Trees, Forests and People最新文献

Mixed plantations of Alnus formosana and Pinus massoniana improve ecosystem multifunctionality than monoculture plantations 台湾桤木与马尾松混交林比单一人工林能提高生态系统的多功能性

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-24 DOI: 10.1016/j.tfp.2026.101171

Luocan Zhou , Linjuan Huang , Jingzhong Shi , Yandi Qin , Lihui Deng , Shiyao Liang , Qile Tang , Guoqiang Tang , Wenhui Shen , Zhangqiang Tan , Weichao Teng

Long-term management of Pinus massoniana monoculture faces significant challenges, including low productivity, nutrient depletion, and weakened ecological functions. Alnus formosana, a native nitrogen-fixing species in southern China, can increase soil fertility and accelerates nutrient cycling. However, the impact of its mixed cultivation with P. massoniana on ecosystem multifunctionality (EMF) remains unclear. This study assessed tree growth, soil characteristics, enzyme activity, and EMF in monocultures and mixed forests at 1:2, 1:1, and 2:1 ratios (APP, AP, and AAP). Results showed that mixed-species treatment significantly increased tree growth index (TGI) of A. formosana but decreased that of P. massoniana (P<0.05). In mixed forests, A. formosana had higher diameter at breast height (DBH), tree height (TH), crown width (CW), clear bole height (CBH) and tree volume (V) than P. massoniana, and exhibited stronger competitive effects (Slope-A=1.12∼1.27) on DBH and CW compared to P. massoniana (Slope-P=0.65∼0.96). Soil quality index (SQI) and EMF significantly increased in mixed forests than in monocultures, as evidenced by higher soil C- and N-acquisition enzyme activities and related nutrients. In mixed forests, TGI was positively correlated with SQI of A. formosana but negatively correlated with that of P. massoniana, which led to the growth of A. formosana being more sensitive to available nutrients (nitrate nitrogen, available phosphorus, and ammonium nitrogen), while the growth of P. massoniana was more reliant on soil total nutrients (total nitrogen and total phosphorus). Notably, A. formosana exhibited the highest TGI, SQI, and EMF in the AAP treatment. Thus, the 2:1 (AAP) mixing ratio is recommended for the scientific management of P. massoniana and A. formosana mixed forests.

马尾松单一栽培的长期管理面临着生产力低下、养分耗竭和生态功能减弱等重大挑战。台湾桤木是华南地区特有的固氮树种，具有提高土壤肥力和加速养分循环的作用。然而，其与马尾草混种对生态系统多功能性（EMF）的影响尚不清楚。本研究以1:2、1:1和2:1的比例（APP、AP和AAP）评估了单一栽培和混交林中的树木生长、土壤特征、酶活性和EMF。结果表明：混种处理显著提高了台湾杉木的林木生长指数（TGI），降低了马尾松的林木生长指数（P<0.05）；在混交林中，台湾杉树胸径、树高、冠宽、净孔高和树体积均高于马尾松，且对胸径和净孔高的竞争效应（Slope-A=1.12 ~ 1.27）高于马尾松（Slope-P=0.65 ~ 0.96）。混交林土壤质量指数（SQI）和EMF显著高于单作，土壤C、n获取酶活性和相关养分显著增加。在混交林中，台湾桤木的TGI与SQI呈显著正相关，与马尾松的SQI呈显著负相关，说明台湾桤木的生长对速效养分（硝态氮、速效磷、铵态氮）更为敏感，而马尾松的生长对土壤全养分（全氮、全磷）更为依赖。在AAP处理下，台湾槐树表现出最高的TGI、SQI和EMF。因此，建议以2:1 （AAP）的混合比例进行马尾松与台湾杉木混交林的科学管理。

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引用次数: 0

The vacuum system increases maple sap yield without extending the sugar season 真空系统在不延长制糖季节的情况下提高枫汁产量

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-23 DOI: 10.1016/j.tfp.2026.101169

Nita Dyola, Roberto Silvestro, Sergio Rossi

The vacuum system is largely used in the maple industry to enhance sap yield without compromising its quality. Understanding how vacuum influences the timings and dynamics of exudation compared with the traditional gravity system is crucial for maximizing yield and optimizing the productive process. This study tests two diverging hypotheses, i.e., the vacuum (i) extends the productive time window, and (ii) enhances the rate of sap extraction. We monitored sap exudation at high temporal resolution in 2023 in a commercial sugar bush at the Northern boundary of maple distribution in Quebec, Canada. Sap yield in vacuum and gravity was measured continuously with flow meters and tipping-bucket gauges, respectively. The sap season, lasting 34-36 days, was similar between the two systems. The vacuum reached 26.19 L tap⁻¹ compared with 13.45 L tap⁻¹ for gravity, representing an increase of 94.72%. While 13-20% of the days contributed to 82-89% of the total sap in gravity, the vacuum exhibited a lower variability in sap exudation and maintained a relatively consistent yield. Both systems relied on freeze–thaw cycles to trigger exudation, but vacuum amplified exudation, sustained yield during unfavorable weather conditions, and maintained nighttime production when gravity was unproductive. These results demonstrate how vacuum increases sap yield, primarily accelerating the extraction rates rather than extending the sap season. By stabilizing yield, vacuum ensures more predictable and reliable sap exudation, supporting workforce planning throughout the sap season.

真空系统在枫工业中广泛使用，以提高树液产量而不影响其质量。与传统的重力系统相比，了解真空对渗出时间和动态的影响对于最大限度地提高产量和优化生产过程至关重要。本研究检验了两个不同的假设，即真空(i)延长了生产时间窗口，（ii）提高了树液的提取率。在加拿大魁北克省枫树分布北部边界的一个商业糖丛中，我们在2023年以高时间分辨率监测了树液渗出。分别用流量计和翻斗式量规连续测量真空和重力下的液产率。两种系统的树液季节相似，持续时间为34-36天。真空为26.19 L，而重力为13.45 L，增长了94.72%。在重力条件下，13-20%的时间贡献了总汁液的82-89%，而真空条件下汁液渗出的变异性较低，保持了相对稳定的产量。这两种系统都依赖于冻融循环来触发渗出，但真空放大了渗出，在不利的天气条件下保持产量，在重力无效的情况下保持夜间生产。这些结果证明了真空是如何提高汁液产量的，主要是加快了提取速度，而不是延长了汁液的季节。通过稳定产量，真空确保更可预测和可靠的汁液渗出，支持整个汁液季节的劳动力规划。

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引用次数: 0

Street-tree composition, infrastructure conflicts and carbon storage in a medium-sized Brazilian city 巴西一座中型城市的街道树木组成、基础设施冲突和碳储存

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-23 DOI: 10.1016/j.tfp.2026.101167

Rodrigo Ferreira de Morais , Gustavo Hiroaki Shimizu , Leandro de Souza Pinheiro , Daniela Fernanda da Silva Fuzzo , Edimar Olegário de Campos Júnior , Enéas Ricardo Konzen , Marcos Vinicius Bohrer Monteiro Siqueira

This study presents an integrated qualitative and quantitative assessment of street trees in a medium-sized Brazilian city, aiming to evaluate species composition, tree health, infrastructure conflicts, spatial heterogeneity, and ecosystem service provision. The street-tree community exhibited strong dominance by a limited number of species and a high prevalence of exotic taxa, indicating low structural evenness and long-standing limitations in urban planning practices, which increase vulnerability to pests, diseases, and management failures. Most trees were classified as healthy or in good condition; however, biotic stressors such as fungal infections and insect activity significantly reduced the probability of individuals reaching higher health categories. Conflicts between trees and urban infrastructure were widespread, particularly those related to root exposure and interference with overhead utilities, and displayed clear spatial variation among neighborhoods, suggesting unequal planning strategies and maintenance efforts across the urban landscape. Although direct human damage to trees was generally low, its uneven distribution among species highlights species-specific susceptibility and management challenges. Ecosystem services, including carbon storage and microclimatic regulation, were disproportionately concentrated in a small subset of species, reinforcing the structural fragility of the system despite its current functional importance. By integrating health assessment, conflict indices, spatial analysis, and biomass estimation within a unified analytical framework, this study advances urban forestry practice by offering a replicable approach for diagnosing vulnerabilities and prioritizing management actions. The findings emphasize the importance of coordinated municipal planning that explicitly incorporates species diversity and spatial equity as core elements for developing more resilient and sustainable street-tree systems in medium-sized cities.

本研究对巴西某中型城市的行道树进行了定性和定量的综合评估，旨在评估树种组成、树木健康、基础设施冲突、空间异质性和生态系统服务提供。行道树群落表现出有限数量物种的强烈优势和外来类群的高流行率，表明结构均匀度低和长期存在的城市规划实践局限性，增加了对病虫害和管理失败的脆弱性。大多数树木被归类为健康或状况良好；然而，真菌感染和昆虫活动等生物压力因素显著降低了个体达到更高健康类别的可能性。树木与城市基础设施之间的冲突普遍存在，特别是与树根暴露和对架空公用设施的干扰有关的冲突，并且在社区之间表现出明显的空间差异，表明整个城市景观的规划策略和维护工作不平等。虽然人类对树木的直接损害一般较低，但其在物种间的不均匀分布突出了物种特有的易感性和管理挑战。生态系统服务，包括碳储存和小气候调节，不成比例地集中在一小部分物种中，这加剧了系统的结构脆弱性，尽管它目前具有重要的功能。通过在统一的分析框架内整合健康评估、冲突指数、空间分析和生物量估算，本研究提供了一种可复制的方法来诊断脆弱性并确定管理行动的优先顺序，从而促进了城市林业实践。研究结果强调了协调城市规划的重要性，明确将物种多样性和空间公平作为发展更具弹性和可持续性的中等城市街道树木系统的核心要素。

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引用次数: 0

How does biodiversity monitoring impact those who conduct it? Reported outcomes and perspectives of a field team in Lore Lindu National Park, Indonesia 生物多样性监测如何影响进行监测的人？印度尼西亚洛尔林杜国家公园实地考察小组的成果和观点报告

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-20 DOI: 10.1016/j.tfp.2026.101166

Mary Mulligan , Heiko Faust , Lutz Fehrmann , Fabian Brambach , Cesar A. Mappatoba , Kamaluddin Kamaluddin , Adam Malik , Tatang Tiryana , I Nengah Surati Jaya , Christoph Kleinn

Biodiversity monitoring enhances our understanding of the natural environment, provides insights into ecological trends, and evaluates the effectiveness of conservation and management efforts. However, less is known about how such monitoring affects those who conduct it, both in terms of personal benefits and potential shifts in their environmental perspectives. To explore these impacts, we (the project consortium) interviewed the 44 individuals who participated in a biodiversity monitoring campaign from February 2023 to February 2024 in Lore Lindu National Park, Indonesia. All respondents reported enhanced knowledge and professional networks, while the vast majority also highlighted increased income generation (97 %), capacity development (92 %), and personal fulfillment (97 %). Most respondents reported increased awareness, motivation, and knowledge related to the national park and its preservation, with 43 % of responses classified as a genuine perspective shift. Participants from the local communities in particular described a heightened sense of pride and responsibility towards protecting the park’s natural resources. More broadly, 80 % of respondents expressed a positive perspective shift towards nature and the environment as a whole. These findings align with participant outcomes observed in both citizen science and other collaborative monitoring contexts, suggesting that, beyond scientific and management benefits, biodiversity monitoring campaigns also provide meaningful social, economic, and educational benefits. These additional outcomes support both conservation and local development and should be considered when planning future monitoring campaigns.

生物多样性监测增强了我们对自然环境的认识，提供了对生态趋势的洞察，并评估了保护和管理工作的有效性。然而，就个人利益和环境观点的潜在转变而言，人们对这种监测如何影响进行监测的人知之甚少。为了探讨这些影响，我们（项目联盟）采访了44名参加了2023年2月至2024年2月在印度尼西亚洛林杜国家公园进行的生物多样性监测活动的个人。所有受访者都报告了知识和专业网络的增强，而绝大多数受访者还强调了创收（97%）、能力发展（92%）和个人成就感（97%）的增加。大多数受访者表示，他们对国家公园及其保护的认识、动机和知识都有所提高，43%的受访者认为这是一种真正的观点转变。来自当地社区的参与者特别描述了保护公园自然资源的自豪感和责任感。更广泛地说，80%的受访者表达了对自然和整体环境的积极看法转变。这些发现与在公民科学和其他协作监测背景下观察到的参与者结果一致，表明除了科学和管理效益之外，生物多样性监测运动还提供了有意义的社会、经济和教育效益。这些额外的结果支持保护和当地发展，在规划未来的监测活动时应予以考虑。

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引用次数: 0

Tree shade mitigates stress and enhances chickpea productivity: Insights from an Emblica officinalis-based agroforestry system in semi-arid shallow Basaltic Deccan Plateau, India 树荫减轻了压力，提高了鹰嘴豆的生产力：来自印度半干旱浅玄武岩德干高原Emblica officinalis的农林业系统的见解

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-18 DOI: 10.1016/j.tfp.2026.101164

AR Chichaghare , SB Chavan , GB Rawale , AR Uthappa , VD Kakade , AS Morade , SS Changan , Nobin Paul , VB Gawade , PS Khapte , PS Basavaraj , RR Babar , Sandeep B Adavi , DD Nangare , CB Harisha , Hanamant M Halli , KS Reddy

Agroforestry influences microclimate and resource availability, particularly light, soil moisture, and nutrients, thus favouring the often growth of associated crops. This study aims to assess whether tree shade act as stress or the leveraging factor in degraded soil environment of semi-arid Shallow Basaltic Deccan plateau, India. We hypotheses that tree shades influence physiological and biochemical traits of understory crops and modify yield. This field study evaluated the shade-induced effect of a 9-year-old trees (Emblica officinalis) on microclimate modifications and associated stress regulation on intercropped chickpea varieties (Digvijay and Vijay) in shallow basaltic poor soils. Weekly light intensity readings were collected for 12 weeks to categorise the natural shade gradients as 20 %, 30 %, 40 %, and 50 % shade levels and compared with the open field (0 %). Results revealed that shade delayed the flowering by 12–16 days, improved relative water content by 6–9 %, and reduced canopy temperatures by 3–5°C; consequently, it delayed the maturity by 4–9 days and enhanced biomass accumulation by 36–72 % and other physiological traits in chickpea varieties. Maximum yield (1.55 Mg ha⁻¹) was recorded under 50 % shade, with Digvijay outperforming Vijay (1.46 vs. 1.03 Mg ha⁻¹). As a result, stress indicators such as proline and ascorbic acid were produced at lower levels under shade conditions. The crop status index, effectively captured plant health variation across shade levels, showing a strong correlation with yield. Therefore, findings highlight that tree shade acts as a leveraging factor, effectively buffering against moisture stress and high light intensity, owing to moderation in ambient temperature on degraded soil environments. This nature-based solution could be a sustainable potential climate adaptation option to enhance the productivity and imparting resilience under degraded conditions particularly in face of climate change extremities.

农林业影响小气候和资源供应，特别是光照、土壤湿度和养分，因此往往有利于相关作物的生长。本研究旨在探讨在印度德干半干旱浅玄武质高原退化土壤环境中，遮荫究竟是胁迫因子还是杠杆因子。我们假设树荫影响林下作物的生理生化特性并调节产量。摘要本研究评估了浅玄武质贫瘠土壤中9年树龄鹰嘴豆（Emblica officinalis）遮荫诱导对间作鹰嘴豆（Digvijay和Vijay）小气候变化及相关胁迫调节的影响。收集12周的每周光强读数，将自然阴影梯度分为20%、30%、40%和50%，并与开阔地（0%）进行比较。结果表明：遮荫使花期延迟12 ~ 16 d，使相对含水量提高6 ~ 9%，使冠层温度降低3 ~ 5℃；使鹰嘴豆品种的成熟期推迟4 ~ 9 d，生物量积累提高36 ~ 72%等生理性状。在50%的遮荫下，产量最高（1.55 Mg ha⁻¹），Digvijay的产量比Vijay高（1.46 vs 1.03 Mg ha⁻¹）。因此，在遮荫条件下，脯氨酸和抗坏血酸等胁迫指标的产量较低。作物状况指数有效地捕捉了不同遮荫水平下植物健康状况的变化，显示出与产量的强相关性。因此，研究结果强调，在退化的土壤环境中，由于环境温度的调节，树荫作为一个杠杆因素，有效地缓冲了水分胁迫和高光强。这种基于自然的解决方案可能是一种可持续的潜在气候适应选择，可在退化条件下提高生产力并增强复原力，特别是在面临极端气候变化的情况下。

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引用次数: 0

Explaining ecological drivers and management implications of forest biomass: An explainable deep learning fusion of remote sensing and climate data 解释森林生物量的生态驱动因素和管理意义：遥感和气候数据的可解释深度学习融合

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-07 DOI: 10.1016/j.tfp.2026.101154

Sina Irannejad, Hossein Bagheri

Accurate estimation of aboveground biomass (AGB) is essential for sustainable forest management and climate change monitoring; however, conventional remote sensing approaches often rely on a single data type and provide limited interpretability. This study introduces a novel framework that systematically integrates multi-sensor remote sensing (Sentinel-1 SAR, Sentinel-2, and Landsat-8 optical data), process-based climate variables (Climate-FVS), and LiDAR-derived topographic indices into deep learning models. By coupling these fusion scenarios with explainable AI (XAI) analyses, the framework not only improves predictive accuracy but also reveals the relative contribution of ecological drivers such as precipitation, temperature, and short-wave infrared bands. Seven U-Net-based architectures, including U-Net3+, TransU-Net, and Attention U-Net, were trained and evaluated using RMSE, MAE, and R² metrics. Results showed that U-Net3+ achieved the highest performance under the complete fusion scenario, with an RMSE of 28.10 Mg/ha, an MAE of 17.49 Mg/ha, and an R² of 0.89. XAI analyses highlighted that SWIR1, SWIR2, and Red bands were the most influential predictors, while climatic variables significantly improved model generalization in topographically complex areas. The highest errors occurred at vegetation boundaries and steep terrain. These findings demonstrate that multi-source data fusion combined with interpretable deep learning provides a robust pathway for both accurate AGB estimation and a deeper understanding of its environmental drivers, directly supporting carbon accounting and sustainable forest management.

准确估算地上生物量（AGB）对可持续森林管理和气候变化监测至关重要；然而，传统遥感方法往往依赖单一数据类型，可解释性有限。该研究引入了一个新的框架，系统地将多传感器遥感（Sentinel-1 SAR、Sentinel-2和Landsat-8光学数据）、基于过程的气候变量（climate - fvs）和激光雷达衍生的地形指数集成到深度学习模型中。通过将这些融合情景与可解释人工智能（XAI）分析相结合，该框架不仅提高了预测精度，而且揭示了降水、温度和短波红外波段等生态驱动因素的相对贡献。七个基于U-Net的架构，包括U-Net3+、TransU-Net和Attention U-Net，使用RMSE、MAE和R²指标进行训练和评估。结果表明，U-Net3+在完全融合条件下表现最佳，RMSE为28.10 Mg/ha， MAE为17.49 Mg/ha， R²为0.89。XAI分析强调，SWIR1、SWIR2和Red波段是影响最大的预测因子，而气候变量显著提高了地形复杂地区模式的通用性。在植被边界和陡峭地形上误差最大。这些发现表明，多源数据融合与可解释的深度学习相结合，为准确估计AGB和更深入地了解其环境驱动因素提供了强有力的途径，直接支持碳核算和可持续森林管理。

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引用次数: 0

Integrated climate governance framework for forest fire management: A hypothetical application in Indonesia 森林火灾管理的综合气候治理框架：在印度尼西亚的假设应用

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-04 DOI: 10.1016/j.tfp.2026.101145

I Wayan Koko Suryawan , Sapta Suhardono , Evi Siti Sofiyah , Ari Rahman , Nova Ulhasanah , Mega Mutiara Sari , Chun-Hung Lee

The escalating risks of forest fires, intensified by climate change particularly those linked to anthropogenic factors such as tourist behavior in Bromo, Indonesia underscore the necessity for a comprehensive understanding of stakeholder support for preventive and adaptive management strategies. This study employs an Integrated Climate Governance (ICG) framework to evaluate tourist values and their willingness to pay (WTP) for forest fire management interventions. A Choice Experiment was utilized to present respondents with structured trade-offs concerning key management attributes, and a Latent Class Model (LCM) was implemented to identify distinct preference segments. Three tourist classes emerged from the analysis. Class 1 (55.5%) exhibited a strong WTP for advanced green area management while demonstrating limited support for moderate ecological enhancements. Class 2 (31%) articulated clear preferences for basic early warning systems and effective evacuation facilities, emphasizing practical and accessible safety measures. Conversely, Class 3 (13.5%) displayed WTP estimates that could not be statistically identified, indicating the need for further investigation into the preferences and decision-making tendencies of this cohort. Across all classes, a higher monthly income consistently predicted an increased WTP, reflecting a greater willingness among affluent tourists to contribute financially to fire management initiatives. Overall, the findings indicate that the ICG framework effectively captures heterogeneous tourist preferences and their associated economic implications. By highlighting differentiated priorities among tourist groups, the study reinforces the importance of tailoring fire management strategies to specific user segments and leveraging contributions from higher-income visitors to support critical safety investments. These insights provide a foundation for developing more targeted, equitable, and financially sustainable forest fire management policies in climate-vulnerable tourism destinations.

气候变化，特别是与印度尼西亚布罗莫的游客行为等人为因素有关的气候变化，加剧了森林火灾风险的不断升级，这突显了全面了解利益攸关方对预防性和适应性管理战略的支持的必要性。本研究采用综合气候治理（ICG）框架来评估旅游价值及其对森林火灾管理干预措施的支付意愿。通过选择实验向被调查者展示了关于关键管理属性的结构化权衡，并实施了潜在类别模型（LCM）来识别不同的偏好细分。从分析中出现了三类游客。第1类（55.5%）对高级绿地管理表现出较强的WTP，而对适度生态增强的支持有限。第2类（31%）明确表达了对基本预警系统和有效疏散设施的偏好，强调了实用和可获得的安全措施。相反，第3类（13.5%）显示的WTP估计值无法统计识别，表明需要进一步调查该队列的偏好和决策倾向。在所有阶层中，较高的月收入始终预示着WTP的增加，这反映出富裕的游客更愿意为火灾管理举措做出经济贡献。总体而言，研究结果表明，ICG框架有效地捕捉了异质性游客偏好及其相关的经济影响。通过突出旅游群体的不同优先事项，该研究强调了针对特定用户群体定制消防管理策略的重要性，并利用高收入游客的贡献来支持关键的安全投资。这些见解为在易受气候影响的旅游目的地制定更有针对性、更公平、在财政上更可持续的森林火灾管理政策奠定了基础。

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引用次数: 0

“Paying not to work?” examining the validity of forest sector narratives on COVID-19 pandemic relief and labor impacts “付钱不工作？”，考察森林部门关于COVID-19大流行救济和劳动力影响的叙述的有效性

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-01 DOI: 10.1016/j.tfp.2026.101144

Manuja Jayasundara , Puneet Dwivedi , Joseph L. Conrad IV , Jesse B. Abrams

The COVID-19 pandemic caused major disruptions in labor markets across the United States. This study examines forest-sector stakeholders’ narratives around pandemic assistance programs and their perceived labor impacts, drawing on 35 semi-structured interviews with mill representatives, loggers, landowners, and foresters in Georgia, a major forestry state located in the southern United States. We identified narratives around stimulus payments, expanded unemployment insurance, and the Paycheck Protection Program (PPP) and assessed validity of those narratives using available evidence. We also explored how broader cultural beliefs and public rhetoric shaped these narratives using a narrative based theoretical lens.

A recurring narrative was that government assistance to individuals, particularly stimulus payments and expanded unemployment insurance, reduced labor availability and led to wage increases. We found mixed evidence for this claim, along with a more complex picture indicating that pandemic assistance also stimulated business activity and consumer demand, which in turn contributed to tighter labor markets and rising wages. Another common theme focused on the Paycheck Protection Program (PPP). While some participants viewed PPP as essential for business survival, others criticized it as fiscally irresponsible and poorly targeted, especially within a sector that largely remained operational during the pandemic. Evidence suggests both interpretations have merit, as PPP supported employment but incurred high costs and lacked precise targeting.

These narratives were shaped by broader cultural factors, including trust in government, views on public spending, as well as public rhetoric during the pandemic. As policy perceptions are shaped by cultural narratives as much as by empirical evidence, future policies should account for influence of such narratives.

COVID-19大流行对美国各地的劳动力市场造成了重大破坏。本研究通过对位于美国南部主要林业州佐治亚州的工厂代表、伐木者、土地所有者和林农的35次半结构化访谈，考察了林业部门利益相关者对流行病援助计划及其感知到的劳动力影响的叙述。我们确定了有关刺激支出、扩大失业保险和工资保护计划（PPP）的说法，并利用现有证据评估了这些说法的有效性。我们还探讨了更广泛的文化信仰和公共修辞如何使用基于叙事的理论镜头塑造这些叙事。一个反复出现的说法是，政府对个人的援助，特别是刺激支出和扩大的失业保险，减少了劳动力供应，导致工资上涨。我们发现了支持这一说法的混合证据，同时还有一种更复杂的情况表明，大流行援助也刺激了商业活动和消费者需求，这反过来又导致了劳动力市场趋紧和工资上涨。另一个共同的主题是工资保障计划。一些与会者认为公私伙伴关系对企业生存至关重要，而另一些与会者则批评公私伙伴关系在财政上不负责任，目标不明确，特别是在大流行期间基本保持运营的部门。有证据表明，这两种解释都有其可取之处，因为购买力平价支持了就业，但成本高且缺乏精确的目标。这些叙述受到更广泛的文化因素的影响，包括对政府的信任、对公共支出的看法以及大流行期间的公开言论。由于政策观念不仅受到经验证据的影响，也受到文化叙事的影响，因此未来的政策应考虑到这种叙事的影响。

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引用次数: 0

Modeling soil organic carbon in the Brazilian amazon with geostatistical and machine learning techniques 用地质统计学和机器学习技术模拟巴西亚马逊地区的土壤有机碳

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-01 DOI: 10.1016/j.tfp.2026.101150

Gizachew Ayalew Tiruneh , Ciro Abbud Righi , Jefferson Lordello Polizel , Vinicius Gonçalves , Carlos Rodrigues Pereira

Reliable estimation of soil carbon storage is essential to quantify human effects on the terrestrial carbon cycle. In this work, we analyzed soil organic carbon (SOC) content and stocks in the Brazilian Amazon at two depths (0–30 and 30–60 cm) using 486 georeferenced samples that were evaluated for texture, pH, SOC, and bulk density. In this study, inverse distance weighting (IDW) and machine learning algorithms (Random Forest, Support Vector Machine, Multiple Linear Regression, and Artificial Neural Network) were applied and validated through 10-fold cross-validation. Random Forest had the highest accuracy for SOC content (R² = 0.96), and IDW was the best method for SOC stock (R² = 0.88). Predicted SOC content and stock also followed the trend forest > pasture > cropland, and varied from 2.71–4.52 % (103.89–261.95 Mg C ha−¹) in forest soils to 2.03–2.14% (80.05–86.06 Mg C ha⁻¹) on croplands. Clay content, temperature, and land use were the major factors influencing SOC variation. It also indicates the possibility of combining IDW and machine learning approaches to bridge data gaps to guide climate-resilient land management and improvement of SOC, not only in the Amazon but across other tropical and subtropical areas where soil data is sparse. By delivering scalable and transferable modeling systems, this work enables a wider scope for impact in global carbon accounting, sustainable agriculture, and land-use planning for climate mitigation.

土壤碳储量的可靠估算对于量化人类对陆地碳循环的影响至关重要。在这项工作中，我们分析了巴西亚马逊地区两个深度（0-30 cm和30-60 cm）的土壤有机碳（SOC）含量和储量，使用486个地理参考样品进行了质地、pH、SOC和容重评估。在本研究中，应用了逆距离加权（IDW）和机器学习算法（随机森林、支持向量机、多元线性回归和人工神经网络），并通过10倍交叉验证进行了验证。随机森林法测定土壤有机碳含量的准确度最高（R²= 0.96），IDW法测定土壤有机碳储量的准确度最高（R²= 0.88）。预测土壤有机碳含量和储量也与森林、牧场、农田土壤有机碳含量变化趋势一致，森林土壤有机碳含量为2.71 ~ 4.52% (103.89 ~ 261.95 Mg C ha−1)，农田土壤有机碳含量为2.03 ~ 2.14% （80.05 ~ 86.06 Mg C ha−1）。粘土含量、温度和土地利用是影响土壤有机碳变化的主要因素。它还表明，将IDW和机器学习方法相结合，不仅可以在亚马逊地区，还可以在土壤数据稀少的其他热带和亚热带地区，弥合数据差距，指导气候适应型土地管理和改善土壤有机碳。通过提供可扩展和可转移的建模系统，这项工作能够在全球碳核算、可持续农业和缓解气候变化的土地利用规划方面产生更广泛的影响。

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引用次数: 0

Improving LAI retrieval in complex mountains with implicit mutual terrain irradiance 利用隐式相互地形辐照度改进复杂山地LAI反演

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2026-01-01 DOI: 10.1016/j.tfp.2026.101151

Chenghao Liu , Guyue Hu , Shaoda Li , Ronghao Yang , Junxiang Tan , Xiao Wang , Siqi Li , Jinhu Bian , Guangbin Lei

Leaf area index (LAI), a key indicator of vegetation canopy structure, is vital to regional ecological assessment and environmental monitoring. However, rugged terrain can induce the radiation distortion recorded by senses, thus resulting in substantial uncertainties in LAI retrievals. Existing canopy reflectance models often ignore the mutual terrain irradiance within soil-canopy layers, thereby limiting the completeness of the physical mechanism. In this study, an LAI retrieval method with physical completeness was proposed tailored for mountainous regions. Radiation interactions within diverse forest scenes were simulated using a discrete anisotropic radiative transfer model to account for the mutual terrain irradiance. Machine learning algorithms were integrated to enhance computational efficiency. The proposed method was validated through typical retrieval algorithms, analyses of topography and canopy effects, and comparisons of LAI retrievals with field observations. The results suggested that the proposed LAI retrieval method, which use the random forest algorithm, performed optimally under various terrain conditions (R² = 0.99, RMSE= 0.15, MAE = 0.13). Moreover, the proposed method significantly outperformed models that neglect mutual terrain irradiance (by 0.29, 0.17, and 0.10 in terms of R², RMSE, and MAE, respectively). The method also exhibited strong robustness across varying terrains and canopy structural conditions, accurately capturing the terrain-induced variations in LAI distribution (R² = 0.88, RMSE = 0.33, MAE = 0.28) in a real mountainous region. Therefore, considering that the mutual terrain irradiance is crucial in surface radiative transfer modelling, the proposed LAI retrieval method can provide a reliable tool for biophysical parameter extraction over rugged terrains.

叶面积指数（LAI）是反映植被冠层结构的重要指标，在区域生态评价和环境监测中具有重要意义。然而，崎岖的地形会引起感官记录的辐射畸变，从而导致LAI反演存在很大的不确定性。现有的冠层反射率模型往往忽略了土壤-冠层内部的相互地形辐照度，从而限制了物理机制的完整性。本研究提出了一种适合山区的具有物理完备性的LAI检索方法。利用离散各向异性辐射传输模型模拟了不同森林场景的辐射相互作用，以考虑相互的地形辐照度。结合机器学习算法，提高计算效率。通过典型检索算法、地形和冠层效应分析以及LAI检索结果与野外观测结果的比较，验证了该方法的有效性。结果表明，采用随机森林算法的LAI检索方法在不同地形条件下的检索效果最优（R2 = 0.99， RMSE= 0.15, MAE = 0.13）。此外，该方法显著优于忽略相互地形辐照度的模型（R2、RMSE和MAE分别高出0.29、0.17和0.10）。该方法在不同地形和冠层结构条件下均表现出较强的鲁棒性，能够准确捕获山地地形引起的LAI分布变化（R2 = 0.88, RMSE = 0.33, MAE = 0.28）。因此，考虑到地形相互辐照度在地表辐射传输建模中至关重要，本文提出的LAI检索方法可以为崎岖地形的生物物理参数提取提供可靠的工具。

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引用次数: 0