Biochemical characteristics of urban maple trees

The study, which covers the period between 2014 and 2018, was carried out in the city of Naberezhnye Chelny, Republic of Tatarstan, Russia. The aim of the study was to examine the biochemical response of maple trees growing in the anthropogenic environments. Leaf samples from 600 trees (Acer platanoides L. and Acer negundo L.) were collected at monthly intervals from June through August. Sampling was performed early in the morning (11 a.m.) in the middle of the month. The study offers statistical data on the tannin content, determined via permanganometry; the ascorbic acid concentration, found via titration with 2.6-dichlorophenolindophenol; the ascorbate oxidase activity determined by absorbance at 265 nm; and the polyphenol oxidase activity, found by the spectrophotometric method. Relatively higher ascorbate oxidase activity was detected in August among ash-leaved Acer platanoides L. and Acer negundo L. in areas with strong anthropogenic impact. Due to increased air pollution, maple trees were found to exhibit an increase of polyphenol oxidase activities. The condensed tannin content in Norway maple trees dropped over time: by 1.24 in July (avenue); by 0.94 (buffer area) and 0.76 (avenue) in August. The condensed tannin content in the ash-leaved maple trees also decreased: by 0.69 (buffer area) and 0.22 (avenue) in July; by 0.37 (buffer area) and 0.61(avenue) in August.     

Species richness,abundance and diversity of ichneumonid wasps in Japanese beech forests impacted by sika deer and sawfly herbivory

We investigated the community structure of ichneumonid wasps inhabiting beech forests at six sites in the Tanzawa Mountains of Japan under different magnitudes of impact by sika deer Cervus nippon and beech sawfly Fagineura crenativora on vegetation. Using yellow flight-interception traps, we captured 2,528 ichneumonid wasps representing 367 species in 23 subfamilies. The number of species at each site ranged from 77 to 136 and approximately 80% of these were low-density species (i.e. only one to two individuals captured per site). The number of individuals at each site ranged from 248 to 897, and the percentage of the beech sawfly parasitoids varied widely from 1% to 57%. The numbers of species in parasitoid groups categorized according to their hosts, that is, sawfly (not including the beech sawfly), Lepidoptera, woodborer, fungivore or the others, did not greatly differ among the study sites. Parasitoids attacking herbivorous insects exceeded others in species richness and abundance at all sites. Six sites were classified into four groups in terms of abundance of the host groups when excluding the parasitoids of the beech sawfly, but into only two groups when including these parasitoids. Species diversity and evenness were the highest at the least impacted site even if the beech sawfly parasitoids were excluded from calculation. We suggested some environmental factors, such as groundcover vegetation, abundance of the beech sawfly and structure and age of forest stands, that could have affected the community structure of ichneumonid wasps in the beech forests.     

Life cycle of an endangered riffle beetle,Leptelmis gracilis Sharp (Coleoptera: Elmidae), in the Hiikawa River system,Shimane prefecture,Japan

We studied the life cycle of the riffle beetle Leptelmis gracilis Sharp, 1888 from a population located in a river stream with lotic environments. Samples were collected monthly, between September 2018 and August 2019, from a tributary of the Hiikawa River in Izumo city, Shimane Prefecture, Honshu, Japan. Larvae were separated into five distinct groups based on size. The first and last instar larval sizes were identified through rearing methods. From these results, we determined that the larval stage of this species consists of five instars. From the monthly evaluations, the number of individuals corresponding to each instar period suggested that last-instar larvae were dominant in May and that new adults emerged from July to August. Landing and pupation were estimated to occur from May to June. Monthly observations revealed that mature eggs were present in the female abdomen from April to June, as well as from August to September. It is, therefore, predicted that overwintering adults mainly oviposit from spring to early summer, while new adults oviposit from late summer to early autumn.     

Quantified 123I-Thyroid Scan based classification of hyperthyroidism

The original thyroid scan (TS) was widely used to identify typical imaging patterns, suggesting the widely accepted main following clinical diagnoses: Grave's disease, Toxic adenoma, [hetero]-nodular goiters and thyroiditis. With the diffusion of sensitive TSH assays, considerable advances in the comprehension of the molecular mechanisms of hormonosynthesis, and new quantification possibilities especially using ¹²³I, the TS is a textbook of molecular imaging. The image can be finely quantified with, not only as regards the Uptake (¹²³IUp) and related parameters but also, the quantification of the spatial targeting leading to a Spatial Target Index (STI). Using this new molecular ¹²³I-TS, TSH values, and when required, correlation to Multiparametric Ultrasounds (MPUS), we generated a basic classification system of hyperthyroidism, with well-defined indexed criteria (C11-1 to C17-3), that allows reporting 24 distinct etiologies. Selected criteria involve TS and contrast patterns, precocious ¹²³IUp (p¹²³IUp), maximal TSH-dependent physiological Uptake, lobar concentration, Uptake and concentration ratios, STI, ^99mTc-MIBI TS and correlative MPUS. This approach allows to identify 4 subtypes of Graves’ disease, including hyperplastic, nodular and common GD variants entangled with Hashimoto's struma, 4 subtypes of Thyroid Functional Autonomy, including Disseminated Functional Autonomy, that cannot be diagnosed with other conventional procedures. Criteria C14-1 to C17-3 report on hyperthyroidism and iodine overload, factitia, main thyroiditis presentations and rare central or tumoral etiologies of hyperthyroidism. This classification, based on ¹²³I-TS molecular imaging, leads to unprecedented diagnostic finesse and paves the way for a personalized theranostic approach in thyroid pathology. Further development towards artificial intelligence networks is under study.     

中国植被分类系统修订方案

为了推动《中国植被志》研编工作, 该文回顾了中国植被分类系统的发展过程和主要阶段性成果, 提出了作为《中国植被志》研编技术框架组成部分的中国植被分类系统修订方案, 对各植被型组及各植被型进行了简单定义和描述, 并针对中国植被分类系统若干问题, 特别就中国植被分类系统总体框架、混交林的界定以及土壤在植被分类中的重要性等问题进行了讨论。1960年侯学煜在《中国的植被》中首次提出了中国植被分类的原则和系统, 1980年出版的《中国植被》制定了分类等级和划分依据等更加完善的系统, 之后《中国植被及其地理格局——中华人民共和国1:1 000 000植被图说明书》和《中国植物区系与植被地理》以及很多省区的植被专著对该系统进行过修订。2017年宋永昌在《植被生态学》中提出了一个分类等级单位调整的方案。本次提出的中国植被分类系统修订方案基本沿用《中国植被》的植被分类原则、分类单位及系统, 采用“植物群落学-生态学”分类原则, 主要以植物群落特征及其与环境的关系作为分类依据, 包含三级主要分类单位, 即植被型(高级单位)、群系(中级单位)和群丛(低级单位); 在三个主要分类单位之上分别增加辅助单位植被型组、群系组和群丛组, 在植被型和群系之下主要根据群落的生态差异和实际需要可再增加植被亚型或亚群系。修订方案包含了森林、灌丛、草本植被(草地)、荒漠、高山冻原与稀疏植被、沼泽与水生植被(湿地)、农业植被、城市植被和无植被地段9个植被型组, 划分为48个植被型(含30个自然植被型、12个农业植被型、5个城市植被型和无植被地段)。自然植被中有23个植被型进一步划分出了81个植被亚型。     

地被植物对广东常绿阔叶林土壤养分的指示作用

为了解地被植物群落对土壤养分的响应和指示作用,利用指示种分析(ISA)法研究了广东常绿阔叶林地被植物与土壤养分的关系。结果表明,速效氮(AN)、速效磷(AP)、速效钾(AK)和有机质(OM)的综合作用对地被植物分布有显著影响(P0.05),且以速效磷有机质速效钾速效氮。地被植物的组成与分布在不同AP和OM梯度中均有显著差异(P 0.05),但在不同AK和AN梯度中差异不显著。土壤AN≤270 mg/kg的指示种是广东蛇葡萄(Ampelopsis cantoniensis)和油点草(Tricyrtis macropoda),270～360 mg/kg的指示种是狗骨柴(Tricalysia dubia);AP≤2 mg/kg的指示种是华山姜(Alpinia chinensis);AK≤100mg/kg的指示种是赤楠蒲桃(Syzygiumbuxifolium),AK为100～150mg/kg的指示种是十字苔草(Carexcruciate),AK150 mg/kg的指示种是金钗凤尾蕨(Pterisfauriei);OM 0.8%的指示种是箬竹(Indocalamustessellatus),OM≤0.6%的指示种是华山姜(Alpinia chinensis)和蔓胡颓子(Elaeagnus glabra),OM为0.6%～0.8%的指示种是豆腐柴(Premna microphlla)。利用有效的地被植物调查方式来监测森林的土壤状况为森林经营管理及土壤健康评价带来方便。地被植物指示种对土壤养分的响应不但能为研究地的立地条件提供理论支撑,还能为该物种的人工栽培提供理论依据,这对于生物多样性保育、生境恢复的引种栽培有重要意义。     

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.