Using Long-Term Regeneration Data From Multiple Studies to Model Regeneration Outcomes in Southern Appalachian Hardwoods
Event Website
http://www.nafew2009.org/
Start Date
6-25-2009 8:40 AM
End Date
6-25-2009 9:00 AM
Description
The portfolio of research associated with a designated forest research field facility typically consists of both case studies and studies with replicated field designs. This is particularly true on research sites whose establishment predates the widespread use of experimental statistics. Even with the development of statistical methodology, case studies with pre-treatment data collection and post-treatment evaluation of outcomes have continued to be installed for a variety of reasons. Both sources of data, case and replicated studies, can be valuable sources of inference. In this paper, we utilize data from numerous case and replicated studies of natural regeneration treatments applied to southern Appalachian hardwood stands to develop a working hypothesis that is consistent with contemporary concepts of succession and provides the basis for a model to predict species composition following regeneration harvests. The studies used in this effort were located on the Bent Creek Experimental Forest, or on nearby national forests, and have strongly influenced the silvicultural practices employed by managers in the southern Appalachians. The development of a prediction model based on these studies in these relatively complex forests provides an essential tool for managers, further enhancing the value of these long-term data. A modeling framework is suggested, along with one approach to validating and updating the model.
Using Long-Term Regeneration Data From Multiple Studies to Model Regeneration Outcomes in Southern Appalachian Hardwoods
The portfolio of research associated with a designated forest research field facility typically consists of both case studies and studies with replicated field designs. This is particularly true on research sites whose establishment predates the widespread use of experimental statistics. Even with the development of statistical methodology, case studies with pre-treatment data collection and post-treatment evaluation of outcomes have continued to be installed for a variety of reasons. Both sources of data, case and replicated studies, can be valuable sources of inference. In this paper, we utilize data from numerous case and replicated studies of natural regeneration treatments applied to southern Appalachian hardwood stands to develop a working hypothesis that is consistent with contemporary concepts of succession and provides the basis for a model to predict species composition following regeneration harvests. The studies used in this effort were located on the Bent Creek Experimental Forest, or on nearby national forests, and have strongly influenced the silvicultural practices employed by managers in the southern Appalachians. The development of a prediction model based on these studies in these relatively complex forests provides an essential tool for managers, further enhancing the value of these long-term data. A modeling framework is suggested, along with one approach to validating and updating the model.
https://digitalcommons.usu.edu/nafecology/sessions/longterm/7