Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

Sampling approaches to predict urban street noise levels using fixed and temporary microphones

Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90,)L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 × 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq,60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 × 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators.     

Top-down control inhibits spatial self-organization of a patterned landscape

Regular, self-organized spatial patterns in primary producers have been described in a wide range of ecosystems and are predicted to affect community production and resilience. Although consumers are abundant in most systems, the effect of trophic interactions on pattern formation in primary producers remains unstudied. We studied the effects of top-down control by herbivores on a self-organized landscape of regularly spaced, diatom-covered hummocks alternating with water-filled hollows on an intertidal mudflat in The Netherlands. Spatial patterns developed during spring but were followed by a rapid collapse in summer, leading to a flat landscape with low diatom densities and little variation in sediment bed level. This dramatic decline co-occurred with a gradual increase of benthic herbivores. A manipulative field experiment, where benthic herbivores were removed from the sediment, revealed that both diatom growth and hummock formation were inhibited by the activity of benthic herbivores. Our study provides clear evidence of top-down control of spatial self-organized patterns by benthic herbivores within a biological-geomorphic landscape.     

A robust-design formulation of the incidence function model of metapopulation dynamics applied to two species of rails

The incidence function model (IFM) uses area and connectivity to predict metapopulation dynamics. However, false absences and missing data can lead to underestimates of the number of sites contributing to connectivity, resulting in overestimates of dispersal ability and turnovers (extinctions plus colonizations). We extend estimation methods for the IFM by using a hierarchical Bayesian model to account both for false absences due to imperfect detection and for missing data due to sites not surveyed in some years. We compare parameter estimates, measures of metapopulation dynamics, and forecasts using stochastic patch occupancy models (SPOMs) among three IFM models: (1) a Bayesian formulation assuming no false absences and omitting site-year combinations with missing data; (2) a hierarchical Bayesian formulation assuming no false absences but incorporating missing data; and (3) a hierarchical Bayesian formulation allowing for imperfect detection and incorporating missing data. We fit the models to multiyear data sets of occupancy for two bird species that differ in body size and presumed dispersal ability but inhabit the same network of sites: the small Black Rail (Laterallus jamaicensis) and the medium-sized Virginia Rail (Rallus limicola). Incorporating missing data affected colonization parameters and led to lower estimates of dispersal ability for the Black Rail. Detection rates were high for the Black Rail in most years but moderate for the Virginia Rail. Incorporating imperfect detection resulted in higher occupancy and lower turnover rates for both species, with largest effects for the Virginia Rail. Forecasts using SPOMs were sensitive to both missing data and false absences; persistence in models assuming no false absences was more optimistic than from robust models. Our results suggest that incorporating false absences and missing data into the IFM can improve (1) estimates of dispersal ability and the effect of connectivity on colonization, (2) the scaling of extinction risk with patch area, and (3) forecasts of occupancy and turnover rates.     

城乡融合评价研究综述：内涵辨识、理论认知与体系重构

科学的城乡融合评价是城乡融合工作的重要环节,是建立健全城乡融合体制机制的基础。以“内涵辨识—理论认知—体系重构”为逻辑主线,从城乡融合的概念内涵、基础理论、评价指标、评价方法、评价尺度及演化机理等方面,开展城乡融合评价综述。研究表明：学界对城乡融合概念与内涵的认识基本一致,且已有一定理论基础;城乡融合评价指标选取呈现多维化、多属性化特征,但指标体系构建尚未突破静态性层面;定量评价方法较为单一;研究尺度整体偏向中宏观,缺少微观视角下的量化以及不同融合模式对比研究;城乡融合的时空分异格局及其机理研究亟待进一步深化。对此,提出了以下五点展望：（1）加强基础理论体系建设,完善系统研究框架构建;（2）优化多维评价指标体系,识别城乡融合发展模式;（3）深化城乡要素流动机制,推动城乡空间均衡发展;（4）加强微观尺度细节挖掘,健全城乡融合推进机制;（5）强化数字经济赋能作用,创新城乡高质量融合发展机制。     

聚甲醛废水的生物强化处理及微生物种群动态分析

聚甲醛工业废水含有甲醛、三聚甲醛和酚类等有害物,而且盐分和COD也较高,很难实现生物处理至达标排放.在聚甲醛污水厂建立中试系统并接种活性污泥,同时投加了经筛选的三聚甲醛降解菌Bacillus methylotrophicus和甲醛降解菌Candida maltosa、Pseudomonsa putida组成的复合菌剂,进行了聚甲醛、甲醛等有毒物质的选择性生物强化,通过温度梯度凝胶电泳(PCR-TGGE)技术对污水反应器进行了微生物群落结构分析,并与污水厂同期出水进行对照研究.结果表明,在投加复合菌剂的强化生物系统中,最终出水的甲醛、三聚甲醛(Trioxane,TOX)和COD降解率分别在97.8%、94.2%和92.6%以上,且系统表现出更高稳定性和抗冲击负荷能力.PCR-TGGE图谱表明,非生物强化系统中未检测到B.methylotrophicus,而该菌在生物强化系统中的活性一直得以维持,其对有毒物质的持续降解解除了其它微生物群落的抑制因子,污泥活性有效增强,说明该菌及复合菌剂确实对TOX及甲醛等毒性物质可有效降解,选择性生物强化可成为工业污水处理的可靠手段之一.     

Bioaccumulation Dynamic by Crassostrea gigas Oysters of Viruses That Are Proposed as Surrogates for Enteric Virus Contamination in Environmental Samples

Food and Environmental Virology - Oysters are filter-feeders and retain sewage-derived pathogens in their organs or tissues. Since most enteric viruses involved in outbreaks cannot grow in cell...     

当量加速腐蚀条件下飞机结构耐久性评估方法研究

目的研究某型飞机机翼纵墙下缘条的结构细节模拟试件的耐久性。方法根据实测环境数据编制某沿海机场环境加速试验谱,开展不同当量腐蚀年限的加速腐蚀试验,然后进行耐久性试验,基于裂纹萌生寿命(TTCI)服从双参数威布尔分布和对数正态分布,建立表征腐蚀损伤下机翼纵墙结构细节原始疲劳质量(IFQ)的当量初始缺陷尺寸(EIFS)分布,并对机群机翼纵墙的经济寿命进行预测。结果铝合金材料在θ=40℃,pH=4.0,质量分数为5%的NaCl溶液盐雾环境中作用189.7 h,腐蚀损伤与该海洋大气环境腐蚀1 a相当。结论该关键结构在沿海机场环境条件下的耐久性能满足寿命指标要求。     

温度和氯离子浓度对30CrMnSiNiA腐蚀速率的影响研究

目的研究温度和氯离子浓度对金属腐蚀速率的影响。方法通过失重法研究对比30CrMnSiNiA结构钢在不同氯离子浓度和温度下的腐蚀速率。结果 30CrMnSiNiA钢的腐蚀速率都经历了一个增大-减小-趋于稳定的过程,说明腐蚀机理并未发生改变。在温度较低和氯离子浓度较低的条件下,升高温度和氯离子浓度将会提高腐蚀速率;当温度和氯离子浓度很高时,继续升高温度和氯离子浓度将会降低溶液中溶解氧的含量,使腐蚀速率降低,溶解氧的极限扩展速率将会成为限制腐蚀速率的关键因素。结论不同温度和氯离子浓度下金属腐蚀规律相同,温度和氯离子浓度在一定范围内促进了金属的腐蚀速率。当超过转化点后,提高温度和氯离子浓度会降低腐蚀速率。