Improved allometric equations for tree aboveground biomass estimation in tropical dipterocarp forests of Kalimantan, Indonesia

Background Currently, the common and feasible way to estimate the most accurate forest biomass requires ground measurements and allometric models. Previous studies have been conducted on allometric equations development for estimating tree aboveground biomass (AGB) of tropical dipterocarp forests (TDFs) in Kalimantan (Indonesian Borneo). However, before the use of existing equations, a validation for the selection of the best allometric equation is required to assess the model bias and precision. This study aims at evaluating the validity of local and pantropical equations; developing new allometric equations for estimating tree AGB in TDFs of Kalimantan; and validating the new equations using independent datasets. Methods We used 108 tree samples from destructive sampling to develop the allometric equations, with maximum tree diameter of 175 cm and another 109 samples from previous studies for validating our equations. We performed ordinary least squares linear regression to explore the relationship between the AGB and the predictor variables in the natural logarithmic form. Results This study found that most of the existing local equations tended to be biased and imprecise, with mean relative error and mean absolute relative error more than 0.1 and 0.3, respectively. We developed new allometric equations for tree AGB estimation in the TDFs of Kalimantan. Through a validation using an independent dataset, we found that our equations were reliable in estimating tree AGB in TDF. The pantropical equation, which includes tree diameter, wood density and total height as predictor variables performed only slightly worse than our new models. Conclusions Our equations improve the precision and reduce the bias of AGB estimates of TDFs. Local models developed from small samples tend to systematically bias. A validation of existing AGB models is essential before the use of the models

Effect of species grouping and site variables on aboveground biomass models for lowland tropical forests of the Indo-Malay region

Key message: This study assessed the effect of ecological variables on tree allometry and provides more accurate aboveground biomass (AGB) models through the involvement of large samples representing major islands, biogeographical zones and various succession and degradation levels of natural lowland forests in the Indo-Malay region. The only additional variable that significantly and largely contributed to explaining AGB variation is grouping based on wood-density classes. Context: There is a need for an AGB equation at tree level for the lowland tropical forests of the Indo-Malay region. In this respect, the influence of geographical, climatic and ecological gradients needs to be assessed. Aims: The overall aim of this research is to provide a regional-scale analysis of allometric models for tree AGB of lowland tropical forests in the Indo-Malay region. Methods: A dataset of 1300 harvested trees (5 cm ≤ trunk diameter ≤ 172 cm) was collected from a wide range of succession and degradation levels of natural lowland forests through direct measurement and an intensive literature search of principally grey publications. We performed ANCOVA to assess possible irregular datasets from the 43 study sites. After ANCOVA, a 1201-tree dataset was selected for the development of allometric equations. We tested whether the variables related to climate, geographical region and species grouping affected tree allometry in the lowland forest of the Indo-Malay region. Results: Climatic and major taxon-based variables were not significant in explaining AGB variations. Biogeographical zone was a significant variable explaining AGB variation, but it made only a minor contribution on the accuracy of AGB models. The biogeographical effect on AGB variation is more indirect than its effect on species and stand characteristics. In contrast, the integration of wood-density classes improved the models significantly. Conclusion: Our AGB models outperformed existing local models and will be useful for improving the accuracy on the estimation of greenhouse gas emissions from deforestation and forest degradation in tropical forests. However, more samples of large trees are required to improve our understanding of biomass distribution across various forest types and along geographical and elevation gradients.We are grateful to GIZ and KFW Forclime for supporting field-data collection. The support of the Australia Award Scholarship is gratefully acknowledged

ANALISIS HASIL TANGKAPAN FINGERLING IKAN SIDAT (Anguilla spp. ) DENGAN ALAT TANGKAP BUBU BAMBU DI MUARA SUNGAI JENGGALU KOTA BENGKULU

Muara SUngai Jenggalu merupakan salah satu sungai yang ada di Bengkulu yang termasuk ke dalam habitat jenis Anguilla spp. sebab parameter kualitas air masih dalam keadaan baik bagi kelangsungan hidup ikan sidat tersebut . Hasil tangkapan ikan sidat dengan menggunakan bubu bambu semakin berkurang serta banyaknya permintaan dan kurangnya produksi anakan dari alam untuk budi daya. Penelitian ini bert berujuan untuk menganalisis komposisi jumlah hasil tangk apan fingerlingsidat , dan menghitung produktivitas dan sel ektivitas hasil tangkapan bubu berbahan bambu di Muara Sungai Jenggalu, Kota Bengkulu. Penelitian ini menggun akan metode experimental fishing, yakni uji coba pengop erasian 20 unit bubu bambu dengan menggunakan objek penel itianya ngtertangkap sebagai sampel . Hasil penelitian menunjukkan Persentase HTU ( Hasil Tangkapan Utama ) berjumlah 4% dan HTS ( Hasil Tangkapan Sampingan ) berj umlah 96%, nilai produktifitas alat tangkap bubu bambu yaitu 46,067 gram / unit serta selektifitas bubu bambu termasuk ke dalam kriteria sangat rendah . Kata Kunci : Sidat , Bubu Bambu, Muara Sungai , Komposisi Hasil Tangkapan