-way coupled ocean-wave model system to investigate both the relationship between wave-driven mixing and bloom formation, and the sensitivity of model results to the method by which wave-driven mixing is parameterised. In deep regions, during the spring bloom, a wave-driven mixing event is likely to mix surface chlorophyll to deeper layers, away from light. In contrast, when phytoplankton activity is low in deep regions, wave-driven mixing can entrain nutrients, fueling the growth of nutrient starved phytoplankton near the surface. In June–October, in shallow but weakly stratified regions of the shelf, surface chlorophyll tends to be elevated following a wave-driven mixing event, which can bring to the surface both phytoplankton and nutrients from deeper layers. When contrasted with ocean-only runs, the two way-coupled ocean-wave model tends to produce greater vertical mixing and a delay in bloom onset. These results indicate bloom dynamics are sensitive to the way in which waves are modelled, and that the role of waves in bloom formation should be considered in future studies.

  PublisherDOI

• Continental Contrasts in Climate Extremes That Control Tree Fecundity

  Global Change Biology · 2026-02-01 · 1 citations

  articleOpen access1st authorCorresponding

  In 2023, more than half of olive harvests (Olea europaea) across Spain, Greece, and Türkiye were lost to drought. The same year late freeze destroyed 90% of the peach crop (Prunus persica) on the Georgia Piedmont and the apple crop (Malus domestica) in central New York, Vermont, and southern Quebec. Climate extremes now rank with the costliest threats to agriculture, but their role in forest recovery from diebacks that are happening globally is unknown for lack of tree fecundity estimates in forests. Tolerance of climate extremes could depend on past exposure but constrained by phylogenetic conservatism. We report a continental scale analysis of climate extremes and forest fecundity across North America and Europe showing that responses to late freeze and drought are happening now. Species differences are not explained by the traits typically included in ecological studies and they are weakly associated with phylogeny. Late freeze, that is, freezing temperatures that follow the onset of flower development in spring, is shown to be "normal" in North America, but not Europe, potentially explaining failed seed production due to delayed onset and the resultant shorter growing period by North American transplants dating back at least to the 18th century. Drought has thus far had the greatest impacts in dry forested regions, but here too, species differences are not explained by traditional trait values. If responses have been buffered from drought and late freeze by past exposure, acclimation and local adaptation prove inadequate as extremes intensify.

  PublisherOA PDFDOI

• Fungal community and taxa specialization to host and environment interactions in two temperate forests

  PLoS ONE · 2025-05-09

  articleOpen accessSenior author

  The structure and function of plant-associated fungal communities (i.e. mycobiome) is shaped by biotic and abiotic factors, and can impact plant community dynamics. We evaluated the effects of different environmental factors in structuring the communities of seedling-associated fungi in temperate tree species, considering both the Janzen-Connell hypothesis as well as the impacts of climate warming. We tested the hypothesis that fungal host-specialization is observed at both the individual fungus and fungal community levels and is modulated by environmental conditions. The seedling fungal communities were characterized from tree species grown in two forests, under experimental manipulation of light, warming, and distance to and density of conspecifics. Fungal communities were analyzed using generalized joint attribute models. While warming, light, and forest site played a role in structuring seedling fungal communities, host, distance to, and density of conspecifics were stronger contributors. Furthermore, we could identify which fungal taxa responded to which predictors. This work supports the concept of fungal host-specialization at the community level, and points to particular fungal taxa which may play roles in density- and distance-dependent regulation of plant species diversity in the studied forests.

  PublisherDOI

• Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species

  UNC Libraries · 2025-03-22

  articleOpen accessSenior author

  Understanding community responses to climate is critical for anticipating the future impacts of global change. However, despite increased research efforts in this field, models that explicitly include important biological mechanisms are lacking. Quantifying the potential impacts of climate change on species is complicated by the fact that the effects of climate variation may manifest at several points in the biological process. To this end, we extend a dynamic mechanistic model that combines population dynamics, such as species interactions, with species redistribution by allowing climate to affect both processes. We examine their relative contributions in an application to the changing biomass of a community of eight species in the Gulf of Maine using over 30 years of fisheries data from the Northeast Fishery Science Center. Our model suggests that the mechanisms driving biomass trends vary across space, time, and species. Phase space plots demonstrate that failing to account for the dynamic nature of the environmental and biologic system can yield theoretical estimates of population abundances that are not observed in empirical data. The stock assessments used by fisheries managers to set fishing targets and allocate quotas often ignore environmental effects. At the same time, research examining the effects of climate change on fish has largely focused on redistribution. Frameworks that combine multiple biological reactions to climate change are particularly necessary for marine researchers. This work is just one approach to modeling the complexity of natural systems and highlights the need to incorporate multiple and possibly interacting biological processes in future models.

  PublisherDOI

• An energy-adjusted Mediterranean diet adherence screener for use in older adults with reduced energy requirements

  Proceedings of The Nutrition Society · 2025-04-01

  articleOpen access1st authorCorresponding

  In recent decades there has been an increased interest in the Mediterranean diet’s (MedDiet) protective capacity against age-related diseases. The MedDiet is comprised of wholefoods, with moderate to high dietary fat and a kilojoule intake of approximately 9,300kJ (1) . The Mediterranean Diet Adherence Screener (MEDAS) has allowed for rapid assessment of MedDiet adherence across intervention and cohort studies globally (2) . However, well-established reductions in older adults’ energy requirements often present a barrier to full MedDiet adherence (3,4) . We sought to create an energy-adjusted MEDAS (E-MEDAS) for use in populations with reduced energy requirements, with a secondary analysis to determine that the strength of the relationship between E-MEDAS adherence and cardiometabolic biomarkers is not diminished through energy-adjustment. Baseline data from independently living, 60–90 year old participants enrolled in the MedWalk clinical trial were used. Estimated energy requirements (EER) were calculated for all participants (n = 161) using gender and age specific Schofield Equations, multiplied by a physical activity level (PAL) we derived from a novel method to calculate PAL’s from Actigraph and IPAQ-E data. Three distinct energy categories of E-MEDAS criteria were identified, with evenly reduced cutoff criteria across all food components. Participants with a completed MEDAS (n = 157) had their MedDiet adherence re-scored according to the reduced criteria cutoffs. Spearman’s rank correlation coefficient analyses, with 95% confidence intervals constructed by accelerated bias-corrected bootstrapping, were used to determine the strength and direction of association between both MEDAS and E-MEDAS adherence scores and 8 cardiometabolic biomarkers. The newly calculated E-MEDAS categories included Category 3 (corresponding to the original MEDAS) with a range of 9100–10500kJ (n = 30), Category 2 with a range of 7700–9100kJ (n = 81) and Category 1 with a range of 6300–7700kJ (n = 44). There was a significant (p < 0.05) weak negative correlation between the re-scored E-MEDAS and 5 cardiometabolic biomarkers; BMI (rs = −0.228, BCa 95% CI [−0.388, −0.074]), WHR (rs = −0.189, BCa 95% CI [−0.352, −0.027]), LDL (rs = −0.174, BCa 95% CI [−0.347, 0.009]), Total:HDL Ratio (rs = −0.288, BCa 95% CI [−0.429, −0.127]), Trigs (rs = −0.235, BCa 95% CI [−0.373, −0.079]. In contrast, the original MEDAS score resulted in a significant (p < 0.05) weak negative correlation in only 3 cardiometabolic biomarkers; WHR (rs = −0.167, BCa 95% CI [−0.317, −0.011]), Total:HDL Ratio (rs = −0.205, BCa 95% CI [−0.354, −0.049], and Trigs (rs = −0.217, BCa 95% CI [−0.360, −0.054]). Ultimately, we have successfully developed two categories of E-MEDAS, using a novel calculation of PALs, for use in individuals with reduced EERs. E-MEDAS scores showed a modest increase in the strength of relationship with five cardiometabolic biomarkers, indicating that reducing serves of individual components, while maintaining the overall dietary pattern does not negate the protective capacity of a MedDiet.

  PublisherOA PDFDOI

• Understanding the continuous phenological development at daily time step with a Bayesian hierarchical space-time model: impacts of climate change and extreme weather events

  UNC Libraries · 2025-07-09

  articleOpen accessSenior author
  PublisherDOI

• Disturbance sensitivity shapes patterns of tree species distribution in Afrotropical lowland rainforests more than climate or soil

  Ecology and Evolution · 2024-05-01 · 1 citations

  articleOpen access

  Understanding how tropical forests respond to abiotic environmental changes is critical for preserving biodiversity, mitigating climate change, and maintaining ecosystem services in the coming century. To evaluate the relative roles of the abiotic environment and human disturbance on Central African tree community composition, we employ tree inventory data, remotely sensed climatic data, and soil nutrient data collected from 30 1-ha plots distributed across a large-scale observational experiment in forests that had been differently impacted by logging and hunting in northern Republic of Congo. We show that the composition of Afrotropical plant communities at this scale responds to human disturbance more than to climate, with particular sensitivities to hunting and distance to the nearest village (a proxy for other human activities, including tree-cutting and gathering). These findings contrast neotropical predictions, highlighting the unique ecological, evolutionary, and anthropogenic history of Afrotropical forests.

  PublisherOA PDFDOI

• Leveraging relationships between species abundances to improve predictions and inform conservation

  Journal of Applied Ecology · 2024-05-10 · 6 citations

  articleSenior author

  Abstract Many management and conservation contexts can benefit from understanding relationships between species abundances, which can be used to improve predictions of species occurrence and abundance. We present conditional prediction as a tool to capture information about species abundances via residual covariance between species. From a fitted joint species distribution model, this framework produces a species coefficient matrix that contains relationships between species abundances. The species coefficients allow co‐observed species to be treated as a second set of predictors supplementing covariates in the model to improve prediction. We use simulations to demonstrate the potential benefits and limitations of conditional prediction across data types and species covariance before applying conditional prediction to two management contexts with real data. Simulations demonstrate that conditional prediction provides the largest benefits to continuous data and when there is residual covariance between many species. In our first application, we show that conditioning on other species improves in‐sample and out‐of‐sample predictions of fish and invertebrate species, including Atlantic cod. In our second application, we show that the species coefficient matrix can be used to identify bird species at risk of nest parasitism by Brown‐headed Cowbirds. Synthesis and applications . We present guidelines for using conditional prediction, which can help understand relationships between species abundances, improve predictions and inform conservation in a variety of contexts.

  PublisherDOI

• Interspecific interactions influence bird population responses to global changes

  2024-02-07

  preprint
  PublisherDOI

• Remotely sensed crown nutrient concentrations modulate forest reproduction across the contiguous United States

  Zenodo (CERN European Organization for Nuclear Research) · 2024-05-22

  datasetOpen access

  Software for the paper published in Ecology. Global forests are increasingly lost to climate change, disturbance, and human management. Evaluating forests' capacities to regenerate and colonize new habitats has to start with the seed production of individual trees and how it depends on nutrient access. Studies on the linkage between reproduction and foliar nutrients are limited to a few locations and few species, due to the large investment needed for field measurements on both variables. We synthesized tree fecundity estimates from the Masting Inference and Forecasting (MASTIF) network with crown nutrient concentrations from hyperspectral remote sensing at the National Ecological Observatory Network (NEON) across the United States. We evaluated the relationships between seed production and foliar nutrients for 56,544 tree-years from 26 species at individual and community scales. We found a prevalent association between high foliar phosphorous (P) concentration and low individual seed production (ISP) at the continental scale. With-species coefficients to nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) are related to species differences in nutrient demand, with distinct biogeographic patterns. Community seed production (CSP) decreased four orders of magnitude from the lowest to the highest foliar P. This first study on hyperspectral imagery indicates promise for future monitoring of reproductive potential. The fact that both ISP and CSP decline at high foliar P levels has immediate applications in improving forest demographic and regeneration models by providing more realistic nutrient effects at multiple scales.

  PublisherDOI

Recent grants

• DISSERTATION RESEARCH: The role of seedling pathogens in temperate forest recuitment

  NSF · $12k · 2007–2010

• Belmont Forum Collaborative Research: Scenarios of Biodiversity and Ecosystem Service

  NSF · $180k · 2019–2022

• Collaborative Research: DDDAS-TMRP: Dynamic Sensor Networks - Enabling the Measurement, Modeling, and Prediction of Biophysical Change in a Landscape

  NSF · $1.3M · 2006–2012

• Experimental and Model Analysis of Large Disturbance Consequences for Forest Diversity

  NSF · $480k · 2000–2005

• Collaborative Research EAGER-NEON: Probabilistic Forecasting of Biodiversity Response to Intensifying Drought by Combining NEON, National Climate, Species, and Trait Data Bases

  NSF · $266k · 2015–2018

Frequent coauthors

• Anna F. Dominiczak

  100 shared

• Benoı̂t Courbaud

  Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

  91 shared

• Georges Künstler

  83 shared

• Niall Anderson

  University of Edinburgh

  78 shared

• Ghislain Vieilledent

  Institut de Recherche pour le Développement

  75 shared

• Baxter Jeffs

  52 shared

• Robert E. Goodin

  Australian National University

  49 shared

• Dwight Lee

  49 shared

Awards & honors

• William Skinner Cooper Award
• George Mercer Award
• ESA Aldo Leopold Leadership Fellow
• National Science Foundation’s Presidential Faculty Fellow Aw…
• Humboldt Research Prize