scholarly journals The effects of velocity and nitrate on Phormidium accrual cycles: a stream mesocosm experiment

2018 ◽  
Vol 37 (3) ◽  
pp. 496-509 ◽  
Author(s):  
Tara G. McAllister ◽  
Susanna A. Wood ◽  
Michelle J. Greenwood ◽  
Felix Broghammer ◽  
Ian Hawes
Keyword(s):  
Mesocosm Experiment ◽  
Stream Mesocosm

Individual and combined effects of fine sediment and glyphosate herbicide on invertebrate drift and insect emergence: a stream mesocosm experiment

2016 ◽  
Vol 35 (1) ◽  
pp. 139-151 ◽  
Author(s):  
Francis S. Magbanua ◽  
Colin R. Townsend ◽  
Kimberly J. Hageman ◽  
Jeremy J. Piggott ◽  
Christoph D. Matthaei
Keyword(s):  
Fine Sediment ◽  
Mesocosm Experiment ◽  
Invertebrate Drift ◽  
Combined Effects ◽  
Insect Emergence ◽  
Stream Mesocosm ◽  
Glyphosate Herbicide

Patterns of benthic algae and cyanobacteria along twin-stressor gradients of nutrients and fine sediment: a stream mesocosm experiment

2013 ◽  
Vol 58 (9) ◽  
pp. 1849-1863 ◽  
Author(s):  
Annika Wagenhoff ◽  
Katharina Lange ◽  
Colin R. Townsend ◽  
Christoph D. Matthaei
Keyword(s):  
Benthic Algae ◽  
Fine Sediment ◽  
Mesocosm Experiment ◽  
Stream Mesocosm

scholarly journals Drought intensification alters the composition, body size, and trophic structure of invertebrate assemblages in a stream mesocosm experiment

2019 ◽  
Author(s):  
Thomas W. H. Aspin ◽  
Kris Hart ◽  
Kieran Khamis ◽  
Alexander M. Milner ◽  
Matthew J. O'Callaghan ◽  
...  
Keyword(s):  
Body Size ◽  
Trophic Structure ◽  
Mesocosm Experiment ◽  
Stream Mesocosm ◽  
Invertebrate Assemblages

Anthropogenic stressors affect fungal more than bacterial communities in decaying leaf litter: A stream mesocosm experiment

2020 ◽  
Vol 716 ◽  
pp. 135053 ◽  
Author(s):  
Noël P.D. Juvigny-Khenafou ◽  
Yixin Zhang ◽  
Jeremy J. Piggott ◽  
David Atkinson ◽  
Christoph D. Matthaei ◽  
...  
Keyword(s):  
Leaf Litter ◽  
Bacterial Communities ◽  
Mesocosm Experiment ◽  
Anthropogenic Stressors ◽  
Stream Mesocosm

Low flow and heatwaves alter ecosystem functioning in a stream mesocosm experiment

2021 ◽  
Vol 777 ◽  
pp. 146067
Author(s):  
Raquel Arias Font ◽  
Kieran Khamis ◽  
Alexander M. Milner ◽  
Gregory H. Sambrook Smith ◽  
Mark E. Ledger
Keyword(s):  
Ecosystem Functioning ◽  
Mesocosm Experiment ◽  
Low Flow ◽  
Stream Mesocosm

scholarly journals Semi-automated classification of colonial Microcystis by FlowCAM imaging flow cytometry in mesocosm experiment reveals high heterogeneity during seasonal bloom

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yersultan Mirasbekov ◽  
Adina Zhumakhanova ◽  
Almira Zhantuyakova ◽  
Kuanysh Sarkytbayev ◽  
Dmitry V. Malashenkov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
Spatial Resolution ◽  
Mesocosm Experiment ◽  
Imaging Flow Cytometry ◽  
Leibler Divergence ◽  
Temporal And Spatial ◽  
High Level ◽  
Training Sets

AbstractA machine learning approach was employed to detect and quantify Microcystis colonial morphospecies using FlowCAM-based imaging flow cytometry. The system was trained and tested using samples from a long-term mesocosm experiment (LMWE, Central Jutland, Denmark). The statistical validation of the classification approaches was performed using Hellinger distances, Bray–Curtis dissimilarity, and Kullback–Leibler divergence. The semi-automatic classification based on well-balanced training sets from Microcystis seasonal bloom provided a high level of intergeneric accuracy (96–100%) but relatively low intrageneric accuracy (67–78%). Our results provide a proof-of-concept of how machine learning approaches can be applied to analyze the colonial microalgae. This approach allowed to evaluate Microcystis seasonal bloom in individual mesocosms with high level of temporal and spatial resolution. The observation that some Microcystis morphotypes completely disappeared and re-appeared along the mesocosm experiment timeline supports the hypothesis of the main transition pathways of colonial Microcystis morphoforms. We demonstrated that significant changes in the training sets with colonial images required for accurate classification of Microcystis spp. from time points differed by only two weeks due to Microcystis high phenotypic heterogeneity during the bloom. We conclude that automatic methods not only allow a performance level of human taxonomist, and thus be a valuable time-saving tool in the routine-like identification of colonial phytoplankton taxa, but also can be applied to increase temporal and spatial resolution of the study.

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