Water quality in streams typically changes fast, and sensitive biological indicators are crucial for monitoring these changes in water quality. Diatoms are widely used in biological stream quality assessment. However, interannual and intra-annual variation of diatom population densities is large, often hampering a reliable quality assessment. We studied the importance of different species traits on temporal occurrence of diatom species. We also examined whether temporal occurrence of diatoms is related to species' local abundance or regional distribution using a data set collected in Finnish streams. According to the general linear model (GLM), temporal occurrence of diatoms increased with increasing local abundance and regional distribution. Species that occurred more frequently also had larger niche breadths and nonmarginal niche positions. In addition, cell size and attachment ability were positively related to species temporal occurrence. Our results imply that abundant and widely distributed species with large niches and ability to attach sustain persistent populations in varying environmental conditions typical for streams. We suggest that future studies could concentrate on monitoring these common (abundant) species when detecting the possible changes in the biological state of streams. We advise, however, to consider a relatively large number of species as many of the most common species may have low indicator values.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/j.1529-8817.2011.01068.x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
DGMSCL: A dynamic graph mixed supervised contrastive learning approach for class imbalanced multivariate time series classification.
Neural Netw
January 2025
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430070, Hubei, China.
In the Imbalanced Multivariate Time Series Classification (ImMTSC) task, minority-class instances typically correspond to critical events, such as system faults in power grids or abnormal health occurrences in medical monitoring. Despite being rare and random, these events are highly significant. The dynamic spatial-temporal relationships between minority-class instances and other instances make them more prone to interference from neighboring instances during classification.
View Article and Find Full Text PDFEpidemiology of metabolic syndrome.
Pflugers Arch
January 2025
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
The global increase of overweight and obesity in children and adults is one of the most prominent public health threats, often accompanied by insulin resistance, hypertension, and dyslipidemia. The simultaneous occurrence of these health problems is referred to as metabolic syndrome. Various criteria have been proposed to define this syndrome, but no general consensus on the specific markers and the respective cut-offs has been achieved yet.
View Article and Find Full Text PDFPopulation-Level SARS-CoV-2 RT-PCR Cycle Threshold Values and Their Relationships with COVID-19 Transmission and Outcome Metrics: A Time Series Analysis Across Pandemic Years.
Viruses
January 2025
Antiguo Hospital Civil de Guadalajara, "Fray Antonio Alcalde", Guadalajara 44280, Mexico.
This study investigates the relationship between SARS-CoV-2 RT-PCR cycle threshold (Ct) values and key COVID-19 transmission and outcome metrics across five years of the pandemic in Jalisco, Mexico. Utilizing a comprehensive time-series analysis, we evaluated weekly median Ct values as proxies for viral load and their temporal associations with positivity rates, reproduction numbers (Rt), hospitalizations, and mortality. Cross-correlation and lagged regression analyses revealed significant lead-lag relationships, with declining Ct values consistently preceding surges in positivity rates and hospitalizations, particularly during the early phases of the pandemic.
View Article and Find Full Text PDFSeasonal Pattern of Endo-β-Mannanase Activity During Germination of , Exhibiting Morphophysiological Dormancy.
Plants (Basel)
January 2025
Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon 24341, Republic of Korea.
Morphophysiological dormancy (MPD) is considered one of the most primitive dormancy classes among seed plants. While extensive studies have examined the occurrence of endo-β-mannanase in seeds with physiological dormancy (PD) or non-dormancy, little is known about the activity of this enzyme in seeds with MPD. This study aimed to investigate the temporal and spatial patterns of endo-β-mannanase activity during dormancy break and germination.
View Article and Find Full Text PDFEstablishment and Evaluation of Atmospheric Water Vapor Inversion Model Without Meteorological Parameters Based on Machine Learning.
Sensors (Basel)
January 2025
College of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China.
Precipitable water vapor (PWV) is an important indicator to characterize the spatial and temporal variability of water vapor. A high spatial and temporal resolution of atmospheric precipitable water can be obtained using ground-based GNSS, but its inversion accuracy is usually limited by the weighted mean temperature, Tm. For this reason, based on the data of 17 ground-based GNSS stations and water vapor reanalysis products over 2 years in the Hong Kong region, a new model for water vapor inversion without the Tm parameter is established by deep learning in this paper, the research results showed that, compared with the PWV information calculated by the traditional model using Tm parameter, the accuracy of the PWV retrieved by the new model proposed in this paper is higher, and its accuracy index parameters BIAS, MAE, and RMSE are improved by 38% on average.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!