A fisheries acoustic multi-frequency indicator to inform on large scale spatial patterns of aquatic pelagic ecosystems

Fisheries acoustic instruments provide information on four major groups in aquatic ecosystems: fish with and without swim bladder (tertiary and quaternary consumers), fluidlike zooplankton (secondary consumers) and small gas bearing organisms such as larval fish and phytoplankton (predominantly primary producers). We entertain that this information is useable to describe the spatial structure of organism groups in pelagic ecosystems. The proposal we make is based on a multi-frequency indicator that synthesises in a single metric the shape of the acoustic frequency response of different organism groups, i.e. the dependence of received acoustic backscattered energy on emitting echosounder frequency. We demonstrate the development and interpretation of the multi-frequency indicator using simulated data. We then calculate the indicator for acoustic water-column survey data from the Bay of Biscay and use it to create reference maps for the spatial structure of the four scattering groups as well as their small scale spatial variability. These maps provide baselines for monitoring future changes in the structure of the pelagic ecosystem

Observing and modelling phytoplankton community structure in the North Sea

© Author(s) 2017. CC Attribution 3.0 License. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical-biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs

Modelling dimethylsulphide production at the Bermuda Atlantic time series (BATS)

Dimethylsulphide (DMS) is produced by upper ocean ecosystems and emitted to the atmosphere where it may have an important role in climate regulation. Several attempts to quantify the role of DMS in climate change have been undertaken in modeling studies. We examine a model of biogenic DMS production and describe its endogenous dynamics and sensitivities. We extend the model to develop a one-dimensional version that more accurately resolves the important processes of the mixed layer in determining the ecosystem dynamics. Comparisons of the results of the one-dimensional model with vertical profiles of DMS in the upper ocean measured at the Bermuda Atlantic Time Series suggest that the model represents the interaction between the biological and physical processes well. Our analysis of the model confirms its veracity and provides insights into the important processes determining DMS concentration in the oceans

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of pigments, including phycocyanin (PC) and chlorophyll-a (Chl-a), in cyanobacteria. However, such simulations were undesirable in certain cases, due to the difficulty of representing dynamically changing aerosol and water vapor in the atmosphere and the optical complexity of inland water. Thus, this study was focused on the development of a deep neural network model for AC and cyanobacteria estimation, without considering the physical formulation. The stacked autoencoder (SAE) network was adopted for the feature extraction and dimensionality reduction of hyperspectral imagery. The artificial neural network (ANN) and support vector regression (SVR) were sequentially applied to achieve AC and estimate cyanobacteria concentrations (i.e., SAE-ANN and SAE-SVR). Further, the ANN and SVR models without SAE were compared with SAE-ANN and SAE-SVR models for the performance evaluations. In terms of AC performance, both SAE-ANN and SAE-SVR displayed reasonable accuracy with the Nash???Sutcliffe efficiency (NSE) > 0.7. For PC and Chl-a estimation, the SAE-ANN model showed the best performance, by yielding NSE values > 0.79 and > 0.77, respectively. SAE, with fine tuning operators, improved the accuracy of the original ANN and SVR estimations, in terms of both AC and cyanobacteria estimation. This is primarily attributed to the high-level feature extraction of SAE, which can represent the spatial features of cyanobacteria. Therefore, this study demonstrated that the deep neural network has a strong potential to realize an integrative remote sensing application

Estimating specific inherent optical properties of tropical coastal waters using bio-optical model inversion and in situ measurements: case of the Berau estuary, East Kalimantan, Indonesia

Specific inherent optical properties (SIOP) of the Berau coastal waters were derived from in situ measurements and inversion of an ocean color model. Field measurements of water-leaving reflectance, total suspended matter (TSM), and chlorophyll a (Chl a) concentrations were carried out during the 2007 dry season. The highest values for SIOP were found in the turbid waters, decreasing in value when moving toward offshore waters. The specific backscattering coefficient of TSM varied by an order of magnitude and ranged from 0.003 m2 g-1, for clear open ocean waters, to 0.020 m2 g-1, for turbid waters. On the other hand, the specific absorption coefficient of Chl a was relatively constant over the whole study area and ranged from 0.022 m2 mg-1, for the turbid shallow estuary waters, to 0.027 m2 mg-1, for deeper shelf edge ocean waters. The spectral slope of colored dissolved organic matter light absorption was also derived with values ranging from 0.015 to 0.011 nm-1. These original derived values of SIOP in the Berau estuary form a corner stone for future estimation of TSM and Chl a concentration from remote sensing data in tropical equatorial water

Vertical distribution and composition of phytoplankton under the influence of an upper mixed layer

The vertical distribution of phytoplankton is of fundamental importance for the dynamics and structure of aquatic communities. Here, using an advection-reaction-diffusion model, we investigate the distribution and competition of phytoplankton species in a water column, in which inverse resource gradients of light and a nutrient can limit growth of the biomass. This problem poses a challenge for ecologists, as the location of a production layer is not fixed, but rather depends on many internal parameters and environmental factors. In particular, we study the influence of an upper mixed layer (UML) in this system and show that it leads to a variety of dynamic effects: (i) Our model predicts alternative density profiles with a maximum of biomass either within or below the UML, thereby the system may be bistable or the relaxation from an unstable state may require a long-lasting transition. (ii) Reduced mixing in the deep layer can induce oscillations of the biomass; we show that a UML can sustain these oscillations even if the diffusivity is less than the critical mixing for a sinking phytoplankton population. (iii) A UML can strongly modify the outcome of competition between different phytoplankton species, yielding bistability both in the spatial distribution and in the species composition. (iv) A light limited species can obtain a competitive advantage if the diffusivity in the deep layers is reduced below a critical value. This yields a subtle competitive exclusion effect, where the oscillatory states in the deep layers are displaced by steady solutions in the UML. Finally, we present a novel graphical approach for deducing the competition outcome and for the analysis of the role of a UML in aquatic systems.Comment: 20 pages, 8 figure

WISER deliverable D3.1-4: guidance document on sampling, analysis and counting standards for phytoplankton in lakes

Sampling, analysis and counting of phytoplankton has been undertaken in European lakes for more than 100 years (Apstein 1892, Lauterborn 1896, Lemmermann 1903, Woloszynska 1912, Nygaard 1949). Since this early period of pioneers, there has been progress in the methods used to sample, fix, store and analyse phytoplankton. The aim of the deliverable D3.1-4 is to select, harmonize and recommend the most optimal method as a basis for lake assessment. We do not report and review the huge number of European national methods or other published manuals for phytoplankton sampling and analysis that are available. An agreement on a proper sampling procedure is not trivial for lake phytoplankton. In the early 20th century, sampling was carried out using plankton nets. An unconcentrated sample without any pre-screening is required for quantitative phytoplankton analysis, for which various water samplers were developed. Sampling of distinct water depths or an integral sample of the euphotic zone affects the choice of the sampler and sampling procedure. The widely accepted method to quantify algal numbers together with species determination was developed by Utermöhl (1958), who proposed the counting technique using sediment chambers and inverse microscopy. This is the basis for the recently agreed CEN standard “Water quality - Guidance standard on the enumeration of phytoplankton using inverted microscopy (Utermöhl technique)” (CEN 15204, 2006). This CEN standard does not cover the sampling procedure or the calculation of biovolumes for phytoplankton species, although Rott (1981), Hillebrand et al (1999) and Pohlmann & Friedrich (2001) have contributed advice on how to calculate taxa biovolumes effectively. Willén (1976) suggested a simplified counting method, when counting 60 individuals of each species. For the Scandinavian region an agreed phytoplankton sampling and counting manual was compiled, which has been in use for about 20 years (Olrik et al. 1998, Blomqvist & Herlitz 1998). It is very unfortunate that no European guidance on sampling of phytoplankton in lakes was agreed before the phytoplankton assessment methods for the EU-WFD were developed and intercalibrated by Member States. In 2008 an initiative by the European Commission (Mandate M424) for two draft CEN standards on sampling in freshwaters and on calculation of phytoplankton biovolume was unfortunately delayed by administrative difficulties. Recently a grant agreement was signed between the Commission and DIN (German Institute for Standardization) in January 2012 to develop these standards. We believe this WISER guidance document can usefully contribute to these up-coming standards

Report of the 2005 Workshop on Ocean Ecodynamics Comparison in the Subarctic Pacific

I. Scientific Issues Posed by OECOS II. Participant Contributions to the OECOS Workshop A. ASPECTS OF PHYTOPLANKTON ECOLOGY IN THE SUBARCTIC PACIFIC Microbial community compositions by Karen E. Selph Subarctic Pacific lower trophic interactions: Production-based grazing rates and grazing-corrected production rates by Nicholas Welschmeyer Phytoplankton bloom dynamics and their physiological status in the western subarctic Pacific by Ken Furuya Temporal and spatial variability of phytoplankton biomass and productivity in the northwestern Pacific by Sei-ichi Saitoh, Suguru Okamoto, Hiroki Takemura and Kosei Sasaoka The use of molecular indicators of phytoplankton iron limitation by Deana Erdner B. IRON CONCENTRATION AND CHEMICAL SPECIATION Iron measurements during OECOS by Zanna Chase and Jay Cullen 25 The measurement of iron, nutrients and other chemical components in the northwestern North Pacific Ocean by Kenshi Kuma The measurement of iron, nutrients and other chemical components in the northwestern North Pacific Ocean by Kenshi Kuma C. PHYSICAL OCEANOGRAPHY, FINE-SCALE DISTRIBUTION PATTERNS AND AUTONOMOUS DRIFTERS The use of drifters in Lagrangian experiments: Positives, negatives and what can really be measured by Peter Strutton The interaction between plankton distribution patterns and vertical and horizontal physical processes in the eastern subarctic North Pacific by Timothy J. Cowles D. MICROZOOPLANKTON Microzooplankton processes in oceanic waters of the eastern subarctic Pacific: Project OECOS by Suzanne Strom Functional role of microzooplankton in the pelagic marine ecosystem during phytoplankton blooms in the western subarctic Pacific by Takashi Ota and Akiyoshi Shinada E. MESOZOOPLANKTON Vertical zonation of mesozooplankton, and its variability in response to food availability, density stratification, and turbulence by David L. Mackas and Moira Galbraith Marine ecosystem characteristics and seasonal abundance of dominant calanoid copepods in the Oyashio region by Atsushi Yamaguchi, Tsutomu Ikeda and Naonobu Shiga OECOS: Proposed mesozooplankton research in the Oyashio region, western subarctic Pacific by Tsutomu Ikeda Some background on Neocalanus feeding by Michael Dagg Size and growth of interzonally migrating copepods by Charles B. Miller Growth of large interzonal migrating copepods by Toru Kobari F. MODELING Ecosystem and population dynamics modeling by Harold P. Batchelder III. Reports from Workshop Breakout Groups A. PHYSICAL AND CHEMICAL ASPECTS WITH EMPHASIS ON IRON AND IRON SPECIATION B. PHYTOPLANKTON/MICROZOOPLANKTON STUDIES C. MESOZOOPLANKTON STUDIES IV. Issues arising during the workshop A. PHYTOPLANKTON STOCK VARIATIONS IN HNLC SYSTEMS AND TROPHIC CASCADES IN THE NANO AND MICRO REGIMES B. DIFFERENCES BETWEEN EAST AND WEST IN SITE SELECTION FOR OECOS TIME SERIES C. TIMING OF OECOS EXPEDITIONS D. CHARACTERIZATION OF PHYSICAL OCEANOGRAPHY V. Concluding Remarks VI. References (109 page document