Next Article in Journal
Topographic Modulation of Vegetation Vigor and Moisture Condition in Mediterranean Ravine Ecosystems of Central Chile
Previous Article in Journal
The Machine-Learning-Driven Transformation of Forest Biometrics: Progress and Pathways Ahead Review
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 17
Issue 2
10.3390/f17020197
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Increasing Forest Ecosystem Resilience Is a Matter of Ecosystem Legacy Management: Conceptual Model for Restoration in Hemiboreal Forests

by
Kalev Jõgiste
1,2,*,
Lee E. Frelich
3,
Floortje Vodde
1,
Āris Jansons
1,4,
Endijs Bāders
4,
Peter B. Reich
3,5,
John A. Stanturf
1,
Sille Rebane
1,
Kajar Köster
6 and
Marek Metslaid
1
1
Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
2
Ecological Research LLC, Riia 17/63, 51010 Tartu, Estonia
3
Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N., St. Paul, MN 55108, USA
4
Latvian State Forest Research Institute “Silava”, Rīgas Iela 111, LV-2169 Salaspils, Latvia
5
Institute for Global Change Biology, School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, USA
6
Department of Environmental and Biological Sciences, University of Eastern Finland, P.O. Box 111 (Yliopistokatu 7), 80101 Joensuu, Finland
*
Author to whom correspondence should be addressed.
Forests 2026, 17(2), 197; https://doi.org/10.3390/f17020197
Submission received: 28 November 2025 / Revised: 14 January 2026 / Accepted: 30 January 2026 / Published: 2 February 2026
(This article belongs to the Section Forest Ecology and Management)
Browse Figures
Review Reports Versions Notes

Abstract

In the face of accelerating climate change and increasingly complex disturbance regimes, enhancing forest ecosystem resilience has become a core priority in forest ecology and management. This paper argues that long-term resilience in hemiboreal forests depends fundamentally on the management of ecosystem legacies—structural, compositional, and functional remnants that persist following past disturbances and land use. Organized under the resilience framework, this perspective emphasizes that resilience is not solely a matter of response or effect, but an emergent property shaped by abiotic and biotic legacies, including life history traits, landscape heterogeneity, and both anthropogenic and natural disturbance. In this paper, drawing from disturbance ecology, resilience theory, and regional empirical studies, a conceptual model is presented that integrates legacy attributes, environmental filters, and management objectives to support adaptive restoration strategies. It helps design restoration pathways that are ecologically meaningful, operationally realistic, and robust to novel disturbance regimes. By operationalizing legacy–action linkages, the model offers practitioners concrete entry points for retention, disturbance use, and landscape design to enhance resilience.

1. Introduction

Disturbance is a fundamental process in forest dynamics, altering the structure, composition, and functioning of ecosystems [1,2,3,4]. Jentsch and White [5] defined disturbance as a pulse event that disrupts ecosystem structure and resource pathways in a pattern preset by the system’s disturbance history. Building on this, Seidl and coauthors [6], as well as Seidl and Turner [7], emphasized the role of compound and interacting disturbances in reshaping forest ecosystems. Their conceptualization highlights the importance of post-disturbance reorganization, where legacy structures mediate both the direction and pace of forest development. Moreover, in addition to pulse disturbances, forest dynamics can be interpreted through the lens of press and ramp patterns that describe sustained or gradually intensifying physical modes of disturbance, exerting chronic and cumulative effects on ecosystem structure and function, concepts well-expressed in seascape ecology [8,9].
Earlier studies from the Baltic region have highlighted how ecosystem legacies from disturbances that include human impact can shape the long-term dynamics of forest ecosystems [10]. In the Baltic countries, forest ecosystem dynamics have been strongly influenced by long-term anthropogenic pressures, particularly forest management, drainage of forested wetlands, and historical land-use change. Clear-cut–based silviculture and the dominance of even-aged stands have substantially altered natural disturbance regimes, leading to simplified stand structures and reduced amounts of dead wood compared to natural and semi-natural forests [2,11]. These management-driven legacies affect species composition, functional diversity, and nutrient cycling, while also interacting with climate variability to shape recovery pathways following disturbances [12]. Consequently, resilience in Baltic forest ecosystems emerges from the interplay between historical management legacies and contemporary environmental drivers, rather than reflecting responses to natural disturbances alone [13]. In this context, resilience is understood not merely as the combination of resistance and recovery but as a property that emerges from the interaction between ecosystem legacies and environmental drivers. Several modelling approaches have been developed to integrate knowledge from observations, experiments, and earlier descriptions of forest dynamics in this region. For example, the “Newton Forest” framework introduces a process-based algorithm approach to represent ecological mechanisms and enhance our perception of natural phenomena [14]. Closely related are the functional insights gained from descriptions of plant traits and diversity, which support organization of systematic knowledge [15,16,17].
Regional research [18,19,20,21] provides conceptualization for the influence of legacy properties and land-use history on forest structure and regeneration patterns. These findings align with broader calls to enhance adaptive strategies in restoration approaches [22,23,24]. Ecosystem legacies from historic land-use remain visible in many landscapes and can be evaluated to inform and improve future management.
A key question in the planning of land-management tools and decision-making frameworks is how to define appropriate reference states within the mosaic-like distribution of natural resources. The concept of naturalness [25,26] has traditionally provided the foundation for basic guidelines, but its utility may be increasingly limited in the future [27,28].
That is because climate change (including new or altered press, ramp, and pulse disturbances of multiple kinds) introduces a transformational context for planning—one that requires a thorough analysis of historical legacy pathways and the life-history traits underlying plant functional strategies.
Here we highlight two key areas of inquiry related to ecosystem-legacy management: (1) the resilience of ecosystems in the face of novel disturbances regarding how ecosystem legacies carry adaptation to novelty, and (2) the evolving discourse on the role of ecosystem legacies in guiding management, including restoration practices and especially through influencing resilience in these changing times. Although resilience is a much-discussed term, we find the perspective from a socio-ecological system as described by Burton [29] most useful, where resistance and recovery are responses to disturbance that more or less maintain the pre-disturbance ecosystem. System responses to an altered composition (adjustment) or structure (restructuring) retain essential functioning, while transformation results in a replacement system. This concept of resilience compares well to the four disturbance responses suggested by Millar and Stephenson [30] from minimal to severe. In any case, the desirability of the ecosystem that results from transformation or severe response is determined by context and social values. At all times, we must be mindful of questions like resilience of what to what [31]?
Building on these areas/themes, this paper develops a conceptual model that links ecosystem legacy attributes, environmental filters, and management actions into a unified framework for adaptive restoration in hemiboreal forests. This model aims to clarify how the recognition and use of legacies can translate resilience theory into practical restoration pathways. The novelty of this work lies in its explicit, disturbance-oriented structuring of ecosystem legacies, providing a comparative and operational perspective for adaptive restoration.

2. Materials and Methods

This paper develops a conceptual framework for legacy-based forest restoration, grounded in the integration of disturbance ecology, resilience theory, and empirical evidence from hemiboreal forests. Rather than a systematic review, our approach follows a targeted synthesis of key studies and concepts that describe how ecosystem legacies interact with environmental variables and management actions to shape resilience outcomes.
In Northern Europe, Ahti et al. [32] and later, e.g., Hällfors et al. [33] distinguished the hemiboreal zone and referred to it as a northern biotope characterized by a predominantly coniferous forest composition with a substantial admixture of broadleaved deciduous species. They emphasized that, despite this admixture, the hemiboreal zone shares more structural and functional features with true boreal biomes than with temperate forest systems. The term “boreal–temperate forest ecotone” is also used as a North American equivalent for the European hemiboreal forest [34]. Major disturbances that threaten the forests of this zone include logging, wind, drought, fire, and insect infestation.
A literature search was conducted using the Web of Science Core Collection (all editions). The search was performed as a fielded topic query, combining the following keywords with the Boolean operator AND: ecosystem legacy, resilience, forest, disturbance, and restoration. This search strategy was designed to capture studies addressing forest ecosystem legacies in the context of disturbance processes and restoration, with explicit reference to resilience concepts. The query returned 26 records, which formed the basis for further qualitative analysis. The aim was to identify key studies that inform the conceptual relationships among ecosystem legacies, resilience mechanisms, and restoration practices. Evidence of current trends was drawn from restoration practices in hemiboreal forests, focusing on reforestation examples from both the Baltic region and the hemiboreal and temperate zones of the United States.

3. Results

This section presents the conceptual model developed in this paper, which links ecosystem legacy attributes (structural, biological, and biogeochemical) with environmental filters and management actions/strategies. The model illustrates how legacy elements pass through successive filtering processes that determine the resistance and recovery capacity of hemiboreal forest ecosystems. By integrating these filters and flows, the framework highlights three interrelated domains:
(1)
the composition and dynamics of ecosystem legacies,
(2)
the environmental filters and trajectories shaping them (legacy retention), and
(3)
the management levers (disturbance management) that can restore or enhance these legacies to support resilience. The definitions of key terms used throughout this paper are shown in Table 1.

3.1. Ecosystem Legacies

Resilience as we use it here is ecological resilience [35], best characterized by both resistance and recovery characteristics, and quantified by their combination [36]. Resilience can be conceptualized as the capacity of an ecosystem to maintain its structure and function—for forests often framed as falling within its Natural Range of Variation (NRV)—where the boundaries of this variation correspond to the “basin of attraction”—a concept widely used to describe the system’s tendency to return to a prior state following disturbance [13,37]. This return capacity is governed by ecological memory. Disturbances act as a filtering factor for ecosystem legacies, particularly by selecting among the life-history traits of legacy entities that are important for the flow of ecological information during disturbance and subsequent recovery. Response traits determine the filtering effects of major disturbances such as wind, fire, and insect infestation on foundational tree species, while the conditions set by the foundational tree species, combined with structural legacies from disturbances, are filters for the many species of diverse taxonomic groups that depend on the foundational tree species. The suites of filters present on the hemiboreal landscape differ between the historic natural disturbance regime and the current management regime dominated by harvesting [18]. This suggests that the resistance to change in forest tree species composition from historic (natural) disturbance regimes (also known as legacy lock) might be lost [38], eventually affecting the entire multi-trophic species composition. However, it also implies that: (1) restoration of natural filters is possible [39], since disturbance itself can serve as a powerful management tool, and (2) that filters imposed by management can be altered to enhance resistance and recovery after disturbance.
Biological legacies, as integral components of broader ecosystem legacies, function as conduits transferring matter and energy through time, while simultaneously undergoing ecological filtering as dynamic entities shaped by successive disturbance and recovery phases [40]. This filtering primarily directly affects the biological dimension of ecosystem legacies, where life cycle traits govern the persistence and transformation of material and informational attributes [41] that indirectly then influence their pools and fluxes. The post-disturbance pools of material legacies—including complex structural attributes such as standing and downed dead wood of varied sizes and stages of decay, pit and mound microtopography, remnant live trees—are important substrates/habitats for a variety of functionally important fungi, mosses, insects, and small mammals, as well as seedbeds for plants and tree seedlings. These structures embody the ecological memory of past processes and are critical for mediating post-disturbance development.
Therefore, biological, structural and biogeochemical legacies not only record past ecological processes but also influence the trajectory of post-disturbance reorganization within the encompassing ecosystem legacy. To fully understand the past and future trajectories of hemiboreal forests, we need to understand the temporal and spatial contexts within which these ecological legacies operate. Temporally, the “time template” of ecosystem legacy functioning determines which components are likely to persist and how they contribute to the reorganization phase (Figure 1). Illustration shows that live (α) and dead (β) biomass are filtered through successive ecological processes (ϕ1, ϕ2), during which energy (E) is released and ecosystem legacy structure is modified. Identifying which legacy components are most likely to endure disturbance provides the basis for precautionary management actions and targeted retention strategies. The first step is the condition model, which defines potential legacies. To apply this effectively, however, it must be complemented by sufficient knowledge of the following disturbance regime. The biological and structural components must be assessed for their potential to be legacies that enter the dynamic trajectory. In other words, it is necessary to first identify which parts of the forest are likely to persist. Such knowledge provides the basis for developing precautionary measures, thereby guiding subsequent decision-making in practical operations—a process that has long been standard forestry practice.
In addition to structural and biological legacies, disturbances also generate critical biogeochemical legacies that shape post-fire and post-windthrow ecosystem trajectories [42,43]. For example, fire-derived substrates, such as pyrogenic organic compounds, charred organic matter, and redistributed nutrient pools, represent a durable chemical memory of disturbance. These biogeochemical legacies can influence soil microbial composition, enzyme activity, nitrogen and phosphorus availability, and long-term carbon stabilization. Similarly, shifts in soil hydrology, thermal regimes, and oxygen availability following disturbance act as below-ground filters that determine whether microbial networks recover, reorganize, or collapse. Recognizing these biogeochemical pathways adds another dimension to the legacy concept, highlighting that resilience in hemiboreal forests relies equally on the persistence of functional soil processes and the chemical signatures left by past disturbance regimes. Land use similarly creates biogeochemical legacies, from severe soil erosion to added available phosphorous or higher pH from fertilization.
Internal consistency and transparency are important in model design. Axiomatic modeling [14] is an interesting approach to algorithm generation that provides a structured background, establishing clear starting points from which credible algorithms can be derived. This approach facilitates expressing ecological processes in logical, testable sequences. A deeper understanding of disturbance regimes allows us to recognize why certain parts of the ecosystem survive and what trajectories they follow. A first axiom emerges: biotic components of the ecosystem are inevitably subject to mortality. A second axiom states that post-disturbance, a dual system of living and non-living components merges with a shift in proportions. The non-living fraction declines, undergoing decomposition through the activity of microbial and other detritivores
Living legacies are governed by life-cycle traits that carry adaptive properties, yet disturbance alters their status, transferring biomass from the living pool to dead matter [20,44]. The flow between living and dead forest components is determined by processes that must be identified and described. Once the detrital part of the ecosystem is defined, the inputs and outputs establish the criteria for assessing its status—for example, the amount of decomposing biomass (litter, coarse woody debris—CWD), the abundance and live and dead biomass of decomposers, and the overall dynamics. In essence, changes in necromass (the total dead-biomass pool, including plant and microbial-derived carbon) are determined by the balance between organic material entering and leaving the system (Figure 2). As illustrated in Figure 2, ecosystem biomass legacies are structured by dynamic exchanges between live (α) and dead (β) biomass pools, governed by mortality (M) and disturbance-related filters (φ1, φ2, φn). Energy release (E) represents cumulative energetic losses from the system, occurring through heterotrophic respiration (R; regulated by k2) and combustion of dead biomass (Cβ; regulated by φ1 and k3), with an additional direct combustion pathway from live biomass (α → E) during fire events.
Furthermore, the types and spatial patterns of the living and dead pools may differ greatly between natural disturbances and the current harvesting regime. Natural disturbances create more heterogeneity of live and dead structures across spatial scales than commonly used harvesting practices in the hemiboreal zone, where clearfelling is the norm. Even heavy windstorms and severe fires leave a legacy of large pools of spatially complex standing and downed dead wood, fine-scale habitat diversity (pit and mound topography or patches of intact forest floor and exposed soil), and surviving mature trees, root systems, and seeds—i.e., forests are born complex after natural disturbance [45]. Less severe natural disturbances also create complex mixtures of microhabitats and live trees via gap dynamics.
This leads to axiom 3: when live tree components persist through a disturbance, the surviving stand-level structures tend to be more heterogeneous after natural disturbances and axiom 4: legacies such as dead-wood and pit-and-mound microtopography are typically more abundant and spatially complex following natural disturbances. This pattern is often accentuated in comparisons with conventionally managed stands, which are structurally more homogeneous than naturally developed forests. However, in systems with very high pre-disturbance heterogeneity, a severe stand-replacing disturbance may temporarily reduce heterogeneity, underscoring that post-disturbance structural outcomes depend both on the survival of live legacies and on the pre-disturbance baseline. At the stand scale, therefore, there are dual live and dead components, with more uniform structures after harvesting and more heterogeneous structures after natural disturbances.
Regarding the landscape context within which stands sit, natural disturbances typically create more variable structural legacy components at all scales [2,45]. Even after large-scale severe wind and fire events, untouched and partially disturbed stands remain in the landscape, in addition to within-stand and microhabitat structures [18,46,47]. In some landscapes, however, these smaller-scale legacies could be lacking, such as in forests with extensive histories of land use change, plantation forests that had undergone site preparation, or intensive harvesting including salvage logging. In those instances, species that use spatially diverse habitats after natural disturbances might not have reached older stands, so managers may have to intervene to avoid the potentially permanent loss of information legacies. In consequence, a wide range of stand ages alone is insufficient to guarantee persistence of legacies for long-term maintenance of biodiversity. Conversely, young stands in landscapes with a continuous heritage of natural disturbances can be spatially complex with surprisingly high levels of diversity.
The diversity of landforms (landscape diversity) is especially important for maintaining ecosystem legacies in hemiboreal forests. Topographic relief and aspect create variability in temperature and water balance regimes that facilitates regeneration of temperate and boreal species [48]. Even in gently rolling glaciated topography, lowlands and lower slope positions can be much cooler throughout the year [49]. This juxtaposition of warm and cool landscape positions helps with bottlenecks in response to changing climate, like seed dispersal, germination, and recruitment, allowing temperate species to expand while protecting boreal refugial areas as long as possible [50,51]. Furthermore, even microtopographic legacy features such as woody debris and pit-and-mound microtopography can help protect tree seedlings from increasing herbivore pressure and excessive heat and drought in a warming climate.

3.2. Legacy Retention

One of the key concerns in forest management is retaining or restoring legacies. Legacy management mostly pertains to secondary (with natural regeneration after clearfelling) or planted stands. Retaining legacies requires knowing the current stand condition to establish a reference point prior to management interventions and to ascertain the potential for legacy retention. Operational monitoring (including a stand exam before harvesting) characterizes the initial state and describes the basic structural components. This early phase allows projecting possible stand development trajectories and triggers silvicultural interventions needed to steer the dynamic functional process.
The secondary stands considered for legacy management developed after primary or second-growth forests were severely disturbed by human activity. On the one hand, secondary forests often have a clearly defined starting point expressed as stand age (there may be records of the year of cutting by settlers, major harvest, or abandonment of agriculture). On the other hand, their ecological legacies can vary widely, even among stands of the same age and species composition. For example, in the Great Lakes Region of North America, stands that were clearcut by settlers during winter and left to regenerate have more intact legacies than stands that were burned or farmed after cutting. Similarly, harvesting can maintain, push forward, or push backwards the successional stage of a forest stand, and its effects do not always match those of natural disturbances. Harvesting can create uniformity in structural attributes and species composition among stands, potentially homogenizing the landscape, as compared to a landscape under a natural disturbance regime [52]. Planting can be singled out as a specific mechanism whose effects on legacy dynamics are analytically distinguishable from those of broader historical disturbances.
Secondary and near-natural forests [53,54] can be managed to favor one dominant species (preventing succession) and/or harvested for several rotations before a stand transitions to a multi-aged condition, which would allow formation of many of the legacy features discussed above. Old even-aged stands are (often, but with some exceptions) most susceptible to wind, fire, and insect disturbances. Therefore, aiming for more multi-aged stands with maximum attainable diversity of tree species, sizes, and microhabitats can lead to greater future resilience [55,56]. An assessment of ecosystem legacies as real-world indicators with quantifiable metrics can build on this foundation so that scenario development can produce a fruitful array of models [47].
At this stage of the paper, we define the basic components subject to management decisions. Selective filtering is applied to identify potential legacies—those components that are recognized and designated for retention before disturbance or intervention takes place. Understanding this filtering mechanism enables the construction of an operational chain of impact factors. The impact itself arises when a disturbance agent or management intervention acts on the system.
Resilience is focused on the response characteristics [57] within the interplay of reactions to disturbance. The effects of these reactions mirror the outcome, allowing managers to assess both operational responses and potential adaptive capacity. For a complete understanding of resilience, we need to define resilience across scales, microhabitat legacies, stand structure legacies, and landscape legacies, and probably need different systems of spatial and temporal patterns of legacies in different locations—likely at the ecological section level of classification—since species composition and disturbance regimes vary.
When management intervenes, the original structural mosaic of the ecosystem is evaluated and assessed. Vegetation patterns that may become management targets include, for example, abandoned agricultural lands planned for afforestation [58]. In such cases, the deliberate management intervention (or non-intervention) is expected to create an initial structure in the vegetation and guide the system’s functions toward a new state aligned with management goals.
The result is a condition that includes partial restoration of ecological legacies. Soil, too, can be a subject of management, as physical reactions are transmitted through this environment [59,60]. Silvicultural operations such as fertilization, draining, and mechanical preparation of planting spots, or removal of specific soil layers, illustrate this process (Figure 3). In peatlands, however, the organogenic horizon may be removed during mining operations, or drainage for agriculture or forestry can accelerate the decomposition of peat, resulting in negative filtering and degradation rather than the intended restoration.
An important question in legacy management (i.e., retention and restoration) is what levels are desirable and sustainable? The NRV provides an operational approximation of ecological resilience constraints [55,61], representing the bounds within which key structural and functional attributes fluctuate under natural disturbance regimes (Figure 4). Juxtaposing the NRV with ranges observed in managed forests and those incorporating restoration interventions establishes a comparative framework for evaluating the ecological impact of management (Figure 4). It also identifies potential equivalencies across systems, thereby offering a structured basis for assessing how restoration actions may help re-align managed systems with historically resilient conditions.

3.3. Disturbance Management

Figure 4 provides a schematic overview of how key attributes of ecosystem resilience vary across three contrasting contexts: (a) natural conditions (NRV), (b) managed forests, and (c) managed forests with restoration interventions. The blue curves illustrate hypothetical temporal dynamics of individual attributes following disturbance, while the vertical bars indicate the corresponding range of variation under each context. In managed systems, both the range of variation and absolute attribute values are typically reduced relative to NRV. Restoration actions are conceptualized as interventions that selectively expand the range of variation toward NRV without fully recreating natural dynamics. The figure should be read vertically, comparing individual attributes across contexts, and horizontally, illustrating how management and restoration influence the coupled behaviour of multiple attributes within a landscape-level legacy matrix.
Disturbance management means altering the vulnerability of stands to disturbance agents, limiting the negative effects of disturbance events, and enhancing recovery. Susceptibility and vulnerability have distinct meanings in different ecological contexts, being mindful to specify resilience of what ecosystem attribute to what disturbance agent [31,62]. Susceptibility refers to the likelihood an organism will sustain negative impacts from a specific disturbance, if exposed. In contrast, vulnerability incorporates both susceptibility and likelihood of exposure to a disturbance [20,24]. Susceptibility is usually defined by traits of the organism, such as species, age, and size. Vulnerability can cover a broader domain of disturbance responses, including ecosystem adaptive capacity and potential resilience [63]. In resilience terms, disturbance management strategies include reducing the susceptibility of individual trees and avoiding or limiting exposure to disturbance events (resistance) or aiding in recovery. With the advent of restoration ecology, an additional resilience perspective emerges, where ecosystems follow strategies that may be incremental, anticipatory, or transformational in their trajectories [24,29].
Fire disturbance represents one of the greatest physical forces and energy transfers affecting ecosystems globally and likely to increase in frequency and intensity in many ecosystems [64,65]. Understanding wildfire history is foundational to the use of management tools such as prescribed fire [66,67,68,69]. The relevance of restoring historical fire regimes must also be weighed against humanitarian concerns, as fire poses significant threats to lives and property. Moreover, novel fire behaviors may emerge under changing atmospheric conditions [70,71]. However, we can also learn from Indigenous burning practices, which often involve frequent low-intensity burns conducted during non-drought weather conditions that do not favor accidental spread or high-intensity fires that are hard to control. The cumulative effects of such fires over several decades can be equivalent to a single high-intensity fire. For example, burning in red pine (Pinus resinosa Ait.) forests in northern Minnesota, USA, over several centuries maintained the red pine by preventing succession to balsam fir (Abies balsamea (L.) Mill.) and other very flammable late-successional conifers that can be ladder fuels carrying flames into the crowns of the large pines. This led to the presence of groves of very large red pines across the landscape, which would otherwise have been killed in wildfires (which would have had higher intensities), and maintained conditions for the growth of blueberries—a major food source—underneath the pines [72].
Wildfires (as well as large-scale wind throws), when they occur, can be interpreted as a part of landscape diversity that is hard to create by management, offering a novel way to view events that are often considered disasters [2]. We can learn a lot about ecological legacies from these large-scale events; they are common in forests that have adapted to them over millions of years, and forests are very good at recovering from them [13].
Vicinity to stands with fully developed ecological legacy components (e.g., reserved area with an intact forest) is important for the recovery of ecological legacies and is often linked to landscape diversity [73]. Landscapes lacking a fully developed ecological legacy component can reach a condition where most of the legacies perpetuate themselves, e.g., through transfer from adjacent stands in natural areas and restored stands. Creating such stands via management actions increases resilience, such that no stand is far away from a stand with high diversity. Furthermore, stands with microhabitats characteristic of stands with a natural disturbance regime (e.g., many patches of remnants of smaller species such as mosses and lichens on downed and standing tree trunks, small pieces of forest floor that survive fires) serve as source areas for species with poor dispersal ability [18].
Reducing exposure to disturbances, so-called pre-emptive management solutions, involves harvesting stands just before they reach maximum vulnerability to wind disturbance [74]. Similar strategies might be employed for wildfires to increase the probability of harvests occurring prior to intense fire. Salvage logging and pre-emptive management can, however, both deplete the future landscape of stands with large snags, downed coarse woody debris, and tip-up mounds [74]. A complex mixture of interactions can emerge from the combination of anthropogenic and natural disturbances such as salvage logging after disturbances [13,75]. Salvage logging remains a contested issue and the predictability of physical responses remains an urgent question [76,77].
Restoration after disturbance is a central challenge in the management paradigm. During disturbance events, life-history traits are subjected to strong filtering effects, and knowledge of such changes becomes crucial [15,78]. Elements such as seed banks, advance regeneration, and resprouting capacity, therefore, become critical survival-oriented components in the management toolbox [37,79].
The nature of disturbance is a key indicator for managing ecosystem legacies in forest landscapes. Windstorms, fires, and insect infestations generate different legacy profiles (Figure 4). In contrast to wildfires or windstorms [16,80,81], insect outbreaks generate a legacy profile with an essential ecological component of dead standing trees that contribute significantly to biomass fluxes through deadwood dynamics and decomposition [75,82,83,84]. Biodiversity concerns are often rooted in the absence of dead wood, and the flux between standing and downed dead-wood pools represents a critical dynamic that underpins their role in sustaining diversity. Clearfelling as commonly practiced in the hemiboreal zone generates a legacy profile distinct from natural disturbances with a much narrower range of variability and longer recovery times (Figure 4).

3.4. The Integrated Legacy Concept for Hemiboreal Forested Landscapes

The legacy management target would include ecologically intact legacy stands as well as less diverse stands that comprise the landscape matrix. From our review of ecosystem legacies in the hemiboreal forest landscape, we can see the true nature of the total forest legacy with interactions across spatial scales and landscape diversity. The integrated legacy concept we propose here includes spatial patterns of varied stand types at the landscape scale, stands with a variety of structures and tree composition at the stand scale, and diverse microhabitat structures within all stand types (including young even-aged stands) [2,45,48].
Incorporating the integrated legacy concept into management would require some modifications, including the ones listed below for stands with intact legacies, stands in the matrix currently under even-aged or uneven-aged management, or areas without forest legacies:
  • Intact legacy stands. Natural or restored stands with legacies similar to stands under the natural disturbance regime, with respect to the variety of tree ages, species, and microhabitats that support smaller plants, fungi, insects, and mammals [18,20,45]. These would occur systematically across the landscape to provide the full information legacy to surrounding stands [13].
    Some variants of intact legacy stands could include:
    • Natural disturbance stands after severe wind and fire disturbance, and insect infestation, and varied interactions of those disturbances [39,46,47,57]. The presence of these stands would vary over time according to the frequencies of natural disturbances.
    • Cultural stands managed according to Indigenous practices that exist(ed) in a given ecoregion. These stands were historically managed to amplify the presence of certain stand types that supported useful native species, spiritual values, and that locally lowered the intensity of wildfires; but they also added to the functional and biological diversity of the landscape [72].
    • Stands on cool or warm refugial sites in the landscape, holding the legacies of boreal and temperate species that can contract or expand with a changing climate.
  • Stands that comprise the legacy of the landscape include:
    • Even-aged stands managed to have as much tree species diversity and microhabitat structure as possible; these stands and the following stand type will also benefit over time from the proximity to intact legacy stands.
    • Uneven-aged stands managed by single tree or small group selection with attention to leaving microhabitat features intact.
  • Afforestation or restoration of severely degraded stands [85]:
    • Focus on creating multispecies stands, with a variety of mixtures
    • Restore natural disturbance regimes (e.g., fire, inundation, gap creation)
Maintaining the integrated legacy requires a continuous flow of live and dead components at all scales (Figure 3). The representation of stand types across the landscape requires constant larger disturbances, while the maintenance of age structures and species compositions of trees within stands requires smaller disturbances, and microhabitats are created by all types of disturbances. To meet this objective, managers would try to move stand structures closer to the range of natural variability for a variety of structural attributes and ecological processes, as shown in Figure 4. Although managers are adept at creating a continuous flow of even-aged stands—and, to some extent, uneven-aged stands—they are less adept at, or were not given the objective of, creating the other types of flows that maintain the integrated legacy over time.
Climate change presents both challenges and benefits for maintaining an integrated legacy during the 21st century. More windstorms, fires, insect outbreaks and droughts are expected in the hemiboreal zone [46,55]. These disturbances are traditionally viewed as having negative effects on forests; however, from an ecological legacy perspective, they may also have positive effects in maintaining the flows depicted in Figure 1 and Figure 3 and moving to conditions closer to the natural range of variability shown in Figure 4 [45,66]. For example, windstorms can greatly accelerate successional processes in early-successional stands [52], potentially including facilitating release of late-successional understory species that are adapted to a warmer climate, while also creating complex landscape structures and microhabitats [20,47]. In contrast, windstorms could also accelerate the increasing dominance of late-successional species that are not adapted to the future climate.
Fires, insect infestations, and droughts can also facilitate targeted trajectories, for example, by allowing reproduction of temperate species (e.g., Quercus or Acer) to advance relatively fast as older boreal species (e.g., Pinus, Picea, and Betula) pine, spruce and birch are eliminated by disturbances [46]. Thus, maintaining occurrences of temperate species on the landscape or adding those species to the landscape so that they can take advantage of disturbances later on is a recommended management practice for a warming climate [55]. Forest vegetation is individualistic—with landscapes having a variety of current conditions depending on landform diversity and degree of impacts of previous land use, as well as several different potential future trajectories (or frames) depending on the magnitude of climate change expected. Therefore, the analysis of positive and negative effects of climate change on future ecological legacies is also complex and individualistic.

4. Discussion

Traditionally, resilience has been viewed as an outcome—how quickly systems recover after disturbance. Here, we propose a process-based perspective, grounded in ecosystem legacies and the ways inherited structures enable renewal. In this view, resilience (i.e., resistance and recovery) depends on the continuity and interaction of legacy elements, such as living and dead biomass (e.g., standing trees and fallen logs), microhabitats (like pit-and-mound topography), seed sources, soil processes, and the biogeochemical signatures left by past disturbances. The conceptual model of integrated legacies highlights three interconnected areas: the nature of ecosystem legacies, the environmental filters that shape them, and the management actions that can restore or enhance these legacies to support ecological resilience.
Ecosystem resilience, defined as the capacity to maintain structure and function within a natural range of variation, is influenced by ecological memory and filtering through disturbances. Disturbances selectively impact ecosystem legacies, influencing life-history traits and thereby affecting recovery. The composition and dynamics of legacies, such as biological remnants and structural attributes, are vital for ecosystem functioning and recovery post-disturbance. Retaining legacies is critical to resilience and creating conditions that support development of legacies is an important aspect of forest restoration.
Maintaining the full suite of legacies relies on the ongoing transfer of biological materials, such as the cycling of live and dead wood, from microhabitats to stands with varied structures, and across landscapes with diverse disturbance histories. Additionally, biogeochemical legacies, influenced by disturbances, shape soil health and microbial dynamics crucial for ecosystem recovery. These patterns often mirror those created by natural disturbances. Comparing this flow under natural and management conditions, using the natural range of variation in components, can reveal the potential to create and maintain resilient forest stands and landscapes, as well as the limitations in doing so. This understanding can guide restoration strategies that enhance resilience in the face of climate change.
The flow of habitat features across scales will help to maintain species diversity and maximize resilience notwithstanding disturbances, forest management, and climate change. While landscapes can be envisioned as a mosaic of stands, the internal quality of each stand is crucial. Managers may sometimes assume that microhabitat features are present, but restoration efforts may be needed to recreate these features and achieve optimal landscape diversity. However, this synthesis remains conceptual, and future work should empirically test how restored microhabitat features contribute to biodiversity and resilience under varying disturbance and management regimes.
Recognizing that natural disturbances generate diverse legacy structures compared to conventional harvesting practices emphasizes the need for management that fosters ecological complexity. Management strategies involve retaining essential legacies through selective filtering and operational monitoring. The integrated management concepts encompassing intact legacy stands and diverse landscapes can enhance ecosystem resilience amidst climate change. This approach champions adaptive management that respects both historical disturbance regimes and contemporary ecological needs while also considering the potential impacts of climate change on forest dynamics.
The integrated legacy concept was developed by reviewing studies from the Baltic region that showed how ecosystem legacies developed from disturbances [10] and the influence of legacy properties and land-use history on forest structure and regeneration patterns [18,19,20,21]. Additionally, the concept was informed by insights from descriptions of plant traits and diversity [15,16,17]. This provided a foundation for modifications necessary to incorporate the integrated legacy concept into management. Although specific to maintaining existing legacy conditions or creating legacies, these modifications would benefit from further research and evaluation under operational conditions. The flow under natural and management conditions can be compared to reveal the potential to create and maintain resilient forest stands and landscapes, as well as the limitations in doing so.
Evaluating our conceptual model and its applicability to real disturbance and management contexts requires examining how its core elements can be interpreted using empirical information. Although the model is not intended as a data-driven predictive framework, it should nevertheless be able to engage with observed disturbance patterns in a transparent and interpretable way.
For example, the characteristic φ can be derived from annual fire statistics for Estonia [86]. Accordingly, φ may initially be interpreted as an indicator of fire frequency; however, fire frequency alone does not adequately represent the total area affected by fire or the associated energetic loss. Estonian data demonstrate that φ, when treated solely as a frequency-based fire characteristic, is not suitable for estimating overall fire impact on forests. Instead, φ is better interpreted as a shifting characteristic that reflects variation in the fire regime, possibly a transition toward more frequent but smaller fires as seen in recent decades. Concurrent with an overall trend of reduced fire frequency in Estonian forests, an increase in the variability of fire size is observed. This filtering effect is likely influenced by increasingly effective fire prevention and suppression measures, which alter the relationship between fire occurrence, fire size, and ecological impact.
The relationship between fire frequency and average fire size varied substantially among decades (Table 2). In the 1990s, φ1 was more strongly influenced by fire frequency, whereas in the 2000s it was dominated by a small number of high-magnitude events. In contrast, the 2010s were characterized by a strong decoupling between fire occurrence and burned area, suggesting a weakened or fragmented fire filter. These patterns illustrate how φ1 integrates both disturbance intensity and exposure opportunity, and how shifts in their balance alter biomass legacy filtering.

5. Conclusions

Ecosystem legacy management is a central mechanism for enhancing forest ecosystem resilience in hemiboreal forests under changing disturbance regimes. The conceptual framework introduced here builds on disturbance ecology and resilience theory, arguing that resilience is not merely an outcome measured by resistance or recovery speed, but an emergent property shaped by the continuity, interaction, and filtering of ecosystem legacies across spatial and temporal scales. The landscape matrix, an essential background construct, provides the spatial context for examining ecosystem dynamics through legacy detection over time.
The conceptual framework emphasizes the roles of past disturbances, land-use history, and life-history traits in constraining or enabling future ecosystem trajectories. This legacy filtering integrates biological, structural, and biogeochemical legacies with environmental filters and management actions, clarifying how disturbances and management selectively transmit ecological information through time and space, influencing recovery pathways and adaptive capacity.
A central contribution is the Integrated Legacy Concept that links stand-level and landscape-level processes by treating managed and semi-natural stands as interacting components of a landscape matrix. Using the Natural Range of Variation (NRV) as a comparative reference, the framework illustrates how management typically sets limits on the range of key resilience attributes. Within the NRV, targeted restoration actions can partially redefine this range without fully recreating natural disturbance regimes.
The model is illustrated using a semi-quantitative fire example from Estonia to demonstrate how conceptual filters can be operationalized without implying empirical validation. Overall, the framework provides a structured way to translate resilience theory into practical restoration pathways, offering managers concrete entry points for legacy retention, disturbance-based management, and landscape design aimed at sustaining resilience under climate change.
Further development of the management models for macro-level capture of ecosystem legacies could be supported by approaches that strengthen validity and realism [87]. In this context, machine learning and large language models contribute an arsenal of semantic and syntactic capabilities that enhance both precision and creative formulation [88,89,90,91,92]. Large language models can address the complexity of cross-scale interactions when these are fine-tuned and oriented toward axiomatic modeling and algorithmic structuring. Such an approach supports the development of theoretically coherent and computationally operational frameworks that enable the representation of multifaceted relationships within forest ecosystems, particularly in the context of resilience modeling [57,78]. By capturing essential assumptions and structuring key interdependencies, these tools aid in formalizing conceptual models grounded in ecological realism.

Author Contributions

Conceptualization, K.J. and L.E.F.; Methodology, K.J., L.E.F. and S.R.; Literature Analysis and Curation, K.J., L.E.F., P.B.R., E.B. and K.K.; Writing—Original Draft Preparation, K.J.; Writing—Review and Editing, K.J., L.E.F., F.V., Ā.J., E.B., P.B.R., J.A.S., S.R., K.K. and M.M.; Visualization, K.J. and F.V.; Supervision, K.J. and P.B.R.; Project Administration, K.J. and M.M.; Funding Acquisition, M.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Estonian Research Council grant number PRG1586 “Effects of forest fires on dynamics of vegetation, soil fungal community and physical chemical properties in hemiboreal forests” and by European Regional Development Fund project number EE-LV00001 “Riparian forest management based on assessment of ecosystem services”.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We thank the anonymous reviewers for their valuable comments.

Conflicts of Interest

Author Kalev Jõgiste was employed by the company Ecological Research LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. White, P.S.; Pickett, S.T.A. Natural disturbance and patch dynamics: An introduction. In The Ecology of Natural Disturbance and Patch Dynamics; Pickett, S.T.A., White, P.S., Eds.; Academic Press: New York, NY, USA, 1985; pp. 3–13. [Google Scholar] [CrossRef]
  2. Kuuluvainen, T. Forest management and biodiversity conservation based on natural ecosystem dynamics in northern Europe: The complexity challenge. Ambio 2009, 38, 309–315. [Google Scholar] [CrossRef]
  3. Travers, S.K.; Woodward, R.; Slavich, E.; McAllister, D.; Chu, N.; Lawrie, K.; Gorrod, E. Interacting contemporary and legacy disturbances affect management of floodplain forest vegetation. Basic Appl. Ecol. 2025, 90, 99–108. [Google Scholar] [CrossRef]
  4. Frank, G.S.; LaBonte, J.R.; Betts, M.G.; Kroll, A.J.; Rivers, J.W.; Verschuyl, J.; Swanson, M.E.; Krawchuk, M.A. Disturbance type shapes initial community assembly patterns of early seral forest ground beetles in southwest Oregon. For. Ecol. Manag. 2026, 602, 123395. [Google Scholar] [CrossRef]
  5. Jentsch, A.; White, P.S. A theory of pulse dynamics and disturbance in ecology. Ecology 2019, 100, e02734. [Google Scholar] [CrossRef]
  6. Seidl, R.; Fernandes, P.M.; Fonseca, T.F.; Gillet, F.; Jönsson, A.M.; Merganičová, K.; Netherer, S.; Arpaci, A.; Bontemps, J.-D.; Bugmann, H.; et al. Modelling natural disturbances in forest ecosystems: A review. Ecol. Model. 2011, 222, 903–924. [Google Scholar] [CrossRef]
  7. Seidl, R.; Turner, M.G. Post-disturbance reorganization of forest ecosystems in a changing world. Proc. Natl. Acad. Sci. USA 2022, 119, e2202190119. [Google Scholar] [CrossRef]
  8. Lake, P.S. Disturbance, patchiness, and diversity in streams. J. N. Am. Benthol. Soc. 2000, 19, 573–592. [Google Scholar] [CrossRef]
  9. Jackson, E.L.; Santos-Corujo, R.O.; Pittman, S.J. Seascape patch dynamics. In Seascape Ecology; Pittman, S.J., Ed.; John Wiley & Sons: Hoboken, NJ, USA, 2017; pp. 153–188. [Google Scholar]
  10. Palang, H.; Mander, Ü.; Luud, A. Landscape diversity changes in Estonia. Lands Urban Plan. 1998, 41, 163–169. [Google Scholar] [CrossRef]
  11. Lindenmayer, D.B.; Franklin, J.F.; Fisher, J. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conserv. 2006, 131, 433–445. [Google Scholar] [CrossRef]
  12. Seidl, R.; Thom, D.; Kautz, M.; Martin-Benito, D.; Peltoniemi, M.; Vacchiano, G.; Wild, J.; Ascoli, D.; Petr, M.; Honkaniemi, J.; et al. Forest disturbances under climate change. Nat. Clim. Chang. 2017, 7, 395–402. [Google Scholar] [CrossRef] [PubMed]
  13. Johnstone, J.F.; Allen, C.D.; Franklin, J.F.; Frelich, L.E.; Harvey, B.J.; Higuera, P.E.; Mack, M.C.; Meentemeyer, R.K.; Metz, M.R.; Perry, G.L.W.; et al. Changing disturbance regimes, ecological memory, and forest resilience. Front. Ecol. Environ. 2016, 14, 369–378. [Google Scholar] [CrossRef]
  14. Hari, P.; Bäck, J.; Heliövaara, K.; Kerminen, V.-M.; Kulmala, L.; Mäkelä, A.; Nikinmaa, E.; Petäjä, T.; Kulmala, M. Towards quantitative ecology: Newton’s principia revisited. Boreal Environ. Res. 2014, 19, 142–152. Available online: http://hdl.handle.net/10138/228733 (accessed on 29 January 2026).
  15. Bruelheide, H.; Dengler, J.; Purschke, O.; Lenoir, J.; Jiménez-Alfaro, B.; Hennekens, S.M.; Botta-Dukát, Z.; Chytrý, M.; Field, R.; Jansen, F.; et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evol. 2018, 2, 1906–1917. [Google Scholar] [CrossRef]
  16. Díaz, S.; Hodgson, J.G.; Thompson, K.; Cabido, M.; Cornelissen, J.H.C.; Jalili, A.; Montserrat-Martí, G.; Grime, J.P.; Zarrinkamar, F.; Asri, Y.; et al. The plant traits that drive ecosystems: Evidence from three continents. J. Veg. Sci. 2004, 15, 295–304. [Google Scholar] [CrossRef]
  17. Dee, L.E.; Miller, S.J.; Helmstedt, K.J.; Boersma, K.S.; Polasky, S.; Reich, P.B. Quantifying disturbance effects on ecosystem services in a changing climate. Nat. Ecol. Evol. 2025, 9, 436–447. [Google Scholar] [CrossRef]
  18. Jõgiste, K.; Korjus, H.; Stanturf, J.A.; Frelich, L.E.; Baders, E.; Donis, J.; Jansons, A.; Kangur, A.; Köster, K.; Laarmann, D.; et al. Hemiboreal forest: Natural disturbances and the importance of ecosystem legacies to management. Ecosphere 2017, 8, e01706. [Google Scholar] [CrossRef]
  19. Paal, J.; Turb, M.; Köster, T.; Rajandu, E.; Liira, J. Forest land-use history affects the species composition and soil properties of old-aged hillock forests in Estonia. J. For. Res. 2011, 16, 244–252. [Google Scholar] [CrossRef]
  20. Palm-Hellenurm, K.; Bāders, E.; Frelich, L.E.; Köster, K.; Metslaid, M.; Polyachenko, O.; Seedre, M.; Shorohova, E.; Stanturf, J.A.; Vodde, F.; et al. The fate of remnant trees after wind disturbances in boreal and temperate forests. Front. For. Glob. Change 2024, 7, 1405430. [Google Scholar] [CrossRef]
  21. Bāders, E.; Jõgiste, K.; Elferts, D.; Vodde, F.; Kiviste, A.; Luguza, S.; Jansons, Ā. Storm legacies shaping post-windthrow forest regeneration: Learnings from spatial indices in unmanaged Norway spruce stands. Eur. J. For. Res. 2021, 140, 819–833. [Google Scholar] [CrossRef]
  22. Beatty, S.W.; Owen, B.S. Incorporating disturbance into forest restoration. In Restoration of Boreal and Temperate Forests; Stanturf, J.A., Madsen, P., Eds.; CRC Press: Boca Raton, FL, USA, 2005; Chapter 4; pp. 61–72. [Google Scholar]
  23. Kates, R.W.; Travis, W.R.; Wilbanks, T.J. Transformational adaptation when incremental adaptations to climate change are insufficient. Proc. Natl. Acad. Sci. USA 2012, 109, 7156–7161. [Google Scholar] [CrossRef]
  24. Stanturf, J.A.; Madsen, P.; Sagheb-Talebi, K.; Hansen, O.K. Transformational restoration: Novel ecosystems in Denmark. Plant Biosyst. 2018, 152, 536–546. [Google Scholar] [CrossRef]
  25. Çolak, A.H.; Rotherham, I.D.; Çalikoglu, M. Combining ‘naturalness concepts’ with close-to-nature silviculture. Forstwiss. Centralbl 2003, 122, 421–431. [Google Scholar] [CrossRef]
  26. Brūmelis, G.; Jonsson, B.G.; Kouki, J.; Kuuluvainen, T.; Shorohova, E. Forest naturalness in Northern Europe: Perspectives on processes, structures and species diversity. Silva Fenn. 2011, 45, 807–821. [Google Scholar] [CrossRef]
  27. Millar, C.I.; Stephenson, N.L.; Stephens, S.L. Climate change and forests of the future: Managing in the face of uncertainty. Ecol. Appl. 2007, 17, 2145–2151. [Google Scholar] [CrossRef]
  28. Williams, J.W.; Jackson, S.T. Novel climates, no-analog communities, and ecological surprises. Front. Ecol. Environ. 2007, 5, 475–482. [Google Scholar] [CrossRef]
  29. Burton, P.J. Resilient Forest Management; Oxford University Press: Oxford, UK, 2025; 400p. [Google Scholar]
  30. Millar, C.I.; Stephenson, N.L. Temperate forest health in an era of emerging megadisturbance. Science 2015, 349, 823–826. [Google Scholar] [CrossRef]
  31. Carpenter, S.; Walker, B.; Anderies, J.M.; Abel, N. From metaphor to measurement: Resilience of what to what? Ecosystems 2001, 4, 765–781. [Google Scholar] [CrossRef]
  32. Ahti, T.; Hämet-Ahti, L.; Jalas, J. Vegetation zones and their sections in northwestern Europe. Ann. Bot. Fenn. 1968, 5, 169–211. Available online: https://www.jstor.org/stable/23724233 (accessed on 29 January 2026).
  33. Hällfors, M.H.; Lindén, L.; Rita, H.; Schulman, L.E. Using a botanic garden collection to test a bioclimatic hypothesis. Biodivers. Conserv. 2011, 20, 259–275. [Google Scholar] [CrossRef]
  34. Evans, P.; Brown, C.D. The boreal–temperate forest ecotone response to climate change. Environ. Rev. 2017, 25, 423–431. [Google Scholar] [CrossRef]
  35. Gunderson, L.H. Ecological resilience—In theory and application. Ann. Rev. Ecol. Syst. 2000, 31, 425–439. [Google Scholar] [CrossRef]
  36. Sterk, M.; Gort, G.; Klimkowska, A.; van Ruijven, J.; van Teeffelen, A.J.A.; Wamelink, G.W.W. Assess ecosystem resilience: Linking response and effect traits to environmental variability. Ecol. Indic. 2013, 30, 21–27. [Google Scholar] [CrossRef]
  37. Nikinmaa, L.; Lindner, M.; Cantarello, E.; Jump, A.S.; Seidl, R.; Winkel, G.; Muys, B. Reviewing the use of resilience concepts in forest sciences. Curr. For. Rep. 2020, 6, 61–80. [Google Scholar] [CrossRef] [PubMed]
  38. Johnstone, J.F.; Hollingsworth, T.N.; Chapin, F.S., III; Mack, M.C. Changes in fire regime break the legacy lock on successional trajectories in Alaskan boreal forest. Glob. Change Biol. 2010, 16, 1281–1295. [Google Scholar] [CrossRef]
  39. Reed, S.P.; Royo, A.A.; Carson, W.P.; Olmsted, C.F.; Frelich, L.E.; Reich, P.B. Multiple disturbances, multiple legacies: Fire, canopy gaps and deer jointly change the forest seed bank. J. Ecol. 2025, 113, 353–370. [Google Scholar] [CrossRef]
  40. Gauthier, S.; Vaillancourt, M.-A.; Kneeshaw, D.; Drapeau, P.; De Grandpré, L.; Claveau, Y.; Paré, D. Forest ecosystem management: Origins and foundations. In Ecosystem Management in the Boreal Forest; Gauthier, S., Vaillancourt, M.-A., Leduc, A., De Grandpré, L., Kneeshaw, D., Morin, H., Drapeau, P., Bergeron, Y., Eds.; Presses de l’Université du Québec: Quebec, QC, Canada, 2009; pp. 13–39. [Google Scholar]
  41. Hughes, T.P.; Kerry, J.T.; Connolly, S.R.; Baird, A.H.; Eakin, C.M.; Heron, S.F.; Hoey, A.S.; Hoogenboom, M.O.; Jacobson, M.; Liu, G.; et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat. Clim. Chang. 2019, 9, 40–43. [Google Scholar] [CrossRef]
  42. Nave, L.E.; Gough, C.M.; Maurer, K.D.; Bohrer, G.; Hardiman, B.S.; Le Moine, J.; Munoz, A.B.; Nadelhoffer, K.J.; Sparks, J.P.; Strahm, B.D.; et al. Disturbance and the resilience of coupled carbon and nitrogen cycling in a north temperate forest. J. Geophys. Res. 2011, 116, G04016. [Google Scholar] [CrossRef]
  43. McLauchlan, K.K.; Higuera, P.E.; Gavin, D.G.; Perakis, S.S.; Mack, M.C.; Alexander, H.; Battles, J.; Biondi, F.; Buma, B.; Colombaroli, D.; et al. Reconstructing disturbances and their biogeochemical consequences over multiple timescales. BioScience 2014, 64, 105–116. [Google Scholar] [CrossRef]
  44. Seidl, R.; Rammer, W.; Spies, T.A. Disturbance legacies increase the resilience of forest ecosystem structure, composition, and functioning. Ecol. Appl. 2014, 24, 2063–2077. [Google Scholar] [CrossRef]
  45. Donato, D.C.; Campbell, J.L.; Franklin, J.F. Multiple successional pathways and precocity in forest development: Can some forests be born complex? J. Veg. Sci. 2012, 23, 576–584. [Google Scholar] [CrossRef]
  46. Anoszko, E.; Frelich, L.E.; Rich, R.L.; Reich, P.B. Wind and fire: Rapid shifts in tree community composition following multiple disturbances in the southern boreal forest. Ecosphere 2022, 13, e3952. [Google Scholar] [CrossRef]
  47. Peterson, C.J. Damage diversity as a metric of structural complexity after forest wind disturbance. Forests 2019, 10, 85. [Google Scholar] [CrossRef]
  48. Anderson, M.G.; Clark, M.; Olivero Sheldon, A. Estimating climate resilience for conservation across geophysical settings. Conserv. Biol. 2014, 28, 959–970. [Google Scholar] [CrossRef]
  49. Kolstela, J.; Aakala, T.; Maclean, I.; Niittynen, P.; Kemppinen, J.; Luoto, M.; Rissanen, T.; Tyystjärvi, V.; Gregow, H.; Vapalahti, O.; et al. Revealing fine-scale variability in boreal forest temperatures using a mechanistic microclimate model. Agric. For. Meteorol. 2024, 350, 109995. [Google Scholar] [CrossRef]
  50. Stralberg, D.; Arseneault, D.; Baltzer, J.L.; Barber, Q.E.; Bayne, E.M.; Boulanger, Y.; Brown, C.D.; Cooke, H.A.; Devito, K.; Edwards, J.; et al. Climate-change refugia in boreal North America: What, where, and for how long? Front. Ecol. Environ. 2020, 18, 261–270. [Google Scholar] [CrossRef]
  51. Weldon, J.; Grandin, U. Major disturbances test resilience at a long-term boreal forest monitoring site. Ecol. Evol. 2019, 9, 4275–4288. [Google Scholar] [CrossRef]
  52. Abrams, M.D.; Scott, M.L. Disturbance-mediated accelerated succession in two Michigan forest types. For. Sci. 1989, 35, 42–49. [Google Scholar] [CrossRef]
  53. Bongers, F.; Chazdon, R.; Poorter, L.; Pena-Claros, M. The potential of secondary forests. Science 2015, 348, 642–643. [Google Scholar] [CrossRef]
  54. Chokkalingam, U.; De Jong, W. Secondary forest: A working definition and typology. Int. For. Rev. 2001, 3, 19–26. Available online: https://www.jstor.org/stable/42609342 (accessed on 29 January 2026).
  55. Frelich, L.E.; Jõgiste, K.; Stanturf, J.; Jansons, A.; Vodde, F. Are secondary forests ready for climate change? It depends on magnitude of climate change, landscape diversity and ecosystem legacies. Forests 2020, 11, 965. [Google Scholar] [CrossRef]
  56. Paquette, M.; Boudreault, C.; Fenton, N.J.; Pothier, D.; Bergeron, Y. Bryophyte species assemblages in fire and clear-cut origin boreal forests. For. Ecol. Manag. 2016, 359, 99–108. [Google Scholar] [CrossRef]
  57. Mitchell, J.C.; Kashian, D.M.; Chen, X.; Cousins, S.; Flaspohler, D.; Gruner, D.S.; Johnson, J.S.; Surasinghe, T.D.; Zambrano, J.; Buma, B. Forest ecosystem properties emerge from interactions of structure and disturbance. Front. Ecol. Environ. 2023, 21, 14–23. [Google Scholar] [CrossRef]
  58. Lutter, R.; Tullus, A.; Vares, A.; Sopp, R.; Tullus, T.; Kaivapalu, M.; Ots, K.; Kharel, B.; Lundmark, T.; Tullus, H. Twenty years of afforestation of former agricultural lands with silver birch plantations affects vertical distribution of SOC and macronutrients in the topsoil layer. Plant Soil 2023, 482, 385–400. [Google Scholar] [CrossRef]
  59. Rähn, E.; Lutter, R.; Riit, T.; Tullus, T.; Tullus, A.; Tedersoo, L.; Drenkhan, R.; Tullus, H. Soil mycobiomes in native European aspen forests and hybrid aspen plantations have a similar fungal richness but different compositions, mainly driven by edaphic and floristic factors. Front. Microbiol. 2024, 15, 1372938. [Google Scholar] [CrossRef]
  60. Jílková, V.; Adámek, M.; Angst, G.; Tůmová, M.; Devetter, M. Post-fire forest floor succession in a Central European temperate forest depends on organic matter input from recovering vegetation rather than on pyrogenic carbon input from fire. Sci. Total Environ. 2023, 861, 160659. [Google Scholar] [CrossRef]
  61. Millar, C.I. Historic variability: Informing restoration strategies, not prescribing targets. J. Sustain. For. 2014, 33, S28–S42. [Google Scholar] [CrossRef]
  62. DeRose, R.J.; Long, J.N. Resistance and resilience: A conceptual framework for silviculture. For. Sci. 2014, 60, 1205–1212. [Google Scholar] [CrossRef]
  63. Weißhuhn, P.; Müller, F.; Wiggering, H. Ecosystem vulnerability review: Proposal of an interdisciplinary ecosystem assessment approach. Environ. Manag. 2018, 61, 904–915. [Google Scholar] [CrossRef]
  64. de Groot, W.J.; Flannigan, M.D.; Cantin, A.S. Climate change impacts on future boreal fire regimes. For. Ecol. Manag. 2013, 294, 35–44. [Google Scholar] [CrossRef]
  65. Jain, P.; Castellanos-Acuna, D.; Coogan, S.C.P.; Abatzoglou, J.T.; Flannigan, M.D. Observed increases in extreme fire weather driven by atmospheric humidity and temperature. Nat. Clim. Chang. 2022, 12, 63–70. [Google Scholar] [CrossRef]
  66. Pausas, J.G.; Keeley, J.E. Wildfires as an ecosystem service. Front. Ecol. Environ. 2019, 17, 289–295. [Google Scholar] [CrossRef]
  67. Foster, D.R. Vegetation development following fire in Picea mariana (black spruce)–Pleurozium forests of south-eastern Labrador, Canada. J. Ecol. 1985, 73, 517–534. [Google Scholar] [CrossRef]
  68. Godfree, R.C.; Knerr, N.; Encinas-Viso, F.; Albrecht, D.; Bush, D.; Cargill, D.C.; Clements, M.; Gueidan, C.; Guja, L.K.; Harwood, T.; et al. Implications of the 2019–2020 megafires for the biogeography and conservation of Australian vegetation. Nat. Commun. 2021, 12, 1023. [Google Scholar] [CrossRef]
  69. Lanta, V.; Adámek, M.; Chlumská, Z.; Pánková, K.; Kopecký, M.; Macek, M.; Růžičková, A.; Busse, A.; Vébrová, D.; Ruka, A.T.; et al. Plant colonisation, soil nutrient patterns and microclimate after a large forest fire in temperate Central Europe. For. Ecol. Manag. 2025, 585, 122643. [Google Scholar] [CrossRef]
  70. Sayedi, S.S.; Abbott, B.W.; Vannière, B.; Leys, B.; Colombaroli, D.; Gil Romera, G.; Słowiński, M.; Aleman, J.C.; Blarquez, O.; Feurdean, A.; et al. Assessing Changes in Global Fire Regimes. Fire Ecol. 2024, 20, 18. [Google Scholar] [CrossRef]
  71. Sahila, A.; Boutchiche, H.; Viegas, D.X.; Reis, L.; Pinto, C.; Zekri, N. Experimental study of the burning characteristics of dead forest fuels. Int. J. Wildland Fire 2023, 32, 593–609. [Google Scholar] [CrossRef]
  72. Larson, E.R.; Kipfmueller, K.F.; Johnson, L.B. People, fire, and pine: Linking human agency and landscape in the Boundary Waters Canoe Area Wilderness and beyond. Ann. Am. Assoc. Geogr. 2021, 111, 1–25. [Google Scholar] [CrossRef]
  73. Mandl, L.; Cerioni, M.; Bače, R.; Bončina, A.; Brůna, J.; Chećko, E.; de Koning, J.H.C.; Diaci, J.; Dobrowolska, D.; Fidej, G.; et al. The Amount of undisturbed forest in proximity of severe disturbance patches enhances their recovery in temperate Europe. Land. Ecol. 2025, 40, 199. [Google Scholar] [CrossRef]
  74. Frelich, L.E.; Jõgiste, K.; Stanturf, J.A.; Parro, K.; Baders, E. Natural disturbances and forest management: Interacting patterns on the landscape. In Ecosystem Services from Forest Landscapes; Perera, A.H., Peterson, U., Pastur, G.M., Eds.; Springer: Cham, Switzerland, 2018; pp. 221–248. [Google Scholar] [CrossRef]
  75. Buma, B. Disturbance interactions: Characterization, prediction, and the potential for cascading effects. Ecosphere 2015, 6, 70. [Google Scholar] [CrossRef]
  76. Waldron, K.; Ruel, J.-C.; Gauthier, S. Forest structural attributes after windthrow and consequences of salvage logging. For. Ecol. Manag. 2013, 289, 28–37. [Google Scholar] [CrossRef]
  77. Thorn, S.; Chao, A.; Georgiev, K.B.; Müller, J.; Bässler, C.; Campbell, J.L.; Castro, J.; Chen, Y.-H.; Choi, C.-Y.; Cobb, T.P.; et al. Estimating retention benchmarks for salvage logging to protect biodiversity. Nat. Commun. 2020, 11, 4762. [Google Scholar] [CrossRef] [PubMed]
  78. Gough, C.M.; Buma, B.; Jentsch, A.; Mathes, K.C.; Fahey, R.T. Disturbance theory for ecosystem ecologists: A primer. Ecol. Evol. 2024, 14, e11403. [Google Scholar] [CrossRef]
  79. Turetsky, M.R.; Baltzer, J.L.; Johnstone, J.F.; Mack, M.C.; McCann, K.; Schuur, E.A.G. Losing legacies, ecological release, and transient responses: Key challenges for the future of northern ecosystem science. Ecosystems 2017, 20, 23–30. [Google Scholar] [CrossRef]
  80. Marozas, V.; Racinskas, J.; Bartkevicius, E. Dynamics of ground vegetation after surface fires in hemiboreal Pinus sylvestris forests. For. Ecol. Manag. 2007, 250, 47–55. [Google Scholar] [CrossRef]
  81. Marozas, V.; Armolaitis, K.; Aleinikovienė, J. Changes of ground vegetation, soil chemical properties and microbiota following surface fires in Scots pine forests. J. Environ. Eng. Landsc. Manag. 2013, 21, 67–75. [Google Scholar] [CrossRef]
  82. Voolma, K.; Mandelshtam, M.J.; Shcherbakov, A.N.; Yakovlev, E.B.; Õunap, H.; Süda, I.; Popovichev, B.G.; Sharapa, T.V.; Galasjeva, T.V.; Khairetdinov, R.R.; et al. Distribution and spread of bark beetles (Coleoptera: Scolytidae) around the Gulf of Finland: A comparative study with notes on rare species of Estonia, Finland and North-Western Russia. Entomol. Fenn. 2004, 15, 198–210. [Google Scholar] [CrossRef]
  83. Vodde, F.; Ait, K.; Orumaa, A.; Jõgiste, K.; Kaart, T.; Kiviste, A.; Õunap, H.; Stanturf, J.A.; Metslaid, M. Drivers behind the spatial dispersion of European spruce bark beetle (Ips typographus) infestation in protected areas in Estonia, four years after a major storm. For. Ecol. Manag. 2025, 578, 122469. [Google Scholar] [CrossRef]
  84. Rebane, S.; Jõgiste, K.; Põldveer, E.; Stanturf, J.A.; Metslaid, M. Direct measurements of carbon exchange at forest disturbance sites: A review of results with the eddy covariance method. Scand. J. For. Res. 2019, 34, 585–597. [Google Scholar] [CrossRef]
  85. Enescu, C.M.; Mihalache, M.; Ilie, L.; Dincă, L.; Timofte, A.I.; Murariu, G. Afforestation of degraded lands: A global review of practices, species, and ecological outcomes. Forests 2025, 16, 1743. [Google Scholar] [CrossRef]
  86. Keskkonnaagentuur. Mets: Aastaraamat Mets 2023 (Yearbook Forest 2023); Keskkonnaagentuur: Tallinn, Estonia, 2025; Available online: https://keskkonnaportaal.ee/sites/default/files/Teemad/Mets/Mets%202023.pdf (accessed on 29 January 2026).
  87. Boukhris, I.; Marano, G.; Dalmonech, D.; Valentini, R.; Collalti, A. Modeling forest growth under current and future climate. Curr. For. Rep. 2025, 11, 17. [Google Scholar] [CrossRef]
  88. Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A.N.; Kaiser, Ł.; Polosukhin, I. Attention is All You Need. In Advances in Neural Information Processing Systems, Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA, 4–9 December 2017; Curran Associates Inc.: Red Hook, NY, USA, 2017; Volume 30, pp. 5998–6008. [Google Scholar] [CrossRef]
  89. Castro, A.; Pinto, J.; Reino, L.; Pipek, P.; Capinha, C. Large language models overcome the challenges of unstructured text data in ecology. Ecol. Inform. 2024, 82, 102742. [Google Scholar] [CrossRef]
  90. Thomas, I.N.; Roche, P.; Grêt-Regamey, A. Harnessing artificial intelligence for efficient systematic reviews: A case study in ecosystem condition indicators. Ecol. Inform. 2024, 83, 102819. [Google Scholar] [CrossRef]
  91. Durlević, U.; Čegar, N.; Ilić, V.; Kovjanić, A. Machine learning and deep learning approaches for wildfire susceptibility prediction: A case study of the Djerdap Geopark, Serbia. Earth Syst. Environ. 2025, 1–22. [Google Scholar] [CrossRef]
  92. Eker, R.; Alkış, K.C.; Aydın, A. Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: An Izmir Regional Forest Directorate case. J. For. Res. 2024, 35, 65–83. [Google Scholar] [CrossRef]
Forests 17 00197 g001
Figure 1. Conceptual model of ecosystem legacy filtering, where live (α) and dead (β) biomass pass through successive ecological filters (φ1, φ2), releasing energy (E) and altering ecosystem structure.
Figure 1. Conceptual model of ecosystem legacy filtering, where live (α) and dead (β) biomass pass through successive ecological filters (φ1, φ2), releasing energy (E) and altering ecosystem structure.
Forests 17 00197 g001
Forests 17 00197 g002
Figure 2. Dynamic conceptual model of ecosystem biomass legacy filtering. Live biomass (α) and dead biomass (β) represent major ecosystem stocks. Mortality (M), influenced by fire severity (φ1), biotic activity (φ2), severity of meteorological disturbance type n (φn), and live combustion efficiency (k1), transfers live biomass to the dead biomass pool. Dead biomass contributes to energy release (E) via respiration (R, influenced by k2) and combustion (Cβ, influenced by φ1 and k3). Direct combustion of live biomass (α → E) is represented by a dashed link.
Figure 2. Dynamic conceptual model of ecosystem biomass legacy filtering. Live biomass (α) and dead biomass (β) represent major ecosystem stocks. Mortality (M), influenced by fire severity (φ1), biotic activity (φ2), severity of meteorological disturbance type n (φn), and live combustion efficiency (k1), transfers live biomass to the dead biomass pool. Dead biomass contributes to energy release (E) via respiration (R, influenced by k2) and combustion (Cβ, influenced by φ1 and k3). Direct combustion of live biomass (α → E) is represented by a dashed link.
Forests 17 00197 g002
Forests 17 00197 g003
Figure 3. Conceptual model of restoration (anti-filtering) of ecosystem legacies. Live (α) and dead (β) biomass are complemented with artificial inputs acting through ecological filters (φ1, φ2). These filters represent management-dependent processes that can vary in sequence and intensity—such as abiotic reconditioning or biological enrichment. Energy input (E) during antifiltering may be small in magnitude but large in informational effect. It can also be expressed as the energy embodied in the work invested to improve or transform the forest ecosystem. The (α + β):γ ratio serves as an indicative measure of ecosystem legacy status. New biomass (γ) modifies the system after φ1 and φ2, reflecting enrichment processes such as planting, biological fertilization, or mycorrhizal enhancement.
Figure 3. Conceptual model of restoration (anti-filtering) of ecosystem legacies. Live (α) and dead (β) biomass are complemented with artificial inputs acting through ecological filters (φ1, φ2). These filters represent management-dependent processes that can vary in sequence and intensity—such as abiotic reconditioning or biological enrichment. Energy input (E) during antifiltering may be small in magnitude but large in informational effect. It can also be expressed as the energy embodied in the work invested to improve or transform the forest ecosystem. The (α + β):γ ratio serves as an indicative measure of ecosystem legacy status. New biomass (γ) modifies the system after φ1 and φ2, reflecting enrichment processes such as planting, biological fertilization, or mycorrhizal enhancement.
Forests 17 00197 g003
Forests 17 00197 g004
Figure 4. Hypothetical range of variation (a) under natural conditions (NRV); (b) in managed forests; and (c) in managed forests with potential restoration interventions, for key attributes of resilience: live biomass; dead biomass; species diversity; habitat/microsite diversity; spatial stand/landscape diversity; average decay stage (1–5: fresh to entirely decayed); functional diversity; and average recovery time. The term Matrix approach refers to the twofold representation of stands that comprise the matrix of the landscape under the integrated legacy concept for hemiboreal forested landscapes presented here.
Figure 4. Hypothetical range of variation (a) under natural conditions (NRV); (b) in managed forests; and (c) in managed forests with potential restoration interventions, for key attributes of resilience: live biomass; dead biomass; species diversity; habitat/microsite diversity; spatial stand/landscape diversity; average decay stage (1–5: fresh to entirely decayed); functional diversity; and average recovery time. The term Matrix approach refers to the twofold representation of stands that comprise the matrix of the landscape under the integrated legacy concept for hemiboreal forested landscapes presented here.
Forests 17 00197 g004
Table 1. Operational definitions of key legacy-related concepts used in this study.
Table 1. Operational definitions of key legacy-related concepts used in this study.
TermDefinition
Ecosystem legacyA physical, biological, or biogeochemical condition (or combination of conditions) of a pre-disturbance ecosystem element that persists long-term after a disturbance and influences post-disturbance ecosystem structure, composition, and functioning. Ecosystem legacies encompass both material legacies (biotic and abiotic remnants) and information legacies (life-history traits, functional strategies, and biogeochemical signals)
Ecological legacyUsed synonymously with biological legacy in this manuscript; refers specifically to organic remnants of a pre-disturbance ecosystem state that condition ecosystem recovery.
Biological legacyThe above- and below-ground organic remnants of a pre-disturbance ecosystem, including living organisms, dead organic matter, seed banks, and spatial patterns of these elements, which positively influence post-disturbance recovery processes. Examples include surviving trees, coarse woody debris, and soil seed banks.
Legacy traitsLife-history, physiological, or functional characteristics of organisms that persist through disturbance events and act as information legacies, shaping post-disturbance regeneration pathways and ecosystem dynamics
Legacy filteringThe process by which natural or anthropogenic disturbances, acting as environmental filters, constrain which ecosystem legacies persist and how they influence subsequent ecosystem trajectories. Legacy filtering integrates disturbance intensity, exposure opportunity, and management context, thereby shaping recovery options and ecosystem resilience.
Ecosystem resilienceThe capacity of an ecosystem to resist disturbance and recover its structure, composition, and functions, mediated by the continuity, interaction, and integrity of ecosystem legacies rather than by recovery speed alone.
Legacy restorationManagement actions aimed at maintaining, enhancing, or reintroducing ecosystem legacies—both material and information legacies—to restore ecosystem processes, support biodiversity, and increase resilience under altered disturbance regimes or climate change.
Table 2. Decadal fire statistics in Estonian forests (source [86]).
Table 2. Decadal fire statistics in Estonian forests (source [86]).
DecadeTotal FiresTotal Area (ha)Mean Area/Fire (ha)r (Fires vs. Total Area)r (Fires vs. Mean Area)
1990s20586211.33.020.690.17
2000s13028226.16.320.800.23
2010s746830.01.110.83–0.18
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jõgiste, K.; Frelich, L.E.; Vodde, F.; Jansons, Ā.; Bāders, E.; Reich, P.B.; Stanturf, J.A.; Rebane, S.; Köster, K.; Metslaid, M. Increasing Forest Ecosystem Resilience Is a Matter of Ecosystem Legacy Management: Conceptual Model for Restoration in Hemiboreal Forests. Forests 2026, 17, 197. https://doi.org/10.3390/f17020197

AMA Style

Jõgiste K, Frelich LE, Vodde F, Jansons Ā, Bāders E, Reich PB, Stanturf JA, Rebane S, Köster K, Metslaid M. Increasing Forest Ecosystem Resilience Is a Matter of Ecosystem Legacy Management: Conceptual Model for Restoration in Hemiboreal Forests. Forests. 2026; 17(2):197. https://doi.org/10.3390/f17020197

Chicago/Turabian Style

Jõgiste, Kalev, Lee E. Frelich, Floortje Vodde, Āris Jansons, Endijs Bāders, Peter B. Reich, John A. Stanturf, Sille Rebane, Kajar Köster, and Marek Metslaid. 2026. "Increasing Forest Ecosystem Resilience Is a Matter of Ecosystem Legacy Management: Conceptual Model for Restoration in Hemiboreal Forests" Forests 17, no. 2: 197. https://doi.org/10.3390/f17020197

APA Style

Jõgiste, K., Frelich, L. E., Vodde, F., Jansons, Ā., Bāders, E., Reich, P. B., Stanturf, J. A., Rebane, S., Köster, K., & Metslaid, M. (2026). Increasing Forest Ecosystem Resilience Is a Matter of Ecosystem Legacy Management: Conceptual Model for Restoration in Hemiboreal Forests. Forests, 17(2), 197. https://doi.org/10.3390/f17020197

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop