Development of a linear mixed-effects individual-tree basal area increment model for masson pine in Hunan Province, South-central China

Zeng

et al. 2020

Self Cite

Crown ratio (CR) and height to crown base (HCB) are important crown characteristics influencing the behavior of forest canopy fires. However, the labor-intensive and costly measurement of CR and HCB have hindered their wide application to forest fire management. Here, we use 301 sample trees collected in 11 provinces in China to produce predictive models of CR and HCB for Masson pine forests (Pinus massoniana Lamb.), which are vulnerable to forest canopy fires. We first identified the best basic model that used only diameter at breast height (DBH) and height (H) as independent variables to predict CR and HCB, respectively, from 11 of the most used potential candidate models. Second, we introduced other covariates into the best basic model of CR and HCB and developed the final CR and HCB predictive models after evaluating the model performance of different combinations of covariates. The results showed that the Richards form of the candidate models performed best in predicting CR and HCB. The final CR model included DBH, H, DBH0.5 and height-to-diameter ratio (HDR), while the final HCB model was the best basic model (i.e., it did not contain any other covariates). We hope that our CR and HCB predictive models contribute to the forest crown fire management of Masson pine forests.

Section: Parameter Estimation and Evaluationmentioning

confidence: 99%

Development of Crown Ratio and Height to Crown Base Models for Masson Pine in Southern China

Zeng

et al. 2020

Self Cite

“…Masson pine (Pinus massoniana Lamb. ), an evergreen pioneer tree species [1,2], is one of the most widely distributed native tree species throughout Southern China [3]. According to the 8th Chinese National Forest Inventory (NFI), China's existing Masson pine forests cover 10.1 million ha, which corresponds to 6% of the total area in China.…”

Section: Introductionmentioning

confidence: 99%

“…Masson pine, distributed across 17 provinces in China, exerts dominance over regional forests and assumes a vital role in upholding the structure and functionality of forest ecosystems within the entire subtropical zone [4]. Due to this, Masson pine is commonly used in ecological restoration projects in poor site conditions [1]. It is also an important industrial raw material wood with extensive commercial usage.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the growth models of Masson pine in Southern China generally focus on the individual tree approach [39]. For example, Wang, Bai, Jiang, Yang, and Meng [1] produced an individual-tree basal area increment model for Masson pine in Hunan Province using a linear mixed-effects approach. Fu et al [40] employed a mixedeffects modeling approach to develop individual-tree biomass models for Masson pine for nine provinces in Southern China.…”

Section: Introductionmentioning

confidence: 99%

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A Climate-Sensitive Transition Matrix Growth Model for Masson Pine (Pinus massoniana Lamb.) Natural Forests in Hunan Province, South-Central China

Meng

2023

Self Cite

Masson pine natural forests are ecologically and economically valuable forest ecosystems extensively distributed across China. However, they have been subject to deforestation due to human disturbance. Moreover, climate change affects the growth, mortality, and recruitment of forests, yet available forest growth models do not effectively analyze the impacts of climate. A climate-sensitive transition matrix model (CM) was developed using data from 330 sample plots collected during the 7th (2004), 8th (2009), and 9th (2014) Chinese National Forest Inventories in Hunan Province. To assess model robustness, two additional models were created using the same data: a non-climate-sensitive transition matrix model (NCM) and a fixed probability transition matrix model (FM). The models were compared using tenfold cross-validation and long-term predictive performance analysis. The cross-validation results did not show any significant differences among the three models, with the FM performing slightly better than the NCM. However, the application of the CM for long-term prediction (over a span of 100 years) under three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) revealed distinct dynamics that demonstrated enhanced reliability. This is attributed to the consideration of climate variables that impact forest dynamics during long-term prediction periods. The CM model offers valuable guidance for the management of Masson pine natural forests within the context of changing climatic conditions.

Development of a Climate-Sensitive Matrix Growth Model for Larix gmelinii Mixed-Species Natural Forests and Its Application for Predicting Forest Dynamics under Different Climate Scenarios

Zhang

et al. 2022

Larix gmelinii natural forests, which are of great ecological and economic importance, are mainly distributed in northeast China. Sustainable management of these forests play a vital role in ecological security in northeast China, especially in the context of climate change. Forest growth models, which support forest management decision-making, are lacking for Larix gmelinii natural forests, hampering the prescription of forest management strategies. In this study, we produced a climate-sensitive, transition-matrix model (CM) for Larix gmelinii natural forests. For comparison, a variable transition model without including climate change effects (NCM) and a fixed-parameter model (FM) were also built. We examined the performance of the CM, NCM, and FM by conducting short- (5 years) and long-term (100 years) simulations. The results showed that for short-term prediction, no significant difference was observed among the three predictive models. However, the long-term prediction ability of the CM under the three different RCPs was superior to that of the FM and NCM. The number of trees and basal area were predicted to increase under climate change, which might result in natural disasters, such as snow break, windthrow, and forest fire. Silvicultural practices, such as reducing the intermediate thinning interval and the enrichment planting of slow-growing trees, should be implemented to mitigate the deleterious effects of climate change.