Abstract. Kusnadi A, Kurnianto D, Madduppa H, Zamani NP, Ibrahim PS, HernawanU E, Utami RT, Triandiza T. 2022. Genetic diversity and population structure of the boring giant clam (Tridacna crocea) in Kei Islands, Maluku, Indonesia. Biodiversitas 23: 1273-1282. Giant clams (Tridacninae) are ecologically important species in the coral reef ecosystems. They provide valuable functionsto traditional fisheries in Kei Islands, Maluku. However, their population isunder great pressure due to anthropogenic threats, such as overfishing and habitat degradation. To provide important data for devising effective conservation management strategies for giant clams, we investigated genetic diversity and population structure of the boring giant clams Tridacna croceain Kei Islands based on partial mitochondrial COI gene sequence. Tissue samples were collected from six sites: Kur, Dullah Laut, Tanimbar Kei, Dar, Labetawi, and Difur. We sequenced 477 base pairs of COI gene and identified 42 haplotypes and 52 polymorphic sites. Analysis of genetic diversity showed Dullah Laut and Dar had the highest genetic diversity. Population structure and genetic distance analysis showed unstructured populations with high genetic closeness among sites. This finding was also confirmed by the mixture pattern of the haplotype network. Further analysis using Bayesian models on gene flow revealed high genetic exchange among sites and that Dullah Population predominantly served as a source site for the other sites. This indicated a high probability of successful larval dispersal among sites. Based on these findings, we predict that the boring giant clams likely form a single population in Kei Islands. Our study warrants conservation priority for Dullah population as the main source of gene flow.
Abstract. Fitrian T, Madduppa H, Ismet MS, Rahayu DL. 2022. Taxonomy and molecular phylogeny analysis of the genus Diogenes “Edwardsii group” (Decapoda: Anomora: Diogenidae) based on mitochondrial DNA sequences. Biodiversitas 23: 5302-5313. Many variations of morphological characters differ from one species to another, showing high interspecific variation within the genus Diogenes Dana, 1851. Subtle morphological differences among certain species make it difficult to identify diagnostic characters. Although the genus is very speciose, the study on the molecular is poorly reported. This study aimed to evaluate the taxonomy and phylogeny of the genus Diogenes using morphological and molecular features. The molecular phylogeny of 15 species of Diogenes included in the "Edwardsii group" was constructed based on two mitochondrial genes COI and 16S rRNA. The results of the phylogeny tree construction based on concatenated mitochondrial genes COI and 16S rRNA mtDNA formed 5 clades of monophyletic. Phylogenetic relationships of Diogenes species based on concatenated mitochondrial genes COI and 16S rRNA sequenced suggest that the morphological and molecular analyses of the species in this study corroborated one another. Among 15 species studied, three species were challenging to identify due to their resemblance to other species traits. The phylogenetic tree demonstrates that the three taxa denoted by 'sp.' were different from the known species of Diogenes so far. Diogenes sp.1 was closely related to Diogenes moosai Rahayu & Forest, 1995, Diogenes sp.2 resembles Diogenes laevicarpus Rahayu, 1996, while Diogenes sp.3 was closely related to Diogenes goniochirus Forest, 1956.
Knowledge about coastal and small island ecosystems is increasing for the monitoring of marine resources based on remote sensing. Remote sensing data provides up-to-date information with various resolutions when detecting changes in ecosystems. Studies have defined a shift in marine resources but were limited only to pixel or object classification in changes of seagrass area. In the present study, two classification method analysis approaches were compared to obtain optimum results in detecting changes in seagrass extent. It aimed to determine the dynamics of a seagrass ecosystem by comparing two classification methods in the waters of Gusung Island and Pajenekang, South Sulawesi, these methods being pixel-based and object-based classification methods. This research used SPOT-7 satellite imagery with 6 m2 of spatial resolution. Accuracy assessment using the confusion matrix showed optimum accuracy in object-based classification with an accuracy value of 87 %. Meanwhile, pixel-based classification showed an accuracy value of 78 % around Gusung Island. Pajenekang Island had accuracy values of 69 % with object-based classification and 65 % with pixel-based classification. A comparison of both classification methods revealed statistically high accuracy in mapping the benthic habitats of seagrass ecosystems. The results of the classifications showed a decline in the area of seagrass populations around Gusung Island from 2016 - 2018 and around Pajenekang Island from 2013 - 2017, with a change rate of 11.8 % around the island of Gusung and 7.6 % around the island of Pajenekang. This can explain the reason for the temporal method of object-based research classification having the best potential to process data changes in areas of seagrass in South Sulawesi waters and remote sensing information for the mapping of coastal area ecosystems. HIGHLIGHTS Information on coastal ecosystems globally with remote sensing data is currently very easy to access, but information related to ecosystem management and seagrass ecology in certain areas is still limited Analysis of seagrass benthic changes in shallow water requires data processing methods with high accuracy The OBIA (Object Based Image Analysis) method is one of the analytical methods that can provide optimal results in observing changes in seagrass ecosystems in the waters of South Sulawesi, Indonesia GRAPHICAL ABSTRACT
Abstract. Widiarti R, Zamani NP, Bengen DG, Madduppa H. 2022. Molecular characterization of toxic benthic dinoflagellate, Prorocentrum lima in west Indonesian waters using LSU 28S rDNA gene. Biodiversitas 23: 3257-3263. Prorocentrum lima is one of the toxic benthic dinoflagellates known to cause Diarrhetic Shellfish Poisoning (DSP), which is also associated with ciguatoxin-producing species, Gambierdiscus toxicus that causes Ciguatera Fish Poisoning (CFP). P. lima has a wide range of morphological variability and genetic diversity, but such research has never been reported from Indonesian waters yet. This study aimed to determine the molecular characteristics of P. limain west Indonesian waters, namely Bintan Island, Belitung Island, Seribu Islands, and Karimunjawa Islands. Molecular characterization was conducted by amplification on large subunit (LSU)28S rDNA gene. Extraction was conducted using freeze-thaw which was continued with single cell PCR method. Genetic distance values and phylogenetic analysis were analyzed using MEGA software. Based on molecular analysis, P. lima from this research was divided into two subclades, namely subclade A from Seribu Islands and Belitung Island, and subclade B from Karimunjawa Islands and Bintan Island. P. lima from Bintan Island showed a closer relationship with the reference sequence from the Genbank. Observation of molecular characters of P. lima showed that the genetic diversity of P. lima depended on the variation of the island’s morphogenesis type.These findings could support a further study on the distribution of P. lima in Indonesian waters, related to the genetic variation and toxin production, since Indonesia consists of many small islands.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.