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Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data
Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.
Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016
Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.
Reggeometry of deeply Virtual Compton Scattering and Exclusive Vector Meson Production at HERA
N/A
Virtual reality-based sensory stimulation preferences at Amundsen-Scott South Pole station in Antarctica
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SVSBI: sequence-based virtual screening of biomolecular interactions
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Virtual array beamforming of GPS TEC observations of coseismic ionospheric disturbances near the Geomagnetic South Pole triggered by teleseismic megathrusts
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Roles of Flow Braking, Plasmaspheric Virtual Resonances, and Ionospheric Currents in Producing Ground Pi2 Pulsations
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The Virtual Astronomical Observatory: Re-engineering access to astronomical data
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Virtual Transitions to the Continuum in O16
Negative parity level shifts of O16 due to low momentum energy shell transitions calculated for neutrons and protons
Apparent rotation of hologram virtual images.
Apparent rotation of spectral lines as viewed through holograms, obtaining equations for angular change of image position
Virtual-image display system for flight simulators
Dual TV monitor and collimated lens system in windscreens of standard aircraft cockpit simulator permits both pilot and copilot to simultaneously view three dimensional presentation. Proper design of complete system permits depth and viewpoint of visual displays to be accurately presented.
Development of a dc motor with virtually zero powered magnetic bearing
The development of magnetic bearings for use in direct current electric motors is discussed. The characteristics of the magnets used in the construction of the bearings are described. A magnetic bearing using steel armoring on permanent magnets was selected for performance tests. The specifications of the motor are presented. The test equipment used in the evaluation is described.
Effect of image tilt of a virtual image display on simulated transport touchdown performance
An evaluation of the visual effect of image tilt of a refractive lens display system is presented. The system was used to present a rudimentary computer generated out the window scene to the pilot of a flight simulator during approach, flare, and touchdown. Comparisons are made of sink rate at touchdown and performances for untilted and tilted displays. Sixty four landings with each condition for a total of 128 touchdowns were made by 3 subjects. Performance measures, such as the flare and touchdown footprints, were recorded and analyzed. The visual effect of the image tilt was investigated for a terrain model board scene.
Chromatically corrected virtual image visual display
An in-line, three element, large diameter, optical display lens is disclosed which has a front convex-convex element, a central convex-concave element, and a rear convex-convex element. The lens, used in flight simulators, magnifies an image presented on a television monitor and, by causing light rays leaving the lens to be in essentially parallel paths, reduces eye strain of the simulator operator.
Virtual-Center Antenna-Arraying System
Separate signals averaged to produce reference frequency and phase. System develops reference carrier from separate received signals. Phase of signal at each receiver determined by comparison with reference phase. Useful in applications requiring accurate phase estimates: reception of weak telemetry signals, transmitter or reflector locating, nondestructive testing of structures, or geophysical exploration.
The virtual front end: Towards better management of solid geometric data
Throughout the last decade, Computer Aided Design was seen as a Great Promise. Much was accomplished, but that pales in comparison with what was promised. Ultimate achievement has always seemed just a step away. During the era of the early turnkey system, the one step was limited by modeling geometry through a wire frame. Besides being cumbersome to deal with in three dimensions, it was continually shown that a wire frame is ambiguous. This made the modeling of geometry for engineering purposes even more frustrating. The fundamentals of computer aided engineering design rest on the ability to do various analyses. Presently, solid modeling is taking the mechanical engineering CAD world by storm. There are no fewer than 20 solid modeling packages around the world, and more appearing with each vendor show. The question of integration, that is, the combination of elements of the CAD process into unified and easily usable design tools still exists.