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Authors = Ati Dwi Nurhayati

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14 pages, 635 KiB  
Article
Nutrient Resorption in Young Stands of Three Native Tree Species to Support Restoration of Degraded Tropical Peatland in Indonesia
by Ahmad Junaedi, Avry Pribadi, Nina Mindawati, I Wayan Susi Dharmawan, Dona Octavia, Hery Kurniawan, Ridwan Fauzi, Hengki Siahaan, Bambang Tejo Premono, Ardiyanto Wahyu Nugroho, Yunita Lisnawati, Yulianti, Ati Dwi Nurhayati and Mohamad Iqbal
Land 2024, 13(8), 1169; https://doi.org/10.3390/land13081169 - 30 Jul 2024
Cited by 1 | Viewed by 1233
Abstract
Nutrient resorption (NR) is a critical ecological process in forest ecosystems. However, there is a lack of knowledge about this process in the peatlands of Indonesia, and this may be seen as a research gap. In the present study, NR in young trees [...] Read more.
Nutrient resorption (NR) is a critical ecological process in forest ecosystems. However, there is a lack of knowledge about this process in the peatlands of Indonesia, and this may be seen as a research gap. In the present study, NR in young trees of three native species (Macaranga pruinosa, Cratoxylum arborescens, and Macaranga gigantea) and one exotic species (Acacia crassicarpa) in a drained tropical peatland was investigated. This study was conducted at an experimental plot in Pelalawan-Riau, Indonesia. Nutrient resorption efficiency (RE) and proficiency (RP) were calculated and correlated with soil properties, foliar nutrients, and growth variables. Our results revealed that M. pruinosa exhibited an RE value for phosphorus (PRE) that was 64% higher than that for the second-ranked native species but still significantly (84%) lower than that for A. crassicarpa. RE values for nitrogen (NRE) and potassium (KRE) did not differ significantly among species, ranging from 39 to 42% and 41 to 56%, respectively, for native species, with figures of 45% and 66%, respectively, for A. crassicarpa. Finally, PRE exhibited strong and significant correlations with PRP and tree growth, a finding that indicated that the uptake and conservation of P nutrients are essential for the fitness of the three native species. Overall, the results of the present study may be seen as beneficial for species selection and the management of nutrients by those engaged in restoration of tropical peatland forests. Full article
(This article belongs to the Special Issue Restoration of Tropical Peatlands: Science Policy and Practice)
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21 pages, 4391 KiB  
Article
Modeling of Evaporation Rate for Peatland Fire Prevention Using Internet of Things (IoT) System
by Lu Li, Aduwati Sali, Nor Kamariah Noordin, Alyani Ismail, Fazirulhisyam Hashim, Mohd Fadlee A. Rasid, Marsyita Hanafi, Sheriza Mohd Razali, Nurizana Amir Aziz, Imas Sukaesih Sitanggang, Lailan Syaufina and Ati Dwi Nurhayati
Fire 2023, 6(7), 272; https://doi.org/10.3390/fire6070272 - 13 Jul 2023
Cited by 4 | Viewed by 4165
Abstract
Peatland refers to the peat soil and wetland biological environment growing on the surface. However, unexpected fires in peatlands frequently have brought severe greenhouse gas emissions and transboundary haze to Southeast Asia. To alleviate this issue, this paper first establishes an Internet of [...] Read more.
Peatland refers to the peat soil and wetland biological environment growing on the surface. However, unexpected fires in peatlands frequently have brought severe greenhouse gas emissions and transboundary haze to Southeast Asia. To alleviate this issue, this paper first establishes an Internet of Things (IoT) system for peatland monitoring and management in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, and proposes a more efficient and low-complexity model for calculating the Duff Moisture Code (DMC) in peatland forests using groundwater level (GWL) and relative humidity. The feasibility of the IoT system is verified by comparing its data with those published by Malaysian Meteorological Department (METMalaysia). The proposed Linear_DMC Model and Linear_Mixed_DMC Model are compared with the Canadian Fire Weather Index (FWI) model, and their performance is evaluated using IoT measurement data and actual values published by METMalaysia. The results show that the correlation between the measured data of the IoT system and the data from METMalaysia within the same duration is larger than 0.84, with a mean square error (MSE) of 2.56, and a correlation of 0.91 can be achieved between calculated DMC using the proposed model and actual values. This finding is of great significance for predicting peatland forest fires in the field and providing the basis for fire prevention and decision making to improve disaster prevention and reduction. Full article
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