A review of forest carbon cycle models on spatiotemporal scales

Jun, Zhao; Li, Dongsheng; Zhu, Yan; Peng, Huiwen; Xie, Hongfei

doi:10.1016/j.jclepro.2022.130692

Cited by 34 publications

(10 citation statements)

References 97 publications

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“…As one of the major terrestrial ecosystems, forest ecosystems, which cover about 30% of the land area [9], are one of the largest conduits for transferring carbon from the atmosphere to the terrestrial ecosystems through photosynthesis [10,11] and reformulating the global or regional climate via water consumption of transpiration [5,12,13]. The Chinese subtropical forest ecosystems, with an area of nearly 1.4 × 10 6 km 2 , are an extremely important component of the global forest ecosystems and are hence crucial to the global carbon cycle and regional climate change.…”

Section: Introductionmentioning

confidence: 99%

Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China’s Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model

et al. 2023

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The subtropical forests in China play a pivotal part in the global and regional carbon–water cycle and in regulating the climate. Ecosystem water-use efficiency (WUE) is a crucial index for understanding the trade-off between ecosystem carbon gain and water consumption. However, the underlying mechanisms of the WUE in forest ecosystems, especially the different subtropical forests, have remained unclear. In this paper, we developed a simple framework for estimating forest WUE and revealing the underlying mechanisms of forest WUE changes via a series of numerical experiments. Validated by measured WUE, the simulated WUE from our developed WUE framework showed a good performance. In addition, we found that the subtropical forest WUE experienced a significant increasing trend during 2001–2018, especially in evergreen and deciduous broadleaf forests where the increasing rate was greatest (0.027 gC kg−1 H2O year−1, p < 0.001). Further analysis indicated that the atmospheric CO2 concentration and vapor pressure deficits (VPD), rather than leaf area index (LAI), were the dominant drivers leading to the subtropical forest WUE changes. When summed for the whole subtropical forests, CO2 and VPD had an almost equal spatial impact on annual WUE change trends and accounted for 45.3% and 49.1% of the whole study area, respectively. This suggests that future forest management aiming to increase forest carbon uptake and protect water resources needs to pay more attention to the long-term impacts of climate change on forest WUE.

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Section: Introductionmentioning

confidence: 99%

Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China’s Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model

et al. 2023

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“…As revealed in Pyles et al (2022), FCS growth is not only related to natural factors such as precipitation, temperature, radiation changes, biodiversity, fires, pests, and diseases but also influenced by factors such as forest harvesting, land use change, factor input, management level, urbanization expansion, population growth, agricultural production, etc. Furthermore, Zhao et al (2022) proposed that forest logging, forest disaster severity, and precipitation influence FCS levels differently. Similarly, scholar Heinrich et al (2023) argued that FCS has regional, phased, and unstable characteristics, and the impact of different factors on FCS is highly heterogeneous.…”

Section: The Measurement and Influencing Factors Of Fcsmentioning

confidence: 99%

An exploration of spatial-temporal characteristics and spatial spillover effects of forest carbon sinks in the Yellow River Basin, China

2023

Preprint

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Developing forest carbon sinks (FCS) is significant for China to achieve carbon neutrality. The Yellow River Basin is a principal area for China’s energy consumption, and the forest resource distribution of this vast basin is spatially dependent, determining that the development of FCS cannot be separated geographically. Based on the spatial panel data of 69 prefecture-level cities in the Yellow River basin from 1988 to 2018, we used ESDA to reveal the spatial–temporal characteristics of FCS, and we established a spatial econometric model to investigate the transregional spillover effects of FCS. The results showed that: ① the overall FCS showed a gradually increasing trend, with a general distribution characteristic of “upstream > midstream > downstream” from 1988 to 2018. ②FCS presented an agglomeration distribution pattern with significant spatial spillover effects, and the degree of uneven spatial agglomeration varied across the years. ③Urbanization rate, forestry fixed assets investment, labor input, and afforestation management level directly promote FCS growth, whereas forest harvesting, precipitation, and temperature decrease FCS. ④Urbanization rate, forest harvesting, forestry fixed assets investment, labor input, and afforestation management level have positive spillover effects on FCS, while precipitation and temperature have adverse spillover effects on FCS. Hence, pertinent policy suggestions are put out to serve as a guide for increasing FCS.

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“…Remote sensing data, characterized by long time series and wide coverage, has become an essential means for estimating the spatiotemporal characteristics and driving mechanisms of global vegetation NPP through top-down research methods based on remote sensing data inversion [17]. Currently, both domestically and internationally, the monitoring of large-scale vegetation NPP relies mainly on remote sensing interpretation estimates [18]. MODIS data, due to its high temporal resolution and low cost, has become one of the primary remote sensing data sources for simulating and estimating regional vegetation NPP [19].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia

Peng,

Li,

Wang

et al. 2024

Agriculture

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The Hetao Irrigation District in Inner Mongolia, a vital grain-producing region in northern China, faces growing environmental challenges. Studying net primary productivity (NPP) is essential for understanding spatiotemporal vegetation shifts and guiding locally adapted restoration and management efforts. Utilizing MOD17A3/NPP data, this study applies the Theil–Sen median trend, Mann–Kendall significance, and the Hurst index to scrutinize the spatiotemporal distribution patterns of NPP from 2001 to 2021 and forecast future changes in the area. The findings reveal cyclic temporal trends, forming a “∧” shape with initial increases followed by decreases, notably during the July to August period each year. The multi-year average NPP exhibits a slight upward fluctuation trend, averaging 172.40 gCm−2a−1. Peaks occur approximately every three years, reaching the highest average in 2012 at 218.96 gCm−2a−1. Spatially, NPP distribution stays consistent over the years, influenced by various land cover types, especially cropland, shaping the spatial patterns. Monthly and yearly NPP trends over the 21 years indicate a significant decrease in May and June, with other months mostly showing a non-significant increase. The Hurst index for monthly and yearly NPP changes over 21 years shows relatively high weak anti-persistence. In summary, over the past 21 years, the NPP trend in the study area has not significantly improved and is expected to decline in the future. This study offers data support and a scientific foundation for refining the carbon cycle model, quantifying vegetation carbon sequestration capacity, addressing climate change policies, and striving for carbon peak and neutrality in the Hetao Irrigation District.

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A review of forest carbon cycle models on spatiotemporal scales

Cited by 34 publications

References 97 publications

Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China’s Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model

Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China’s Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model

An exploration of spatial-temporal characteristics and spatial spillover effects of forest carbon sinks in the Yellow River Basin, China

Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia

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