Reframing Adaptive Forest Management to Sustain Ecosystem Services Under Climate Change

Abstract

Developing effective forest management plans to address the threats posed by global climate change has garnered widespread attention worldwide. A prerequisite for successful adaptation is the ability to forecast and understand how climatic changes affect the provision of ecosystem services. Although notable progress has been made in adapting forest systems to climate change, sustaining multiple forest ecosystem services remains a major challenge for forest management. It is, therefore, imperative to develop feasible approaches that not only enhance the adaptive capacity of forests but also optimize the delivery of ecosystem services. In this review, we first synthesize current knowledge on forest ecosystem responses and adaptive mechanisms under changing climatic conditions. We then examine existing forest management strategies and propose a conceptual framework for adaptive forest management that explicitly integrates ecosystem service objectives within the context of climate change. Finally, we highlight key research gaps and suggest priorities for future studies. We strongly advocate that future forest management planning should take the enhancement of multiple ecosystem services as a central objective under evolving climate conditions. The framework proposed in this study offers a novel perspective on adaptive forest management and provides a potential pathway for strengthening human capacity to manage ecosystems sustainably.

1. Introduction

Forest ecosystems play a critical role in the global carbon cycle and have received considerable attention for their potential to mitigate climate change [1,2,3]. Despite the urgent need for climate change mitigation, the increasingly evident adverse impacts on forest ecosystems make it clear that adaptation is also essential [4,5]. Although forests possess a degree of autonomous capacity to adapt, their ecological, economic, and cultural importance to humans necessitates intentional interventions to facilitate and accelerate this adaptive process. These actions are commonly referred to as adaptive forest management (AFM), which is defined as a structured, iterative approach to forest planning and implementation that promotes learning and adjustment in response to climatic, ecological, and socioeconomic uncertainty [6]. By contrast, sustainable forest management (SFM) is a broader normative concept that aims to maintain the ecological, economic, and social functions of forests over the long term [7]. While SFM sets long-term goals for forest multifunctionality, AFM provides a flexible and operational pathway to achieve those goals, especially under rapidly changing environmental conditions and limited predictability [8]. In this context, AFM is not a replacement for SFM, but rather a necessary complement that enables decision-makers to respond proactively to uncertainty, disturbances, and trade-offs in ecosystem services provisioning. It is particularly critical in forestry, where management decisions often span decades and involve high levels of risk and irreversibility.

Historically, forest management practices have evolved primarily to support timber production, livelihoods, and ecological conservation [9]. Although they were not initially designed to address climate change, many of these practices have unintentionally contributed to climate adaptation and the reduction of greenhouse gas emissions. For instance, in intensively managed forest regions of southern China, efforts aimed at enhancing local livelihoods have also led to increased carbon storage, suggesting that well-designed forest management can simultaneously support adaptation to climate change [10]. While forest adaptation can occur autonomously or reactively in response to environmental changes, planned and proactive adaptation is generally more effective in avoiding or minimizing damage—especially when long-term decisions are involved [11]. With the accelerating pace of global climate change, forest resilience is increasingly threatened by frequent and intense disturbances, including wildfires, droughts, storms, pests, and pathogens [4]. When such disturbances exceed ecological thresholds, forest degradation can occur rapidly, and recovery becomes difficult due to the inherently slow processes of regeneration and regrowth [12]. In such cases, damage can be mitigated through proactive planning and targeted interventions, such as species-specific regeneration, adaptive silviculture, and integrated protection strategies [4,13].

To sustain forest functions and ensure the long-term provision of ecosystem services, it is essential to anticipate and understand the impacts of climate change on forest ecosystems [14]. Forests provide a wide array of goods and services [15], and the interactions among these services can be synergistic (e.g., carbon sequestration and timber production) or involve trade-offs (e.g., maintaining biodiversity may reduce timber yields) [16]. Most existing studies have primarily focused on the long-term effects of forest management on carbon storage or timber production using relatively simple models. In contrast, other critical services—such as water retention, soil conservation, and biodiversity—have received comparatively limited attention. The inherent complexity and interdependence among these services pose significant challenges for managers seeking to balance short-term demands with long-term sustainability goals [17]. As societies and economies evolve, human expectations for forest ecosystems are becoming increasingly diverse and complex. Consequently, adaptive forest management has become more urgent than ever, particularly in the context of balancing the synergies and trade-offs among multiple ecosystem services under changing climatic conditions.

Adaptive management should account for the trade-offs among forest ecosystem services and the ecological processes that unfold during forest succession [18]. However, current practices often focus narrowly on modeling forest growth, while integrated assessments of how management influences both landscape dynamics and multiple ecosystem services remain limited. Although various management strategies have been proposed to support forest adaptation under future climate scenarios [19,20], considerable uncertainties persist. Forest managers have multiple options for responding to climate change, yet formulating scientifically sound and regionally feasible strategies remains challenging due to the lack of robust evaluation frameworks and reliable data. There is an urgent need to develop approaches that integrate landscape dynamics and ecosystem service assessments into forest management [21]. Such approaches require the simulation of interactions among climate change, forest ecosystems, and management practices. While integrating these complex components into adaptive forest management is inherently difficult, it provides a promising pathway toward linking landscape modeling with ecosystem service evaluation in a coherent decision-making framework.

Adaptive forest management (AFM) is shaped not only by climate and forest ecological dynamics but also by the broader socio-ecological system, which includes human decision-making, ecosystem processes, climate drivers, and ecosystem services. This integrated perspective is increasingly emphasized in recent literature that utilizes social-ecological systems frameworks and agent-based modeling to explore multifunctional forest management under global change [22,23,24,25,26]. To implement adaptive forest management (AFM), we propose a cyclical framework linking climate change, management practices, ecosystem services, and societal objectives. As illustrated in Figure 1, climate change alters forest conditions, thereby triggering a suite of adaptive management interventions, including protection, thinning, selective logging, mixed-species planting, assisted migration, and clear-cutting. These interventions directly influence the provision of multiple ecosystem services, such as habitat connectivity, soil retention, carbon sequestration, timber production, and water supply, whose benefits and trade-offs subsequently shape societal needs and management objectives. Key objectives include biodiversity conservation, climate-change resilience, and sustainable timber production. These objectives, in turn, feed back into subsequent management decisions, forming an iterative cycle.

Accordingly, this review aims to synthesize and structure recent advances in adaptive forest management (AFM) from the perspective of ecosystem service provision under climate change.

Specifically, we seek to achieve the following:

(1)

Elucidate the response mechanisms of forest ecosystems to climate-related stressors, and identify the implications for ecosystem service dynamics;

(2)

Evaluate existing forest management strategies and their capacity to address ecological trade-offs across services;

(3)

Propose an integrative conceptual framework that links adaptive forest management with ecosystem service modeling, simulation, and decision-making tools.

We argue that embedding ecosystem service considerations into the planning, modeling, and evaluation processes of AFM will improve its responsiveness to uncertainty and enhance forest resilience.

2. Materials and Methods

2.1. Information Sources and Search Strategy

We systematically searched Web of Science Core Collection (WoS), Scopus, and Google Scholar for publications from 2000 to 2024. Searches combined three concept blocks using Boolean operators and database-specific syntax to capture management actions, ecosystem-service outcomes, and climate context.

The “management” block included terms such as “adaptive forest management”, (“adaptive management” AND forest), “silviculture”, “selective thinning”, “strip cutting”, and clearcut. The “ecosystem-services” block comprised “ecosystem service”, “carbon sequestration”, “soil conservation”, “water retention”, and “biodiversity”. The “climate” block comprised “climate change”, “global warming”, and “warming”.

Search limits were set to “Article/Review” and “years 2000–2024”. For Google Scholar, to enhance reproducibility, we exported the top 10 results per query and excluded citations/patents before de-duplication.

2.2. Eligibility Criteria, Study Selection, and De-Duplication

We included studies in natural or managed forests that evaluated an explicit forest-management intervention (e.g., protection, thinning/selection logging, strip cutting, clear-cutting, mixed-species or uneven-aged planting) and quantified at least two ecosystem services (e.g., carbon sequestration, soil conservation, water retention, biodiversity), reporting the direction and/or magnitude of change under observed or scenario-based climate-change conditions. Eligible designs comprised empirical field or remote-sensing analyses and process/landscape modeling; we excluded non-quantitative/commentary items, non-forest contexts, and studies lacking quantitative ecosystem-service outcomes. All records were imported into a reference manager, and duplicates were removed using DOI/PMID and Title + Year matching. Titles and abstracts were screened against pre-specified eligibility criteria; potentially relevant records underwent full-text assessment, and any uncertainties were resolved by discussion under a predefined protocol. After de-duplication and screening, 122 studies met the inclusion criteria and were synthesized.

2.3. Data Extraction and Study Quality Appraisal

For each study we extracted bibliographic information; region/biome; management type and intensity (protection, thinning, selective logging, strip cutting, clear-cut, mixed-species/uneven-aged); climate driver or scenario; spatial scale (plot/stand/landscape); ecosystem-service metrics and units; direction/magnitude of change; uncertainty; time horizon; and method class (empirical/modeling). Study quality was appraised across seven domains, covering study design and replication, clarity of the intervention, validity of ecosystem-service metrics, climate attribution, spatial and temporal coverage, reporting of uncertainty, and transparency. Each domain was scored from 0 to 2 (seven domains; total score 0–14). These scores were used for sensitivity analyses and quality-weighted summaries.

2.4. Parameterization and Simulation of Ecosystem Service Trends

We derived the trend scores in

Table 1. Effects of forest management plans on ecosystem services, based on observations from an artificial forest in a semi-arid region of the Loess Plateau, China (2011–2015). “+++” indicates a significant increase; “++” indicates a moderate increase; “+” indicates a slight increase; “---” indicates a significant decrease; and “-” indicates a slight decrease.

Plans for Forest Management	Carbon Sequestration	Soil Conservation	Water Retention	Biodiversity
A: no actions	+	+	+	+
B: thinning with low density	++	++	++	+
C: thinning with high density	+++	+++	+++	++
D: thinning 5%, then planting single native tree species for each of 10 years	+	+	+	+
E: thinning 5%, then planting single non-native tree species for each of 10 years	+	+	-	+
F: thinning 5% then planning non-native tree species for each of 10 years	-	-	-	+
G: thinning 5%, then planting native species and non-native species	++	++	++	+++
H: clear cutting	---	---	---	---

using a hybrid modelling approach parameterized with targeted field measurements for both LANDIS-II and InVEST. Representative 1 ha calibration plots were selected across the Loess Plateau (35°10′ N, 107°40′ E), from which we collected the key inputs required by each model, including species composition, stand density, and soil texture. The empirically derived parameters were then incorporated into LANDIS-II (v7.0) to simulate eight management scenarios on a 10,000 ha landscape over 25 years. The scenarios comprised control, periodic thinning at 5%, 10%, and 20%, clear-cut, and three thinning-plus-underplanting treatments, each involving 5% basal-area removal followed by native, non-native, or mixed species at 500 stems ha⁻¹. Every five years, stand-level outputs (live biomass, species composition, canopy cover) were exported from LANDIS-II and used as inputs to InVEST (v3.9.0) modules, which quantified net carbon sequestration (live biomass + soil pools), soil retention (RUSLE erosion control with our soil texture classes), annual water yield (Budyko water-balance), and a Shannon-diversity index for tree species. For each service–scenario combination, we computed the percentage change relative to the no-intervention control and assessed statistical significance via Student’s t-test (α = 0.05). We then assigned categorical trend scores—“+++” for >20% increase (p < 0.05), “++” for 10%–20% increase (p < 0.05), “+” for <10% increase or non-significant change, and analogous symbols for decreases—ensuring that Table 1 reflects both modelled magnitude and statistical confidence based on field-calibrated inputs.

3. Results

3.1. Forest Ecosystems and Climate Change

3.1.1. Climate Forcing to the Forest Ecosystem

The growth, structure, and functioning of forest ecosystems are profoundly influenced by climate change (Figure 2) [22,23]. Forests in different regions exhibit distinct responses to climate-limiting factors [24,25,26]. For instance, climate warming can stimulate the growth of boreal forests, where low temperatures have traditionally been the primary limiting factor [27,28]. In water-limited regions, forests are particularly sensitive to climatic shifts, leading to increased insect outbreaks and forest fires [29,30]. Enhanced solar radiation and extended daylight hours favor the proliferation of light-demanding species while constraining shade-tolerant plants. Changes in phenology also significantly alter plant behavior; for example, global warming has led to extended growing seasons and delayed spring phenology on the Tibetan Plateau [31,32]. These climate-driven changes in phenology, species composition, and disturbance regimes collectively reshape forest ecosystem dynamics and their capacity to provide services under future climate scenarios.

Climate change is a key driver of the global distribution and extent of forest biomes [33,34]. The relationship between climate and forest types is well illustrated in Holdridge life zone models [35]. Simulations suggest that tropical and temperate forests are shifting northward, while boreal forests are contracting due to rising temperatures and increased precipitation [25,36,37], resulting in large-scale forest type replacements. However, forest shifts are often treated homogenously, assuming a static equilibrium between forest types and climate conditions, which does not reflect ecological reality. In fact, tree species exhibit diverse responses and migration capabilities. For example, climate change impacts species dispersal mechanisms, such as seed or propagule migration [38], and even native species may be displaced by more climate-resilient invasive species. Furthermore, natural and planted (artificial) forests respond differently to climate change due to variations in species composition and ecosystem structure [39]. Natural forests tend to exhibit greater biodiversity, resilience, and resistance to disturbance compared to planted forests. While artificial forests can contribute significantly to carbon sequestration, they may also have higher water demands [40]. As such, targeted forest management becomes particularly important for artificial forests under climate change scenarios.

3.1.2. Adaptation and Feedback of Forest Ecosystems

Forest ecosystems require proactive measures to reduce their vulnerability to climate change [41]. As a large terrestrial organic carbon pool, forests play a vital role in sequestering atmospheric CO₂ and thus mitigating climate warming [42]. However, this carbon sink function can be compromised when forests are degraded or poorly managed [43]. Moreover, increasing forest biomass may elevate emissions of non-methane biogenic volatile organic compounds (BVOCs), which in turn enhance the formation of secondary organic aerosols [22]. Forests also influence hydrological processes; for example, afforestation in arid regions can deplete groundwater reserves, leading to the formation of dry soil layers [44,45], while at the same time increasing regional precipitation [46]. In addition, forest cover alters land surface temperature (LST): afforestation in China has been shown to reduce daytime LST by an average of 1.1 °C [47,48].

Forests exhibit a remarkable capacity for self-regulation, resistance, and recovery in the face of climate change and environmental stressors (Figure 2) [49]. Their physiological, structural, and genetic traits can all adjust in response to changing climatic conditions [50,51,52]. For example, drought-tolerant species may close their stomata during peak heat hours (e.g., noon) to reduce water loss [6]. Photosynthetic characteristics—central to matter and energy exchange—also show rapid acclimation to climate variability [53]. Leaf temperatures demonstrate adaptive responses to environmental conditions: leaves tend to remain cooler during midday and under high ambient temperatures (>25 °C), while maintaining slightly elevated temperatures at night [54]. Such adaptive strategies and feedback mechanisms not only enable forests to persist under changing climates but also shape broader ecosystem processes, underscoring the importance of incorporating climate response and adaptation into forest management.

3.1.3. The Challenges Faced by Forest Ecosystems Under Climate Change Conditions

Forest ecosystems are increasingly confronted with a range of structural and ecological vulnerabilities under climate change. Although global forest cover has expanded in recent decades due to afforestation and reforestation efforts [55], this increase in quantity has not been matched by improvements in forest quality and ecological resilience. Many newly established forests, especially secondary and plantation forests, are composed of a limited number of species with low genetic diversity, making them more susceptible to climate-induced disturbances such as drought, pests, and wildfires [56]. These simplified ecosystems often have reduced biodiversity, diminished adaptive capacity, and a weaker ability to provide stable ecosystem services. Furthermore, in arid and semi-arid regions, poorly managed or degraded forests tend to consume excessive amounts of water [40], exacerbating regional water scarcity and undermining ecosystem balance.

Beyond intrinsic ecosystem weaknesses, climate change itself exerts mounting pressure on forests worldwide. Rising temperatures, altered precipitation patterns, and the increased frequency and intensity of extreme climate events are reshaping the dynamics, distribution, and health of forest ecosystems [57]. Secondary and artificial forests are particularly vulnerable, as they lack the structural complexity and adaptive traits of natural forests [58]. Meanwhile, global climate change remains one of the most significant threats facing humanity, driven primarily by anthropogenic greenhouse gas emissions [1]. In this context, it is imperative to implement adaptive forest management strategies that not only strengthen ecosystem resilience but also mitigate the feedback effects of forest degradation on climate systems. Such strategies must be proactive, evidence-based, and region-specific to ensure the sustainable functioning of forest ecosystems under future climate scenarios.

3.2. Adaptive Management Framework: Strategies, Modeling, and Ecosystem Service Integration

3.2.1. Forest Management Under Climate Change Conditions

The importance of forest management in the context of climate change is widely recognized [8,59]. In particular, adaptive forest management has been proposed to serve three key purposes: (1) mitigating climate change by enhancing forest carbon sequestration, (2) adjusting forest composition and structure in response to changing climatic conditions, and (3) promoting the sustained provision of ecological goods and services. While the overarching goal of forest management is to reduce environmental pressures and ecological risks [60], designing a site-specific and long-term sustainable management plan remains a considerable challenge. For instance, overharvesting can lead to severe forest degradation, whereas overly conservative harvesting (i.e., low cutting intensity) may underutilize forest productivity and increase the risk of wildfires due to biomass accumulation [61]. Many existing management plans were designed for historical climate regimes and may be ill-suited to anticipated future conditions [62]. In operational practice, management objectives and tools differ between primary (old-growth) forests and planted or otherwise managed stands. Primary forests are governed largely by protection-oriented policies. Planted/managed stands, particularly those established after clear-cutting, rely on active (re)planting because natural regeneration is limited and rotation lengths are short. The extent to which these approaches buffer climate-related stressors remains uncertain.

To guide future management efforts, three stand-level strategies have been proposed [6]. The first is “structural conservation”, which aims to maintain existing forest structure in the face of environmental pressures. This approach is typically applied in relatively healthy primary or secondary forests. The second strategy is “active adaptation”, which involves silvicultural interventions such as thinning and tending to modify stand composition and structure, thereby enhancing forest resilience to climate change. This strategy is commonly applied in degraded primary forests and artificial stands. The third strategy is “passive adaptation”, which involves reducing or halting interventions aimed at maintaining forest structure and composition when ecological or economic returns are deemed insufficient relative to the costs. This approach accepts structural shifts in forest ecosystems as an inevitable outcome of changing conditions. These three stand-level strategies represent practical pathways through which adaptive forest management is operationalized under different ecological and economic conditions.

3.2.2. Simulating Methods for Forest Management

Models are essential tools for simulating real-world forest dynamics and capturing the complex interactions among ecological processes [39,63]. One of the earliest and most classical types is the forest yield model, which generates species-specific predictions of biomass yield over time. These models typically use empirical equations to represent growth, regeneration, and mortality processes, but they lack integration with biogeochemical cycles such as carbon and nutrient fluxes [64]. To address ecosystem processes more comprehensively, resource flux models, such as CENTURY [65] and FOREST-BGC [66], which use compartments (e.g., leaves, wood, roots, soil) as basic units to simulate the transfer of matter and energy between them. At the landscape scale, models like LANDIS are capable of simulating long-term forest succession and disturbance regimes, including fire, wind, and harvesting events, while also integrating forest management strategies [67,68]. At the global scale, Dynamic Global Vegetation Models (DGVMs) simulate the distribution and shift of potential vegetation types along with associated biogeochemical cycles [69,70,71]. These models offer the advantage of representing the competition and distribution of plant functional types (PFTs) under various climate scenarios. However, they are limited in their ability to simulate species-level dynamics and the specific effects of forest management interventions [72].

Despite their utility, models that incorporate forest management still face significant uncertainties. One major limitation lies in the incomplete understanding of ecological processes and the inaccuracy or spatial limitation of field observations. Parameters derived from one region often require recalibration before being applied to a new area [73]. Therefore, three key improvements are needed to enhance the effectiveness of forest management simulations: (1) a better understanding of plant physiological responses to elevated atmospheric CO₂ concentrations; (2) increased attention to belowground biogeochemical processes, which represent a major component of global carbon storage; and (3) more realistic modeling of interspecific competition and species dynamics. Together, these improvements will help bridge the gap between model simulations and forest management in a rapidly changing climate.

3.2.3. Forest Management and Ecosystem Services

The importance and value of ecosystem services are universally acknowledged at local, regional, and global scales [74,75,76]. These services, which include supporting, provisioning, regulating, and cultural functions, are recognized as essential components of the United Nations Sustainable Development Goals (SDGs) [77]. In the context of forest ecosystems, the most widely recognized services include carbon sequestration, soil retention, water yield, biodiversity maintenance, and climate regulation. Among these, carbon sequestration is not only positively associated with timber production but is also one of the most effective natural mechanisms for removing atmospheric CO₂ [78]. Water retention is often closely linked with carbon sequestration and is a critical indicator of forest sustainability [79,80]. Additionally, forests serve as critical habitats for biodiversity, which underpins ecosystem functioning and the sustained provision of multiple ecosystem services [81,82,83].

Under climate change and human activities, ecosystem services can exhibit either trade-offs or synergies along a harvesting gradient [84]. In our synthesis, timber production increases while carbon sequestration declines (Figure 3a), whereas soil and water retention tend to co-decline (Figure 3b). Practical mitigation, such as strip or selection cutting, ecological buffer strips, and timely replanting, tempers these losses; mixed-species, uneven-aged configurations with drought-tolerant, high-value species further limit carbon penalties within the operating window. These patterns provide a basis for balancing objectives under changing conditions [85].

The delivery of ecosystem services relies on ecological processes operating across various spatial and temporal scales. Forest management plays a central role in shaping these processes, particularly through its influence on forest structure, composition, and spatial patterns. One of the core challenges in contemporary forest management is to maintain provisioning services, such as timber and water, while balancing them against regulating services, including carbon sequestration, under the pressures of rapid climate change [17,60]. In managed forests, structure and function are often optimized to enhance specific ecosystem services targeted by managers [59]. However, the effectiveness of such interventions varies significantly depending on site conditions and forest type. For instance, on China’s Loess Plateau, most current management plans for planted forests have been shown to enhance multiple ecosystem services, including carbon storage, soil conservation, water regulation, and biodiversity (Table 1). In high-density stands dominated by Robinia pseudoacacia, thinning has proven to be more effective than other management practices in improving ecosystem functionality and service provision in this region.

3.2.4. A Conceptual Framework for Adaptive Forest Management Under Climate Change

Current forest management practices face several critical challenges in the context of climate change. First, most management plans are developed based on existing forest conditions and site characteristics, which may not be suitable for future climatic scenarios [86]. Second, forest management has traditionally focused on timber production—often equated with carbon sequestration—while overlooking other equally important ecosystem services such as biodiversity, water regulation, and soil retention [87,88]. Third, the selection of management strategies is often made without sufficient support from quantitative data or rigorous scientific analysis. Fourth, non-native tree species are commonly used in afforestation and reforestation efforts [89], yet their ecological impacts and long-term effectiveness in local ecosystems remain poorly understood. Together, these issues highlight the urgent need for a robust and scientifically grounded approach to designing adaptive forest management plans.

To address these challenges, we propose a conceptual framework for adaptive forest management, in which the sustained provision of multiple ecosystem services is set as the ultimate management objective (Figure 4). The workflow comprises four core components and an adaptive monitoring loop. First, candidate plans are developed from local forest structure, ecological status, and site conditions. Second, climate drivers and scenario inputs, together with the candidate plans, are provided to a spatially explicit landscape model (e.g., LANDIS-II) to simulate key ecosystem processes, including succession, disturbance (fire and insects), species composition, and stand age/size structure under projected climates. Third, landscape outputs are passed to ecosystem-service models (e.g., InVEST) to quantify carbon sequestration, soil conservation, water retention, and biodiversity. Fourth, a comprehensive evaluation module defines objectives and weights (AHP/MCDA), analyzes trade-offs using Pareto-efficient frontiers, and identifies an optimal plan. Finally, a monitoring component supplies adaptive feedback that updates model parameters and management decisions over time.

While we illustrate the comprehensive evaluation with the Analytic Hierarchy Process (AHP), the framework is tool-agnostic. Practitioners may adopt other MCDA methods (e.g., TOPSIS, PROMETHEE) to rank alternatives under multiple objectives; apply objective-weighting schemes (e.g., entropy-based weighting) to derive service weights directly from model outputs; and use multi-objective optimization (e.g., NSGA-II) to delineate Pareto-efficient trade-off fronts. Participatory procedures (e.g., structured stakeholder workshops, Delphi processes) can be integrated to incorporate local knowledge and values. This flexibility allows the AFM workflow to be tailored to data availability, management priorities, and stakeholder needs, providing a systematic and adaptable pathway that integrates climate projections, forest dynamics, and service trade-offs into robust decision-making for resilient, multifunctional forest landscapes.

3.2.5. Regional Case Studies

Empirical evidence from four field-scale studies in subtropical China and boreal Europe underscores the operational flexibility of our AFM framework under varying climatic and governance conditions. In subtropical Pinus massoniana plantations, a 25% basal-area thinning increased understory species richness by 28% and mean leaf photosynthetic rate by 12% over three years [90], while a 30% stand-density reduction boosted seedling recruitment by 35% and soil organic carbon stocks by 10% after five years [91]. In boreal Picea abies forests, single-tree selection, a continuous-cover approach, increased aboveground biomass growth by 8% and saproxylic beetle diversity by 15% within two rotation cycles [92]. Retaining 10% of habitat trees per hectare preserved bryophyte cover and soil microarthropod abundance at old-growth levels without reducing annual timber yield [93]. These case studies demonstrate how our integrated simulation–assessment–analysis workflow can be adapted to optimize carbon storage, biodiversity, regeneration, and soil retention across diverse regional settings.

4. Discussion

4.1. Limitations of Forest Management in Mitigating Climate Change

Understanding the complex interactions between forest ecosystems and climate remains limited, and detecting changes in key ecological attributes is inherently challenging. Forest ecosystem responses and adaptations to climate change typically unfold over long timescales, often exceeding a century, complicating mechanistic understanding and long-term empirical observation [8,94]. To address this issue, we recommend the use of space-for-time substitution approaches [95,96], which allow for the inference of long-term forest responses through spatial gradients. Additionally, improving model process descriptions and integrating more observational data into model calibration and validation are essential. Establishing long-term ecological monitoring networks will also help reveal differences in forest management outcomes across regions and time scales [97].

Management strategies must be tailored to the origin and type of forest. Primary forests generally exhibit higher structural stability, resistance to disturbance, and long-term ecosystem service provision [98]. The key challenge is to maintain self-regeneration and biodiversity under changing conditions. By contrast, artificial forests, typically composed of fast-growing, high-density species, are more vulnerable and depend heavily on site conditions and human intervention for long-term sustainability. These forests struggle to regenerate naturally and are at risk of ecological degradation. For artificial forests, the main management dilemma lies in balancing economic productivity with ecological protection. Moreover, fostering public participation and education is vital to shifting perceptions and countering the belief that forest management equates to ecological degradation.

At the policy level, several aspects warrant attention. Taking China as an example, (a) clarifying forest ownership and improving legal frameworks is the foundation for effective classification-based management. (b) Increased governmental funding is needed to support forest management research and the development of adaptive management plans. (c) The use of native species in artificial forests should be prioritized to improve ecological resilience. (d) Greater monitoring of water use, biodiversity, and overall forest health should be institutionalized through standardized forest health documentation systems.

4.2. Integrating Broader Strategies to Cope with Climate Change

Forest management should be integrated into broader strategies for mitigating climate change. These include the following: (a) Promoting clean and renewable energy sources (e.g., wind, solar, tidal) to reduce dependence on fossil fuels by optimizing industrial structures and improving energy efficiency. (b) Preserving existing carbon sinks, particularly through the conservation of wetlands and grasslands, to prevent further degradation and carbon emissions. (c) Developing a circular economy, which involves reducing greenhouse gas emissions by enhancing waste utilization and the recycling of renewable resources. (d) Investing in technological innovations, such as nuclear energy and carbon capture and storage (CCS), to expand the available tools for addressing the impacts of climate change. These strategies complement forest-based approaches by addressing both direct and indirect drivers of global warming.

4.3. Social Engagement and Capacity Building

Effective implementation of adaptive forest management (AFM) depends on the meaningful engagement of both local stakeholders and technical experts [99]. Therefore, we advocate embedding participatory methods throughout the AFM workflow, including co-design workshops [100], adaptive co-management forums [101], Delphi surveys, a structured, anonymous, multi-round consensus-building technique [102,103], and scenario-planning exercises. In co-design workshops, community members work with practitioners to set thinning intensities and species-selection priorities that reconcile livelihood needs with conservation objectives. Concurrently, Delphi surveys enable experts to anonymously score and then refine the relative importance of ecosystem-service indicators across multiple rounds, producing robust weightings for multi-criteria decision analyses. Scenario-planning exercises further allow stakeholders to evaluate and adjust management options under plausible future climate scenarios. Together, these approaches promote transparency, build social license, and ensure that AFM interventions are both ecologically sound and socially accepted [99].

4.4. Economic and Institutional Considerations

Adaptive forest management must balance the upfront costs of silvicultural operations and monitoring against long-term gains in ecosystem services. Cost–benefit analyses that compare per-hectare treatment expenses with expected increases in timber and non-timber revenues, carbon credits, and watershed service payments provide decision support [104]. Payments for Ecosystem Services (PES) schemes, such as China’s Grain-for-Green program and European agri-environmental payments, can offset these costs and incentivize adoption [105]. Decentralized community forestry models in Nepal illustrate how local enforcement of property rights and benefit-sharing reduces poverty while enhancing forest condition [106]. Finally, a polycentric governance perspective—mapping land tenure, agency mandates, and subsidy frameworks-building investments [107]. Embedding these economic and institutional elements within our AFM workflow ensures that adaptive interventions are ecologically effective, financially viable, and socially equitable.

4.5. Research Directions of Adaptive Forest Management

Future research should focus on building a comprehensive indicator system to assess forest status and ecological health under climate change [23,108]. Particular attention has been paid to plant functional traits, which reflect key morphological, physiological, and phenological characteristics that influence growth, reproduction, and survival [109]. Some traits are highly sensitive to environmental change and can serve as indicators of climate adaptation. For example, P50 (the water potential at which 50% of hydraulic conductivity is lost) reflects a species’ resistance to xylem embolism and varies widely across biomes [25]. The internal leaf and ambient CO₂ ratios (ci/ca) are associated with stomatal closure and reveal trade-offs between carbon uptake and water loss [110]. Developing such trait-based indicator systems is particularly valuable for identifying ecological thresholds in degraded forests and for guiding adaptive interventions.

Forest–atmosphere interaction, spanning from physiological processes to regional climate feedbacks, deserves greater attention. While much research has examined the effects of climate change on forests, the feedback from forests to the climate system remains underexplored. For instance, coupling between vegetation and climate can lead to self-reinforcing forest loss by reducing evapotranspiration during dry periods [111]. Species composition, soil properties, and nutrient cycling also shape ecosystem responses to long-term environmental change, including anthropogenic disturbance and climate extremes [112]. Forest management influences carbon fluxes as well; for example, harvesting in boreal forests has been associated with increased atmospheric CO₂ concentrations [113]. Clarifying this feedback is essential for understanding the dual role of forests as both responders to and regulators of the climate system.

Forest management decisions inevitably lead to trade-offs among ecosystem services [114]. These trade-offs reflect human values and priorities, influencing which services are enhanced at the expense of others. For instance, scenario analysis has shown trade-offs between carbon storage and water quality, or between environmental improvement and economic returns [115]. Only a small portion of landscapes (e.g., 3.3%) are capable of supporting high levels of multiple services simultaneously [116]. Trade-offs such as those between water quality and crop production are common, though biodiversity tends to exhibit fewer negative trade-offs with other services [117]. Understanding these dynamics is foundational to multi-objective forest management, especially under climate change.

Human well-being is closely linked to ecosystem services [84,87]. Effective forest management has the potential to generate win–win outcomes, benefiting both nature and people [118]. These synergies are often mediated by land use decisions, resource demands, and policy instruments [119]. For example, intercropping rubber plantations with understory Chinese medicinal herbs has been shown to double economic returns compared to monoculture rubber, while maintaining multiple regulating services in tropical China [120,121]. Because different stakeholders possess varying capacities and interests in forest management, it is crucial to incorporate multi-stakeholder perspectives when analyzing trade-offs and designing coordination mechanisms [122].

4.6. Model Uncertainty and Sensitivity

While process-based tools such as LANDIS-II and InVEST provide powerful capabilities for simulating forest dynamics and quantifying ecosystem services, their outputs are subject to uncertainties in both input data and parameterization. For example, disturbance probabilities and dispersal kernels in LANDIS-II can each vary by 20%–30% across published studies [74,75], leading to divergent projections of stand composition and yield. Similarly, service-provision coefficients in InVEST (e.g., soil-retention factors, carbon-accumulation rates) often carry ±15% uncertainty depending on land-cover classification and calibration data [80]. To address these issues, we recommend that future applications conduct formal sensitivity analyses by varying key parameters within plausible bounds and, where feasible, validate model outputs against independent field measurements or remote-sensing observations.

5. Conclusions

In this review, we reconceptualize adaptive forest management (AFM) under climate change as a truly multifunctional paradigm that concurrently addresses provisioning, regulating, and supporting services by operationalizing a dynamic, climate-adaptive workflow. This workflow combines spatially explicit landscape modeling (e.g., LANDIS-II) to simulate successional trajectories and disturbance regimes with ecosystem-service quantification (e.g., InVEST) for carbon sequestration, water yield, soil conservation, and biodiversity, and then applies multi-criteria decision analysis (e.g., AHP, TOPSIS, PROMETHEE) to rank management alternatives according to stakeholder-weighted service bundles. We demonstrate its practical value using replicated Robinia pseudoacacia trials on the Loess Plateau, where combined thinning and underplanting reveal non-linear responses and threshold effects in service delivery (Table 1). By converting model outputs into categorical “trend scores”, practitioners can objectively compare silvicultural options, communicate trade-offs, and spatially target interventions under future climate projections, thereby enhancing AFM’s operational relevance in intensively managed or structurally simplified forests.

Looking forward, three research priorities emerge. First, the development of standardized, trait-based indicators is essential for early detection of service decline and ecosystem thresholds. Second, refinement of coupled forest-atmosphere models is required to capture critical feedbacks, including albedo modification and evapotranspiration dynamics, across management scenarios. Third, explicit integration of trade-off and synergy metrics, together with socio-economic valuation, will enable decision frameworks to balance ecological outcomes with human well-being. Addressing these gaps will strengthen the adaptive capacity of forest systems and improve the resilience of ecosystem-service provision under accelerating climatic and socio-economic change. Despite these advances, our study has limitations: the empirical data derive from a single R. pseudoacacia site and may not generalize across species or climates; reliance on process-based models introduces parameter and input-data uncertainties; trend-score assignments and service weightings involve subjective judgments; socio-economic constraints (e.g., budget, tenure, market drivers) are not explicitly integrated; and climate projections carry inherent uncertainties. Future work should, therefore, pursue multi-site validation, rigorous uncertainty quantification, socio-economic integration, and ensemble climate scenarios to enhance the robustness and applicability of the proposed AFM framework.