Extreme drought pushes stream invertebrate communities over functional thresholds

Functional traits are increasingly being used to predict extinction risks and range shifts under long‐term climate change scenarios, but have rarely been used to study vulnerability to extreme climatic events, such as supraseasonal droughts. In streams, drought intensification can cross thresholds of habitat loss, where marginal changes in environmental conditions trigger disproportionate biotic responses. However, these thresholds have been studied only from a structural perspective, and the existence of functional nonlinearity remains unknown. We explored trends in invertebrate community functional traits along a gradient of drought intensity, simulated over 18 months, using mesocosms analogous to lowland headwater streams. We modelled the responses of 16 traits based on a priori predictions of trait filtering by drought, and also examined the responses of trait profile groups (TPGs) identified via hierarchical cluster analysis. As responses to drought intensification were both linear and nonlinear, generalized additive models (GAMs) were chosen to model response curves, with the slopes of fitted splines used to detect functional thresholds during drought. Drought triggered significant responses in 12 (75%) of the a priori‐selected traits. Behavioural traits describing movement (dispersal, locomotion) and diet were sensitive to moderate‐intensity drought, as channels fragmented into isolated pools. By comparison, morphological and physiological traits showed little response until surface water was lost, at which point we observed sudden shifts in body size, respiration mode and thermal tolerance. Responses varied widely among TPGs, ranging from population collapses of non‐aerial dispersers as channels fragmented to irruptions of small, eurythermic dietary generalists upon extreme dewatering. Our study demonstrates for the first time that relatively small changes in drought intensity can trigger disproportionately large functional shifts in stream communities, suggesting that traits‐based approaches could be particularly useful for diagnosing catastrophic ecological responses to global change.     

Valuing urban green spaces in mitigating climate change: A city‐wide estimate of aboveground carbon stored in urban green spaces of China's Capital

Urban green spaces provide manifold environmental benefits and promote human well‐being. Unfortunately, these services are largely undervalued, and the potential of urban areas themselves to mitigate future climate change has received little attention. In this study, we quantified and mapped city‐wide aboveground carbon storage of urban green spaces in China's capital, Beijing, using field survey data of diameter at breast height (DBH) and tree height from 326 field survey plots, combined with satellite‐derived vegetation index at a fine resolution of 6 m. We estimated the total amount of carbon stored in the urban green spaces to be 956.3 Gg (1 Gg = 10⁹ g) in 2014. There existed great spatial heterogeneity in vegetation carbon density varying from 0 to 68.1 Mg C ha^‐1, with an average density of 7.8 Mg C ha^?1. As expected, carbon density tended to decrease with urban development intensity (UDI). Likely being affected by vegetation cover proportion and configuration of green space patches, large differences were presented between the 95th and 5th quantile carbon density for each UDI bin, showing great potential for carbon sequestration. However, the interquartile range of carbon density narrowed drastically when UDI reached 60%, signifying a threshold for greatly reduced carbon sequestration potentials for higher UDI. These findings suggested that urban green spaces have great potential to make contribution to mitigating against future climate change if we plan and design urban green spaces following the trajectory of high carbon density, but we should be aware that such potential will be very limited when the urban development reaches certain intensity threshold.     

Managing the middle: A shift in conservation priorities based on the global human modification gradient

An increasing number of international initiatives aim to reconcile development with conservation. Crucial to successful implementation of these initiatives is a comprehensive understanding of the current ecological condition of landscapes and their spatial distributions. Here, we provide a cumulative measure of human modification of terrestrial lands based on modeling the physical extents of 13 anthropogenic stressors and their estimated impacts using spatially explicit global datasets with a median year of 2016. We quantified the degree of land modification and the amount and spatial configuration of low modified lands (i.e., natural areas relatively free from human alteration) across all ecoregions and biomes. We identified that fewer unmodified lands remain than previously reported and that most of the world is in a state of intermediate modification, with 52% of ecoregions classified as moderately modified. Given that these moderately modified ecoregions fall within critical land use thresholds, we propose that they warrant elevated attention and require proactive spatial planning to maintain biodiversity and ecosystem function before important environmental values are lost.     

我国男子橄榄球运动员有氧能力的评定和比赛时能耗的初探*

目的:探究我国男子橄榄球运动员的有氧能力和比赛时的能量消耗,为精准化训练和比赛时营养策略的制定提供理论依据。方法:以18名男子橄榄球运动员(健将级)为研究对象,分别进行最大摄氧量(VO₂max),乳酸阈(LT)和conconi场地测试来评定其有氧能力,并比较前、后锋之间的供能差异,用wGT3X加速度计结合团队心率探究比赛时的能量消耗,所得数据进行独立样本t检验。结果:本次检测的橄榄球运动员相对最大摄氧量较差为(42.05±3.69) ml/min·kg^-1,前峰队员相对最大摄氧量为(38.83±3.52) ml/min·kg^-1、后锋队员相对最大摄氧量为(47.31±3.17)ml/min·kg^-1,二者之间的差异有统计学意义(P＜0.05);血乳酸阈测定在7 min时出现血乳酸拐点,后锋的血乳酸阈值要高于前锋运动员;conconi场地测试与实验室VO₂max有较高的相关性(r=0.772)。比赛中平均能量消耗上半场约为(276.94±18.08) kcals,下半场约为(225.58±22.86) kcals,下半场的能耗小于上半场(P＜0.05)。结论:英式7人制橄榄球运动员有氧能力较弱,且前、后锋队员存在差异。     

Dynamic evaluation of blood flow microcirculation by combined use of the laser Doppler flowmetry and high‐speed videocapillaroscopy methods

The dynamic light scattering methods are widely used in biomedical diagnostics involving evaluation of blood flow. However, there exist some difficulties in quantitative interpretation of backscattered light signals from the viewpoint of diagnostic information. This study considers the application of the high‐speed videocapillaroscopy (VCS) method that provides the direct measurement of the red blood cells (RBCs) velocity into a capillary. The VCS signal presents true oscillation nature of backscattered light caused by moving RBCs. Thus, the VCS signal can be assigned as a reference one with respect to more complicated signals like in laser Doppler flowmetry (LDF). An essential correlation between blood flow velocity oscillations in a separate human capillary and the integral perfusion estimate obtained by the LDF method has been found. The observation of blood flow by the VCS method during upper arm occlusion has shown emergence of the reverse blood flow effect in capillaries that corresponds to the biological zero signal in the LDF. The reverse blood flow effect has to be taken into account in interpretation of LDF signals.      

Electrocardiogram Data Compression Techniques for Cardiac Healthcare Systems: A Methodological Review

Objective: Globally, cardiovascular diseases (CVDs) are one of the most leading causes of death. In medical screening and diagnostic procedures of CVDs, electrocardiogram (ECG) signals are widely used. Early detection of CVDs requires acquisition of longer ECG signals. It has triggered the development of personal healthcare systems which can be used by cardio-patients to manage the disease. These healthcare systems continuously record, store, and transmit the ECG data via wired/wireless communication channels. There are many issues with these systems such as data storage limitation, bandwidth limitation and limited battery life. Involvement of ECG data compression techniques can resolve all these issues.Method: In the past, numerous ECG data compression techniques have been proposed. This paper presents a methodological review of different ECG data compression techniques based on their experimental performance on ECG records of the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database.Results: It is observed that experimental performance of different compression techniques depends on several parameters. The existing compression techniques are validated using different distortion measures.Conclusion: This study elaborates advantages and disadvantages of different ECG data compression techniques. It also includes different validation methods of ECG compression techniques. Although compression techniques have been developed very widely but the validation of compression methods is still a prospective research area to accomplish an efficient and reliable performance.     

Motor Imagery EEG Spectral-Spatial Feature Optimization Using Dual-Tree Complex Wavelet and Neighbourhood Component Analysis

BackgroundFrequency band optimization improves the performance of common spatial pattern (CSP) in motor imagery (MI) tasks classification because MI-related electroencephalograms (EEGs) are highly frequency specific. Many variants of CSP algorithm divided the EEG into various sub bands and then applied CSP. However, the feature dimension of MI-EEG data increases with addition of frequency sub bands and requires efficient feature selection algorithms. The performance of CSP also depends on filtering techniques.MethodIn this study, we designed a dual tree complex wavelet transform based filter bank to filter the EEG into sub bands, instead of traditional filtering methods, which improved the spatial feature extraction efficiency. Further, after filtering EEG into different sub bands, we extracted spatial features from each sub band using CSP and optimized them by a proposed supervised learning framework based on neighbourhood component analysis (NCA). Subsequently, a support vector machine (SVM) is trained to perform classification.ResultsAn experimental study, conducted on two datasets (BCI Competition IV (Dataset 2b), and BCI competition III (Dataset IIIa)), validated the MI classification effectiveness of the proposed method in comparison with standard algorithms such as CSP, Filter bank CSP (CSP), and Discriminative FBCSP (DFBCSP). The average classification accuracy obtained by the proposed method for BCI Competition IV (Dataset 2b), and BCI Competition III (Dataset IIIa) are 84.02 ± 12.2 and 89.1 ± 7.50, respectively and found significant than that achieved by standard methods.ConclusionAchieved superior results suggest that the proposed algorithm can improve the performance of MI-based Brain-computer interface devices.     

Ecological application of wavelet analysis in the scaling of spatial distribution patterns of Ceratoides ewersmanniana

Ecological experiments are usually conducted on small scales, but the ecological and environmental issues are usually on large scales. Hence, there is a clear need of scaling. Namely, when we deal with patterns and processes on larger scales, a special connection needs to be established on the small scales that we are familiar with. Here we presented a wavelet analysis method that could build relationships between spatial distribution patterns on different scales. With this method, we also studied how spatial heterogeneity and distribution patterns changed with the scale. We investigated the distribution and the habitat of C. ewersmanniana in two plots (200 m × 200 m; the distance between these two plots is 15 km) at Mosuowan desert. The results demonstrated that spatial heterogeneity and distribution patterns were incorporated into larger scales when the wavelet scale varied from one (5 m) to four (20 m). However, if the wavelet scale was above five (25 m), the spatial distribution patterns varied placidly, the oscillation frequency of landforms stabilized at 110 m, and the dynamic quantity period of C. ewersmanniana stabilized at 115–125 m. We also identified signal mutation points with wavelet analysis and verified the heterogeneity degree of local space with position variance. We found that position variance decomposed the distribution patterns on large scales into small sampling plots, and the position with the largest variance also had the strongest heterogeneity. In a word, the wavelet analysis method could scale-up spatial distribution patterns and habitat heterogeneity. With this method and other methods derived from this one, such as wavelet scale, wavelet variance, position variance and extremely direct-viewing graphs, wavelet analysis could be widely applied in solving the scaling problem in ecological and environmental studies.     

The influences of arboraceous layer on spatial patterns and morphological characteristics of herbaceous layer in an arid plant community

The objectives of this study were to examine the effects of arboraceous layer on the spatial pattern and morphological characteristics of herbaceous layer in Elaeagnus angustifolia–Achnatherum splendens community in Ningxia Hui Autonomous Region, China. The analyses of community composition and structural characteristics as well as the investigation of soil moisture and salinity showed that different life forms of plants differ in the soil depth at which they absorb and utilize soil moisture. Wavelet analysis showed that there were differences between the spatial patterns of A. splendens in the canopy-projected regions and other regions, and the intrinsic scales were detected. The results from the buffer analysis showed that the control of arboraceous layer on the herbaceous layer on the spatial patterns and the morphological characteristics were influenced not only by canopy shading but also by other causes such as distribution patterns of roots as the morphological characteristics did not monotonically change with distance.