Quantifying the Effect of Crown Vertical Position on Individual Tree Competition: Total Overlap Index and Its Application in Sustainable Forest Management

Boheng Wang, Yuankun Bu, Guanhu Tao, Chenran Yan, Xiaolu Zhou, Weizhong Li, Pengxiang Zhao, Yanzheng Yang and Ruikun Gou
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Boheng Wang: College of Forestry, Northwest A&F University, Yangling 712100, China
Yuankun Bu: College of Forestry, Northwest A&F University, Yangling 712100, China
Guanhu Tao: College of Forestry, Northwest A&F University, Yangling 712100, China
Chenran Yan: College of Forestry, Northwest A&F University, Yangling 712100, China
Xiaolu Zhou: College of Forestry, Northwest A&F University, Yangling 712100, China
Weizhong Li: College of Forestry, Northwest A&F University, Yangling 712100, China
Pengxiang Zhao: College of Forestry, Northwest A&F University, Yangling 712100, China
Yanzheng Yang: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, China Academy of Science, Beijing 100085, China
Ruikun Gou: Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China

Sustainability, 2020, vol. 12, issue 18, 1-18

Abstract: Competition is an essential driving factor that influences forest community sustainability, yet measuring it poses several challenges. To date, the Competition Index (CI) has generally been the tool of choice for quantifying actual competition. In this study, we proposed using the Total Overlap Index (TOI), a CI in which the Area Overlap (AO) index has been adapted and modified to consider the “shading” and “crowding” effects in the vertical dimension. Next, based on six mixed forest plots in Xiaolong Mountain, Gansu, China, we assessed the results to determine the TOI’s evaluation capability. Individual-tree simulation results showed that compared to the modified Area Overlap index (AO M ), the TOI has superior quantification capability in the vertical direction. The results of the basal area increment (BAI) model showed that the TOI offers the best evaluation capability among the four considered CIs in mixed forest (with Akaike Information Criterion (AIC) of 1041.60 and log-likelihood (LL) of −511.80 in the model fitting test, mean relative error of −28.67%, mean absolute percent error of 117.11%, and root mean square error of 0.7993 in cross-validation). Finally, the TOI was applied in the Kaplan–Meier survival analysis and Cox proportional-hazards analysis. The Kaplan–Meier survival analysis showed a significant difference between the low- (consisting of trees with the TOI lower than 1) and high-competition (consisting of trees with the TOI higher than 1) groups’ survival and hazard curves. Moreover, the results of the Cox proportional-hazards analysis exhibited that the trees in the low-competition group only suffered 34.29% of the hazard risk that trees in the high-competition group suffered. Overall, the TOI expresses more dimensional information than other CIs and appears to be an effective competition index for evaluating individual tree competition. Thus, the competition status quantified using this method may provide new information to guide policy- and decision-makers in sustainable forest management planning projects.

Keywords: competition index; Total Overlap Index; three-dimensional; basal area increment model; tree mortality model; survival and hazard analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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