Seasonal variations in biomass and species composition of seaweeds along the northern coasts of Persian Gulf (Bushehr Province)

Abstract

This study was carried out to evaluate the seasonal variations of seaweed biomass and species composition at six different sites along the coastal areas in Bushehr Province. Sampling depths varied among sites, from 0.3 to 2.0 m below mean sea level. A total of 37 (i.e., 10 Chlorophyta, 12 Phaeophyta and 15 Rhodophyta) seaweed species were collected. Studies were conducted for quantifying the seaweeds during four seasons from October 2008 until July 2009. During present research, Ulva intestinalis and Cladophora nitellopsis of green, Polycladia myrica, Sirophysalia trinodis and Sargassum angustifolium of brown and Gracilaria canaliculata and Hypnea cervicornis of red seaweeds showed highest biomass in coastal areas of Bushehr Province. The Cheney's ratio of 2.1 indicated a temperate algal flora to this area. All sites exhibited more than 50% similarity of algal species, indicating a relatively homogenous algal distribution. Total biomass showed the highest value of 3280.7 ± 537.8 g dry wt m −2 during summer and lowest value of 856.9 ± 92.0 g dry wt m −2 during winter. During this study, the highest and lowest seaweed biomass were recorded on the site 2 (2473.7 ± 311.0 g dry wt m −2) and site 5 (856.7 ± 96.8 g dry wt m −2), respectively.

Zonation patterns, composition and diversity of macroalgal communities in the eastern coasts of Qeshm Island, Persian Gulf, Iran

“…This resut is not unexpected and has been previously documented (Thongroy et al 2007;Raffo et al 2014). Moreover, the values of the Shannon-Wiener diversity index (H') obtained in this study (between 1.11 and 1.95) were considerably lower than those of Dadolahi-Sohrab et al, (2012) reported from the northern coasts of Persian Gulf in Bushehr province (between 2.28 and 2.87). Both urbanization and substratum can cause such a low diversity in the eastern coast of Qeshm Island.…”

“…Hence, the result of this study which showed the highest biomass of macroalgae in winter may be attributable to increased nutrient availability in this season. Dadolahi-Sohrab et al, (2012) also demonstrated that the period of maximum algal growth is late winter to mid-summer along the northern coasts of the Persian Gulf. In our study, the BIOENV analysis indicated chemical parameters (TDS and pH) as significantly influencing the macroalgal communities along the easthern cost of Qeshm Island.…”

“…The previous studies have focused on the biomass variation and diversity of seaweeds among seasons, whereas the species composition in different seasons and the role of specific macroalgae in the variation of community were neglected. The only previous quantitative study on variation in biomass and seaweed diversity using univariate analysis was undertaken by Dadolahi-Sohrab et al (2012). The purpose of this study, therefore, was to provide the first comprehensive quantitative investigation of vertical and seasonal changes in the composition and structure of macroalgae at a local scale with regard to community structure and composition.…”

Hubungan Substrat Dasar Perairan Dengan Kehadiran Rumput Laut Alam Di Perairan Ujung Genteng, Sukabumi, Jawa Barat

“…Alga coklat memiliki kemampuan untuk beradaptasi karena memiliki lapisan lendir (mucus) yang dapat mengatasi kekurangan air, serta memiliki toleransi terhadap pasang surut yang lebih lama (Dadolahi-Sohrab et al, 2012), sehingga pada perairan Ujung Genteng distribusinya dapat ditemukan berada pada ketiga kawasan pengamatan. Jenis alga yang paling banyak ditemukan di kawasan perairan Ujung Genteng adalah alga merah, yaitu 13 jenis ditemukan di kawasan-2, 11 jenis di kawasan-3, dan sembilan jenis di kawasan-1.…”

“…Jenis rumput laut yang berbeda akan memiliki kemampuan terbaik agar bisa bertahan Gambar 3. Rata-rata tutupan substrat dasar perairan pada tiga kawasan pengamatan di perairan Ujung Genteng, Jawa Barat (L: lamun, P: pasir, K: karang hidup, PK: pecahan karang, BK: batu karang, SW: seaweed) (huruf yang berbeda menunjukkan hasil uji yang berbeda nyata (P<0,05)) di lokasi yang berbeda dengan cara seoptimal mungkin (Dadolahi-Sohrab et al, 2012).…”