Our research focuses on modeling the biotic, abiotic and management conditions that lead to the regeneration of mixed-oak forests, and on modeling forests to aid management of resilient forests.

We are developing species-specific models of advance regeneration using an extensive field dataset and ensemble classification trees. In addition, we are modeling species composition at the stem exclusion stage after an overstory removal treatment in mixed-oak forests. We aim at understanding which biotic, abiotic, and management characteristics lead to the regeneration of a mixed-oak forest and under which scenarios a changed forest species composition arises.

Related publications

Curtze, A., A. Muth, J. Larkin, and L. Leites. 2022. Decision support tools to inform the rehabilitation and management of high graded forests. Journal of Forestry. https://doi.org/10.1093/jofore/fvab077

Rittenhouse, J. and L. Leites. 2022. Modeling advance oak regeneration at landscape scale: the relative importance of abiotic and biotic factors. Forest Science https://doi.org/10.1093/forsci/fxac009

Rittenhouse, J., L. Leites, K. Derham, S. Miller. 2018. Insights on the use of decision support tools to sustain forest ecosystems from a case study in Pennsylvania, USA. Journal of Forestry. 116(4):391-395.