Trees, Forests and People最新文献_第8页

Functional plant strategies mediate post-fire ash–precipitation effects on soil–vegetation feedbacks in a dry-valley forest ecosystem: implications for restoration 功能性植物策略调节火灾后灰降水对干谷森林生态系统土壤-植被反馈的影响：对恢复的影响

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-12-04 DOI: 10.1016/j.tfp.2025.101114

Honghu Wang , Huanhuan Qi , Panpan Wang , Jun Luo , Fachao Qin , Bin Zhang

Wildfire fundamentally alters forest soil properties and vegetation dynamics through changes in ash deposition and post-fire precipitation, yet the coupled mechanisms governing soil–plant feedbacks remain unclear. We conducted a full-factorial pot experiment in the dry valleys of southwestern China, crossing four ash thicknesses with four precipitation levels and incorporating two contrasting plant functional types: the pioneer grass Digitaria sanguinalis (L.) Scop. and the drought-tolerant crop Fagopyrum tataricum (L.) Gaertn. We monitored soil respiration, near-surface soil moisture and temperature, and plant height throughout early growth. Structural equation modeling and response surface analysis revealed distinct regulatory mechanisms. D. sanguinalis exhibited a nutrient-driven, water-tolerant strategy in which ash and temperature dominated respiratory responses, supporting rapid growth under moderate ash layers. In contrast, F. tataricum followed an ash-facilitated, moisture-threshold strategy, where high ash combined with high precipitation suppressed respiration but maintained stable height. Across both species, a consistent negative association between respiration and plant height reflected a fundamental carbon allocation trade-off between metabolic expenditure and structural growth. Based on these findings, we propose a staged restoration model that leverages the contrasting functional strategies of pioneer and drought-tolerant species to accelerate ground cover formation and stabilize ecosystem functioning in fire-affected dry-valley forests. These results provide mechanistic insights and practical guidance for post-fire restoration and carbon management in fire-prone landscapes.

野火通过灰沉降和火后降水的变化从根本上改变了森林土壤性质和植被动态，但控制土壤-植物反馈的耦合机制尚不清楚。我们在中国西南干旱山谷进行了全因子盆栽试验，跨越4种灰分厚度和4种降水水平，并纳入两种不同的植物功能类型：先驱草马地黄（Digitaria sanguinalis， L.）；吟游诗人。以及耐旱作物苦荞（Fagopyrum tararicum）。Gaertn。我们监测了整个生长早期的土壤呼吸、近地表土壤湿度和温度以及植物高度。结构方程模型和响应面分析揭示了不同的调控机制。血杨表现出一种营养驱动的耐水策略，在这种策略中，灰分和温度主导呼吸反应，支持中等灰分层下的快速生长。相比之下，鞑靼白檀则采用了灰分促进的湿度阈值策略，高灰分与高降水相结合抑制了呼吸作用，但保持了稳定的高度。在这两个物种中，呼吸和植物高度之间一致的负相关反映了代谢消耗和结构生长之间基本的碳分配权衡。基于这些发现，我们提出了一个阶段恢复模型，该模型利用先锋物种和耐旱物种的对比功能策略来加速火灾影响的旱谷森林的地表覆盖形成和稳定生态系统功能。这些结果为火灾易发景观的火灾后恢复和碳管理提供了机制见解和实践指导。

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引用次数: 0

Ethnomycology of Termitomyces species in the Benishangul-Gumuz Region, Southwest Ethiopia 埃塞俄比亚西南部Benishangul-Gumuz地区白蚁菌种的民族真菌学研究

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-12-04 DOI: 10.1016/j.tfp.2025.101113

Miheret Semere , Tatek Dejene , Pablo Martín-Pinto

Wild mushrooms, particularly Termitomyces species, are important non-timber forest products in Ethiopia; however, their ethnomycological aspects are under-documented. We assessed the ethnomycological knowledge of the Berta, Amhara, and Oromo ethnic groups in Bambasi woreda, in the Benishangul-Gumuz Region in Southwest Ethiopia. Data were collected by conducting semi-structured household interviews, focus group discussions, and key informant interviews. Ten Termitomyces species were identified. All three ethnic groups collect Termitomyces mushrooms. The Berta have extensive ethnomycological knowledge, a well-developed ethnotaxa, and diverse utilization practices. Among the Amhara and Oromo, children are the main collectors, whereas the Berta collect mushrooms as a family (i.e., women and children). The Berta identified termite mounds, woodlands, and riparian areas as key habitats. Although Termitomyces mushrooms are a seasonal food, commercialization is limited and there is no ethnomedicinal usage by these ethnic groups. The Berta are more dependent on wild and commercial sources of Termitomyces than the Amhara or Oromo. The Berta consume both fresh and preserved (i.e., sun dried, smoked, or salted) mushrooms, and use powdered Termitomyces as a spice or condiment. Unlike other societies, the Berta consider Termitomyces to be a symbol of prosperity, linking the early emergence of Termitomyces to good fortune. Traditional knowledge and beliefs are passed on orally by elders at social gatherings and village meetings. Documenting traditional knowledge, enhancing the value of collected mushrooms, and providing research and training support could promote the sustainable use of Termitomyces while enhancing the economic and ecological significance of Termitomyces in the study area.

野生蘑菇，特别是白蚁菌种，是埃塞俄比亚重要的非木材林产品；然而，他们的人种学方面文献记载不足。我们评估了埃塞俄比亚西南部Benishangul-Gumuz地区Bambasi woreda的Berta、Amhara和Oromo族群的人种学知识。通过半结构化家庭访谈、焦点小组讨论和关键信息提供者访谈收集数据。鉴定出10种白蚁菌。这三个民族都收集白蚁菌。伯塔人具有丰富的民族学知识、发达的民族分类群和多样的利用方式。在阿姆哈拉和奥罗莫，儿童是主要的收集者，而贝尔塔收集蘑菇作为一个家庭（即妇女和儿童）。伯塔人确定白蚁丘、林地和河岸地区是白蚁的主要栖息地。虽然白蚁蘑菇是一种季节性食品，但商业化是有限的，这些民族没有民族医学用途。伯塔人比阿姆哈拉人或奥罗莫人更依赖野生和商业来源的白蚁菌。伯塔人食用新鲜的和腌制的（即晒干的、烟熏的或盐渍的）蘑菇，并使用粉末状的白蚁菌作为香料或调味品。与其他社会不同，伯塔人认为白蚁是繁荣的象征，将白蚁的早期出现与好运联系在一起。传统知识和信仰由长者在社交聚会和乡村会议上口头传递。通过记录传统知识、提高采集蘑菇的价值、提供研究和培训支持，可以促进白蚁菌的可持续利用，同时提高研究区白蚁菌的经济和生态意义。

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引用次数: 0

Integrating remote sensing and traditional ecological knowledge to assess land use change and vegetation dynamics in semi-arid region 结合遥感和传统生态知识评估半干旱区土地利用变化和植被动态

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-29 DOI: 10.1016/j.tfp.2025.101107

Akhtar Rehman , Khalid Ahmad , Naveed Rehman , Fu Benchen , Maliha Ghani , Shafee Ahmad , Muhammad Hamza , Asad Aziz , Muhammad Sibt e Ali

Land use and land cover (LULC) changes driven by urbanization and climate variability have significantly eroded traditional ecological knowledge (TEK) in Karak district, Pakistan. This study investigates the relationship between vegetation dynamics, assessed via Normalize Difference Vegetation Index (NDVI) from Landsat images (1986–2017), and TEK loss across three tehsils: Karak, Takhte Nasrati, and Banda Daud Shah. Supervised classification in ArcGIS 10.5 and QGIS 2.18 revealed a marked decline in vegetation cover—from 8 % to 4 %, 6 % to 3 %, and 7 % to 4 %, respectively—while built-up and bare land are increasing. Field surveys and focus group discussions with local communities documented diminishing knowledge of wild plant uses, correlating with habitat loss. Spatial and statistical analyses (ArcGIS, SPSS) confirmed a significant negative correlation between vegetation degradation and TEK preservation. As the first integrative study in this semi-arid region, it underscores the coupled impacts of environmental and socio-cultural change. Findings highlight the urgency of embedding TEK into biodiversity conservation and sustainable land management policies. This approach provides a replicable framework for regions facing similar ecological and cultural transitions, advocating for science-TEK synergy to enhance ecosystem resilience and adaptive capacity in vulnerable landscapes.

城市化和气候变率驱动的土地利用和土地覆盖（LULC）变化严重侵蚀了巴基斯坦Karak地区的传统生态知识（TEK）。本研究通过1986-2017年Landsat图像的归一化植被指数（NDVI）评估了植被动态与Karak、Takhte Nasrati和Banda Daud Shah三个地区的TEK损失之间的关系。ArcGIS 10.5和QGIS 2.18的监督分类显示，植被覆盖率明显下降，分别从8%下降到4%，从6%下降到3%，从7%下降到4%，而建成区和裸地在增加。实地调查和与当地社区的焦点小组讨论记录了野生植物利用知识的减少，与栖息地的丧失有关。空间和统计分析（ArcGIS， SPSS）证实植被退化与TEK保存呈显著负相关。作为这一半干旱地区的第一个综合研究，它强调了环境和社会文化变化的耦合影响。研究结果强调了将TEK纳入生物多样性保护和可持续土地管理政策的紧迫性。这种方法为面临类似生态和文化转型的地区提供了一个可复制的框架，倡导科学与技术的协同作用，以增强脆弱景观的生态系统恢复力和适应能力。

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引用次数: 0

Automated UAV-based tool for urban forest tree monitoring using machine learning and image processing 使用机器学习和图像处理的城市森林树木监测自动化无人机工具

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-28 DOI: 10.1016/j.tfp.2025.101104

Vighnesh Budharapu , Shubham Bhuvad , Tushar Garje , Varsha Turkar , Mugdha Agarwadkar , Yogesh Agarwadkar

Urban forest management requires accurate and scalable methods for monitoring tree structure and health. Traditional inventory approaches are labor-intensive and limited in spatial coverage, while existing remote sensing methods often lack the resolution and adaptability needed for diverse urban environments. This study presents an automated UAV-based framework that integrates machine learning, image processing, and topographical analysis for individual tree detection and characterization. The framework employs YOLOv8 object detection for initial tree identification, followed by slope-based region-growing segmentation that refines canopy boundaries using Digital Elevation Model (DEM) and Digital Terrain Model (DTM) data. A two-stage Otsu's thresholding approach addresses small tree exclusion in mixed height canopies. Tree structural attributes including height and canopy girth, are derived from DEM/DTM analysis, while vegetation health is assessed using the Modified Green-Red Vegetation Index (MGRVI). The methodology was validated on UAV datasets from Maharashtra and Telangana, achieving 95% detection accuracy in sparse canopy regions and 85% in dense areas. An interactive WebGIS interface enables spatial visualization of tree attributes and health metrics to support data-driven urban forestry decisions. The framework demonstrates adaptability across diverse tree species and canopy densities, offering a scalable solution for automated urban forest monitoring and management.

城市森林管理需要精确和可扩展的方法来监测树木的结构和健康。传统的清查方法是劳动密集型的，空间覆盖范围有限，而现有的遥感方法往往缺乏对不同城市环境所需的分辨率和适应性。本研究提出了一个基于无人机的自动化框架，该框架集成了机器学习、图像处理和地形分析，用于单个树的检测和表征。该框架采用YOLOv8目标检测进行初始树木识别，然后使用数字高程模型（DEM）和数字地形模型（DTM）数据进行基于坡度的区域生长分割，细化树冠边界。Otsu的两阶段阈值方法解决了混合高度树冠中的小树排除问题。树木结构属性包括高度和冠层周长，由DEM/DTM分析得出，而植被健康则使用改进的绿红植被指数（MGRVI）进行评估。该方法在马哈拉施特拉邦和特伦甘纳邦的无人机数据集上进行了验证，在稀疏的冠层区域实现了95%的检测精度，在密集的区域实现了85%的检测精度。交互式WebGIS界面支持树木属性和健康指标的空间可视化，以支持数据驱动的城市林业决策。该框架展示了对不同树种和冠层密度的适应性，为自动化城市森林监测和管理提供了可扩展的解决方案。

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引用次数: 0

Guiding sustainable land use planning in Ethiopia: A decision support framework using analytic hierarchy process 指导埃塞俄比亚可持续土地利用规划：使用层次分析法的决策支持框架

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-28 DOI: 10.1016/j.tfp.2025.101106

Shibire Bekele Eshetu , Katharina Löhr , Mahlet Degefu Awoke , Marcos Lana , Stefan Sieber

Land use planning in countries like Ethiopia faces persistent challenges, including outdated technical standards, fragmented institutional coordination, and limited community participation. These issues are particularly pronounced in land use and watershed development initiatives. In the implementation of Forest Landscape Restoration (FLR), emphasis is often placed on restoring ecological functions, mitigating land degradation, reducing soil erosion, and enhancing carbon sequestration than local community well-being. Therefore, adopting a holistic approach is essential when approaching land use decisions, carefully considering various factors that influence land use decisions. This study seeks to develop a multi-stakeholder land use decision support framework that integrates environmental, social, and economic dimensions to inform land use planning decision-making processes in Ethiopia. To achieve this objective, the Analytical Hierarchy Process (AHP) model, a Multi Criteria Decision Making (MCDM) method, is applied. We organized four workshops with different stakeholders, including farmers and experts from woreda, zonal, and federal levels. In the workshops, land use decision factors at the indicator and sub-indicator levels were developed, and a ranking of these decision factors was applied using the AHP matrix. Results show that a higher degree of consistency is achieved in the matrix with a Consistency Ratio (CR) of 0.01, as determined by federal-level experts. A tolerable CR of 0.01 is also achieved with farmers’ criteria ranking. Although respective stakeholders have varying priorities, in general, climatic, economic, and environmental factors are among the top three, showing high priority weights above 0.4. A sensitivity analysis of the priority weights is conducted, and sensitive factors are identified, which are then used to develop a decision support tree for land use factor prioritization. The decision tree highlights seven critical sub-factors that hold a priority weight above 0.4 and are sensitive at the threshold level of 0.01. Selecting well-defined and compelling indicators will help align stakeholder perspectives and foster consensus in decision-making.

埃塞俄比亚等国的土地利用规划面临着持续的挑战，包括过时的技术标准、支离破碎的机构协调和有限的社区参与。这些问题在土地利用和流域发展倡议中尤为突出。在实施森林景观恢复（FLR）时，重点往往放在恢复生态功能、减轻土地退化、减少土壤侵蚀和加强碳固存而不是当地社区福祉。因此，在作出土地使用决定时，必须采取整体方法，仔细考虑影响土地使用决定的各种因素。本研究旨在开发一个多利益相关者土地利用决策支持框架，该框架整合了环境、社会和经济层面，为埃塞俄比亚的土地利用规划决策过程提供信息。为了实现这一目标，应用了层次分析法（AHP）模型，一种多准则决策（MCDM）方法。我们组织了四次与不同利益相关者的研讨会，包括农民和来自州、地区和联邦各级的专家。在讲习班上，制定了指标和子指标水平上的土地利用决策因素，并使用层次分析法矩阵对这些决策因素进行了排序。结果表明，由联邦专家确定的一致性比（CR）为0.01，该矩阵具有较高的一致性。农民标准排序也达到了0.01的可容忍CR。尽管各利益相关者的优先级不同，但总体而言，气候、经济和环境因素排在前三位，优先级权重高于0.4。对优先级权重进行敏感性分析，识别出敏感因子，并利用敏感因子构建土地利用因子优先级决策支持树。决策树突出了7个关键子因素，这些子因素的优先级权重高于0.4，并且在0.01的阈值水平下敏感。选择定义明确和引人注目的指标将有助于协调利益相关者的观点并促进决策中的共识。

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引用次数: 0

N-fixing species outperform non-N-fixing species in promoting soil organic carbon stability via enhancing edaphic-litter nitrogen availability in Eucalyptus plantations 在桉树人工林中，固氮树种通过提高土壤凋落物氮素有效性来促进土壤有机碳稳定性的作用优于非固氮树种

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-28 DOI: 10.1016/j.tfp.2025.101108

Daihan Fu , Angang Ming , Haoyang Cao , Runxia Huang , Hao Fu , Weiwei Shu , Zhichao Wang , Wankuan Zhu , Apeng Du , Yuxing Xu

Aims

Mixed planting is a more favorable approach than monocultures for soil organic carbon (SOC) sequestration; however, due to the diversity in mixed-species assemblages, the underlying mechanisms remain unclear, hindering afforestation schemes that protect SOC stocks.

Methods

A 13-year mixed-species experiment was conducted in a subtropical region, focusing on a Eucalyptus urophylla × E. grandis pure plantation (PP), a Eucalyptus and nitrogen-fixer Erythrophleum fordii mixed plantation (EE), and Eucalyptus and non-nitrogen-fixer Castanopsis hystrix mixed plantation (EC), by measuring SOC in bulk soil and aggregates, followed by partitioning SOC into active carbon pools (labile carbon pool I [LPI-C] and labile carbon pool II [LPII-C]) and a recalcitrant carbon pool (RP-C). The present study considered various environmental factors, including plants, soil, microflora, and enzyme activities, to analyze the processes and factors underlying SOC sequestration within different mixed plantation modes.

Results

Mixed forests improved SOC sequestration by optimizing soil aggregate stability, increasing fertility, relieving phosphorus limitation, and stimulating microbial activity. SOC sequestration in EE soils was driven by both fine root biomass and litter quality, whereas SOC sequestration in EC soils relied on fine root elongation. Only nitrogen-fixing mixtures enhanced SOC stability, favoring long-term carbon storage. The high carbon (C)/nitrogen (N) ratio in the soil and the nitrogen-rich environment promoted an increase in Gram-negative bacteria, achieving stable SOC storage by forming large aggregates.

Conclusion

The present study highlights the advantages of mixed-species afforestation in SOC sequestration and reveals the unique value of nitrogen-fixing species in long-term carbon storage. The present findings offer theoretical and practical guidance for scientific afforestation and enhancing the carbon sink function of forest ecosystems.

混合种植比单一种植更有利于土壤有机碳的固存；然而，由于混合物种组合的多样性，其潜在机制尚不清楚，阻碍了保护有机碳资源的造林计划。方法在亚热带地区以尾巨桉纯人工林（PP）、桉树与固氮剂fordii红壤混交林（EE）和桉树与不固氮剂Castanopsis hystrix混交林（EC）为研究对象，进行了为期13年的混种试验，测定了土壤和团聚体的有机碳含量。然后将SOC划分为活性碳库（稳定碳库I [LPI-C]和稳定碳库II [LPI-C]）和顽固性碳库（RP-C）。本文综合考虑植物、土壤、微生物区系和酶活性等环境因素，分析了不同混交林模式下土壤有机碳固存的过程和影响因素。结果混交林通过优化土壤团聚体稳定性、提高肥力、缓解磷限制和刺激微生物活性等途径促进土壤有机碳的固存。EE土壤有机碳固存主要受细根生物量和凋落物质量驱动，而EC土壤有机碳固存主要受细根伸长驱动。只有固氮混合物能提高土壤有机碳的稳定性，有利于碳的长期储存。土壤中较高的碳氮比和富氮环境促进了革兰氏阴性菌的增加，通过形成大团聚体实现稳定的有机碳储量。结论本研究突出了混合树种造林在固碳方面的优势，揭示了固氮树种在长期碳储存方面的独特价值。研究结果为科学造林和增强森林生态系统碳汇功能提供了理论和实践指导。

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引用次数: 0

The influence of orchard and forest management on rainfall-induced landslides: A study of Hiraenoki Community in southwestern Japan 果园和森林管理对降雨诱发滑坡的影响——以日本西南部平野木社区为例

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-27 DOI: 10.1016/j.tfp.2025.101103

Ken-ichiro Shimizu , Kazuo Asahiro

Landslides triggered by heavy rainfall pose significant risks to mountainous communities worldwide, and their frequency is expected to increase due to climate change. Vegetation and land management are known to influence slope stability, but their effects in rural landscapes remain understudied. This study evaluates the influence of forest and orchard vegetation, along with topography, rainfall, and geology, on shallow landslide occurrence in the Hiraenoki Community, Asakura City, southwestern Japan, which experienced severe rainfall-induced disasters in July 2017. Landslide areas were identified using pre- and post-disaster digital elevation models, and vegetation and orchard data were compiled from forest registers, aerial photographs, and local interviews. Binary logistic regression analysis was conducted with landslide presence as the dependent variable and explanatory variables including vegetation type, orchard type, slope angle, slope aspect, elevation, rainfall, surface geology, and topographic position index (TPI). The final model revealed that mixed secondary forests and 50–59-year-old sugi cedar (Cryptomeria japonica) plantations exhibited higher landslide probabilities. Rainfall, slope angle, elevation, and TPI also significantly influenced landslide occurrence, with valleys and lower elevations being particularly vulnerable. The results suggest that overtopped arakashi (Quercus glauca) and sudajii (Castanopsis sieboldii) in mixed secondary forests and old sugi cedar are considered to have acted as triggers that increased the probability of landslides. Periodic thinning of canopy trees is proposed to enhance root anchorage and promote natural regeneration. These findings provide guidance for the conservation of satoyama landscapes with consideration of disaster risk.

暴雨引发的山体滑坡对世界各地的山区社区构成了重大威胁，而且由于气候变化，山体滑坡的发生频率预计会增加。众所周知，植被和土地管理会影响斜坡的稳定性，但它们对农村景观的影响仍未得到充分研究。本研究评估了森林和果园植被以及地形、降雨和地质对日本西南部浅仓市平野木社区浅层滑坡发生的影响，该社区在2017年7月经历了严重的降雨灾害。利用灾前和灾后数字高程模型确定滑坡区域，并根据森林登记、航空照片和当地采访汇编植被和果园数据。以滑坡存在为因变量，植被类型、果园类型、坡角、坡向、高程、降雨量、地表地质、地形位置指数（TPI）为解释变量，进行二元logistic回归分析。最终模型显示，混合次生林和50 - 59年树龄杉木人工林具有较高的滑坡概率。降雨、坡角、高程和TPI对滑坡的发生也有显著影响，其中山谷和低海拔地区尤为脆弱。结果表明，混合次生林和老杉木中被覆盖的栎（Quercus glauca）和杉（sudajii）被认为是增加滑坡发生概率的触发因素。建议对冠层树木进行周期性间伐，以增强根系的固结，促进自然更新。这些发现为考虑灾害风险的中山景观保护提供了指导。

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引用次数: 0

A comprehensive analysis of the use of modelling and remote sensing techniques for monitoring and managing rangelands 综合分析利用模型和遥感技术监测和管理牧场

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-26 DOI: 10.1016/j.tfp.2025.101102

Renaud Kévin Houinato , Rodrigue Idohou , Romain Lucas Glèlè Kakaï , Yves Brostaux

Sustainable rangeland management supports livestock production, food security, and key ecological services such as carbon sequestration and water regulation. However, rangelands face increasing pressure from climate change, land degradation, and agricultural expansion, requiring effective management strategies. This review follows the PRISMA guidelines and systematically examines 102 peer-reviewed publications selected from 511 initially identified studies across multiple databases, including Scopus, Google Scholar, ScienceDirect, AJOL and Web of Science. This review explores the latest tools enabling accurate monitoring and prediction of rangeland dynamics. The results show that key technologies include machine learning algorithms, unmanned aerial vehicles (UAVs), and multispectral sensors, all of which have revolutionized biomass estimation. Satellite remote sensing, particularly Sentinel-2 and Landsat 8/9, represents a transformative advancement by delivering consistent, scalable, and repeatable observations from regional to global scales. Methods such as Deep Neural Networks (DNN), Random Forest (RF), and Object-Based Image Analysis (OBIA) have outperformed conventional algorithms, achieving performance metrics such as

R^{2} > 0.85

. Generalized Linear Models (GLM) have also been widely applied, particularly for environmental impact assessment. The development of multispectral sensors, especially bands such as NIR and red-edge, has improved vegetation index calculations, while LiDAR technology has enhanced biomass prediction by incorporating terrain structure and canopy height data. Despite these advances, challenges remain, including issues related to data quality, sensor integration, and harmonizing datasets for predictive modelling. This review highlights both the strengths and limitations of current approaches and emphasizes the need for further integration of advanced technologies such as hyperspectral sensors.

可持续牧场管理支持畜牧生产、粮食安全以及碳固存和水调节等关键生态服务。然而，放牧地面临着气候变化、土地退化和农业扩张带来的越来越大的压力，需要有效的管理策略。本综述遵循PRISMA指南，系统地检查了102篇同行评议的出版物，这些出版物从多个数据库（包括Scopus、b谷歌Scholar、ScienceDirect、AJOL和Web of Science）的511项初步确定的研究中选出。本文综述了能够精确监测和预测牧场动态的最新工具。结果表明，关键技术包括机器学习算法、无人机（uav）和多光谱传感器，所有这些都彻底改变了生物量估算。卫星遥感，特别是Sentinel-2和Landsat 8/9，通过提供从区域到全球范围的一致、可扩展和可重复的观测，代表了一种变革性的进步。深度神经网络（DNN）、随机森林（RF）和基于对象的图像分析（OBIA）等方法优于传统算法，实现了R2>；0.85等性能指标。广义线性模型（GLM）也得到了广泛的应用，特别是在环境影响评价方面。多光谱传感器的发展，特别是近红外和红边等波段的发展，改善了植被指数的计算，而激光雷达技术通过结合地形结构和冠层高度数据，增强了生物量预测。尽管取得了这些进步，但挑战依然存在，包括与数据质量、传感器集成和协调预测建模数据集相关的问题。这篇综述强调了当前方法的优势和局限性，并强调了进一步整合高光谱传感器等先进技术的必要性。

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引用次数: 0

Local Ecological Knowledge and forest inventories reveal Afzelia africana Sm. decline in Benin, West Africa 当地生态知识和森林调查揭示了非洲南部非洲。西非贝宁的人口下降

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-25 DOI: 10.1016/j.tfp.2025.101097

Agbatan Marc Koutchoro , Laurent Gbenato Houessou , Amah Akodewou , Narcisse Yehouenou , Ogoudje Isidore Amahowe

Afzelia africana is a key forest species in West Africa, particularly in Benin, where it supports both ecological stability and local livelihoods. However, the species has been listed as Vulnerable on the IUCN Red List since 2019 due to increasing human pressure. This study combines Local Ecological Knowledge (LEK) with forest inventory data to provide a comprehensive assessment of its conservation status in Benin. LEK revealed that the species is declining mainly due to logging, with additional pressures from branch pruning, agricultural expansion, vegetation fires, and drought. Forest inventories confirmed these perceptions, showing populations dominated by small-diameter trees (5–30 cm) and very few large individuals (>60 cm). Adults were present in about 74.55 % of plots, while regenerating and subadult trees occurred in fewer plots (<38.79 % and 23.03 %, respectively), indicating an overall imbalance in life stages and limited successful recruitment. Communities reported several traditional conservation measures, including assisted natural regeneration, targeted reforestation, planting A. africana as a shade tree in house courtyards, and preserving it as a sacred species. Integrating LEK with quantitative data yields a nuanced understanding of threats to A. africana. It not only confirms its population decline but also reveals regeneration bottlenecks and highlights community-led strategies that support its persistence. It provides critical added value by uncovering the complex social-ecological drivers behind observed trends. This biocultural approach represents the first assessment of A. africana in Benin that explicitly links population structure with local conservation practices, offering a transferable framework for managing threatened tree species in tropical regions.

非洲梧桐是西非的一种重要森林物种，特别是在贝宁，它支持着当地的生态稳定和生计。然而，由于人类压力的增加，自2019年以来，该物种已被列为世界自然保护联盟红色名录中的易危物种。本研究将当地生态知识（LEK）与森林清查数据相结合，对贝宁的森林保护状况进行了全面评估。LEK显示，该物种的减少主要是由于伐木，以及来自树枝修剪、农业扩张、植被火灾和干旱的额外压力。森林调查证实了这些看法，显示种群以小直径树木（5-30厘米）为主，大个体（60厘米）很少。成虫生长在74.55%的样地，而再生树和亚成虫生长在较少的样地（分别为38.79%和23.03%），表明成虫生长阶段总体上不平衡，成功繁殖有限。社区报告了一些传统的保护措施，包括协助自然再生，有针对性的重新造林，在家庭庭院种植非洲古树作为遮荫树，并将其作为神圣的物种保存下来。将LEK与定量数据相结合，可以对非洲古猿所面临的威胁有细致的了解。它不仅证实了其人口的下降，而且揭示了再生瓶颈，并突出了支持其持续存在的社区主导战略。它通过揭示观察到的趋势背后复杂的社会生态驱动因素，提供了重要的附加价值。这种生物栽培方法是对贝宁非洲古树的首次评估，它明确地将种群结构与当地保护实践联系起来，为管理热带地区受威胁树种提供了一个可转移的框架。

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引用次数: 0

Quantifying tree species effects on soil organic carbon using machine learning algorithm: A case study in tropical agroforestry system of gayo coffee, Indonesia 用机器学习算法量化树种对土壤有机碳的影响——以印度尼西亚加约咖啡热带农林复合系统为例

IF 2.9 Q1 FORESTRY

Trees, Forests and People

Pub Date : 2025-11-23 DOI: 10.1016/j.tfp.2025.101098

Rahmat Pramulya , Rahmat Asy’Ari , Nihawa Hajar Pudjawati , Abd Malik A Madinu , Azelia Dwi Rahmawati , Fachruddin Fachruddin , Muhammad Reza Aulia , Dahlan Dahlan , Tarmizi Tarmizi , Fakhruddin Fakhruddin , Elida Novita , Adi Sutrisno , Devi Maulida Rahmah , Moh Zulfajrin , Heru Bagus Pulunggono , Fitria Yuliasmara , Rika Ratna Sari , Danny Dwi Saputra , Yudi Setiawan

Gayo coffee based on tropical agroforestry systems in Aceh plays an ecological role in mitigating climate change and a socio-economic role as a social livelihood in Indonesia. Ecologically, coffee agroforestry systems can increase soil carbon stocks through complex vegetation that produces litter as a source of nutrients. However, studies on measuring the contribution of vegetation to soil carbon dynamics in agroforestry lands using advanced machine learning-based statistical models in Indonesia are still very rare. Therefore, this study involved 18 complex vegetation variables to prove their contribution to soil organic carbon (SOC) dynamics using machine learning-based predictions with the random forest (RF) algorithm and hyperparameter tuning settings. The SOC available in the study area reached 173.46 ± 60.34 Mg ha^-1, with 9.20 % ± 3.87 % organic C, in agroforestry systems characterized by vegetation density of 1752.94 ± 459.20 trees ha^-1 (range: 850–2850 trees ha^-1), and consisted of 11 overstory species. Based on two RF model tests (rf and ranger model), SOC dynamics were influenced by vegetation by 95 % (R-squared) with an error rate of 0.05 (RMSE) and 0.04 (MAE). The contribution of vegetation focuses on the variable of agroforestry richness as the most important factor in predicting SOC, even though the species Leucaena leucocephala dominates around 88 % of the species composition. These results recommend that increasing agroforestry species diversity is key to increasing SOC in coffee agroforestry. This information is expected to strengthen the implementation of SFA policies and enhance the sustainability of climate change mitigation-based social livelihoods in tropical Indonesia.

在印度尼西亚，基于亚齐热带农林复合系统的加约咖啡在减缓气候变化方面发挥着生态作用，并作为一种社会生计发挥着社会经济作用。从生态学上讲，咖啡农林复合系统可以通过产生凋落物作为营养来源的复杂植被来增加土壤碳储量。然而，在印度尼西亚，利用先进的基于机器学习的统计模型测量农林业用地植被对土壤碳动态的贡献的研究仍然非常罕见。因此，本研究涉及18个复杂植被变量，使用基于机器学习的预测与随机森林（RF）算法和超参数调整设置来证明它们对土壤有机碳（SOC）动态的贡献。研究区植被密度为1752.94±459.20株ha-1（范围：850 ~ 2850株ha-1），由11种林分组成的农林业系统，土壤有机碳含量为173.46±60.34 Mg ha-1，有机碳含量为9.20%±3.87%。基于两个RF模型（RF和ranger模型），植被对土壤有机碳动态的影响为95% （r²），错误率分别为0.05 （RMSE）和0.04 （MAE）。植被的贡献主要集中在农林业丰富度变量上，作为预测有机碳的最重要因子，尽管Leucaena leucocephala在物种组成中占88%左右。这些结果表明，增加农林业物种多样性是提高咖啡农林业有机碳的关键。预计这些信息将加强国家林业局政策的执行，并提高印度尼西亚热带地区以减缓气候变化为基础的社会生计的可持续性。

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引用次数: 0