<link https: uol.de suche>Prof. Dr. Pedro Martinez-Arbizu
Institute of Biology and Environmental Sciences (IBU)
Phone +49 (0)4421 9475 100
PI: Pedro Martinez Arbizu, Co-PI Gabriele Gerlach
Understanding biodiversity patterns of marine benthic meiofauna is difficult because the number of species in usually very high and identification of species is requires advanced taxonomic expertise. In recent years, molecular barcoding, meaning the characterization of species using the sequence of the mitochondrial COI gene, has repeatedly been claimed as a method for fast and accurate species identification. However barcoding has never grew up over the state of pilot studies and has not been used in massive routine species identifications. Reason for this is the relatively high specimen handling time is (DNA-extraction, PCR, sequencing), the taxon biased amplification success of COI and the relatively high costs per specimen. Maldi-Tof (Matrix-assisted laser desorption/ionization – Time of flight) has proved to produce species specific fingerprints of proteome spectra for metazoans. Maldi-Tof analyses are quick and cheap and can become a versatile alternative to molecular barcoding.
Quick specimen identification will allow faster processing of a higher number of benthic samples, thus increasing other understanding of how environmental factors structure species ranges and biodiversity patterns. Modelling the distribution of species will allow predicting the probability of species presence in space and time.
The PhD candidate will work on following specific tasks: During the first year, a gene and Maldi library will be produced for 300 benthic copepod and 300 nematode species living in the North Sea. Each species will be identified morphologically, photographed, and COI-gene will be amplified. In addition a Maldi-Tof proteome fingerprint will be produced. Main questions to address are i) how accurate is Madi-Tof for species identification in relation to live-stage and gender, season and fixative used ; ii) which clustering and machine learning methods perform better for species discrimination using Maldi-Tof spectra ?
During the second year, the Maldi-Tof species identification protocols will be tested to characterize the meiofauna communities and meiofauna diversity patterns in the German EEZ. To achieve this, several cruises are planned in the North Sea with FS Senckenberg and other vessels. Main questions to be addressed during second years are: How environmental factors structure meiofauna diversity in the North Sea?, are there distinct and predictable meiofauna communities in the North Sea and how are they spatially distributed?
During the third year, the dataset of species records and environmental factors produced during year 2, will be used to predict the distribution of each species on the whole North Sea using species distribution models (randomForest, Maxent).