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Utility of tree crown condition indicators to predict tree survival using remeasured Forest Inventory and Analysis dataAuthor(s): Randall S. Morin; Jim Steinman; KaDonna C. Randolph
Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 210-215.
Publication Series: Paper (invited, offered, keynote)
Station: Northern Research Station
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DescriptionThe condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during surveys of Forest Inventory and Analysis (FIA) Phase 3 (P3) plots since 1999. In this study, remeasured data from 39,357 trees in the northern United States were used to assess the probability of survival among various tree species using the suite of crown condition variables. Logistic regression procedures were employed to assess the importance of individual crown condition variables alone and in combination for predicting tree survival. Results of the regression analyses indicated that crown dieback was the most important crown condition variable for predicting tree survival for all species combined and for the 10 individual species in the study. Additionally, one-way analysis of variance (ANOVA) results identified differences among the ability of different tree species to survive varying levels of crown dieback. The results provide statistical evidence for selecting crown dieback as one of the crown condition variables to be collected on a subset of Phase 2 plots (P2+) starting in 2012.
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CitationMorin, Randall S.; Steinman, Jim; Randolph, KaDonna C. 2012. Utility of tree crown condition indicators to predict tree survival using remeasured Forest Inventory and Analysis data. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 210-215.
Keywordsstatistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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