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Land
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Carbon Cycling in Terrestrial Ecosystems
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Carbon Cycling in Terrestrial Ecosystems

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land–Climate Interactions".

Deadline for manuscript submissions: closed (25 December 2022) | Viewed by 9709

Special Issue Editor

Dr. Nima Madani

E-Mail Website
Guest Editor
NASA Jet Propulsion Laboratory (JPL), 4800 Oak Grove Dr, Pasadena, CA 91109, USA
Interests: terrestrial ecosystem productivity modeling; carbon-climate feedbacks; species-climate interactions and habitat modeling

Special Issue Information

Dear Colleagues,

With the continuation of increasing CO2 emissions, recent studies indicate emerging positive climate feedback due to increasing temperatures and moisture constraints that is highly expected to limit ecosystem productivity. As climate change is becoming the main threat to life on Earth, local authorities in multiple countries, states and cities are developing plans to reduce their emissions and reach the zero emissions target in the near future. However, the estimation of ecosystem productivity at regional to local levels is still challenging and improvements in understanding carbon sources and sinks at regional to local scales allows authorities to reach their targets and help the global modeling community to improve model performance and predictions.

In this Special Issue on “Carbon Cycling in Terrestrial Ecosystems”, we call for papers involving one or more of the following topical areas, with emphasis on terrestrial ecosystem productivity using multi-scale satellites, field-based observations, and multiple modeling approaches:

  • Application of global models to analyze ecosystem productivity, including gross and net primary production, and net ecosystem exchange at regional to local scales.
  • Satellite observations and airborne remote sensing approaches to monitor the response of ecosystems to changes in climate.
  • Analyzing trends and anomalies in terrestrial ecosystem productivity, including the impact of disturbance events on vegetation activity.
  • New application and developments in plant productivity estimates, vegetation phenology indices, and drought detection and forecast.

Dr. Nima Madani
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

16 pages, 4577 KiB  
Article
Inventory of China’s Net Biome Productivity since the 21st Century
by Chaochao Du, Xiaoyong Bai, Yangbing Li, Qiu Tan, Cuiwei Zhao, Guangjie Luo, Luhua Wu, Fei Chen, Chaojun Li, Chen Ran, Xuling Luo, Huipeng Xi, Huan Chen, Sirui Zhang, Min Liu, Suhua Gong, Lian Xiong, Fengjiao Song and Biqin Xiao
Land 2022, 11(8), 1244; https://0-doi-org.brum.beds.ac.uk/10.3390/land11081244 - 04 Aug 2022
Cited by 7 | Viewed by 1469
Abstract
Net biome productivity (NBP), which takes into account abiotic respiration and metabolic processes such as fire, pests, and harvesting of agricultural and forestry products, may be more scientific than net ecosystem productivity (NEP) in measuring ecosystem carbon sink levels. As one of the [...] Read more.
Net biome productivity (NBP), which takes into account abiotic respiration and metabolic processes such as fire, pests, and harvesting of agricultural and forestry products, may be more scientific than net ecosystem productivity (NEP) in measuring ecosystem carbon sink levels. As one of the largest countries in global carbon emissions, in China, however, the spatial pattern and evolution of its NBP are still unclear. To this end, we estimated the magnitude of NBP in 31 Chinese provinces (except Hong Kong, Macau, and Taiwan) from 2000 to 2018, and clarified its temporal and spatial evolution. The results show that: (1) the total amount of NBP in China was about 0.21 Pg C/yr1. Among them, Yunnan Province had the highest NBP (0.09 Pg C/yr1), accounting for about 43% of China’s total. (2) NBP increased from a rate of 0.19 Tg C/yr1 during the study period. (3) At present, NBP in China’s terrestrial ecosystems is mainly distributed in southwest and south China, while northwest and central China are weak carbon sinks or carbon sources. (4) The relative contribution rates of carbon emission fluxes due to emissions from anthropogenic disturbances (harvest of agricultural and forestry products) and natural disturbances (fires, pests, etc.) were 70% and 9.87%, respectively. This study emphasizes the importance of using NBP to re-estimate the net carbon sink of China’s terrestrial ecosystem, which is beneficial to providing data support for the realization of China’s carbon neutrality goal and global carbon cycle research. Full article
(This article belongs to the Special Issue Carbon Cycling in Terrestrial Ecosystems)
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15 pages, 2936 KiB  
Article
A Study of Carbon Stock Changes in the Alpine Grassland Ecosystem of Zoigê, China, 2000–2020
by Rui Qu, Li He, Zhengwei He, Bing Wang, Pengyi Lyu, Jiaxian Wang, Guichuan Kang and Wenqian Bai
Land 2022, 11(8), 1232; https://0-doi-org.brum.beds.ac.uk/10.3390/land11081232 - 04 Aug 2022
Cited by 5 | Viewed by 1391
Abstract
Terrestrial carbon sequestration capacity is an important indicator of ecosystem service function, and the carbon storage value can reflect the climate regulation capacity of the regional ecological environment. The Zoigê alpine grassland is a representative area of the Qinghai-Tibet Plateau grassland ecosystem, with [...] Read more.
Terrestrial carbon sequestration capacity is an important indicator of ecosystem service function, and the carbon storage value can reflect the climate regulation capacity of the regional ecological environment. The Zoigê alpine grassland is a representative area of the Qinghai-Tibet Plateau grassland ecosystem, with carbon sequestration types such as alpine grassland and marsh meadow and also an important water-conserving area in the upper reaches of the Yangtze River and the Yellow River. In this study, based on the land use/cover change pattern of the Zoigê alpine grassland region from 2000 to 2020, the carbon density coefficients corrected by the regional average annual precipitation and temperature factors were used to assess the carbon stocks of the Zoigê alpine grassland for three periods from 2000 to 2020 using the InVEST model. The results showed that the carbon stocks of the Zoigê alpine grassland region were 786.19 Tg, 780.02 Tg, and 775.22 Tg in 2000, 2010, and 2020, respectively, with a cumulative loss of 10.97 Tg and carbon densities of 183.70 t/ha, 182.26 t/ha, and 181.14 t/ha, showing a decreasing trend year by year. The carbon stock of the grassland ecosystem is the absolute contributor to the regional carbon stock, and the carbon stock accounts for 75.28% of the total carbon stock. The increase in the cultivated land area with a lower carbon density and the decrease in the grassland area with a higher carbon density are the main factors leading to the decrease in the carbon stock in the regional ecosystem of the Zoigê alpine grassland. Full article
(This article belongs to the Special Issue Carbon Cycling in Terrestrial Ecosystems)
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18 pages, 10111 KiB  
Article
India’s Greening Trend Seems to Slow Down. What Does Aerosol Have to Do with It?
by Manoj Hari and Bhishma Tyagi
Land 2022, 11(4), 538; https://0-doi-org.brum.beds.ac.uk/10.3390/land11040538 - 07 Apr 2022
Cited by 6 | Viewed by 1427
Abstract
Multiple drivers perturb the terrestrial carbon cycle, which ultimately reshapes the fertilization of carbon dioxide (CO2) and reorientates the climate. One such driver is atmospheric aerosols, which cascade the ecosystem’s productivity in a large proportionality. Investigating this relation is non-conventional and [...] Read more.
Multiple drivers perturb the terrestrial carbon cycle, which ultimately reshapes the fertilization of carbon dioxide (CO2) and reorientates the climate. One such driver is atmospheric aerosols, which cascade the ecosystem’s productivity in a large proportionality. Investigating this relation is non-conventional and limited across the globe. With the abundance of heterogenetic terrestrial ecosystems, India’s primary productivity has a large proportion of the global carbon balance. Under climate change stress, India’s unique spatial and climatological features perturb atmospheric aerosols from natural sources to anthropogenic sources. In light of that, this study utilizes the Carnegie–Ames Stanford Approach (CASA) model to elucidate the consequence by examining the potential effect of aerosol load on the ecosystem productivity (Net Primary Production; NPP) for various agroclimatic zones of India from 2001–2020. CASA reveals a negative decadal amplitude with an overall increase in the NPP trend. In contrast, aerosol loadings from MODIS highlight the increasing trend, with definite seasonal intensities. Employing the CASA model and earth observations, the study highlights the increase in NPP in forest-based ecosystems due to relatively lower aerosols and higher diffuse radiation. Critically, strong dampening of NPP was observed in the agroecological and sparse vegetation zones inferring that the aerosol loadings affect the primary productivity by affecting the photosynthesis of canopy architecture. Spatial sensitivity zones across different ecological regions result in a non-homogenous response because of different phenological and canopy architecture that is mediated by the radiation intensities. Based on the analysis, the study infers that AOD positively influences the canopy-scale photosynthesis by diffuse radiation, which promotes NPP but is less likely for the crop canopy ecosystems. Barring the limitations, enhancement of NPP in the forest ecosystems offset the demand for carbon sink in the agroecosystems. Findings from this study reveal that a more precise provenance of aerosol effects on carbon fluxes is required to understand the uncertainties in the terrestrial carbon cycle. Full article
(This article belongs to the Special Issue Carbon Cycling in Terrestrial Ecosystems)
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16 pages, 4508 KiB  
Article
Model Selection for Ecosystem Respiration Needs to Be Site Specific: Lessons from Grasslands on the Mongolian Plateau
by Huimin Zou, Jiquan Chen, Changliang Shao, Gang Dong, Meihui Duan, Qingsong Zhu and Xianglan Li
Land 2022, 11(1), 87; https://0-doi-org.brum.beds.ac.uk/10.3390/land11010087 - 06 Jan 2022
Cited by 2 | Viewed by 1522
Abstract
Selecting an appropriate model for simulating ecosystem respiration is critical in modeling the carbon cycle of terrestrial ecosystems due to their magnitude and high variations in time and space. There is no consensus on the ideal model for estimating ecosystem respiration in different [...] Read more.
Selecting an appropriate model for simulating ecosystem respiration is critical in modeling the carbon cycle of terrestrial ecosystems due to their magnitude and high variations in time and space. There is no consensus on the ideal model for estimating ecosystem respiration in different ecosystems. We evaluated the performances of six respiration models, including Arrhenius, logistic, Gamma, Martin, Concilio, and time series model, against measured ecosystem respiration during 2014–2018 in four grassland ecosystems on the Mongolian Plateau: shrubland, dry steppe, temperate steppe, and meadow ecosystems. Ecosystem respiration increased exponentially with soil temperature within an apparent threshold of ~19.62 °C at shrubland, ~16.05 °C at dry steppe, ~16.92 °C at temperate steppe, and ~15.03 °C at meadow. The six models explained approximately 50–80% of the variabilities of ecosystem respiration during the study period. Both soil temperature and soil moisture played considerable roles in simulating ecosystem respiration with R square, ranging from 0.5 to 0.8. The Martin model performed better than the other models, with a relatively high R square, i.e., R2 = 0.68 at shrubland, R2 = 0.57 at dry steppe, R2 = 0.74 at temperate steppe, and R2 = 0.81 at meadow. These models achieved good performance for around 50–80% of the simulations. No single model performs best for all four grassland types, while each model appears suitable for at least one type of ecosystem. Models that oil moisture include models, especially the Martin model, are more suitable for the accurate prediction of ecosystem respiration than Ts-only models for the four grassland ecosystems. Full article
(This article belongs to the Special Issue Carbon Cycling in Terrestrial Ecosystems)
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19 pages, 5302 KiB  
Article
High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data
by Haruko M. Wainwright, Rusen Oktem, Baptiste Dafflon, Sigrid Dengel, John B. Curtis, Margaret S. Torn, Jessica Cherry and Susan S. Hubbard
Land 2021, 10(7), 722; https://0-doi-org.brum.beds.ac.uk/10.3390/land10070722 - 09 Jul 2021
Cited by 4 | Viewed by 2820
Abstract
Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m [...] Read more.
Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange. Full article
(This article belongs to the Special Issue Carbon Cycling in Terrestrial Ecosystems)
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