Decision support tools to improve the effectiveness of hazardous fuel reduction treatments in the New Jersey Pine Barrens
Kenneth L. Clark A D , Nicholas Skowronski A , John Hom A , Matthew Duveneck B , Yude Pan A , Stephen Van Tuyl A , Jason Cole A , Matthew Patterson A and Stephen Maurer CA Silas Little Experimental Forest and Northern Global Change Program, USDA Forest Service, Newtown Square, PA 19073, USA.
B Fire Science Department, Southern Maine Community College, Portland, ME 04106, USA.
C New Jersey Forest Fire Service, 501 State St., Trenton, NJ 08625, USA.
D Corresponding author. Email: kennethclark@fs.fed.us
International Journal of Wildland Fire 18(3) 268-277 https://doi.org/10.1071/WF08080
Submitted: 29 May 2007 Accepted: 16 May 2008 Published: 28 May 2009
Abstract
Our goal is to assist the New Jersey Forest Fire Service and federal wildland fire managers in the New Jersey Pine Barrens evaluate where and when to conduct hazardous fuel reduction treatments. We used remotely sensed LIDAR (Light Detection and Ranging System) data and field sampling to estimate fuel loads and consumption during prescribed fire treatments. This information was integrated with data on prescribed fire treatments conducted by the New Jersey Forest Fire Service over the last 15 years to produce and interpret maps of current fuel loads. Forest productivity measurements and models were then used to estimate rates of fuel accumulation through time. We could then calculate return intervals for desired fuel load conditions. Through formal workshops and frequent discussions with state and federal fire managers, our results enhance the ability of these agencies to make key decisions regarding the effectiveness and longevity of hazardous fuels treatments.
Additional keywords: forest productivity, fuel accumulation, fuel load estimates, LIDAR, prescribed fire treatments.
Acknowledgements
The present research is funded by the National Fire Plan and the Eastern LANDFIRE Prototype. We thank the NJFFS for making this research possible, and Robert Somes for digitizing prescribed fire history data.
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