Ecosystem Carbon Stocks Research Articles

Forest Aboveground Biomass Estimation Based on Unmanned Aerial Vehicle-Light Detection and Ranging and Machine Learning.

Eucalyptus is a widely planted species in plantation forests because of its outstanding characteristics, such as fast growth rate and high adaptability. Accurate and rapid prediction of Eucalyptus biomass is important for plantation forest management and the prediction of carbon stock in terrestrial ecosystems. In this study, the performance of predictive biomass regression equations and machine learning algorithms, including multivariate linear stepwise regression (MLSR), support vector machine regression (SVR), and k-nearest neighbor (KNN) for constructing a predictive forest AGB model was analyzed and compared at individual tree and stand scales based on forest parameters extracted by Unmanned Aerial Vehicle-Light Detection and Ranging (UAV LiDAR) and variables screened by variable projection importance analysis to select the best prediction method. The results of the study concluded that the prediction model accuracy of the natural transformed regression equations (R2 = 0.873, RMSE = 0.312 t/ha, RRMSE = 0.0091) outperformed that of the machine learning algorithms at the individual tree scale. Among the machine learning models, the SVR prediction model accuracy was the best (R2 = 0.868, RMSE = 7.932 t/ha, RRMSE = 0.231). In this study, UAV-LiDAR-based data had great potential in predicting the AGB of Eucalyptus trees, and the tree height parameter had the strongest correlation with AGB. In summary, the combination of UAV LiDAR data and machine learning algorithms to construct a predictive forest AGB model has high accuracy and provides a solution for carbon stock assessment and forest ecosystem assessment.

Effects of salvage logging after forest fire on Siberian larch regeneration and ecosystem carbon stocks at the drought limit of the boreal forest in Mongolia

Post-fire salvage logging is widely applied in Mongolia's boreal forests with the intent to prevent intact forests from logging. The rationale behind this approach is the assumption that the additional disturbance caused by the removal of standing deadwood after stand-replacing fire is of no further significance for the already heavily disturbed ecosystem. However, while there is a global debate on effects of salvage logging for regeneration success, biodiversity, and soil health, little evidence has been collected from strongly drought-limited southern boreal forests of Central Asia. Comparing sites with and without salvage logging, we investigated forests of Siberian larch (Larix sibirica) ca. 20 years after stand-replacing fire and asked whether postfire salvage logging affected regeneration density, terminal shoot length and radial stem increment, ecosystem carbon stock densities, and reduced organic layer depth and compacted the soil. The biomass of the larch regeneration was significantly reduced by salvage logging, while tree growth was not affected. The ecosystem carbon stock density of burnt forest without salvage logging was 202 Mg C ha−1 and thus even in the lower range of intact larch forests from Mongolia, whereas burnt forests with salvage logging had organic carbon stock densities (104 Mg C ha−1) that were lower than those of unburned grasslands in the forest-steppe. These results show that removing deadwood from burnt forest is not insignificant, but has the potential to delay forest recovery and strongly reduces organic carbon storage. However, we did not find significant reductions in soil organic carbon stocks or soil compaction. Nonetheless, our findings raise the question of whether careful management of intact forests (especially by selective felling under a continuous-cover forestry regime) would be a more ecologically sustainable alternative than post-fire salvage logging.

Acclimation of Photosynthesis to CO2 Increases Ecosystem Carbon Storage due to Leaf Nitrogen Savings.

Photosynthesis is the largest flux of carbon between the atmosphere and Earth's surface and is driven by enzymes that require nitrogen, namely, ribulose-1,5-bisphosphate (RuBisCO). Thus, photosynthesis is a key link between the terrestrial carbon and nitrogen cycle, and the representation of this link is critical for coupled carbon-nitrogen land surface models. Models and observations suggest that soil nitrogen availability can limit plant productivity increases under elevated CO2. Plants acclimate to elevated CO2 by downregulating RuBisCO and thus nitrogen in leaves, but this acclimation response is not currently included in land surface models. Acclimation of photosynthesis to CO2 can be simulated by the photosynthetic optimality theory in a way that matches observations. Here, we incorporated this theory into the land surface component of the Energy Exascale Earth System Model (ELM). We simulated land surface carbon and nitrogen processes under future elevated CO2 conditions to 2100 using the RCP8.5 high emission scenario. Our simulations showed that when photosynthetic acclimation is considered, photosynthesis increases under future conditions, but maximum RuBisCO carboxylation and thus photosynthetic nitrogen demand decline. We analyzed two simulations that differed as to whether the saved nitrogen could be used in other parts of the plant. The allocation of saved leaf nitrogen to other parts of the plant led to (1) a direct alleviation of plant nitrogen limitation through reduced leaf nitrogen requirements and (2) an indirect reduction in plant nitrogen limitation through an enhancement of root growth that led to increased plant nitrogen uptake. As a result, reallocation of saved leaf nitrogen increased ecosystem carbon stocks by 50.3% in 2100 as compared to a simulation without reallocation of saved leaf nitrogen. These results suggest that land surface models may overestimate future ecosystem nitrogen limitation if they do not incorporate leaf nitrogen savings resulting from photosynthetic acclimation to elevated CO2.

Root-Driven Soil Reduction in Wadden Sea Salt Marshes

The soil redox potential in wetlands such as peatlands or salt marshes exerts a strong control over microbial decomposition processes and consequently soil carbon cycling. Wetland plants can influence redox by supplying both terminal electron acceptors (i.e. oxygen) and electron donors (i.e. organic matter) to the soil system. However, quantitative insight into the importance of plant effects on wetland soil redox and associated plant traits are scarce. In a combined mesocosm and field study we investigated the impact of plants on soil reduction using IRIS (Indicator of Reduction in Soils) sticks. Vegetated plots were compared to non-vegetated plots along an elevational gradient in a salt marsh of the Wadden Sea and along an artificially created gradient in a tidal tank mesocosm experiment. Our findings from the mesocosm experiment demonstrated that vegetation both enhanced and suppressed soil reduction relative to non-vegetated control pots. The direction of the plant effect (i.e., net oxidizing or net reducing) was inversely correlated with background redox conditions. Insights from high-resolution oxygen profiling via planar optode imaging corroborated these findings. In the field study, vegetation consistently reduced the comparatively well-aerated Wadden Sea salt marsh soil. Reduction correlated positively with soil organic matter content and belowground biomass, indicating that greater availability of plant-derived electron donors, in the form of organic matter, increased soil reduction. Challenging the dominant paradigm that wetland plants primarily act as soil oxidizers, our study reveals their potential to exert a net reducing effect. The documented impact of these plant-induced changes in soil redox conditions suggests a previously overlooked role in shaping the stability of soil organic carbon stocks in wetland ecosystems with variable water tables.

Carbon Stock Estimation of Poplar Plantations Based on Additive Biomass Models

Accurate estimation of biomass and carbon stocks in forest ecosystems is critical for understanding their roles in carbon sequestration and climate change mitigation. Currently, the development of stand biomass models and carbon stock estimation at the regional scale has emerged as a prominent research priority. In this study, 225 Populus spp. (poplar) trees in Shandong Province, China, were destructively sampled to obtain the biomass of their components. Two models (MS1 and MS2) were developed using allometric equations and the seemingly unrelated regression (SUR) method to ensure additive properties across tree components. The model evaluation employed the leave-one-out jackknife (LOO) method, considering statistics such as adjusted R-squared (Ra2), root mean square error (RMSE), mean absolute percent error (MAPE), and mean absolute error (MAE). The results from our models demonstrated high accuracy, with MS2 slightly outperforming MS1 after incorporating tree height as an independent variable. The models reliably estimated component-specific biomass and carbon stocks, with distinct variations observed in the carbon content among foliage (47.14 ± 2.07%), branches (47.26 ± 2.48%), stems (47.67 ± 2.21%), and roots (46.37 ± 2.78%). Carbon stocks in poplar plantations increased with the diameter class, ranging from 5 to 35 cm and correspondingly from 3.670 to 172.491 Mg C ha−1. As the diameter class increases, the carbon allocation strategy of poplars aligns with the CSR strategy, transitioning from prioritizing growth competition to emphasizing self-stabilization. Our research proposes a robust framework for assessing biomass and carbon stocks in poplar plantations, which is essential for evidence-based forest management strategies.

Multi-Scenario Simulation of Land Use and Assessment of Carbon Stocks in Terrestrial Ecosystems Based on SD-PLUS-InVEST Coupled Modeling in Nanjing City

In the context of achieving the goal of carbon neutrality, exploring the changes in land demand and ecological carbon stocks under future scenarios at the urban level is important for optimizing regional ecosystem services and developing a land-use structure consistent with sustainable development strategies. We propose a framework of a coupled system dynamics (SD) model, patch generation land-use simulation (PLUS) model, and integrated valuation of ecosystem services and trade-offs (InVEST) model to dynamically simulate the spatial and temporal changes of land use and land-cover change (LUCC) and ecosystem carbon stocks under the NDS (natural development scenario), EPS (ecological protection scenario), RES (rapid expansion scenario), and HDS (high-quality development scenario) in Nanjing from 2020 to 2040. From 2005 to 2020, the expansion rate of construction land in Nanjing reached 50.76%, a large amount of ecological land shifted to construction land, and the ecological carbon stock declined dramatically. Compared with 2020, the ecosystem carbon stocks of the EPS and HDS increased by 2.4 × 106 t and 1.5 × 106 t, respectively, with a sizable ecological effect. It has been calculated that forest and cultivated land are the two largest carbon pools in Nanjing, and the conservation of both is decisive for the future carbon stock. It is necessary to focus on enhancing the carbon stock of forest ecosystems while designating differentiated carbon sink enhancement plans based on the characteristics of other land types. Fully realizing the carbon sink potential of each ecological functional area will help Nanjing achieve its carbon neutrality goal. The results of the study not only reveal the challenges of ecological conservation in Nanjing but also provide useful guidance for enhancing the carbon stock of urban terrestrial ecosystems and formulating land-use planning in line with sustainable development strategies.

How does the value of ecological restoration techniques affect ecosystem carbon density: A resource endowment-based perspective

In the context of carbon neutrality and carbon peaks, innovations in ecological restoration technology play a key role in carbon adsorption and maintaining ecological balance. Regional governments, tasked with formulating differentiated and rational ecologically sustainable development plans and carbon-neutral strategies tailored to various resource endowment conditions, require timely identification of the mechanisms by which ecological restoration technologies affect the carbon density of ecosystems. Based on data from 31 provinces in China from 2006 to 2021, this study employed the Spatial Durbin Model with both time and space fixed effects to examine the impact of the value of ecological restoration technologies on ecosystem carbon density under varying resource endowments. The empirical results indicate that (1) the value of ecological restoration technology has a significantly positive effect on ecosystem carbon density, particularly in neighbouring areas; (2) energy resource endowment exhibits a significantly inverted U-shaped boundary effect, whereby regions with moderate energy endowment can optimise the positive impact of ecological restoration technology; (3) the heterogeneity analysis, based on levels of regional environmental governance and forest cover, shows that in regions with less investment in environmental infrastructure and lower forest cover, ecosystem carbon density is more sensitive to the value of ecological restoration techniques, making their carbon sink effect more pronounced. This study elucidates the key role of ecological restoration techniques in enhancing carbon storage, promoting the goal of carbon neutrality, and identifying optimal pathways for increasing ecosystem carbon stocks across various regions with differing resource endowments. Moreover, it provides a reference for accelerating the achievement of carbon neutrality targets.

Ecosystem Carbon Stock in Iron-Metamorphic Soils with Different Types of Land Use in South Karelia

Ecosystem Carbon Stock in Iron-Metamorphic Soils with Different Types of Land Use in South Karelia

The Impact of Drought on Terrestrial Carbon in the West African Sahel: Implications for Natural Climate Solutions

AbstractTerrestrial ecosystems store more than twice the carbon of the atmosphere, and are critical to climate change mitigation efforts. This has led to a proliferation of land‐based carbon sequestration efforts, such as re/afforestation associated with the Great Green Wall in the West African Sahel (WAS GGW). However, we currently lack comprehensive assessments of the long‐term viability of these ecosystems' carbon storage in the context of increasingly severe climate extremes. The WAS is particularly prone to recurrent and disruptive extremes, exemplified by the persistent and severe late‐20th century drought. We assessed the response and recovery of WAS GGW carbon stocks and fluxes to this late‐20th century drought, and the subsequent rainfall recovery, by leveraging a suite of terrestrial ecosystem models. While multi‐model mean carbon fluxes (e.g., gross primary production, respiration) partly recovered to pre‐drought levels, modeled total (above and below ground) ecosystem carbon stock falls to as much as two standard deviations below pre‐drought levels and does not recover even ∼20 years after the maximum drought anomaly. Furthermore, to the extent that the modeled regional carbon stock recovers, it is nearly entirely driven by atmospheric CO2 trends rather than the precipitation recovery. Uncertainties in regional ecosystem carbon simulation are high, as the models' carbon responses to drought displayed a nearly 10‐standard deviation spread. Nevertheless, the multi‐model average response highlights the strong and persistent impact of drought on terrestrial carbon storage, and the potential risks of relying on terrestrial ecosystems as a “natural climate solution” for climate change mitigation.

Relationship between seagrass community structure and carbon stocks on the coasts of Karimunjawa Marine National Park, Indonesia

The seagrass ecosystem is considered one of the most effective coastal ecosystems in storing carbon. Carbon stock estimation for a certain ecosystem is highly affected by factors such as species diversity and habitat type. This study aims to investigate the relationship between plant community structure and carbon stocks in the seagrass ecosystem using a case study of six coastal sites in Karimunjawa Marine National Park, Indonesia. In this region, eight seagrass species were recorded, i.e., Enhalus acoroides, Thalassia hemprichii, Cymodocea rotundata, Halodule pinifolia, Halophila ovalis, Halophila minor, Syringodium isoetifolium, and Oceana serrulata. From the six study sites, the highest estimated carbon stock was 426.2 Mg C ha−1 (Site 5; Telaga, dominated by E. acoroides). Meanwhile, the lowest estimated carbon stock was 127.4 Mg C ha−1 (Site 4; Koin, dominated by T. hemprichii). The density of E. acoroides was positively correlated with the total seagrass biomass carbon stocks (r = 0.97; p < 0.01), while its dominance was positively correlated with sediment carbon stocks (r = 0.92; p < 0.05) and total seagrass ecosystem carbon stocks (r = 0.92; p < 0.05). Seagrass ecosystems with different community structures showed different carbon storage capacities. Seagrass ecosystems dominated by large-sized species such as E. acoroides showed higher estimated carbon stocks thus suggesting the importance of considering the variability of community structure in managing seagrass ecosystems for carbon sequestration and storage.

Impact of Land Use and Land Cover (LULC) Changes on Carbon Stocks and Economic Implications in Calabria Using Google Earth Engine (GEE).

Terrestrial ecosystems play a crucial role in global carbon cycling by sequestering carbon from the atmosphere and storing it primarily in living biomass and soil. Monitoring terrestrial carbon stocks is essential for understanding the impacts of changes in land use on carbon sequestration. This study investigates the potential of remote sensing techniques and the Google Earth Engine to map and monitor changes in the forests of Calabria (Italy) over the past two decades. Using satellite-sourced Corine land cover datasets and the InVEST model, changes in Land Use Land Cover (LULC), and carbon concentrations are analyzed, providing insights into the carbon dynamics of the region. Furthermore, cellular automata and Markov chain techniques are used to simulate the future spatial and temporal dynamics of LULC. The results reveal notable fluctuations in LULC; specifically, settlement and bare land have expanded at the expense of forested and grassland areas. These land use and land cover changes significantly declined the overall carbon stocks in Calabria between 2000 and 2024, resulting in notable economic impacts. The region experienced periods of both decline and growth in carbon concentration, with overall losses resulting in economic impacts up to EUR 357.57 million and carbon losses equivalent to 6,558,069.68 Mg of CO 2 emissions during periods of decline. Conversely, during periods of carbon gain, the economic benefit reached EUR 41.26 million, with sequestered carbon equivalent to 756,919.47 Mg of CO 2 emissions. This research aims to highlight the critical role of satellite data in enhancing our understanding and development of comprehensive strategies for managing carbon stocks in terrestrial ecosystems.

Perennial species diversity, ecosystem carbon stocks and carbon income in coffee-based agroforestry systems along an elevation gradient in South-eastern Ethiopia

In the current context of deforestation, coffee-based agroforestry system (CAFS) is credited for climate change (CC) mitigation and biodiversity conservation while supporting local livelihoods. Despite integrating shade tree species in CAFS, empirical studies to support this assertion are inadequate in Eastern Africa, and hence, its ecosystem services provisions are less understood. We evaluated perennial species diversity, carbon (C) stocks in the biomass and soil organic C (SOC) along an elevation gradient of 72 plots of shade coffee, while 36 plots were selected for without-shade coffee systems within three elevations, namely, low (1600–1750 masl), mid (1750–1850 masl) and high (1850–2000 masl) elevations in Southeastern Ethiopia. The perennial species diversity and biomass, SOC, fine root and litter C stocks were evaluated. Perennial species Shannon diversity significantly differed among the studied elevations (p < 0.001). Shaded coffee had significantly higher ecosystem C stocks than without shaded coffee systems (p < 0.05). The highest C stocks were found in the soil in both coffee systems. However, we found a weak relationship between the Shannon diversity and biomass C. The C income in shaded coffee was 70 % higher than without shaded coffee systems. The present study showed that shaded coffee accumulates more C and provides additional benefits from C credits. Hence, CAFS deliver ecosystem services that enhance biodiversity conservation and CC mitigation while generating an additional C income for farmers. However, we learned that the impact of perennial plant diversity on C stock and C income is context and site-specific.

Predictions of Carbon Stock in the Southern Moscow Region Forests Under Different Forest Use Scenarios

The results of forest simulation modelling of the dynamics of carbon pools and fluxes in forest ecosystems under different forest management scenarios were considered on the example of the Dankovsky forest enterprise (south of the Moscow region, subzone of coniferous-broadleaved mixed forests). The impact of such changes in forest management practices, as the reserve regime, the reduction in the proportion of forest lands as a result of residential development, and zoning of the territory with an emphasis on increasing the recreational use of forests on the carbon balance was analysed. In computational experiments, a set of Russian models was used: the dynamic model of a forest stand FORRUS-S, the model of soil organic matter dynamics Romul_Hum, the model of the hydrothermal regime of soils SCLISS. Calculations were performed for a time period of 100 years at the forestry unit level, and were also aggregated at the level of the entire forestry district. The diversity of types of forest growth conditions (FGC), together with the species diversity and the initial different ages of stands, determined significant variations of the calculated indicators of forest stands’ production, the quantity and quality of plant litter entering the soil. For all cases, model estimates of changes in carbon reserves occurred in the forest stands within the initial 40–60 years with a subsequent decrease in the calculated values. Under the conservation scenario, an increase in the organic substances reserves in forest litter and soil was observed: for FGCs C2 and C3, an increase over 100 years was approximately 5–10 kg m–2, for the remaining FGCs — at the level of 2–3 kg m–2 in terms of carbon. Under the economic use scenarios, a relative “levelling” of forest enterprise area towards the lower end of the spectrum was shown in terms of soil carbon reserves. The maximum ecosystem carbon stock was calculated for FGC C2 and C3, the minimum — for A5 and C4. Depending on the scenario, over 100 years, the total net sequestration of carbon by the forests of the Dankovsky forest enterprise (with a total area of forested land of 6836 ha) was estimated within the range of 0.15–0.57 Tg.

Carbon stocks in mangrove ecosystems of Sri Lanka: Average contributions and determinants of sequestration potential

Mangroves are crucial in carbon sequestration despite covering only a small percentage of the Earth's surface. Latitudinal gradient primarily determines the distribution of climatic zones of distinct sunlight, temperature, and precipitation patterns, which influence the community structure of the mangrove ecosystem. The tropical climate of Sri Lanka contributes to the island's lush mangrove forests. The present study estimated that the average island's carbon sequestration capacity of Sri Lankan mangrove ecosystems is 524.25 t/ha representing a substantial volume of carbon storage that contributes to offset greenhouse effect due to increasing atmospheric CO2. Our results substantiated that rainfall positively influences total carbon sequestration capacity of mangrove ecosystems.It was also revealed that a positive relationship exists between vegetation structural complexity and sediment organic carbon, highlighting the influence of vegetation structure, that is primarily dependent on climatic conditions, on production of organic matter and sediment carbon sequestration. Globally, the carbon sink function of mangrove ecosystems is reported to be highest in the tropical areas and it declines towards sub-tropical higher latitudes while those in the southern hemisphere perform better carbon sinks than those in the northern hemisphere.The vertical distribution of total organic matter content in mangrove sediments was revealed to be in a descending order, manifesting the weak tidal removal of surface organic matter under the microtidal conditions in Sri Lankan marine waters, thus qualifying mangrove ecosystems in microtidal coasts as effective carbon sinks.

Interconnectivity can be as important as habitat type in explaining carbon stocks in the coastal lagoons of arid regions

Coastal blue carbon ecosystems, typically comprising interconnected habitat mosaics, are globally important pathways of carbon sequestration and play a significant role in climate change regulation and mitigation. Current coastal management strategies often rely on simplified regional carbon stock estimates, that overlook the geographical variability and intricate ecological dynamics within these ecosystems. This study adopts a seascape ecology approach to evaluate the role of multiple seascape characteristics on carbon storage in two arid region coastal lagoons. We show that seascape location is the most influential driver of carbon stocks. Additionally, carbon isotopic variability, a proxy for connectivity, can be as influential as habitat type, particularly in the UAQ lagoon. This challenges the conventional reliance on data from individual habitat types (e.g., seagrass, mangrove, or tidal marsh) and highlights the context-dependency of carbon stocks. Moreover, the specific characteristics driving carbon stocks vary between seascapes: in Khor Faridah, connectivity to seagrass and mangrove habitats is crucial, while in the UAQ lagoon, sheltered and elevated areas are more influential. Our findings suggest that the interconnectivity between different habitat types, such as mangroves and saltmarshes, significantly enhances carbon storage. This is especially pronounced in large, sheltered mangrove habitat types within upper intertidal zones. Notably, small patches of mangroves, up to 10 ha, are associated with an approximate 10 % increase in carbon stocks. These results underscore the need for a more holistic, context-specific approach to designing nature-based solutions for coastal management and ecosystem restoration. By considering the specific characteristics and connectivity of seascape mosaics, we can more effectively enhance carbon stock potential in coastal ecosystems. This study contributes to a deeper spatially explicit understanding of the complex factors influencing carbon stocks in blue carbon ecosystems, highlighting the importance of tailored management strategies that reflect the unique ecological patterns of each seascape.

Assessment of Soil Carbon Stock Potential in Different Soil Layers of Grassland Ecosystems

Mostly soil carbon stock research is done in areas with natural vegetation, ignoring university campuses. This study assesses soil carbon stocks in different soil layers of grassland ecosystems within the Bharathiar University campus in Tamil Nadu, India. Soil samples were collected from grasslands in four sections (namely, East section, West section, North section, and South section) of the campus and analyzed for carbon content across depths of 0-10cm, 10-20cm, and 20-30cm. Results indicate soil carbon stocks in grassland ecosystems ranging from 1.36% to 2.26%, with notable variations observed among campus sections and soil layers. One-way ANOVA revealed that there is a significant variation in soil carbon stock values among the four sections in the 20-30cm layer (F(3,16)=3.865, p&lt;0.05), but not for the 0-10cm layer (F(3,16)=1.454, p&gt;0.05) and the 10-20cm layer (F(3,16)=3.011, p&gt;0.05). Pearson’s Correlation analysis revealed that the soil carbon stock had no significant relationships with soil pH, Conductivity, and total dissolved solids at all four sections of the university campus, except for a positive correlation between soil carbon stock and total dissolved solids at the East section (r=0.563, p&lt;0.05), and between soil carbon stock and soil pH at the South section (r=0.550, p&lt;0.05). These findings underscore the complexity of soil carbon dynamics in grassland ecosystems of university campuses and emphasize the potential for localized assessments to inform sustainable land management strategies. This study contributes valuable insights into enhancing carbon sequestration efforts at the university campus, useful for global climate change mitigation. Integrating such localized findings into broader environmental policies can optimize carbon management strategies across similar ecosystems globally.

Spatial Pattern of Ecosystem Carbon Stocks in the Lhasa River Basin and Its Response Mechanism to Land Use Change

Spatial Pattern of Ecosystem Carbon Stocks in the Lhasa River Basin and Its Response Mechanism to Land Use Change

The relationship between habitat quality and the diversity of phytoplankton, zooplankton, and nekton in mangrove ecosystems of Bawean Island, Indonesia

Abstract. Retnaningdyah C, Arisoesilaningsih E, Vidayanti V, Salsabila Q, Purnomo P. 2024. The relationship between habitat quality and the diversity of phytoplankton, zooplankton, and nekton in mangrove ecosystems of Bawean Island, Indonesia. Biodiversitas 25: 3017-3026. Mangrove ecosystem consists of biotic and abiotic components that interact with each other to form a food chain. This study aims to analyze the relationship between the diversity and abundance of phytoplankton, zooplankton, and nekton and water quality, human activities, and carbon stock in the mangrove ecosystem in Bawean Island. Data was collected from 11 sampling locations across the island. At each location, we observed the diversity of phytoplankton, zooplankton, and nekton and carbon stock of mangroves along with data of water quality (salinity, pH, dissolved oxygen/DO, biochemical oxygen demand/BOD, nitrate, orthophosphate, dihydrogen sulfide/H2S, dissolved lead/Pb) and human activities based on the hemeroby index. The research results showed that the level of DO, H2S, nitrate, and orthophosphate did not meet the quality standard according to the Indonesian government. The level of disturbance from human activities varied from ?-mesoherobic to metahemerobic categories. Human activities and higher levels of H2S in waters had a negative relationship with mangrove ecosystem carbon stock and the diversity and taxa richness of phytoplankton, zooplankton, and nekton. Phytoplankton diversity had a positive relationship with zooplankton, while zooplankton diversity had a positive relationship with nekton. High carbon stock in the mangrove ecosystem will likely increase the diversity of phytoplankton, zooplankton, and nekton. The result of this study implies that anthropogenic activities need to be controlled to improve the Bawean Island mangrove ecosystem services.

Estimating aboveground biomass dynamics of wheat at small spatial scale by integrating crop growth and radiative transfer models with satellite remote sensing data

Aboveground biomass (AGB) of plants is an agroecological indicator that can be used to monitor crop growth status and quantify biomass carbon stock in agricultural ecosystems. Although satellite remote sensing data and crop models are widely employed to estimate AGB dynamics, their application in small-scale research plots is often constrained by the unavailability of freely and timely high-resolution satellite imageries and the challenge of acquiring reliable model inputs like initial soil water and nitrogen content. This study integrated a crop growth model (APSIM-Wheat) and radiative transfer model (PROSAIL) to estimate AGB dynamics at a small plot scale (ca. 5 to 20 m2) within variety trials (ca. 1 to 2 ha) by assimilating trial-level remote sensing data into the hybrid APSIM-PROSAIL model. The APSIM-PROSAIL integration, developed by deriving PROSAIL input parameters from APSIM-Wheat output variables, was verified by evaluating its capacity to reproduce trial-level Sentinel-2 (S2) NDVI dynamics across 30 variety trials in 2020. The comparison of the simulated and observed trial-level S2 NDVI dynamics yielded an overall RRMSE of 18.2% (n = 646 observations), suggesting the potential of using observed S2 NDVI dynamics to constrain APSIM-PROSAIL and estimate environment variables in cropping systems. This constraint was subsequently assessed in 28 variety trials in 2021, where APSIM-PROSAIL inversely estimated unknown trial-specific variables including initial soil water and nitrogen content across the trials. Using the estimated initial soil status and the plot information including genotypes and management as sown, we demonstrated that this method could also facilitate accurate retrievals of plot-level AGB dynamics with an overall RRMSE of 20.9% (n = 976 measurements). The proposed APSIM-PROSAIL demonstrated the capability to accurately retrieve plot-level AGB dynamics and reproduce trial-level S2 NDVI dynamics across a broad and diverse range of variety trials in the Australian Wheatbelt, indicating its potential utility to facilitate biomass carbon stock assessment. It holds the potential as a tool to explore the relationships between canopy spectral information and crop traits in response to genotype-environment-management interactions in agricultural ecosystems. The method enables the examinations of within-field variabilities for crop traits through retrieving them at small spatial scales from coarse remote sensing data.

Anthropogenic and climate impacts on carbon stocks of grassland ecosystems in Inner Mongolia and adjacent region

Up to date, most studies reported that degradation is worsened in the grassland ecosystems of Inner Mongolia and adjacent regions as a result of intensified grazing. This seems to be scientific when considering the total forage or total above-ground biomass as a degradation indicator, but it does not hold true in terms of soil organic carbon density (SOCD). In this study, we quantified the changes of grassland ecosystem carbon stock in Inner Mongolia and adjacent regions from the 1980s to 2000s and identified the major drivers influencing these variations, using the National Grassland Resource Inventory and Soil Survey Dataset in 1980s and the Inventory data during 2002 to 2009 covering 624 sampling plots concerned vegetal traits and edaphic properties across the study region. The result indicated that the above-, below-ground and total vegetation biomass declined from the 1980s to 2000s by ∼ 10 %. However, total forage production increased by 6.72 % when considering livestock intake. SOCD remained stable despite a 67 % increase in grazing intensity. A generalized linear model (GLIM) analysis suggested that an increase in grazing intensity from the 1980s to 2000s could only explain 1.04 % of the total biomass change, while changes in precipitation and temperature explained 17.7 % (p < 0.05) of total vegetation biomass (TVB) change. Meanwhile, SOCD change during 1980s - 2000s could be explained 10.08 % by the soil texture (p < 0.05) and <1.6 % by changes in climate and livestock. This implies that the impacts of climate change on grassland biomass are more significant than those of grazing utilization, and SOCD was resistant to both climate change and intensified grazing. Overall, intensified grazing did not result in significant negative impacts on the grassland carbon stocks in the study region during the 1980s and 2000s. The grassland ecosystems possess a mechanism to adjust their root-shoot ratio, enabling them to maintain resilience against grazing utilization.