Effects of Climate on Stand-Level Biomass for Larch Plantations in Heilongjiang Province, Northeast China

Author:

Mahardika Surya Bagus1ORCID,Xin Shidong1,Wang Weifang1,Jiang Lichun12

Affiliation:

1. Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China

2. Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, China

Abstract

Climate change affects forest resource availability, growing season length, and thus forest biomass accumulation. However, only a limited number of studies have been conducted on forest biomass management based on climate effects, particularly at the stand-level. Thus, an allometric biomass equation based on conventional and climate-based stand biomass models, was developed and compared for larch trees (Larix spp.). A total of 160 experimental plots of larch plantations have been collected in Heilongjiang Province, Northeast China. In this study, we developed four types of additive model systems for stand-level biomass: two types of the stand-level biomass basic models (M-1 and M-2) with stand variables (stand basal area (BA) and stand mean height (Hm)) as the predictors, and two types of the proposed stand-level biomass climate-based models (M-3 and M-4) with stand variables (BA and Hm) and climatic variables (mean annual temperature (MAT) and annual precipitation (AP)) as the predictors. Accordingly, this study evaluated the effects of climatic variables (MAT and AP) and stand variables (BA and Hm) on the model’s performance. Model fitting and validation results revealed that the climatic variables significantly improved the model performance of the fitted equation by increasing the coefficient of determination (R2) values and reducing the root mean square error (RMSE) values. A higher R2 and a lower RMSE were consistently generated by M-2 and M-4, whereas M-1 and M-3 consistently generated a lower R2 and a higher RMSE. We found that the proposed stand-level biomass climate-based model type 4 (M-4) performed better than the other models and slightly better than in previous studies of climate-sensitive models. This study provided an additional and beneficial method of analyzing climate effects on stand-level biomass estimation.

Funder

Heilongjiang Province Applied Technology Research and Development Plan Project of China

Publisher

MDPI AG

Subject

Forestry

Reference88 articles.

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3. United Nations Environment Programme and International Union for Conservation of Nature (2021). Nature-Based Solutions for Climate Change Mitigation, IUCN.

4. Climate Change Threats to Plant Diversity in Europe;Thuiller;Proc. Natl. Acad. Sci. USA,2005

5. Carbon Sequestration from China’s Afforestation Projects;He;Environ. Earth Sci.,2015

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