We used the global fire detection record provided by the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to determine the number of fires detected inside 823 tropical and subtropical moist forest reserves and for contiguous buffer areas 5, 10, and 15 km wide. The ratio of fire detection densities (detections per square kilometer) inside reserves to their contiguous buffer areas provided an index of reserve effectiveness. Fire detection density was significantly lower inside reserves than in paired, contiguous buffer areas but varied by five orders of magnitude among reserves. The buffer: reserve detection ratio varied by up to four orders of magnitude among reserves within a single country, and median values varied by three orders of magnitude among countries. Reserves tended to be least effective at reducing fire frequency in many poorer countries and in countries beset by corruption. Countries with the most successful reserves include Costa Rica, Jamaica, Malaysia, and Taiwan and the Indonesian island of Java. Countries with the most problematic reserves include Cambodia, Guatemala, Paraguay, and Sierra Leone and the Indonesian portion of Borneo. We provide fire detection density for 3964 tropical and subtropical reserves and their buffer areas in the hope that these data will expedite further analyses that might lead to improved management of tropical reserves.
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http://dx.doi.org/10.1890/06-1330.1 | DOI Listing |
BMC Neurol
December 2024
Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, 02115, USA.
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high energy and have complex architecture. Considering these limitations, a time-varying synaptic efficacy function based leaky-integrate and fire neuron model, called SEFRON is used for the detection of PD.
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December 2024
Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602 105, India.
Chimp optimization algorithm (CHOA) is a recently developed nature-inspired technique that mimics the swarm intelligence of chimpanzee colonies. However, the original CHOA suffers from slow convergence and a tendency to reach local optima when dealing with multidimensional problems. To address these limitations, we propose TASR-CHOA, a twofold adaptive stochastic reinforced variant.
View Article and Find Full Text PDFACS Appl Mater Interfaces
December 2024
College of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Polyurethane sponge is frequently selected as a substrate material for constructing flexible compressible sensors due to its excellent resilience and compressibility. However, being highly hydrophilic and flammable, it not only narrows the range of use of the sensor but also poses a great potential threat to human safety. In this paper, a conductive flexible piezoresistive sensor (CHAP-PU) with superhydrophobicity and high flame retardancy was prepared by a simple dip-coating method using A-CNTs/HGM/ADP coatings deposited on the surface of a sponge skeleton and modified with polydimethylsiloxane.
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December 2024
School of Geological Engineering and Geomatics, Chang'an University, Xi'an, 710054, China.
The array of wildfire activities instigated by human endeavors has emerged as a significant source of atmospheric pollution, posing considerable risks to both public health and property safety. This study harnesses Sentinel-2 satellite data, employing a variety of methods including spectral index methods, thresholding, and the Random Forest (RF) model for active fire spot detection. The research encompasses a wide range of land cover types across various Chinese regions.
View Article and Find Full Text PDFGlob Chang Biol
December 2024
Faculdade de Ciências, Instituto Dom Luiz, Universidade de Lisboa, Lisbon, Portugal.
In fire-prone regions such as the Mediterranean biome, fire seasons are becoming longer, and fires are becoming more frequent and severe. Post-fire recovery dynamics is a key component of ecosystem resilience and stability. Even though Mediterranean ecosystems can tolerate high exposure to extreme temperatures and recover from fire, changes in climate conditions and fire intensity or frequency might contribute to loss of ecosystem resilience and increase the potential for irreversible changes in vegetation communities.
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