COLLEGE OF ARTS AND SOCIAL SCIENCE ADI- KEIH Department of Geography Program Geoinformatics Master of Science degree

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1 COLLEGE OF ARTS AND SOCIAL SCIENCE ADI- KEIH Department of Geography Program Geoinformatics Master of Science degree Spatial and seasonal variability of phytoplankton concentration in the territorial waters of Eritrean Red Sea by Hadgu Eyesab K. Advisor: Dr. Zekeria Abdelkerim Zekeria 12 March

2 Spatial and seasonal variability of phytoplankton concentration in the territorial waters of Eritrean Red Sea 2

3 The name Red Sea: Introduction Greek word Erythra Thalassa means Red Sea. Most scholars agree due to the seasonal bloom of phytoplankton microscopic red algae (Trichodesmium erythraeum) 3

4 The Red Sea is semi enclosed, warm, saline and oligotrophic water body bounded by arid region. 4

5 Phytoplankton Phytoplankton: drifting, photosynthetic, microscopic Base of marine food chain. They provide food, directly or indirectly, for virtually every other marine creature. 90%- 96% of the surface ocean carbohydrates Produce food as equal as all land plants. contribute 50% of the food made by photosynthesis on the planet. bind 50 trillion kilograms of carbon into carbohydrates/year O 2, CO 2 reduce global worming 5

6 Objectives of the study 1. to investigate spatial and temporal patterns of primary productivity based on remote sensing and in-situ data sets. 2. To map monthly surface Chl-a and SST. 3. Evaluate the correlation between SST and Chl-a and how the phytoplankton abundance are influences by SST. 6

7 Study Area Satellite study area 7

8 In-situ study area Most accessible part of the coast. most Eritrean maritime activities take place Better and health coral reefs coverage most bio divers Annually the largest fisheries catch 8

9 Methodology Two independent methods for Productivity 1. Chl-a and SST in-situ data 2. Satellite data (Chl-a and SST) Chl-a in-situ data Study period = (June/2017 to January/2018) There area 10 sampling points in the study area (Massawa to Dahlak). 9

10 Laboratory analysis A. Filtration GF/F watmans filter paper 0.45µm pore size 10

11 B. pigment extraction 10ml o 90% acetone In defreezer C for15 hrs GIERI PROJECT MASTERS OF SCIENCE IN 11

12 C. Centrifuging and Spectrophotometry (665nm and 750nm) GIERI PROJECT MASTERS OF SCIENCE IN 12

13 D. Chl-a calculation chl a in µg/l = 11.9 (A665 A750) LS 1000V Where: A665 = absorbance at a wavelength of 665 nm; A750 = absorbance at a wavelength of 750 nm. S = the volume of water sample filtered (ml) V = the volume of acetone used for the extraction (ml) L = the length of light path in the spectrophotometer in (cm) GIERI PROJECT MASTERS OF SCIENCE IN 13

14 2. Temperature 1. Surface temperature of 1.5 m depth was measure by deploying HOBOware tools This tool was programed to measure at every 30 Min interval for 8 months Analyzed by: 14

15 3. Remote Sensing data sets 1. Daily Chl-a from OC-CCI Products ESA Merged Products of MODIS, VIIRS, SeaWiFS, MERIS has better temporal resolution 2. SST from MODIS, To avoid the solar radiation bias in SST during day-time, only the nighttime product was acquired. 15

16 Image processing OC-CCI MODIS 8 day SST daily Chl-a Monthly Merging Monthly Merging Monthly average image Time series SST analysis Monthly average image Time series Chl-a analysis Correlation b/n SST & Chl-a 16

17 Software utilized 17

18 Result and discussion GIERI PROJECT MASTERS OF SCIENCE IN 18

19 Monthly time series Chl-a Monthly Chl-a The highest productivity was observed in the summer season(july and August) and winter season (January) The lowest was in June and October 19

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21 Instruction of GAIW regulates summer pick and GASW regulates winter pick Monsoon wind regime 21

22 Place wise As we move close to land there is high productivity Land induced nutrients Shallow-no thermocline the study area in the whole study time 22

23 In-situ SST GIERI PROJECT MASTERS OF SCIENCE IN 23

24 Satellite SST GIERI PROJECT MASTERS OF SCIENCE IN 24

25 r/n ship b/n SST and Chl-a Except in the summer season temperature and Chl-a are inversely related 25

26 Conclusion Chl-a high- in summer (July) and winter (January) low in Jun and October Coastal area are more productive than offshore Temperature is high in summer months and decreases toward winter SST and Chl-a are directly related in summer and indirectly related in winter GIERI PROJECT MASTERS OF SCIENCE IN 26

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