The amount of carbon stored in deadwood is equivalent to about 8% of global forest carbon stocks 1 . Deadwood decomposition is largely governed by climate [2][3][4][5] with decomposer groups, such as microbes and insects, contributing to variations in decomposition rates 2,6,7 . At the global scale, the contribution of insects to deadwood decomposition and carbon release remains poorly understood 7 . Here we present a field experiment of wood decomposition across 55 forest sites on six continents. We find that deadwood decomposition rates increase with temperature, with the strongest temperature effect at high precipitation levels. Precipitation affects decomposition rates negatively at low temperature and positively at high temperatures. As net effect, including direct consumption and indirect effects via interactions with microbes, insects accelerate decomposition in tropical forests (3.9% median mass loss per year).In temperate and boreal forests we find weak positive and negative effects with a median mass loss of 0.9% and -0.1% per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesised from empirical and remote sensing data. This allows for a first estimate of 10.9 ± 3.2 Pg yr -1 of carbon released from deadwood globally, with 93% originating from tropical forests. Globally, the net effect of insects accounts for a carbon flux of 3.2 ± 0.9 Pg yr -1 or 29% of the total carbon released from deadwood, which highlights the functional importance of insects for deadwood decomposition and the global carbon cycle.
As part of carbon pools, forest soil stores soil organic matter (SOM) that contains many elements including organic C, N, P, and K. These elements contribute nutrients for biogeochemical cycles within the ecosystem. This study was done to determine the ecological value of forest soil organic matter at tropical evergreen Aglaia-Streblus forest of Meru Betiri National Park (MBNP), East Java, Indonesia. The data were sampled along gradient topography in Pringtali tropical forest of TMBNP. Direct measurements of soil moisture, temperature, and pH were taken in the field. The soil samples were extracted from 6 points of soil solum using soil auger, and then oven-dried to get value of dry-weight. The elements content of organic C, N, P, and K were analyzed and estimated at the laboratory. The ecoval of SOM was appraised using developed ecological valuation tool. The result showed that SOM contributed higher ecoval of organic C (66.03 Mg ha-1) than other elements. Compared to P and K elements, N had the highest stock of element content. However, comparing to other two tropical forest ecosystems of Asia the ecoval of SOM elements in TMBNP was relatively low because of its natural geomorphological features.The ecoval of SOM elements in TMBNP was relatively low because of its natural geomorphological features. The ecovals contributed about 2.440,64 - 6.955,50 USD or 31.271.923,73 - 89.120.837,23 IDR per hectare of ecological value (d) to the ecosystem. This value was mainly contributed by organic C stock in the TMBNP forest SOM. It means the forest SOM had higher element content of organic C than N, P, and K elements. This d value is an indicator for TMBNP to protect the SOM elements meaning protecting their resources to sustain the biogeochemical cycles in the forest ecosystem. All the management and policy correlated to this protected area should consider this valuable information for their plan and actions.
The Phil-LiDAR 2 program aims to extract the natural resources of the Philippines from the available two points per square meter LiDAR data. Mangroves, being coastal resources, were one of the foci of this program under the Aquatic Resources Extraction from LiDAR Surveys (CoastMap). The object-based image analysis (OBIA) approach, and support vector machine (SVM) algorithm were utilized to classify three major classes from the LiDAR data, namely: mangrove, other vegetation, and non-vegetation. Object feature values used in the classification include the mean, standard deviation, mode, and texture values from the generated LiDAR derivatives. These derivatives include the Digital Surface Model (DSM), Digital Terrain Model (DTM), Canopy Height Model (CHM), Intensity, Number of Returns, Normalized DSM (NDSM), Slope, and Slope of Slope. Moreover, field data collection and validation provided key references in the supervised SVM classification and contextual editing of the extracted mangrove areas. From the implemented classification, an overall accuracy of above 90% was achieved. Focusing with the final classified mangrove coverage, management of the mangrove resources can be made proper and efficient. Furthermore, high resolution or detailed spatial information can support programs like Reducing Emissions from Deforestation and forest Degradation Plus (REDD+) and biodiversity studies.
Contamination of lead in fishes from Laguna de Bay was previously recorded to have the highest concentrations that may pose a hazard to human health. However, no previous study was conducted on its biomagnification. This research is the first exploratory study that examined lead biomagnification in a food web of the lake. Water quality, aquatic communities, trophic levels and lead concentrations were analyzed during the dry and wet seasons. Lead concentrations were analyzed using Atomic Absorption Spectrometry. Levels of lead in the water were 0.05 mg L-1 and 0.03 mg L-1for dry and wet seasons, respectively. Lead concentrations increased in phytoplankton with 3.87 and 9.66 mg kg-1 lead during wet and dry season, respectively. Furthermore, lead levels increased in zooplankton with 2.92 and 14.31 mg kg-1 during wet and dry seasons, respectively. In fishes, the highest lead concentration in dry season was detected in Hypophthalmichthys nobilis with 0.38 mg kg-1 while the highest during wet season was observed in Oreochromis niloticus with 0.67 mg kg-1. Lead biomagnification was observed in this study in the following order: water < phytoplankton < zooplankton. However, this increasing trend did not continue up to fishes.
A strong belief by Clavaria farmers that there is 'gold in Gmelina growing' turned out to be a huge frustration among tree out growers in southern Philippines in the late 1990s. The lack of a market study and appropriate government support system to address farmers' tree growing risks resulted in a great loss, not only financially but also in terms of local people's confidence in tree growing in the area. A large number of tree growers returned to subsistence farming while others opted to have their land rented out to multi-nationals for high value crops production (including bananas and pineapples). However, the majority shifted to fruit bearing trees. Ten farmers were interviewed using Problem in Context analysis, and they made various recommendations for government to improve the financial performance and regulatory environment for tree farming. These recommendations included the removal of the cutting permit requirements for timber grown in private woodlots, setting the wood price regulatory system to safeguard the interest of small tree growers, providing wood market information and strategic networks for tree growers to find alternative markets or use for their timber produce, and encouraging the private sector to establish small wood processing plants in every municipality in order to provide ready markets for timber produce. It was also suggested that government initiate contract tree growing between the private sector and farmers' groups, provide more planting area for interested tree growers, and assist small tree farmers to form or strengthen local cooperatives.
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