In vitro regeneration of apomictic bluestem grasses

Explants from immature inflorescences of four genotypes of Old World bluestem grasses, (Bothriochloa spp.), produced callus tissue on Linsmaier and Skoog (RM) and 1/2 Murashige and Skoog (1/2 MS) media containing high levels of growth regulators. Callus masses were composed of two distinct tissue types, one a compact, white, embryogenic portion (E calli), the other soft, translucent, gelatinous and nonembryogenic (NE calli). When transferred to medium with a reduced level of 2,4-D, and/or supplemented with zeatin, E callus underwent further organization culminating in shoot production. Light and scanning electron microscopy confirmed the embryogenic pathway of differentiation. Genotype significantly affected callus induction frequency and the number of plants regenerated. The RM medium induced more explants to initiate callus compared to the 1/2 MS medium. Age of the inflorescence explant, as indicated by size, was critical for callus induction. Inflorescences with racemes 8 mm in length were superior to older ones. Five-hundred-twenty-two plantlets were regenerated and grown to maturity.     

用杀虫双大粒剂防治水稻二化螟和三化螟的研究

本文报告一种防治水稻螟虫的杀虫双新剂型和使用效果.含有效成份5%的杀虫双大粒剂,每公斤含2000粒左右,在每亩1—1.25公斤的用量下,药效显著优于六六六、呋喃丹及杀虫脒等残留和高毒性农药.处理一亩田只需数分钟.在七个县和四个农场共266440亩稻田的示范试验中,防治效果达84.5—100%.杀虫双在田水中扩散迅速,24小时内即可扩散分布到全田.持效期较长,可达两周之久.但在蝗虫已蛀入稻茎后施用大粒剂,有效施药期只有3—4天.本文对杀虫双大粒剂的使用技术进行了经济效益、社会效益和生态效益方面的评价.     

Epicuticular wax of Poa ampla leaves

Leaf wax of a glaucous variety of Poa ampla contains hydrocarbons (5%, C₂₃–C₃₅), esters (9%, C₃₆–C₅₆), free acids (3%, C₁₆–C₃₄), free alcohols (6%, mainly C₂₆); hentriacontane-14,16-dione (14%), 5-oxohentriacontane-14,16-dione (1%); hydroxy β-diketones (56%) and unidentified material (6%). The hydroxy β-diketones, which are more abundant in this wax than in others, were shown by ¹³C NMR to consist of 4-hydroxy (15%), 5-hydroxy (70%) and 6-hydroxy (15%) hentriacontane-14,16-diones.     

Passive restoration of vegetation and biological soil crusts following 80 years of exclusion from grazing across the Great Basin

Restoration targets for biological soil crusts are largely unknown. We surveyed seven 80‐year‐old grazing exclosures across northern Nevada for biocrusts to quantify reference conditions at relatively undisturbed sites. Exclosures were associated with the following plant communities: Wyoming big sagebrush, black sagebrush, and areas co‐dominated by winterfat and Wyoming big sagebrush. Cover of biocrusts and shrubs were generally higher than other plant groups at these sites, regardless of being inside or outside of the exclosures, suggesting these groups make up most of the native flora across the region. Important in forming soil structure, cyanobacteria of the order Oscillatoriales were less abundant and diverse in black sagebrush communities. Grazing had a negative effect on the abundance of Oscillatoriales but not the number of algal taxa, including cyanobacteria. Abundance of light algal crusts were not influenced by plant community or grazing. Dark algal crusts were generally less abundant on grazed sites. Influences of plant community and grazing were most apparent when accounting for reproductive rates of lichens and mosses based on establishment mechanisms. Abundance of shrubs, perennial grasses, Oscillatoriales, fast reproducing biocrusts and the number of algal and cyanobacterial taxa, varied by plant community, suggesting that restoration should be plant community specific. We demonstrate the affinity of rapidly reproducing biocrusts for winterfat‐Wyoming big sagebrush co‐dominated plant communities, regardless of grazing pressure. Across sites, the effects of grazing were most evident on the abundance of Oscillatoriales and slowly reproducing biocrusts following 80 years of cessation from grazing.     

基于植保大数据的病虫害移动智能采集新设备

为提高农作物重大病虫害发生信息自动化、智能化采集能力,全面提升监测预警水平,笔者基于大数据、人工智能和深度学习技术,研发了一款农作物病虫害移动智能采集设备——智宝,主要实现了3个方面的功能:一是病虫害发生信息自动采集上报.通过该产品进行人工拍照,可实现对田间农作物重大病虫害发生图像、发生位置、发生数量、微环境因子等数据的实时采集和上报.二是自动识别计数.基于植保大数据与人工智能技术,通过构建病虫害自动识别系统,可实现重大病虫害精准识别与分析,只要拍摄照片,即可快速、精确地识别病虫害种类,并自动计数、上报到指定的测报系统.三是自动分析判别分级.针对拍摄采集上报的重大病虫害发生信息,系统可在自动识别和计数的基础上,进一步对病虫害发生严重程度进行智能判别分级,甚至根据相关预测模型,对病虫害的发生趋势进行辅助分析预测,提出预测建议.通过2016—2019年组织多地植保机构进行试验改进,该技术产品日趋成熟,有望在未来的农作物病虫害发生信息采集和预测预报工作中推广使用.     

Anthropogenic and Natural Disturbance Differentially Affect Sagebrush Bird Habitat Use

North American sagebrush (Artemisia spp.)-obligate birds are experiencing steep population declines due in part to increased disturbance, mainly human-caused, across their range. At the eastern edge of the sagebrush steppe, this issue may potentially be exacerbated because of natural disturbance by black-tailed prairie dogs (Cynomys ludovicianus). Our goal was to compare local and landscape models of habitat use by greater sage-grouse (Centrocercus urophasianus), Brewer's sparrow (Spizella breweri), and sage thrasher (Oreoscoptes montanus) with models including effects of natural (i.e., prairie dog) and anthropogenic disturbance. We used a combination of field data collection, and state and national datasets for the Thunder Basin National Grassland, eastern Wyoming, USA, to understand the factors that influence lek attendance by sage-grouse and habitat use by 2 passerines in this system. For all 3 species, models including big sagebrush (Artemisia tridentata) cover at local and landscape scales were the most competitive among univariate models, supporting the paradigm that sagebrush is key for these species. Models including anthropogenic disturbance (well density, road density) explained more variation than models of prairie dog disturbance alone for 2 of the 3 species, but long-term disturbance by prairie dogs did reduce abundance of Brewer's sparrows. Although long-term prairie dog disturbance has the potential to reduce sagebrush cover for sagebrush-obligate birds, such events are likely rare because outbreaks of plague (Yersina pestis) and lethal control on borders with private land reduce prairie dog disturbance. Conversely, anthropogenic disturbance is slated to increase in this system, suggesting potentially accelerated declines for sagebrush birds into the future. © 2020 The Wildlife Society.     

Dynamic occupancy models for analyzing species' range dynamics across large geographic scales

Large‐scale biodiversity data are needed to predict species' responses to global change and to address basic questions in macroecology. While such data are increasingly becoming available, their analysis is challenging because of the typically large heterogeneity in spatial sampling intensity and the need to account for observation processes. Two further challenges are accounting for spatial effects that are not explained by covariates, and drawing inference on dynamics at these large spatial scales. We developed dynamic occupancy models to analyze large‐scale atlas data. In addition to occupancy, these models estimate local colonization and persistence probabilities. We accounted for spatial autocorrelation using conditional autoregressive models and autologistic models. We fitted the models to detection/nondetection data collected on a quarter‐degree grid across southern Africa during two atlas projects, using the hadeda ibis (Bostrychia hagedash) as an example. The model accurately reproduced the range expansion between the first (SABAP1: 1987–1992) and second (SABAP2: 2007–2012) Southern African Bird Atlas Project into the drier parts of interior South Africa. Grid cells occupied during SABAP1 generally remained occupied, but colonization of unoccupied grid cells was strongly dependent on the number of occupied grid cells in the neighborhood. The detection probability strongly varied across space due to variation in effort, observer identity, seasonality, and unexplained spatial effects. We present a flexible hierarchical approach for analyzing grid‐based atlas data using dynamical occupancy models. Our model is similar to a species' distribution model obtained using generalized additive models but has a number of advantages. Our model accounts for the heterogeneous sampling process, spatial correlation, and perhaps most importantly, allows us to examine dynamic aspects of species ranges.     

Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms,and cancer drug design using big database mining and genome-wide next-generation sequencing data

Recent studies have demonstrated that cell cycle plays a central role in development and carcinogenesis. Thus, the use of big databases and genome-wide high-throughput data to unravel the genetic and epigenetic mechanisms underlying cell cycle progression in stem cells and cancer cells is a matter of considerable interest.

Real genetic-and-epigenetic cell cycle networks (GECNs) of embryonic stem cells (ESCs) and HeLa cancer cells were constructed by applying system modeling, system identification, and big database mining to genome-wide next-generation sequencing data. Real GECNs were then reduced to core GECNs of HeLa cells and ESCs by applying principal genome-wide network projection. In this study, we investigated potential carcinogenic and stemness mechanisms for systems cancer drug design by identifying common core and specific GECNs between HeLa cells and ESCs. Integrating drug database information with the specific GECNs of HeLa cells could lead to identification of multiple drugs for cervical cancer treatment with minimal side-effects on the genes in the common core. We found that dysregulation of miR-29C, miR-34A, miR-98, and miR-215; and methylation of ANKRD1, ARID5B, CDCA2, PIF1, STAMBPL1, TROAP, ZNF165, and HIST1H2AJ in HeLa cells could result in cell proliferation and anti-apoptosis through NFκB, TGF-β, and PI3K pathways. We also identified 3 drugs, methotrexate, quercetin, and mimosine, which repressed the activated cell cycle genes, ARID5B, STK17B, and CCL2, in HeLa cells with minimal side-effects.