基于日光诱导叶绿素荧光的北半球森林物候研究

植被物候是反映植被生长规律的重要指标, 对气候的反馈具有重要意义。日光诱导叶绿素荧光(SIF)通过复杂的能量耗散机制与光合作用相关联, 提供了从空间直接探测大范围植被物候的可能性。为了探究气候变化背景下SIF反演不同森林类型物候的适用性, 该文以北半球35个全球通量网(FLUXNET)森林站点为研究对象, 利用2007-2014年SIF值和总初级生产力(GPP)通过双逻辑生长模型和动态阈值法来估算3种典型森林类型的物候, 并采用相关性分析等方法评价SIF在估算不同森林类型物候时的差异性。主要结果为: 1) SIF对生长季开始时间(SOS)的估算精度高于生长季结束时间(EOS); 2) SIF能够更准确地估算混交林(MF)的SOS, 但是不能精确追踪落叶阔叶林(DBF)和常绿针叶林(ENF)的SOS; 3)春季季前短波辐射是驱动SOS的主要气候因素。综上, 建议在将来的研究中将SIF数据与其他遥感指数整合, 应用于不同植物类型的物候监测。     

Dietary intake of artificial food color additives containing food products by school-going children

Nutritional risk in children is associated with food safety. This is the first study to identify the food type consumed by 6–17-year-old school-going children in Saudi Arabia. Eight permitted artificial food color additives, including Tartrazine (E102), Sunset Yellow (E110), Carmoisine (E122), Allura Red (E129), Indigo Carmine (E132), Brilliant Blue (E133), Fast Green (E143), and Black PN (E151), and two non-permitted ones, Erythrosine (E127) and Red 2G (E128), were determined using 24-h dietary recall questionnaires. Artificial color additives in 839 food products were divided into nine categories, including biscuits, cakes, chocolates, chips, ice cream, juices and drinks, candy, jelly, and chewing gum, are determined using high performance liquid chromatography and diode array detector. The results indicated a high intake of juices and drinks, ice cream, and cakes, but low consumption of chewing gum among school-going children. Among the permitted artificial food color additives, Brilliant Blue (E133) (54.1%) and Tartrazine (E102) (42.3%) were the most commonly used. Sunset Yellow (E110) in one chocolate sample, Tartrazine (E102) and Sunset Yellow (E110) in one and two juice and drink samples, respectively, and Brilliant Blue (E133) in two candy samples exceeded the permitted level. Therefore, further investigations are needed to provide insights into the possible adverse health effects of high intake of these additives in artificial food coloring on the test population are warranted.     

Novel artificial intelligence machine learning approaches to precisely predict survival and site-specific recurrence in cervical cancer: A multi-institutional study

BackgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.MethodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.ResultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.ConclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

长江中下游岸带(宜昌-铜陵段)湿生植物的群落构建机制研究

沿长江中下游（宜昌-铜陵段）13座城市共37个位点,分别于丰水期和枯水期对岸带的湿生植物进行调查,从物种和系统发育2个维度研究群落的构建机制,并结合环境和空间因子探讨其驱动因素。结果显示：（1）丰水期湿生植物群落的α多样性高于枯水期,且丰水期α多样性主要与水分条件呈正相关,而枯水期则主要与温度和土壤总氮含量有关。（2）丰水期的系统发育结构指数呈聚集趋势,暗示生境过滤起着主导作用,而枯水期的NRI（net relatedness index）和NTI（nearest taxon index）呈不同趋势,暗示存在近期的群落分化。（3）群落的α多样性在物种层面和系统发育层面存在显著关联性,其多样性水平可在一定程度上互为表征。（4）长江中下游沿岸湿生植物群落的构建机制在不同时期存在差异,丰水期的群落构建是环境筛选和扩散限制共同作用的结果,且以环境筛选作用占主导,而枯水期的群落构建仅在物种层面受一定程度环境筛选作用的影响。（5）大生境的温度变化、微生境的土壤水分和养分条件是影响长江中下游岸带湿生植物群落差异的主要驱动因素。该研究结果可为长江中下游岸带湿地生态系统的管理和保护提供科学支持。     

A Comparison of Vegetation and Ground‐Dwelling Ants in Abandoned and Restored Gullies and Landslide Surfaces in the Western Colombian Andes

Landslides and gullies are two common manifestations of land degradation in the densely populated Colombian Andes. In these unstable areas, further mass movements pose a serious threat to local populations and cause off‐site environmental damage through sedimentation, pollution, and increased flooding. A novel approach for restoring severely eroded slopes combines the use of stabilization structures made with stalks of Guadua angustifolia Kunth, Poaceae (bamboo), with high‐density planting of species that exhibit quick growth and sprouting. This study compared the vegetation and ground‐dwelling ant assemblages of 10 pairs of gullies, each pair formed by one enhanced and one untreated or control gully, 6–8 years after restoration or abandonment. The restoration treatment had significant effects on the complexity of vegetation. Average values for plant species richness, basal area, stem density, foliage density index, and total vegetation volume were 11.6, 140, 30, 11.5, and 15.6 times larger, respectively, in enhanced than in control gullies. Mirroring the differences in vegetation, average ant species richness was significantly larger (13 vs. 7.6 species per gully), and a higher proportion of ant species nested within enhanced than control gullies (52.5 vs. 30%). While control gullies were dominated by generalist ants such as Ectatomma ruidum and Linepithema angulatum, enhanced gullies had more specialized ground‐dwelling species, normally associated with high plant cover and abundant leaf litter such as Octostruma balzani and Heteroponera inca. We conclude that this restoration strategy promotes a fast recovery of vegetation and the ground‐dwelling ant fauna in these tropical mountains.     

Artificial Spawning Habitats Improve Egg Production of a Declining Diadromous Fish,Galaxias maculatus (Jenyns, 1842)

Anthropogenic impacts from urbanization, deforestation, and agriculture have degraded the riparian margins of waterways worldwide. In New Zealand, such impacts have caused changes in native vegetation, enhanced invasion by exotic grasses, and altered river bank morphology. One consequence has been a great reduction in obligate spawning habitat of a diadromous fish, Galaxias maculatus. Juvenile G. maculatus comprise a culturally important fishery that has been considerably reduced over recent decades. Rehabilitation of riparian vegetation needed for spawning is relatively straightforward, but slow. We hypothesized that artificial spawning habitats could accelerate restoration of fish egg production by creating an environment that would support at least the same density and survival of eggs as non‐impacted vegetation. We tested three artificial devices (straw bales, straw tubes, and moss tubes) in degraded and intact sites. Eggs were laid in all of these with numbers and survival usually exceeding that in riparian grasses. Where habitat was degraded, artificial spawning habitats yielded up to 10,000 eggs compared to none in nearby natural spawning habitat. The ground‐level environment of artificial habitat was similar to that of intact vegetation in buffering ambient temperature and humidity fluctuations. Crucial properties of the artificial habitats were (1) shelter to provide shade and hold moisture; (2) accessibility to allow adult fish to deposit and fertilize eggs; and (3) robustness to provide reliable surfaces and protection for the eggs during their development. We show that artificial spawning habitats are a viable short‐term alternative to rehabilitating spawning habitat while legacy effects abate and riparian vegetation recovers.     

旅游干扰对云丘山景区内植被的影响

选择云丘山景区为研究区域,以该区域的主要植被为研究对象,采用样方法对旅游干扰对云丘山景区内植被的影响进行了研究,共设置了40个乔木样方,并利用TWINSPAN聚类分析以及旅游干扰程度（TDD）对所取样方进行分析。结果表明：TWINSPAN聚类分类将景区内的植物群落划分为5个群系,其中、群系Ⅱ中伴人植物的优势度明显高于其它。干扰程度分析表明,在景区的40个乔木样方中,只有4个样方基本没有受到干扰,有3个样方受到中度干扰,其余的33个样方均为轻度干扰。TWINSPAN聚类分析科学合理地对旅游活动作用下植被景观的类型特征进行了分析。旅游干扰程度（TDD）直观地反映出各个样方所在地植被被干扰的程度,该研究结果可为旅游管理者提供一定的理论依据。     

Correlation between macrophyte vegetation and some water properties in the irrigation system of the Lower river Po Plane

Abstract

The distribution of macrophytic plant communities, defined by phytosociological numerical methods, in the irrigation system of the Lower river Po Plane was correlated with water characteristich. Water samples were collected periodically within phytocoena well-characterized from the phytosociological viewpoint. Nymphaeid-dominated communities (all. Nymphaeion) usually occur in deeper waters than elodeid- myriophyllid-, and ceratophyllid-dominated vegetation types (all. Potamogetonion). Hydrochemically, all of the studied waterbodies can be classified as rich in electrolytes and in bicarbonates. The distribution of phytocoena reflects a gradient in nutrient content: the Nymphoidetum peltatae characterizes waters moderately rich; the Myriophyllum spicatum community and the Trapetum natantis fairly rich; the Potamogetonetum pectinati and the Ceratophyllum demersum community very rich in nutrients.     

Ago-Allosteric Modulation and Other Types of Allostery in Dimeric 7TM Receptors

Conventionally, an allosteric modulator is neutral in respect of efficacy and binds to a receptor site distant from the orthosteric site of the endogenous agonist. However, recently compounds being ago-allosteric modulators have been described i.e., compounds acting both as agonists on their own and as enhancers for the endogenous agonists in both increasing agonist potency and providing additive efficacy—superagonism. The additive efficacy can also be observed with agonists, which are neutral or even negative modulators of the potency of the endogenous ligand. Based on the prevailing dimeric concept for 7TM receptors, it is proposed that the ago-allosteric modulators bind in the orthosteric binding site, but–importantly–in the “other” or allosteric protomer of the dimer. Hereby, they can act both as additive co-agonists, and through intermolecular cooperative effects between the protomers, they may influence the potency of the endogenous agonist. It is of interest that at least some endogenous agonists can only occupy one protomer of a dimeric 7TM receptor complex at a time and thereby they leave the orthosteric binding site in the allosteric protomer free, potentially for binding of exogenous, allosteric modulators. If the allosteric modulator is an agonist, it is an ago-allosteric modulator; if it is neutral, it is a classical enhancer. Molecular mapping in hetero-dimeric class-C receptors, where the endogenous agonist clearly binds only in one protomer, supports the notion that allosteric modulators can act through binding in the “other” protomer. It is suggested that for the in vivo, clinical setting a positive ago-allosteric modulator should be the preferred agonist drug.