scholarly journals Habitat preference, movements and growth of giant mottled eels, Anguilla marmorata, in a small subtropical Amami-Oshima Island river

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10187
Author(s):  
Hikaru Itakura ◽  
Ryoshiro Wakiya

Although anguillid eel populations have decreased remarkably in recent decades, few detailed ecological studies have been conducted on tropical eels such as the giant mottled eel whose range extends across the whole Indo-Pacific. This species was studied throughout the entire 0.5 km mainstem reaches of Oganeku River on the subtropical Amami-Oshima Island of Japan over a two-year period using four sampling periods to understand its habitat preference, early life-stage dispersal process, movements, and annual growth using a mark-recapture experiment conducted with quantitative electrofishing. A total of 396 juvenile growth-phase A. marmorata eels were caught and tagged, with 48 individuals being recaptured at least once. Their density irrespective of size of eels was most strongly determined by distance from the river mouth, followed by riverbank type according to random forest models. Eel density decreased with increasing distance from the freshwater tidal limit located about 100–150 m from the river mouth. Eels preferred vegetated riverbanks, while they avoided those of concrete and sand. The density of small eels (total length: TL < 240 mm) was also associated with depth and velocity, with small eels tending to prefer riffle or run habitats. In contrast, large eels (TL ≥ 240 mm) were found in habitats of any depth and velocity. The TL of eels had a minimum peak at around the tidal limit, and it increased with increasing distance from the tidal limit. The observed density and size gradients of eels in relation to the distance from the river mouth suggested that A. marmorata initially recruited to freshwater tidal limit areas and then dispersed in both downstream and upstream directions. The growth rate of eels varied greatly among individuals that were at large for various periods of time and ranged from 0 to 163.2 mm/year (mean ± SD of 31.8 ± 31.0 mm/year). Of the recaptured eels, 52.1% were recaptured in a section that was different from the original capture section, and their mean ± SD distance travelled was 46.5 ± 72.5 m (median = 20 m). 47.9% of the eels were recaptured from the original section of capture (i.e., <10 m distances travelled), suggesting that they had strong fidelity to specific habitats with limited movements. The distance travelled of eels that had moved was greater for small eels (range = 10–380 m; mean ± SD = 84.4 ± 121.9 m) than large individuals (range = 10–120 m; mean ± SD = 30.9 ± 31.0 m), which indicates that the mobility of the eels declines as they grow. This is the first clear detailed documentation of the spatial distribution, growth, and movements of tropical eels in a small river system in relation to environmental conditions that provides an example of how future studies can be conducted in other areas to understand how conservation efforts can be most efficiently targeted for maximum success.

2021 ◽  
Vol 322 ◽  
pp. 01006
Author(s):  
Didit Abdillah ◽  
Charles P.H. Simanjuntak ◽  
Muhammmad. F. Rahardjo ◽  
Djumanto ◽  
Neri Kautsari ◽  
...  

The coastal ecosystem plays a vital role as essential habitat for juvenile and small marine fishes. This study aimed to analyze juvenile and small-sized fish assemblage in the nearshore habitats of Sumbawa Island. Sampling was carried out in the morning at low tide when new and full moon from November 2020 to January 2021. Five sampling sites were selected based on habitats their adjacency to the river mouth. During the study period, 6349 individuals belonging to 74 species and 37 families were recorded. The number of Ambassis vachellii was the most significant, followed by Hypoatherina temminckii, and Eubleekeria splendens. The highest fish biomass was occupied by E. splendens, followed by Plotosus lineatus, and Planiliza macrolepis. Physico-chemical parameters were not varied between sampling sites, except salinity. Estuaries with vegetated areas have a higher species richness, diversity, and evenness index than the unvegetated area. Juvenile and small-sized fishes varied between sites but not varied between moon phases. Research findings confirm that the nearshore habitat of Sumbawa Island has a significant capacity to support the early life stage of many marine fish species.


Author(s):  
Robyn J. Wright ◽  
Morgan G. I. Langille ◽  
Tony R. Walker

Abstract It is now indisputable that plastics are ubiquitous and problematic in ecosystems globally. Many suggestions have been made about the role that biofilms colonizing plastics in the environment—termed the “Plastisphere”—may play in the transportation and ecological impact of these plastics. By collecting and re-analyzing all raw 16S rRNA gene sequencing and metadata from 2,229 samples within 35 studies, we have performed the first meta-analysis of the Plastisphere in marine, freshwater, other aquatic (e.g., brackish or aquaculture) and terrestrial environments. We show that random forest models can be trained to differentiate between groupings of environmental factors as well as aspects of study design, but—crucially—also between plastics when compared with control biofilms and between different plastic types and community successional stages. Our meta-analysis confirms that potentially biodegrading Plastisphere members, the hydrocarbonoclastic Oceanospirillales and Alteromonadales are consistently more abundant in plastic than control biofilm samples across multiple studies and environments. This indicates the predilection of these organisms for plastics and confirms the urgent need for their ability to biodegrade plastics to be comprehensively tested. We also identified key knowledge gaps that should be addressed by future studies.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yansheng Tian ◽  
Tong Hao ◽  
Bin Cao ◽  
Wei Zhang ◽  
Yan Ma ◽  
...  

There is a recent emerging theory that suggests a cross-link between pathogens and cancer. In this context, we examined the association between theMycobacterium tuberculosis(MTB) with its L-forms (MTB-L) and lung cancer. In the present study, we have optimized and applied a highly sensitive assay to detect the presence of MTB and MTB-L in 187 lung cancer samples and 39 samples of other cancer origins. By carefully controlling confounding factors, we have found that 62% of the lung cancer samples are MTB-L positive, while only 5.1% of the other cancer samples are MTB-L positive. Through generalized linear models and random forest models, we have further identified a set of clinical end-points that are strongly associated with MTB-L presence. Our finding provides the basis for future studies to investigate the underlying mechanism linking MTB-L infection to lung cancer development.


Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 109
Author(s):  
Ashima Malik ◽  
Megha Rajam Rao ◽  
Nandini Puppala ◽  
Prathusha Koouri ◽  
Venkata Anil Kumar Thota ◽  
...  

Over the years, rampant wildfires have plagued the state of California, creating economic and environmental loss. In 2018, wildfires cost nearly 800 million dollars in economic loss and claimed more than 100 lives in California. Over 1.6 million acres of land has burned and caused large sums of environmental damage. Although, recently, researchers have introduced machine learning models and algorithms in predicting the wildfire risks, these results focused on special perspectives and were restricted to a limited number of data parameters. In this paper, we have proposed two data-driven machine learning approaches based on random forest models to predict the wildfire risk at areas near Monticello and Winters, California. This study demonstrated how the models were developed and applied with comprehensive data parameters such as powerlines, terrain, and vegetation in different perspectives that improved the spatial and temporal accuracy in predicting the risk of wildfire including fire ignition. The combined model uses the spatial and the temporal parameters as a single combined dataset to train and predict the fire risk, whereas the ensemble model was fed separate parameters that were later stacked to work as a single model. Our experiment shows that the combined model produced better results compared to the ensemble of random forest models on separate spatial data in terms of accuracy. The models were validated with Receiver Operating Characteristic (ROC) curves, learning curves, and evaluation metrics such as: accuracy, confusion matrices, and classification report. The study results showed and achieved cutting-edge accuracy of 92% in predicting the wildfire risks, including ignition by utilizing the regional spatial and temporal data along with standard data parameters in Northern California.


2021 ◽  
Author(s):  
Patrick M. Graham ◽  
James S. Franks ◽  
Evan J. Anderson ◽  
Robert T. Leaf ◽  
Jason D. Tilley

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