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        <title>Frontiers in Forests and Global Change | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/forests-and-global-change</link>
        <description>RSS Feed for Frontiers in Forests and Global Change | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-04-05T12:13:25.912+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1746510</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1746510</link>
        <title><![CDATA[A review on the resilience of temperate forests to extreme precipitation and wind events]]></title>
        <pubdate>2026-04-02T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Tijs Kuzee</author><author>Tommaso Locatelli</author><author>Suzanne Robinson</author><author>Mike P. Perks</author><author>Paul J. Burgess</author><author>Abdou Khouakhi</author>
        <description><![CDATA[Temperate forests which provide vital ecosystem functions through the provision of timber resources, carbon sequestration, and recreational value are increasingly affected by extreme weather events, with wind and precipitation extremes (drought and excessive rainfall) posing significant challenges to forest resilience. This review synthesizes current knowledge on the impacts of wind and precipitation extremes on temperate forests, focusing on compound disturbance interactions, vulnerability factors, and recovery processes through a systematic review of 248 sources. Research concentrated on single disturbances, with drought and wind most frequently studied. Moreover, there is a focus on short-term resistance and recovery, with limited evidence on reorientation (i.e., transition to a new ecosystem state). Furthermore, we assess recent advancements in disturbance modeling, remote sensing, and machine learning for detecting and forecasting damage from these events. The key observation is that remote sensing and disturbance models are rapidly growing areas of study, but they are skewed toward single disturbance types and are highly specific to particular ecosystems. Machine learning has reduced this specificity and allowed for more data integration in recent years, although small-scale disturbance detection in remote sensing remains challenging owing to data availability limitations. By integrating climate, ecological, and management perspectives, this review concludes that future research and practice must explicitly integrate compound events into multi-hazard models, supported by strengthened long-term (remote sensing) monitoring networks, and adopt adaptive silvicultural strategies. Improved monitoring and multi-hazard modeling will enhance early warning, attribution, and predictive capacity, thereby supporting risk-informed decision-making and the design of targeted adaptive management interventions. Such shifts are essential to sustain ecosystem services and enhance forest resilience under increasing climate extremes.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1724355</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1724355</link>
        <title><![CDATA[Impacts of historical land cover changes on carbon stocks in the Itacaiúnas River Basin, eastern Amazon]]></title>
        <pubdate>2026-03-31T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rosane Barbosa Lopes Cavalcante</author><author>Emily Ane Dionizio</author><author>Vitor Cirilo Araújo Santos</author><author>Lucas Felipe Ferraro Cardoso</author><author>Uilson Ricardo Venâncio Aires</author><author>Sâmia Nunes</author><author>Markus Gastauer</author>
        <description><![CDATA[Quantifying the long-term impacts of land use and land cover (LULC) change on carbon stocks is critical for guiding climate change mitigation strategies in tropical forest frontiers. In this study, we assessed the spatially explicit carbon balance of the Itacaiúnas River Basin (IRB), located in the Amazon arc of deforestation, from 1985 to 2021. To achieve this, we combined annual LULC maps with estimates of biomass and soil carbon stocks and burned area data to quantify carbon losses from deforestation, carbon gains from secondary forest regrowth, and direct fire emissions. Over the 36-year period, the IRB lost 335 Mt-C (40% of its original stock), mainly due to biomass loss associated with the conversion of primary forests to pasture. Protected areas, which cover 29% of the basin, contained 51% of the remaining carbon stock in 2021 and contributed only 4% to the net carbon loss. Fire emissions accounted for up to 12% of annual carbon losses during prolonged drought years. Secondary forests stored 23 Mt-C in 2021, although current regrowth rates remain insufficient to offset ongoing deforestation. These findings reinforce the importance of protected areas, forest restoration, deforestation control, and improved pasture management in supporting climate change mitigation and sustainable land management strategies across the Amazon.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1668996</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1668996</link>
        <title><![CDATA[Stakeholder insights for digital business model development in forest road monitoring]]></title>
        <pubdate>2026-03-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Felipe de Miguel-Díez</author><author>Ferréol Berendt</author><author>Ina Ehrhardt</author><author>Sergej Chmara</author><author>Tobias Cremer</author>
        <description><![CDATA[IntroductionVital to forest management, forest roads enable operations such as timber harvesting, fire protection, and recreational access. However, their functionality is threatened by insufficient maintenance driven by limited financial and human resources, and constraints related to the availability and quality of information, as well as suitable tools for systematic condition assessment. Traditional visual inspections are widely used in Germany but are subjective, inconsistent, and difficult to scale. This study examines stakeholder perspectives on implementing a digital forest road condition monitoring system to support predictive maintenance approaches.MethodsTo evaluate the feasibility and stakeholder acceptance, semi-structured qualitative interviews were conducted with 30 representatives from five stakeholder categories across Germany. Thematic content analysis was applied to assess current maintenance practices, data needs, technical and legal constraints, and the stakeholders’ willingness to contribute across stages of the system (data collection, processing, provision, and use).ResultsStakeholders broadly recognized the potential value of digital forest road condition data for planning maintenance, estimating costs, and improving navigation. However, adoption is constrained by limited digital competence and staffing, financial barriers, data protection and access-right concerns, and coordination challenges associated with fragmented forest ownership. Participants emphasized the need for reliable, standardized, and user-friendly solutions, and highlighted that long-term implementation depends on viable business model configurations (e.g., subscription or pay-per-use access models and remuneration schemes for data collection, such as flat rate) spanning multiple stakeholders.DiscussionBy aligning stakeholder interests and addressing legal, technical, and financial barriers, such configurations can enable the long-term operability of digital forest roads monitoring systems. These findings provide a qualitative foundation for developing scalable implementation concepts and business model configurations for digital forest road monitoring that are transferable beyond the German context.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1718836</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1718836</link>
        <title><![CDATA[Impact of forestry carbon sink policies on farmers’ willingness to utilize idle forest land: evidence from Fujian province, China]]></title>
        <pubdate>2026-03-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yunshu Tan</author><author>Xiang Huang</author><author>Rui Shu</author><author>Xiaojin Ren</author><author>Qin Chen</author>
        <description><![CDATA[The willingness of farmers to participate in forest land utilization is crucial to the realization of the “two-carbon” goal and the high-quality development of forestry, but existing studies lack empirical analyses of the specific impacts of carbon-neutral policies. Based on survey data from 411 farmers in Fujian Province, this study used a binary probit model to analyze the effects of farmers’ perceived effectiveness of carbon-neutral policies and related factors on their willingness to participate in forest land use. The results show that 74.6% of farmers are willing to utilize idle forest land. Farmers who perceive carbon financial policies, fiscal policies, tax preference policies, and sink price policies as effective are significantly more willing to participate. Additionally, years of education, number of family laborers, and forest land quality also have a positive effect. Conversely, family non-farm income and accessibility to transportation show a negative association, whereas gender, age, occupation, forestry business activities, and subsidies do not demonstrate statistically significant effects. The study suggests that policy instruments and farmers’ characteristics jointly shape their behavior. Drawing on the link between perceived policy incentives and participation willingness, the findings imply that prioritizing financial support systems and carbon financial products could lower participation thresholds. Furthermore, optimizing fiscal policies, offering tax incentives to reduce burdens, and coordinating carbon sink markets to stabilize price expectations may help align policy designs with farmers’ incentives to efficiently utilize forest land. These measures provide a practical basis for the “dual-carbon” goal.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1770225</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1770225</link>
        <title><![CDATA[Towards in-field live fuel moisture content estimation using multi-wavelength terrestrial laser scanning]]></title>
        <pubdate>2026-03-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jesús Torralba</author><author>F. Mark Danson</author><author>Luis A. Ruiz</author><author>Jaime Almonacid-Caballer</author><author>Pablo Crespo-Peremarch</author><author>Juan Pedro Carbonell-Rivera</author>
        <description><![CDATA[The impact of climate change on vegetation dynamics and wildfire risk has been a subject of considerable research interest. Live fuel moisture content (LFMC) is a critical factor in assessing fire risk and influencing fire ignition and behaviour. Satellite remote sensing techniques provide information on LMFC dynamics, but spatial and temporal resolution hinder understanding in structurally complex forests with interconnected tree and shrub layers. Multi-wavelength terrestrial laser scanning (TLS) sensors can measure the structural and spectral properties of forests and have demonstrated their potential for monitoring LFMC. However, studies of LFMC in shrubs are scarce despite their key role in fire spread. In this study, we investigated the capacity of a dual-wavelength SALCA (Salford Advanced Laser Canopy Analyser) TLS (1063 and 1545 nm) and the single-wavelength Trimble X6 (1500 nm) to estimate LFMC in six Mediterranean forest plots (135 individual plants, 18 species). Analysis at different separate plots and individual-species levels identified key factors affecting LFMC prediction using TLS. At plot level, linking spectral indices and LFMC is challenging due to species diversity in crown structures, ages, sizes and leaf types. Our results suggest that detector heating by solar radiation could alter the sensor calibration and reduce model accuracy. Nevertheless, in some areas the multiple linear regression models achieved an Radj2 up to 0.82 and an RMSE of 7.66%. At the species level, models showed stronger relationships with LFMC (Radj2ranging from 0.43 to 0.88) and a relatively low RMSE (RMSE from 1.92 to 3.97%). Overall, univariate relationships between LFMC and individual-wavelength reflectance were not consistent across species or most plots. Considering these results, combining the capacity of dual TLS devices to estimate LFMC with the structural information that they provide, open a potential to improve field work sampling for wildfire risk assessment. Extending the research to cover a wider range of tree, shrub and herbaceous species in the future will advance our understanding of LFMC dynamics and contribute to more accurate fire behaviour modelling.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1762054</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1762054</link>
        <title><![CDATA[Optimizing the landscape pattern of blue-green space is more effective than simply increasing the area for cooling effect]]></title>
        <pubdate>2026-03-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Guanglong Bao</author><author>Xiaohan Sun</author><author>Chenchen Fan</author><author>Wenwen Li</author><author>Xiaoming Li</author><author>Fei Yan</author><author>Tianran Zhao</author>
        <description><![CDATA[BackgroundBlue-Green Space (BGS) is critical for mitigating the Urban Heat Island (UHI) effect amid rapid global urbanization. However, the comparative cooling efficiency of BGS landscape configuration versus simple area expansion remains understudied, particularly regarding long-term spatiotemporal non-stationarity in large-scale economic zones.MethodsThis study investigates the spatiotemporal evolution of BGS and its regulatory effects on Land Surface Temperature (LST) in the Yangtze River Economic Belt (YEB) from 2000 to 2024. Using Landsat-derived metrics, we employed Global/Local Moran’s I to identify thermal clustering and the Spatiotemporal Geographically Weighted Regression (GTWR) model to quantify non-stationary relationships, explicitly comparing the marginal cooling contributions of landscape pattern indices against area proportion (PLAND).ResultsThe YEB exhibited a “downstream cooling, mid-upstream warming” trend with significant spatial clustering. The GTWR model (R2 = 0.840) revealed that optimizing landscape configuration yields superior cooling benefits to mere area expansion in specific spatiotemporal contexts. High patch connectivity (CONTAG) significantly mitigated heat in early urbanization stages, while complex patch shapes (FRAC_MN) and edge density (ED) were more effective in high-density urban cores.ConclusionThese findings challenge the “area-first” planning paradigm, supporting an “efficiency-first” strategy. To maximize urban climate resilience, we propose differentiated optimization pathways that prioritize contiguous preservation in mountainous regions and hydrological connectivity in water-rich networks.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1744089</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1744089</link>
        <title><![CDATA[Multidimensional analysis of factors affecting rural development in forest villages: a case study of Bursa/Türkiye]]></title>
        <pubdate>2026-03-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Murat Köse</author><author>Bekircan Balcı</author>
        <description><![CDATA[Forest villages in Türkiye, similar to those in many other countries, constitute some of the most low-income and low-access communities. This situation has caused more migration from forest villages to cities. The aim of this study is to reveal the most important factors affecting rural development in Bursa, to rank the villages according to their development levels, to derive a comprehensive, applicable, and generalizable development index (DI), and to determine the variables that best explain the differences in development levels. The study also aims to evaluate the subject in terms of forestry policy and to develop suggestions within this scope to eliminate development differences between villages and ensure rural development. Therefore, in order to achieve the purpose of this study and to provide concrete data for the strategies and policies to be developed; various combined and complementary analyses, such as factor analysis, Geographic Information Systems (GIS), regression analysis, and discriminant analysis, were used. In this study, as a result of factor analysis conducted with 52 variables, approximately 72% of the factors affecting rural development in forest villages were explained by three factors: (1) population characteristics and infrastructure status, (2) location of the forest village and number of employees, (3) climatological factors and income status. Based on these three factors, index coefficients were developed at the village level using variables representing the factor dimensions, and villages and districts were ranked according to their level of development using these coefficients. Furthermore, the suitability of this ranking was tested using discriminant analysis based on 52 variables. According to the results of the discriminant analysis, the success rate of the ranking based on DI was found to be 93.2%. Allocating a higher share of resources to underdeveloped villages arguably would support sustainable development of the region. Although forestry work plays an important role in the livelihoods of villagers in underdeveloped villages, forestry-related livelihoods alone are not sufficient.”]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1771857</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1771857</link>
        <title><![CDATA[Climate-driven susceptibility of natural wildfires using Random Forest under future climate scenarios in Mediterranean forests of Türkiye]]></title>
        <pubdate>2026-03-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Nuri Bozali</author>
        <description><![CDATA[IntroductionMediterranean forest ecosystems are highly susceptible to natural wildfires under climate change, driven by rising temperatures, reduced precipitation, and pro¬longed dry periods. This study aimed to develop a climate-based natural wildfire susceptibility model using the Random Forest (RF) machine learning algorithm for the Emet Forest Management Directorate in the Mediterranean climate zone of Türkiye. This study considers only natural wildfires and excludes human-induced fire events.MethodsAll fire occurrence data used in the modeling process consist solely of recorded natural wildfire ignitions. The model incorporated 19 bioclimatic variables with historical wildfire occurrence data, using 258 recorded natural fire locations from 2015 to 2025 as reference points. Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis.Results and discussionAn Area Under the Curve (AUC) value of 0.711, which indicates moderate but acceptable predictive performance and is consistent with values reported in similar climate-driven susceptibility studies. The model results showed that the most influential drivers of fire susceptibility were temperature seasonality (BIO4), dry season precipitation (BIO17), and the minimum temperature of the coldest month (BIO6). According to future projections based on the Representative Concentration Pathways (RCP) 2.6 scenario using the Beijing Climate Center-Climate System Model Version 2-Medium Resolution (BCC-CSM2-MR) climate model for 2050 and 2070, the proportion of areas with high and extremely high fire susceptibility is projected to increase from 56.4% in 2025 to 64.0% in 2070, while low-and moderate-suscep¬tibility zones decline. This study provides one of the first climate-only, machine learning-based evaluations of present and future natural wildfire susceptibility in Mediterranean forests of Türkiye. These results revealed the escalating threat of wildfires in Mediterranean forests under climate change.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1741821</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1741821</link>
        <title><![CDATA[The psychological mediations of green window view exposure on campus and freshman adaptation: a cross-sectional study in Nanjing, China]]></title>
        <pubdate>2026-03-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yurui Feng</author><author>Wei Wei</author><author>Yue Yin</author><author>Xuedong Li</author>
        <description><![CDATA[Campus green window views function as vital micro-scale urban forests for students, offering mental health benefits. However, the quantitative links between perceived green window view characteristics and the psychological adaptation of university freshmen, along with the underlying mediations, are not well established. This study examined these relationships by assessing three perceived green window view characteristics—Naturalness, Visual Scale, and Stewardship—from dormitories, classrooms, and libraries at Nanjing Forestry University’s Baima Campus. Data were collected from first-year freshmen via an online questionnaire, which measured perceived green window view exposure, student adaptation to college (SAC), perceived stress (PS), positive and negative affect (PAff/NAff), and sociodemographic factors. We employed Spearman’s correlation to analyze associations. Structural equation modeling (SEM) was used to test the mediating roles of perceived stress, positive affect, and negative affect. Results revealed that the dormitory visual scale (Dorm_VS) has a significant direct association with freshmen’s adaptation. Mediation analysis identified significant pathways: dormitory visual scale (Dorm_VS) could reduce negative affect (NAff); library visual scale (Lib_VS) could increase positive affect (PAff); and classroom stewardship (Cl_D) could lower both perceived stress (PS) and negative affect (NAff), which, in turn, was associated with student adaptation to college (SAC). Additionally, the classroom visual scale (Cl_VS) could exhibit a marginally significant (p < 0.1) indirect association with freshmen’s adaptation by increasing positive affect (PAff). Meanwhile, the classroom stewardship (Cl_D) could also show a marginally significant (p < 0.1) indirect association with freshmen’s adaptation by decreasing positive affect (PAff). In summary, the perceived green window view exposure in campus serves as a Nature-Based Solution (NbS), which reveals the core principle that the association of perceived greenery window views varies according to building function and is achieved through different psychological mediating pathways, by constructing a comprehensive model encompassing multiple buildings (dormitories, classrooms, libraries) and multiple perceived indicators (Naturalness, Visual Scale, Stewardship). These findings offer scientific insights for precision green space planning in sustainable campus and urban development.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1767810</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1767810</link>
        <title><![CDATA[Systematic protection of threatened vertebrates—a solution balancing ecological benefits and socio-economic costs]]></title>
        <pubdate>2026-03-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kun Ma</author><author>Yinghui Chen</author><author>Xiaoming Li</author><author>Weiming Li</author><author>Han Cai</author><author>Feng Lv</author>
        <description><![CDATA[It is critical for global conservation to expand protected area networks in biodiversity hotspots with dense human populations, but this faces substantial socioeconomic constraints. Relying solely on area expansion can trigger resistance to implementation, which undermines conservation outcomes. To address this issue, we developed a dual-cost framework that integrates land-use opportunity costs and environmental conflict risks in order to evaluate the feasibility of conserving threatened vertebrates. Stacked Maximum Entropy (MaxEnt) habitat suitability predictions (33 species) and known distribution ranges (20 species), we mapped critical habitats for 53 species, then used Marxan to compare spatial efficiencies under varying cost scenarios. The final priority conservation network under the integrated optimization scenario (S3-b) covers an area of 134,938 km2, which constitutes 20.02% of the total study area. This area includes 660 existing national protected areas (NPAs), with a total overlap of 53,329 km2, representing 32.54% of the priority conservation areas. The network is mainly distributed across the northern parts of Region III, the southern regions of Region I, and the central parts of Region IV, reflecting critical biodiversity hotspots with high ecological value. Our findings suggest that the integrated optimization scenario (S3) most effectively balances ecological gains with social costs. In contrast, the status quo augmentation strategy (S3-b) revealed that over 52% of priority units, including 462 existing national protected areas, fall within high-conflict “low-feasibility zones”. While this scenario requires lower annual funding (6.44–12.18 billion CNY) than complete restructuring, the high conflict risk highlights the limitations of strict uniform protection in areas with frequent human–land interaction. We therefore argue that transitioning to differentiated management based on feasibility grading would provide a more effective way of balancing ecological security with community livelihoods.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1692799</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1692799</link>
        <title><![CDATA[Storing plant photosynthetic products as a complementary climate mitigation strategy: a conceptual perspective on carbon storage and ecological trade-offs]]></title>
        <pubdate>2026-03-18T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Lei Gao</author><author>Hui Xiang</author><author>Wenjun Liu</author>
        <description><![CDATA[Global warming driven by carbon dioxide (CO2) emissions is a major global concern. Forests play a vital role in climate mitigation as significant carbon sinks, and avoiding deforestation and forest degradation remains essential for limiting atmospheric CO₂. However, it remains unclear whether minimizing the use of plant-derived biomass necessarily maximizes climate benefits. We present a conceptual Perspective synthesizing existing literature and argue that forests should be viewed not only as static carbon reservoirs but also as dynamic systems that continuously sequester carbon through photosynthesis. Where forest area, ecological integrity, biodiversity, and soil stability are maintained, moderate and well-regulated use of plant-based materials—particularly for durable, non-combustion applications—may extend the residence time of biogenic carbon within the human economy and complement in situ forest carbon storage. We emphasize that carbon represents only one dimension of sustainability. Strategies aimed at increasing storage of plant photosynthetic products must consider trade-offs involving soil carbon, nutrient cycling, biodiversity, hydrology, and non-CO₂ greenhouse gas dynamics. This Perspective aims to stimulate discussion on evaluating plant-derived carbon storage within integrated, multi-objective sustainability frameworks rather than pursuing carbon maximization alone.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1732188</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1732188</link>
        <title><![CDATA[Predicting people perceived plant diversity in urban green spaces using panoramic photos: a case study of Shanghai]]></title>
        <pubdate>2026-03-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuting Yin</author><author>Binyi Liu</author><author>Qing Chang</author>
        <description><![CDATA[IntroductionUrban green spaces (UGSs) play a dual role in high-density cities: they are crucial for biodiversity conservation and serve as key venues for promoting residents’ health. However, the benefits gained by people in these settings depend less on objectively measured biodiversity and more on their subjective perception of it. Visual cues, which account for over 80% of sensory input, significantly shape this perception.MethodsThis study explores the interrelationships among measured plant diversity, perceived plant diversity, and visual landscape characteristics in UGSs, so that to develop a predictive model for perceived diversity using the other two variables. Based on a case study of nine representative parks in Shanghai, the research compared measured plant diversity—using four indices (arbor, shrub, herbaceous, and community diversity)—with perceived plant diversity and evaluated the influence of visual landscape features.ResultsResults showed a significant mismatch between measured and perceived diversity. Furthermore, visual characteristics were more effective than measured biodiversity in predicting perceived plant diversity. These findings offer practical, short-term design strategies for enhancing perceived biodiversity in urban parks—complementing longer-term ecological measures aimed at increasing actual biodiversity.DiscussionThis study advances the understanding of how objective biodiversity, human perception, and visual environment interact, and supports the design of nature-based solutions that benefit both human well-being and biodiversity conservation.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1763211</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1763211</link>
        <title><![CDATA[Study on the path of green total factor productivity improvement in forestry in China under spatio-temporal heterogeneity: based on dynamic QCA analysis]]></title>
        <pubdate>2026-03-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Danyang Xu</author><author>Yunfan Zhang</author><author>Congcong Cao</author><author>Yuan Wang</author><author>Zhen Lin</author>
        <description><![CDATA[IntroductionUnder the common agenda of addressing global climate change and promoting sustainable development, forestry has become a key area for achieving carbon neutrality and ecological product value. Forestry green total factor productivity (GTFP) is a core indicator for measuring the low-carbon transformation and green growth capacity of forestry.MethodsBased on panel data from 30 provinces (regions) in China from 2005 to 2022, this study uses the global super efficiency SBM model to measure forestry GTFP in each province, combines the center of gravity model and spatial autocorrelation analysis to reveal the spatiotemporal distribution characteristics and evolutionary trends of forestry GTFP, applies the Dagum Gini coefficient to decompose regional differences and their sources, and identifies multidimensional configurational paths for enhancing provincial forestry GTFP through the dynamic qualitative comparative analysis (QCA) method, revealing the forestry green growth patterns and their driving mechanisms under different combinations of conditions.Results(1) The overall trend of forestry GTFP showed a fluctuating upward trend, with the mean increasing from 0.75 to 1.27. The spatial pattern evolved from local point aggregation to multipolar diffusion, and high-value areas exhibited significant spatial spillover effects; (2) The overall differences in forestry GTFP show a fluctuating convergence trend, with the overall Gini coefficient decreasing from 0.275 to 0.198. Regional differences are the main source of overall imbalance, and some low-value areas exhibit catch-up effects; (3) The seven conditional variables are not necessary conditions, and six configuration modes are identified for four paths: resource capital driven, capital driven, resource industry driven, and management industry driven.DiscussionBased on these findings, this study proposes to build a new pattern of new quality productivity of forestry that is oriented toward consolidating foundational capacity, centered on improving quality and efficiency, with institutional innovation as the guiding thread, and ensured through full-process regulation and management.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1755489</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1755489</link>
        <title><![CDATA[Infrared spectroscopy enables rapid identification of Scots pine resistant to Diplodia sapinea]]></title>
        <pubdate>2026-03-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Patrick Sherwood</author>
        <description><![CDATA[Many forest pathogens have become increasingly damaging as climate-driven stress intensifies disease outbreaks. A prominent example is Diplodia sapinea, which is causing more frequent and destructive shoot blight and dieback, particularly across northern Europe. Developing resistant planting stock is a priority, but screening currently depends on destructive inoculation assays and multi-year field trials, making the process slow and difficult to scale. This study evaluated whether a handheld Fourier-transform infrared (FT-IR) spectrometer that provides rapid and non-destructive sampling can identify constitutive chemical signatures associated with relative resistance prior to infection. FT-IR spectra were collected from needles, shoots, and stem phloem from Swedish pine families across two experimental years, followed by artificial inoculations to phenotype lesion development. A combined sparse partial least squares discriminant analysis and support vector machine workflow achieved 65–81% cross-validated accuracy in distinguishing resistant from susceptible trees, with shoot spectra consistently producing the strongest models. Principal component analysis indicated clear chemical differences between years, yet resistance-associated patterns were stable across tissues. The most frequently selected wavenumbers grouped into four biochemical domains: cell-wall polysaccharides, cellulose/hemicellulose bonding, phenolics and proteins, and aliphatic lipids/cutin, corresponding to known conifer defense pathways. These findings demonstrate that portable FT-IR spectroscopy can capture biologically meaningful variation in constitutive defense chemistry and offers a rapid, scalable approach for resistance phenotyping in Scots pine breeding programs.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1769882</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1769882</link>
        <title><![CDATA[#SecureTree: pursuing new trajectories for risk assessment models in precision forestry]]></title>
        <pubdate>2026-03-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Oscar Tamburis</author><author>Mario Magliulo</author><author>Vincenzo Magliulo</author><author>Giulio Perillo</author><author>Adriano Tramontano</author><author>Eugenio Vocaturo</author>
        <description><![CDATA[The #SecureTree model presents a novel method for assessing tree risk through IoT-based sensors and analytics within a precision forestry context. Unlike conventional techniques that often depend on individual, subjective mechanical assessments, #SecureTree utilizes a network of minimally invasive sensors to continuously monitor key biophysical factors such as temperature, humidity, and branch movement. These data are processed to generate real-time risk assessment maps based on the analysis of trees’ behavioral progression under varying environmental conditions. The primary innovation of the model lies in its capability to track multiple trees over extended periods, providing forest managers with objective, data-driven insights into tree stability and health. These insights make it possible to identify long-term risk patterns, allowing for proactive interventions and improved emergency management. By moving from isolated evaluations to a scalable, sensor-based approach, #SecureTree greatly enhances the accuracy of tree risk assessment and establishes a new benchmark in environmental management. This model allows for significant advancements in precision forestry, enabling more effective, real-time decision-making while promoting sustainable forest management practices aligned with digital innovation.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1792325</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1792325</link>
        <title><![CDATA[Use of rosemary (Rosmarinus Officinalis) plant as impregnation in wood material and retention values]]></title>
        <pubdate>2026-03-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tahsin Çetin</author>
        <description><![CDATA[This study investigated the suitability of rosemary (Rosmarinus officinalis) plant extract and hydrosol for use as a preservative in Scots pine (Pinus sylvestris l.) and Turkish beech (Fagus orientalis l.) wood. The air-dry and fully dry specific gravity, tensile-shrinkage, water absorption-expansion (swelling) properties, and retention quantities of the impregnated samples were determined and statistically evaluated. Experimental applications were carried out using short, medium and long-term immersion methods; samples were soaked in water for 6, 12, 24, 48, 72, and 96 h and performance analyses were performed. The findings revealed that tree species was a statistically significant and decisive factor on specific gravity values (F = 15.013; p < 0.001). Turkish beech wood (Mean = 0.63) exhibited higher specific gravity values compared to Scots pine wood (Mean = 0.53). While the impregnation period and some factor interactions were found to be significant on air-dry specific gravity, it was determined that the effect of variables other than tree species was limited in terms of fully dry specific gravity. A significant effect of time (F = 97.764; p < 0.001), concentration (F = 12.627; p < 0.001) and impregnation time (F = 11.713; p < 0.001) factors was detected in the tensile-shrinkage behavior. In particular, it was found that hydro-sol and hydro-sol+mordant applications increased dimensional stability by reducing tensile-shrinkage values. The dominant effect of tree species (F = 271.081; p < 0.001) and time (F = 169.730; p < 0.001) on water absorption properties was noteworthy; Scots pine (67.26%) was found to have a higher water absorption rate than Turkish beech (48.87%). Among the applications, a 10% hydrolysate concentration increased the water uptake rate to 60.92%, whereas the extract+mordant combination yielded more balanced results at 55.93%. It was determined that expansion (swelling) values were particularly affected by tree species, concentration, and time factors; extract-based applications tended to increase expansion, while hydrosol applications provided more limited dimensional changes. It was found that a 10% hydrosol application yielded an average swelling value of 4.26%, representing a reduction of approximately 22% compared to the control group’s value of 5.51%. Tree species was a determining factor in terms of retention values; results ranged from 0.34–1.62% in Scots pine and 0.13–0.73% in Turkish beech. In conclusion, rosemary hydrosol demonstrated more favorable performance in terms of dimensional stability in wood materials, while extract applications were found to have enhancing effects on certain physical properties. The findings suggest that rosemary extract and hydrosol could be considered as environmentally friendly alternatives in the ecological wood preservation industry, particularly for interior applications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1755893</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1755893</link>
        <title><![CDATA[Analysis of the perception and acceptability of circular economy strategies by stakeholders in the wood and forestry sector in Benin]]></title>
        <pubdate>2026-03-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yann Emmanuel Miassi</author><author>Nancy Gélinas</author><author>Kossivi Fabrice Dossa</author><author>Idiatou Bah</author>
        <description><![CDATA[The circular economy is now being presented as a promising way to respond to the increasing depletion of forest resources. However, its application remains limited in value chains in sub-Saharan Africa. This study aims to analyses the perception and acceptability of four circular approaches proposed to actors in the timber and forestry sector in Benin, to assess their potential for implementation in a local context. The research is based on a field survey conducted in the north and south of the country, using semi-structured interviews with direct and indirect actors in the sector. The data collected was subjected to qualitative analysis, supported by descriptive statistics and econometric models to achieve the study’s objectives. Four circular economy strategies were proposed: eco-design, focused on sustainable product design; optimization of operations, aimed at improving process efficiency while taking ecological criteria into account; loan-exchange, which encourages the pooling of resources between actors; and industrial ecology, focused on inter-company coordination for systemic flow management. The results show overall favorable acceptability, with a marked preference for eco-design, optimization, and industrial ecology, which are perceived as particularly beneficial from an environmental standpoint. The loan-exchange strategy stands out for its social roots, strengthening solidarity and community cooperation. However, the use of these strategies remains dependent on factors such as the size and legal status of companies, access to information, the profile of stakeholders, and the local context.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1795519</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1795519</link>
        <title><![CDATA[Interactions between biotic and abiotic factors shape phylogenetic community assembly in southern range-margin Picea jezoensis forests]]></title>
        <pubdate>2026-03-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Seung-Jae Lee</author><author>Ah-Ran Jo</author><author>Seong-Rok Lee</author><author>Dong-Bin Shin</author><author>Yeong-Eun Kim</author><author>Jun-Gi Byeon</author><author>Seung-Hwan Oh</author>
        <description><![CDATA[Identifying factors that control community formation is crucial for understanding biodiversity patterns. Although numerous studies utilize either within- or among-community indicators to explain community formation processes, few have assessed the additional insights gained by integrating the two. Accordingly, we examined Picea jezoensis forests in South Korea and northeastern China using complementary within- and among-community approaches and discuss the implications of interpreting these metrics together: (1) we identified the abiotic (e.g., topography and climate) and biotic (e.g., stand structural diversity and community-weighted proportion values of dormancy and dispersal forms) controls of phylogenetic community structure (net relatedness index [NRI] and nearest taxon index [NTI]) across forest strata (whole strata, upperstory, and understory) using piecewise structural equation modeling (pSEM); and (2) we quantified among-community phylogenetic differentiation by decomposing phylogenetic beta diversity (PBD) into turnover and nestedness and testing their relationships with climatic distance, geographic distance, and pairwise elevational difference. (3) We explored how within-community phylogenetic structure (NRI/NTI) relates to among-community phylogenetic differentiation (PBD components). Our results showed that the primary drivers of phylogenetic structure varied by forest strata and metric. Specifically, elevation, mean annual temperature (MAT), and community-weighted proportion (CWP)-based dormancy forms were the dominant predictors for NRI in both the whole strata and understory. In contrast, NTI were primarily shaped by abiotic factors (elevation and MAT) in the upperstory, while biotic constraints—specifically dormancy forms—showed a greater contribution in the understory. Furthermore, among PBD components, turnover was the primary contributor and was strongly associated with climatic distance. This climatic influence remained dominant even after controlling for geographic distance. In contrast, nestedness was best explained by pairwise elevational differences. By bridging within- and among-community metrics, this study helps contextualize how local-level assembly signals may scale up into regional phylogenetic patterns, offering a more unified understanding of forest community formation across spatial scales.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1775825</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1775825</link>
        <title><![CDATA[Murphy’s law, Parkinson’s law, Pareto principle: collaborative management of forest fires based on risk analysis]]></title>
        <pubdate>2026-03-10T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Yanyan Li</author><author>Yuntao Bai</author>
        <description><![CDATA[The escalating frequency and scale of global forest fires, exacerbated by climate change and human activities, present a critical challenge to ecosystem stability and public safety. Traditional forest fire management often suffers from inefficient resource allocation and inadequate risk mitigation due to its failure to systematically address inherent systemic biases and uncertainties. The purpose of this study is to investigate how three fundamental principles—Murphy’s Law, Parkinson’s Law, and the Pareto Principle—influence the effectiveness of collaborative forest fire management from a risk analysis perspective. Methodologically, the study employs a differential game theory framework to model the strategic interactions between government agencies and environmental organizations, incorporating risk assessment parameters. The key findings reveal that the strategic approach of stakeholders is highly sensitive to the perceived benefits of collaboration. Specifically, government agencies tend to adopt strategies aligned with the Pareto Principle when collaboration benefits are low, focusing on critical priorities, but shift towards behaviors reflective of Parkinson’s Law when benefits are high, potentially leading to resource expansion and inefficiency. In contrast, environmental organizations consistently demonstrate management approaches that adhere to the Pareto Principle. The study concludes that explicitly accounting for these behavioral principles is crucial for designing robust collaborative mechanisms. The primary contribution and novelty of this research lie in the original integration of these well-known sociological and management principles into a formal analytical model for disaster management. This novel framework provides a valuable tool for policymakers to anticipate stakeholder behavior, optimize resource deployment, and enhance the overall resilience of forest fire management systems against unforeseen risks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/ffgc.2026.1768700</guid>
        <link>https://www.frontiersin.org/articles/10.3389/ffgc.2026.1768700</link>
        <title><![CDATA[Enhanced forest monitoring through mapping with integrated seasonal canopy and spectral reflectance features]]></title>
        <pubdate>2026-03-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Byungwoo Chang</author><author>Wontaek Lim</author><author>Dongwook W. Ko</author><author>Wanmo Kang</author><author>Kwangil Cheon</author>
        <description><![CDATA[Forest mapping is essential for sustainable forest management and climate adaptation, enabling the assessment of forest composition and condition to prevent degradation. This study developed a U-Net-based deep learning framework for forest type classification using Sentinel-2 MSI satellite imagery and vegetation indices that capture seasonal canopy properties. A two-step approach was adopted, first delineating forested areas and then classifying forest types into needleleaf, broadleaf, and mixed forests. The forest area classification model achieved an overall accuracy of 0.958 (Kappa = 0.916), confirming reliable separation of forest and non-forest areas. For forest type classification, incorporating multi-seasonal imagery consistently enhanced performance, with the NDVI-based model achieving the highest overall accuracy of 0.831 (Kappa = 0.698). These results highlight the importance of integrating multi-seasonal spectral information to capture canopy variability and improve classification accuracy. The resulting reproducible framework thus supports ecosystem monitoring, hazard assessment, and adaptive forest management, offering foundational data for near real-time resource management under changing climatic conditions.]]></description>
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