E. Louise Loudermilk

Research Ecologist
Fire Science Team
Center for Forest Disturbance Science
USDA Forest Service
elloudermilk@fs.fed.us
SRS Staff Directory Profile

SRS Publications List

Education

Ph.D. Interdisciplinary Ecology May 2010 University of Florida
M.S. Forestry December 2005 University of Florida

Interests and Specializations

Forest ecology, fire science and ecology, ecosystem ecology, landscape ecology, global climate change, forest and fire management, biological and ecosystem modeling, GIS, remote sensing, LIDAR, Infrared imagery, spatial and multivariate statistics, scaling analysis, scientific computing and programming.

Research

Fire Ecology & Modeling at Eglin Air Force Base, FL

In this research three scales of processes linking fire-fuel-fire effects are modeled from coarse to fine scales in a xeric longleaf pine forest. LIDAR is used to determine landscape overstory structure. This data are used to generate the second scale of the model: a fine scale map of fuels generated from a function of canopy inputs (litter, cones, woody fuels) linked to the forest structure. Fire simulations are run using the fuels maps as inputs and the predicted patterns in fire behavior that inform the processes that define the finest scale layer generated by simulations of plant community dynamics driven by fire effects. Field data inputs to develop this modeling framework include intense, spatially explicit surface fuel and plant species monitoring in varying canopy openness, as well as fire behavior measurements from time-elapsed thermal imagery. This research will aid in guiding management and restoration practices that may alter the spatial structure and abundance of the overstory that maintains understory plant diversity.

Landscape Modeling (LANDIS-II) of the Lake Tahoe Basin, CA, NV

We are evaluating the effects of fire suppression, prescribed fire, wildfire, and fuel treatments on the long-term potential for Lake Tahoe forests and soils to sequester carbon in a climate change context, while assessing their tradeoffs when managing for carbon sequestration using a multiple fuel treatment scenario design. Using a broad-scale modeling approach (i.e., LANDSI-II), I examine the physiological responses of trees and shrubs to the coupled effects of changes in soil moisture, light conditions, seasonal temperature fluctuations, and nitrogen and carbon cycling. The interactive effects from climate (changes in forest productivity, wildfires, thinning activities) produce complex spatial and temporal patterns of carbon flux and allocation across the landscape. I am a Co-PI on a grant to extend this project to implement mortality from drought and bark beetle infestations to the current modeling framework.

Longleaf Pine Modeling in southeastern U.S.

A spatially explicit simulation model was developed to represent inter- and intra- species plant competition in association with forest fire dynamics in the fire-maintained longleaf pine (Pinus palustris) ecosystem of the southeastern U.S. The model is used to assess long-term forest dynamics including plant competition, gap analysis, site-specificity, and changing fire regime. The model is currently being extended to include aboveground carbon estimates and forest response from various silvicultural methods (e.g., single tree selection, uneven aged management). Further work includes incorporating plot to stand level fire effects (e.g., plant mortality, fuel consumption).

LIDAR research

In collaboration with the Geosensing Engineering and Mapping Center at UF, we developed techniques to characterize the understory vegetative fuelbed with ground-LIDAR (Light Detection and Ranging) and analyze overstory tree structure and distribution using aerial-LIDAR. Fine-scale (sub-meter) vegetation characteristics (e.g., volume) were estimated using the ground-LIDAR data and compared with leaf area and biomass measurements. This resulted in a more precise and novel approach for volume estimation compared to traditional methods. Furthermore, the heterogeneous fuelbed (also gained from ground-LIDAR and in situ data) was used to predict fine-scale fire behavior (measured with FLIR instrumentation) attributes using regression-tree statistics. Aerial-LIDAR was used to evaluate the longleaf model (above) for two different research sites.

Publications

Peer-Reviewed

  • Loudermilk, E.L., Scheller, R.M., Weisberg, P.J., Yang, J., Dilts, T., Karam, S., Skinner, C. 2013. Carbon Dynamics in the Future Forest: The Importance of Long-Term Successional Legacy and Climate-Fire Interactions. Global Change Biology. 9: 3502-3515.
  • Loudermilk, E.L., O’Brien, J.J., Mitchell, R.J., Cropper Jr., W.P., Hiers, J.K., Grunwald, S., Grego, J., Fernandez, J.C. 2012. Linking complex forest fuel structure and fire behavior at fine-scales. International Journal of Wildland Fire. 21: 882-893.
  • Loudermilk, E.L., Cropper Jr., W.P., Mitchell, R.J., Lee, H. 2011. Longleaf pine (Pinus palustris) and hardwood interactions in a fire-maintained ecosystem: a simulation approach. Ecological Modelling. 222: 2733-2750.
  • Loudermilk, E.L., Hiers, J.K., O’Brien, J.J., Mitchell, R.J., Singhania, A., Fernandez, J.C., Cropper Jr., W.P., Slatton, K.C. 2009. Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics. International Journal of Wildland Fire. 18: 676-685.
  • Hiers, J.K., O’Brien, J.J., Mitchell, R.J. Grego, J.M., and Loudermilk, E.L. 2009. The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests. International Journal of Wildland Fire. 18: 315-325.
  • Loudermilk, E.L., Cropper, Jr., W.P. 2007. Multiscale modeling of longleaf pine (Pinus palustris). Canadian Journal of Forest Research. 37: 2080-2089.
  • Cropper, Jr., W.P., Loudermilk, E.L. 2006. The interaction of seedling density dependence and fire in a matrix population model of longleaf pine (Pinus palustris). Ecological Modeling. 198: 487-494.

Non-Peer-Reviewed

  • Loudermilk E.L., Stanton A.E., Scheller R.M., Weisberg P.J., Yang J., Dilts T.E., Skinner C. 2012. Final Report: Management Options for Reducing Wildfire Risk and Maximizing Carbon Storage under Future Climate Changes, Ignition Patterns, and Forest Treatments In: Southern Nevada Public Lands Management Act. pp 100, Pacific Southwest Research Station, Tahoe Center for Environmental Studies, Incline Village, NV.
  • Scheller, R.M., Luchash, M.S., Loudermilk, E.L. 2012. LANDIS-II Century Succession v3.0 Extension User Guide. Portland State University, Portland, OR.
  • Loudermilk, E.L., Singhania, A., Fernandez, J., Hiers, J.K., O’ Brien, J.J., Cropper Jr., W.P., Slatton, K.C. Application of ground-based LIDAR for fine-scale forest fuel modeling. In: Butler, B.W., Cook, W., comps. 2007. The Fire Environment – Innovations, Management, and Policy, (National) conference proceedings, 26-30 March 2007, Destin, FL. Proceedings RMRS-P-46. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.
  • Rasser, M.K., Loudermilk, E.L. 2003. Monitoring and decision support for Florida’s Watermelon Pond. Final Report, Florida Division of Forestry and School of Forest Resources and Conservation, UF.

Center for Forest Disturbance Science (SRS RWU 4156)

University of Georgia
Forestry Sciences Laboratory
320 Green Street
Athens, GA 30602

Clemson University
233 Lehotsky Hall
Clemson, SC 29634