The pressures and the ecological quality status of the Marmara Sea (Turkey) by using marine macroalgae and angiosperms

Taşkın, Ergün; Tan, İbrahi̇m; Minareci, Orkide; Minareci, Ersin; Polat-Beken, Çolpan; Atabay, Hakan

doi:10.36253/978-88-5518-147-1.63

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Until the thesis study on which this article data is based, no record of P. morrowii was found for the Sea of Marmara (Çetin 2014). P. morrowii was also detected in different studies in Marmara waters in the following years (Taşkın 2016, Taşkın et al 2018, Taşkın et al 2019, Taşkın 2022. It is stated that it was transported to this region by ship and ballast waters, and it is also an invasive/alien red algae species (Taşkın 2022).…”

Section: Discussionmentioning

confidence: 79%

Polysiphonia morrowii Harvey'nin Biyokimyasal ve Fizyolojik Özellikleri Üzerinde Etkili Bir Parametre: Tuzluluk Stresi

ÖZEN,

YILDIZ,

DERE

2023

Afyon Kocatepe University Journal of Sciences and Engineering

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In recent years, rising temperatures due to global climate change can constitute a decrease in salinity in the oceans by causing the ice to melt early and freeze late in its annual cycle and increased precipitation. On the other hand, high temperatures can increase the salinity of seawater locally by enhancing evaporation. It is expected that the changes in salinity of sea water would affect communities of seaweeds. In this study, Polysiphonia morrowii Harvey samples were collected from Altıntaş station in the Gulf of Gemlik in April 2013, and cultured in mediums with four different salt concentrations (10‰, 23‰, 33‰, 42‰). The changes of this species in the amounts of total protein, total phenol, phycocyanin (PC), phycoerythrin (PE), chlorophyll-a (Chl a), water-soluble antioxidant, oil-soluble antioxidant, total solid organic matter and the activity of the carbonic anhydrase were determined. The study clearly showed that studied biochemical and physiological properties of the species were affected by salinity changes. It is also detected that P. morrowii is a tolerant species that can adapt to changing salinity conditions with various defense strategies.

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Section: Discussionmentioning

confidence: 79%

Polysiphonia morrowii Harvey'nin Biyokimyasal ve Fizyolojik Özellikleri Üzerinde Etkili Bir Parametre: Tuzluluk Stresi

ÖZEN,

YILDIZ,

DERE

2023

Afyon Kocatepe University Journal of Sciences and Engineering

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“…The island's coastline presents a diverse range of habitats and ecosystems, including rocky shores, sandy beaches, and seagrass beds. The waters are relatively shallow, with an average depth of 5 m. The water quality is generally good, but there are some concerns about pollution from nearby sources [26]. The island's coastline presents a diverse range of habitats and ecosystems, includin rocky shores, sandy beaches, and seagrass beds.…”

Section: Study Areamentioning

confidence: 99%

Improving the Accuracy of Satellite-Derived Bathymetry Using Multi-Layer Perceptron and Random Forest Regression Methods: A Case Study of Tavşan Island

Çelik,

Büyüksalih,

Gazioğlu

2023

JMSE

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The spatial and spectral information brought by the Very High Resolution (VHR) and multispectral satellite images present an advantage for Satellite-Derived Bathymetry (SDB), especially in shallow-water environments with dense wave patterns. This work focuses on Tavşan Island, located in the Sea of Marmara (SoM), and aims to evaluate the accuracy and reliability of two machine learning (ML) regression methods, Multi-Layer Perceptron (MLP) and Random Forest (RF), for bathymetry mapping using Worldview-2 (WV-2) imagery. In situ bathymetry measurements were collected to enhance model training and validation. Pre-processing techniques, including water pixel extraction, sun-glint correction, and median filtering, were applied for image enhancement. The MLP and RF regression models were then trained using a comprehensive dataset that included spectral bands from the satellite image and corresponding ground truth depth values. The accuracy of the models was assessed using metrics such as Root-Mean-Square Error (RMSE), Mean Absolute Error (MAE), and R2 value. The RF regression model outperformed the MLP model, with a maximum R2 value of 0.85, lowest MAE values from 0.65 to 1.86 m, and RMSE values from 0.93 to 2.41 m at depth intervals between 6 and 9 m. These findings highlight the effectiveness of ML regression methods, specifically the RF model, for SDB based on remotely sensed images in wave-dense shallow-water environments.

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The pressures and the ecological quality status of the Marmara Sea (Turkey) by using marine macroalgae and angiosperms

Cited by 2 publications

References 7 publications

Polysiphonia morrowii Harvey'nin Biyokimyasal ve Fizyolojik Özellikleri Üzerinde Etkili Bir Parametre: Tuzluluk Stresi

Polysiphonia morrowii Harvey'nin Biyokimyasal ve Fizyolojik Özellikleri Üzerinde Etkili Bir Parametre: Tuzluluk Stresi

Improving the Accuracy of Satellite-Derived Bathymetry Using Multi-Layer Perceptron and Random Forest Regression Methods: A Case Study of Tavşan Island

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