Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)
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Assessment of Mangrove Species Composition, Biomass, and Carbon Stock Potential for Climate Change Mitigation in Pekalongan, Indonesia
No full textMangrove forests are vital coastal ecosystems that support biodiversity and deliver key ecological services, particularly in tropical regions. In Pekalongan, Central Java, rapid coastal development and land-use change threaten their ecological integrity, particularly their role in carbon sequestration. This study assessed mangrove species richness, biomass, and carbon stock in both conservation and non-conservation areas to evaluate their ecological status and contribution to climate change mitigation. Six sampling sites, comprising protected and unprotected areas, were surveyed using 60 nested square plots to record tree and sapling populations. Biomass estimates, including above and below ground components, were calculated through specific allometric models. Results showed that conservation areas stored higher carbon (248.82 tC ha⁻¹) than non-conservation sites, though Degayu which an unprotected area had the second-highest carbon stock (159.66 tC ha⁻¹). Among species, Sonneratia alba contributed the most carbon, while dense saplings of Rhizophora apiculata and Bruguiera gymnorhiza suggest potential shifts in species dominance. The mean carbon stock (125.02 tC ha⁻¹, equivalent to 495.07 t CO₂e ha⁻¹) indicates substantial emission risks if degradation occurs. These findings underscore the critical role of both conservation and non-conservation mangroves in climate regulation and align with Indonesia’s current policy focus on blue carbon ecosystems, coastal resilience, and community-based conservation
Linking Surface Water Content to Groundwater Levels in Tropical Peatlands: Insights from the van Genuchten Approach
No full textTropical peatland in Indonesia have always been characterized by Peat Hydrology Units which have a function as a large amount of carbon storage and are able to regulate the hydrological cycle naturally. This study has two objectives, namely to analyze the variability of SWC, GWL, and rainfall parameters, to be able to understand the patterns of hydrological interactions in peatlandecosystems and to explain the quantitative relationship between SWC and GWL parameters using the van Genuchten Equation (VG) approach. The study also uses a VG based soil hydraulic curve modeling approach to describe groundwater retention and its impact on groundwater surface dynamics. The results showed that the SWC value was significantly influenced by the depth of theGWL and the intensity of rainfall, this underlined that the relationship between the two parameters is reciprocal. In addition, understanding the relationship between these parameters is very important, since the SWC value greatly determines the moisture status of the peat surface, in addition to directly the SWC value also affects the susceptibility of peat fires, while the GWLregulates the long-term hydrological balance and carbon emission potential. Therefore, conducting this study can improve understanding of hydrological feedback in peatlands. The results of the correlation analysis between parameters in this study showed that there was a strong relationship between SWC and GWL (R² = 0.6–0.8), while the correlation between GWL and Rainfall was weak(R² = 0.1–0.2). This suggests that SWC variation is primarily influenced by groundwater fluctuations rather than precipitation
Menilai Pemulihan Ekologis: Analisis Ekonomi Lingkungan terhadap Remediasi Tanah Terkontaminasi Minyak di Hutan Hujan Tropis
No full textThe hydrocarbon contamination affects approximately 5.9 ha of soil in Sultan Syarif Hasyim Grand Forest Park (Tahura SSH), a tropical rainforest in Riau Province, Indonesia. This study aims to determine the costs required to rehabilitate petroleum-contaminated soil and evaluate the economic significance of ecological restoration in a 5.9 ha area designated in Tahura SSH. This study provides a novel economic framework for assessing ecological damage and guiding recovery in a hydrocarbon-impacted area, integrating the Replacement Cost Method (RCM) through restoration cost calculations and the Resource Equivalence Analysis (REA) to assess and compensate for environmental damage-related losses. The study results show that the three main remediation technologies selected, bioventing, bioaugmentation & biostimulation, and ex-situ landfarming, were used to remediate oil-contaminated soil in Tahura SSH. The highest remediation costs are exsitu landfarming, followed by bioaugmentation and biostimulation, and then bioventing. The ex-situ land farming method incurred the highest remediation costs. Nevertheless, it causes ecological harm in the SSH Tahura Area. REA determined that the area required to replace oil-contaminated land should be twice the baseline from 5.9 ha to 12.8 ha. Furthermore, the compensation paid by REA for environmental damage exceeded the initial assessment by 116.1% compared to using the Replacement Cost Method (Bioaugmentation & Biostimulation, Bioventing, and Ex-Situ Landfarming). This study offers stakeholders guidance on determining a fair environmental value for oil-contaminated soil. Future studies Hutan hujan tropis, ekosistem global yang vital, menghadapi degradasi parah akibat aktivitas antropogenik, termasuk pencemaran minyak yang meluas. Artikel penelitian ini menyajikan penilaian ekonomi pemulihan ekologi di area hipotetis seluas 5,9 hektar yang terdampak hidrokarbon di dalam Taman Hutan Raya Sultan Syarif Hasyim, Provinsi Riau. Menggunakan Metode Biaya Penggantian, studi ini memperkirakan pengeluaran ekonomi yang terkait dengan tiga teknologi remediasi utama: bioventing, bioaugmentasi & biostimulasi, dan ex-situ landfarming. Secara bersamaan, Analisis Kesetaraan Sumber Daya (REA) digunakan untuk mengukur nilai ekologi layanan yang hilang dan mengarahkan restorasi kompensasi. Penilaian ini menjelaskan dampak lingkungan pencemaran minyak terhadap tanah, vegetasi, dan satwa liar, serta merinci biaya dan efektivitas setiap pendekatan remediasi. Hasil penelitian menunjukkan bahwa biaya remediasi sebagai kompensasi lingkungan untuk pencemaran minyak di hutan adalah bioventing (1.547.100,62), bioaugmentasi & biostimulasi (1.584.994,61), dan ex-situ landfarming ($2.624.841,35), masing-masing. Penerapan terintegrasi Metode Biaya Penggantian dan REA menyediakan kerangka kerja komprehensif untuk menilai kerusakan lingkungan, meningkatkan penilaian sumber daya alam dan lingkungan sebesar 46,6%, serta memberikan informasi untuk strategi pengelolaan adaptif guna pemulihan ekologi jangka panjang di hutan hujan tropis yang rentan.
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Peran Masyarakat Lokal dalam Mengelola Kerusakan Lingkungan untuk Mengatasi Konflik Sosial
No full textEnvironmental damage from palm oil production remains a pressing and significant global issue, driving ecosystem disruption and social conflicts. Local communities, as the first to experience its impacts, are central actors in addressing deforestation, pollution, and biodiversity loss. This study examines the role of local communities in the Subah sub-district, Indonesia, in managing environmental degradation and mitigating social conflicts associated with palm oil plantations. A mixed-methods approach was employed, combining a Likert scale questionnaire with 101 respondents and field observations to capture both quantitative trends and community perspectives. The study underscores the importance of empowering local communities by integrating their traditional knowledge and practices into broader environmental governance frameworks. Over 60% of respondents agreed that active participation improves environmental quality and reduces conflict, with nearly 70% reporting direct involvement in conflict resolution. For instance, community-led reforestation in Sabung Village restored biodiversity and strengthened social cohesion, while waterway cleanups in Mukti Raharja Village reduced pollution and eased tensions with plantation companies. These examples highlight how grassroots initiatives can foster both ecological restoration and social harmony. This study’s novelty lies in its focus on community driven environmental practices as dual strategies for ecological management and peacebuilding in palm oil-producing regions. The results suggest the need for participatory approaches, where companies collaborate with communities to promote sustainable practices, prevent environmental degradation, and ensure long-term social stability
Unintended Effects of Forestry Fiscal Transfers on Deforestation in Indonesia
Get PDFSumber emisi terbesar (63 persen) di Indonesia berasal dari aktivitas penggunaan lahan serta kebakaran hutan dan lahan. Deforestasi dipengaruhi oleh beberapa faktor, seperti pertumbuhan penduduk, kebakaran hutan, perluasan lahan pertanian, pertanian, kekeringan, penebangan kayu, dan kurangnya perhatian pemerintah. Sebagai bagian dari upaya menekan deforestasi, Pemerintah Indonesia telah mengalokasikan beberapa jenis pendanaan untuk industri kehutanan. Namun, terdapat perbedaan pendapat mengenai pendanaan yang paling efektif dan kesulitan pelaksanaannya. Penelitian ini bertujuan untuk menganalisis dampak transfer fiskal sektor kehutanan terhadap deforestasi menggunakan Spatial Autoregressive di Indonesia. Hasil penelitian menunjukkan bahwa transfer fiskal sektor kehutanan yang berpengaruh signifikan terhadap deforestasi di Indonesia adalah Dana Bagi Hasil Hutan dengan nilai koefisien positif. Faktor lain yang signifikan mempengaruhi deforestasi di Indonesia adalah Anggaran Pendapatan dan Belanja Daerah Bidang Lingkungan Hidup, jumlah penduduk, Produk Domestik Regional Bruto sektor pertambangan, luas lahan perkebunan, dan pendapatan per kapita. Temuan penelitian menyimpulkan bahwa transfer fiskal berkontribusi terhadap deforestasi, menyimpang dari tujuan transfer fiskal, yaitu untuk memitigasi laju deforestasi.The largest source of emissions (63%) in Indonesia comes from land use activities as well as forest and land fires. Deforestation is affected by several factors, such as population growth, forest fires, expansion of agricultural land, farming, drought, timber harvesting, and the lack of government attention. As part of its efforts to suppress deforestation, the Indonesian Government has allocated several types of funding for the forestry industry. However, there are disagreements over the most effective funding and implementation difficulties. This research aims to analyze the impact of forestry fiscal transfer on deforestation using spatial autoregressive in Indonesia. The results show that the forestry significantly affects deforestation in Indonesia is Forest Revenue-Sharing Fund with a positive coefficient value (0.65). Other factors that significantly affect deforestation in Indonesia are the Regional Budget for Environment (0.77), population size (–2.21), Gross Regional Domestic Product in the mining sector (0.83), area (0.99), and income per capita (–2.39). The research findings conclude that forestry fiscal transfers contribute to deforestation, instead of mitigatingdeforestation. The Central Government should refine ecological fiscal transfer (EFT) schemes by adopting innovative, performance-based models and collaborating with Regional Governments to implement detail-earmarked budgeting, ensuring alignment with conservation goals. 
Dampak Pembangunan Proyek Strategis Nasional (Bandara Internasional Yogyakarta) terhadap Dinamika Penggunaan Lahan
No full textThis paper aims to map land use change, pattern, and direction of built-up land development, before, during, and after the development of Yogyakarta International Airport. The data source employed was Pleiades imagery with a spatial resolution of 0.5 m. The visual method was used for image interpretation and the accuracy test was conducted through the confusion matrix. Land use change data obtained by overlay. The distribution pattern is determined by the average nearest neighbour, while the direction of development of built-up land is determined by the standard deviational ellipse The results indicate that the land use map has a very high accuracy of 92.52%. Moreover, the results of the overlay showed that land use changes occurred very massively, in that within eight years there were decreases of mixed plantations decreased by 528.17 Ha and of agricultural land by 112.66 Ha. On the other hand, there was a significant increase in residential area of 29.42 Ha and a service and trade area of 11.2 Ha. The results show the ratio value of the built-up land pattern in 2014 of 0.63, in 2018 of 0.59 and in 2022 of 0.33, with this value the built-up land pattern is clustered. The results showed that there was a change in the direction of the built land pattern which was initially eastward changed to the northeast parallel to the arterial road. Monitoring the pattern of land use dynamics is an important part in planning and regulating spatial patterns and the direction of regional development.Penelitian ini bertujuan untuk memetakan perubahan penggunaan lahan, pola, dan arah perkembangan lahan terbangun, sebelum, saat, dan setelah pembangunan Bandara Internasional Yogyakarta. Sumber data yang digunakan adalah citra Pleiades dengan resolusi spasial 0,5 m. Metode visual digunakan untuk interpretasi citra, dan uji akurasi dilakukan dengan menggunakan confusion matrix. Data perubahan penggunaan lahan diperoleh dengan cara tumpang susun (overlay). Pola persebaran ditentukan dengan rata-rata tetangga terdekat, sedangkan arah perkembangan lahan terbangun ditentukan dengan standar deviasi elips. Hasil penelitian menunjukkan bahwa peta penggunaan lahan memiliki akurasi yang sangat tinggi yaitu 92,52%. Selain itu, hasil overlay menunjukkan bahwa perubahan penggunaan lahan terjadi sangat masif, dimana dalam kurun waktu delapan tahun terjadi penurunan luas kebun campuran sebesar 528,17 Ha dan lahan pertanian sebesar 112,66 Ha. Di sisi lain, terjadi peningkatan yang signifikan pada lahan permukiman sebesar 29,42 Ha dan lahan jasa dan perdagangan sebesar 11,2 Ha. Hasil penelitian menunjukkan nilai rasio pola lahan terbangun pada tahun 2014 sebesar 0.63, tahun 2018 sebesar 0.59 dan tahun 2022 sebesar 0.33, dengan nilai tersebut pola lahan terbangun adalah mengelompok. Hasil penelitian menunjukkan bahwa terjadi perubahan arah pola lahan terbangun yang awalnya ke arah timur berubah menjadi ke arah timur laut sejajar dengan jalan arteri. Pemantauan pola dinamika penggunaan lahan merupakan bagian penting dalam perencanaan dan pengaturan pola ruang dan arah pengembangan wilayah.
 
The Effect of Information, Fear, and Risk Perceptions to Pro-Environmental Behavior among University Students in Indonesia
Get PDFClimate change is a serious threat to human safety and health. Pro-environmental behavior can avoid more serious risks and harm. Pro-environmental behavior is influenced by information, fear, and risk perceptions. As future educators, planners, and policymakers, it is critical to understand the factors influencing students\u27 pro-environmental behavior. This study, therefore, aims to examine the factors influencing students\u27 pro-environmental behavior based on the Protection Motivation Theory. A 77-item questionnaire was completed by 415 students from the Faculty of Arts and Languages, Science, and Education, randomly selected using the cluster sampling method in their last lecture class. Confirmatory factor analysis and structural equation modeling showed that information, fear, and risk perception (reward, perceived severity, and perceived vulnerability) are both directly and indirectly mediated by motivation. In addition, the research identified the indirect and negligible effects of various protection motivation theory factors, including cost, responseefficacy, and self-efficiency. Further, an unexpected finding determines that pro-environmental behavior was unrelated to demographic and socioeconomic background. Overall, the study\u27s outcomes offer recommendations to socialize the risks climate change better causes to human health and safety, increasing fear and risk perceptions that may improve pro-environmental behavior. Additionally, stricter environmental behavior regulations are needed to penalize polluters and stop rewarding maladaptive behaviors
Short-term movements of the Pig-Nosed Turtle (Carrettochelys insculpta) in the Kao River, South Papua, Indonesia
Get PDFUnderstanding animal movement is essential for assessing species\u27 ecological needs and informing effective conservation strategies. This study investigates the short-term daily movement and home range of the Endangered (EN) pig-nosed turtle (Carettochelys insculpta) in the Kao River, Boven Digoel District, South Papua, Indonesia. Native to Papua New Guinea, Northern Australia, and Southern Papua, this freshwater turtle faces heavy egg harvesting pressure. Using low-cost GPS tracking devices, we monitored six adult individuals (one male and five females) over a three-day period during November–December 2023. The results indicated that the daily movements of C. insculpta ranged from 84.95 to 648.77 m. Average home range estimates were 18.03 ha (minimum convex polygon), 7.51 ha (50% kernel density), and 12.44 ha (95% kernel density). The movement overlaps among the four turtles totaled 30.64 ha, with an average overlap of 6.12 ha. The hotspot analysis identified 76.16 ha as key movement areas, revealing that the pig-nosed turtles tend to stay near sandbanks, primary dryland forest, secondary dryland forest, and shrublands. Our studyprovides important baseline ecological data that can be used to inform future conservation and recovery programs. Elaboration between stakeholders and the local community can be carried out to protect the species
Developing a Decision Tree Algorithm for Detecting Agroforestry and Monoculture Coffee Plantations Using Landsat 8 Imagery: A Case Study inBandung Regency, Indonesia
No full textKopi arabika merupakan komoditas unggulan di Kabupaten Bandung, Provinsi Jawa Barat, Indonesia, yang memiliki potensi pengembangan yang besar dengan menggunakan sistem penanaman agroforestri. Oleh karena itu, penelitian ini bertujuan untuk mendeskripsikan pengembangan algoritma pohon keputusan dengan mengkombinasikan variabel spektral yang berasal dari citra Landsat 8 dan variabel sosio-geo-biofisik. Variabel yang dikaji meliputi citra sintetis dan faktor sosio-geo-fisik, seperti elevasi, kemiringan lereng, jarak dari jalan dan sungai, jarak dari permukiman, kepadatan penduduk, jarak dari desa, dan peta tutupan lahan yang ada. Algoritma decision tree machine learning (DTML) dikembangkan untuk mendeteksi distribusi spasial penanamn kopi agroforestri dan kopi monokultur di Kabupaten Bandung. Parameter pohon keputusan yang diuji untuk mengidentifikasi bobot masing-masing variabel adalah gain ratio, information gain, dan gini indeks. Sementara itu, metode brute force diterapkan untuk memilih variabel yang paling signifikan dalam model. Hasil penelitian menunjukkan bahwa variabel yang paling signifikan untuk mengidentifikasi agroforestry dan monokultur kopi adalah kombinasi dari variabel spektral, biogeofisik, dan tutupan lahan, dengan kriteria terbaik adalah information gain. Penggunaan peta penggunaan dan tutupan lahan yang ada merupakan variabel yang paling berpengaruh dalam model. Dalam konteks ini, akurasi keseluruhan (OA) yang diperoleh adalah 84,65%, dengan akurasi kappa (KA) sebesar 82,60%.Data on the potential of coffee commodities in Bandung Regency is still mixed with data on other commodities. Therefore, the study aims to develop an algorithm that provides accurate spatial information through maps for both coffee plantations in agroforestry and monoculture systems. This study integrates the data derived from remotely sensed data and data derived using socio-geobiophysical aspects, such as elevation, slope, distance from the road and rivers, proximity of the settlements, population density, proximity of villages, and a visually-based land-use-land cover map. The importance value for each variable was computed using several criteria, such as information gain, Gini index, and gain ratio. Meanwhile, the brute force method was applied to select the most significant variables in the model. The study found that the most significant variables for identifying coffee agroforestry and monoculture were ARVI, EVI, GARI, NRGI, and VDVI, as well as DEM, slope, proximity to roads, and visual-based LULC, using the criterion of information gain. The use of existing land-use and cover maps was the most influential variable in the model. The algorithm achieved an overall accuracy (OA) of 84.65% and a kappa accuracy (KA) of 82.60%. Based on overall accuracy and high kappa accuracy, the maps produced facilitate local governments and cooperatives in planning specific interventions for coffee-producing areas, supporting policies related to sustainable agriculture, climate-smart agroforestry expansion, and supply chain traceability
Monitoring Forest Cover Change and Encroachment Risk Mapping Using the Normalized Difference Fraction Index (NDFI): A Case Study of Gunung HalimunSalak National Park, Indonesia
No full textGunung Halimun Salak National Park (GHSNP) is one of the most biodiversity-rich protected areas in Java, yet it remains highly vulnerable to deforestation and forest degradation. This study examines forest cover dynamics from 1994 to 2024 and projects village-level encroachment risk for 2034. Landsat 5 TM, Landsat 7 ETM+, and Landsat 8–9 OLI imagery were processed in Google Earth Engine to generate the Normalized Difference Fraction Index (NDFI) using spectral mixture analysis of GV, NPV, soil, and shade fractions. Changes in NDFI (ΔNDFI) were used to classify degradation, deforestation, regrowth, and intact forest. Encroachment risk mapping was modeled using a 3 × 3 kernel neighborhood with two analytical approaches: the sum of risk weight and the majority of risks around. Forest cover declined by 19,424 ha between 1994 and 2004, largely driven by illegal encroachment linked to governance uncertainty in 2003. An increase of 6,678 ha during 2004–2014 reflects the impact of restoration initiatives and strengthened area protection, although a subsequent decline of 1,992 ha occurred between 2014 and 2024 due to renewed encroachment. Model evaluation indicates low predictive performance for both kernel methods (Precision 4%). Despite this limitation, areas of elevated risk consistently appeared along forest edges near settlements and footpath access routes. Citorek Kidul was identified as the village most susceptible to encroachment in 2034. Improving the accuracy of encroachment prediction will require the integration of socio-economic drivers and advanced machine-learning approaches capable of capturing the complex and non-linear patterns of forest encroachment.