Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPP_VPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPP_EC), for the period from August to November 2015. Results revealed that the cumulative GPP_EC for the entire growth period of maize crop was 1871 g C m⁻². However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPP_EVI) was 1979 g C m⁻², and that determined as a function of the normalized difference vegetation index – NDVI (GPP_NDVI) was 1754 g C m⁻². These results indicated that the GPP_EVI was significantly higher than the GPP_EC (R² = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPP_NDVI was significantly lower than the GPP_EC (R² = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPP_EC and both the GPP_EVI and the GPP_NDVI was −6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.     

遥感反演植被含氮量研究进展

植被含氮量表征植被氮素状态。它作为植被生长状况的重要指标,在生态系统健康状况检测、生态系统生产估测、精准农业、生态系统干扰评估等方面均有重要意义。遥感监测植被含氮量主要基于高光谱和多光谱数据,采用的算法包括经验方法(波谱指数与回归分析)及物理方法(辐射传输模型法)。但受数据源和研究方法的局限,目前植被氮含量遥感监测局限于区域范围较小且内部植被类型与环境条件(气候、地形等)基本一致的情形,而对复杂生态系统的监测能力不足。未来的研究需针对氮沉降和人类活动的生态系统响应这一重大研究需求,发展和改进现有植被含氮量遥感反演方法。可考虑开展对不同环境条件下、不同类型植被光谱曲线进行标准化的研究,以形成普适的植被含氮量反演方法。并考虑综合运用多种数据(如微波遥感、无人机遥感),形成多尺度同步监测,以提高遥感对区域乃至全球范围内植被氮含量常规监测的能力。     

神农架川金丝猴栖息地优势乔木树种遥感识别及其分布特征

针对神农架川金丝猴生境基础研究中乔木树种大范围分布数据难以获取问题,尝试利用多源多时相遥感数据结合专家知识分层次实现树种识别。首先采用冬季Landsat8/OLI数据根据物侯特性分层提取常绿、落叶林的地域范围;进而依据夏季Worldview-2高分遥感影像的实地乔木样本的光谱特征分层次完成常绿树种(巴山冷杉、华山松、青$、刺叶栎)和落叶树种(红桦、日本落叶松、米心水青冈、漆树、锐齿槲栎、椅杨)的识别;并通过实地植被样方及专家知识通过高程数据完成分类结果的修正;最后结合GIS对主要优势树种的地形及地域分布特征进行了空间分析。实验精度表明常绿林中巴山冷杉、华山松、刺叶栎、虫害华山松整体精度较高,落叶林中红桦、漆树等识别精度相对较高,部分树种如椅杨、锐齿槲栎识别精度较低;总体上常绿树种的精度要优于落叶树种。从植物地理学、遥感、GIS三者相结合的角度,将多源、多时相遥感数据与物种物候特性、专家知识进行有效整合,提出了一种乔木树种识别的方法(1)提供了复杂山地环境的主要乔木优势种识别途径,且具有通用性;(2)完成了物种物候特性与遥感数据特性的整合利用,有效降低数据成本费用;(3)配合地面样方及专家知识修正结果,避免了过分依赖光谱特征引起的误判。这将为神农架川金丝猴栖息地保护与恢复提供更精确的数据依据。     

Anti-biofilm and anti-adherence properties of novel cyclic dipeptides against oral pathogens

Microorganisms embedded in a biofilm are significantly more resistant to antimicrobial agents and the defences of the human immune system, than their planktonic counterpart. Consequently, compounds that can inhibit biofilm formation are of great interest for novel therapeutics. In this study, a screening approach was used to identify novel cyclic dipeptides that have anti-biofilm activity against oral pathogens. Five new active compounds were identified that prevent biofilm formation by the cariogenic bacterium Streptococcus mutans and the pathogenic fungus Candida albicans. These compounds also inhibit the adherence of microorganisms to a hydroxylapatite surface. Further investigations were conducted on these compounds to establish the structure–activity relationship, and it was deduced that the common cleft pattern is required for these molecules to act effectively against biofilms.     

Quorum-sensing- and type VI secretion-mediated spatiotemporal cell death drives genetic diversity in Vibrio cholerae

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A multiscale analysis of ecosystem services supply in the NW Iberian Peninsula from a functional perspective

In recent years, the assessment of ecosystem services (ES) supply has been based on the use of Land Use/Land Cover (LULC) data as proxies for spatial representation of ecosystems. Nevertheless, some shortcomings of this method, such as uncertainties derived from generalization of the ecosystem types and assumptions of invariance across spatial scales, indicate the need for new approaches. Such approaches could be aimed at improving knowledge of the relationships between ecosystem services and landscape structure and the spatial characteristics of ES patterns. In this study, we propose an integrative approach that involves the generation and analysis of continuous maps representing the supply of five ES potentially related to the amount of biomass. Five remote sensing images of the Northwestern Iberian Peninsula, obtained with Landsat-5 TM, were used to generate a proxy for net primary production by combining the normalized difference vegetation index (NDVI) of each image to calculate a ΣNDVI index that could act as a potential indicator of some ecosystem services. This information was combined with three variables – terrain slope, population density and occurrence of protected areas – to produce spatial models for the five ES and eventually a series of five supply maps. Food, materials and energy provision services showed a clustered pattern, with high supply values in flat zones and areas with high population densities. In contrast, mass flow and climate regulation services were more widely distributed throughout the study area. The five ecosystem service patterns were analyzed at different scales by two methods: lacunarity and four term local quadrat variance (4TLQV) analysis. These methods revealed differences in the spatial pattern: lacunarity analysis was useful for detection of scale thresholds at the local level, whereas 4TLQV was more sensitive to scale thresholds at larger spatial levels. Thus, the variance analysis yielded higher values for larger windows sizes, particularly for provisioning services. The results demonstrated the suitability of the proposed approach for the spatially explicit modeling of ecosystem services, avoiding the uncertainty of other assessments such as those based on LULC data, and for the exploratory analysis of ES supply from a spatial point of view.