Primary Production Research Articles

Spatiotemporal Dynamics of Vegetation Net Primary Productivity (NPP) and Multiscale Responses of Driving Factors in the Yangtze River Delta Urban Agglomeration

Against the backdrop of global climate change and rapid urbanization, understanding the spatiotemporal dynamics and driving mechanisms of vegetation net primary productivity (NPP) is critical for ensuring regional ecological security and achieving carbon neutrality goals. This study focuses on the Yangtze River Delta Urban Agglomeration (YRDUA) and integrates multi-source remote sensing data with socioeconomic statistics. By combining interpretable machine learning (XGBoost-SHAP) with multiscale geographically weighted regression (MGWR), and incorporating Theil–Sen trend analysis and Mann–Kendall significance testing, we systematically analyze the spatiotemporal variations in NPP and its multiscale driving mechanisms from 2001 to 2020. The results reveal the following: (1) Total NPP in the YRDUA shows an increasing trend, with approximately 24.83% of the region experiencing a significant rise and only 2.75% showing a significant decline, indicating continuous improvement in regional ecological conditions. (2) Land use change resulted in a net NPP loss of 2.67 TgC, yet ecological restoration and advances in agricultural technology effectively mitigated negative impacts and became the main contributors to NPP growth. (3) The results from XGBoost and MGWR are complementary, highlighting the scale-dependent effects of driving factors—at the regional scale, natural factors such as elevation (DEM), precipitation (PRE), and vegetation cover (VFC) have positive impacts on NPP, while the human footprint (HF) generally exerts a negative effect. However, in certain areas, a dose–response effect is observed, in which moderate human intervention can enhance ecological functions. (4) The spatial heterogeneity of NPP is mainly driven by nonlinear interactions between natural and anthropogenic factors. Notably, the interaction between DEM and climatic variables exhibits threshold responses and a “spatial gradient–factor interaction” mechanism, where the same driver may have opposite effects under different geomorphic conditions. Therefore, a well-balanced combination of land use transformation and ecological conservation policies is crucial for enhancing regional ecological functions and NPP. These findings provide scientific support for ecological management and the formulation of sustainable development strategies in urban agglomerations.

Growth, Productivity, and Size Structure of Spirulina Strain Under Different Salinity Levels: Implications for Cultivation Optimization

Salinity serves as a critical environmental factor influencing the physiological and morphological characteristics of Spirulina, a filamentous cyanobacterium used for food production and commercial purposes. This study examined a Spirulina strain’s responses to different salinity levels (10–45 ppt) through three independent laboratory experiments that determined growth, productivity, and size structure. Growth across salinity treatments was assessed by monitoring optical density in 24-well microplates over 20 days and estimating specific growth rates using a logistic growth model. Primary productivity under different salinity and light conditions was measured using light and dark bottle experiments to calculate gross primary productivity (GPP) and to estimate photosynthetic efficiency through linear regression of GPP against light intensity. The size structure was assessed through tube-based experiments and image analysis, with organism sizes categorized and analyzed to identify salinity-induced patterns in filament structure. The study demonstrated that the Spirulina strain achieved its greatest growth at 10 ppt yet produced the highest photosynthetic efficiency between 27 and 45 ppt because it reallocated energy during salinity stress. The morphological analysis revealed that the Spirulina strain produced medium-sized filaments between 400 and 799 µm at elevated salinity levels, and our analysis confirmed substantial variations in size structure. The Spirulina strain demonstrates both physiological and morphological plasticity when exposed to salinity changes. The cultivation of the Spirulina strain at 27 ppt provides conditions that support moderate growth, enhanced productivity, and manageable morphological shifts while using its natural salinity tolerance to improve the efficiency and scalability of production for diverse biotechnological applications.

Quantifying Ecological Dynamics and Anthropogenic Dominance in Drylands: A Hybrid Modeling Framework Integrating MRSEI and SHAP-Based Explainable Machine Learning in Northwest China

Arid and semi-arid regions serve as crucial ecological barriers in China, making the spatiotemporal evolution of their ecological environmental quality (EEQ) scientifically significant. This study developed a Modified Remote Sensing Ecological Index (MRSEI) by innovatively integrating the Comprehensive Salinity Indicator (CSI) into the Remote Sensing Ecological Index (RSEI) and applied it to systematically evaluate the spatiotemporal evolution of EEQ (2014–2023) in Yinchuan City, a typical arid region of northwest China along the upper Yellow River. The study revealed the spatiotemporal evolution patterns through the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test, and adopted the Light Gradient Boosting Machine (LightGBM) combined with the Shapley Additive Explanation (SHAP) to quantify the contributions of ten natural and anthropogenic driving factors. The results suggest that (1) the MRSEI outperformed the RSEI, showing 0.41% higher entropy and 5.63% greater contrast, better characterizing the arid region’s heterogeneity. (2) The EEQ showed marked spatial heterogeneity. High-quality areas are concentrated in the Helan Mountains and the integrated urban/rural development demonstration zone, while the core functional zone of the provincial capital, the Helan Mountains ecological corridor, and the eastern eco-economic pilot zone showed lower EEQ. (3) A total of 87.92% of the area (7609.23 km2) remained stable with no significant changes. Notably, degraded areas (934.52 km2, 10.80%) exceeded improved zones (111.04 km2, 1.28%), demonstrating an overall ecological deterioration trend. (4) This study applied LightGBM with SHAP to analyze the driving factors of EEQ. The results demonstrated that Land Use/Land Cover (LULC) was the predominant driver, contributing 41.52%, followed by the Digital Elevation Model (DEM, 18.26%) and Net Primary Productivity (NPP, 12.63%). This study offers a novel framework for arid ecological monitoring, supporting evidence-based conservation and sustainable development in the Yellow River Basin.

Запасы фитомассы подлесочных пород и их прирост в лесостепных экосистемах Окско-Донской равнины

Introduction. The study of stocks and annual dynamics of phytomass of undergrowth species in forest ecosys-tems of the Oksko-Donskaya Plain is important for understanding the contribution of different tier forest components to the carbon cycle, especially under changing climate conditions. Aim of the study is to estimate phytomass stocks of undergrowth species and their annual growth in different types of forest ecosystems of the specified region, as well as to determine their role in carbon accumulation and dy-namics. Materials and Methods. The studies were conducted on permanent sample plots in two types of forest ecosys-tems of the Voronezh Region: (1) pure pine stands of the Levoberezhnoye forest division and (2) mixed deciduous stands of pedunculate oak (Quercus robur) with admixture of small-leaved lime (Tilia cordata), sharp-leaved maple (Acer platanoides) and common ash (Fraxinus excelsior) (Pravoberezhnoye forest division). For each undergrowth spe-cies, species affiliation, condition category, understorey structure, height, width, projective cover values and other den-drometric parameters were determined. Carbon stocks in phytomass were calculated using taxation methods. Annual net primary production (NPP) was determined by the dynamics of aboveground biomass stocks. Results. It was found that undergrowth makes a significant contribution to the formation of biomass stocks and carbon storage in forest ecosystems of the region. The highest values of annual phytomass growth were recorded in old-growth oak stands under fresh oak forest conditions, which is associated with increased productivity under the in-fluence of a rich layer of forest litter and humus. In pine stands, lower growth and less complex undergrowth structure are observed. Conclusion. The data expand the ideas about the structural and functional organisation of undergrowth in dif-ferent types of forest-steppe ecosystems and its role in the biogeochemical carbon cycle. The results can be used to improve carbon monitoring systems and adaptive forest management planning with climate targets in mind.

The Performance of the Supply Chain of Arabica Coffee Processing Business (Case Study: Kintamani Arabica Coffee Processing Business, Bangli Regency, Bali Province)

Arabica Coffee is one of Bali's primary products in trade activities, both foreign and domestic. The rise of the downstream coffee industry has resulted in an increasing demand for Arabica coffee. Balinese Arabica coffee processing businesses are required to be able to compete by strengthening their supply chains. Changes in the very dynamic business situation require coffee processing businesses to be able to adapt and take adjustment steps. For this reason, evaluations related to supply chain performance must be carried out consistently. This study aims to evaluate the performance of the Kintamani Bali Arabica coffee supply chain. The research approach utilised a quantitative survey method. The research informants used were 55 people, consisting of farmers, agricultural extension workers, coffee processing businesses, coffee shops, and academics. The data was analysed using the SCOR (Supply Chain Operation References) approach and the Analytical Hierarchy Process (AHP) method. The results of this study obtained as many as 49 validated key performance indicators. The results of the measurement of the performance of the Kintamani Bali Arabica Coffee processing business supply chain showed a result of 84.97%, with a good category. It is hoped that the coffee processing business will be able to improve the performance of the supply chain in the plan process, through improving the information system by continuously recording, and deploying workforces that have expertise in business information documentation activities.

Resource Recovery from Green Tide Biomass: Sustainable Cascading Biorefinery Strategies for Ulva spp.

This review examines sustainable cascading biorefinery strategies for the green alga Ulva, which is globally prevalent in eutrophic marine waters and often forms extensive “green tides.” These blooms cause substantial environmental and economic damage to coastal communities. The primary target products within an Ulva biorefinery typically encompass salts, lipids, proteins, cellulose, and ulvan. Each of these components possesses unique properties and diverse applications, contributing to the economic robustness of the biorefinery. Salts can be repurposed for agricultural or even human consumption. Lipids offer high-value applications in nutraceuticals and animal feed. Proteins present significant potential as plant-based nutritional supplements. Cellulose can be transformed into various advanced materials. Finally, ulvan, a polyanionic oligosaccharide unique to Ulva, holds promise due to its distinct properties, particularly in the biomedical field. Furthermore, state-of-the-art chemical modifications of ulvan are presented with the aim of tailoring its properties and broadening its potential applications. Future research should prioritize optimizing these integrated extraction and fractionation processes. Furthermore, a multi-product biorefining approach, integrated with robust Life Cycle Assessment studies, is vital for transforming this environmental challenge into a significant opportunity for sustainable resource valorization and economic growth.

A Review of the Progress in Molecular Dynamics Simulation of Calcium Aluminosilicate Hydrate: From Structure and Properties to Applications

Recyclable aluminum-containing industrial solid waste can be used as supplementary cementitious materials (SCMs) to replace cement (30–50%), thereby reducing CO2 emissions during cement production and improving the mechanical properties and durability of concrete. Therefore, the use of SCMs in building materials presents significant potential. Due to the presence of the aluminum phase in the SCMs, the hydration products of cements blended with SCMs are changed. Compared to the primary hydration product of conventional cement, calcium silicate hydrate (CSH), the main hydration product of cement blended with SCMs is calcium aluminosilicate hydrate (CASH), which exhibits a more complex molecular structure. Understanding the role of Al in C-A-S-H at the atomic scale facilitates mechanistic insights and promotes the sustainable utilization of SCMs in eco-friendly construction. Molecular dynamics enables the rapid and accurate structural analysis and property prediction of materials. Therefore, this paper presents a systematic review of molecular dynamics simulations of CASH and discusses the role of Al in the molecular structure, dynamic, and mechanical behavior of CASH. It also analyzes the interfacial properties of CASH composites, the immobilization and transport of ions in CASH, and the temperature effect on the structure and properties of CASH. Finally, the challenges and perspectives for molecular dynamics simulation of CASH are presented.

Resilience and exploitation of mussels: the convergence of history and biology leads to overexploitation of a key marine natural resource.

History, geography and biology have converged to establish two west-east gradients along the southern coast of South Africa, one biological, one human. Historically, the Nguni- speaking peoples of the country spread from east to west along the coast, with the later European settlers moving west to east. The two peoples met in the vicinity of the Great Fish river. Under apartheid, two ‘homelands’, Ciskei and Transkei, were established leading to starkly different contemporary patterns of settlement and economic development. Poverty and reliance on marine natural resources, particularly mussels, are markedly higher in these former homelands. Mussel recruitment diminishes from west to east in South Africa, and the coastline of these former homelands, dominated by the oligotrophic Agulhas Current, exhibits low primary productivity and particularly low recruitment. The result is a west-east gradient of greater poverty and dependence on marine natural resources mirrored by decreased recruitment and biological resilience of mussel populations. Similarly, mussel recruitment and growth are greater on inaccessible wave-exposed shores and towards the low shore where exploitation is more difficult. The mismatch across large and small scales between where marine resources are most able to sustain exploitation and where exploitation is most intense leads to serious environmental degradation.

Nonlinear variations and drivers of vegetation NPP on the Tibetan Plateau: Interaction of natural and human factors.

Understanding the drivers of changes in vegetation net primary productivity (NPP) is critical for comprehending ecosystem dynamics and their ability to respond to environmental shifts. However, the complexity and nonlinear variations of NPP across the Tibetan Plateau, along with spatial and temporal inconsistencies, present significant analytical challenges. This study leverages the Google Earth Engine (GEE) platform and applies non-parametric trend analysis methods, such as the Sen slope estimator, Mann-Kendall test, coefficient of variation, and Hurst exponent, to investigate NPP trends from 2001 to 2021. The Optimal Parameters-based Geographical Detector (OPGD) model was employed to assess the combined effects of natural factors and human activities on NPP's spatial distribution and variability, identifying key drivers and their optimal ranges for promoting NPP growth. Results revealed nonlinear fluctuations in NPP during the study period, ranging from 184.06 to 208.53 gC m-2.a-1, with an average annual growth rate of 1.16 gC m-2.a-1. Significant spatial differences were observed, with higher NPP in the grasslands and forests of the southeast, while lower productivity was found in the alpine deserts of the northwest. Over 55% of the study area showed an increasing trend in NPP, with 28.14% experiencing significant growth (p < 0.05). The study further indicated that natural factors such as elevation, solar radiation, and mean annual temperature were major determinants of NPP fluctuations, while human activities (e.g., distance, population density, and land use) also played a crucial role in shaping NPP patterns. The significant interaction between natural factors and human activities demonstrates synergistic enhancement and non-linear effects, highlighting the complexity of multi-factor drivers influencing NPP changes. The key promoting factors and their optimal ranges identified provide a foundation for understanding the impact of natural and human activities on NPP variation, offering scientific support for ecosystem management and sustainable development on the Tibetan Plateau.

Relationships among multiple ecosystem services in mountainous regions: A case study of the Gaoligong Mountains.

Relationships among multiple ecosystem services in mountainous regions: A case study of the Gaoligong Mountains.

Resilience response of China's terrestrial ecosystem gross primary productivity under environmental stress.

Resilience response of China's terrestrial ecosystem gross primary productivity under environmental stress.

Automated machine learning integrating multi-source satellite observations to predict gross and net CO2 fluxes of coastal wetlands in China

Abstract Coastal wetlands are increasingly vital carbon sinks, helping mitigate atmospheric CO2 and slow global warming. However, we have limited knowledge about the carbon sink capacity of coastal wetlands, whereby developing advanced skills for predicting CO2 fluxes of coastal wetlands is critical. Here, by employing recent cutting-edge achievements in artificial intelligence, we evaluated three automated machine learning (AutoML) platforms, including Lazy Predict, H2O AutoML and FLAML, for predicting gross primary production (GPP), ecosystem respiration (RE), and net ecosystem exchange (NEE) in China’s of mangrove and saltmarsh coastal wetlands with multi-source satellite observations. Our results indicate that these AutoML platforms effectively predicted GPP, RE and NEE, with superior performance for GPP and RE compared to NEE. For individual predictions across 14 sites, the testing set yielded average determination coefficient (R2) values of 0.74, 0.79, and 0.63, and root mean square error (RMSE) values of 0.83, 0.45, and 0.76 gC m-2 s-1 for GPP, RE, and NEE respectively. Cross-site predictions performed better for saltmarsh (average R2 : 0.86, 0.84, and 0.76 for GPP, RE, and NEE) than mangrove ecosystems (average R2 : 0.72, 0.76, and 0.59). In addition, ensemble ML models, particularly on the Lazy Predict platform, significantly outperformed individual models. Feature important analyses revealed that vegetation variables (LAI and FAPAR) play pronouncedly important roles in mangrove ecosystems, followed by climate variables (air temperature and precipitation) with considerably important roles, while air temperature dominated in saltmarsh ecosystems, with vegetation variables but playing a lesser role. Our study offers valuable insights for utilizing AutoML techniques to enhance CO2 flux predictions and regional budget estimations for coastal wetlands, potentially advancing strategies for monitoring large-scale coastal “blue carbon” dynamics.

Impact pathways of wind farms on grassland carbon and water cycles.

Impact pathways of wind farms on grassland carbon and water cycles.

Assessing ozone pollution and climate change impacts on winter wheat: flux modeling vs. dose-response modeling.

Assessing ozone pollution and climate change impacts on winter wheat: flux modeling vs. dose-response modeling.

Multiscale spatio-temporal variability of suspended sediment front in the Yangtze River Estuary and its ecological effects.

Multiscale spatio-temporal variability of suspended sediment front in the Yangtze River Estuary and its ecological effects.

Fish sing louder in conjunction with a wind-forced coastal upwelling system off south-east Australia.

Fish sing louder in conjunction with a wind-forced coastal upwelling system off south-east Australia.

Navigating stress: Impacts of temperature, polycyclic aromatic hydrocarbons, and heavy metals on the diatom Thalassiosira weissflogii adapted to tropical waters of the Gulf of Guinea.

Navigating stress: Impacts of temperature, polycyclic aromatic hydrocarbons, and heavy metals on the diatom Thalassiosira weissflogii adapted to tropical waters of the Gulf of Guinea.

Paleoredox, iron cycling, and primary productivity in the late Devonian of southern Laurussia (Woodford Shale, Oklahoma, USA)

Paleoredox, iron cycling, and primary productivity in the late Devonian of southern Laurussia (Woodford Shale, Oklahoma, USA)

Capturing constraints on boreal gross primary productivity using the remote sensing-based CAN-TG model.

Capturing constraints on boreal gross primary productivity using the remote sensing-based CAN-TG model.

Unravelling the eco-monitoring potential of phytoplankton towards a sustainable aquatic ecosystem.

Unravelling the eco-monitoring potential of phytoplankton towards a sustainable aquatic ecosystem.