Longleaf pine (pinus palustris mill.) forest is a valued but endangered ecosystem in the USA

The Department of Agriculture National Institute of Food and Agriculture awarded Alabama A & M University $299,529 under the 1890 Institution Capacity Building Grants program (CFDA 10.216) on December 15, 2025.

The award funds research quantifying relationships between longleaf pine cone production, tree structure and phenology, and ecological factors including air temperature, soil water, and nutrient availability. The project will employ hyperspectral imaging, tree radar, and lidar to characterize individual tree structure and phenology across multiple field monitoring locations, establish correlations between these processes and cone production, identify weather and ecological determinants of cone production and tree growth, develop quantitative methods to analyze yearly dynamics of cone production and tree growth in longleaf pine, and train graduate and undergraduate students in advanced technology for forest ecological research. Work is performed in Normal, Huntsville, Alabama, with a period of performance through December 14, 2028. The project strengthens the connection between Alabama A & M University's forestry program and the USDA Forest Service for forest and ecological science research.

One of the critical issues is its sporadic seed production which challenges forest restoration. Our previous studies indicated the complicated relationship between cone production and its ecosystem. For example, on a decade scale the coefficients of variance (CVS) of cone production were positively correlated with the CVS of annual air temperature but negatively correlated with the CVS of annual precipitation. IT needs to clarify how cone production relates to tree morphological and phenological conditions and ecological fluctuations. This research will quantify this relationship using systematic field monitoring data from multiple sensors. The objectives include (i) characterizing tree structure and phonology for individual trees by the hyperspectral imaging, tree radar, and lidar at variouslocations; (II) comparing tree structure, phenology, and cone production and establishing possible relationships between these processes; (III) identifying the likely weather and ecological factors (e.g. air temperature, soil water, and nutrients) which may determine cone production, tree growth and phenological activities; (IV) generating a quantitative approach which can analyze the yearly dynamics of cone production and tree growth in longleaf pine trees; and (v) training the graduate and undergraduate students to use advanced technology for basic forest ecological research. This proposed research project will provide management implications and involve training students. IT will strengthen the link between the forestry program at aamu (1890 institution) and the USDA forest service for quality research in forest and ecological sciences.