Project Details
Projekt
Assessing species distributions and morphometrics in Southern Ocean diatoms using high throughput imaging and semi-automated image analysis
Subject Area
Oceanography
Term
from 2014 to 2019
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 257060905
Diatoms are the dominant primary producers of the Southern Ocean (SO), strongly influencing ecological and biogeochemical processes in this extensive pelagic habitat. Both occurrence of individual species, and morphometric features of some of them, are related to water mass properties, and, through the latter, to climatic changes. Accordingly, both assemblage composition and species-specific morphometrics are heavily used as indicators of past climatic changes. On the other hand, ongoing climate change affects SO oceanography, and through that, also diatom distributions, which in turn affect food web structure and biogeochemical cycles. The central tool in studies of diatom-environment relationships has been light microscopy (LM), whether for development / application of proxies or for learning about current and future distribution ranges. LM, practiced in the traditional way, has numerous issues, including low throughput, requirement of highly qualified taxonomic experts, and problems related data archival / quality and reproducibility. To address these issues, the applicants of this project have recently started a collaboration bringing together high throughput light microscopy and automated image analysis methods for morphometric characterization and assemblage composition assessment of diatoms. Within the first 9 months of this collaboration, we successfully established workflows for high throughput, semi-automated microscopic imaging of diatom specimens on permanent slides; developed software (under publication) for automated detection and outline characterization of diatom valves providing the possibility for manual interaction and quality control; tested the extraction of texture features from diatom images; and performed first tests using machine learning methods for the taxonomic classification of diatoms based on the morphometric features extracted by the above methods. These methods allow us to photograph and analyze large numbers of diatom slides combining the throughput of automated methods with the stringency of manual quality control. Here we propose to apply these methods to the extensive collection of SO samples of the Hustedt Diatom Study Centre to characterize the geographic distribution and morphometrics of abundant planktonic SO diatom species, and to relate them to environmental parameters using statistical techniques. The work proposed will allow us to validate distribution models using presence-absence data for the first time for diatoms species, and to explore morphometric trends related to environmental parameters across multiple species, which might open novel possibilities for the development of robust paleo-oceanographic proxies.
DFG Programme
Infrastructure Priority Programmes
Subproject of
SPP 1158:
Infrastructure area - Antarctic Research with Comparative Investigations in Arctic Sea Ice Areas
Participating Person
Dr. Rainer Gersonde
