The Effects of Alewife on the Zooplankton Community in Townhouse Pond

The purpose of this study was to determine what plankton species was more dominant in Townhouse Pond and what effects predation has on the food web. Plankton size is important when determining pelagic food web structure. Plankton size along with predation determines whether the lake is dominated by top-down or bottom-up control. Plankton size and biomass, grazing rates, light intensity, and chemistry parameters were all determined for Townhouse Pond in October 2008. We concluded that Townhouse Pond is a mesotrophic lake and is mainly dominated by phytoplankton, such as Microystis and Dinobryon. Alewife (Alosa pseudoharengus), planktivorous fish, are dominant in this pond resulting in top-down control. Although various studies were conducted here, further research could determine the abundance of alewife and their prey and specific parameter that effect their predation

Some aspects of the ecology of the limnoplankton, with special reference to the phytoplankton. [Translation from: Svensk Botanisk Tidskrift 13(2) 129-163, 1919.]

This paper tries to develop more generally some fundamental bases for the ecological study of freshwater plankton. A special attention is given to the phytoplankton associations which can be separated out and made into groups according to their dependence upon changing environments. Plankton formations in different types of water bodies (ponds, lakes and rivers) are studied

Planktonic communities and chaotic advection in dynamical models of Langmuir circulation

A deterministic mechanism for the production of plankton patches within a typical medium scale oceanic structure is proposed and investigated. By direct numerical simulation of a simple model of Langmuir circulation we quantify the effects of unsteady flows on planktonic communities and demonstrate their importance. Two qualitatively different zones within the flow are identified: chaotic regions that help to spread plankton and locally coherent regions, that do not mix with the chaotic regions and which persist for long periods of time. The relative importance of these regions to both phytoplankton and zooplankton is investigated, taking into account variations in plankton buoyancy. In particular, species-specific retention zone structure is discussed in relation to variations in environmental forcing

Long-Term Trends in Calcifying Plankton and pH in the North Sea

Relationships between six calcifying plankton groups and pH are explored in a highly biologically productive and data-rich area of the central North Sea using time-series datasets. The long-term trends show that abundances of foraminiferans, coccolithophores, and echinoderm larvae have risen over the last few decades while the abundances of bivalves and pteropods have declined. Despite good coverage of pH data for the study area there is uncertainty over the quality of this historical dataset; pH appears to have been declining since the mid 1990s but there was no statistical connection between the abundance of the calcifying plankton and the pH trends. If there are any effects of pH on calcifying plankton in the North Sea they appear to be masked by the combined effects of other climatic (e.g. temperature), chemical (nutrient concentrations) and biotic (predation) drivers. Certain calcified plankton have proliferated in the central North Sea, and are tolerant of changes in pH that have occurred since the 1950s but bivalve larvae and pteropods have declined. An improved monitoring programme is required as ocean acidification may be occurring at a rate that will exceed the environmental niches of numerous planktonic taxa, testing their capacities for acclimation and genetic adaptation

Automatic plankton quantification using deep features

The study of marine plankton data is vital to monitor the health of the world’s oceans. In recent decades, automatic plankton recognition systems have proved useful to address the vast amount of data collected by specially engineered in situ digital imaging systems. At the beginning, these systems were developed and put into operation using traditional automatic classification techniques, which were fed with handdesigned local image descriptors (such as Fourier features), obtaining quite successful results. In the past few years, there have been many advances in the computer vision community with the rebirth of neural networks. In this paper, we leverage how descriptors computed using Convolutional Neural Networks (CNNs) trained with out-of-domain data are useful to replace hand-designed descriptors in the task of estimating the prevalence of each plankton class in a water sample. To achieve this goal, we have designed a broad set of experiments that show how effective these deep features are when working in combination with state-of-the-art quantification algorithms

The efficiency of plankton in the utilization of the sun radiation [Translation from: Briroda, 12, 29-35, 1948]

The efficiency of utilisation of the sun's radiation by natural communities has not been properly demonstrated with what so far has been obtained of reliable values, and it represents a great interest in many respects. A systematic study of the biotic balance of lakes was done in the course of a succession of summers starting in 1932, extensive material was obtained, which permitted to compute a value fear the utilisation of the sun's radiation by plankton in lakes, and to compare this with corresponding values for marine plankton and terrestrial vegetation

Plankton Tow Project

This activity focuses on constructing a plankton net using materials found around the house. Students must think of items that could be used for the different parts of the plankton net, including towing bridle, hoop or collar, filtering material, and collector. Each component has its own thought-provoking questions to help students understand its function and why it is important to the system. The two supplemental worksheets are available from the COSEE-NE OSEI resource site. Educational levels: Middle school, High school

The continuous plankton recorder survey: A long-term, basin-scale oceanic time series

In the 1920s, before the advent of echo sounders, fishery biologists were greatly concerned with assisting the fisherman to locate schools of pelagic fish. One of the approaches they developed was to relate the distribution of the planktonic food organisms to the presence of the schools of predators such as herring (Clupea harengus). The British planktologist, Alister Hardy, who had already carried out extensive studies on the feeding preferences of herring (Hardy, 1926a), initiated a program to examine the fishermen's contention that herring schools avoided 'green', i.e., phytoplankton-rich, water but could be correlated with high concentrations of zooplankton. This practical program was centered on the use of a specially developed instrument, the 'Plankton Indicator', designed to be used by the fisherman to assist in the search for suitable waters. It had limited success in its main aim but, as a collecting device, it embodied several profoundly important features. It was a simple instrument which was robust enough to be deployed and recovered by the crew of commercial vessels (in this case fishing vessels) while they were underway. The Indicator however, was no more than a high speed net which integrated the plankton over the area of sampling, but Hardy had also become interested in describing the patchiness of planktonic populations. He thus developed the Continuous Plankton Recorder (CPR) where he substituted the fixed filter screen of the Indicator by a continually moving length of silk mesh. The screen traversed at constant speed across the path of the incoming water and the trapped organisms were retained in place by sandwiching beneath an additional second mesh screen. Thus, knowing the speed of the towing vessel and the shooting and hauling positions, the spatial patterns of the plankton could be determined. Hardy took the first CPR to the Antarctic where he used it in the Southern Atlantic (Hardy, 1926b) and later deployed it in the North Sea to make some of the earliest contiguous records of plankton patchiness

Phytoplankton Hotspot Prediction With an Unsupervised Spatial Community Model

Many interesting natural phenomena are sparsely distributed and discrete. Locating the hotspots of such sparsely distributed phenomena is often difficult because their density gradient is likely to be very noisy. We present a novel approach to this search problem, where we model the co-occurrence relations between a robot's observations with a Bayesian nonparametric topic model. This approach makes it possible to produce a robust estimate of the spatial distribution of the target, even in the absence of direct target observations. We apply the proposed approach to the problem of finding the spatial locations of the hotspots of a specific phytoplankton taxon in the ocean. We use classified image data from Imaging FlowCytobot (IFCB), which automatically measures individual microscopic cells and colonies of cells. Given these individual taxon-specific observations, we learn a phytoplankton community model that characterizes the co-occurrence relations between taxa. We present experiments with simulated robot missions drawn from real observation data collected during a research cruise traversing the US Atlantic coast. Our results show that the proposed approach outperforms nearest neighbor and k-means based methods for predicting the spatial distribution of hotspots from in-situ observations.Comment: To appear in ICRA 2017, Singapor