<p>Sungai Cikaniki merupakan salah satu sungai yang berhulu di Taman Nasional Gunung Halimun Salak (TNGHS) terletak di Kabupaten Bogor dipilih sebagai lokasi penelitian dikarenakan sepanjang aliran sungai Cikaniki mendapat masukkan senyawa yang berasal dari pemukiman maupun industri yang menggunakan sianida dan merkuri untuk ekstraksi bijih emas. Penelitian dilaksanakan selama bulan Maret – Juni 2019. Tujuan dari penelitian ini adalah untuk 1) Menganalisis kondisi sungai Cikaniki berdasarkan bioindikator makrofauna, 2) Menganalisis nilai indeks pencemaran sungai Cikaniki 3) Mengetahui korelasi antara Kelimpahan Makrofauna dengan nilai indeks pencemaran sungai Cikaniki. Pemilihan stasiun pengamatan secara terpilih (<em>purposive sampling</em>) yaitu berdasarkan pertimbangan terwakilinya keadaan perairan. Analisis status mutu air sungai dilakukan menggunakan metode indeks pencemaran yang telah dianggap komprehensif menurut Keputusan Menteri Lingkungan Hidup Republik Indonesia Nomor 115 Tahun 2003. Hasil penelitian menunjukkan status mutu air sungai pada Sungai Cikaniki di semua stasiun adalah cemar ringan.</p><p> </p><p>Kata kunci : status mutu air sungai, indeks pencemaran, sungai cikaniki</p><br clear="all" /><p> </p>
To determine emission levels, information on carbon stocks and changes in each carbon pool is required. Aboveground biomass, particularly on dry land, is one carbon pool that contributes significantly to carbon storage. The goal of this study was to develop a model for estimating aboveground carbon stocks in the Mbeliling landscape, in Nusa Tenggara Timur, using a vegetation index that was correlated with field carbon stocks. The best model was then used to create a map of the distribution of carbon stocks as the final result. Simple linear regression analysis and multiple linear regression analysis were used in the study. Google Earth Engine was used to process the images on a cloud system. When comparing the RGI index for measuring field carbon stocks to other indexes, the correlation test revealed a perfect correlation. The linear regression model for aboveground biomass = 14.046 + 272.496 RGI (R-sq = 0.86) was found to be the best model for aboveground biomass. In the multiple linear regression model, there were signs of multicollinearity. With an overall accuracy of 68% and a cappa accuracy of 54.23%, the best model was able to be used to create a carbon stock map in Mbeliling landscape. Keywords: Carbon stock estimation model, Above Ground Biomass, Sentinel 2A
Providing comprehensive information on carbon stock data on all carbon pools needs to be done to plan and measure climate change mitigation efforts that are carried out. This research was conducted by analyzing spatial characteristics and estimating carbon stocks with model development. Spatial analysis is carried out to provide an overview of the distribution of spatial values that can use the built model. Estimation of carbon stock is carried out by building a carbon stock estimator model that correlates the value of remote sensing parameters with the value of carbon stocks in all carbon storage sources. The characteristics of the vegetation index value in the forest category are greater than in the non-forest category and vice versa for the distribution of the digital number average value. The model development is only carried out on aboveground biomass and belowground biomass carbon pools. The results of the analysis of the estimation of carbon stocks based on the selected model showed the potential for aboveground biomass was 5,200,841.45 tC and the potential for belowground biomass was 1,317,948.10 tC.
The success of revegetation in the context of forest land rehabilitation and post-mining land reclamation is often often caused by constraints due to marginal land conditions, such as high acidity/alkalineity, low organic matter content, and low availability of macro nutrients. Mycorrhiza Biofertilizer (MB) is one alternative technology that has been reported to be able to increase the success of the rehabilitation. Forest farmers, as one of the actors in forest rehabilitation activities, do not yet have sufficient knowledge and skills in developing biofertilizer such as MB. The objectives of theis community services were to introduce and improve forest farmer about the MB, as well as to establish the demonstration plot for MB development. The result showed that field training and counseling on mycorrhiza and its benefits, as well as the manufacture of mycorrhizal biofertilizers have been carried out in Cisangku, Malasari village, Bogor Regency involving Forest Farmers Model Conservation Village (KTH MKK). The counseling and training were attended by 25 forest farmer participants. Based on the postest carried out after the implementation of counseling and training, there was an increase in farmers' knowledge about mycorrhizal and its benefits as well as procedures for developing mycorrhizal fertilizers. The participants wer also satisfied and increased their skill in preparing mycorrhizal culture materials and caring for their selves. The participating farmers were even willing to develop MB independently if they have sufficient skills and know the benefits. The increasing knowledge and skills of forest farmers had an impact on improving the quality of forest farmers in supporting forest rehabilitation and becomes an alternative of additional income.
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