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Can FIA soils data improve models predicting ponderosa pine density in the Southwest?

Status: 
Start-up
Dates: 
September, 2017 to December, 2018

Puhlick et al.(2012) evaluated the influence of numerous abiotic and biotic factors on ponderosa pine regeneration densities in the southwestern United States. Their regional model of ponderosa pine density was developed using USDA Forest Inventory and Analysis (FIA) data from Arizona and New Mexico. At the time, detailed soils data were not available for FIA plots in the region. The FIA group has now released soils data associated with field samples collected on a subset of these plots from 2001-2016. The current study will use this data to test the influence of soils and other variables (such as presence of seed trees) on ponderosa pine seedling densities. This will require the development and testing of new structural equation models, which can elucidate the direct and indirect factors within a system that influence tree regeneration dynamics.

Conceptual model illustrating the directional relationships among general factors and tree regeneration. Arrows indicate the hypothesized causal relationships. (Puhlick et al. 2012)
Conceptual model illustrating the directional relationships among general factors and tree regeneration. Arrows indicate the hypothesized causal relationships. (Puhlick et al. 2012)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

This project is of interest to local and regional silviculturists, burned area response teams charged with post-wildfire rehabilitation, and scientists interested in ponderosa pine regeneration dynamics. By understanding factors that are associated with successful ponderosa pine regeneration, silviculturists and ecologists can enhance pine seedling survival by choosing planting locations that are more likely to support future pine forests.

Approach

The methodology framework is detailed in Puhlick et al. (2012).  The researchers will develop a detailed study plan by September 30, 2017 and then work with FIA to acquire and interpret FIA plot data (September-October 2017), develop initial structural equations and preliminary analyses for a poster presentation at a scientific meeting in November 2017, refine analyses and write a draft manuscript and annual report by December 2017, and revise the manuscript for review by the team by March 2018.  The goal is to submit the manuscript to a scientific journal by June 2018 and prepare the final report by December 2018.



Project Contact: 

Principal Investigators:
Joshua Puhlick - University of Maine

Co-Investigators:
Daniel Laughlin - University of Wyoming
Margaret Moore - Northern Arizona University

Collaborators: