System Resilience Research Articles

Convergence of IoT and PLC in Industrial Automation: A Systematic Review of Emerging Trends, Technical Challenges, and Prospects

Integrating PLCs with emerging IoT technologies for industrial automation has transformed the manufacturing ecosystems towards a smarter and data-driven one. This systematic review explores the synergistic potential of IoT's connectivity and PLCs' reliability in modern industrial settings. It analyses trends such as edge computing, AI-driven analytics and digital twins for technical challenges and proposes future directions using blockchain integration and 5G-enabled automation to support them. This review synthesizes academic literature, industry case studies and technological frameworks to outline a roadmap for resilient, efficient and adaptable industrial systems.

Defining potential pathways for improving the resilience and sustainable development of rangeland grazing systems: Insights from northern Australia.

Defining potential pathways for improving the resilience and sustainable development of rangeland grazing systems: Insights from northern Australia.

Resilience Analysis of Seaport–Dry-Port Network in Container Transport: Multi-Stage Load Redistribution Dynamics Following Cascade Failure

Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance network resilience. Extending the Motter–Lai framework, the model introduces multiple port state transitions and accounts for uncertainties in load redistribution, tailoring it to the cascading failure dynamics of SDNCT. Using empirical data from China’s coastal port system, the proposed MLRS dynamically reallocates loads through dry-port buffering, neighboring seaport sharing, and port skipping. This strategy effectively contains cascading failures, mitigates network efficiency losses, and protects major seaports while reducing mutual disruptions. Resilience analysis demonstrates that the network exhibits scale-free properties, with its resilience being highly sensitive to random port failures and critical port vulnerabilities. The experimental results highlight the pivotal role of dry ports, where operational numbers influence resilience more significantly than capacity. In addition, the study identifies the optimal port-skipping probability that mitigates cascading disruptions. These findings provide valuable insights for port management and logistics planning, contributing to the development of more resilient container transport networks.

Resilient generation planning considering long periods of low-RES output

The growing concerns over mitigating climate change effects resulted in power system planning and generation expansion strategies that aim in increasing penetration of intermittent renewable energy sources (RES) to fulfill the national energy and climate plans (NECPs) of countries worldwide. However, the variable and intermittent nature of RES output, compounded by uncertainties arising from climatic and weather changes, poses significant challenges. These challenges necessitate careful consideration in generation planning and in determining the operational reserves of RES-rich power systems to ensure resilience. This paper employs a generation capacity operational planning method based on the Screening Curve Method (SCM), assuming various levels of large RES penetration and diverse spinning generation reserve policies, necessary to cope with various levels of RES generation deficits, to guarantee power system resilience. The proposed approach can be used to assess the overall reduction of capacity and decommissioning of thermal units, while ensuring resilient operation against various levels of annual RES generation deficits. Furthermore, an approximation of the total annual system operation cost is also provided, considering the impact of the employed spinning reserve policies.

Disaster Resilience in Residential Area (Case Study: Siau Islands District Tagulandang Biaro, North Sulawesi Province Post Space Mountain Eruption in 2024)

Indonesia, located on the Pacific Ring of Fire, has a high potential for volcanic disaster due to tectonic plate subduction. The eruption of Mount Ruang on April 16 2024 in the Siau Islands District of Tagulandang Biaro (Sitaro), North Sulawesi Province, resulted in a significant impact on the local community with 9,083 people and 5,000 houses affected. This research aims to understand the factors that influence community resilience in facing natural disasters, especially volcanic eruptions, as well as identify weaknesses and strengths in existing resilience systems. The method used is qualitative with secondary data analysis from BNPB and PVMBG. The research results show the need for volcanic emergency training, building disaster-resistant infrastructure, strengthening early warning systems, relocating residents, and increasing coordination between institutions. Mitigation efforts by the North Sulawesi Provincial government and BPBD, including evacuation and restoration of learning activities, are expected to increase community resilience to future volcanic disasters and minimize their impact.

Prioritizing simulation-based stress tests to assess the resilience of transport systems: a computation-free methodology

This paper introduces a computation-free method for evaluating and prioritizing simulation-based stress tests for resilience assessment of transport systems. It enables infrastructure managers to efficiently screen and rank stress tests, optimizing the selection process to maximize insights into system resilience while minimizing computational demands. Stress tests have been proven to be a practical tool for understanding and mitigating the impact of disruptive events, yet conducting all possible tests using simulations, particularly for complex systems including plausible scenarios to account for climate change and other stressors, is computationally impractical, thus discouraging their use in practice. To address this, the paper suggests a methodology to estimate the impact of stress tests on risks at no computation cost and rank them accordingly to be selected for more detailed assessment. It uses the results of an initial risk assessment and, through a novel implementation of importance sampling and Bootstrapping resampling, selects subsets of the initial results to mimic specific stress test conditions, estimating their impact on risks. The methodology was validated through application to a Swiss road network facing flooding, demonstrating its practical effectiveness in identifying stress tests with significant potential impact on risks, hence having higher priority for more detailed assessment. In the presented case study, the proposed method enabled instant screening of 80 stress test scenarios, saving approximately 56 weeks of computation.

Intercropping the halophyte Tetragonia decumbens Mill. with salt-sensitive Spinacia oleracea L. mitigated salinity stress by enhancing the physiological, biochemical, and nutritional quality of the salt-sensitive species under saline cultivation

Increasing soil salinity is already having a significant effect on production losses of commercial vegetables around the globe. Thus, the implementation of innovative techniques is crucial to cultivate these vegetables amidst these unfavourable conditions. Halophytes are potential plants for resilient agricultural systems, such as intercropping with glycophytes, to enhance their productivity in saline soils. Therefore, the purpose of this study was to examine the intercropping potential of the halophyte Tetragonia decumbens in alleviating the damaging effects of salinity stress on spinach (Spinacia oleracea). Spinach seedlings were grown alone and in consociation with the halophyte under various salt stresses (50, 100, 150 and 200 mM NaCl). Results showed that increasing salinity reduced crop growth, relative water content, chlorophyll, and nutritional quality of spinach in monocultured system. Similarly, high salinity treatment induced severe oxidative stress depicted by high amounts of superoxide, malondialdehyde and the upregulation of superoxide dismutase, catalase, peroxidase, polyphenols, and flavonoids. Interestingly, intercropped spinach irrigated with 50 and 100 mM revealed a substantial enhancement in crop performance, reduction in oxidative stress and had improved nutritional quality depicted by high amounts of minerals, proximate constituents, and vitamins. These results support the introduction of T. decumbens in vegetable farming systems and highlights its positive impact on improving the overall crop performance of salt sensitive vegetables under saline condition.

How can food system actors influence food system resilience? A literature review via an actor-based lens

Abstract A growing body of research highlights the central role that actors play in shaping food system resilience. While individual studies have examined the contributions of specific actors, there remains a lack of synthesis that captures cross-sectoral patterns and underlying mechanisms. This review addresses this gap by analysing empirical evidence on how food system actors influencing food system resilience in the face of disruptions—not through abstract system properties alone, but through their concrete activities, capacities, and relationships.
Drawing on studies that focus on producers, intermediaries in the supply chain, and consumers, this review identifies four recurring mechanisms through which actors influence food system resilience: (1) actors' capability and agency to act under pressure; (2) the diversity of actors and their functions; (3) the connectivity and connections among actors; and (4) actors' capacity to learn and adapt. These mechanisms underpin the system’s ability to sustain or reconfigure essential functions during crises.
In addition, the review highlights the importance of supportive structures that bind actors to one another and to the broader food system. These include physical and institutional infrastructures such as logistics, energy, natural resources, digital platforms, and governance systems. Actor influence is also shaped by geographic location and position within the value chain, which affect their access to resources and ability to respond. Recognising that actors’ interests may not always align with system-level resilience, it is imperative to critically explore whose resilience is being supported, and for governance approaches that foster collective, system-oriented agency.

In-hospital trends of non-communicable disease mortality during the pandemic for patients without COVID-19 at a regional referral hospital in southwestern Uganda

BackgroundNon-communicable diseases (NCDs) represent a growing health burden in sub-Saharan Africa, especially in Uganda. The COVID-19 pandemic presented significant challenges for the Ugandan healthcare system, though changes in hospital admissions and outcomes for adults with NCDs and without COVID-19 infection remain unknown. We evaluated trends of NCD-related in-hospital mortality among patients without COVID-19 in a large regional referral hospital in Uganda from March 2019 through August 2021.MethodsBetween March 1, 2019, and August 31, 2021, we conducted a chart review of Ugandan adults who carried a history of or were admitted for an NCD to Mbarara Regional Referral Hospital. Based on mortality trends, we broke admissions into three periods: Pre-Pandemic (March 1, 2019, to May 31, 2020), Early Pandemic (June 1, 2020, to March 31, 2021), and Late Pandemic (April 1, 2021, to August 31, 2021), and calculated admission and mortality rates for the most common NCD diagnoses. A multivariable logistic regression model was fitted for a primary outcome of in-hospital mortality.ResultsOf 3777 total individuals, 1655 were admitted Pre-Pandemic, 1423 in the Early Pandemic, and 699 in the Late Pandemic. We found a five-fold increase in mortality in the Early Pandemic period compared to the Pre-Pandemic and Late Pandemic periods (15.4 vs 2.9 vs 2.4, p < 0.001). Factors associated with increased odds for in-hospital mortality included admission during the Early Pandemic period (odds ratio [OR] 5.59; 95% CI 3.90, 8.02; p < 0.001), admission with hypotension (OR 2.13; 95% CI 1.40, 3.24; p < 0.001), admission diagnosis of malignancy (OR 1.79; 95% CI 1.06, 3.01; p = 0.028) and stroke (OR 1.75; 95% CI 1.06, 2.88; p = 0.028), and each unit increase in SOFA score (OR 1.41; 95% CI 1.30, 1.52; p < 0.001). Length of stay greater than 7 days was associated with decreased odds of in-hospital mortality (OR 0.56; 95%CI 0.40, 0.79; p = 0.001).ConclusionsNCD-associated in-hospital mortality was high in the early COVID-19 pandemic period. Disruptions in longitudinal NCD care that occurred due to the pandemic may have been contributory, though this requires further investigation. Future work should focus on NCD care for hospitalized individuals in resource limited settings and developing more resilient systems of NCD care.

Hybrid encryption and Riesz-based biometric authentication: a novel approach for secure greyscale image transmission

This paper presents a novel greyscale image encryption and authentication mechanism by combining hybrid encryption with the Riesz transform for the first time. The system employs asymmetric encryption and optoelectronic implementation, integrating key techniques such as spiral phase mask, unequal modulus, random modulus decomposition and the QZS algorithm to enhance key space and enable authentication. The system's resilience is demonstrated through numerical simulations in MATLAB environment. Excellent statistical measures for decrypted image are obtained from the proposed approach: a mean squared error ( MSE ) of 4.9436 × 10 − 18 , a peak signal-to-noise ratio ( PSNR ) of 221 .19 dB and a perfect correlation coefficient ( CC ) of 1 . Additionally, with number of pixel change rate ( NPCR ) of 99.94 % and unified average changing intensity ( UACI ) of 33.348 , the system exhibits strong resilience against differential attacks. The high entropy value of 7.9954 confirms strong randomness and security, reinforcing the system’s resilience against differential attacks. Despite offering a high degree of security and accuracy the system maintains an efficient total encryption time of 2.37 seconds, including both encryption and authentication procedures, these findings establish the proposed system as a robust solution for secure image transmission and storage in today’s data-sensitive environment. This work represents a significant advancement in biometric-based image encryption by integrating novel hybrid transforms with Riesz-based authentication.

Optimal Microgrid Protection Coordination for Directional Overcurrent Relays Through Mixed-Integer Linear Optimization

Microgrids (MGs) are revolutionizing modern power systems by enabling decentralized energy production, renewable energy integration, and enhanced grid resilience. However, the increasing complexity of MGs, particularly with the integration of Distributed Energy Resources (DERs), poses significant challenges for traditional protection schemes. This study addresses the coordination of Directional Overcurrent Relays (DOCRs) in MGs through a Mixed-Integer Linear Programming (MILP) model. The main contribution is a MILP model that optimizes relay settings, including Time Multiplier Settings (TMS) and standard characteristic curves, to minimize tripping times, while ensuring selectivity. Another key contribution of this work is the integration of both IEC and IEEE standard curves, which enhances coordination performance compared to using a single standard. The model was tested on the IEC benchmark microgrid, and the results demonstrated significant improvements in fault-clearing times across various operational modes. By leveraging advanced optimization techniques and diverse characteristic curves, this study contributes to the development of resilient and efficient protection systems for modern microgrids, ensuring reliable operation under varying fault conditions and DER penetration.

Joint Probabilistic Forecasting of Wind and Solar Power Exploiting Spatiotemporal Complementarity

Reliable and precise joint probabilistic forecasting of wind and solar power is crucial for optimizing renewable energy utilization and maintaining the safety and stability of modern power systems. This paper presents an innovative joint probabilistic forecasting model designed to address probabilistic spatiotemporal power output forecasting challenges. Leveraging a multi-network deep learning framework, the model integrated the temporal convolutional network for temporal feature extraction, the convolutional neural network for spatial feature analysis, and the attention mechanism for spatiotemporal focus enhancement, thereby capturing the spatiotemporal complementarity of wind and solar power. It also incorporated a quantile regression-based uncertainty quantification technique, contributing to reliable probabilistic predictions. A wind farm and two solar farms in China were used as a case study. Comparison results between the proposed model and ten established models demonstrated its superior performance in both reliable deterministic and probabilistic predictions, offering valuable insights for sustainable and resilient energy system operation.

Enhanced Cyber-Physical System Security: A Model Checking Approach Using UPPAAL for OT-Specific Applications

Introduction: Cyber-physical systems (CPS) unite computing elements and physical operations but remain vulnerable to cybersecurity threats which threaten human safety along with environmental safety. These systems experience high susceptibility to attack when cybercriminals conduct the five phases of communication while comprehending the IT and operational technology aspects of the targeted system. Security enhancement along with prevention of malicious activities requires immediate attention to these system vulnerabilities. This paper establishes an all-inclusive framework which includes specific recommendations that guide security assessment of CPS while focusing on operational technology (OT) and employing the UPPAAL model checking tool. Objectives: A research method for CPS security verification serves as the main goal to develop security verification methods which meet inherent safety standards. A three-fold approach to CPS security management consists of establishing safety-oriented security constraints while building security threat detection systems and adding model checking protocols for defense system reinforcement. The research expands security modeling by designing a specific Attack Module which targets OT-based cyber threats. The research utilizes UPPAAL’s dynamic simulation tools to identify precise security threats by performing system evaluations of human-computer interfaces while developing a continuous security assessment framework. Method: The research handles security verification through structured utilization of UPPAAL which operates as a formal verification tool. The safety requirements of CPS OT components form the basis of security constraints at the starting point. A series of tests under model checking procedures ensures both the effectiveness and identification of potential vulnerabilities. Real-time reactivity and advanced simulation methods in UPPAAL allow users to properly define temporal characteristics of system behaviors. The OT-specific Attack Module permits operators to perform simulations of cyber attacks for determining system resilience through its integrated features. Result: The requested method led to vital findings which verify its success in safeguarding CPS systems. The predefined security rules allow real-time detection of threats that originate from operating technology safety requirements. Model checking in cooperation with UPPAAL helps achieve exhaustive security measure verification. The Attack Module which was developed proved successful in creating OT-specific threat models which delivered important system vulnerability information. Conclusion: Research findings demonstrate that formal verification remains crucial for protecting CPS against cyber attacks in actual systems. The researchers used UPPAAL simulation techniques to develop an effective framework that detects and resolves security weaknesses in Operational Technology systems. System protection improves significantly when security constraints receive structured implementation while an Attack Module is integrated into the system. Security assessments under the proposed methodology run continuously to maintain long-term readiness against developing cyber threats in the environment. Research efforts in the coming period will concentrate on verifying the security evaluation procedures while adding support for different CPS frameworks to apply this method.

Dynamic dual-layer network resilience assessment as a system architecting tool

Abstract Modern complex systems should be resiliently designed to enable recovery in a variety of expected or unexpected environments. Resilience is defined as the ability to withstand and recover from disruptive events. The objective of developing resilient systems drives the need of analysis tools to guide the system architecture process. There is a need for the creation of resilience tools that are time-based and are applicable for the system architecture process. The larger literature offers a variety of methods and quantitative metrics for assessing resilience. Still, there is a lack of system architecting tools that focus on assessing the resilience of system architecture options considering the dual nature of the system's physical and functional aspects while taking into account the design of redundancy into the system's recoverability behavior. To bridge this gap, this paper proposes a dynamic network-based resilience assessment method that models systems as a dual layer functional and physical network. The method, which has been developed into a computational tool, generates a measure of resilience that serves as a quantitative evaluation indicator during system architecting. As a case study, the method is applied to eight power and propulsion system architecture options. The findings demonstrate that, even before a system architecture has matured, the tool supports informed decision-making, for example in terms of measuring the effectiveness of redundancy introduced to improve resilience, as well as early detection of system vulnerabilities.

Resilient and Flexible Electrohydrodynamics Pumps for Human-Machine Interfaces.

Soft fluidic systems can be a versatile tool to design human-machine interfaces such as hydraulic actuators, liquid displays, and thermal haptics. Yet the bulkiness, noise, and rigidity of pumps and valves required for fluid circulation prevent their use in flexible and portable devices. This study introduces an electrohydrodynamic (EHD) driven flexible pump with resilience against dielectric breakdown. Previous EHD pumps, despite their excellent features such as quietness and high power density, suffer from dielectric breakdowns and subsequent permanent failures. This pump with novel electrode construction has the passive resilience to recover the insulation essential for EHD without any external input in the event of dielectric breakdown. The passive resilience of our pump is demonstrated in various scenarios. Notably, this pump withstands 100 dielectric breakdowns and maintains 90% of its performance. An active resilient system is also configured to enable continuous pumping. This system automatically removes bubbles and other impurities to recover flow generation. This pumps drive various soft fluid-driven human-machine interfaces like soft actuators, prosthetic hands, and tube-format displays. The combination of passive resilience inherent in the pump and active resilience configured by the system ensures adaptability and robustness, setting the stage for the next generation of human-machineinterfaces.

Technical report on interventions during the global fund resilient and sustainable systems strengthening for health project in Edo state, Nigeria

Access to affordable healthcare and commodities is a major challenge in developing countries such as Nigeria; thus, the training of state-employed personnel in state institutions by certified implementing partner consultants remains a significant approach to achieving universal health coverage and sustainable development goals. This report contains all the interventions employed by the author as a consultant for the Global Fund Resilient and Sustainable Systems Strengthening for Health project in the Edo State Ministry of Health, Nigeria. The interventions are premised on human capacity development, coordination and systems strengthening, improving health commodity availability, and operationalizing the state and local logistics management coordinating units (LMCUs). Among the major successes achieved include building the capacities of key state and local government area LMCU members over time, so they were able to offer effective services and interventions that will guarantee health commodity management and security. Coordination among relevant health stakeholders and good logistics management information systems (LMIS) were also enhanced during the one-year duration of the project (December 2019 to December 2020). The exposition from this report suggests a holistic and ‘resilient sustainable system strengthening’ approach for managing global health challenges that can also be employed in managing global disease cases or pandemics.

Exploring Sustainable Finance and ESG Investing

Since they promote the inclusion of social, political, and environmental factors in financial decision-making, sustainable finance and environmental, social, and governance (ESG) investing have become important forces behind the transformation of the economy. The concept, history, importance, and ramifications of sustainable finance and ESG investing are briefly summarized in this abstract. The text delves into the underlying principles of sustainable development and emphasizes the significance of coordinating financial operations with these objectives. Additionally, it looks at the best practices, empirical data, and analytical techniques related to incorporating ESG factors into investment plans. The summary highlights the increasing evidence that sustainable practices may reduce risks, improve resilience, and open up new economic prospects, which is driving the impetus behind sustainable finance and ESG investing. It also highlights the necessity of strong standards, open reporting procedures, and exacting impact assessment processes in order to direct investment choices and promote accountability. In the end, this abstract aim to further the current conversation on sustainable finance by providing stakeholders with useful information and promoting a more resilient, inclusive, and sustainable financial system.

An Adaptive Framework for Intrusion Detection in IoT Security Using MAML (Model-Agnostic Meta-Learning)

With the rapid emergence of the Internet of Things (IoT) devices, there were new vectors for attacking cyber, so there was a need for approachable intrusion detection systems (IDSs) with more innovative custom tactics. The traditional IDS models tend to find difficulties in generalization in the continuously changing and heterogeneous IoT environments. This paper contributes to an adaptive intrusion detection framework using Model-Agnostic Meta-Learning (MAML) and few-shot learning paradigms to quickly adapt to new tasks with little data. The goal of this research is to improve the security of IoT by developing a strong IDS that will perform well across assorted datasets and attack environments. Finally, we apply our proposed framework to two benchmark datasets, UNSW-NB15 and NSL-KDD99, which provide different attack scenarios and network behaviors. The methodology trains a base model with MAML to allow fast adaptation on specific tasks during fine-tuning. Our approach leads to experimental results with 99.98% accuracy, 99.5% precision, 99.0% recall, and 99.4% F1 score on the UNSW-NB15 dataset. The model achieved 99.1% accuracy, 97.3% precision, 98.2% recall, and 98.5% F1 score on the NSL-KDD99 dataset. That shows that MAML can detect many cyber threats in IoT environments. Based on this study, it is concluded that meta-learning-based intrusion detection could help build resilient IoT systems. Future works will move educated meta-learning to a federated setting and deploy it in real time in response to changing threats.

Strengthening regulatory compliance in the U.S. food industry to support health system resilience and public health preparedness

Foodborne illnesses continue to pose a significant threat to public health in the United States, with regulatory lapses in food production and distribution contributing to widespread outbreaks that strain already burdened healthcare systems. Incidents involving E. coli, Listeria monocytogenes, and Salmonella have highlighted critical vulnerabilities in the nation’s food safety infrastructure, resulting in increased hospital admissions, emergency response activation, and disruption of healthcare services. These failures reveal the urgent need to reframe food safety not only as a regulatory concern but as a critical component of public health preparedness and health system resilience. This paper examines the cascading impact of regulatory non-compliance in the U.S. food industry on health system capacity, especially during outbreaks and emergencies. It analyzes systemic gaps in current compliance frameworks and identifies missed opportunities to mitigate preventable health crises through stronger regulatory mechanisms. Drawing on real-world case studies, we demonstrate how insufficient inspections, inconsistent enforcement, and a fragmented compliance ecosystem undermine both food security and public health readiness. To address these challenges, we propose a multi-pronged strategy to strengthen regulatory compliance through enhanced digital audits, predictive analytics, workforce training, and integration of real-time monitoring technologies. These tools not only improve risk forecasting and outbreak prevention but also contribute to the agility and responsiveness of health systems during crises. Furthermore, we present actionable policy recommendations for federal and state agencies, emphasizing the alignment of food regulatory functions with national public health preparedness goals. By modernizing food safety oversight and embedding it within the framework of public health resilience, the U.S. can more effectively safeguard communities, reduce economic disruptions, and build a future-ready health system capable of withstanding both biological threats and systemic shocks. Keywords: Food Safety Surveillance, Public Health Integration, Risk Assessment, Regulatory Compliance.

Coupling Coordination Relationships Between Water Resource–Water Environment–Social Economy Resilience and Ecosystem Services in Five Provinces of Northwest China

In the context of global climate change and intensified anthropogenic pressures, the coordinated development of a social-ecological system (SES) faces unprecedented challenges, necessitating an enhanced understanding of complex system interactions to achieve SES sustainability. This study quantified water resource–water environment–social economy resilience (WR-WE-SEr) and four ecosystem services (ESs)—water yield (WY), habitat quality (HQ), soil retention (SR), and carbon storage (CS)—in Northwest China from 2010 to 2020. Intersystem interactions were analyzed using resilience theory, the InVEST model, and the coupling coordination degree (CCD) model. The key findings include the following: (1) Spatiotemporal evolution patterns (RQ1): WR-WE-SEr exhibited sustained growth with significant regional disparities (Qinghai &gt; Xinjiang &gt; Gansu &gt; Shaanxi &gt; Ningxia), predominantly driven by resistance-dominated dynamics. ESs showed spatial heterogeneity: WY was concentrated in humid areas but declined temporally, while HQ and CS aligned with vegetation/land cover. All ESs followed a “V”-shaped trajectory of initial decline and recovery, with localized fluctuations but regional stability. (2) Coordinated coupling relationships (RQ2): The CCD between WR-WE-SEr and ESs maintained temporal stability but mirrored ESs’ spatial patterns, characterized by a southeast–northwest diminishing gradient. Coordination hierarchy (CS &gt; HQ &gt; WY &gt; SR) and regional performance (Shaanxi &gt; Ningxia &gt; Qinghai &gt; Gansu &gt; Xinjiang) revealed synergies between system resilience and ES provisioning capacity. Transitional coordination (dissonance to coordination) at the integrated ES level highlighted gradual optimization of human–nature interactions. These findings underscore the need for multidimensional strategies to enhance WR-WE-SE-ES synergies in Northwest China.