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All Journal Jurnal Biologi Tropis Wana Lstari
Pangestu, Agung Yoga
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Immunology & microbiology

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Mangroves as Carbon Sequesterers: Diversity and Carbon Estimation Study in Pantai Mekar Village, Muara Gembong District, Bekasi Regency Amin, Septian Faris Al; Pangestu, Agung Yoga; Dharma, Yossi; Sari, Nurika Arum; Maulidia, Oktarina; Octaviani, Eti Artiningsih; Anita, Vilda Puji Dini; Hasibuan, Mhd Muhajir; Dimyati, Ahmad Iqbal Wahid; Rahmasari, Shinta Nur; Agus, Ferri; Salimah, Wardah
Jurnal Biologi Tropis Vol. 25 No. 1 (2025): Januari - Maret
Publisher : Biology Education Study Program, Faculty of Teacher Training and Education, University of Mataram, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbt.v25i1.8618

Abstract

Mangrove forests are important for storing carbon dioxide (CO2) and reducing the effects of climate change. Indonesia possesses 20% of the global mangrove cover, which substantially impacts global climate mitigation efforts. However, understanding of the diversity of plant species in mangrove forests remains limited, as evidenced by the high rate of conversion of mangrove areas into aquaculture ponds, resulting in mangrove degradation. Our research in Pantai Mekar Village was conducted to augment information on mangrove plant species diversity in Indonesia, specifically in Bekasi Regency. Mangrove vegetation data were collected in Pantai Mekar Village, Muara Gembong, Bekasi from 8 to 12 July 2019. Data were collected using 2x2 m (seedlings and understory), 5x5 m (saplings), and 10x10 m (trees) plots. Importance value index (INP), Shannon-Wiener species diversity, evenness, richness, and carbon stock estimation were utilized to analyze the data. The study documented 21 species from 15 families. Species from the Acanthaceae family were predominant in the study site. Avicennia alba was the species with the largest biomass and carbon content. The estimated biomass contained in Mekar Beach is 380.42 tonnes/Ha with carbon sequestration of 190.21/Ha.
Forest Biomass Modeling Based on Landsat-8 Spectral Indices Using Google Earth Engine Pangestu, Agung Yoga; Al Amin, Septian Faris; Sari, Nurika Arum; Hasibuan, Mhd Muhajir
Jurnal Biologi Tropis Vol. 25 No. 4 (2025): Oktober-Desember
Publisher : Biology Education Study Program, Faculty of Teacher Training and Education, University of Mataram, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbt.v25i4.10266

Abstract

Estimating forest biomass is essential for sustainable forest management and carbon monitoring. This study aimed to develop an aboveground biomass (AGB) estimation model by integrating multispectral Landsat-8 OLI imagery and field measurements in a 95.76 ha rehabilitation area near Rindam II Sriwijaya, Muara Enim, South Sumatra. Field data were collected using the National Forest Inventory Protocol, recording tree diameter and height to calculate AGB through species-specific allometric equations. Several vegetation indices (NDVI, EVI, SAVI, MSAVI, RVI, TVI, NDWI) were derived and analyzed on the Google Earth Engine (GEE) platform to identify the most responsive spectral indicator for biomass estimation.The analysis showed that AGB and carbon stocks varied across the rehabilitation site, reflecting differences in stand structure and vegetation moisture. Among all tested indices, NDWI demonstrated the highest correlation with AGB, indicating its effectiveness in capturing canopy water content and biomass variation under humid, mixed-vegetation conditions. These results emphasize the potential of GEE-based vegetation indices as a cost-efficient and replicable approach for monitoring biomass in tropical rehabilitation forests. NDWI proved to be the most suitable index for modeling forest biomass, offering a practical reference for applying similar remote sensing methods in other tropical regions to support large-scale forest carbon assessments
EVALUATION OF THE WELFARE AND HEALTH OF WILDLIFE TRADED IN BANDAR LAMPUNG Hasibuan, Mhd Muhajir; Pangestu, Agung Yoga; Maulidia, Oktarina; Tohir, Rizki Kurnia; Suwanda, Astri Aulia; Sanjaya, Dhinta Aurellia; Julyatmojo, Fajar Aditya; Hafidz, Muhammad; Hutahaean, Ruben Josafat Sadatua; Evo, Yasyafri
Wana Lestari Vol 6 No 2 (2024): Wana Lestari
Publisher : Program Studi Kehutanan, Fakultas Pertanian, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/wanalestari.v6i2.19908

Abstract

Indonesia known for its high biodiversity, is home to various species of wildlife, with 17% of the world's wild animals found in its territory. However, this wealth makes Indonesia one of the major suppliers of both legal and illegal wildlife trade, which threatens conservation efforts. This study aims to identify the potential of wildlife trade, health factors, and the welfare of traded animals. Conducted in Bandar Lampung in February 2022, the research employed direct observation through structured interviews with pet shop owners, as well as document studies. The findings indicate that despite a post-pandemic decline, wildlife trade in the region still holds significant potential. Health factors, such as mouth ulcers in pythons and metabolic diseases in geckos, pose major challenges, although adequate care is provided in these shops. Animal welfare remains a critical concern, as dependence on wild-caught animals from the wild threatens their sustainability. This study emphasizes the importance of implementing sustainable management practices and adhering to existing regulations to ensure the continuity of wildlife trade in Indonesia
Co-Authors Agus, Ferri Al Amin, Septian Faris Amin, Septian Faris Al Anita, Vilda Puji Dini Dharma, Yossi Dimyati, Ahmad Iqbal Wahid Eti Artiningsih Octaviani Evo, Yasyafri Hutahaean, Ruben Josafat Sadatua Julyatmojo, Fajar Aditya Maulidia, Oktarina Mhd Muhajir Hasibuan Muhammad Hafidz, Muhammad Rahmasari, Shinta Nur Salimah, Wardah Sanjaya, Dhinta Aurellia sari, nurika arum Suwanda, Astri Aulia Tohir, Rizki Kurnia