Forest Management Strategies Research Articles

Land sharing, land sparing, and Triad forestry: modeling forest composition, diversity, and carbon storage under climate change and natural disturbances

ContextForests are vital renewable resources for timber, while also serving as carbon reservoirs and habitats for many terrestrial species. However, there are tradeoffs between timber production and other ecosystem services, such as carbon storage and biodiversity, highlighting the need for new management strategies that more effectively balance these tradeoffs. This case study models the effectiveness of four such strategies, based on a newly proposed management plan for a state forest in coastal Oregon.ObjectivesWe tested the effectiveness of four landscape-scale forest management strategies designed to minimize tradeoffs between timber production, carbon storage, and biodiversity. These strategies include land sparing (spatially separating timber production from conservation), land sharing (integrating timber production with conservation), and two variants of Triad management (dividing forests into intensive, extensive, and reserve areas). This study assesses the long-term impacts of these strategies on timber production, tree and shrub diversity, and carbon storage, while also evaluating how natural disturbances (i.e. wind and fire) and climate change could affect their relative benefits.MethodsWe used the spatially interactive, raster-based forest landscape model, LANDIS-II, to simulate forest succession, management, windthrow, and wildfire under a range of potential climate futures from 2016 until 2100.ResultsOur results demonstrate that while all management strategies ensured sustainable timber production, land sharing promoted the highest occupancy, Shannon diversity index, and biomass of key early and mid-successional tree and shrub species identified by managers for their conservation value. In contrast, Triad management and land sparing tended to maximize carbon storage. Under extreme climate projections, carbon storage was equally compromised across all management strategies and there was a further shift towards Douglas-fir dominance.ConclusionTo our knowledge, this study represents the first modelled comparison of land sharing, land sparing, and Triad management under climate change and natural disturbance regimes. Management strategies differed in their provisioning of carbon, diversity, and plant biomass, and while the relative differences between these benefits remained consistent, all outcomes were negatively affected by climate change. We demonstrate the use of LANDIS-II in strategic forest planning and highlight the necessity of using spatial models for informed decision-making to simultaneously achieve multiple forest management objectives under climate change and disturbances.

Soil Aggregation, Aggregate Stability, and Associated Soil Organic Carbon in Huron Mountains Forests, Michigan, USA

Soil organic carbon (SOC) plays a critical role in regulating the global carbon (C) cycle, with forest soils serving as significant C sinks. Soil aggregate stability and the distribution of SOC in different aggregate fractions would be affected by different forest types. In this study, we investigate the distribution and dynamics of SOC within different soil aggregate fractions across three main forest types in the Huron Mountains, Michigan, USA: white birch–eastern hemlock mixed forest, eastern-hemlock-dominated forest, and sugar maple forest. We hypothesize that variations in species composition and soil depth influence SOC storage and aggregate stability through mechanisms such as root interactions, microbial activity, and soil structure development. Soil samples were collected from three depth intervals (0–20 cm, 20–40 cm, and 40–60 cm) and analyzed for aggregate size distribution and SOC content. The results showed that aggregate size distribution and SOC stocks differ significantly across forest types, with the white birch–eastern hemlock mixed forest exhibiting the highest proportion of large aggregates (>1.0 mm), which contribute to more stable soil structures. This forest type also had the highest total aggregate mass and mean weight diameter, indicating enhanced soil stability. In contrast, sugar maple forest displayed a greater proportion of smaller aggregates and a lower macroaggregate-to-microaggregate ratio, suggesting fewer stable soils. SOC stocks were closely linked to aggregate size, with macroaggregates containing the highest proportion of SOC. These differences in SOC distribution and soil aggregate stability can be attributed to several underlying mechanisms, including variations in plant root interactions, microbial activity, and the physical properties of the soil. Forests with diverse species compositions, such as the white birch–eastern hemlock mixed forest, tend to support more complex root systems and microbial communities, leading to improved soil aggregation and greater SOC storage. Additionally, forest management practices such as selective thinning and mixed-species planting contribute to these processes by enhancing soil structure, increasing root biomass, and promoting soil microbial health. These interactions play a crucial role in enhancing C sequestration and improving soil health. Our findings emphasized the importance of forest composition in influencing SOC dynamics and soil stability, offering insights into the role of forest management in C sequestration and soil health. This study provided a reference to a deeper understanding of SOC storage potential in forest ecosystems and supports the development of sustainable forest management strategies to mitigate climate change.

Leveraging the Internet of Things, Remote Sensing, and Artificial Intelligence for Sustainable Forest Management

Sustainable forest management is vital for addressing climate change, biodiversity loss, and deforestation. Human-induced stresses on forest ecosystems demand innovative approaches to ensure long-term health and productivity. This study explores how cutting-edge technologies, including the Internet of Things (IoT), remote sensing, and artificial intelligence (AI), enhance sustainable forest management practices. Researchers reviewed 196 studies published between 2021 and 2024 from IEEE Xplore Digital Library, MDPI, Taylor & Francis, ScienceDirect, Frontiers, Springer, SAGE, Hindawi, Nature, Wiley Online Library, and Google Scholar. The findings highlight IoT devices like drones, enabling real-time data collection on temperature, humidity, soil moisture, and tree growth, facilitating continuous forest monitoring. Remote sensing technologies, utilizing satellite imagery and aerial surveys, deliver high-resolution data for large-scale forest assessments, including forest cover changes, biomass estimation, and early detection of illegal logging. When integrated with AI, these tools enhance predictive modeling, data analysis, and decision-making, leading to more effective forest management strategies. The study also identifies challenges such as data security concerns, bandwidth limitations, interoperability issues, and high costs. Despite these barriers, IoT, remote sensing, and AI present transformative potential for improving forest resilience, carbon sequestration, and biodiversity conservation. These technologies are crucial in preserving forest ecosystems and mitigating climate change impacts by advancing real-time monitoring, optimizing resource allocation, and enabling data-driven decisions.

Assessing Relationships Between Deer (Cervidae) Damage and Stand Structure of Scots Pine (Pinus sylvestris) Stands in Hemiboreal Latvia

Intensive forest management has promoted an increase in deer (Cervidae) population density. Various silvicultural activities, such as pre-commercial thinning, can change the feeding conditions for deer species, therefore impacting browsing pressure on target tree species. In this study, we analyzed how several factors, including the density of the main tree species, admixture, undergrowth, and forest type, affect deer damage intensity in pine stands, considering deer densities and regional aspects in hemiboreal Latvia. GLMM analysis, based on data from 1238 sample plots, showed that the probability of browsing damage decreases with an increase in the density of undergrowth in young (<20 years) pine stands with a dominant height below 3 m. Also, the probability of pines being damaged by deer was significantly (p = 0.001) higher in stands with fresh pre-commercial thinning than in those with no thinning. However, differences in deer density between regions also determined browsing pressure. Results indicated that undergrowth density, pre-commercial thinning, and deer density may be important drivers of damage levels, especially in the winter browsing of young pine stands on wet mineral soils. Therefore, future research should continue to evaluate applied forest management strategies in hemiboreal forests that provide additional natural food base in the form of woody plants and shrubs in winter forage to ensure more deer-adapted practices.

Ecosystem carbon storage, allocation and carbon credit values of major forest types in the central Himalaya

Himalayan forests are crucial global carbon reservoirs that contribute significantly to carbon mitigation efforts. Although situated within a single climatic zone, Himalayan forests include diverse forest types within a short distance due to variations in altitude, mountain range, slope, and aspect. This study aimed to estimate ecosystem carbon storage (including plant biomass, deadwood, litter, and soil organic carbon [SOC]) and allocation and to evaluate carbon sequestration and carbon credit potential in chir-pine plants (Pinus roxburghii Sarg.), deodar (Cedrus deodara [Roxb.] G. Don), oak (Quercus leucotrichophora A. Camus), and sal (Shorea robusta [Roth]) forests in the central Himalaya. Volumetric equations were utilized across diverse tree species and supplemented by field sampling, particularly by employing the quadrat method to quantify tree biomass. The carbon stocks within ecosystems varied considerably, ranging between 122.44 and 306.44 Mg C ha−1, with discernible differences among forest types, with oak forests exhibiting the highest carbon stock, followed by deodar and sal forests, and pine forests showing the lowest. The allocation of ecosystem carbon stocks among the different components, including trees (21%–34%), soil (64%–77%), deadwood (0.9%–0.35%), and litter (0.46%–1.20%), demonstrated significant variability. The Mantel test revealed the significant influence of environmental factors on carbon storage. Carbon dioxide (CO2) sequestration ranged from 448.98 (pine forest) to 1123.16 (oak forest) Mg CO2 ha−1, while carbon credit values ranged from 1346.96 EUR ha−1 (pine forests) to 3379.49 EUR ha−1 (oak forest). In this study, dominant trees in various forest types contributed to higher carbon storage in their biomass and forest soil, resulting in greater carbon credits. The present research evaluated ecosystem carbon storage, CO2 sequestration potential, and carbon credit valuation for major forests in the central Himalaya. By incorporating these findings into forest management plans and strategies, the carbon sequestration potential and carbon trading of the central Himalayan forest ecosystem in India can be enhanced.

Evaluating Annual Growth Dynamics Across Forest Types Using Permanent Sample Plots in Yellapur Forest Division, Karnataka, India

Annual tree increment requires repeated assessments on permanent sample plots, which are crucial for evaluating changes in tree size and stem volume. These plots enable long-term monitoring to estimate timber production and analyse growth dynamics. This study examines the current annual increment of growth parameters like tree height, GBH, basal area, and volume in dry, moist deciduous, and semi-evergreen forests within the Yellapur Forest Division, Uttara Kannada, Karnataka. The Permanent sample plots were utilized to assess growth patterns across various forest types. Total of nine one-hectare permanent plots were established across the forest types with three plots laid in each forest type and divided into subplots of size 33.33m× 33.33m and data were collected for tree parameters including girth at breast height and tree height using digital laser hypsometer. Measurements were conducted over two consecutive years i.e., in 2022 and repeated in 2023 to calculate CAI. The results revealed significant variation among forest types. Moist deciduous forests exhibited the highest CAI in height (0.45 m/year) and GBH (1.84 cm/year), while dry deciduous forests showed lower increments due to water stress and leafless periods. Semi-evergreen forests, although with dense canopy competition, demonstrated moderate growth rates. The basal area increment was highest in moist deciduous forests (0.93 m²/ha/year), reflecting favourable moisture and nutrient conditions. The tree volume increased significantly in moist deciduous forests (22.80 m³/ha/year). Variations in basal area and volume suggest that environmental conditions and anthropogenic activities, such as litter collection, impacted growth across forest types. These insights are critical for developing sustainable forest management practices and mitigating the impact of anthropogenic activities on forest ecosystems. This research underscores the importance of monitoring permanent plots to understand forest dynamics and supports sustainable forest management strategies.

Comparative analysis of volume growth processes of Masson pine and Chinese fir forests in different regions of southern China.

Masson pine (Pinus massoniana Lamb.) and Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) are important coniferous species commonly found in southern China and play crucial ecological and economic roles. Understanding how regionally variable conditions influence their growth patterns can support effective forest management strategies and conservation efforts. Here, we used the Richards growth equation to comprehensively analyze their volumetric growth processes through multiple diverse regions in southern China, representing a pioneering large-scale application of unified modeling techniques. This work provides theoretical and technical knowledge to support the sustainable stewardship of these vital forest ecosystems. We found that: (1) The highest per-hectare volume accumulation occurs in southwestern China, at 97.455 m3hm-2 for P. massoniana and 85.288 m3hm-2 for C. lanceolata. These values are higher than in the southeastern (71.424 m3hm-2 and 79.520 m3hm-2, respectively) or south-central regions (70.697 m3hm-2 and 65.647 m3hm-2), predominantly due to varying stand maturity across these regions. (2) Both species exhibit age-dependent growth patterns in the first 100 years of forest development, characterized by rapid early growth and transitioning into slower, stable phases. The highest total volume growth for P. massoniana occurred in the southwest, followed by the southeast and south-central regions. Conversely, C. lanceolata growth is highest in the southeast, followed by south-central and the southwest. (3) Quantitative maturity for P. massoniana ranges from 27 to 29 years (average: 30 years) whereas C. lanceolata matures earlier, between 16 to 19 years (average: 20 years). Climate and soil factors significantly influence their growth dynamics, with precipitation, temperature variation, and soil characteristics driving differences in suitability and growth potential across distinct regions in southern China. Tailored management practices that align with local climatic and environmental conditions are recommended to optimize growth and ensure sustainable management and development of P. massoniana and C. lanceolata forests.

Management strategies for shrinking and aging tree plantations are constrained by the synergies and trade-offs between carbon sequestration and other forest ecosystem services.

Planted forests have expanded globally over the last three decades and are expected to act as carbon sinks to mitigate further climate change. However, the planted coniferous forests in Japan are now predicted to shrink in area and age in the future. To quantify the impact of the shrinking and aging of Japanese cedar (Cryptomeria japonica D. Don) stands on the carbon sequestration rate in 2010, 2050, and 2090, we estimated net ecosystem production (NEP) at the national scale for Japan. We ran a process-based model under four forest management scenarios, in which 4-34% of the area of Japanese cedar stands were replaced by secondary broadleaf forests by 2050, and the average age of the remaining cedar stands increased from 44.4 to 59.4-80.8 years old. Contrary to our expectations, NEP was estimated to decrease from 2010 to 2050 or 2090 under all climate/forest management scenarios. The average decline in NEP from 2010 to 2050 under the shared socioeconomic pathway 1-2.6 (SSP1-2.6) was -21% across the four forest management scenarios. We also estimated the synergies and trade-offs of NEP values with two types of forest ecosystem service, landslide prevention and habitat provisioning for broadleaf trees. As a result, high rates of cutting and planting of Japanese cedar were presented as a forest management strategy in southern Japan, while low rates were more appropriate in northern Japan. The newly-developed framework for exploring climate change mitigation pathways is likely to be effective in the future, especially in developed countries where planted forests are projected to shrink and age in the coming decades.

Species-specific responses of canopy greenness to the extreme droughts of 2018 and 2022 for four abundant tree species in Germany.

Germany experienced extreme drought periods in 2018 and 2022, which significantly affected forests. These drought periods were natural experiments, providing valuable insights into how different tree species respond to drought. The quantification of species-specific drought responses may help to identify the most climate-change-resilient tree species, thereby informing effective forest regeneration strategies. In this study, we used remotely sensed peak-season canopy greenness as a proxy for tree vitality to estimate the drought response of four widely abundant tree species in Germany (oak, beech, spruce, and pine). We focused on two questions: (1) How were the four tree species affected by these two droughts? (2) Which environmental parameters primarily determined canopy greenness? To address these questions, we combined a recently published tree species classification map with remotely sensed canopy greenness and environmental variables related to plant available water capacity (PAWC) and atmospheric vapor pressure deficit (VPD). Our results indicate that the more isohydric species featured a greater decline in canopy greenness under these droughts compared to the more anisohydric species despite similar soil moisture conditions. Based on spatial lag models, we found that the influence of PAWC on canopy greenness increases with increasing isohydricity while the influence of VPD decreases. Our statistical analysis indicates that oak was the only species with significantly higher canopy greenness in 2022 compared to 2018. Yet, all species are likely to be susceptible to accumulated drought effects, such as insufficient recovery time and increased vulnerability to biotic pathogens, in the coming years. Our study provides critical insights into the diverse responses of different tree species to changing environments over a large environmental gradient in Central Europe and sheds light on the complex interactions between soil moisture, climate variables, and canopy greenness. These findings contribute to understanding forests' climate-change resilience and may guide forest management and conservation strategies.

Inconsistency between process-based model and dose-response function in estimating biomass losses in Northern Hemisphere due to elevated O3.

Tropospheric ozone (O3) concentrations in the Northern Hemisphere have significantly increased since the pre-industrial era, with ongoing growth driven by emissions from industrial, agricultural, and transportation activities, further exacerbated by the warming temperatures and altered atmospheric circulation patterns associated with climate change. This study compared different methodologies for estimating biomass potential losses (BPL) in forests due to elevated O3 using both concentration-based (AOT40) and flux-based (POD1) metrics. Moreover, to further assess the impact of O3 on forest health and carbon uptake across the dominant forest types in the Northern Hemisphere, we also compared BPL estimates from dose-response functions with those derived from the process-based model ORCHIDEE. Our analysis showed that deciduous forests, particularly boreal and continental types, are more sensitive to O3-induced biomass loss compared to evergreen forests. Importantly, the study also revealed significant regional differences, with Europe and North America experiencing higher BPL than Asia and North Africa. Regression analysis between BPL and Gross Primary Production anomalies indicated that the relationship between O3 exposure and forest productivity varied across forest types, with continental deciduous forests showing stronger correlations. The findings highlighted the importance of using flux-based metrics like POD1 in assessing O3 impacts and that current dose-response functions may require further validation across diverse ecological settings to propose effective forest management and conservation strategies.

Multi-scale temporal and spatial variations of soil heat flux under varying riparian forests: From a day to a year.

This study delves into the multi-scale temporal and spatial variations of soil heat flux (G) within riparian zones and its correlation with net radiation (Rn) across six riparian woodlands in Shanghai, each characterized by distinct vegetation types. The objective is to assess the complex interrelations between G and Rn, and how these relationships are influenced by varying vegetation and seasons. Over the course of a year, data on G and Rn is collected to investigate their dynamics. The multi-scale temporal patterns of G and its relationship with Rn are significantly influenced by both vegetation type and season, with the most pronounced variability observed seasonally, exhibiting distinct cycles for both broadleaf and conifer forests. The presence of shrubs is found to increase G, and the dominant temporal scales were found to vary within broadleaf forests. Additionally, G demonstrates a non-linear gradient with respect to the proximity to the river, with the river's influence on G diminishing at distances less than 11m in broadleaf and 6m in conifer woodlands. While the river enhances G and its hysteresis with Rn, vegetation characteristics dominate in dense canopies. This study underscores the importance of understanding the spatio-temporal variation patterns of soil heat flux and their response to different vegetation attributes. Such knowledge is vital for developing riparian soil heat flux models and informing riparian forest management strategies, especially in the context of climate change. The results provide insights into the complex interactions between soil heat flux, net radiation, and vegetation, offering a foundation for future research and management practices aimed at preserving and enhancing the ecological functions of riparian ecosystems.

STRATEGI PENGELOLAAN PROGRAM HUTAN KEMASYARAKATAN (HKm) DI KESATUAN PENGELOLAAN HUTAN PRODUKSI BARITO TENGAH

The aim of this research is to formulate a strategy for community forest management in the Central Barito Production Forest Management Unit. Data analysis used the SWOT formula with planning techniques to evaluate strengths, weaknesses, opportunities and threats in a project. The research object is the Datah Berbuahl Forest Farmer Group in Sei Rahayu II Village with SK KTH SK.2580/MENLHK-PSKL/PKPS/PSL.0/4/2018 and the Karya Bersama Forest Farmer Group in Hajak Village with SK KTH SK.7132/MENLHK-PSKL/PKPS/PSL.0/4/2019. The selection of informants for interviews in the Focus Group Discussion was carried out deliberately to represent groups of community forest farmers who have influence in making group decisions and representatives of informants related institutions in community forestry programs, such as the KPHP Central Barito, NGOs/Customary Heads and Village Heads. The results of the SWOT matrix are built based on the results of an analysis of external and internal strategic factors, there are four main strategies, namely utilizing the availability of large enough land (SO), improving road access to the location of Forest Farmers Groups (WO), designating clear forest areas (ST) and increasing farmers' interest in managing Hkm (WT). The score calculation results on the matrix based on the EMP development strategy in North Barito Regency are in quadrant I (0.62; 0.29). Quadrant I (Strategy Aggressive), that is, with the strengths possessed by forest farmer groups, they must be able to take advantage of existing opportunities, while overcoming all weaknesses that arise and constitute a profitable situation, forest farmer groups have opportunities and strengths so that they can take advantage of existing opportunities.

Partisipasi Masyarakat Dalam Pengelolaan Hutan Mangrove di Desa Alang-Alang Kabupaten Tanjung Jabung Timur Provinsi Jambi

Sustainable mangrove management requires community efforts and participation. Where positive community perceptions of the existence of mangroves will increase community participation in mangrove management activities. Several factors that encourage the community to participate are both internal and external factors. This study aims to see the perception and participation of the community towards the mangrove forest ecosystem and recommend sustainable mangrove forest management strategies. The study was conducted from August to September 2024 using qualitative research methods by collecting descriptive data in written or oral form, which were then interpreted descriptively holistically, contextually using researchers as the main instrument for collecting data. To formulate a mangrove management strategy for the sustainability of the mangrove ecosystem, a SWOT (Strengths, Weaknesses, Opportunities and Treaths) analysis was carried out. The results of the study showed that the Alang-Alang Village community had a good and positive perception of the existence of the mangrove forest ecosystem, but their participation was still passive (participating if there was someone to accommodate and not yet their own initiative) in the management and preservation of mangrove forests. Where good community perception and community participation also influenced the good ecology of the Alang-Alang Village mangrove forest, including the area and density of good mangroves. However, there are still individuals from other villages who sometimes still cut down mangrove trees and added high waves and strong tidal currents also damage the existing mangrove forest ecosystem. For the management of the mangrove forest ecosystem, Alang-Alang Village is in quadrant I, where the strategy that can be applied in this condition is to support an aggressive strategy or aggressive growth policy (Growth oriented strategy) by utilizing existing strengths and opportunities

Tradeoffs between thinning treatments and rotation periods of planted Larix olgensis forests: a perspective from carbon balance

IntroudctionThe current CO2 levels are higher than ever in the past two million years. Forests, as one of the climate change mitigation solutions, are becoming increasingly technically feasible and cost-effective. However, limited research comprehensively considers thinning in the context of optimizing the rotation period for carbon sequestration.MethodsThis study utilizes stand-level growth models and diameter distribution models to simulate the carbon balance dynamics of Larch (Larix olgensis) plantations under various thinning scenarios. The effects of different initial planting densities (N0∈{2,500, 3,333, 4,444} tree ha−1) and site class index (SCI∈[14–20] m) on the optimal forest management measures are also quantified.ResultsThe results reveal that the overall trend of carbon balance gradually increases and then decreases over time under the baseline scenario (3,333 tree ha−1 of N0, 16 m of SCI, 5% of discount rate, 100 CNY ton−1 C of carbon price); the carbon balances of all thinning forests were less than that of the unthinned forest before until 56th year. The optimal rotation period and net present value (NPV) increase with increasing thinning frequency and intensity. The sensitivity of NPV to thinning frequency increases with higher thinning intensities, SCI, and carbon prices.DiscussionThis study further expands the scope of forest management strategies, providing optimal forest management plans for all 21 combinations of different SCIs and N0. The optimal forest management strategy in the baseline scenario is 3 thinnings, with the first thinning at 20% intensity in the 15th year, the second thinning at 30% intensity in the 18th year, and the third thinning at 30% intensity at 21 years, with a rotation period of 26 years, resulting in an NPV of 37,180 CNY ha−1.

Saproxylic beetle assemblages exhibit distinct seasonal patterns across different decay classes of dead wood in a mixed temperate forest

Abstract Saproxylic organisms play a pivotal role in the decomposition of woody materials, profoundly impacting nutrient cycling within forest ecosystems. With their rich biodiversity and diverse ecological functions, saproxylic species provide unique ecological services and interactions that are closely linked to specific dead wood types. Given the distinctive roles and diversity of saproxylic beetles, forest loss and management practices that reduce dead wood amount and quality pose a risk of greater biodiversity loss. This highlights the critical need for comprehensive research into saproxylic beetle diversity and community structures from various perspectives to support sustainable forest management strategies. We sampled 60 Quercus logs in a temperate mixed forest during both winter and summer, and reared saproxylic beetles using emergence traps. Consequently, we collected a total of 1793 saproxylic beetles from 27 families and 75 species across three decay classes. Season was a key environmental variable, clearly distinguishing saproxylic beetle assemblages between winter and summer. While decay class did not clearly differentiate the beetle assemblages in summer, it distinctly separated the assemblages in winter. Our findings indicate that saproxylic beetles are influenced by changing resource availability and microclimate, driven by environmental variables such as season. This variability reveals the overlooked biodiversity potential, emphasizing the need for continuous and comprehensive research to achieve conservation goals and improve understanding of saproxylic organisms.

Improving European Black Pine Stem Volume Prediction Using Machine Learning Models with Easily Accessible Field Measurements

Reliable prediction of tree stem volume is crucial for effective forest management and ecological assessment. Traditionally, regression models have been applied to estimate forest biometric variables, yet they often fall short when handling the complex, non-linear patterns typical of biological data, potentially introducing biases and errors. Tree stem volume, a critical metric in forest biometrics, is generally estimated through easily measured parameters such as diameter at breast height (d) and total tree height (h). This study investigates advanced machine learning (ML) techniques—Extreme Gradient Boosting (XGBoost), epsilon-Support Vector Regression (ε-SVR), and Random Forest regression (RFr)—to predict the stem volume of European black pine (Pinus nigra) on Mount Olympus, Greece, using basic field measurements. Machine learning (ML) approaches demonstrated substantial improvements in prediction accuracy compared to traditional non-linear regression-based models (RMs). Notably, XGBoost significantly enhanced predictive performance by reducing the Furnival index (FI) by as much as 42.3% (from 1.1859 to 0.1056) and 21.3% (from 0.1475 to 0.1161) in the test and fitting datasets, respectively, for the single-entry model. For the double-entry model, XGBoost achieved FI reductions of 40.5% (from 0.1136 to 0.0676) and 41.3% (from 0.1219 to 0.0715) in the test and fitting datasets, respectively. These findings highlight the potential of ML models to improve the accuracy of forest inventory predictions, thereby supporting more effective and data-driven forest management strategies.

Assessment of Forest Composition, Structure and Biomass Dynamics Using Permanent Plot Inventories in Yellapur Forest Division, India

This study assesses the forest composition, structure and biomass dynamics in the Yellapur Forest Division using permanent plot inventories. Located in the Western Ghats of Karnataka, the Yellapur region features diverse forest types, including tropical dry deciduous and semi-evergreen forests. Permanent plots were established to evaluate tree species distribution, structural attributes and biomass dynamics. The volume and biomass were calculated based on species-specific allometric equations. Results revealed significant differences in forest structure across forest types. Tropical dry deciduous forests exhibited lower tree density (250 trees per hectare) and biomass (55 tons per hectare) compared to semi-evergreen forests, which had higher tree density (350 trees per hectare) and biomass (95 tons per hectare). Biomass volume in the tropical dry deciduous forests was reduced by 15-18 percent in areas impacted by anthropogenic activities such as logging and grazing. The semi-evergreen forests showed a higher carbon stock, with biomass volume accounting for 140 tons per hectare, while tropical dry deciduous forests had a reduced biomass volume of 110 tons per hectare. Species composition in semi-evergreen forests was dominated by Shorea robusta, Terminalia arjuna and Tectona grandis, while tropical dry deciduous forests were characterized by species such as Ziziphus mauritiana and Anogeissus latifolia. The study also highlighted a significant decline in biomass in degraded areas, emphasizing the impact of human-induced disturbances on carbon sequestration. The results suggest that degradation has led to a 12-15 percent reduction in forest biomass volume, with substantial implications for carbon storage and forest health. This research underscores the importance of permanent plot inventories for understanding biomass dynamics and highlights the need for effective forest management strategies to mitigate degradation and enhance carbon storage in these ecosystems.

Trade-offs and management strategies for ecosystem services in mixed Scots pine and Maritime pine forests

AbstractMixed forests are increasingly recognized for their resilience to climate change and enhanced ecosystem services (ESs) provision, making them a focal point for sustainable forest management strategies. This study examines the trade-offs in ESs provision between pure and different proportions of mixed stands of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in the Northern Iberian Range, Spain. Using the SIMANFOR simulation platform, we evaluated various silvicultural scenarios developed to obtain different ESs such as carbon sequestration, timber and mushroom yields. Our findings reveal that ESs provision varies depending on the forest type (pure or mixed) and the mixture proportion, following different trends on each ES. The initial species proportions and their maintenance were less critical than the management approach itself, which significantly influenced ESs outcomes. Focusing solely on individual ESs can lead to trade-offs, as highlighted by our study on silviculture focused on large saw timber yields. However, adopting a balanced approach that considers multiple ESs can mitigate these trade-offs. Our findings underscore the effectiveness of this approach in maximizing yields of mushrooms, sequestered carbon, and small saw timber. This research provides valuable insights for forest managers aiming to balance productivity and sustainability in ESs provision, providing strategies to maximize compatible ESs effectively.

Investigating the potential of ICEYE-SAR data in storm damage detection in a coniferous forest with rugged terrain

ABSTRACT Adaptive forest management strategies require accurate detection of forest disturbance, in various spatial scales. Synthetic Aperture Radar (SAR) data can provide information about the forest attributes, penetrating the canopy at different levels under any weather and lighting conditions. ICEYE consists of the largest constellation of SAR satellites, enabling very high spatial and temporal resolution. In this study, ICEYE data were investigated in the detection of storm damage, in a fir forest with complex topography which was recently hit by the Daniel storm, resulting in severe damage to the forest structure (FS) and alluvium depositions (AD). To identify the best potential for storm damage detection using ICEYE data, an unsupervised change detection approach was employed combining wavelet transform and adaptive thresholds at spatial scales of 0.5 m (R05), 1 m (R1), 2 m (R2) and 3 m (R3). Additionally, two morphological filters were applied in best-performing resolutions to assess the impact of post-processing on the detection accuracy. Finally, FS and AD damage were investigated separately in order to provide detailed information about the detection capabilities of ICEYE. The results showcased that R1 (UA = 32.35, PA = 18.34 and K = 0.31) provided the best detection performance, followed by R05 (UA = 20.62, PA = 20.12 and K = 0.19). Furthermore, the employment of morphological filters slightly increased UA and Kappa metrics in both R1(UA = 33.40 and K = 0.32) and R05 (UA = 25.60 and K = 0.24), suggesting that post-processing is necessary to mitigate false detections. Regarding the investigation of AD and FS damage, it was revealed that post-processed ICEYE data in both R05 and R1 are capable of identifying AD with satisfying accuracy (UA = 47.41, PA = 22.36, K = 0.47), while FS damage detection is more challenging (UA = 10.15%-14.40%, PA = 14.55%-15.11%, and Kappa = 0.10-0.17). Overall, this study demonstrated that ICEYE can be used to detect storm-affected areas in mountainous forest ecosystems, especially in cases where detection with other methods is not feasible.

Estimation of Forest Phenology’s Relationship with Age-Class Structure in Northeast China’s Temperate Deciduous Forests

Phenological changes in forests directly influence the spatiotemporal dynamics of carbon fixation and the carbon and water cycles in terrestrial ecosystems. Previous studies have shown that variations in biological factors (e.g., canopy height, leaf area, water use efficiency) can increase uncertainty in forest phenology, and these variations are closely linked to tree species and forest age-class structure. However, the interaction mechanisms through which tree species and forest age-class structure influence phenological changes remain insufficiently explored. In this study, phenological changes and their interactions and response mechanisms to different dominant tree species and forest age-class structures were analyzed via Sentinel-2 normalized difference vegetation index (NDVI) time series data from 2020 and 2021 across 480 typical deciduous forest plots in northeastern China. The results were as follows: (1) There were significant differences (p < 0.05) in the intra-annual phenological responses of temperate deciduous landscapes to the interaction between tree species and forest age-class structure. (2) The indirect effect of forest age-class structure through tree species on phenology exceeded the indirect effect of tree species through forest age-class structure, with a difference of 30.77%–35.09%. (3) When the dominant tree species and forest age-class structure were not distinguished, phenological differences in temperate forests ranged from 3 to 41 days and 2 to 23 days, respectively. This study highlights the differential impacts of key biological factors and their interactions on regional forest phenology, offering valuable insights into how these factors influence forest landscapes and providing a theoretical basis for improving forest management strategies.