Sustainable Ecosystem Research Articles

Desertification indirectly affects soil fauna by reducing complexity of soil habitats and diversity of energy sources

Soil fauna is closely linked to ecological functions such as biogeochemical cycling, soil structure, ecosystem sustainability and trophic interactions. However, little consideration has been given to how desertification influences the abundance and diversity of soil fauna in arid areas. In this study, soil fauna was sampled in four desert habitats (gravel, sand, salt and mud desert) in northwest China. At the same time, the plant traits, geographic location and soil properties were investigated. We also measured contribution of environmental factors explained faunal community diversity and abundance, and by what pathways desertification controls soil fauna. The results showed that total abundance and diversity of soil fauna in the mud desert were significantly (P < 0.05) higher than salt, sand and gravel deserts. Soil fauna diversity, composition and community were more sensitive to desertification-induced changes in soil properties than to changes in plant traits and geographic locations (changes in soil properties explained 68.9 % and 73.7 % of the variation in diversity and abundance of soil fauna community, respectively). Among them, the available phosphorus, volumetric water content had a significant positive effect on community diversity and abundance, while pH had a significant negative effect (P < 0.01). The results of piecewise structural equation modeling imply that desertification may have mainly indirect impacts on soil fauna community, and that direct effects are almost zero. In summary, regardless of the type of desertification, it will affect the material cycle, energy flow and information transfer of ecosystems by destroying the soil habitats and vegetation conditions, and will affect the structure and diversity of soil fauna from the bottom up.

Altitude-Dependent Morphophysiological, Anatomical, and Metabolomic Adaptations in Rhodiola linearifolia Boriss.

Rhodiola linearifolia Boriss., a perennial alpine plant from the Crassulaceae family, is renowned for its unique medicinal properties. However, existing research on this species is limited, particularly regarding the impact of altitude on its physiological and medicinal compounds. The current study employed morphophysiological and anatomical methods to explore the adaptive mechanisms of R. linearifolia across different altitudinal gradients, while also examining photosynthetic pigments and metabolomic changes. Our results indicate that despite the simultaneous effects of various mountain abiotic factors, significant correlations can be identified between altitude and trait variation. An optimal growth altitude of 2687 m above sea level was identified, which is pivotal for sustainable ecosystem management and potential species introduction strategies. It is noted that increasing altitude stress enhances the synthesis of secondary antioxidant metabolites in R. linearifolia, enhancing its pharmaceutical potential.

Community organization and network complexity and stability: contrasting strategies of prokaryotic versus eukaryotic microbiomes in the Bohai Sea and Yellow Sea.

Unraveling the effects of spatial gradients on microbiome assembly and association is a challenging topic that remains understudied in the coastal ecosystem. Here, we aimed to investigate the effects of spatial variation on the network complexity and stability of plankton microbiomes in the Bohai Sea and Yellow Sea. These seas serve as spawning and nursery grounds for economically important fisheries valued at billions of dollars annually. Environmental heterogeneity structures microbial communities into distinct spatial patterns, leading to complex direct/indirect relationships and broader ecological niches of bacterioplankton compared to microeukaryotic communities. Interestingly, salinity gradients positively influenced the richness of rare subgroups of bacterioplankton, while the rare microeukaryotic subgroups showed an opposite trend. Abundant subgroups of prokaryotic/eukaryotic microbiomes exhibited greater environmental niche breadth and lower phylogenetic distance compared to the rare subgroups. Stochastic processes contributed greatly to microbiome dynamics, and deterministic processes governed the bacterioplankton organization with a lower phylogenetic turnover rate. Compared to microeukaryotes, bacterioplankton exhibit higher network modularity, complexity, and robustness and lower fragmentation, and vulnerability. These observations offer vital insights into the anti-interference ability and resistance of plankton microbiomes in response to environmental gradients in terms of organization and survival strategy as well as their adaptability to environmental disturbances.IMPORTANCEAn in-depth understanding of community organization and stability of coastal microbiomes is crucial to determining the sustainability of marine ecosystems, such as the Bohai Sea and Yellow Sea. Distinct responses between prokaryotic and eukaryotic microbiomes to spatial heterogeneity were observed in terms of geographical distribution, phylogenetic distance, niche breadth, and community assembly process. Environmental variations are significantly correlated with the dynamics of rare eukaryotic plankton subcommunities compared to prokaryotic plankton subcommunities. Deterministic processes shaped prokaryotic plankton community organization with a lower phylogenic turnover rate. Rare subgroups had noticeably higher phylogenetic distance and lower niche breadth than the corresponding abundant subgroups. Prokaryotic microbiomes had higher molecular network complexity and stability compared to microeukaryotes. Results presented here show how environmental gradients alter both the geographical characteristics of the microbial organization in coastal seas and also their co-occurrence network complexity and stability and thus have critical implications for nutrient and energy cycling.

Electric Vehicle Integration in Coupled Power Distribution and Transportation Networks: A Review

Integrating electric vehicles (EVs) into the coupled power distribution network (PDN) and transportation network (TN) presents substantial challenges. This paper explores three key areas in EV integration: charging/discharging scheduling, charging navigation, and charging station planning. First, the paper discusses the features and importance of EV integrated traffic–power networks. Then, it examines key factors influencing EV strategy, such as user behavior, charging preferences, and battery performance. Next, the study establishes an EV charging and discharging model, with particular emphasis on the complexities introduced by factors such as pricing mechanisms and integration approaches. Furthermore, the charging navigation model and the role of real-time traffic information are discussed. Additionally, the paper highlights the importance of multi-type charging stations and the impact of uncertainty on charging station planning. The paper concludes by identifying significant challenges and potential opportunities for EV integration. Future research should focus on enhancing coupled network modeling, refining user behavior models, developing incentive pricing mechanisms, and advancing autonomous driving and automated charging technologies. Such efforts will be essential for achieving a sustainable and efficient EV ecosystem.

Influence of coronavirus disease 2019 on attitudes toward forest biodiversity and nature conservation

The goal of this study is to better understand public perceptions of biodiversity loss, with a focus on the connections between deforestation and the eventual extinction of plants, animals, and birds. In Malaysia, a questionnaire study covering five variables &amp;ndash; deforestation, the extinction of mammals, birds, and plants &amp;ndash; as well as the moderating effect of coronavirus disease 2019 (COVID-19) on public attitudes toward biodiversity loss &amp;ndash; was conducted. Using online survey methods, 505 valid responses in total were acquired, and SMART-PLS was used for data analysis. Deforestation (the independent variable) is significantly and positively correlated with the extinction of birds, mammals, and plants, respectively. The study also demonstrates how COVID-19 moderates animal extinction and its impact on public perceptions of biodiversity protection. However, statistical study shows that popular perceptions of biodiversity protection are not significantly impacted by the loss of birds or plants. This study adds to the body of knowledge on the importance of public attitudes in reducing environmental degradation by providing a thorough analysis of popular attitudes toward biodiversity protection. The research has important ramifications for governments and organizations working to promote environmentally friendly behaviors, improve ecosystem sustainability, and encourage environmentally friendly organizations.

Conservation of Food, Medicinal and Dyes Crops Based on Local Community Wisdom in Mareje Village, West Lombok

Mareje Village, located in Sheet District, West Lombok Regency, NTB, Indonesia, is one of five villages and sub-districts in the Sheet District area. Nature protection is carried out to care for and protect natural resources, including flora, fauna, ecosystems and the environment. It involves a series of actions to ensure the sustainability and balance of ecosystems and natural habitats. This research aims to identify various food, medicinal and dye plants that have long been part of the conservation practices of the Mareje Village community. The research method used is descriptive qualitative, with data collected through trusted online sources, as well as interviews and questionnaires with local residents. The research results show that the people of Mareje Village still rely on various plants as a source of food, dyes and medicine. This includes rice, corn, cassava, taro, long beans, peanuts, green beans, and sweet potatoes for food; turmeric, pandan, katuk leaves, butterfly pea flowers, and dragon fruit for coloring; as well as white binahong, cat's whiskers, castor leaves, Chinese betel leaves, katuk leaves, black turmeric, bridal flowers, and horsewhip for medicine.

Analysis of The Impact of Climate Change on The Vulnerability of Coastal Areas and Small Islands in Gili Air, North Lombok

This research analyzes the impact of climate change on the vulnerability of coastal areas and small islands in Gili Air, North Lombok. Climate change, including rising temperatures and sea levels, is affecting coastal ecosystems, such as coral reefs which are vulnerable to bleaching and death. This study identifies a trend of increasing built-up land on Gili Air in the 2013-2022 period, which is caused by tourism promotion policies. The impact of this policy causes an increase in the number of tourists and local residents, which then increases the need for tourism supporting facilities. These land cover changes and development pressures increase Gili Air's environmental and economic vulnerability to climate change. These findings emphasize the importance of comprehensive adaptation and mitigation strategies to preserve the sustainability of ecosystems and the livelihoods of local residents.

Modeling of soil erosion based on geospatial techniques and the RUSLE model for the Ugam Chatkal National Park, Uzbekistan

Soil erosion significantly impacts agriculture and the environment, posing threats to food security, economic stability, and social development . Today, modern technologies are effectively used by world scientists to assess soil erosion and take measures against it. This study leverages modern technological advancements for the evaluation and management of soil erosion, specifically within the Ugam Chatkal National Park in Tashkent region. This research employed Geographic Information Systems (GIS) and the Revised Universal Soil Loss Equation (RUSLE) model to assess erosion processes and quantify annual soil loss in the park. Thematic layers (R,P,C,K,LS) for this model were created using GIS. In this way, the impact of each factor on soil erosion can be seen more clearly. According to the obtained results, it was found that the R and LS factors have a greater effect on soil erosion than the other factors. Findings indicate a heightened susceptibility of the Ugam Chatkal National Park to water erosion. The estimated average annual soil erosion rate ranges between 0.00 and 250 tons per hectare per year (t ha-1 yr-1). The results underscore the need for developing and implementing strategic measures to prevent water erosion in the park and to mitigate its impacts. The study emphasizes the importance of current technologies in recognizing and addressing environmental issues, particularly soil erosion, which has far-reaching implications for ecological preservation and sustainable development. This study not only sheds light on the erosion dynamics of the Ugam Chatkal National Park, but it also stresses the critical importance of taking proactive actions to protect the park’s ecological integrity. Failure to treat erosion in time could result in lasting damage to the park’s rich biodiversity and scenic vistas. The integration of modern technologies such as GIS and the RUSLE model not only enhances our understanding of soil erosion processes but also empowers conservation efforts, offering a promising pathway towards ensuring the long-term sustainability of natural ecosystems.

Implementation of Fuzzy Logic to Regulate Water Quality in Maintaining the Aquascape Ecosystem

Aquascape is an artificial aquarium ecosystem that is increasingly popular, considering the high cost of creating and maintaining an aquascape. Several aspects need to be considered in maintaining an aquascape, namely maintaining water quality. To know the water quality, it is necessary to periodically check the aquascape manually and carry out maintenance, therefore knowledge is needed to regulate and maintain the water quality in the aquascape. This research aims to implement fuzzy logic as a water quality control system in aquascape maintenance. The research method includes collecting data from the literature as well as developing a fuzzy logic model to identify and control water quality such as pH and temperature. The output of the system developed is a water quality control device with the categories "Unbalanced", "Quite Balanced", "Balanced". This research method includes calculations by collecting data and using MATLAB software to develop a fuzzy logic system. The research results show that the application of fuzzy logic is able to regulate water quality effectively and minimize the risk of ecosystem damage in the aquascape. The research conclusion shows that the application of fuzzy logic to regulate water quality in aquascapes has great potential in maintaining the sustainability of aquascape ecosystems.

Ship detection in reefs and deep-sea with medium-high resolution images

ABSTRACT Accurate and efficient ship detection is crucial for ocean monitoring and management, especially in reefs and deep-sea, where fishing and illegal activities threaten sustainability of ecosystems. Obtaining the size of ships in reefs and deep-sea helps to identify ship types and to assess the impact of ships on marine ecosystems quantitatively. Ship detections were mainly applied at coast or river of the inland region using high spatial resolution remote sensing data due to its rich details and frequent coverage. However, the ships located in reefs and deep-sea regions were rarely studied because of price, and availability of high spatial resolution remote sensing data. Global covered medium-high resolution (10–30 m) remote sensing data (such as Sentinel-2) makes it possible to obtain the spatial-temporal distribution of ships, especially small ships. This study developed a deep learning ship detection algorithm – an enhanced Rotated-Ship Detector (RShipDet) to detect ships in reefs and deep-sea regions. RShipDet was applied to Nansha Islands based on two medium-high resolution ship detection datasets (Sentinel2-Ship and SDGSAT-Ship). These two datasets include various backgrounds of reefs and deep-sea, and complex scenarios such as cloud cover and parallel ships, adapting RShipDet to ship detection under complex circumstances in reefs and deep-sea. The results showed that: (1) Small gains: gains of 3.3% and 8.7% Average-Precision (AP) compared to Rotation-equivariant Detector (ReDet) and Faster-RCNN on Sentinel2-Ship dataset; (2) Strong generalization capabilities: 77.4% AP on SDGSAT-Ship dataset; (3) Better performance under complex conditions: RShipDet obtained more accurate ship detection results over regions with cloud cover, islands and reefs, deep-sea, and ports compared to other classical detectors. Our algorithm could be applied for better management of ocean resources and activities in reefs and deep-sea.

Governmental Policies and Sustainable Outcomes in EU: How Innovations Change the Game?

Environmental degradation is one of the main challenges in today's world. Impact on the environment can be reduced through the introduction of clean and more efficient technologies. And innovation plays a crucial role in this process by replacing old equipment and methods. There are different ways how researchers understand sustainable innovations and sustainable innovation ecosystems. The terms "sustainable" and "sustainable development" have become very widely used in recent years. Sustainability is crucially important for the development of regions and national economies. Existing literature on the topic of sustainable innovation ecosystems includes vague and ambiguous definitions of sustainable innovation, as well as ways to measure it. A number of studies analyse the impact of different factors on conventional innovations and eco-innovations. However, not enough research has been done on the effects of innovations on all three dimensions of sustainable innovations, which are economic, environmental, and social. The aim of the article is to define whether governmental policies that promote innovation and sustainable development lead to environmental, social, and economic improvements in the EU countries. Our study uses the Eurostat data for 27 European Union countries. The literature review will include studies on sustainable innovation ecosystems. In the second chapter, we will describe the sustainable innovation ecosystems and ways to measure the sustainable outcomes of innovations. We study sustainable innovation ecosystems on a national level. We use partial least squares structural equation modeling (PLS-SEM) to determine the influence of governmental policies on sustainable outcomes, with product and process innovation as mediating variables. Under sustainable outcomes, we mean the economic, social, and environmental improvements on a national scale. The analysis is based on applying a quantitative method with empirical data using SmartPLS software. The results demonstrated a significant direct impact of governmental policies on innovation, as well as on environmental and social outcomes. However, they showed no indirect impacts connected to innovations. The results contribute to the current state of knowledge on sustainable innovation ecosystems and give policymakers valuable insights on factors that influence such ecosystems.

Optimalisasi Program Permaculture Melalui Adaptasi dan Mitigasi Berbasis Kearifan Lokal di Kelurahan Rejowinangun Selatan

The southern district of Rejowingan in Magelang faces challenges like large dumpstores, poor water quality, floods, and rising food needs. Villagers are working with the Ormawa DPM KM PPK team to address these issues. The government launched the Climate Village Program to improve the region's climate and resilience to natural disasters. Permaculture principles can be applied to organic waste management through maggot cultivation, which reduces waste volume and supports sustainable agriculture. This combination of permaculture and maggot cultivation can be an effective and environmentally friendly model for addressing organic waste and ecosystem sustainability.

Harmonizing models and measurements: Assessing soil erosion through RUSLE model.

Soil erosion poses significant ecological and socioeconomic challenges, driven by factors such as inappropriate land use, extreme rainfall events, deforestation, farming methods, and climate change. This study focuses on the Kozhikode district in Kerala, South India, which has seen increased vulnerability to soil erosion due to its unique geographical characteristics, increase in extreme events, and recent land use trends. The research employs RUSLE (Revised Universal Soil Loss Equation), considering multiple contributing factors such as rainfall erosivity (R), slope length and steepness (LS), cover management (C), conservation practices (P), and soil erodibility (K). The study is unique and novel, since it integrates extensive field data collected from agricultural plots across Kozhikode with the RUSLE model predictions, providing a more accurate and context-specific understanding of soil erosion processes and also suggesting management strategies based on risk priority. The study found that Kozhikode experiences an average annual soil loss of 28.7 tons per hectare. A spatial analysis revealed varying erosion risk levels across the district. 52.0% of the area experiences very slight erosion, 10.31% has slight erosion, 6.18% undergoes moderate erosion, 3.88% is moderately severe, 7.34% is at severe erosion risk, 5.6% has very severe erosion, and 14.65% faces extremely severe erosion. Field data collected from agricultural plots across Kozhikode were compared with RUSLE-predicted values, revealing a low root mean square error, indicating a strong correlation between observed and simulated data. Based on these findings, the district was categorized into low, medium, and high-priority regions, with tailored recommendations proposed for each. Implementing these measures could mitigate erosion, preserve soil fertility, and support the long-term sustainability of natural and agricultural ecosystems in Kozhikode. Given the practical challenges in estimating RUSLE factors in Southern India, where data scarcity is a common issue, this preliminary study underscores the need for expanded, long-term field observations to enhance understanding of soil erosion processes at the watershed level.

Biomimetic Adaptive Building Façade Modeling for Sustainable Urban Freshwater Ecosystems: Integration of Nature's Water-Harvesting Strategy into Sun-Breakers.

Urban freshwater ecosystems have many critical functions, such as providing water to all living things and supporting biodiversity. Factors such as water pollution, increased water consumption, habitat loss, climate change, and drought threaten the health of urban freshwater ecosystems. Looking for solutions to these challenges, this article aims to recycle water and return it to its life cycle using a climate-sensitive water collection strategy. The model focuses on the biomimetic method as a basic strategy. In this regard, the concept of water-harvesting has been examined in detail by conducting a deep literature review, including architecture and engineering disciplines. With all these data obtained, a synthesis/integration study was carried out by developing a model proposal based on adaptive building façade elements to solve the water problems experienced in cities. The model proposal, which is directly related to the titles of "Clean Water and Sanitation (SDG 6)" and "Sustainable Cities and Communities (SDG 11)", which are among the Sustainable Development Goals (SDGs), aims to provide different perspectives on the disciplines with its superficial and functional features. In this context, it is anticipated that the article will become an indispensable resource for other researchers working on the subject.

Regulatory Challenges in AI/ML-Enabled Medical Devices: A Scoping Review and Conceptual Framework

Abstract Amidst rapid advancements in artificial intelligence and machine learning-enabled medical devices (AI/ML-MD), this article investigates the regulatory challenges highlighted in the current academic literature. Using a PRISMA-guided scoping review, 18 studies were selected for in-depth analysis to highlight the multifaceted issues in regulating AI/ML-MD. The study's findings are organized into key themes: adaptive AI/ML, usability and stakeholder engagement, data diversity and use, health disparities, synthetic data use, regulatory considerations, medicolegal issues, and cybersecurity threats. The scoping review reveals numerous challenges associated with the regulation of AI/ML-based medical devices, reflecting various sustainability pillars. The study advocates for integrating sustainability principles into the materiovigilance ecosystem of AI/ML-MD and proposes a novel sustainable ecosystem for AI/ML-MD materiovigilance. This proposed ecosystem incorporates social, economic, and environmental sustainability principles to create a comprehensive and balanced regulatory approach. By presenting a thorough analysis of regulatory challenges, the study provides policymakers with a nuanced understanding of the complex landscape surrounding these technologies. This insight enables the development of informed strategies and solutions to address regulatory gaps and ensure the safe and effective integration of AI/ML-MD into healthcare systems.

Transport Mission Mitigation of Personalized Daily Commuting in China

Daily commuting constitutes a major part of urban mobility. Personalized transport modes for daily commuting have been adopted increasingly, such as car driving, shared mobility, etc. In general, this trend is against the Sustainable Development Goals’ aim of reducing emissions from the transport sector and improving urban ecosystem sustainability. We show the related statistics and advocate the use of nonmotor vehicles to mitigate greenhouse gas emissions and adverse environmental impacts of personalized daily commuting.

Toward a personalized autonomous transportation system: Vision, challenges, and solutions

The fragmented design of Intelligent Transportation Systems creates isolated intelligent systems. Resource competition and information gaps are fierce and widespread, worsening traffic issues and degrading overall service levels. Therefore, empowered by advanced technologies, an evolution towards Autonomous Transportation System (ATS) is observed. This evolution aims to develop a collaborative and sustainable ecosystem, prompting interoperability within the cloud-edge-device continuum. It can, accordingly, dismantle internal resource barriers and achieve a systematic balance between demand and supply with less human intervention. Despite the promising vision of ATS, it encounters three key challenges: disparate data, deficient models, and conflicting interests in supporting autonomous and personalized mobility. Hence, as an innovative solution, a trustworthy, private, and equal-serving framework called TPE is designed. It seamlessly integrates Blockchain, Federated Learning, and Large-scale Model to deploy a trustworthy operating environment, process private data for globally shareable knowledge, and develop a foundation model for personalized adaptation, respectively. Consequently, ATS empowered by TPE can serve diverse user groups both privately and equally.

A growth-effective age-based periodic site-index for the estimation of dynamic forest site productivity under environmental changes

Key messageA novel periodic site index is introduced for the quantification of dynamic forest site productivity. The measure is age-independent, sensitive to environmental changes and efficient for the estimation and prediction of stand height and stand volume increment.ContextAccurate and up-to-date prediction of site productivity is crucial for the sustainable management of forest ecosystems, especially under environmental changes.AimsThe aim of this study was to introduce a novel concept: a periodic site index based on growth-effective age for the quantification of dynamic forest site productivity.MethodsThe growth-effective age based periodic site index is estimated from repeated or multi-temporal measurements of stand dominant height. Furthermore, a recursive procedure to update the underlying site index model is presented by using repeated measurements of stand dominant height. The database used in this study comprised repeated measurements of 945 Norway spruce (Picea abies L.) experimental plots at 508 different locations in Southwest Germany.ResultsThe evaluation shows that periodic site index is statistically superior to the conventional site index, based on chronological stand age, for estimating stand height and stand volume increment. The analysis of temporal differences between growth-effective stand age and chronological stand age and between periodic site index and conventional site index in the period 1900 to 2020 reveals trends referring to stand age and site productivity, which corroborate earlier regional studies on forest growth trends due to environmental changes.ConclusionsThe periodic site index is a better indicator for site productivity than conventional site index. Under conditions of environmental changes, conventional site index is biased, whereas the growth-effective age based site index provides an unbiased estimate of stand height development. With the more widespread application of remote sensing techniques, such as airborne laser scanning, the availability of multi-temporal stand height data will increase in the near future. The novel concept provides an adaptive modeling approach perfectly suited to these data for an improved estimation and prediction of forest site productivity under environmental changes and can straightforwardly be applied also to uneven-aged and multi-species stands.

Mechanism for airborne ozone decomposition on X-MIL-53(Fe) (X = H, NH2, NO2)

Ground−level ozone (O3) pollution poses a significant threat to both ecosystem sustainability and human health. The catalytic decomposition of O3 presents as a promising technology to address the issues of O3 pollution. This study undertook the synthesis of various functionalized metal−organic framework (MOF) catalysts (i.e., X-MIL-53(Fe) (X = H, NH2, NO3)) to delve into the influence of ligand functional groups on skeletal structure and catalytic efficacy, particularly focusing on unraveling the mechanism of O3 catalytic decomposition under humid conditions. NH2-MIL-53(Fe) catalyst achieved complete O3 decomposition under ambient temperature and high humidity conditions (RH=75 %), exhibiting a reaction rates (mol·m−2·s−1) 129 and 10.5 times greater than that of MIL-53(Fe) and NO2-MIL-53(Fe). The NH2 group promotes electron flow within the backbone towards the hydroxyl group (OH) linked to Fe atom. In humid O3, H2O molecules augment the interaction between O3 and NH2-MIL-53(Fe), and OH is converted to·O2− after deprotonation, promoting O3 decomposition. Additionally, leveraging three−dimensional (3D) printing technology, a monolithic catalyst for O3 decomposition was prepared for application. This study not only advances understanding of the mechanisms underlying O3 decomposition but also offers practical solutions for addressing O3 pollution at humid conditions.

Climate change driven by LUCC reduced NPP in the Yellow River Basin, China

Anthropogenic activities and the resulting climate change affect the type, structure, and function of ecosystems. Understanding vegetation dynamics related to anthropogenic activities and climate change is critical to address the terrestrial carbon cycle in the context of global warming. The objective of this study is to quantify the effects of human-induced land use and land cover change (LUCC) and LUCC-induced climate change on terrestrial net primary productivity (NPP) in the Yellow River Basin (YRB) during 2000–2020 using Weather Research and Forecasting (WRF) model and Integrated Biosphere Simulator (IBIS) model through different experimental scenarios. Results indicated that LUCC can cause an increase in NPP of 1.2 ± 0.67 gC m−2 yr−1 in YRB. The increased precipitation and decreased temperature due to LUCC showed weak negative effect on annual mean NPP in YRB (−0.2 ± 0.74 gC m−2 yr−1). The coupling of LUCC and LUCC-induced climate change increased annual mean NPP approximately 0.6 ± 0.86 gC m−2 yr−1. The impacts of LUCC and LUCC-induced climate change and their coupling effects on NPP were greatest in spring, increasing NPP by 5.1 ± 0.51, 3.4 ± 0.41, and 6.1 ± 0.79 gC m−2 yr−1, respectively. These findings provide important guidance for the sustainable and adaptive management of terrestrial ecosystems in river basin in the context of global change.