Table of Content

28 April 2026, Issue 2

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Policy Discussion

Research on the optimization paths for deepening reform of the collective forest tenure system based on the Smith model: A case study of Fuzhou City,Jiangxi Province

WANG Ye, YAN Maolin, XU Yajun, YAO Di, ZHANG Junping, NIU Xin, NIE Jinshan

2026,(2):  1-9.  doi:10.13466/j.cnki.lczyyj.2026.02.001

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The reform collective forest tenure system is an important institutional change related to the sustainable development of China's forestry sector. The implementation of related policy is a key part for advancing the reform. To enhance the effectiveness of policies for reform of the collective forest tenure system and contribute to modernization of forestry,this study focuses on Fuzhou City,Jiangxi Province,a national comprehensive pilot city for forestry reform and development. Based on the Smith's policy implementation process model,this study comprehensively employs policy text analysis,semi-structured interviews,and case studies to systematically analyze the practical difficulties in implementation policies for reform of the collective forest tenure system in Fuzhou City across four dimensions:idealized policy,the target group,implementing organization,and environmental factors. The results showed that,in the idealized policy dimension,some policies are disconnected from the grassroots implementation contexts;in the target group dimension,policy acceptance is low with shortcomings in endogenous motivation and capacity for participation;in the implementing organization dimension,there are challenges such as a human capital shortage and insufficient professional capacity;in the environmental factors dimension,external conditions are inadequate,constraining the policy implementation and effectiveness. Based on these,this study proposes specific paths in terms of enhancing policy adaptability and feasibility,empowering target groups,innovating governance mechanisms,and improving the policy implementation environment.

Extension evaluation,spatiotemporal evolution,and obstacle factors of new quality productive forces in forestry

ZHOU Liqin, MAI Qiangsheng, LYU Xiufen, CHEN Jiancheng

2026,(2):  10-21.  doi:10.13466/j.cnki.lczyyj.2026.02.002

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This study analyzes the development level,spatiotemporal evolution and main constraining factors of China's new quality productive forces in forestry to provide a basis for optimizing the cultivation path for new quality productive forces in forestry.Based on the panel data from 31 provincial-level administrative regions in China from 2013 to 2022,this study constructs an evaluation index system from three dimensions:new-quality laborers,new-quality means of labor,and new-quality objects of labor.An improved variable-weight matter-element extension model is adopted to measure the development level of new quality productive forces in forestry,and the Dagum Gini coefficient and the obstacle degree model are used to analyze regional differences and the main obstacle factors.1)From 2013 to 2022,China's new quality productive forces in forestry were generally at a medium level and had not yet reached a good level.Spatially,it presents a pattern in which the eastern region led,the central region followed,and the western region lagged behind.2)The national Dagum Gini coefficient ranged from 0.005 to 0.008,indicating that the overall regional differences were relatively small,although the uneven development within regions still persisted.3)The main obstacle factors have gradually shifted from insufficient fixed asset investment,inadequate forest health management,and insufficient cultivation of new-quality industries to low labor efficiency,insufficient supply of science and technological service,inadequate infrastructure support,and insufficient and upgrading of traditional industries toward new-quality development.China's new quality productive forces in forestry are still at the stage of cultivation and improvement.Efforts should therefore be made to improve the training system for new-quality laborers in forestry and strengthen forestry science and technology services;accelerate the upgrading of new-quality means of labor in forestry and enhance investment and equipment support;and improve the utilization mechanism for new-quality objects of labor in forestry and expand channels for realizing the value of forestry resources.

Scientific Research

Construction ecological security pattern of Saihanba Mechanical Forest Farm based on an improved ant colony algorithm

DONG Haowen, MAO Yankang, ZHANG Zhenwei, YANG Huijuan, CHENG Tao, XU Haiyun

2026,(2):  22-32.  doi:10.13466/j.cnki.lczyyj.2026.02.003

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To address the technical limitations of high corridor redundancy,poor path adaptability,and difficulty in adapting to fragmented and heterogeneous in landscapes in conventional ecological security pattern construction,this study took Saihanba Mechanical Forest Farm,a typical vulnerable forest-grassland ecotone,as the study area and established a three-stage technical framework.Based on Morphological Spatial Pattern Analysis(MSPA)and circuit theory,an improved ant colony algorithm integrating a dynamic pheromone updating mechanism and adaptive parameter adjustment strategy was applied for the intelligent identification and optimization of ecological corridors,thereby constructing the ecological security pattern.The results showed that:1)The northern and eastern parts of Saihanba Mechanical Forest Farm exhibited high habitat quality,where core areas accounting for 81.79% of the total study area and serving as key components for maintaining regional ecological connectivity.2)The total length of ecological corridors optimized by the ant colony algorithm reaches 223.78 km,reducing redundant paths by 58% compared with those generated by circuit theory.Based on the constructed ecological security pattern,an optimized management strategy of "three cores and two corridors" was proposed.The proposed strategy provides scientific support for ecological conservation planning and sustainable development decisionmaking of Saihanba Mechanical Forest Farm,offers technical support for ecosystem management in arid and semiarid regions,and provides references for conservation and restoration of similar ecologically vulnerable regions worldwide.

Aboveground carbon density and driving factors of typical forest types in the south subtropical zone

PENG Yu, LEI Xiangdong, GUO Hong, SU Jianmiao

2026,(2):  33-46.  doi:10.13466/j.cnki.lczyyj.2026.02.004

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Identifying the factors influencing of aboveground carbon density (ACD) in typical forests in south subtropical zone can provide theoretical support for optimizing regional forest carbon-sink management.Five typical forest types in Chongzuo,Guangxi Zhuang Autonomous Region,China,including Pinus massoniana,Cunninghamia lanceolata,Eucalyptus grandis×urophylla,Mytilaria laosensis pure stands,and conifer-broadleaf mixed forest,were investigated.Based on forest management inventory data,ACD was estimated using biomass-volume conversion equations,and the its driving mechanisms were systematically analyzed using structural equation modeling (SEM).The results showed that:1) forest type,age class,and stand density significantly affected ACD,while site quality class had no significant main effect.However,forest type,stand density,and site quality class all exhibited significant interactions with age class.2)ACD of the five forest types ranked from highest to lowest as follows:Mytilaria laosensis pure stand (68.10 t/hm²),Pinus massoniana pure stand (33.20 t/hm²),conifer-broadleaf mixed forest (32.40 t/hm²),Cunninghamia lanceolata pure stand (32.00 t/hm²),Eucalyptus grandis×urophylla pure stand (31.30 t/hm²).3) ACD increased consistently with stand age.Mean ACD values for young,middle-aged,near-mature,mature,and overmature stands were 13.7,31.6,35.8,42.2,and 51.8 t/hm²,respectively.4) SEM revealed that stand density,dominant height,and mean diameter at breast height were the predominant positive drivers of ACD across all forest types,all with positive effects.The effects of site factors on ACD varied among forest types.Compared with the other forest types,the Mytilaria laosensis pure stand and the conifer-broadleaf mixed forest were more sensitive to climatic and soil factors.whereas the pure coniferous stands were significantly affected by topographic factors.Optimizing stand ageclass structure and tree-species composition,maintaining a certain proportion of mature and overmature stands,and increasing the proportions of broadleaved and conifer-broadleaf mixed forests can increase aboveground forest carbon stocks.

Hyperspectral identification and cross-temporal classification of wetland vegetation in the Huang-Luo-Wei Sanhekou Wetland

WANG Qian, ZHANG Jingru, WANG Dongdong, LUO Zhiping, GUO Wei

2026,(2):  47-59.  doi:10.13466/j.cnki.lczyyj.2026.02.005

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Accurate identification of wetland vegetation is critical for monitoring and protecting wetland ecosystems.However,traditional multispectral remote sensing struggles to distinguish wetland plants with similar spectral signatures because of its broad spectral bands and cannot capture spectral changes across different phenological stages.Hyperspectral data,with its continuous and fine spectral resolution,provide a solution for detailed plant classification.Nevertheless,the variation patterns of spectral characteristics of different plants during phenological changes remain unclear,limiting the accuracy of cross- temporal classification.To investigate the difference in spectral characteristic of wetland plants under phenological changes and their impact on cross-temporal classification accuracy,the Sanhekou Wetland,where the Yellow River,Wei River,and Beiluo River converge,was selected as the study area.Field hyperspectral observations were conducted during vigorous growth stage (June) and senescence stage (September) in 2022.Using the envelope removal,“three-edge”parameter extraction,vegetation index construction,and PCA-CNN feature fusion,spectral differentiation patterns were analyzed and cross-phase classification models were established.The results indicated that:1) Plants with reflectance less than 45% at 750 nm and a red-edge reflectance increment less than 0.3 per 10nm were identified as woody plants,while those with the opposite characteristics were identified as herbaceous plants.The red-edge chlorophyll index (RECI) and red-edge normalized difference vegetation index (RENDVI) exhibited higher sensitivity for distinguishing plant types than conventional vegetation indices.2) The PCA-CNN feature fusion model achieved a classification accuracy of 66.24%,significantly improving classification performance compared with single-feature models.3) The model trained using June data showed a significant drop in accuracy to 41.1% when tested with September data.This decline was mainly attributed to the asymmetric spectral responses of different plants to phenological stages,which weakened the cross-temporal generalization capability of the model.These results reveal that wetland vegetation exhibits distinct spectral differentiation patterns during phenological changes.The PCA-CNN feature fusion model effectively improves fine-scale wetland vegetation classification performance,and phenological changes are an important factor affecting cross-temporal classification accuracy.This study provides technical support for fine-scale identification of regional wetland plants and large-scale hyperspectral remote sensing classification.

Effects of simulated nitrogen deposition on soil nutrients and nitrogen mineralization in Larix gmelinii var. principis-rupprechtii plantations

YANG Liu, CUI Hongna, JIA Yanlong, XU Zhongqi

2026,(2):  60-69.  doi:10.13466/j.cnki.lczyyj.2026.02.006

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Increasing global nitrogen deposition can affect nutrient cycling in terrestrial ecosystems and profoundly influence forest soil nutrients and nitrogen mineralization rates.A typical Larix gmelinii var.principis-rupprechtii (Mayr)Pilg.plantations in the northern Yanshan Mountains were selected as the study site.A simulation nitrogen(N)deposition experiment was conducted with seven N addition levels of 0,5,10,20,40,80,and 160 kg/(hm²·a),designated T0,T5,T10,T20,T40,T80,and T160,respectively.The effects of N addition on soil nutrients and N mineralization rates were analyzed after three years of treatment.The results showed that:1)Simulated nitrogen deposition significantly affected soil ${\mathrm{N}\mathrm{O}}_{3}^{-}$-N content,with significant differences between T160 and T5,T10,and T20 treatments(P<0.05).2)With increasing N addition,soil net N ammonification rate,net N nitrification rate,and net N mineralization rate initially increased and then decreased.The turning points of the net N nitrification rate and net N mineralization rate were both more than 80 kg/(hm²·a)(R²=0.92,P<0.01;R²=0.93,P<0.01).Soil gross N ammonification rate decrease with increasing N addition(R²=0.67,P>0.05),while gross N nitrification rate initially increased and then decreased,with a turning point>80 kg/(hm²·a)(R²=0.81,P<0.05).3)The main soilfactors affecting the net N ammonification rate were ${\mathrm{N}\mathrm{O}}_{3}^{-}$-N,pH,and total phosphorus(TP),whereas those affecting the net nitrification rate were ${\mathrm{N}\mathrm{O}}_{3}^{-}$-N content,C∶P,and N∶P.The nonlinear response of soil N mineralization rates to N addition provides a theoretical basis for predicting dynamic changes in soil N mineralization rates under N deposition.

Spatial regulation of soil organic carbon fractions and enzyme activities by Morchella sextelata mycelium activity in an under-forest semi-natural cultivation system

PENG Bin, WEI Haixia, LI Xun, ZHANG Yan, MA Hongliang, ZHANG Danju

2026,(2):  70-79.  doi:10.13466/j.cnki.lczyyj.2026.02.007

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To elucidate the spatial effects of Morchella sextelats mycelium activity on soil organic carbon fractions and enzyme activities,under-forest semi-natural cultivation of Morchella sextelata under a Pinus densata forest was investigated,with uncultivated soil serving as the control (CK).Soil samples were collected at distances of 0,20,and 40 cm from the fruiting bodies (R,R₂₀,and R₄₀,respectively).Changes in soil organic carbon fractions [readily oxidizable organic carbon (ROC),particulate organic carbon (POC),mineral-bound organic carbon (MOC),and total organic carbon (SOC)]and enzyme activities [catalase (CAT),urease (URE),β-1,4-glucosidase (BG),and cellobiohydrolase (CBH)]were analyzed to clarify the spatial regulatory mechanisms affecting the soil carbon pool and enzyme activities.The results showed that:1)Compared with CK,cultivation of Morchella sexta.decreased soil pH and electrical conductivity (EC),with the lowest values occurring at R and R20,respectively.Total phosphorus (TP)tended to decrease,whereas total nitrogen (TN) tended to increase and reached its highest value at R₂₀;however,neither change was significant.2)Compared with CK,SOC and MOC contents at R area were significantly lower,whereas SOC and its fractions (POC,MOC,and ROC)at R₂₀ area increased.3)Compared with CK,CAT and URE activities at R a,BG,andCBH activities of R₂₀ were significantly lower.However,BG and CBH activities at R and CAT and URE activities at R₄₀ showed increasing trends.4)Mantel test and redundancy analysis (RDA)showed that pH and EC were the core regulatory factors,exerting direct positive effects on soil enzyme activities,SOC,and MOC,whereas TP negatively regulated the transformation of soil organic carbon fractions.In summary,Morchella sextelata mycelium activity significantly regulated the spatial variation in soil organic carbon fractions and enzyme activity,with pH and EC serving as the key drivers this process.

Analysis of characteristics and distribution patterns of ancient and famous tree resources by using geographically weighted regression: A case study of Yongjia County in Zhejiang Province

CHEN Zhenming, LI Maosheng, ZHENG Jiemin, LIN Haiping, DAI Huiming

2026,(2):  80-92.  doi:10.13466/j.cnki.lczyyj.2026.02.008

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Yongjia County,Zhejiang Province has abundant resources of ancient and famous trees.Analyzing their characteristics and distribution patterns is of great significance for protecting local ancient and famous trees.Based on two surveys of ancient and famous tree resources in Yongjia County,Zhejiang Province,the growth potential index is introduced as a quantitative standard.Pearson correlation coefficient and ArcGIS spatial autocorrelation analysis methods are used to establish a geographically weighted regression model to analyze the resource characteristics,spatial heterogeneity,and distribution pattern of ancient and famous trees within Yongjia County.The results showed that:1)There are 1 381 ancient and famous trees surviving in Yongjia County,belonging to 31 families,51 genera,and 70 species.2)Through Pearson correlation analysis,environmental factors such as slope,altitude,soil layer thickness,annual average temperature,annual evaporation,and annual precipitation were selected from 8 environmental factors that have a significant impact on the growth and development of ancient and famous trees.Among them,altitude and annual average temperature have the most significant impact,and these two environmental factors are highly correlated with tree age,height,diameter at breast height,and crown width,with correlation coefficients(r)of -0.089,0.072,0.116,and 0.347,respectively.3)The Moran’s index for spatial autocorrelation analysis of ancient and famous trees in Yongjia County is 0.142,with pvalue of 0.077,which is at the marginal significance level.This indicates that there is a weak spatial autocorrelation in the spatial distribution,which has certain clustering characteristics and significant differences in spatial distribution.The northern region is a high clustering and high-density area.4)The response degree of the growth index of ancient and famous trees in Yongjia County to environmental factors shows significant spatial heterogeneity,with an overall trend of gradually increasing from the central region to the surrounding areas.The response degree is the lowest in the central region and the highest in the northwest region.The research results would provide a theoretical basis for the protection and management of ancient and famous trees in Yongjia County in the future.

Technical Application

Urban single-tree crown detection method for camphor trees based on an improved YOLOv5 model

ZHENG Zhe, XIA Kai

2026,(2):  93-101.  doi:10.13466/j.cnki.lczyyj.2026.02.009

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Individual tree detection plays a critical role in urban ecosystem management and greening monitoring.While deep learning algorithms are widely applied in tree detection due to their strong performance in computer vision,most methods struggle to achieve precise detection in complex urban environments,especially with varying crown sizes,diverse species,and high canopy density.To address these challenges,this paper proposes an improved YOLOv5-based algorithm,YOLOv5-CSC,for detecting camphor trees in unmanned aerial vehicle(UAV RGB)images.The model uses diverse convolution kernels in the ConvNeXt module for fine-grained local feature extraction,and incorporates SPPF and C3TR modules to enhance the receptive field and feature fusion efficiency,significantly improving crown detection in complex urban settings.Experimental results show that the YOLOv5-CSC model achieves mean average precision(mAP@0.5)improvements of 5.3%,8.8%,and 8.2% compared to existing models such as Faster R-CNN,SSD,and YOLOv7.Compared to the baseline YOLOv5 model,the mAP increased from 80.3% to 85.5%.The improved model demonstrates higher accuracy and robustness in handling complex backgrounds and overlapping crowns,and excels in adaptability across various scenarios,effectively supporting urban greening management and ecological monitoring.

Inversion of aboveground biomass of Dendrocalamus giganteus by using spaceborne LiDAR and optical remote sensing data

WANG Mingxing, SHU Qingtai, XIA Cuifen, WU Zaikun, ZHOU Sai, DUAN Dandan, LI Shengjiao

2026,(2):  102-114.  doi:10.13466/j.cnki.lczyyj.2026.02.010

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Investigating the potential of combining Global Ecosystem Dynamics Investigation(GEDI)multi-beam LiDAR data(referred to as GEDI data)with Sentinel-2 optical remote sensing data(referred to as Sentinel-2 data)for estimating aboveground biomass in bamboo forests plays a crucial role in assessing the state of forest ecosystems.This estimation is essential for evaluating the condition of forest ecosystems.With Xinping Yi and Dai Autonomous County,Yuxi City,Yunnan Province as the research area and by utilizing GEDI data alongside Sentinel-2 data as primary information sources,a total of 51 661 point parameters were extracted from the GEDI data.Utilizing Kriging interpolation,continuous and comprehensive surface information was generated.In conjunction with Sentinel-2 data and 52 sample images,two modeling techniques,involving Random Forest(RF)and Gradient Boosting Regression Trees(GBRT),were employed to estimate the biomass of Dendrocalamus giganteus in Xinping County.The results indicated that:1)The four parameters provided by GEDI L2B data,namely modis_treecover,landsat_treecover,digital_elevation_mode,and modis_nonvegetated,along with the four vegetation indices calculated from Sentinel-2 Level-2A surface reflectance imagery,including DVI,ARVI,RVI,and NDVI,exhibited a high correlation with the above-ground biomass of Dendrocalamus giganteus.They can be used to estimate the above-ground biomass of Dendrocalamus giganteus at the county scale.2)In single-source modeling scenarios,GBRT demonstrates superior performance compared to RF:With exclusive use of Sentinel-2 data vegetation indices,GBRT achieves estimation accuracy metrics of the coefficient of determination with R² of 0.84 and the root mean square error(RMSE)of 11.00 t/hm²,whereas RF yields R² is 0.74 and RMSE is 14.17 t/hm².This performance trend persists when utilizing GEDI data parameters,where GBRT attains R² of 0.92 and RMSE of 7.77 t/hm²,contrasting with RF’s results of R² of 0.87 and RMSE of 9.95 t/hm².3)When combining GEDI data parameters and vegetation indices,GBRT achieves higher predictive accuracy with R² of 0.93 and RMSE of 7.47 t/hm²,whereas RF shows slightly lower accuracy with R² of 0.88 and RMSE of 9.60 t/hm².4)Based on the evaluation results of GEDI data and Sentinel-2 data,the biomass of Dendrocalamus giganteus,Xinping County is estimated to be 1.45×10⁷ t,with an average biomass of 61.91 t/hm².This demonstrates that combining GEDI data and Sentinel-2 data optical remote sensing to estimate the biomass of Dendrocalamus giganteus,Xinping County would provide a reference for multi-source remote sensing inversion in county-level data integration.

Research Briefing

Current status,challenges,and pathways for incorporating China’s protected area data into the World Database on Protected Areas

LI Xiao, WU Zhengyu, TAO Yijun, WANG Xiaoli, LU Wenhai

2026,(2):  115-124.  doi:10.13466/j.cnki.lczyyj.2026.02.011

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The World Database on Protected Areas (WDPA) is an important dataset for assessing progress toward the conservation targets of the Kunming-Montreal Global Biodiversity Framework.Its records directly influence the international comparability of conservation achievements,the visibility of national contributions,and countries’ influence in global environmental governance.To assess the insufficient representation and potential biases of China's protected area data in the WDPA and its underlying causes,while also exploring the strategic value and feasible pathways for incorporating these data into the database,a quantitative and qualitative evaluation was conducted based on WDPA and domestic datasets from the perspectives of global ranking,data sources,and spatial discrepancies.The findings are intended to support the alignment of China's protected area data with international standards and to strengthen China's discourse power in global biodiversity governance.Only 122 Chinese protected areas are currently included in the WDPA,ranking 88^th worldwide and accounting for 0.04% of the global total.The current data mainly originate from international convention reporting channels and are characterized by outdated records and limited category diversity.Spatial analysis of 12 marine protected areas exposes notable anomalies such as boundary misalignment,data format downgrading and geographical location errors.Systematic incorporation of China’s protected area data into the WDPA can enhance China’s visibility and influence in global conservation assessments,and support scientific research and ecological diplomacy,while also involving challenges related to international scrutiny and data security.Strategic pathways are proposed,including establishing a full-chain data management system,implementing differentiated submission strategies,and participating in the formulation of relevant international standards.Integrating China’s protected area data with the WDPA is an important pathway for China’s deeper participation in global biodiversity governance.Phased implementation is recommended to gradually improve data alignment with international standards.

Review

Research progress on mechanisms and mitigation strategies of allelochemicals in invasive plant

GUI Qing, YANG Jianxin, MA Changle

2026,(2):  125-136.  doi:10.13466/j.cnki.lczyyj.2026.02.012

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Invasive plants are among the most widespread and persistent invasive taxa,severely disrupting ecosystem structure and function.Current research allelopathic effects of invasive plants is constrained by limited species coverage,a high proportion of laboratory simulation experiments,and insufficient studies on community-scale interactions,which impede the systematic elucidation of chemically mediated competition mechanisms.By synthesizing reviewing advances in the composition,release mechanisms,and allelopathic inhibition of allelochemicals,this review reveals that invasive plants primarily release phenolic acids,terpenoids,and flavonoids through rainfall leaching and root exudation to suppress native plant growth.Notably,some invasive plant allelochemicals also exhibit autotoxic effects,which may partially restrict excessive population expansion of invasive species.Future research should focus on plant community scales and integrate multidimensional ecological perspectives to clarify how allelopathy modulates plant community assembly and succession under global change.These findings provide theoretical support for understanding plant invasion mechanisms,supporting the development of early-warning frameworks and sustainable management strategies for invasive plant species.