Petrogenesis and mantle source characteristics of volcanic rocks on Jeju Island, South Korea

Lithos ◽  
2019 ◽  
Vol 326-327 ◽  
pp. 476-490 ◽  
Author(s):  
Ji-In Kim ◽  
Sung Hi Choi ◽  
Gi Won Koh ◽  
Jun Beom Park ◽  
Jong-Sik Ryu
Keyword(s):  
South Korea ◽  
Mantle Source ◽  
Volcanic Rocks ◽  
Jeju Island ◽  
Source Characteristics

Petrology of the late Triassic mafic volcanic rocks from the Antalya Complex, southern Turkey: evidence for mantle source characteristics during the Neotethyan rifting

2020 ◽  
Vol 29 (7) ◽  
pp. 1049-1072
Author(s):  
Utku BAĞCI ◽  
Tamer RIZAOĞLU ◽  
Güzide ÖNAL ◽  
Osman PARLAK
Keyword(s):  
Mantle Source ◽  
Volcanic Rocks ◽  
Late Triassic ◽  
Trace Element Geochemistry ◽  
Secondary Phases ◽  
Element Geochemistry ◽  
Source Characteristics ◽  
Enriched Mantle ◽  
Southern Turkey ◽  
Island Basalt

The Antalya Complex in southern Turkey comprises a number of autochthonous and allochthonous units that originated from the Southern Neotethys. Late Triassic volcanic rocks are widespread in the Antalya Complex and are important for the onset of the rifting stage of the southern Neotethys. The studied Late Triassic volcanic rocks within the Antalya Complex are exposed in the southern part of Saklıkent (Antalya) region. They are represented by pillow, massive, and columnar-jointed lava flows with volcaniclastic breccias and pelagic limestone intercalations. Spilitic basalts exhibit intersertal, microlithic porphyritic, and ophitic textures and are represented by plagioclase, pyroxene, and olivine. Secondary phases are characterized by serpentine, calcite, chlorite, epidote, zeolite, and quartz. Based on Zr/Ti vs. Nb/Y ratios, the volcanic rocks are represented by alkaline basalts (Nb/Y = 1.54–2.82). A chondrite normalized REE diagram for the volcanic rocks displays significant LREE enrichment with respect to HREE ([La/Yb]N = 15.14–19.77). Trace element geochemistry of the studied rocks suggests that these rocks are more akin to ocean island basalt (OIB) and were formed by small degrees (~2–4%) of partial melting of an enriched mantle source (spinel + garnet-bearing lherzolite). The volcanic rocks of the Saklıkent region exhibit similarities to the Late Triassic volcanics of the Koçali Complex in SE Anatolia and the Mamonia Complex (Cyprus) in terms of their geochemical features. All evidence suggests that the Late Triassic alkaline volcanics in Antalya, Mamonia (Cyprus), and the Koçali (Adıyaman) Complexes were formed in an extensional environment at the continent-ocean transition zone during the rifting of the southern Neotethyan Ocean.

scholarly journals Sm-Nd age and mantle source characteristics of the Dhanjori volcanic rocks, Eastern India.

2002 ◽  
Vol 36 (5) ◽  
pp. 503-518 ◽  
Author(s):  
A. Roy ◽  
A. Sarkar ◽  
S. Jeyakumar ◽  
S. K. Aggrawal ◽  
M. Ebihara
Keyword(s):  
Mantle Source ◽  
Volcanic Rocks ◽  
Eastern India ◽  
Source Characteristics

scholarly journals Comparison of Forest Inventory Methods at Plot-Level between a Backpack Personal Laser Scanning (BPLS) and Conventional Equipment in Jeju Island, South Korea

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 308
Author(s):  
Chiung Ko ◽  
Seunghyun Lee ◽  
Jongsu Yim ◽  
Donggeun Kim ◽  
Jintaek Kang
Keyword(s):  
South Korea ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Jeju Island ◽  
Time Data ◽  
Non Invasive ◽  
Coniferous Plantation ◽  
Standing Trees ◽  
Time Required ◽  
Inventory Method

In recent years, light detection and ranging (LiDAR) has been increasingly utilized to estimate forest resources. This study was conducted to identify the applicability of a LiDAR sensor for such estimations by comparing data on a tree’s position, height, and diameter at breast height (DBH) obtained using the sensor with those by existing forest inventory methods for a Cryptomeria japonica forest in Jeju Island, South Korea. For this purpose, a backpack personal laser scanning device (BPLS, Greenvalley International, Model D50) was employed in a protected forest, where cutting is not allowed, as a non-invasive means, simultaneously assessing the device’s field applicability. The data collected by the sensor were divided into seven different pathway variations, or “patterns” to consider the density of the sample plots and enhance the efficiency. The accuracy of estimating the variables of each tree was then assessed. The time spent acquiring and processing real-time data was also analyzed for each method, as well as total time and the time required for each measurement. The findings showed that the rate of detection of standing trees by LiDAR was 100%. Additionally, a high statistical accuracy was observed in pattern 5 (DBH: RMSE 1.22 cm, bias—0.90 cm, Height: RMSE 1.66 m, bias—1.18 m) and pattern 7 (DBH: RMSE 1.22 cm, bias—0.92 cm, Height: RMSE 1.48 m, bias—1.23 m) compared to the results from the typical inventory method. A range of 115–162.5 min/ha was required to process the data using the LiDAR, while 322.5–567.5 min was required for the typical inventory method. Thus, the application of a backpack personal LiDAR can lead to higher efficiency when conducting a forest resource inventory in a coniferous plantation with understory vegetation. Further research in various stands is necessary to confirm the efficiency of using backpack personal laser scanning.

scholarly journals Conservation, Restoration, and Sustainable Use of Biodiversity Based on Habitat Quality Monitoring: A Case Study on Jeju Island, South Korea (1989–2019)

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 774
Author(s):  
Hyun-Jung Hong ◽  
Choong-Ki Kim ◽  
Hyun-Woo Lee ◽  
Woo-Kyun Lee
Keyword(s):  
South Korea ◽  
Habitat Quality ◽  
Sustainable Use ◽  
Habitat Type ◽  
Biodiversity Loss ◽  
Well Being ◽  
Jeju Island ◽  
Natural Habitats ◽  
Invest Model ◽  
Aichi Biodiversity Targets

Biodiversity loss is progressing despite biodiversity being essential for human survival, prosperity, and well-being. Conservation, restoration, and sustainable use of the habitat, given that its change is the most prominent factor causing the deterioration of biodiversity, represents a highly effective way of securing biodiversity. Therefore, we assessed and monitored habitat quality as a proxy for biodiversity with habitat quantity in Jeju Island, South Korea. We used an InVEST model with data on the habitat type, suitability, sensitivity, accessibility, and threat factors. Natural habitats throughout Jeju had rapidly decreased in area by 24.9% from 1989 to 2019, and this change contributed to the degradation of habitat quality by 15.8%. We provided significant evidence on the critical degradation of habitat for a long period of over 30 years and highlighted the urgent need for policies and behaviors that enhance biodiversity. We proposed appropriate strategies to prompt people to conserve better, restore effectively, and use biodiversity sustainably. We expect that our findings will provide scientific and evidence-based guidance for policy-making on biodiversity enhancement and will further support achievement of the Sustainable Development Goals and Aichi Biodiversity Targets, in addition to compliance with the New Deal for Nature and People.

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