Changes in Biomass Turnover Times in Tropical Forests and Their Environmental Drivers From 2001 to 2012

Wang, Jingmeng; Li, Wei; Ciais, Philippe; Ballantyne, Ashley P.; Goll, Daniel S.; Zhao, Zhe; Zhu, Lei

doi:10.1029/2020ef001655

Cited by 6 publications

(3 citation statements)

References 94 publications

(213 reference statements)

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“…Over the past 20 years, the global NPP generally displayed an increasing trend with significant improvements in tropical rainforests in Africa [34], subtropical regions [35], and the alpine Tibetan Plateau in China [36]. In contrast, the vegetation NPP monitored in Southeast Asia [37], western Amazonian tropical rainforests [37], temperate desert-steppe in Inner Mongolia of China [38], and semi-dry grasslands in Australia showed a decreasing trend [39]. Gang et al found that the main changes in grassland NPP were positively correlated with precipitation (PRE) after comparing the analyses of grassland NPP in China, North America, Europe, and Australia from 1981 to 2010 [10].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Spatiotemporal Variation of NPP of Different Land Cover Types and the Contribution of Its Associated Factors in the Songnen Plain

Lin,

Li,

Jiang

et al. 2023

Forests

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Net primary productivity (NPP) of vegetation is considered an important indicator for ecological stability and is the main object for analyzing the factors influencing the terrestrial carbon cycle. Recent studies have made clear the changes in the NPP of vegetation and its influencing factors at various scales. However, the variations in NPP based on different land cover types under various natural conditions, along with their driving factors, remain not well understood. In this study, spatial overlay analysis was used to investigate the link among climatic, soil moisture (SM), and topographic parameters and NPP of various land cover types after analyzing the spatial and temporal trends of NPP in the Songnen Plain from 2001 to 2020. Additionally, the contribution of each influence factor to the NPP of different land cover types was calculated using the elastic net regression model. The elastic net regression model eliminates the multicollinearity among the influencing factors while maintaining the model stability, and the R2 of all lands is greater than 0.62, which can effectively quantify the contribution of each influencing factor to NPP. The results show a continuously increasing trend of the overall NPP in the research area over the selected 20 years, and NPP increased most significantly in forest land (FOR). Precipitation (PRE) and NPP showed high correlations in all the different land cover types, while the correlations between NPP and other influencing factors were significantly different. In addition, we found that perennials led to a more significant degree of NPP enhancement, and the effect of topographic conditions on NPP was mainly reflected in differences in moisture conditions due to surface runoff. From the results of the modeling calculations, the cumulative contribution of PRE to NPP ranks first in all land types and is the most vital influencing factor of NPP in the Songnen Plain. SM was an important influence, but the contribution of NPP was greater in land classes with shallow root systems. The results of the study revealed the positive transformation relationship of NPP among land cover types in ecologically fragile areas, which provides a reference for ecological restoration and rationalization of land use structure in zones such as intertwined agricultural and pastoral zones.

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Section: Introductionmentioning

confidence: 99%

Quantifying the Spatiotemporal Variation of NPP of Different Land Cover Types and the Contribution of Its Associated Factors in the Songnen Plain

Lin,

Li,

Jiang

et al. 2023

Forests

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“…Wang et al. (2020) analysed temporal trends in τ in tropical forests from 2001 to 2012 using remote‐sensing‐based biomass and NPP datasets. They observed that τ was statistically associated with mean annual precipitation (MAP), radiation, and vapour pressure deficit.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Carvalhais et al (2014) calculated the global spatial distribution of τ using multiple sources of carbon stock and flux data, and found a strong association of τ with precipitation and temperature. Wang et al (2020) analysed temporal trends in τ in tropical forests from 2001 to 2012 using remote-sensing-based biomass and NPP datasets. They observed that τ was statistically associated with mean annual precipitation (MAP), radiation, and vapour pressure deficit.…”

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confidence: 99%

Forest biomass turnover time estimation in China based on spatially explicit root : shoot ratios

Guo

Chen

Luo

et al. 2022

Global Ecol. Biogeogr.

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Aim Spatial patterns of root : shoot ratios (R:S) are critical to better estimate biomass turnover time (τ). Given the difficulty of measuring belowground biomass directly, we still lack an understanding of high‐resolution spatial patterns of R:S in China's forests. Here, we explored patterns of R:S and their association with stand age, tree height, elevation, land cover, and climatic and edaphic variables, and estimated τ for China's forests. Location China. Time period 2004 and 2010. Major taxa studied Forests. Methods We used a machine learning algorithm trained with an R:S dataset of 1,907 observations covering five forest types to upscale the spatial distribution of R:S in China as a function of stand age, tree height, elevation, land cover, and climatic and edaphic variables. We calculated τ using the estimated R:S together with satellite‐based aboveground biomass and net primary productivity data at 1 km × 1 km resolution. Results The estimated mean τ for total biomass in China's forests was 10.8‐2.0+3.2years. The longest τ (τ > 20 years) was observed in central China, whereas southern China exhibited the shortest τ (τ < 10 years). Large differences in partial correlations between τ and climatic variables (mean annual precipitation, climatological water deficit, and mean annual temperature) were observed among forest types. Main conclusions Our data‐driven gridded maps of estimated R:S and τ provide valuable baseline information for assessing model performance and improving future carbon‐cycle assessments.

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Role of sacred groves in southwestern Nigeria in biodiversity conservation, biomass and carbon storage

Onyekwelu,

Agbelade,

Stimm

et al. 2024

Environ Monit Assess

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Changes in Biomass Turnover Times in Tropical Forests and Their Environmental Drivers From 2001 to 2012

Abstract: Tropical forests play a key role in the global carbon (C) cycle and the climate system (

Cited by 6 publications

References 94 publications

Quantifying the Spatiotemporal Variation of NPP of Different Land Cover Types and the Contribution of Its Associated Factors in the Songnen Plain

Quantifying the Spatiotemporal Variation of NPP of Different Land Cover Types and the Contribution of Its Associated Factors in the Songnen Plain

Forest biomass turnover time estimation in China based on spatially explicit root : shoot ratios

Role of sacred groves in southwestern Nigeria in biodiversity conservation, biomass and carbon storage

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