Nonlinear imprints of forest coverage on the relationships between gross primary production (GPP) and landscape patterns

Haiqiang Gao; Shuguang Liu; Shuailong Feng; Xi Peng; Ying Ning; Yi Shi; Zhao Wang; Baojing Wei; Wende Yan

Ecological Indicators (Feb 2023)

Nonlinear imprints of forest coverage on the relationships between gross primary production (GPP) and landscape patterns

Haiqiang Gao,
Shuguang Liu,
Shuailong Feng,
Xi Peng,
Ying Ning,
Yi Shi,
Zhao Wang,
Baojing Wei,
Wende Yan

Affiliations

Haiqiang Gao: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Shuguang Liu: Corresponding author.; National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Shuailong Feng: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Xi Peng: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Ying Ning: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Yi Shi: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Zhao Wang: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Baojing Wei: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
Wende Yan: National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, and College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China

Journal volume & issue: Vol. 146
p. 109783

Abstract

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Land use and land cover change (LUCC) has yielded significant impacts on ecosystem structure and functions. Gross primary production (GPP), the largest flux in the terrestrial carbon cycle, has been drastically changed by various LUCC activities. However, the indirect impacts of LUCC on GPP (i.e., local environment changes induced by LUCC), particularly those related to landscape dynamics, remain unclear. Here, we explored the relationships between GPP and landscape metrics of forest ecosystems in China along a forest coverage gradient from 2001 to 2019, using an up-to-date GPP dataset derived from Solar-Induced Chlorophyll Fluorescence and a widely used landcover product MCD12Q1. Results showed that forest landscape features (e.g., core area index, CAI) synchronized with GPP spatially as shown by the distribution of their hot/cold spots on correlations. Furthermore, two nonlinear change patterns of GPP and landscape metrics along forest coverage gradient were found. One is a hump-shaped pattern, which indicated that GPP and some landscape features (e.g., annual median GPP, annual change rate of forest composition) peaked in medium (about 70–80%) forest-cover regions. Another is a super-linear curve, revealing the rapid and accelerated growth of some landscape features (e.g., annual median CAI) in high forest-cover regions. Finally, forest coverage affected the sensitivity of GPP to landscape features in a nonlinear fashion, characterized as an inverted ‘hook’ curve peaking in intermediate (around 70%) forest-coverage regions. Our study proposed the optimal landscape regulation hypothesis to explain the nonlinear pattern: forest GPP is most responsive to the landscape pattern regulation at intermediate to low levels of disturbance, implying that forest coverage has various impacts on landscape features; together they affect GPP nonlinearly. Regulating the forest landscape composition and configuration can enhance the performance of forest ecosystems in addition to managing forest coverage. Thus, we recommend the adoption of suitable region-specific forest management practices to improve GPP and other ecosystem services of forest ecosystems via manipulating landscape composition and configuration.

Published in Ecological Indicators

ISSN: 1470-160X (Print); 1872-7034 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General): Ecology
Website: https://www.sciencedirect.com/journal/ecological-indicators

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