Table of Content

28 February 2024, Issue 1

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Integrated Management and Administration

Analysis of Dominant Causes and Rescue Casualties of Forest Fires in China from 2000 to 2022

WANG Ao, WANG Chenghu, GAO Guiyun, WANG Mingyu

2024,(1):  1-7.  doi:10.13466/j.cnki.lczyyj.2024.01.001

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In order to analyze the main causes of forest fires and casualties in China over the past 20 years,based on the case records of forest fire fighting casualties and statistical data on relevant meteorological factors(average temperature,average precipitation,average wind speed)from 2000 to 2022,statistical analysis and correlation analysis method were used to analyze the main causes of forest fire and the main causes of casualties in fire fighting.The results showed:1)From 2000 to 2022,a total of 134,671 forest fires occurred in China.Among these the period of high incidence of forest fires was from 2003 to 2010.Severe climatic conditions were the main cause of forest fires during that period.In the past 10 years,more than 97% of forest fires have been caused by humans.In regions such as Guangxi,Yunnan,and Guizhou where agriculture and forestry are closely integrated,forest fire accidents occur frequently.2)Analysis of typical forest fire fighting cases shows that the accidents resulting in direct casualties caused by geographical environment,combustible conditions,meteorological conditions and fire activities account for the dominant part,while the casualties caused by non-indirect causes such as asphyxia,accidents and improper operation of fire fighting equipment also occasionally occurred.The research shows that the main causes of forest fires in China are meteorological factors and human factors,with casualties primarily resulting from unfavorable natural conditions.The main causes of forest fires and the causes of casualties are elaborated to provide a reference for efficient firefighting,scientific and accurate command.

The Franchising Development Path of the Hainan Tropical Rainforest National Park Based on the Recreation Opportunity Spectrum

GENG Songtao, SUN Kexin, SONG Liangan, YAN Rong

2024,(1):  8-16.  doi:10.13466/j.cnki.lczyyj.2024.01.002

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The establishment of a national park system is a key reform task put forward by the Third Plenary Session of the 18th CPC Central Committee.It is an important element in the systems for promoting ecological progress.Exploring the path of high-quality development of national park franchising is of great significance in promoting the transformation and upgrading of national park recreation,improving quality and efficiency,and promoting the construction of China ecological civilization.It takes Hainan Tropical Rainforest National Park as the research object.Based on the theory of recreation opportunity spectrum,it clarifies the relationship between the utilization of recreation opportunities and franchising.Applying the factor analysis method and group decision-making hierarchical analysis method,it constructs the evaluation indicator system of recreation opportunities to evaluate the recreation opportunity levels of the seven areas of Hainan Tropical Rainforest National Park.The recreation opportunity spectrum of Hainan Tropical Rainforest National Park has been formalized.The high-quality development path of franchise in Hainan Tropical Rainforest National Park is proposed to reconstruct the franchise mode,enhance the effectiveness of management services,optimize the fund management system,establish a common sharing mechanism,and improve the multi-dimensional supervisory system.This is aimed at providing scientific guidance and useful references for the franchise of national parks and realizing the value-added of the brand of national parks.

Scientific Research

Spatiotemporal Trends and Influencing Factors of Forest Carbon Stock in Jiangxi Province from 2005 to 2020

LI Jiao, WANG Bing, WANG Chen, GAO He, WU Huilong, ZHENG Xin, PENG Huafu

2024,(1):  17-24.  doi:10.13466/j.cnki.lczyyj.2024.01.003

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Forest ecosystems play a key role in mitigating and adapting to climate change.A comprehensive understanding of the spatiotemporal trends in forest carbon stocks is essential for maintaining the regional carbon balance,predicting the potential of forest carbon stocks,adjusting conservation and management measures.Based on the three remote sensing datasets,forest carbon stock(FCS),land use cover change(LUCC)and digital elevation model(DEM),Mann-Kendall nonparametric test and correlation analysis methods were used to analyze the spatiotemporal trends of forest carbon stock and its response to land use change in Jiangxi Province from 2005 to 2020.The results showed that 1)forest carbon stock in Jiangxi Province showed an upward fluctuating trend,with an average annual growth rate of 12.59%,the minimum value appeared in 2009,which was 5.3×10⁸tC,and the maximum value appeared in 2018,which was 6.5×10⁸tC.2)The carbon stock is increasing in hilly areas in the central and southern parts,while it is decreasing in the lower-altitude northern parts.3)Jiangxi Province shows a decreasing trend in forest area but an increasing trend in forest carbon stocks,mainly due to urban expansion and continued sustainable forest management.4)Ecological protection and restoration measure is one of the main factors that promoting the stable increase of forest carbon stock in Jiangxi Province.In the future,the rich forest resources should be fully developed,and the synergistic efficiency of environmental protection,economic development,and poverty alleviation should be promoted through the development of Chinese Certified Emission Reduction(CCER) forestry carbon sink projects.

Assessment of Ecosystem Services in Helan Mountain National Nature Reserve in Ningxia

LI Huijie, LI Wanting, WANG Bing, NIU Xiang, LIANG Yongliang, LI Jingyao

2024,(1):  25-33.  doi:10.13466/j.cnki.lczyyj.2024.01.004

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Ecosystem service functions can promote harmony between human and nature.Exploring the ecosystem service functions of Helan Mountain National Nature Reserve is of great significance for adopting a holistic approach to conserving and management our mountains,rivers,forests,farmlands,lakes,grasslands,and deserts.Based on a series of national standards for long-term observation research and service function evaluation of forest and grassland ecosystems,as well as applying a distributed calculation method based on forestry compartment data,we selected five forest and grassland ecosystem service functions,namely,soil conservation,forest nutrient sequestration,water conservation,carbon sequestration and oxygen release,atmospheric purification to assessed their benefits in terms of physical quality and value quantity.The results show that the physical quality of forest and grassland ecosystem services in the Helan Mountain National Nature Reserve in Ningxia present present a spatial distribution pattern of high in the northeast and low in the southwest;the total value is 2.827 billion yuan/a,of which the functions of water conservation and soil conservation in the top two.There are the main services function of forest and grassland ecosystems in Ningxia Helan Mountain national Nature Reserve.The Helan Mountain National Nature Reserve should further strengthen forest management,optimize tree species and age structures,enhance the quality of forest ecosystems,and fully leverage the ecosystem services.

Wildlife Video Object Detection Based on Deep Learning

WANG Shuai, LU Nan, ZHENG Hong, LI Hui, PENG Jiangui, ZHANG Tong, WEI Yanhua

2024,(1):  34-40.  doi:10.13466/j.cnki.lczyyj.2024.01.005

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Ecological sensing terminals represented by infrared cameras provide massive amounts of image and video data for wildlife monitoring research.To improve the problems of low timeliness and limited processing ability in manual recognition of massive data,and to solve the uncertainty of object detection models in practical scenarios affected by multiple factors such as complex backgrounds,multiple targets,light and dark,a wildlife object detection dataset was established using leopard,adult male bharal,and non-adult male bharal as examples.Four classic object detection models,Faster R-CNN,SSD,YOLOv5,and YOLOv8,were compared and analyzed in terms of detection accuracy,detection speed,and detection effectiveness in actual scenarios.The results show that the detection effect and speed of YOLOv5 and YOLOv8 are overall better than Faster R-CNN and SSD.1)YOLOv8 has higher detection accuracy and stronger robustness under multiple interference factors,making it more suitable for scenarios that pursue detection results;2)All four models can meet the real-time video detection needs of ecological perception terminals,but the YOLOv5 model is the lightest and has the fastest detection speed,making it more suitable for scenarios with limited computability that pursue detection speed.YOLOv5 and YOLOv8 have superior performance and are suitable for detecting wildlife video targets in practical scenarios.

Bark Fire Resistance of 6 Tree Species Based on Entropy Weight Method

LI Shuhui, WU Yan, SUN Zhidong, WANG Cai, LIAO Lili, CHEN Ji'en, XIAO Xuejun, SHEN Junhua

2024,(1):  41-47.  doi:10.13466/j.cnki.lczyyj.2024.01.006

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The frequent occurrence of forest fires in Xichang City posed great threat to local people's property and forest ecology.In order to effectively enhance the forest fire prevention capability,the fire resistance of bark of 6 tree species in mountain forest around Xichang City were measured and analyzed.Using entropy weight method and cluster analysis,the fire resistance performance of 6 tree species were sorted and classified,which is based on their comprehensive physicochemical properties and combustion performances differences.The results indicated that there were significant differences in the physicochemical properties and combustion performances of bark among the tree species.The thickness of the bark and the content of crude ash were relatively high,while the moisture content and crude fat content were relatively low in Sapindus mukorossi bark.The moisture content and ignition point of Phyllanthus emblica bark were significantly higher than those of other tree species,and the content of crude fibre and caloric value were significantly lower than those of other tree species.The bark thickness,the content of crude fat and lignin of Ligustrum lucidum bark were relatively low,and its ignition point was significantly lower than other that of tree species.The bark thickness,the content of crude fat,ignition point,and caloric value of Sapium sebiferum were all relatively high.The content of crude ash in Illicium simonsii bark was relatively low,and the content of crude fibre was significantly higher than that of other tree species.The bark of Pinus armandii had the lowest moisture content and significantly higher caloric value than that of other tree species.Bark fire resistance of the 6 tree species followed the order of S.mukorossi>P.emblica>L.lucidum>S.sebiferum>I.simonsii>P.armandii.The fire resistance of bark from 6 tree species could be divided into 3 class.S.mukorossi had better fire resistance and could be used as the local fire-resistant tree.The fire resistance of P.emblica,L.lucidum and S.sebiferum was average,which could be used in the construction of mixed forest in biological fire barriers.I.simonsii and P.armandii had poor fire resistance,which should be paid attention to fire prevention in large areas of pure forest.

Diversity of Mammals and Birds in the Water Sources of An’nanba Wild Camel National Nature Reserve in Gansu Province

WU Hao, MA Yongsheng, WANG Tianhui, Hezierhan , WANG Shengqi, XUE Yadong, LI Jia

2024,(1):  48-55.  doi:10.13466/j.cnki.lczyyj.2024.01.007

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This study aimed to determine the status of wildlife in An’nanba Wild Camel National Nature Reserve and provide substantial data for diversity conservation.From January 2020 to March 2023,we deployed camera trapping to investigate the diversity of wildlife at water sources in An’nanba,Gansu province,China.We obtained 3 303 photographs of single animals(out of 18 773 total detections)among 11 443 camera-trap days at seven water sources,and identified 17 mammal species(representing to 9 families and 4 orders),and 32 bird species(representing to 12 families and 7 orders).1)Among species,ten of them are listed as the first class in the key protected wild animals of national importance and eighteen are listed as the second class.Twenty-four wildlife species were evaluated as Near Threatened or above by the Red List of China’s Biodiversity.2)The Shannon-Wiener diversity index of the mammal and bird community is 2.67 and 3.03,respectively,and the Pielou evenness index of mammal and bird community is 0.65 and 0.62,respectively.3)Based on the relative abundance index(I_RA),Gazella yarkandensis(99.54),Camelus ferus(53.57),Panthera uncia(35.22),Aegypius monachus(15.64),and Pseudois nayaur(13.81)were ranked as the top most abundant mammals and bird’s species.Our results provided a baseline of the wildlife resource in An’nanba Wild Camel National Nature Reserve,which is essential for biodiversity conservation and long-term monitoring in this area.

Remote Sensing Estimation of Average Diameter at Breast Height of Forest Stands Based on Airborne LiDAR and Machine Learning Algorithms

TANG Jiajun, CHAI Zongzheng

2024,(1):  56-64.  doi:10.13466/j.cnki.lczyyj.2024.01.008

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In order to explore the prediction accuracy of different models on the average diameter at breast height of forest stands,airborne LiDAR point cloud data and ground measured sample plot datawere obtained simultaneously by the Machang working area of Guihua State-owned Forest Farm in Guizhou Province.By extracting point cloud feature variables at the sample plot level,a machine learning model is used toestimate the average diameter at breast height of the sample plot,variance inflation factor analysis and Pearson correlation test are used to select independent variables.The results indicate that:1)Point cloud feature variables show a strong correlation with the average diameter at breast height of the forest stand,such as the average canopy height and height skewness.2)Machine learning models(random forest,support vector machine,nearest neighbor algorithm)outperform multiple linear regression models,with random forest having the best fitting performance.The determination coefficient(R²) for the random forest model is 0.71,withthe root mean square error(RMSE)of 2.50.3)The difference between the predicted and actual average diameter at breast height of four forest types:Cryptomeria forest,mixed coniferous forest,mixed coniferous and broad-leaved forest,and Pinusmassoniana forest further confirms that the random forest model has the highest accuracy and the best fitting effect.In summary,it is feasible to extract point cloud feature variables using airborne LiDAR point cloud data and construct a forest average diameter estimation model based on machine learning algorithms.The accuracy of this method meets the application requirements of forest resource investigation and can be used as a technical means to assist in forestry investigation work.

Remote Sensing Inversion of Mangrove Biomass Based on Machine Learning

HAO Jun, LYU Kangting, HU Tianqi, WANG Yunge, XU Gang

2024,(1):  65-72.  doi:10.13466/j.cnki.lczyyj.2024.01.009

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Accurately investigating mangrove biomass is beneficial for evaluating the carbon sink potential of mangrove ecosystems.Based on field survey data,Landsat 8 remote sensing images and DEM data,22 feature variables were extracted to carry out remote sensing inversion of mangrove biomass in the Ximen Island,which used three machine learning methods:Random Forest(RF),Support Vector Machine model(SVM)and eXtreme Gradient Boosting(XGBoost).The results showed:1)Compared to the RF model and SVM model,the XGBoost model had a better estimation performance(R²=0.932,E_RMS=0.514 t/hm²,E_MA=0.313 t/hm²),which could more accurately estimate the mangrove biomass.2)Among the 10 important characteristic factors selected by Recursive Feature Elimination(RFE),the vegetation index has a relatively high importance in estimating mangrove biomass.3)The biomass inversion map of the XGBoost model,which is composed of 10 important characteristic factors,showed that the estimated mangrove biomass ranges from 9.138 to 29.229 t/hm²,which was similar to the findings of the field survey.It can be seen that the XGBoost algorithm shows good application capabilities in mangrove biomass.This research will provide a technical reference for the accounting of carbon storage in the Chinese mangroves.

Comprehensive Adaptability Evaluation of Six Kinds of Landscapeing Plants in Semi-arid Region

ZHOU Long, YANG Xiaoxue, DUAN Xiaochen

2024,(1):  73-81.  doi:10.13466/j.cnki.lczyyj.2024.01.010

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Comprehensive adaptability evaluation can effectively solve the problem of blind selection of landscaping plants in semi-arid areas.Six candidate landscaping plants transplanted in the typical semi-arid area of Yunzhou Districtin Datong City have been selected asresearch objects.The expert consultation method isadopted to select the comprehensive adaptability evaluation indexes of landscaping plants.The weight of evaluation indexes is determined by combining the analytic hierarchy process(AHP)and the objective weighting method of CRITIC.The comprehensive evaluation is carried out by the fuzzy comprehensive evaluation method to calculate the comprehensive adaptability scores of each plant.The results are verified by conducting experiment in the experimental area.The results showed as follows:1)There were three primary evaluation indexes that affected the comprehensive adaptability of plants:ornamental characteristics,growth characteristics and ecological adaptability.There were 15 secondary indexes:flower observation,fruit observation,color leaf observation and shape observation;tree height,ground diameter,crown width increase,reproductive ability;drought resistance,cold resistance,heat resistance,pest resistance,saline-alkali resistance,waterlogging resistance,wind resistance.2)The score of comprehensive adaptability is:Cotoneaster multiflorus>Lonicera caerulea>Euonymus alatus>Lonicera rupicola>Lonicera chrysantha.The score of comprehensive adaptability of Cotoneaster multiflorus is the highest,which is consistent with the experimental result.The results showed that Cotoneaster multiflorus should be selected as a landscaping plant in this area due to its high comprehensive adaptability evaluation in semi-arid areas.

Height-diameter Model of Cunninghamia lanceolata Based on Deep Neural Network

WANG Guilin, TAN Wei, CHEN Botao

2024,(1):  82-87.  doi:10.13466/j.cnki.lczyyj.2024.01.011

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By using the deep Neural Network (DNN) model to establish the tree height-diameter model of Cunninghamia lanceolata, we are seeking a more efficient method for predicting the tree height of Cunninghamia lanceolata.The diameter at breast height and tree height data of Cunninghamia lanceolata in 49 plots of state-owned forest farm in Qingzhen City,Guizhou Province were studied,and divided into different proportions of training set and test set data.This consists of training set data(20%,30%,40%,50%,60%,70%,80%,respectively)and test set data(80%,70%,60%,50%,40%,30%,20%,respectively).DNN was used to build a tree height-diameter model,and the model was compared with 11 traditional basic models.Select the model with the best predictive performance by comparing the results of R²,RMSE and MAE.Adding the ratio of diameter at breast height to average diameter at breast height(DDH)of dominant trees based on the optimal model to improve the prediction accuracy.When the training set proportion of the DNN model is 20%,the prediction accuracy of the tree height-diameter model can reach more than 0.89 after adding DDH factor.DNN was used to build a height-diameter model to predict the height of Cunninghamia lanceolata,and adding DDH factor could improve the prediction accuracy of Cunninghamia lanceolata height with a smaller dataset.

Technical Application

Construction of a Carbon Storage Measurement Model for Eucalyptus Canopy in Guangxi Based on Drone Oblique Photography

ZHU Zan, WANG Yongjun, WANG Jianqi, XU Yulan, QIU Xinqi, WAN Xi

2024,(1):  88-94.  doi:10.13466/j.cnki.lczyyj.2024.01.012

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Calculating forest carbon storage is an important technology for China to achieve the goals of carbon dioxide peaking and carbon neutrality in the context of global warming.At present,conventional forest carbon storage accounting primarily adopts measuring standing trees in sample plots,which is less efficient and more costly in terms of labor.Meanwhile,there are problems such as the low accuracy of forest canopy data measurement.To address this issue,this study constructed a set of mathematical models based on the volume V of the canopy oblique photography model of Eucalyptus trees in Guangxi to predict their carbon storage T through experiments and data analysis.This was done using the oblique photogrammetry technology of unmanned aerial vehicles,as well as mathematical and statistical methods.Also,it takes reference to the relevant standards set by the forestry department and local authorities.It verified that experimental validation and regression analysis showed that the goodness-of-fit threshold R² of this model reached 0.889 6,and the model can provide support for the investigation of eucalyptus forest carbon storagein Guangxi.At the same time,the methods and techniques in this study can also be appliedas a reference for constructing oblique photography carbon storage measurement models for other tree species.

Carbon Content of Landscaping Tree Species in Zhengzhou City

DING Qike, DOU Hao, ZHANG Ershan, HU Chuanwei, HE Jing

2024,(1):  95-101.  doi:10.13466/j.cnki.lczyyj.2024.01.013

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This study explores the carbon content characteristics of various organs of landscaping tree species in Zhengzhou city.It provides a basis for selecting and formulating policy on landscaping tree species with carbon sequestration value in Zhengzhou city.The carbon content of five organs,including trunk,branches,leaves,bark,and roots,was measured using the potassium dichromate external heating method for 14 landscaping tree species,including Platanus orientalis L.,Populus L.,Michelia alba DC.,Ginkgo biloba L.,Prunus cerasifera 'Atropurpurea',Prunus serrulata var.lannesiana(Carri.)Makino.,Crataegus pinnatifida Bunge,Prunus davidiana (Carrière)Franch.,Osmanthus fragrnas(Thunb.)Lour.,Ligustrum lucidum Ait.,Magnolia grandiflora L.,Cedrus deodara(Roxb.)G.Don,Eriobotrya japonica(Thunb.)Lindl.,hotinia serratifolia(Desf.)Kalkman.The results show that:1)The variation range of carbon content in different organs among 14 tree species is 25.88% to 59.15%.2)For the same tree species(taking the example of the Platanus orientalis L.),the coefficient of variation between barious organs is 7.41% to 9.36%,and the coefficient of variation between the same organs is 0.16% to 2.54%.3)For different tree species,the coefficient of variation between the same organs is 10.44% to 19.30%,and the coefficient of variation between different organs is 4.73% to 22.54%; The overall average carbon content of variaus organ is as follows:trunk>branches>bark>leaves>roots,and the carbon content of the trunk is significantly higher than others.

Phenotypic Variation and Early Selection of Half-sib Families of Pinus yunnanensis

LI Zhongmu, CHE Fengxian, GAO Chengjie, LI Jin, WANG Lu, CUI Kai

2024,(1):  102-110.  doi:10.13466/j.cnki.lczyyj.2024.01.014

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Pinus yunnanensis is a unique native species to Southwest China,distributed in the southeastern margin of the Qinghai-Tibet Plateau,and its genetic degradation is a serious concern.To accelerate the breeding process and diversify the genetic resources,95 half-sib families of P.yunnanensis were evaluated and selected in the early stage based on the systematic analysis of nutritional growth traits(plant height,ground diameter,long crown diameter,short crown diameter,height under the branches,length of primary branches in the current year,and number of lateral branches in the current year) and reproductive growth traits(number of cones).The results indicated that:1)there were significant differences in nutritional growth traits among families of P.yunnanensis,indicating that it had rich genetic variation and selection potential.2)The coefficient of variation and heritability of phenotypic traits were 21.60%~86.07%and 0.75~0.78,respectively,indicating that the traits of P.yunnanensis had large variation,and they are strongly controlled by genetics.3)There is a strong correlation between phenotypic traits.By performing cluster analysis on the nutritional growth traits,the 95 families can be divided into three categories.4)By conducting a membership function analysis on the nutritional growth traits of P.yunnanensis,10 superior families were selected,and the genetic gain and actual gain of plant height were up to 19.63% and 25.17%,respectively,and ground diameter were up to 12.39% and 15.89%,respectively.There were abundant phenotypic variations among half-sib families of P.yunnanensis,and 10 superior families were selected based on vegetative growth traits.The results can provide material support and a theoretical basis for the breeding of improved varieties of P.yunnanensis.

Effects of Nitrogen and pH Treatment on Seedling Growth of Eucalyptus urophylla×E.grandis-Dallergia odorifera Intercropping Systems

WU Hao, DENG Jiazhen, HE Yaqin, LIN Mingye, YE Shaoming

2024,(1):  111-124.  doi:10.13466/j.cnki.lczyyj.2024.01.015

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In order to provide a scientific basis for exploring sustainable management of Eucalyptus plantations with high-efficiency biological nitrogen fixation,this study explores the response of root nodules,seedling growth and physiology to different nitrogen application and pH environments under the intercropping system of legume species Dalbergia odorifera and Eucalyptus urophylla×E.grandis.Adopting controlled pot experiments to simulate the intercropping system of D.odorifera and E.urophylla×E.grandis.The experiment was carried out by using a two-factor complete randomized block design,nitrogen(N)and pH with four concentration gradients were set to control the experiment:N1,N2,N3,N4 and pH4.5,pH5.5,pH7.5 and pH9.5,respectively.The results indicate that:1)Under N2 and N3 treatments,the nodule formation ability of D.odorifera was significantly inhibited(P<0.05).However,there were no significant differences between the N1 level and the control group(CK)in root nodule formation ability,and the root nodulation ability was strongest at pH7.5.2)The biomass and photosynthetic indexes of E.urophylla×E.grandis increased with the rise of N application.Except for pH9.5 treatment,those of D.odorifera initially increased but then decreased with increasing N application.3)The content of superoxide dismutase(SOD),catalase(CAT),peroxidase(POD),and nitrate reductase(NR)of D.odorifera and E.urophylla×E.grandis.leaves were increased with N application,while the content of malondialdehyde(MDA)showed the opposite trend.4)Except for the N3 treatment,the biomass of E.urophylla×E.grandis and D.odorifera seedlings were significantly higher under pH5.5 treatments than that of pH4.5 and pH9.5 treatments.5)The results of redundancy analysis showed that the nodule ability of D.odorifera in the intercropping system was limited by the physiological condition of D.odorifera and biomass of E.urophylla×E.grandis.In conclusion,moderate nitrogen addition and soil pH regulation are beneficial for the mutual development of D.odorifera and E.grandis seedlings in this system.

Winter Birds Diversity in Urban Green Spaces of Fuzhou

GU Lingzhen, YAN Shujun, LYU Wei, CHENG Min, HU Wenjing

2024,(1):  125-133.  doi:10.13466/j.cnki.lczyyj.2024.01.016

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Fuzhou is located on the East Asian-Australasian Flyways.This study explored the characteristics and differences of species,quantity,community structure and diversity of winter birds in different types of urban green spaces of Fuzhou,in order to provide a reference for the protection of winter birds.We investigated bird diversity using the transect line method and sample method in 7 different types of urban green spaces of Fuzhou during 2021 to 2023 in January and February,respectively.The species and quantity of birds in different urban green spaces are recorded.The α diversity was calculated using the Shannon-Wiener diversity index(H'),Pielou's evenness index(J)and Simpson dominance index(λ).The β diversity was calculated using the Sϕrensen similarity index(C_S),which was decomposed by the BAS method.The result showed that:1)197 species were recorded,belonging to 18 orders,54 families.There are 3 species listed in the first category of key protected wild animals of national importance,and 25 species in the second.There are 90 species in the Palearctic realm,72 species in the Oriental realm,and 38 species with wide distribution.There are 87 resident bird species,as well as 10 summer migrant species,91 winter migrant species,6 passing migrant species and 3 straggler species.2)The urban green spaces with the highest Shannon-Wiener diversity index(H')is Fuzhou National Forest Park(H'=3.928),and the lowest is the Wushan Historical Area(H'=2.914).The urban green spaces with the highest Pielou's evenness index(J)is Fuzhou National Forest Park(J=0.871),and the lowest is Fujian Changle Min River Estuary National Wetland Park(J=0.709).The urban green spaces with the highest Simpson dominance index(λ)is Wushan Historical Area(λ=0.088),and the lowest is Fuzhou National Forest Park(λ=0.026).3)Beta diversity species turnover(β_sim=0.278)is higher than Beta diversity nestedness(β_sne=0.242).It has been found that Fuzhou has anabundant quantity and variety of winter birds.Urban green spaces with large water areas or those close to water bodies contain more species and quantities of birds than mountain spaces that are far from water.The seven urban green spaces have an overall conservation value,and protection is equally important for all.

Research and Construction of Stand Form Height Model of Quercus glauca Secondary Forest

WU Sha, BIAN Gengzhan, YI Xuan, LYU Yong

2024,(1):  134-142.  doi:10.13466/j.cnki.lczyyj.2024.01.017

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Exploring the construction and evaluation method of the stand form height model could provide a theoretical basis for the precise measurement of stand volume of Quercus glauca secondary forest in Hunan Province.Based on the measured data of 1055 individual trees from 35 plots,we established the univariate form height model and the binary form height model of Quercus glauca secondary forest in Lutou Forestry Farm and Qingyanhu Forestry Farm.The Quercus glauca tree height curve was derived from the Kunze,M.stem curve to calculate the stand condition mean height.Based on the univariate and binary correlations een form height,stand diameter at breast height and stand condition mean height,6 univariate basic models and 8 binary basic models were selected,and the coefficient of determination(R²),root mean square error(RMSE),explained variance(EA),mean absolute error(MAE)and model prediction accuracy(P₁)were used as evaluation indicators.After evaluation and comparison,the univariate form height model was found to be f(D)=2.870 7×D^{0.261 8}、f(H)=2.022 4+0.339 5×H and the binary form height model was f(D,H)=0.590 6×exp(-0.008 3×D)H、f(D,H)=(0.710 2-0.070 1×logD)H and f(D,H)=2.479 9×(D²×H)^{0.109 2}.The models were tested through cross Leave-One-Out Cross-Validation and Paired T-test.The results showed that both univariate and binary stand form high models had high accuracy and strong applicability.It verified that the method of constructing a stand form height model based on the stand mean diameter at breast height and the stand condition mean height is reasonable and feasible.It can also provide demonstration and reference for the construction of other types of stand form height models and the preparation of stand form height tables.

Effects of Different Crown Density of Hevea brasiliensis Plantations on the Growth Characteristics of Aquilaria sinensis Saplings under Interplanting

ZHANG Fanglan, WU Shaozhong, XU Jianhui, SHA Linhua, LI Zhaojia, FANG Fazhi

2024,(1):  143-150.  doi:10.13466/j.cnki.lczyyj.2024.01.018

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In order to explore and screen out Hevea brasiliensis(Willd.ex A.Juss.)Muell.Arg stand suitable for intercropping of Aquilaria sinensis(Lour.)Spreng.Aquilaria sinensis saplings were interplanted in three different crown densities(0~0.1,0.2~0.3,0.7~0.8,respectively)Hevea brasiliensis plantations.The morphological indexes,total biomass dry weight,physiological and biochemical indexes of Aquilaria sinensis saplings in the experimental plantations were determined.Principal component analysis was used to analyze the response information of each index of Aquilaria sinensis saplings to Hevea brasiliensis forests with different crown densities.The Hevea brasiliensis forests suitable for the growth of Aquilaria sinensis saplings were selected by comparison.Results show :1)The Hevea brasiliensis plantation with a crown density of 0.2~0.3 had the highest growth rate of morphological indexes,the highest dry weight of total biomass,the total chlorophyll content,soluble protein content and catalase activity of Aquilaria sinensis saplings,which were significantly higher than those of the other two Hevea brasiliensis plantations.The malondialdehyde content was low,and the soluble sugar content and superoxide dismutase activity were not significantly different from those of the other two Hevea brasiliensis plantations.2)In Hevea brasiliensis plantations with a crown density of 0.7~0.8,the growth of Aquilaria sinensis saplings was the worst,and the total biomass dry weight was the lowest.3 )The growth of Aquilaria sinensis saplings was moderate in Hevea brasiliensis forest with a crown density of 0~0.1.4)Principal component analysis showed that the comprehensive score of each index of Aquilaria sinensis saplings interplanted in Hevea brasiliensis plantations with a crown density of 0.2~0.3 was the highest.Therefore,the 3-year-old Hevea brasiliensis plantationswith a crown density of 0.2~0.3 was more suitable for mixed intercropping of Aquilaria sinensis saplings.