Tree mycorrhizal associations determine how biodiversity,large trees,and environmental factors drive aboveground carbon stock in temperate forests

Biodiversity,large trees,and environmental conditions such as climate and soil have important effects on forest carbon stocks.However,recent studies in temperate forests suggest that the relative importance of these factors depends on tree mycorrhizal associations,whereby large-tree effects may be driven by ectomycorrhizal(EM)trees,diversity effects may be driven by arbuscular mycorrhizal(AM)trees,and environment effects may depend on differential climate and soil preferences of AM and EM trees.To test this hypothesis,we used forest-inventory data consisting of over 80,000 trees from 631 temperate-forest plots(30 m×30 m)across Northeast China to examine how biodiversity(species diversity and ecological uniqueness),large trees(top 1%of tree diameters),and environmental factors(climate and soil nutrients)differently regulate aboveground carbon stocks of AM trees,EM trees,and AM and EM trees combined(i.e.total aboveground carbon stock).We found that large trees had a positive effect on both AM and EM tree carbon stocks.However,biodiversity and environmental factors had opposite effects on AM vs.EM tree carbon stocks.Specifically,the two components of biodiversity had positive effects on AM tree carbon stocks,but negative effects on EM tree carbon stocks.Environmental heterogeneity(mean annual temperature and soil nutrients)also exhibited contrasting effects on AM and EM tree carbon stocks.Consequently,for the total carbon stock,the positive large-tree effect far surpasses the diversity and environment effect.This is mainly because when integrating AM and EM tree carbon stock into total carbon stock,the opposite diversity-effect(also environment-effect)on AM vs.EM tree carbon stock counteracts each other while the consistent positive large-tree effect on AM and EM tree carbon stock is amplified.In summary,this study emphasized a mycorrhizal viewpoint to better understand the determinants of overarching aboveground carbon profile across regional forests.

Does tree species composition control the soil carbon stocks of the Hyrcanian forest in the Northern Iran?(A case study in Guilan province,Iran)

This work studied the effects of tree species composition on soil carbon storage in five mixed stands dominated by oriental beech and grown in the western Caspian region in Guilan province, called Astara, Asalem, Fuman, Chere and Shenrud. The thickness of the litter layer, soil characteristics, tree composition and percentage of canopy coverage were measured in each stand. Total soil organic carbon differed significantly by stand. Total （organic） carbon stores at Fuman, which had the lowest tree species richness with 2 species and least canopy coverage （75%）, were significantly （p〈0.05） higher than at other locations. Carbon stor-age in topsoil （0-10 cm） was significantly lower in Shenrud, which had the highest tree species richness with 5 species and highest canopy cov-erage （95%）. The high percentage of canopy coverage in Shenrud proba-bly limited the conversion of litter to humus. However, in the second soil layer （10-25 cm）, Asalem, with high tree species richness and canopy coverage, had the highest carbon storage. This can be explained by the different rooting patterns of different tree species. In the Hyrcanian forest. According to the results, it can be concluded that not only tree composi-tion but also canopy coverage percentage should be taken under consid-eration to manage soil carbon retention and release.

基于机载激光雷达点云数据和Catboost算法的杉木单木蓄积量估测研究

选取福建顺昌县洋口国有林场6块杉木标准地内200株杉木的激光雷达点云数据和地面调查数据,基于机载激光雷达点云数据生成的冠层高度模型,运用局域极大值算法检测树冠顶点,提取树高;采用标记极值的分水岭算法估测冠幅面积,将估测的树高和冠幅面积结合单木蓄积量真值,构建基于Catboost算法的单木蓄积量估测模型。结果表明:使用局域极大值算法估测树高,R^(2)为0.91,RMSE为0.81 m;采用标记极值的分水岭算法估测冠幅面积,R^(2)为0.81,RMSE为1.18 m^(2);采用Catboost算法构建单木蓄积量估测模型R^(2)为0.934。因此,机载激光雷达点云数据可以有效估测树高和树冠面积,采用Catboost算法能够实现杉木单木蓄积量的估测,为高精度反演森林蓄积量提供新的思路。

地理加权机器学习模型在单木地上碳储量估测中的应用

2021年7—8月份,在陕西省延安市黄陵县双龙林场,以栎类次生林为研究对象,设置21块20 m×30 m的固定样地,调查样地内胸径5 cm及以上所有乔木树种种名、胸径、树高、株数、冠幅、第一活枝高等因子以及样地内每株乔木的坐标等数据;依据对21块样地调查的数据,以单木地上碳储量为评价指标,以林分因子、单木因子、立地因子为影响因素,分别构建普通最小二乘模型(OLS)、地理加权回归模型(GWR)、地理加权随机森林模型(GRF)、地理加权神经网络模型(GWANN),对研究区的单木地上碳储量进行模拟估测;采用决定系数、均方根误差、平均绝对误差对4种模型的拟合效果进行评价,利用全局莫兰指数检验4种模型残差的空间自相关性,分析地理加权机器学习模型在处理林木空间非线性关系方面的应用。结果表明:使用地理加权的模型,拟合效果明显优于普通最小二乘模型,其中地理加权神经网络模型的拟合效果最好(决定系数为0.980、均方根误差为0.169,平均绝对误差为0.119)。普通最小二乘模型和地理加权回归模型的残差,表现出明显的自相关性;地理加权随机森林模型和地理加权神经网络模型的残差,则表现为随机分布。3种使用地理加权的模型(地理加权回归模型、地理加权随机森林模型、地理加权神经网络模型)大幅度降低了模型的残差自相关性,减少了残差空间上聚集分布情况的出现。综合分析研究结果,与地理加权回归模型相比,地理加权随机森林模型和地理加权神经网络模型2种地理加权机器学习模型,能够更好地反映单木地上碳储量与各影响因素间的复杂关系,预测单木地上碳储量的效果更好,具有良好的应用潜力。

珠江三角洲城市公益林资源分布差异

为了探寻公益林森林生态系统有效管理的科学依据、生态文明建设与经济社会协调发展的经验,研究以广州市、深圳市、珠海市、佛山市、中山市、东莞市共6个珠三角城市为研究对象,基于2021年森林资源管理一张图中的公益林统计数据,从区域角度分析地区间、树种组成间的蓄积量构成差异和原因。结果表明,(1)珠三角六市的公益林面积共计100847.22 hm^(2),蓄积量7593435.84 m^(3),单位面积蓄积量为74.75 m^(3)·hm^(-2);(2)珠三角六市公益林面积、蓄积间差异较大,东莞市单位面积蓄积量达到88.59 m^(3)·hm^(-2),珠海市单位面积蓄积量最低,仅有54.40 m^(3)·hm^(-2),东莞市公益林的面积、蓄积量以及单位面积蓄积量均为六个市最高;(3)在公益林优势树种蓄积量方面,阔叶混交林面积和蓄积量均最高,速生相思单位面积蓄积量最高,达到121.11 m^(3)·hm^(-2),人工纯林表现出较高的生产力,以34%的公益林面积,提供了48%的蓄积量;(4)公益林蓄积与其立地质量、经营水平和混交林的树种组成等有关。结论指出,珠三角六市森林质量提升空间大,需优化公益林树种、林种结构,加强森林经营技术和模式研究,注重树种适应性与立地质量匹配,实现经济与生态文明协同发展。

基于盈余公告漂移的LGBM多因子量化策略

在资本市场波动加剧的时代,挖掘有效因子与市场信息,构建合适的投资组合策略,可以实现对风险的控制和获取稳定且持续的超额收益率.选取2018—2022年第1季度中国沪深两市A股上市股票的业绩报告作为研究对象,以公司盈余公告后的1~12周作为时间窗口,通过研究盈余公告后的股价漂移(post-earnings-announcement drift,PEAD)选取市场异象的代理变量预期外盈余因子与其他5个相关市场异象因子,并使用信息系数(information coefficient,IC)、信息比率(information ratio,IR)和双重排序法进行有效因子的筛选和检验.考虑到本次量化选股是低数据量、低频次、特征值高有效性的分类任务,采用基于轻量梯度提升树的多因子量化策略构建投资组合预测股票的收益率,并与传统量化策略(简单打分法、基于预期外盈余的单因子模型、IC值加权的多因子选股模型)、基于其他机器学习模型(支持向量回归(support vector regression,SVR)、人工神经网络(artificial neural network,ANN)与分布式梯度增强(extreme gradient boosting,XGBoost))的量化策略进行对比.实证结果表明,在基于A股市场第1季度PEAD效应的股票超额收益率预测中,轻量级梯度提升机(light gradient boosting machine,LGBM)机器学习多因子量化策略构建的投资组合在多空组合中实现的年均收益率达到21.633%,超过基准年化收益率20.184%.LGBM多因子量化策略构建的投资组合在A股市场表现优异,较其他量化策略有显著提升且更为稳定,可更好地控制组合风险并获取更高的超额收益.

湖北省森林资源蓄积量年度监测存在的问题及优化思路

结合湖北省森林资源监测发展历程,总结2013—2023年森林资源动态监测体系、蓄积量样地调查监测方法、监测技术、监测内容以及新技术、新设备应用等方面的经验。对不同时期调查数据进行对比分析,归纳不同阶段、不同调查方式蓄积量监测的区别以及监测体系存在的内容与指标单一,调查精度不高,基础数表不完备等问题。提出运用新思路、新技术、新设备来提升信息化程度,包括持续优化监测体系,利用雷达技术开展蓄积量反演,开展智能树种识别研究等蓄积量年度监测优化思路。

Dynamics of ecosystem carbon stocks during vegetation restoration on the Loess Plateau of China

In the last few decades, the Loess Plateau had experienced an extensive vegetation restoration to reduce soil erosion and to improve the degraded ecosystems. However, the dynamics of ecosystem carbon stocks with vegetation restoration in this region are poorly understood. This study examined the changes of carbon stocks in mineral soil （0-100 cm）, plant biomass and the ecosystem （plant and soil） following vegetation restoration with different models and ages. Our results indicated that cultivated land returned to native vegetation （natural restoration） or artificial forest increased ecosystem carbon sequestration. Tree plantation sequestered more carbon than natural vegetation succession over decades scale due to the rapid increase in biomass carbon pool. Restoration ages had different effects on the dynamics of biomass and soil carbon stocks. Biomass carbon stocks increased with vegetation restoration age, while the dynamics of soil carbon stocks were affected by sampling depth. Ecosystem carbon stocks consistently increased after tree plantation regardless of the soil depth; but an initial decrease and then increase trend was observed in natural restoration chronosequences with the soil sampling depth of 0-100 cm. Moreover, there was a time lag of about 15-30 years between biomass production and soil carbon sequestration in 0-100 cm, which indicated a long-term effect of vegetation restoration on deeper soil carbon sequestration.

Aboveground biomass and carbon stock in the largest sacred grove of Manipur,Northeast India

Aboveground biomass and carbon stock in the largest sacred grove of Manipur was estimated for trees with diameter [10 cm at 1.37 m height.The aboveground biomass,carbon stock,tree density and basal area of the sacred grove ranged from 962.94 to 1130.79 Mg ha;,481.47 to 565.40 Mg ha;C,1240 to 1320 stem ha;and79.43 to 90.64 m;ha;,respectively.Trees in diameter class of 30–40 cm contributed the highest proportion of aboveground biomass（22.50–33.73%）.The aboveground biomass and carbon stock in research area were higher than reported for many tropical and temperate forests,suggesting a role of spiritual forest conservation for carbon sink management.

一种基于决策树的用于构建量化策略的分类器

将技术指标引入决策树的构建,并结合Adaboost模型优化,以上证综指为例提出一种交叉验证的股票指数价格涨跌预测模型.基于预测模型构建对时间序列数据的量化择时系统,并评估其策略表现.实证结果表明,本文提出的预测模型精度较高,基于预测模型的量化择时系统有更好的表现,具有较优秀的市场状况识别状态和获得超额收益的能力.该结果为决策树在择时策略中的创新性运用提供参考,为技术指标的创新运用提供新的思路.

Two-Dimensional Rectangular Stock CuttingProblem and Solution Methods

Optimal layout of rectangular stock cutting is still in great demand from industry for diversified applications. This paper introduces four basic solution methods to the problem linear programming, dynamic programming, tree search and heuristic approach. A prototype of application software is developed to verify the pros and cons of various approaches

疏伐强度对红皮云杉人工林林木生长和林分蓄积的影响

以黑龙江省佳木斯市孟家岗林场红皮云杉中龄人工纯林为研究对象,2017年在6种疏伐强度下设立固定样地,连续3 a调查及计算不同疏伐强度处理后的林木生长情况和林分蓄积情况。结果表明,随着疏伐强度增大,树高和活枝下高呈先增后减的趋势,胸径逐渐增大,冠幅呈增大趋势;平均立木材积逐渐增大,单位面积蓄积量呈先增后减趋势,大径材比例、大径材平均立木材积和大径材单位面积蓄积量呈增大趋势。较大强度(50%疏伐强度)的疏伐更适于红皮云杉中龄人工林培育大径材,疏伐处理3 a(2020年生长季末)后,与对照相比,其胸径增长21.85%,东西冠幅和南北冠幅分别增长18.22%和17.18%,平均立木材积增长66.81%,大径材比例增加51.39%,大径材平均立木材积增长22.04%,均优于其余强度;综合3 a数据可知,其树高、冠幅、平均立木材积年增量更大,胸径和平均立木材积的年均增长量最大。通过分析不同疏伐强度处理后的林木生长差异,为建立适宜的红皮云杉林分密度调控技术提供理论依据,为培育红皮云杉大径材提供参考。

Response of plant,litter,and soil C:N:P stoichiometry to growth stages in Quercus secondary forests on the Loess Plateau,China

Ecological stoichiometry is an important indicator of biogeochemical cycles and nutrient limitations in terrestrial ecosystems.However,little is known about the response of ecological stoichiometry to plant growth.In this study,carbon(C),nitrogen(N),and phosphorus(P)concentrations were evaluated in plant tissues(trees,shrubs,and herbs),litter,and soil of young(≤40-year-old),middle-aged(41–60-year-old),near-mature(61–80-year-old),and mature(81–120-year-old)Quercus secondary forests on the Loess Plateau,China.Vegetation composition,plant biomass,and C stock were determined to illustrate their interaction with stoichiometry.Only tree biomass C signifi cantly increased with stand development.Leaf N and trunk P concentrationsgenerally increased,but branch P decreased with growth stage.Fine roots had the highest C and P concentrations at the middle-aged stage.In contrast,shrubs,herbs,litter,and soil C:N:P stoichiometry did not change signifi cantly during stand development.Leaf N and P were positively correlated with soil C,N,P,and their ratios.However,there was no signifi cant correlation between litter and leaves in terms of C:N:P stoichiometry.A redundancy analysis showed that soil N best explained leaf N and P variance,and tree biomass and C stock were related to biotic factors such as tree age and shrub biomass.Hierarchical partitioning analysis indicated that,compared with soil or litter variables,stand age only accounted for a relatively small proportion of leaf C,N,and P variation.Thus,secondary Quercus ecosystems might have inherent ability to maintain sensitive responses of metabolically active organs to environmental factors during stand aging.The results of this work help to elucidate the biogeochemical cycling of secondary forest ecosystems in tree development,provide novel insights into the adaptation strategies of plants in diff erent organs and growth stages,and could be used to guide fertilization programs and optimize forest structure.

不同经营方式对华北落叶松人工林林分生长的短期影响

为了研究不同森林经营方式对华北落叶松人工林林分生长的短期影响,本研究选取内蒙古赤峰市旺业甸林场华北落叶松人工林为对象,设置了落叶松中龄林近自然经营、中龄林常规经营、中龄林未经营、落叶松近熟林近自然经营、近熟林常规经营、近熟林未经营两类树种的3种经营措施,调查了旺业甸林场2013、2016、2019年三年树高、胸径、枝下高等,对比分析了不同经营模式下近自然经营、常规经营、未经营样地林分水平结构变化,林分蓄积量,胸径、胸高断面面积和单木材积生长量,探究了不同经营方式下林分生长动态。结果表明:不同经营方式下径阶树木比例增长量落叶松中龄林和近熟林均为近自然经营(5.85%、36.82%)最大;不同经营方式下6 a间总体蓄积量表现为,落叶松中龄林:未经营[13.74 m^(3)/(hm^(2)·a)]>近自然经营[10.73 m^(3)/(hm^(2)·a)]>常规经营[10.18 m^(3)/(hm^(2)·a)];落叶松近熟林表现为近自然经营最大;落叶松人工林6a间不同经营方式下林木单木生长量变呈现出近自然经营最大。

马尾松林择伐补植阔叶树后生长及其碳储量碳汇分析

千岛湖区马尾松林择伐后补植的木荷、枫香、深山含笑等阔叶树种长势良好,补植14年后,胸径年均生长量达0.50 cm以上,树高年均生长量达0.55 m以上,与原来的植被形成较为稳定的群落结构。第14年新增CO_(2)固定量39.5836~95.7701 t/hm^(2),平均68.5262 t/hm^(2)。利用碳市场CEA价格法、造林成本法、碳税率法计算了其每公顷平均碳汇价值,分别为3974.52、18728.21、82231.44元。结果表明:针阔混交复层高效碳汇森林定向抚育具有明显的碳汇增益潜力和效益,可为马尾松为主的次生林特别是松材线虫病迹地更新提供参考借鉴。

民勤县防沙治沙造林工程主要树种的选择与规划

防沙治沙造林工程是治理荒漠化和沙漠化的重要手段,而主要树种的选择和种植规划则是工程能否顺利进行的关键因素之一。阐述了我国西北民勤县防沙治沙造林工程主要树种的选择标准,探讨了如何科学选择和合理布局主要树种,提高造林效益,达到最佳的防沙治沙效果,分析了如何在树种选择和种植规划过程中结合实际情况和科学技术手段优化防沙治沙造林工程,为相关行业提供参考。

Biomass Estimation Models for Cocoa (Theobroma cacao) Plantations in Ghana, West Africa

The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.

机器学习方法在舟山渔场主要经济蟹类生物量估算中的应用

扫海面积法因其操作简单、计算方便,被广泛应用于渔业生物量评估工作中。但该方法需假设资源均匀分布,若要提高生物量评估的准确性,则须增加站位数量,进而增加经费预算。本研究基于2006年8月和2007年1月、5月、11月在舟山渔场海域开展渔业资源底拖网调查所获得的多种经济蟹类数据资料,模拟分析扫海面积法与机器学习模型(随机森林(RF)、梯度提升回归树模型(GBRT)、极限梯度提升(XGBoost))对舟山渔场海域三疣梭子蟹(Portunus trituberculatus)、双斑鲟(Charybdis bimaculata)、日本鲟(Charybdis japonica)、细点圆趾蟹(Ovalipes punctatus)4种主要经济蟹类生物量的对比评估效果。结果显示,随着投入站点数目的减少,在数据不集中、波动较大的秋、冬季节XGBoost方法对生物量的评估效果明显优于扫海面积法,误差降低7.49%~21.34%;而在较为均匀的春、夏两季,扫海面积法与机器学习方法两者结果的差异不显著(P<0.05)。本研究以几种经济蟹类为例,探索使用机器学习方法评估其生物量,达到了提高评估准确性并节省资源调查成本的效果,可在其他渔业资源种类生物量评估中推广应用。

提高碳汇潜力:量化树种和造林模式对碳储量的影响

全球气候变化背景下,造林再造林固定的碳可以抵消温室气体减限排量。通过造林再造林增加森林面积可以增加林业碳汇,在土地面积有限的情况下,提高造林质量——在有限的造林面积上固定更多的碳是十分必要的。树种和造林模式的选择是增加森林生态系统碳汇的重要管理决策。文章综述了树种和造林模式对生态系统的碳储量的影响。树种从生物量的积累,凋落物和土壤碳储存,以及木材密度、碳贮存量等几个方面探讨其对生态系统碳库的影响。混交林能充分利用立地条件、改善树木营养状况,并且可以减少病虫害和森林火灾。同时分析了我国在森林经营方面存在的问题和改善途径,以期为该领域的研究提供参考。

林业应用稀土的技术与效果

稀土在提高林木种子发芽率，促进杉木（Ｃｕｎｎｉｎｇｈａｍｉａｌａｎｃｅｏｌａｔａ（Ｌａｍｂ．）Ｈｏｏｋ．）、木荷（ＳｃｈｉｍａｓｕｎｅｒｂａＧａｒｄｎ．ｅｔＣｈａｍｐ）、板栗（ＣａｓｔａｎｅａｍｏｌｌｉｓｓｉｍａＢｌｕｍｅ）、泡桐（Ｐａｕｌｏｗｎｉａｓｐ）、杨树（Ｐｏｐｕｌｕｓｓｐ）等的苗期生长并提高苗木质量，提高湿地松（ＰｉｎｕｓｅｌｌｉｏｔｔｉｉＥｎｇｅｌｍ）、杉木种子园的种子产量和质量，提高核桃（ＪｕｇｌａｎｓｒｅｇｉａＬ．）、枣（ＺｉｚｙｐｈｕｓｊｕｊｕｂａＭｉｌｌ）、板栗、苹果（ＭａｌｕｓｐｕｍｉｌａＭｉｌｌ）、梨（ＰｙｒｕｓｂｒｅｔｓｃｈｎｅｉｄｅｒｉＲｅｈｄ）、山楂（ＣｒａｔａｅｇｕｓｐｉｎｕｓｔｉｆｉｄａＢｇｅ）、柿（ＤｉｏｓｐｙｒｏｓｋａｋｉＬ．）、杏（ＰｒｕｎｕｓａｒｍｅｎｉａｃａＬ．）等果树的座果率和产量并改善果实品质等方面有明显效果。同时，稀土对林木苗期和经济林木花果期的生理有促进作用。稀土能促进林木叶绿素形成，提高光合作用强度，促进根系对矿质元素的吸收，增加干物质积累；稀土还影响种实中有机酸、蛋白质、脂肪、糖、Ｖｃ等的含量．稀土林用技术已用于生产实践。