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Register a new userRoadless space is greatly diminished by logging in intact forest landscapes of the Congo Basin
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Forest degradation in the tropics is often associated with roads built for selective logging. The protection of Intact Forest Landscapes (IFL) that are not accessible by roads is high on the biodiversity conservation agenda, a challenge for logging concessions certified by the Forest Stewardship Council (FSC). A frequently advocated conservation objective is to maximise the retention of roadless space, a concept that is based on distance to the nearest road from any point. We developed a novel use of the empty space function - a general statistical tool based on stochastic geometry and random sets theory - to calculate roadless space in a part of the Congo Basin where there has recently been rapid expansion of road networks. We compared the temporal development of roadless space in certified and non-certified logging concessions inside and outside areas declared as IFL in the year 2000. Between 1999 and 2007, rapid road network expansion led to a marked loss of roadless space in IFL. After 2007, this trajectory levelled out in most areas, due to an equilibrium between newly built roads and abandoned roads that became revegetated. However, concessions within IFL that have been certified by FSC since around 2007 showed continued decreases in roadless space, thus reaching a level comparable to all other concessions. Only national parks remained road-free. We recommend that forest management policies make the preservation of large connected forest areas a top priority by effectively monitoring - and limiting - the occupation of space by roads that are permanently accessible.
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Remote sensing techniques have been used effectively for measuring the overall loss of terrestrial ecosystem production and biodiversity due to the forest fire. The current research focuses on assessing the impact of forest fire severity on terrestrial ecosystem productivity using different burn indices in Uttarakhand, India. Satellite-based land surface temperature (LST) was calculated for pre-fire (2014) and fire (2016) year using MODerate Resolution Imaging Spectroradiometer (MODIS) to identify the burn area hotspots across all eco-regions in Uttarakhand. In this study, spatial and temporal changes of different vegetation and burn area indices i.e Normalized Burn Ratio (NBR), Burnt Area Index (BAI), Normalized Multiband Drought Index (NMDI), Soil Adjusted Vegetation Index (SAVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI)were estimated for both pre-fire and fire years. Additionally, two Light Use Efficiency (LUE) models i.e Carnegie- Ames-Stanford-Approach (CASA) and Vegetation Photosynthesis Model (VPM) were selected to quantify the terrestrial Net Primary Productivity (NPP) in pre-fire and fire years across all biomes of the study area.The present approach appears to be promising and has a potential in quantifying the loss of ecosystem productivity due to forest fires. A detailed field observation data is required for further training, and testing of remotely sensed fire maps for future research.
Amyloid precursor with 770 amino acids dimerizes and aggregates, as do its c terminal 99 amino acids and amyloid 40,42 amino acids fragments. The titled question has been discussed extensively, and here it is addressed further using thermodynamic scaling theory to analyze mutational trends in structural factors and kinetics. Special attention is given to Family Alzheimers Disease mutations outside amyloid 42. The scaling analysis is connected to extensive docking simulations which included membranes, thereby confirming their results and extending them to Amyloid precursor.
An effective modeling method for nonlinear distributed parameter systems (DPSs) is critical for both physical system analysis and industrial engineering. In this Rapid Communication, we propose a novel DPS modeling approach, in which a high-order nonlinear Volterra series is used to separate the time/space variables. With almost no additional computational complexity, the modeling accuracy is improved more than 20 times in average comparing with the traditional method.
Irradiation breeding is an important technique in the effort to solve food shortages and improve the quality of agricultural products. In this study, a field test was implemented on the M3 generation of two mutant pea plants gained from previous neutron radiation of pea seeds. The relationship between agronomic characteristics and yields of the mutants was investigated. Moreover, differences in physiological and biochemical properties and seed nutrients were analyzed. The results demonstrated that the plant height, effective pods per plant, and yield per plant of mutant Leaf-M1 were 45.0%, 43.2%, and 50.9% higher than those of the control group. Further analysis attributed the increase in yield per plant to the increased branching number. The yield per plant of mutant Leaf-M2 was 7.8% higher than that of the control group, which could be related with the increased chlorophyll content in the leaves. There was a significant difference between the two mutants in the increase of yield per plant owing to morphological variation between the two mutants. There were significant differences in SOD activity and MDA content between the two mutants and the control, indicating that the physiological regulation of the two mutants also changed. In addition, the iron element content of seeds of the two mutants were about 10.9% lower than in the seeds of the control group, a significant difference. These findings indicate that the mutants Leaf-M1 and Leaf-M2 have breeding value and material value for molecular biological studies.
Associative memory Hamiltonian structure prediction potentials are not overly rugged, thereby suggesting their landscapes are like those of actual proteins. In the present contribution we show how basin-hopping global optimization can identify low-lying minima for the corresponding mildly frustrated energy landscapes. For small systems the basin-hopping algorithm succeeds in locating both lower minima and conformations closer to the experimental structure than does molecular dynamics with simulated annealing. For large systems the efficiency of basin-hopping decreases for our initial implementation, where the steps consist of random perturbations to the Cartesian coordinates. We implemented umbrella sampling using basin-hopping to further confirm when the global minima are reached. We have also improved the energy surface by employing bioinformatic techniques for reducing the roughness or variance of the energy surface. Finally, the basin-hopping calculations have guided improvements in the excluded volume of the Hamiltonian, producing better structures. These results suggest a novel and transferable optimization scheme for future energy function development.
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