Adaptive Management Research Articles

Multi-objective adaptive energy management strategy for fuel cell hybrid electric vehicles considering fuel cell health state

This study proposes a multi-objective adaptive energy management strategy for fuel cell hybrid electric vehicles considering fuel cell health state. By integrating rule-based control with multi-objective optimization methods, the strategy aims to improve system efficiency, extend the lifespan of proton exchange membrane fuel cells (PEMFC), and reduce operating costs. Based on a comprehensive model of PEMFC output characteristics and lifetime degradation, this study introduces an optimized point line (OPL) strategy. This strategy dynamically adjusts operating constraints according to the state of health (SOH) of the PEMFC, ensuring optimal vehicle performance throughout its lifecycle. To optimize the OPL strategy parameters, a particle swarm optimization algorithm with compression factor was employed, enhancing the strategy’s optimization efficiency, adaptability, and robustness to better handle various real-world operating conditions. The strategy was evaluated under US06 and WLTC driving cycles and compared with traditional power following (PF) and point line (PL) strategies. Results show that compared to the PL strategy, the OPL strategy achieved a 36.4% and 34.2% reduction in operating costs under US06 and WLTC cycles, respectively. Moreover, PEMFC lifetime degradation decreased by 44.9% and 39.4% in these cycles. In high-power regions, the average operating efficiency of PEMFC improved by 2%. The strategy demonstrated good adaptability to different driving conditions, providing an effective solution for optimizing the performance and durability of fuel cell hybrid electric vehicles.

An insight into architectural design studio education space from a "time" perspective

This study offers a comprehensive literature review of the evolution of design studio education, focusing on the integration of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) technologies. The research explores current and future design studio models by examining the development of architectural design studio education and the importance of its physical spaces within a timeline framework. The literature review identifies key insights, analyzes patterns, and integrates findings to present a narrative of architectural education's historical evolution and prospects. The study highlights significant shifts in design studio education, moving from the traditional master-apprentice relationship to contemporary design studio spaces within architecture schools. It emphasizes the impact of social, economic, and technological developments on these models, particularly the shift to remote education necessitated by COVID-19. This transition highlighted the need for alternatives to physical studio spaces, directing attention to VR, AR, and MR technologies as potential solutions. Through a meticulous review process, this study examines how these emerging technologies can provide immersive and interactive learning experiences, enhancing flexibility and accessibility in design education. It discusses the benefits and challenges of integrating these technologies, considering their potential to function without needing a specific physical studio. Ultimately, this study contributes to the field by offering theoretical insights and practical guidelines for educators. It explores alternative models to enhance adaptability and addresses the implications of technological adaptation and crisis management. The findings enrich the academic literature and foster future research and discussion on the evolution of design studio education in the digital era.

Prospects on the use of EIA as a Tool for Coastal Resources Conservation

The successful application of EIA in coastal resource conservation has underscored its potential as an effective environmental management tool. Traditional EIA processes often focus on the impacts of individual projects in isolation. However, coastal environments are influenced by multiple activities and stressors. There is a growing recognition of the importance of assessing cumulative impacts to ensure more holistic environmental management. It is essential to implement adaptive management practices that allow for ongoing monitoring and adjustment of mitigation strategies based on real-world outcomes. To enhance the effectiveness of EIA, therefore, it should be integrated with due considerations on environmental impacts at the policy, plan, and program levels, providing a broader context for individual project assessments. This integration can lead to more coherent and sustainable coastal management strategies.

Potential use of Environmental Management Plan for the Sustainability of Coastal Area and Resources

The potential use of Environmental Management Plans (EMPs) for the sustainability of coastal areas has demonstrated significant benefits in enhancing environmental protection, regulatory compliance, and stakeholder engagement. However, challenges such as data collection, monitoring, and the effectiveness of mitigation measures must be addressed to fully realize the potential of EMPs. By investing in baseline data, implementing robust monitoring and adaptive management practices, enhancing stakeholder engagement, integrating EMPs with broader management frameworks, and allocating adequate resources, the effectiveness and sustainability of EMPs can be significantly improved.

Why Can’t We All Just Get Along? Conflict and Collaboration in Urban Forest Management

AbstractUrban forest management is crucial for supporting human well-being, ecosystems, and society, particularly with expanding global urban population and multi-uses of these urban greenspaces. This literature review examines the conceptualization and factors that contribute to conflicts and/or collaborations in urban forest management, including, but not limited to, diverse actors’ uses, needs, and perceptions. Using PRISMA methods, we systematically reviewed 176 scholarly articles published between 2013 and 2021 and found that most articles were primarily from the United States, Australia, and Canada. Findings highlight the need for clearer definitions of collaboration, emphasizing communication, operational tasks, planning, and shared beliefs among actors. Positive collaborations involved multi-level engagement and inclusive decision-making. In most cases, multiple issues contributed to conflict, including a variety of stakeholders with differing viewpoints on a given situation. Conflicts are commonly complex situations that do not lend themselves to a one-size-fits-all solution and tend to be a unique manifestation of the people, places, and perspectives involved. Our review can inform practitioners about more inclusive practices and adaptive management of urban forests. We conclude by providing lessons learned and suggestions for future research on stakeholder involvement, public education, governance, policy, decision-making, and the role of biophysical and ecosystem services in urban forest collaboration and conflicts.

The collateral effects of COVID-19 on coastal and marine environments

The COVID-19 pandemic has generated a global health and economic crisis, significantly impacting coastal and marine environments. Lockdowns and restrictions, while necessary for public health, led to both positive and negative environmental consequences. Reduced human activity resulted in decreased pollution and habitat disruption, allowing for ecosystem recovery and improved water quality. However, the surge in single-use plastics and personal protective equipment (PPE) during the pandemic exacerbated plastic pollution. Additionally, the economic downturn severely affected coastal communities reliant on tourism and fisheries, highlighting the need for sustainable recovery strategies. This Special Issue explores these collateral effects, emphasizing the importance of adaptive management and resilient governance in safeguarding coastal and marine ecosystems against future crises.

Pastoral coping and adaptive management strategies to climate change in communal areas in Namibia and South Africa

Climate change has brought about credible changes in arid landscapes which have resulted in further challenges for pastoralists who require good quality rangeland resources to sustain their livestock. This study assessed local level coping and adaptive management strategies by pastoralists in Namibia and South Africa using a capital assets approach, and also explored non-climate related barriers that increase their vulnerability to climate change. A case study approach was used, which included focus group discussions and semi-structured interviews. The main findings of the research indicate that pastoralists have been exposed to increased temperature extremes and droughts of varying duration over time which reduced the quality and quantity of forage and resulted in losses of income and animal health. The 46 different coping and adaptation strategies used by pastoralists included financial (n = 15), natural (n = 15), human (n = 12), physical (n = 2) and social (n = 2) capital. Of these, 61% of the strategies were common between the two countries. Strategies included income diversification, supplementary feeding and livestock mobility. Pastoralists had to overcome a hierarchy of barriers to implement their coping and adaptation strategies, which were largely related to human capital in Namibia and to natural capital in South Africa. These barriers included a lack of access to grazing lands, land degradation and the loss of traditional knowledge to manage livestock and rangeland resources. Policy development should take these barriers into account while building on the foundation of existing adaptation strategies to reduce the vulnerability to climate change of pastoralists in dryland regions.

Living estuarine shorelines as nature-based green engineering for coastal stabilization: A scientometric analysis

Natural estuarine wetland shorelines play a crucial role in coastal stabilization and preserving ecological security patterns. The effectiveness of estuarine shoreline engineering in reducing coastal erosion and maintaining the stability of ecosystem structures and functions is tightly linked to their types and structures. Although the living estuarine shorelines have received increasing attention, there have been few systematic literature reviews on the development process, research hotspots and future trends in this field. Here we summarized the literatures, and analyzed them in terms of annual publications, subject categories, co-cited journals, countries, institutions, authors, references, and keywords based on OriginPro, VOSviewer, and CiteSpace softwares. Results showed that the studies on living estuarine shorelines have experienced a rapid development phase since 2004, which is mainly categorized into Environmental Sciences and Oceanography, and the research institutions and scholars are mainly from the USA and China. The effects of human activities and climate change on the structures and functions of estuarine ecosystems are the dominant topics. Furthermore, the nature-based management solutions have been proposed to improve the functions and services of estuarine ecosystems. Currently, the habitats of estuarine wetlands worldwide have undergone varying degrees of degradation, therefore, the ecological conservation and restoration of estuarine shorelines urgently require the active participation of the public. It is highly important to integrate multi-disciplinary and multi-technology approaches to construct nature-based, more resilient, multi-service synergistic, and composite living shorelines in coastal zones. The findings of this research can provide scientific guidelines for the adaptive management and conservation of estuarine wetlands.

An efficient multi-fidelity simulation approach for performance prediction of adaptive cycle engines

Adaptive cycle engine (ACE) with multi-stream, modulated bypass ratio, and high-thrust/high-efficiency mode provides the capability of multiple mission adaptation for the next-generation aviation propulsion system. The low-fidelity zero-dimensional (0D) performance simulation method is commonly adopted in conventional engines such as turbofan and turbojet. However, it is hard to accommodate well to ACE with complex variable geometry schemes and strong interaction between components. This paper presents an efficient multi-fidelity simulation approach, often referred to as component zooming, for predicting the performance of ACE with the three-stream configuration. The one-dimensional (1D) mean-line models of the adaptive fan and low-pressure turbine (LPT) are integrated into the 0D ACE model by the iteratively-coupled method. The performance predicted by the multi-fidelity ACE models with different component zooming strategies is compared. The maximum deviations of thrust, specific fuel consumption, turbine inlet temperature, and bypass ratio between the 0D/1D Adaptive Fan/1D LPT coupled model and 0D ACE model are −10.8%, −4.4%, −5.4% (−75 K), and 1.6%, respectively, which are considerable and non-negligible for the application in the design stage of ACE. The computing time of all the multi-fidelity models is less than 2 minutes. The effects of the key aerodynamic parameters of the adaptive fan and LPT on the engine performance are also evaluated. The proposed approach provides a generic and efficient solution for multi-fidelity ACE performance prediction with acceptable computing resource requirements and time cost, which is applicable in the engine conceptual and preliminary design stage.

Distribution, source apportionment and ecological risk assessment of heavy metals in Limbe River sediments, Atlantic Coast, Cameroon Volcanic Line

The objective of this research was to assess sediments contamination, provenance and metal pollution using single and complex pollution indicators. Limbe River sediment samples were analysed using Inductively Coupled Plasma—Mass Spectrometry. The Limbe River sediments exhibit high content in Fe2O3 sourced from haematization of basaltic rocks. The concentration of Cd, Co, Cr, Mn, Ni, Pb, Sn, Sr, V and Zn exceed upper continental crust and local baseline values for heavy metals. Correlation matrix analysis indicates the presence of common input sources and similar geochemical characteristics of heavy metals. Contamination factor (CF: 0.01–10.34), contamination degree (Cdeg: 14.91–36.57), pollution load index (PLI: 0.84–1.77), and nemerow integrated pollution index (NIPI: 0.2–1.7) indicates significant to high levels of contamination. The enrichment factor (EF: 0–5.67) and geo-accumulation index (Igeo: -7.55–2.59), suggests moderate to significant metal pollution of the Limbe River ecosystem, suggesting potential ecological effects. Modified hazard quotient (mHQ: 0.082–6.35) and toxic risk index (TRI: 10.49–27.43), indicates low to extreme pollution severity and high toxicity risks of heavy metals to the aquatic ecosystem fauna and flora. Primarily anthropogenic activities and secondary lithogenic provenance is attributed to sediments contamination and metals pollution. This study suggests that a greater emphasis should be placed on monitoring various provenances of metals entering the aquatic ecosystem from anthropogenic practices. The study emphasizes the significance of continual protection of aquatic ecosystem and biological resources and adaptive management. The development of reasonable goals for monitoring and remedial programmes can be aided by this data.

Using cumulative human impact assessment to support adaptive management of the threatened species’ habitats in the Yangtze River Estuary

The conflict between multiple functions of human use and habitat conservation represents an intractable challenge for environmental management. While numerous studies on marine conservation prioritize cumulative impact assessments (CIA) to tackle this issue, estuaries — despite their immense conservation significance amidst intense human activities — remain overlooked. Taking the Yangtze River Estuary (YRE) as the case study area, it is one of the most intensely human-utilized estuaries globally, yet it serves as a critical habitat and migratory corridor for the endangered Chinese sturgeon (Acipenser sinensis).We employed ecological indicators and quantitative modeling to assess habitat suitability and cumulative anthropogenic impacts on this endangered species in the YRE. The results demonstrated that suitable habitat distribution and human impact varied for juvenile Chinese sturgeon in the YRE. The suitable habitat distribution for juvenile Chinese sturgeon was concentrated in Chongming Dongtan and the North Channel. Ship density, submarine optical cables, and smooth cord grass invasion were the main anthropogenic factors impacting the Chinese sturgeon's migrating habitat in the YRE. Moreover, existing Chinese sturgeon habitats remain at risk, with 36.24 % of potential habitats and 56.60 % of high human impact areas requiring enhanced protection. Adaptive management strategies were proposed, tailored to the spatial and environmental protection needs across the dynamic habitat demands of aquatic species. Our spatially explicit and indicator-based findings provide key scientific support for enlarging protected areas and implementing adaptive management of human activities to balance conservation and sustainable use in this highly utilized ecosystem.

Adaptation of Chinese traditional villages from the perspective of locality preservation

Recently, traditional villages in China have received multiple policy protections and capital injections. While these external interventions protect the cultural heritage of traditional villages and provide opportunities for development, they have gradually eroded their intrinsic adaptive cycle system. This study focused on 6819 traditional villages, revealed the characteristics and transitions of the adaptive cycle stages in traditional villages and described the internal mechanisms of adaptability within these villages. The research findings are as follows: Regarding adaptability characterisation, the adaptability of traditional villages has developed a regionally significant imbalance. The highest proportion of adaptability cycle stages was found in the poverty trap, exploration (r) and gambling traps. Traditional villages are mostly in a rigid state, with a few adaptive processes shifting between the poverty trap and exploration (r), requiring a new impetus to guide positive cycles. In terms of adaptability mechanisms, there was a significant negative relationship between locality, mobility and resilience in traditional villages. Intrinsic adaptive mechanisms gradually disintegrate, and there is an increasing risk of falling into a lock-in trap. This study provides empirical evidence for analysing the issues in traditional villages and offers recommendations for long-term planning and policy formulation of locality protection in traditional villages.

Sediment water content drives movement of intertidal crab Helice tientsinensis more strongly than salinity variations

Intertidal wetlands undergo dynamic water and salinity variations, creating both promising and challenging habitats for diverse organisms. Crabs respond strongly to these variations by means such as altering their movements, thereby restructuring their spatial distribution and influencing coastal ecosystem resilience. However, the movements of crabs under varying environmental conditions require further elucidation. We conducted a systematic mesocosm experiment using the ubiquitous intertidal crab species Helice tientsinensis with four amount levels and six salinity levels of sprayed water applied through a custom apparatus, with a primary focus on crab movement. Crab movement from the experimental side of the apparatus (with altered conditions) to the control side (resembling field conditions of the intertidal wetlands of China's Yellow River Delta) and vice versa was recorded. The results revealed significant differences in moving out of the experimental side and moving in among the different water and salinity conditions, both separately for the two factors and simultaneously. Decreases in water content had a more pronounced effect on crab movement, leading to an increased number of crabs moving out of the experimental side of the apparatus. Conversely, as the experimental side became wetter, crabs tended to move towards it, and this movement was intensified by increases or decreases in water salinity. A structural equation model revealed that the moving-out and moving-in played fundamental roles in determining the number of resident crabs at the end of each experiment. While crabs preferred moist sediment with lower salinity, changes in salinity alone had minimal direct effect compared to sediment water contents. Our results clarify crab movements under varying water and salinity conditions, offering valuable insights to support adaptive interventions for crab populations and inform adaptive conservation and management strategies in intertidal wetlands.

Energy Management Strategy of Fuel Cell Commercial Vehicles Based on Adaptive Rules

Fuel cell vehicles have been widely used in the commercial vehicle field due to their advantages of high efficiency, non-pollution and long range. In order to further improve the fuel economy of fuel cell commercial vehicles under complex working conditions, this paper proposes an adaptive rule-based energy management strategy for fuel cell commercial vehicles. First, the nine typical working conditions of commercial vehicles are classified into three categories of low speed, medium speed and high speed by principal component analysis and the K-means algorithm. Then, the crawfish optimization algorithm is used to optimize the back propagation neural network recognizer to improve the recognition accuracy and optimize the rule-based energy management strategy under the three working conditions to obtain the optimal threshold. Finally, under WTVC and combined conditions, the optimized recognizer is used to identify the conditions in real time and call the optimal rule threshold, and the sliding average filter is used to filter the fuel cell output power in real time, which finally realizes the adaptive control. The simulation results show that compared with the conventional rule-based energy management strategy, the number of fuel cell start–stops is reduced. The equivalent hydrogen consumption is reduced by 7.04% and 4.76%, respectively.

Predicting fish spawning phenology for adaptive management: Integrating thermal drivers and fishery constraints

Climate warming is causing shifts in reproductive phenology, a crucial life history trait determining offspring survival and population productivity. Evaluating these impacts on exploited marine resources is essential for implementing adaptive measures from an ecosystemic approach. This study introduces a statistical model designed to predict fish spawning phenology from sea surface temperature profiles, integrating mortality-corrected hatch-date distributions inferred from fishery-dependent samplings, along with the gonadosomatic index of adult individuals. When applied to different dolphinfish (Coryphaena hippurus) populations across a broad latitudinal range, the model reasonably predicts the spawning phenology across its extensive thermal ranges, elucidating a direct relationship between mean annual temperature and the breadth of the spawning season. Despite the varying thermal profiles, results show a consistent timing of spawning peaks approximately 49 days before the peak in temperature. Importantly, these findings account for the impact of fishery constraints, such as seasonal closures or different sampling schedules, offering a robust tool for adjusting management practices in response to inter-annual temperature variations. These insights are critical for both short-term fishery management, including the strategic planning of seasonal closures, and long-term projections of spawning phenology shifts under changing thermal regimes. By enhancing our ability to predict spawning times, this research contributes significantly to the sustainable management of fish populations and the adaptive response to environmental changes.

Analysis of the Water Quality Status and Its Historical Evolution Trend in the Mainstream and Major Tributaries of the Yellow River Basin

The Yellow River basin, an area of extreme water scarcity, has faced significant challenges in water quality management due to rapid economic and social development since the 1980s. This study analyzes the water quality evolution over nearly 40 years, focusing on primary pollutants like chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and permanganate index (CODMn). In the 1990s, sections of the river were severely polluted, with some areas failing to meet the lowest national standards. In 2000, 32% of the river water was classified as inferior Class V. However, enhanced water resource management and stricter pollutant regulations introduced after 2000 have significantly improved water quality. By 2010, water quality reached its nadir, with 16% of water classified as inferior Class V and 25% as Class IV–V. By 2020, water quality showed marked improvement, with a significant reduction in segments classified as inferior Class V and Class IV–V. Recent years have seen water quality stabilize, with COD meeting Class I standards and NH3-N and CODMn meeting Class II standards based on national criteria. The study also highlights discrepancies in water quality between the mainstream and tributaries of the Yellow River. While the mainstream generally maintains good water quality, many tributaries remain severely polluted. In 2022, 85% of the water in tributaries was classified as Class I to III, 12.3% as Class IV to V, and only 2.7% as Class V. However, all water in the mainstream reached Class I–III, with 86% achieving Class II and 14% achieving Class I. A detailed analysis of the Huayuankou section over the past three decades shows a general decline in pollution indicators. Seasonal water quality fluctuations, correlated with flow rates and temperatures, were observed, often exhibiting normal distribution patterns. These findings underscore the effectiveness of sustained pollution control and the need for continuous, adaptive management strategies to improve and maintain water quality in the Yellow River basin.

Introducing a climate, demographics, and infrastructure multi-module workflow for projected flood risk mapping in the greater Pamba River Basin, Kerala, India

Enhanced understanding of extreme events is essential for comprehensive risk assessment promoting informed decision-making and early warning to ensure the resilience against challenges imposed by changing climate. This study proposes a novel multi-module integration framework for the comprehensive evaluation of future flood risk in the Greater Pamba River basin, Kerala, India. The integrative modelling framework is developed by assembling a Cellular Automata-Markov Chain (CAMC) based and Use/Land Cover (LULC) projections, Reliability Ensemble Averaging (REA) of Global Climate Model (GCM) rainfall projections, Bayesian approach-based population projection, and spatial analysis of projected infrastructure and Digital Elevation Models (DEMs). By seamlessly interweaving the associated datasets, we illustrate the intricacies of flood vulnerability, exposure, and frequency across multiple return periods (2, 5, 10, and 100, 200 and 500 year) leading to the creation of diagnostic and prognostic high-resolution flood risk maps. The resultant flood analytics and analyses shown that around 36 % of the villages/municipalities and between 70 and 80 % of the critical facilities like schools, hospitals, and flood relief camps are falling under high-risk zones, for the 100-year return period flood. This finding is in line with Kerala's devastating flood episode in 2018, which exhibited characteristics of a nearly 100-year return period flood. In light of a changing climate, population growth, and shifting landscapes, these approaches provide a roadmap for more informed decision-making and adaptive flood risk management measures.

A deep-level decomposed model to accelerate hydraulic simulations in large water distribution networks

As the size of water distribution network (WDN) models continues to grow, developing and applying real-time models or digital twins to simulate hydraulic behaviors in large-scale WDNs is becoming increasingly challenging. The long response time incurred when performing multiple hydraulic simulations in large-scale WDNs can no longer meet the current requirements for the efficient and real-time application of WDN models. To address this issue, there is a rising interest in accelerating hydraulic calculations in WDN models by integrating new model structures with abundant computational resources and mature parallel computing frameworks. This paper presents a novel and efficient framework for steady-state hydraulic calculations, comprising a joint topology-calculation decomposition method that decomposes the hydraulic calculation process and a high-performance decomposed gradient algorithm that integrates with parallel computation. Tests in four WDNs of different sizes with 8 to 85,118 nodes demonstrate that the framework maintains high calculation accuracy consistent with EPANET and can reduce calculation time by up to 51.93 % compared to EPANET in the largest WDN model. Further investigation found that factors affecting the acceleration include the decomposition level, consistency of sub-model sizes and sub-model structures. The framework aims to help develop rapid-responding models for large-scale WDNs and improve their efficiency in integrating multiple application algorithms, thereby supporting the water supply industry in achieving more adaptive and intelligent management of large-scale WDNs.

Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment

AbstractQuantifying flood risk depends on accurate probability estimation, which is challenging due to non‐stationarity and the combined effects of multiple factors in a changing environment. The threat of compound flood risks may spread from coastal areas to inland basins, which have received less attention. In this study, a framework based on time‐varying copulas was introduced for the treatment of compound flood risk and bivariate design in non‐stationary environments. Archimedean copulas were developed to diagnose the non‐stationary trends of flood risk. Return periods, average annual reliabilities, and bivariate designs were estimated. Model uncertainty was analyzed by comparing the results for stationary and non‐stationary conditions. The case study investigated the extreme rainfall and water level series from the Qinhuai River Basin and the Yangtze River in China. The results showed that marginal distributions and correlations are non‐stationary in all bivariate combinations. Ignoring composite effects may lead to inappropriate quantification of flood risk. Excluding non‐stationarity may lead to risk over or underestimation. It showed the limitations of the 1‐day scale and quantified the uncertainty of non‐stationary models. This study provided a flood risk assessment framework in a changing environment and a risk‐based design technique, which is essential for climate change adaptation and water management.

Spruce suffers most from drought at low elevations in the Carpathians, though shows high resilience

More frequent and severe droughts have affected forest ecosystems throughout Europe in recent decades. In Central Europe, large-scale dieback of Norway spruce has, for example, been observed, whereas Norway spruce decline was so far less widespread in Eastern Europe. To assess the potential future impacts of drought on Norway spruce in the southeastern part of its natural distribution, studies on drought resilience are urgently needed. Here, we use a tree-ring network consisting of more than 3000 trees from 158 managed Norway spruce stands of different ages distributed along elevational gradients in the Eastern Carpathians to assess growth responses to drought. Specifically, we analyzed differences in resilience components (e.g., resistance, recovery, resilience, recovery period) with elevation and tree age, and used the ‘line of full resilience’ concept to comprehensively assess drought resilience. Our results show that Norway spruce at low elevations (<800 m) is characterized by the lowest resistance to drought, though has a high recovery, while at high elevations (>1400 m), a higher resistance is associated with a low recovery. In general, older trees were found to need more time to recover. Resilience decreases with a higher water deficit, suggesting that Norway spruce is at risk in the Carpathians with ongoing climate change, urging the need for adaptative forest management.