Effective aerial monitoring of cyanobacterial harmful algal blooms is dependent on understanding cellular migration

Cyanobacterial harmful algal blooms (CHABs) degrade water quality and may produce toxins. The distribution of CHABs can change rapidly due to variations in population dynamics and environmental conditions. Biological and ecological aspects of CHABs were studied in order to better understand CHABs dynamics. Field experiments were conducted near Hartington, Ontario, Canada in ponds dominated by Microcystis aeruginosa and CHABs floating experiments were conducted at Lake Taihu during the summers of 2015 and 2016. Single colonies composed of hundreds to thousands of cells with an average median of 0.2–0.5 mm in diameter were the basic form assumed by the Microcystis, and this remained the same throughout the growing season. Thorough mixing of the water column followed by calm conditions resulted in over 90% of the cyanobacteria floating after 1 h. Multiple colonies floated on the water surface in four types of assemblages: aggregates, ribbons, patches, and mats. It is the mats that are conventionally considered the blooming stage of cyanobacteria.Presence of CHABs on open water surfaces also depends on environmental influences such as direct and indirect wind effects. For example, field tests revealed that the surface coverage of CHABs can be reduced to half within an hour at wind speeds of 0.5 m/s.Because our findings indicated that blooming involves surface display of cyanobacteria essentially presenting as a two-dimensional plane under defined conditions, the use of surface imagery to quantify CHABs was justified. This is particularly important in light of the fact that traditional detection methods do not provide accurate distribution information. Nor do they portray CHABs events in a real-time manner due to limitations in on-demand surveillance and delays between sample time and analyzed results. Therefore, a new CHAB detection method using small unmanned aerial systems with consumer-grade cameras was developed at a maximum detection altitude of 80 m. When cyanobacteria were floating on the surface, CHABs detection through RGB band cameras and spectral enhancement techniques was efficient and accurate. Small unmanned aerial systems were capable of providing coverage up to 1 km² per mission and the short intervals between sampling and results (approx. 2 h) allowed for the rapid analysis of data and for implementing follow-up monitoring or treatments. This method is very cost-effective at an estimate of as low as $100 CAD per mission with an average cyanobacterial detection accuracy of 86%. Thus, it is a good candidate method to fill the urgent need for CHABs detection, providing cost effective, rapid, and accurate information to improve risk management at a local level as well as to help quickly allocate resources for purposes of mitigation.     

New pollen classification of Chenopodiaceae for exploring and tracing desert vegetation evolution in eastern arid central Asia

Members of the Chenopodiaceae are the most dominant elements in the central Asian desert. The different genera and species within this family are common in desert vegetation types. Should it prove possible to link pollen types in this family to specific desert vegetation, it would be feasible to trace vegetation successions in the geological past. Nevertheless, the morphological similarity of pollen grains in the Chenopodiaceae rarely permits identification at the generic level. Although some pollen classifications of Chenopodiaceae have been proposed, none of them tried to link pollen types to specific desert vegetation types in order to explore their ecological significance. Based on the pollen morphological characters of 13 genera and 24 species within the Chenopodiaceae of eastern central Asia, we provide a new pollen classification of this family with six pollen types and link them to those plant communities dominated by Chenopodiaceae, for example, temperate dwarf semi‐arboreal desert (Haloxylon type), temperate succulent halophytic dwarf semi‐shrubby desert (Suaeda, Kalidium, and Atriplex types), temperate annual graminoid desert (Kalidium type), temperate semi‐shrubby and dwarf semi‐shrubby desert (Kalidium, Iljini, and Haloxylon types), and alpine cushion dwarf semi‐shrubby desert (Krascheninnikovia type). These findings represent a new approach for detecting specific desert vegetation types and deciphering ecosystem evolution in eastern central Asia.     

Generalized and species-specific prediction models for aboveground biomass in semi-steppe rangelands

Aims The accurate estimation of aboveground biomass in vegetation is critical for global carbon accounting. Regression models provide an easy estimation of aboveground biomass at large spatial and temporal scales. Yet, only few prediction models are available for aboveground biomass in rangelands, as compared with forests. In addition to the development of prediction models, we tested whether such prediction models vary with plant growth forms and life spans, and with the inclusion of site and/or quadrat-specific factors.     

Comparison of leaf area index inversion for grassland vegetation through remotely sensed spectra by unmanned aerial vehicle and field-based spectroradiometer

Aims Remote sensing technology has been proved useful in mapping grassland vegetation properties. Spectral features of vegetation cover can be recorded by optical sensors on board of different platforms. With increasing popularity of applying unmanned aerial vehicle (UAV) to mapping plant cover, the study aims to investigate the possible applications and potential issues related to mapping leaf area index (LAI) through integration of remote sensing imagery collected by multiple sensors.     

An evaluation of sequencing coverage and genotyping strategies to assess neutral and adaptive diversity

Whole genome sequences (WGS) greatly increase our ability to precisely infer population genetic parameters, demographic processes, and selection signatures. However, WGS may still be not affordable for a representative number of individuals/populations. In this context, our goal was to assess the efficiency of several SNP genotyping strategies by testing their ability to accurately estimate parameters describing neutral diversity and to detect signatures of selection. We analysed 110 WGS at 12× coverage for four different species, i.e., sheep, goats and their wild counterparts. From these data we generated 946 data sets corresponding to random panels of 1K to 5M variants, commercial SNP chips and exome capture, for sample sizes of five to 48 individuals. We also extracted low‐coverage genome resequencing of 1×, 2× and 5× by randomly subsampling reads from the 12× resequencing data. Globally, 5K to 10K random variants were enough for an accurate estimation of genome diversity. Conversely, commercial panels and exome capture displayed strong ascertainment biases. Besides the characterization of neutral diversity, the detection of the signature of selection and the accurate estimation of linkage disequilibrium (LD) required high‐density panels of at least 1M variants. Finally, genotype likelihoods increased the quality of variant calling from low coverage resequencing but proportions of incorrect genotypes remained substantial, especially for heterozygote sites. Whole genome resequencing coverage of at least 5× appeared to be necessary for accurate assessment of genomic variations. These results have implications for studies seeking to deploy low‐density SNP collections or genome scans across genetically diverse populations/species showing similar genetic characteristics and patterns of LD decay for a wide variety of purposes.     

Fast protein sequencing of monoclonal antibody by real-time digestion on emitter during nanoelectrospray

Growth in the pharmaceutical industry has led to an increasing demand for rapid characterization of therapeutic monoclonal antibodies. The current methods for antibody sequence confirmation (e.g., N-terminal Edman sequencing and traditional peptide mapping methods) are not sufficient; thus, we developed a fast method for sequencing recombinant monoclonal antibodies using a novel digestion-on-emitter technology. Using this method, a monoclonal antibody can be denatured, reduced, digested, and sequenced in less than an hour. High throughput and satisfactory protein sequence coverage were achieved by using a non-specific protease from Aspergillus saitoi, protease XIII, to digest the denatured and reduced monoclonal antibody on an electrospray emitter, while electrospray high voltage was applied to the digestion mixture through the emitter. Tandem mass spectrometry data was acquired over the course of enzyme digestion, generating similar information compared to standard peptide mapping experiments in much less time. We demonstrated that this fast protein sequencing method provided sufficient sequence information for bovine serum albumin and two commercially available monoclonal antibodies, mouse IgG1 MOPC21 and humanized IgG1 NISTmAb. For two monoclonal antibodies, we obtained sequence coverage of 90.5–95.1% for the heavy chains and 98.6–99.1% for the light chains. We found that on-emitter digestion by protease XIII generated peptides of various lengths during the digestion process, which was critical for achieving sufficient sequence coverage. Moreover, we discovered that the enzyme-to-substrate ratio was an important parameter that affects protein sequence coverage. Due to its highly automatable and efficient design, our method offers a major advantage over N-terminal Edman sequencing and traditional peptide mapping methods in the identification of protein sequence, and is capable of meeting an ever-increasing demand for monoclonal antibody sequence confirmation in the biopharmaceutical industry.     

基于地理探测器的岷江中下游地区植被NPP时空格局演变及其驱动力研究

植被净初级生产力作为反映植被生态系统对气候变化响应的重要指标,是长期以来备受世界各国关注的焦点问题。论文以岷江中下游地区为研究区域,基于2000—2015年MODIS NPP数据,结合同年期海拔、气温、降水、土地利用类型等,运用地理探测器等模型方法,诊断植被NPP分布的主要驱动力,并揭示了不同时段的驱动力决定力的变化。结果表明:(1)2000—2015年岷江中下游植被NPP平均值为513.93gC/m~2;植被年均NPP最大值出现在2000年石棉县北部硗碛藏族乡的林地分布区,为1876gC/m~2,最小值出现在2005年五通桥区中部竹根镇的平原旱地分布区,最小值为26.98gC/m~2;植被NPP具有较强的时空分异性,NPP总量变化除了受NPP强度影响外,植被覆盖总面积是其另外主要的影响因素。(2)影响植被NPP分布的主导因素包括气温、海拔、土地利用等,各因素对NPP分布的决定力存在明显差异。(3)不同时间植被NPP空间分布的驱动力存在明显差异,主要表现在其变化受人类扰动的影响越来越强烈。刻画岷江中下游植被NPP时空演变,并揭示其主要驱动力,可为研究区生态安全预警和生态补偿提供数据支撑和辅助决策。     

2002-2016年华北平原植被生长状况及水文要素时空特征分析

基于MODIS增强型植被指数（EVI）资料,结合降水、GRACE重力卫星水储量（TWS）、地下水、土壤水等资料,分析华北平原植被2002-2016年间的生长状况及各水文要素时空分布特征。研究结果表明：（1）2002-2016年间华北平原植被呈好转趋势,降水、水储量、土壤水、地下水等水文要素值呈减少趋势。（2）黄淮平原区植被以农作物为主,植被覆盖度呈增加趋势,而降水、水储量、地下水、土壤水均呈减少趋势,超采地下水灌溉农作物是短期内保障粮食安全的重要措施。（3）燕山-太行山山麓平原区、冀鲁豫低洼平原区的城乡居民用地区域植被覆盖显著减少,而降水增多,水储量、土壤水、地下水减少,人类活动对植被和水文要素贡献量大。（4）山东丘陵农林区分布着林地和草地,这些区域生长季的植被指数呈减少趋势,与降水量减少呈正相关关系。在气候变化和人类活动影响的大背景下,探讨不同生态环境的植被生长特征,清楚植被对水文变化的响应机理,可以消除影响植被生长的不利因素,为制定合理用水制度提供理论依据。     

植被恢复模式对石漠化生态系统碳储量的影响

为揭示石漠化生态系统碳储量对植被恢复模式的响应,在广西天等县中度石漠化山地,研究了吊丝竹纯林(Dendrocalamus minorD)、任豆纯林(Zenia insignis Z)、任豆、蚬木(Buerretiodendron hsienmu)和顶果木(Acrocarpus fraxinifolius)混交林(mixed plantation M),以及相应同龄封育林(D_(CK)、Z_(CK)、M_(CK))的碳储量。结果表明:人工林碳储量显著高于相应同龄封育林的碳储量,D、Z、M人工林碳储量分别为67.75、66.56、121.20 t/hm~2,而D_(CK)、Z_(CK)、M_(CK)封育林仅为49.75、52.89、60.86 t/hm~2。碳储量在乔木层、地被物层、土壤层分配排序因生态系统类型而异,如M:乔木层土壤层地被物层;D和Z:土壤层乔木层地被物层;D_(CK)、Z_(CK)和M_(CK):土壤层地被物层乔木层。此外,M、D、Z乔木层年平均碳储量差异显著,而封育林尚未形成乔木层,其植被碳储量则随封育时间的增加而提高,即M_(CK)Z_(CK)D_(CK)。可见,在中度石漠化山地,植被恢复模式显著影响生态系统碳储量及其分配。人工造林相对于封山育林更能快速促进植被恢复、形成乔木林,从而提高生态系统碳储量。     

2000-2016年秦岭山地植被覆盖变化地形分异效应

利用2000-2016年MODIS NDVI数据,采用趋势分析及地形差异修正法,探讨秦岭山地植被覆盖变化在南北坡、不同海拔以及不同坡度坡向下的空间分异性。结果表明：近17年来,秦岭山地植被覆盖度良好,整体呈上升趋势,南北坡、不同海拔、不同坡度、不同坡向下植被覆盖度有所差异,植被变化趋势也不同。（1）就南北坡而言,近17年来秦岭南坡植被覆盖度上升趋势大于北坡,南坡植被覆盖以上升趋势为主,而北坡以稳定为主。（2）不同的海拔高度上秦岭山地植被覆盖变化在存在分异性：低海拔区域呈减少趋势,中海拔区呈明显的上升趋势,2000 m以上的高海拔区域北坡的植被覆盖度较为稳定,而南坡的2500到3100 m区域内有较明显的减小趋势。（3）从坡度来看,随着坡度的增加秦岭山地植被覆盖度由减少转为增加再转为稳定,南北坡植被变化分异性不明显。（4）不同坡向上,秦岭南北坡植被覆盖度变化差异明显,由阴坡转为阳坡时,北坡植被覆盖有明显的增长趋势,而南坡则不明显,植被覆盖度减小区在南北坡的分布呈相反趋势,分别分布在南坡的阳坡以及北坡的阴坡。