Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management

Understanding predator–prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify the post-stocking survival and predation of a prey fish in Lake Ontario, 48 bloater Coregonus hoyi were tagged with acoustic telemetry predation tags and were tracked on an array of 105 acoustic receivers from November 2018 to June 2019. Putative predators of tagged bloater were identified by comparing movement patterns of six species of salmonids (i.e., predators) in Lake Ontario with the post-predated movements of bloater (i.e., prey) using a random forests algorithm, a type of supervised machine learning. A total of 25 bloater (53% of all detected) were consumed by predators on average (± S.D. ) 3.1 ± 2.1 days after release. Post-predation detections of predators occurred for an average (± S.D. ) of 78.9 ± 76.9 days, providing sufficient detection data to classify movement patterns. Tagged lake trout Salvelinus namaycush provided the most reliable classification from behavioural predictor variables (89% success rate) and was identified as the main consumer of bloater (consumed 50%). Movement networks between predicted and tagged lake trout were significantly correlated over a 6 month period, supporting the classification of lake trout as a common bloater predator. This study demonstrated the ability of supervised learning techniques to provide greater insight into the fate of stocked fishes and predator–prey dynamics, and this technique is widely applicable to inform future stocking and other management efforts.     

高血压性心脏病生物标志物的筛选：基于中国重庆市7家医疗机构的数据分析研究*

目的: 筛选高血压性心脏病（HHD）的影响因素,建立HHD的预测模型,为HHD的发生提供预警。方法: 选取中国重庆市某医科院校数据研究院平台2016年1月1日至2019年12月31日主要诊断为高血压性心脏病和高血压患者。通过单因素分析、多因素分析筛选HHD的影响因素,采用R语言分别构建Logistics模型、随机森林（RF）模型和极限梯度上升（XGBoost）模型。结果: 单因素分析筛选出60项差异指标,多因素分析筛选出18项差异指标（P<0.05）。Logistics模型、RF模型、XGBoost模型曲线下面积（AUC）分别为0.979、0.983和0.990。结论: 本文建立的3种HHD预测模型结果稳定,其中XGBoost模型对于HHD的发生具有良好的诊断效应。     

不同坡位水曲柳木质部解剖特征及其与气候关系

随着气候变暖,东北地区暖干化加剧。为了解干旱胁迫对小兴安岭地区不同坡位水曲柳径向生长的影响,采用木材解剖学方法,分析了水曲柳木质部解剖特征对不同坡位水分变化的响应。结果表明: 上、下坡位水曲柳木质部解剖参数整体上变化趋势一致,导管数量呈线性分布,最大导管面积和总导管面积总体上呈对数分布,平均导管面积总体上呈偏正态分布。不同坡位多个解剖参数均存在显著差异,下坡位导管数量、导管面积总体上大于上坡位。大部分解剖参数与日积温呈显著正相关,但存在一定差异,上坡位水曲柳总导管面积与日均温呈正相关,导管数量、总导管面积与相对湿度呈正相关,相关性均大于下坡位。上坡位最小导管面积与日积温和相对湿度呈显著负相关;而下坡位,总导管面积与相对湿度呈显著正相关。气候暖干化会导致水曲柳导管面积和导管数量相对减少,但基本上不影响导管分布状况,上、下坡位导管分布基本一致。目前,气候暖干化未限制而是促进了水曲柳的径向生长。     

黄河首曲玛曲县高寒湿地景观格局演变

高寒湿地是青藏高原地区最重要的生态水源涵养区之一, 也是局部气候的有效调节者, 其动态变化与成因亟待深入研究。该研究基于遥感图像分析、地理信息系统空间分析和景观生态指数分析结合的方法, 以黄河首曲玛曲县高寒湿地为研究对象, 对1995-2018年6期湿地的动态变化进行研究。结果表明, 研究区湿地在1995-2010年间不断退化, 1995-2010年湿地面积总共减少了18 680.31 hm²。在2010-2018年间黄河首曲高寒湿地面积有所增加, 但与20世纪90年代相比, 21世纪初开始湿地的面积普遍呈现下降趋势; 1995-2010年湿地斑块数不断增加, 斑块密度不断增大, 平均斑块面积下降, 景观的破碎度升高; 2010-2015年湿地斑块数和斑块密度减少, 2015-2018年湿地斑块数和斑块密度增加, 平均斑块面积先增大后减小, 景观的破碎度先降低后升高。1995-2010年研究区高寒湿地景观Shannon多样性指数和Shannon均匀度指数均呈现下降的趋势, 湿地的景观结构趋于简单, 景观类型分布更加集中。2010-2018年湿地景观Shannon多样性指数和Shannon均匀度指数均呈现上升趋势, 湿地的景观结构趋于复杂, 景观类型增加且分布更加分散。进一步的驱动力分析表明, 引起黄河首曲高寒湿地景观格局演变的主要因素是蒸发量和降水量, 其次是人口数量和大牲畜数量等人类活动影响。气候因子是影响黄河首曲高寒湿地面积变化的主要原因, 过度的人类经济活动在一定程度上加剧了湿地的变化。     

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.     

Endogenous cardiac activity rhythms of continental slope Nephrops norvegicus (decapoda: nephropidae)

The endogenous cardiac activity rhythm of the Norway lobster Nephrops norvegicus was studied under constant conditions of darkness by means of a computer-aided monitoring system (CAPMON). Time series recordings of the heart rate (beats min^?1) were obtained from 47 adult males freshly collected from the continental slope (400–430?m) in the western Mediterranean. Periodogram analysis revealed the occurrence of circadian periodicity (of around 24?h) in most cases. A large percentage of animals showed significant ultradian periods (of around 12 and 18?h). The analysis of the circadian time series revealed the occurrence of peaks of heart rate activity during the expected night phase of the cycle. These results are discussed in relation to the emergence and locomotor activity rhythms of the species.     

Forced evolution of Escherichia coli cells with the ability to effectively utilize non-natural amino acids l-tert-leucine,l-norleucine and γ-methyl-l-leucine

Abstract

In an attempt to develop a novel biocatalyst able to efficiently catalyse the synthesis of non-natural amino acids, Escherichia coli TG1 was treated with 10 mM NaNO₂ and then cultured in selective medium supplemented with 20 mM l-tert-leucine. Each culture was grown for 2 weeks and then subcultured into fresh medium with successive decreases of l-tert-leucine concentration at each transfer to a final value of 0.5 mM. The adapted cells resulting from this forced evolution procedure were able to grow in minimal medium with 0.1 mM l-tert-leucine as sole nitrogen source. Both HPLC and TLC verified progressive removal of l-tert-leucine from the medium during bacterial growth. Further studies revealed that the adapted cells metabolized l-tert-leucine by transamination, removing the amino group but leaving the carbon skeleton of the corresponding 2-oxoacid intact. Despite the mutagenesis, when the four obvious candidate amino acid aminotransferase genes were cloned and sequenced, there was no change in these structural genes. The activity of the adapted cells with l-tert-leucine is apparently attributable to the wild-type branched-chain amino acid aminotransferase (IlvAT), presumably expressed at higher levels as a result of a regulatory mutation. With the isolate I-4, the resting cells transaminate l-tert-leucine, l-norleucine, l-norvaline, γ-methyl-l-leucine and dl-homophenylalanine as effectively as does the crude extract. These evolved cells may be useful for synthesizing non-natural amino acids for the pharmaceutical industry. In addition, the adapted cells can also catalyse transamination of naturally occurring hydrophobic amino acids.     

The impact of microgravity-based proteomics research

Proteomics is performed in microgravity research in order to determine protein alterations occurring qualitatively and quantitatively, when single cells or whole organisms are exposed to real or simulated microgravity. To this purpose, antibody-dependent (Western blotting, flow cytometry, Luminex^® technology) and antibody-independent (mass spectrometry, gene array) techniques are applied. The anticipated findings will help to understand microgravity-specific behavior, which has been observed in bacteria, as well as in plant, animal and human cells. To date, the analyses revealed that cell cultures are more sensitive to microgravity than cells embedded in organisms and that proteins changing under microgravity are highly interactive. Furthermore, one has to distinguish between primary gravity-induced and subsequent interaction-dependent changes of proteins, as well as between direct microgravity-related effects and indirect stress responses. Progress in this field will impact on tissue engineering and medicine and will uncover possibilities of counteracting alterations of protein expression at lowered gravity.     

Validation of discrete time-to-event prediction models in the presence of competing risks

Clinical prediction models play a key role in risk stratification, therapy assignment and many other fields of medical decision making. Before they can enter clinical practice, their usefulness has to be demonstrated using systematic validation. Methods to assess their predictive performance have been proposed for continuous, binary, and time-to-event outcomes, but the literature on validation methods for discrete time-to-event models with competing risks is sparse. The present paper tries to fill this gap and proposes new methodology to quantify discrimination, calibration, and prediction error (PE) for discrete time-to-event outcomes in the presence of competing risks. In our case study, the goal was to predict the risk of ventilator-associated pneumonia (VAP) attributed to Pseudomonas aeruginosa in intensive care units (ICUs). Competing events are extubation, death, and VAP due to other bacteria. The aim of this application is to validate complex prediction models developed in previous work on more recently available validation data.     

Outlier detection methods are still effective even using virtual species created with the probabilistic approach

Liu et al. (Journal of Biogeography, 2018, 45 :164–176) presented an approach to detect outliers in species distribution data by developing virtual species created using the threshold approach. Meynard et al. (Journal of biogeography, 2019, 46 :2141–2144) raised concerns about this approach stating that ‘using a probabilistic approach … may significantly change results’. Here we provide a new series of simulations using the two approaches and demonstrate that the outlier detection approach based on pseudo species distribution models was still effective when using the probabilistic approach, although the detection rate was lower than when using the threshold approach.