Evaluating Spatial-Temporal Dynamics of Net Primary Productivity of Different Forest Types in Northeastern China Based on Improved FORCCHN

Ben Bond-Lamberty,Jianping Guo,Gensuo Jia,Junfang Zhao,Xiaodong Yan

doi:10.1371/journal.pone.0048131

Abstract

An improved individual-based forest ecosystem carbon budget model for China (FORCCHN) was applied to investigate the spatial-temporal dynamics of net primary productivity of different forest types in northeastern China. In this study, the forests of northeastern China were categorized into four ecological types according to their habitats and generic characteristics (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forest). The results showed that distribution and change of forest NPP in northeastern China were related to the different forest types. From 1981 to 2002, among the forest types in northeastern China, per unit area NPP and total NPP of deciduous broadleaf forest were the highest, with the values of 729.4 gC/(m2•yr) and 106.0 TgC/yr, respectively, followed by mixed broadleaf- needleleaf forest, deciduous needleleaf forest and evergreen needleleaf forest. From 1981 to 2002, per unit area NPP and total NPP of different forest types in northeastern China exhibited significant trends of interannual increase, and rapid increase was found between the 1980s and 1990s. The contribution of the different forest type’s NPP to total NPP in northeastern China was clearly different. The greatest was deciduous broadleaf forest, followed by mixed broadleaf- needleleaf forest and deciduous needleleaf forest. The smallest was evergreen needleleaf forest. Spatial difference in NPP between different forest types was remarkable. High NPP values of deciduous needleleaf forest, mixed broadleaf- needleleaf forest and deciduous broadleaf forest were found in the Daxing’anling region, the southeastern of Xiaoxing’anling and Jilin province, and the Changbai Mountain, respectively. However, no regional differences were found for evergreen needleleaf NPP. This study provided not only an estimation NPP of different forest types in northeastern China but also a useful methodology for estimating forest carbon storage at regional and global levels.

Highlights

As a key variable in our understanding of ecosystem processes and carbon exchange between biota and atmosphere, both currently and under climate change scenarios [1], net primary productivity (NPP) is defined as the difference between accumulated photosynthesis and accumulated autotrophic respiration by green plants per unit of time and space [2]
The detailed descriptions of the improved FORCCHN model9s features, mathematical representation, building strategy and validation were previously provided by Zhao et al [12]. This current study presents our first attempt to apply the improved FORCCHN model for studying the spatialtemporal dynamics of NPP of different forest types in northeastern China from 1981 to 2002
Temporal Patterns of NPP of Different Forest Types The temporal pattern of forest NPP was evident in the interannual variation

Summary

Introduction

As a key variable in our understanding of ecosystem processes and carbon exchange between biota and atmosphere, both currently and under climate change scenarios [1], net primary productivity (NPP) is defined as the difference between accumulated photosynthesis and accumulated autotrophic respiration by green plants per unit of time and space [2]. The average forest NPP, which was investigated the spatio-temporal changes of the forest9s NPP in China over the recent two decades based on a geographically weighted regression (GWR) with a cumulative remote sensing index, was essentially unchanged from the 1980s to late 1990s [6]. These previous studies are important for understanding various aspects of forest dynamics, NPP, and carbon balance; because of difficulties in obtaining longterm observations of disturbances, very limited studies have been conducted to quantitatively investigate the spatial-temporal trends of NPP of different forest types in northeastern China at a regional scale so far

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