SBIR/STTR Research Award

Development of statistical models required to implement a longleaf pine decision support system

Award identifier 98c7494fb8464c704d8589b09446677e9a87bcc275858d26febc80404d8bce75Awarding agency Department of Agriculture

Award amount

$60,770

Program and phase

SBIR · Phase I

Award year

2015

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Award details

Awarding agency
Department of Agriculture
Branch
Not reported
Recipient company
Silvics Analytic
Proposal award date
2015-05-20
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
8.1

Research abstract

Expansion and restoration of the longleaf pine timber type is highly dependent on outreach to non-industrial private forests and landowners. Over 60% of longleaf or longleaf-oak timber types are in non-industrial private ownership. Private consultants and state foresters provide much of the technical advice and services to private landowners within the longleaf pine range. Longleaf pine ecosystems are resilient to climate change, sequester carbon, and management practices (early thinning) can provide biomass as an alternative energy source but management is more complex than for other southern pine species. The complexities of longleaf regeneration, inability to fully understand future production of diverse products over long rotations, uncertainty of longer investment periods for higher-valued wood products, and lower short-term wood volume productivity are major limitations to establishment and maintenance of the longleaf pine type. A decision support system that improves the ability of professional foresters, managers, and landowners to accurately characterize long-term expectations from longleaf pine with respect to their interests and with respect to the potential to realize and utilize a more diverse output of products would help overcome some of these limitations.Currently, a major limitation to implementation of a longleaf pine decision support system is the availability of size-class models for long rotations (up to 120 years) that allow construction and projection of stand tables, thinning, and merchandizing of products. The technical hurdle addressed here, in Phase I, is the development and testing of stand table projection techniques similar to those that have been developed for other pine species. An important aspect of this approach is that it uses over 40 years of existing USDA Forest Service research study data to develop models that facilitate the application of this information to applied management decisions by public interests.

Technology keywords

Not reported

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Agency intelligence

Department of Agriculture

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