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Development and evaluation of an individual tree growth and yield model for the mixed species forest of the Adirondacks Region of New York, USA.

Authors :
Weiskittel, Aaron
Kuehne, Christian
McTague, John
Oppenheimer, Mike
Source :
Forest Ecosystems (Springer Nature); 11/26/2016, Vol. 3 Issue 1, p1-17, 17p
Publication Year :
2016

Abstract

Background: Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and complex. However, only a relatively limited number of growth and yield models have been developed and/or can be reasonably extended to this region currently. Methods: In this analysis, 571 long-term continuous forest inventory plots with a total of 10 - 52 years of measurement data from four experimental forests maintained by the State University of New York College of Environmental Science and Forestry and one nonindustrial private forest were used to develop an individual tree growth model for the primary hardwood and softwood species in the region. Species-specific annualized static and dynamic equations were developed using the available data and the system was evaluated for long-term behavior. Results: Equivalence tests indicated that the Northeast Variant of the Forest Vegetation Simulator (FVS-NE) was biased in its estimation of tree total and bole height, diameter and height increment, and mortality for most species examined. In contrast, the developed static and annualized dynamic, species-specific equations performed quite well given the underlying variability in the data. Long-term model projections were consistent with the data and suggest a relatively robust system for prediction. Conclusions: Overall, the developed growth model showed reasonable behavior and is a significant improvement over existing models for the region. The model also highlighted the complexities of forest dynamics in the region and should help improve forest planning efforts there. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20956355
Volume :
3
Issue :
1
Database :
Complementary Index
Journal :
Forest Ecosystems (Springer Nature)
Publication Type :
Academic Journal
Accession number :
119755358
Full Text :
https://doi.org/10.1186/s40663-016-0086-3