Abstract

Estimation of forest population dynamics is critical for forest management decisions making. In this study, we developed an innovative climate-sensitive matrix model using random forests (RF) algorithm to estimate tree diameter growth, tree mortality, and stand recruitment and consequently predict population dynamics of the central hardwood forests under four climate scenarios (i.e. Representative Concentration Pathway [RCP]2.6, 4.5, 6.0, and 8.5). Based on post-sample validation, this RF matrix (RFMatrix) model was more accurate than the traditional climate-sensitive matrix model and Landis pro 7.0. According to the importance values of all predicted variables, the variability in tree diameter growth, tree mortality, and stand recruitment was mainly explained by local tree and stand-level factors, followed by climatic and anthropogenic factors, and soil factors were the least important for all the species. Additionally, our model predictedthat climate change could substantially reduce total stand basal area. The RFMatrix model and its prediction results could assist future forest population dynamics studies on the central hardwood region under changing climate.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.