Advances in Forest Growth and Site Productivity Modeling

Dear Colleagues,

Forest growth is the keystone ecological process that determines forest structure and function. A forest site is characterized as an interaction of various environmental factors, and site productivity is a quantitative estimate of the potential of a site to produce woods and biomass. Modeling forest growth and site productivity has been an intrinsic part of forestry research for decades, as they contribute to the development of effective forest management plans. An increasing body of literature has shown that the influences of biotic and abiotic factors (climate, stand dynamics, natural disturbances, management practices, etc.) on forest growth and site productivity are substantial, and their action on forest growth is compounded nonlinearly, generating indirect and tipping-point processes. Climate change has already caused a remarkable change in growth, mortality, and site productivity, altering the range of species distributions. Growth and site productivity models developed with the integration of all the interacting factors, including climate, provide high prediction accuracy. Among potential data sources available for growth and site productivity modeling, LiDAR data can be the most accurate, and can be acquired with reasonable cost. Since LiDAR allows for 3D modeling of individual trees and stands, time-series matrices derived from LiDAR images can be used for growth and site productivity modeling, regardless of the forest types (monospecific or mixed-species; even-aged or uneven-aged). Advances in LiDAR systems alone or in combination with other sensors may be useful in reducing problems associated with the 3D characterization of mixed forests that are structurally more complex and have higher productivity and more stability against climate change than monospecific forests. Models developed with LiDAR data acquired from mixed forests will become more useful to manage these forests.

This Special Issue aims to compile original research articles focusing on the state-of-the-art studies on forest growth and site productivity responses to multiple interacting factors. Researchers may apply various modeling techniques, ranging from parametric to nonparametric techniques and from simpler to complex ones using LiDAR data alone or in combination with ground-based measurements. Critical reviews on the advancement of forest growth and site productivity modeling, and the validation of conventional growth models against independent data, are suitable for submission. Review articles covering overviews of state-of-the-art growth data acquisition techniques, data processing, forest growth models and their applications are also suitable. Studies based on the empirical- and process-based growth modeling using retrospective environmental and dendrometric databases, including data acquired from LiDAR, UAV, dendrochronology, etc., will be considered. The Issue will contribute to the advancement of knowledge on forest growth and yield, helping researchers globally to better understand the patterns of forest growth and site productivity conditions under the influence of various interacting factors. The Issue will improve our capacity to understand the complex growth and site productivity models, which will be largely supportive for developing silvicultural strategies and forest management plans under the climate change context.

Dr. Ram P. Sharma
Dr. Xiangdong Lei
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.