James Grace, Ph.D.
Senior Research Scientist
Biography
EDUCATION
Ph.D., Michigan State University
M.S., Clemson University
B.S., Biology, Presbyterian College
BACKGROUND
2015 - present Senior Research Scientist. U.S. Geological Survey, ST
2002 - 2014 Senior Research Ecologist, U.S. Geological Survey, GS-15
1993 - 2019 Adjunct Professor, Department of Biology, University of Louisiana
2002 – 2005 Affiliate Faculty, School of Renewable Natural Resources, LSU
1992 - 2002 Research Ecologist, U.S. Geological Survey, Biological Division
1990 - 1993 Professor, Department of Botany, Louisiana State University
1985 - 1990 Associate Professor, Department of Botany, Louisiana State Univ.
1989 Visiting Professor, Louisiana Universities Marine Consortium
1986 Visiting Scientist, Div. Wildlife, CSIRO, Darwin, Australia
1980‑1985 Assistant Professor, Dept. Botany and Microbiology, Univ. Arkansas summer
After graduate school, he held faculty positions at the University of Arkansas and Louisiana State University, where he reached the level of Full Professor. In 2000, he received the millennium Meritorious Research Award from the Society of Wetland Scientists and in 2003 received the National Science Excellence Award from the U.S. Geological Survey. He was selected to be a Fellow of the Ecological Society of America and promoted to the Senior Scientist ranks in 2014. Since 2019 he has been designated as a ‘Highly-Cited Researcher’ by the Web of Science in recognition of his scientific impact during the past decade. He has published over 200 papers and reports, including 3 books, one on competitive interactions, one on community analysis, and one on structural equation modeling. As of 2020, Grace has given over 200 invited lectures and workshops in 9 countries during his career.
For more information, search 'Jim Grace USGS'.
Science and Products
The Response of Coastal Wetlands to Sea-level Rise: Understanding how Macroscale Drivers Influence Local Processes and Feedbacks
The purpose of this work is to advance our understanding of how coastal wetland responses to sea-level rise (SLR) within the conterminous United States are likely to vary as a function of local, regional, and macroscale drivers, including climate. Based on our interactions with managers and decision makers, as well as our knowledge of the current state of the science, we propose to: (a)...
The response of coastal wetlands to sea-level rise: Understanding how macroscale drivers influence local processes and feedbacks
The purpose of this work is to advance our understanding of how coastal wetland responses to SLR within the conterminous United States are likely to vary as a function of local, regional, and macroscale drivers, including climate. Based on our interactions with managers and decision makers, as well as our knowledge of the current state of the science, we propose to (a) conduct a national...
Development of a Multimetric Index for Integrated Assessment of Salt Marsh Condition in the Northeast Coastal and Barrier Network
Salt marsh ecosystems along all US coastlines have been altered, degraded, and destroyed by human activities, including ditching and drainage of the marsh platform, tidal restrictions, discharge of pollutants, and introduction of invasive species. The National Park Service conducts long-term monitoring of salt marsh vegetation and nekton (fish and free-swimming crustaceans) to provide...
Quantitative Analysis Using Structural Equation Modeling
USGS scientists have been involved for a number of years in the development and use of Structural Equation Modeling (SEM). This methodology represents an approach to statistical modeling that focuses on the study of complex cause-effect hypotheses about the mechanisms operating in systems. SEM is increasingly used in ecological and environmental studies and this site seeks to provide...
Improving Our Ability to Forecast Tidal Marsh Response to Sea Level Rise
Our overall objective is to understand what controls the vulnerability of coastal marshes to risks associated with global change drivers and rising sea levels. Fundamental questions pertaining to coastal wetland vulnerability still need to be addressed. What factors explain spatial and geographic variation in tidal wetland vulnerability? How do short term climatic events (storms) influence the...
Structural Equation Modeling in Support of Conservation
Understanding systems sometimes requires approaches that allow for both the discovery of the a system's structure and the estimation of its implications. Structural Equation Modeling - SEM - is one tool scientists use to better understand the complex world in which we live.
Mechanisms of Coastal Marsh Elevation Regulation
Sediment deposition serves an important role in the long-term maintenance of coastal marshes. USGS investigates the mechanisms of coastal marsh elevation regulation to help predict marsh sediment requirements under various sea level rise scenarios.
A protocol for modelling generalised biological responses using latent variables in structural equation models
In this paper we consider the problem of how to quantitatively characterize the degree to which a study object exhibits a generalized response. By generalized response, we mean a multivariate response where numerous individual properties change in concerted fashion due to some internal integration. In latent variable structural equation modeling (...
Akomolafe, Gbenga; Grace, James; Steiner, Magdalena Instrumental variable methods in structural equation models
Instrumental variable regression (RegIV) provides a means for detecting and correcting parameter bias in causal models. Widely used in economics, recently several papers have highlighted its potential utility for ecological applications. Little attention has thus far been paid to the fact that IV methods can also be implemented within structural...
Morrissey, Michael; Grace, James Biodiversity effects on grape quality depend on variety and management intensity
Interactions between plants can be beneficial, detrimental or neutral. In agricultural systems, competition between crop and spontaneous vegetation is a major concern. We evaluated the relative support for three non-exclusive ecological hypotheses about interactions between crop and spontaneous plants based on competition, complementarity or...
Steiner, Magdalena; Grace, James; Bacher, Sven A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: comment
In a recent paper, Schoolmaster, Zirbel, and Cronin (SZC) (2020) claim “Formal causal analysis show[s] that biodiversity–ecosystem function (BEF) correlations are non-causal associations.” If this conclusion is accepted as true, it suggests a reconsideration of much of our current understanding of how biodiversity relates to the functioning of...
Inouye, Brian D.; Grace, James B.; Loreau, Michel; Schmid, Bernhard Hurricane Sandy effects on coastal marsh elevation change
High-magnitude storm events such as Hurricane Sandy are powerful agents of geomorphic change in coastal marshes, potentially altering their surface elevation trajectories. But how do a storm’s impacts vary across a large region spanning a variety of wetland settings and storm exposures and intensities. We determined the short-term impacts of...
Yeates, Alice G.; Grace, James; Olker, Jennifer H.; Guntenspergen, Glenn R.; Cahoon, Donald; Adamowicz, Susan C.; Anisfeld, Shimon C.; Barrett, Nels; Benzecry, Alice; Blum, Linda K.; Christian, Rober T; Grzyb, Joseph; Kracauer Hartig, Ellen; Hines Leo, Kelly; Lerberg, Scott; Lynch, James C.; Maher, Nicole; Megonigal, J Patrick; Reay, William G.; Siok, Drexel; Starke, Adam; Turner, Vincent; Warren, Scott Climate and local environment structure asynchrony and the stability of primary production in grasslands
Aim Climate variability threatens to destabilize production in many ecosystems. Asynchronous species dynamics may buffer against such variability when a decrease in performance by some species is offset by an increase in performance of others. However, high climatic variability can eliminate species through stochastic extinctions or cause similar...
Gilbert, B.; MacDougall, A.S.; Kadoya, T.; Akasaka, M.; Bennett, J. R.; Lind, E.M.; Flores-Moreno, H.; Firn, J.; Hautier, Y.; Borer, E.T.; Seabloom, E.W.; Adler, P.B.; Cleland, E.E.; Grace, James; Harpole, W.S.; Esch, E.H.; Moore, J.L.; Knops, J.; McCulley, R.; Mortensen, B.; Bakker, J.; Fay, P.A. A 'weight of evidence' approach to evaluating structural equation models
It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM). The reason for this is because selecting one model for interpretive use from amongst many possible models is both essential and difficult. The published protocols and advice for model...
Grace, James Structural equation modeling
This chapter introduces background and historical information on how structural equation modeling (SEM) came to be developed. Then, the main differences between SEM and earlier multivariate methods are explained. The chapter describes three main applications of SEM: path analysis, factor analysis, and hybrid models. Some computer programs are...
Miller, Matt; Tasic, Ivana; Lyons, Torrey; Ewing, Reid; Grace, James B. Conceptual frameworks
The chapter starts by addressing some of the issues that come from not using a conceptual framework. This point is illustrated using an example with causal factors. The chapter then goes on to explain the mechanics of establishing conceptual frameworks. Lastly, it lays out a step-by-step guide on how to create a framework—generating a set of...
Park, Keunhyun; Grace, James B.; Ewing, Reid Scientist’s guide to developing explanatory statistical models using causal analysis principles
Recent discussions of model selection and multimodel inference highlight a general challenge for researchers, which is how to clearly convey the explanatory content of a hypothesized model or set of competing models. The advice from statisticians for scientists employing multimodel inference is to develop a well‐thought‐out set of candidate models...
Grace, James B.; Irvine, Kathryn The importance of natural versus human factors for ecological conditions of streams and rivers
Streams are influenced by watershed-scale factors, such as climate, geology, topography, hydrology, and soils, which mostly vary naturally among sites, as well as human factors, agriculture and urban development. Thus, natural factors could complicate assessment of human disturbance. In the present study, we use structural equation modeling and...
Tang, Tao; Stevenson, R. Jan; Grace, James Climatic controls on the distribution of foundation plant species in coastal wetlands of the conterminous United States: Knowledge gaps and emerging research needs
Foundation plant species play a critical role in coastal wetlands, often modifying abiotic conditions that are too stressful for most organisms and providing the primary habitat features that support entire ecological communities. Here, we consider the influence of climatic drivers on the distribution of foundation plant species within coastal...
Osland, Michael; Grace, James; Guntenspergen, Glenn; Thorne, Karen; Carr, Joel; Feher, Laura
Biodiversity Critical to Maintaining Healthy Ecosystems
Researchers have found clear evidence that biological communities rich in species are substantially healthier and more productive than those depleted of species.