Abstract
STRATEGIC MANAGEMENT OF TALAS BENENG (Xanthosoma undipes) AGROFORESTRY IN CIAMIS REGENCY, INDONESIA. Recently, the Indonesian government has sought to secure food production from forestlands by implementing agroforestry in rural areas. Talas beneng or tall elephant ear plant (Xanthosoma undipes) is a potential species for agroforestry that produces medicinal tubers and leaves. It has high productivity and export opportunities, but its management strategy under community forestland needs to be more widely studied. In Ciamis Regency, talas beneng has been cultivated for the last two years, but the progress has not been significant. This study aimed to formulate strategic management for improving its business model by identifying internal and external factors. Two groups of farmers in Ciamis Regency were chosen as the case study. Observation and in-depth interviews with farming group leaders as key informants were employed to gather the existing model business. Internal and external factors were analyzed using a business model canvas (BMC) framework, SWOT analysis and quantitative strategic planning matrix (QSPM). Results show that the market channels between the two groups of talas beneng producers are slightly different. SWOT analysis shows that both groups have positions in which product development and market penetration are required as strategies to improve future management. Specific strategies that need to be prioritized include 1) improving farming intensification, 2) improving talas beneng product competitiveness, and 3) expanding the business partnership to access market information better.

SDGs:
1. SDGs 2:Zero Hunger
2. SDGs 4:Quality Education
3. SDGs 8:Decent Work and Economic Growth
4. SDGs 12:Responsible Consumption and Production
5. SDGs 13:Climate Action
6. SDGs 15:Life on Land

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Abstract
The microbiome is an important consideration for the conservation of endangered species. Studies provided evidence of the effect of behavior and habitat change on the microbiota of wild animals and reported various inferences. It indicates the complexity of factors influencing microbiota diversity, including incomplete sampling procedures. Data abnormality may arise due to the procedures warranting preliminary analysis, such as rarefaction, before downstream analysis. This present study demonstrated the effect of data rarefaction and aggregation on the comparison of wild rusa deer’s gut microbial diversity. Eighty-five feces samples were collected from 11 deer populations inhabiting three national parks in Java and Bali islands. Using the Illumina Nova-Seq platform, fragments of 16s rRNA gene were sequenced, and raw data of 51,389 reads corresponding to 2 domains, 22 phyla, 45 classes, 83 orders, 182 families, and 460 genera of bacteria were obtained. Data rarefaction was applied at two different library sizes (minimum and fixed) and aggregation (11 populations into 3 research sites) to investigate its effect on the microbial diversity comparison. There are significant differences in alpha diversity between populations, but not research sites, at all library sizes of rarefaction. A similar finding is also found in beta diversity. Moreover, data rarefaction and aggregation result in different values of the diversity metrics. This present study shows that statistical analysis remains a substantial concern in microbiome studies applied to conservation biology. It suggests reporting a more detailed data normalization in microbiome studies as an inherent control of suboptimal sampling, particularly when involving feces.

SDGs:
1. SDGs 3:Good Health and Well-being
2. SDGs 4:Quality Education
3. SDGs 9:Industry, Innovation, and Infrastructure
4. SDGs 12:Responsible Consumption and Production
5. SDGs 15:Life on Land

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Abstract
This study aims to determine the lipophilic component that affects the quality of pulp and paper products in wood of 10-year-old Anthocephalus cadamba (families 23, 11 and 6) and 5-year-old Anthocepalus macrophyllus (families 75, 85 and 2). The results showed that the main group of compounds that appeared frequently and were identified in the lipophilic fraction were fatty acids (palmitic, oleic, linoleic and stearic acids), fatty alcohols (eicosanol, heneicosanol and tetracosanol), sterols (β-sitosterol and campasterol), hydrocarbons (hexadecane, tricosene and cyclotetracosane), aldehydes, alongside minor amounts of triterpenoid. F11 and F2 can be promoted as raw materials for pulp and paper, while F6 and F75 are not recommended because of the high levels of lipids such as sterols, triterpenoids, hydrocarbons, fatty acids, and fatty alcohols.

SDGs:
1. SDGs 8:Decent Work and Economic Growth
2. SDGs 9:Industry, Innovation, and Infrastructure
3. SDGs 12:Responsible Consumption and Production
4. SDGs 13:Climate Action
5. SDGs 15:Life on Land

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Keluarga Mahasiswa Islam Kehutanan (KMIK) Fakultas Kehutanan mengadakan sebuah kegiatan rutin yang di lakukan pada bulan ramadan. Kegiatan ini disebut dengan Semarak Ramadan Fakultas Kehutanan (SR FKT). Kegiatan ini bertujuan untuk mengajak seluruh Keluarga Mahasiswa Kehutanan untuk melakukan kegiatan positif. Dalam kegiatan SR FKT 1445 H ini terdapat beberapa kegiatan yang dilaksanakan selama bulan ramadan yaitu iftar yang merupakan kegiatan membagi menu berbuka ke pada mahasiswa Fakultas Kehutanan. Kegiatan ini sangat dinantikan oleh mahasiswa kehutanan dibuktikan dengan di setiap pembagian iftar terlihat selalu memiliki antrian yang panjang.

Kegiatan yang kedua merupakan kajian yang dimana terdapat 1 kajian grand opening dan 3 kajian rutin. Pada di setiap kajian terlihat cukup antusias para mahasiswa kehutanan mengikuti kajian ini. Kegiatan ketiga merupakan lomba fotografi dan cerdas cermat. Pada kegiatan ketiga ini tidak diikuti hanya dari mahasiswa Fakultas Kehutanan namun diikuti oleh peserta dari berbagai fakultas di Universitas Gadjah Mada.

Kegiatan keempat dari semarak ramadan Fakultas Kehutanan disebut dengan rimbawan berbagi. Kegiatan rimbawan berbagi ini dilakukan dengan berkunjung ke panti asuhan. Pada tahun ini tepatnya pada tanggal 29 maret 2024, rimbawan berbagi di adakan di Panti Asuhan Mustika Tama yang berada di daerah Jl. Padokan, Padokan Kidul, Tirtonirmolo, Kasihan Bantul, Daerah Istimewa Yogyakarta. Kegiatan ini diikuti oleh 27 anak dari panti dan 20 panitia yang ikut mensukseskan acara ini. Dalam kegiatan ini juga rimbawan berbagi berkolaborasi dengan teman-teman dari LPI untuk menyiapkan kegiatan kali ini.

Jurnal Ilmu kehutanan Vol. 18 No 1 bisa Download

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Abstract
Teak (Tectona grandis Linn. f.) is one of the most economically valuable types of tropical forest because teak wood has high durability, resilience and good aesthetic qualities. Teak tree improvement in Indonesia was initiated in 1983 producing planting stock for reforestation, i.e. clonal seed orchards (CSO) to produce seedling as sexual reproduction (referred to seedling), and hedge orchards to produce shoot cuttings as asexual (vegetative) reproductive (referred to shoot cuttings). Teak plantations established using seedling and shoot cuttings should improve forest productivity. The objectives of this study were to compare the growth rate, wood properties, and soil fertility of teak plantations propagated using seedling and shoot cuttings. Three square plots of 100 trees (10 × 10 trees; 1,000 m2) were established on both types of plantation and tree growth characteristics, wood properties, and soil fertility were monitored. The tree growth characteristics were diameter at breast height (DBH), tree height (H), clear bole height (CB), and volume of standing stock (Vss), and the wood properties included pilodyn penetration (PP) and stress wave velocity (SWV). Soil fertility was assessed from soil samples collected from three soil depths, with three replicates in each plot: 0–5 cm (top layer), 6–30 cm (middle layer), and 31–60 cm (bottom layer). Soil samples were analysed for total nitrogen, total phosphorus, total potassium, total calcium, and total magnesium. The results showed that the mean DBH, H, CB, and Vss differed significantly between the type of planting stock. The DBH, H, CB, and Vss values were 28.4%, 46.8%, 49.1%, and 130.1% higher, respectively, in teak plantations from shoot cuttings than from seedling. Moreover, the SWV of shoot cuttings planting stock plantation was 3.6% higher than from seedling. The mean PP did not differ significantly between teak plantations from shoot cuttings (22.00 mm) and seedling (21.80 mm). Furthermore, the planting stock did not affect soil fertility, which was highest in the top layer in all treatments. Our results suggest that teak plantations from shoot cuttings would increase growth, forest productivity, maintaining wood quality and soil fertility. Thus, it can maintain sustainable teak forest plantations.

SDGs:
1. SDGs 3:Good Health and Well-being
2. SDGs 8:Decent Work and Economic Growth
3. SDGs 12:Responsible Consumption and Production
4. SDGs 13:Climate Action
5. SDGs 15:Life on Land

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Abstract
Persimmon wood (Diospyros kaki) is a seasonal fruit-producing plant with a beautiful dark pattern in its wood that is suitable for high-quality furniture, sculptures and musical instruments. The utilization of persimmon wood can be improved by determining its anatomical characteristics, such as juvenile and mature wood. This study aimed to determine the boundaries between juvenile and mature wood and observe the anatomical properties of juvenile and mature wood and their variations in the axial direction. Three 30-year-old persimmon (D. kaki) trees grown in Karo, North Sumatra, Indonesia, were used in this study. The boundary between juvenile and mature wood was determined by measuring the fiber length and vessel element length from near the pith to near the bark. Anatomical observations were conducted in the juvenile and mature wood areas. The results showed that the average boundaries between juvenile and mature wood were 44.11 mm from the pith and were not significantly different in the axial direction of the trees. Furthermore, the wood anatomy categories of juvenile and mature wood differed significantly in terms of fiber diameter, fiber proportion, vessel proportion, and axial parenchyma proportion. In the axial direction, vessel diameter, ray parenchyma frequency, and ray parenchyma proportion at the base, middle, and top of the tree were significantly different.

SDGs:
1. SDGs 3:Good Health and Well-being
2. SDGs 9:Industry, Innovation, and Infrastructure
3. SDGs 12:Responsible Consumption and Production
4. SDGs 13:Climate Action
5. SDGs 15:Life on Land

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Abstract
The success of rehabilitation has altered environmental conditions from critical land to new habitats for living organisms. One of the representative and sensitive mesofauna to environmental changes is Collembola. Various vegetation cover almost all of the rehabilitation area, which has impacts on microclimate and soil quality as important factors to Collembola existence. This study investigated the diversity and abundance of Collembola and its relation to environmental factors on various land covers, including teak, grass, and mixed stand land cover. Data were collected in an observation plot of 20 m × 20 m using purposive samples, including environmental measurements, Collembola collection, and soil samples for physical and chemical analysis. The results showed that different land covers affected the abundance and diversity of Collembola, even though the statistical analyses of TLC, GLC, and MLC were not significantly different. However, TLC has a higher litter thickness and organic material than the other land cover types. A few families of Collembola, such as Cyphoderidae, Brachystomellidae, Katiannidae, Isotomidae, Oncopoduridae, and Isotogastruridae, show their correlation to climatic and edaphic factors in a certain land cover.

SDGs:
1. SDGs 4:Quality Education
2. SDGs 6:(Clean Water and Sanitation
3. SDGs 11:Sustainable Cities and Communities
4. SDGs 13:Climate Action
5. SDGs 15:Life on Land

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Abstract
Globally, habitat loss, deforestation, and climate change are mostly caused by land cover changes (LCC). The amount of land covered by trees has had a major impact on global warming and climate change. Increasing the amount of land cover helps to mitigate climate change and global warming. This study aims to investigate the changes in land cover and carbon storage in Plawangan Hill, Indonesia, over four years (2009, 2013, 2017, and 2023). The study site was defined as a conservation area that has been periodically impacted both directly and indirectly by volcanic eruptions. Images from Landsat 7 and 8 were used to collect data. Additionally, land cover changes were assessed using the forest canopy density (FCD Mapper) model, which was then utilized to quantify the carbon storage of the research site. The findings demonstrated fluctuations in land cover changes between 2009 and 2023. Additionally, changes in land cover have a direct impact on changes in carbon storage. The age of the trees, type of vegetation, succession stage, and history of eruptions were the variables that were apparent to be the main causes of these changes.

SDGs:
1. SDGs 4:Quality Education
2. SDGs 6:Clean Water and Sanitation
3. SDGs 9:Industry, Innovation, and Infrastructure
4. SDGs 11:Sustainable Cities and Communities
5. SDGs 13:Climate Action
6. SDGs 15:Life on Land

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Abstract
In this study, we utilize a self-supervised ResNet50 model for classify land-cover imagery combining learning from both Sentinel-1 and Sentinel-2 images using the SEN12MS dataset. The model is further fine-tuned with the DFC2020 dataset, enriched by our addition of 336 new rubber data patches covering 75×90 km² area. The model achieved 98.1% accuracy in classifying rubber using only a 25% training data
split, and 74.9% accuracy in classifying forest using only 5% training data split. This study demonstrates that accurate classification outcomes are achievable with a small number of labeled datasets by fine-tuning self-pretrained models and incorporating it with new labels. This approach not only showcases the model’s ability to efficiently learn from limited data, but also highlights the potential of adapting pre-existing models for land-cover classification tasks.

SDGs:
1. SDGs 4:Quality Education
2. SDGs 9:Industry, Innovation, and Infrastructure
3. SDGs 11:Sustainable Cities and Communities
4. SDGs 13:Climate Action
5. SDGs 15:Life on Land

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