Spatiotemporal Simulation of Net Ecosystem Productivity and Its Response to Climate Change in Subtropical Forests

Zheng, Junlong; Mao, Fangjie; Du, Huaqiang; Li, Xuejian; Zhou, Guomo; Dong, Long; Zhang, Meng; Han, Ning; Liu, Tengyan; Xing, Luqi

doi:10.3390/f10080708

Cited by 18 publications

(8 citation statements)

References 47 publications

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“…We find that the dominant factors on NEP are mainly PRE and VPD at low and high elevations, which is similar with previous studies (T. Zhang et al., 2018; Zheng et al., 2019), while TEM has a greater impact at medium elevations. When elevation <2,000 m, water factors dominate NEP change due to higher water demand in forest, cropland and grassland.…”

Section: Discussionsupporting

confidence: 92%

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

Kong,

Zhang,

Gong

et al. 2023

JGR Biogeosciences

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Net ecosystem productivity (NEP) is important in the carbon cycle. However, the divergent responses of NEP to climate change along topographical gradient, particularly slope, and aspect, is not yet well understood. This study investigates divergent response of NEP to climate change during 1981–2018 along topographical gradient by Ensemble Empirical Mode Decomposition and multiple regression. The results indicate that: (a) NEP increases at low elevations, but first decreases and then increases at mid‐high elevations, and decreases at high elevations. NEP increases with slope. NEP is higher in the east and west but lower in the north and south. (b) With elevation increasing, negative correlation of temperature (TEM) and vapor pressure deficit (VPD), along with the positive correlation of precipitation (PRE) and Solar radiation (SR) strengthens first and then weaken, but PRE's positive correlation strengthens again after 4,000 m, and TEM's negative correlation changes to positive at high elevations. Moreover, soil moisture (SM's) positive correlation strengthens overall. NEP changes are dominated by PRE and VPD below 2,000 m, by TEM and PRE at 2,000–4,000 m, and by PRE and SM above 4,000 m. (c) With slope increasing, the negative correlation of TEM and the positive correlation of SM and SR and their importance strengthen. While PRE's positive correlation and VPD's negative correlation, and their importance weaken. (d) NEP changes are controlled by PRE and VPD in all respect, but the positive relationship of PRE and its importance weakens from north to west, opposite to VPD. Our results highlight the importance of topography for deeply understanding NEP's response to climate changes.

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Section: Discussionsupporting

confidence: 92%

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

Kong,

Zhang,

Gong

et al. 2023

JGR Biogeosciences

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“…The region was characterized as typical subtropical monsoon climate, with a mean annual temperature of 16.4°C and a mean annual precipitation of 1450 mm (Wang et al., 2022 ). Meanwhile, mean annual relative humidity is 79% and mean total sunshine is 1996 h (Xu et al., 2014 ; Zheng et al., 2019 ). The seasonal distribution of precipitation is uneven, with abundant rainfall in spring and during the monsoon season.…”

Section: Methodsmentioning

confidence: 99%

Decoupling of nitrogen allocation and energy partitioning in rice after flowering

Zhong,

Chi,

Ding

et al. 2024

Ecology and Evolution

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Estimation of energy partitioning at leaf scale, such as fluorescence yield (ΦF) and photochemical yield (ΦP), is crucial to tracking vegetation gross primary productivity (GPP) at global scale. Nitrogen is an important participant in the process of light capture, electron transfer, and carboxylation in vegetation photosynthesis. However, the quantitative relationship between leaf nitrogen allocation and leaf energy partitioning remains unexplored. Here, a field experiment was established to explore growth stage variations in energy partitioning and nitrogen allocation at leaf scale using active fluorescence detection and photosynthetic gas exchange method in rice in the subtropical region of China. We observed a strongly positive correlation between the investment proportion of leaf nitrogen in photosynthetic system and ΦF during the vegetative growth stage. There were significant differences in leaf energy partitioning, leaf nitrogen allocation, and the relationship between ΦF and ΦP before and after flowering. Furthermore, flowering weakened the correlation between the investment proportion of leaf nitrogen in photosynthetic system and ΦF. These findings highlight the crucial role of phenological factors in exploring seasonal photosynthetic dynamics and carbon fixation of ecosystems.

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“…Future climate data for Anji County from 2019 to 2024 [38,44] were simulated under the representative concentration pathway (RCP) 2.4, 4.5, 6.0 and 8.5 scenarios proposed by the IPCC AR5 [45]. The concentrations of greenhouse gases such as CO 2 , CH 4 , and N 2 O under the four scenarios from 2004 to 2049 are shown in Figure 2, which suggests that RCP2.6 is the scenario with the lowest greenhouse gas emissions, RCP4.5 and RCP6.0 are the intermediate stability scenarios, and RCP8.5 is the high-emission scenario, with the highest and increasing greenhouse gas concentrations.…”

Section: Datamentioning

confidence: 99%

Spatiotemporal LUCC Simulation under Different RCP Scenarios Based on the BPNN_CA_Markov Model: A Case Study of Bamboo Forest in Anji County

Huang

et al. 2020

IJGI

Self Cite

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Simulating spatiotemporal land use and land cover change (LUCC) data precisely under future climate scenarios is an important basis for revealing the carbon cycle response of forest ecosystems to LUCC. In this paper, a coupling model consisting of a back propagation neural network (BPNN), Markov chain, and cellular automata (CA) was designed to simulate the LUCC in Anji County, Zhejiang Province, under four climate scenarios (Representative Concentration Pathway (RCP) 2.6, 4.5, 6.0, 8.5) from 2024 to 2049 and to analyze the temporal and spatial distribution of bamboo forests in Anji County. Our results provide four outcomes. (1) The transition probability matrices indicate that the area of bamboo forests shows an expansion trend, and the largest contribution to the expansion of bamboo forests is the cultivated land. The Markov chain composed of the average transition probability matrix could perform excellently, with only small errors when simulating the areas of different land-use types. (2) Based on the optimized BPNN, which had a strong generalization ability, a high prediction accuracy, and area under the curve (AUC) values above 0.9, we could obtain highly reliable land suitability probabilities. After introducing more driving factors related to bamboo forests, the prediction of bamboo forest changes will be more accurate. (3) The BPNN_CA_Markov coupling model could achieve high-precision simulation of LUCC at different times, with an overall accuracy greater than 70%, and the consistency of the LUCC simulation from one time to another also had good performance, with a figure of merit (FOM) of approximately 40%. (4) Under the future four RCP scenarios, bamboo forest evolution had similar spatial characteristics; that is, bamboo forests were projected to expand in the northeast, south, and southwest mountainous areas of Anji County, while bamboo forests were projected to decline mainly around the junction of the central and mountainous areas of Anji County. Comparing the simulation results of different scenarios demonstrates that 74% of the spatiotemporal evolution of bamboo forests will be influenced by the interactions and competition among different land-use types and other driving factors, and 26% will come from different climate scenarios, among which the RCP8.5 scenario will have the greatest impact on the bamboo forest area and spatiotemporal evolution, while the RCP2.6 scenario will have the smallest impact. In short, this study proposes effective methods and ideas for LUCC simulation in the context of climate change and provides accurate data support for analyzing the impact of LUCC on the carbon cycle of bamboo forests.

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Spatiotemporal Simulation of Net Ecosystem Productivity and Its Response to Climate Change in Subtropical Forests

Cited by 18 publications

References 47 publications

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

Decoupling of nitrogen allocation and energy partitioning in rice after flowering

Spatiotemporal LUCC Simulation under Different RCP Scenarios Based on the BPNN_CA_Markov Model: A Case Study of Bamboo Forest in Anji County

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