Testing Accuracy of Long-Range Ultrasonic Sensors for Olive Tree Canopy Measurements

PubMed Central

Gamarra-Diezma, Juan Luis; Miranda-Fuentes, Antonio; Llorens, Jordi; Cuenca, Andrés; Blanco-Roldán, Gregorio L.; Rodríguez-Lizana, Antonio

2015-01-01

Ultrasonic sensors are often used to adjust spray volume by allowing the calculation of the crown volume of tree crops. The special conditions of the olive tree require the use of long-range sensors, which are less accurate and faster than the most commonly used sensors. The main objectives of the study were to determine the suitability of the sensor in terms of sound cone determination, angle errors, crosstalk errors and field measurements. Different laboratory tests were performed to check the suitability of a commercial long-range ultrasonic sensor, as were the experimental determination of the sound cone diameter at several distances for several target materials, the determination of the influence of the angle of incidence of the sound wave on the target and distance on the accuracy of measurements for several materials and the determination of the importance of the errors due to interference between sensors for different sensor spacings and distances for two different materials. Furthermore, sensor accuracy was tested under real field conditions. The results show that the studied sensor is appropriate for olive trees because the sound cone is narrower for an olive tree than for the other studied materials, the olive tree canopy does not have a large influence on the sensor accuracy with respect to distance and angle, the interference errors are insignificant for high sensor spacings and the sensor's field distance measurements were deemed sufficiently accurate. PMID:25635414

Harvesting tree biomass at the stand level to assess the accuracy of field and airborne biomass estimation in savannas.

PubMed

Colgan, Matthew S; Asner, Gregory P; Swemmer, Tony

2013-07-01

Tree biomass is an integrated measure of net growth and is critical for understanding, monitoring, and modeling ecosystem functions. Despite the importance of accurately measuring tree biomass, several fundamental barriers preclude direct measurement at large spatial scales, including the facts that trees must be felled to be weighed and that even modestly sized trees are challenging to maneuver once felled. Allometric methods allow for estimation of tree mass using structural characteristics, such as trunk diameter. Savanna trees present additional challenges, including limited available allometry and a prevalence of multiple stems per individual. Here we collected airborne lidar data over a semiarid savanna adjacent to the Kruger National Park, South Africa, and then harvested and weighed woody plant biomass at the plot scale to provide a standard against which field and airborne estimation methods could be compared. For an existing airborne lidar method, we found that half of the total error was due to averaging canopy height at the plot scale. This error was eliminated by instead measuring maximum height and crown area of individual trees from lidar data using an object-based method to identify individual tree crowns and estimate their biomass. The best object-based model approached the accuracy of field allometry at both the tree and plot levels, and it more than doubled the accuracy compared to existing airborne methods (17% vs. 44% deviation from harvested biomass). Allometric error accounted for less than one-third of the total residual error in airborne biomass estimates at the plot scale when using allometry with low bias. Airborne methods also gave more accurate predictions at the plot level than did field methods based on diameter-only allometry. These results provide a novel comparison of field and airborne biomass estimates using harvested plots and advance the role of lidar remote sensing in savanna ecosystems.

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance

PubMed Central

2013-01-01

Background Constructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation. Results We present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem. We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees. Conclusions Our new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as well as phylogenetic error may contribute to gene tree discord. In experiments, the MulRF method estimated species trees accurately and quickly, demonstrating MulRF as an efficient alternative approach for phylogenetic inference from large-scale genomic data sets. PMID:24180377

Prediction of the compression ratio for municipal solid waste using decision tree.

PubMed

Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

2014-01-01

The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

Tree STEM and Canopy Biomass Estimates from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Olofsson, K.; Holmgren, J.

2017-10-01

In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10-15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.

Developing a generalized allometric equation for aboveground biomass estimation

NASA Astrophysics Data System (ADS)

Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

2015-12-01

A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species < genus). This approach provides estimation under incomplete tree information (e.g. missing species) or blurred information (e.g. conjecture of species), plus the biophysical environment. The GAE allowed us to quantify contribution of each different covariate in estimating the AGB of trees. Lastly, we applied the GAE to an existing vegetation plot database - Forest Inventory and Analysis database - to derive per-tree and per-plot AGB estimations, their errors, and how much the error could be contributed to the original equations, the plant's taxonomy, and their biophysical environment.

Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Bijker, Wietske; Tolpekin, Valentyn A.; Stein, Alfred

2012-04-01

Municipalities need accurate and updated inventories of urban vegetation in order to manage green resources and estimate their return on investment in urban forestry activities. Earlier studies have shown that semi-automatic tree detection using remote sensing is a challenging task. This study aims to develop a reproducible geographic object-based image analysis (GEOBIA) methodology to locate and delineate tree crowns in urban areas using high resolution imagery. We propose a GEOBIA approach that considers the spectral, spatial and contextual characteristics of tree objects in the urban space. The study presents classification rules that exploit object features at multiple segmentation scales modifying the labeling and shape of image-objects. The GEOBIA methodology was implemented on QuickBird images acquired over the cities of Enschede and Delft (The Netherlands), resulting in an identification rate of 70% and 82% respectively. False negative errors concentrated on small trees and false positive errors in private gardens. The quality of crown boundaries was acceptable, with an overall delineation error <0.24 outside of gardens and backyards.

Hierarchical models for informing general biomass equations with felled tree data

Treesearch

Brian J. Clough; Matthew B. Russell; Christopher W. Woodall; Grant M. Domke; Philip J. Radtke

2015-01-01

We present a hierarchical framework that uses a large multispecies felled tree database to inform a set of general models for predicting tree foliage biomass, with accompanying uncertainty, within the FIA database. Results suggest significant prediction uncertainty for individual trees and reveal higher errors when predicting foliage biomass for larger trees and for...

Errors in Site Index Determination Caused by Tree Age Variation in Even-Aged Oak Stands

Treesearch

Robert A. McQuilkin

1975-01-01

Age deviations of individual trees in even-aged oak stands in Missouri caused variations in the height growth patterns and site index estimates of these younger or older trees. A correction factor for site index estimates on these age-deviant trees is given.

Design of Probabilistic Random Forests with Applications to Anticancer Drug Sensitivity Prediction

PubMed Central

Rahman, Raziur; Haider, Saad; Ghosh, Souparno; Pal, Ranadip

2015-01-01

Random forests consisting of an ensemble of regression trees with equal weights are frequently used for design of predictive models. In this article, we consider an extension of the methodology by representing the regression trees in the form of probabilistic trees and analyzing the nature of heteroscedasticity. The probabilistic tree representation allows for analytical computation of confidence intervals (CIs), and the tree weight optimization is expected to provide stricter CIs with comparable performance in mean error. We approached the ensemble of probabilistic trees’ prediction from the perspectives of a mixture distribution and as a weighted sum of correlated random variables. We applied our methodology to the drug sensitivity prediction problem on synthetic and cancer cell line encyclopedia dataset and illustrated that tree weights can be selected to reduce the average length of the CI without increase in mean error. PMID:27081304

Community assessment of tropical tree biomass: challenges and opportunities for REDD.

PubMed

Theilade, Ida; Rutishauser, Ervan; Poulsen, Michael K

2015-12-01

REDD+ programs rely on accurate forest carbon monitoring. Several REDD+ projects have recently shown that local communities can monitor above ground biomass as well as external professionals, but at lower costs. However, the precision and accuracy of carbon monitoring conducted by local communities have rarely been assessed in the tropics. The aim of this study was to investigate different sources of error in tree biomass measurements conducted by community monitors and determine the effect on biomass estimates. Furthermore, we explored the potential of local ecological knowledge to assess wood density and botanical identification of trees. Community monitors were able to measure tree DBH accurately, but some large errors were found in girth measurements of large and odd-shaped trees. Monitors with experience from the logging industry performed better than monitors without previous experience. Indeed, only experienced monitors were able to discriminate trees with low wood densities. Local ecological knowledge did not allow consistent tree identification across monitors. Future REDD+ programmes may benefit from the systematic training of local monitors in tree DBH measurement, with special attention given to large and odd-shaped trees. A better understanding of traditional classification systems and concepts is required for local tree identifications and wood density estimates to become useful in monitoring of biomass and tree diversity.

Improving tree age estimates derived from increment cores: a case study of red pine

Treesearch

Shawn Fraver; John B. Bradford; Brian J. Palik

2011-01-01

Accurate tree ages are critical to a range of forestry and ecological studies. However, ring counts from increment cores, if not corrected for the years between the root collar and coring height, can produce sizeable age errors. The magnitude of errors is influenced by both the height at which the core is extracted and the growth rate. We destructively sampled saplings...

Computer programs for optical dendrometer measurements of standing tree profiles

Treesearch

Jacob R. Beard; Thomas G. Matney; Emily B. Schultz

2015-01-01

Tree profile equations are effective volume predictors. Diameter data for building these equations are collected from felled trees using diameter tapes and calipers or from standing trees using optical dendrometers. Developing and implementing a profile function from the collected data is a tedious and error prone task. This study created a computer program, Profile...

Merging tree ring chronologies and climate system model simulated temperature by optimal interpolation algorithm in North America

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Zhao, Zongci; Nie, Suping; Huang, Jianbin; Wang, Shaowu; Tian, Qinhua

2015-04-01

A new dataset of annual mean surface temperature has been constructed over North America in recent 500 years by performing optimal interpolation (OI) algorithm. Totally, 149 series totally were screened out including 69 tree ring width (MXD) and 80 tree ring width (TRW) chronologies are screened from International Tree Ring Data Bank (ITRDB). The simulated annual mean surface temperature derives from the past1000 experiment results of Community Climate System Model version 4 (CCSM4). Different from existing research that applying data assimilation approach to (General Circulation Models) GCMs simulation, the errors of both the climate model simulation and tree ring reconstruction were considered, with a view to combining the two parts in an optimal way. Variance matching (VM) was employed to calibrate tree ring chronologies on CRUTEM4v, and corresponding errors were estimated through leave-one-out process. Background error covariance matrix was estimated from samples of simulation results in a running 30-year window in a statistical way. Actually, the background error covariance matrix was calculated locally within the scanning range (2000km in this research). Thus, the merging process continued with a time-varying local gain matrix. The merging method (MM) was tested by two kinds of experiments, and the results indicated standard deviation of errors can be reduced by about 0.3 degree centigrade lower than tree ring reconstructions and 0.5 degree centigrade lower than model simulation. During the recent Obvious decadal variability can be identified in MM results including the evident cooling (0.10 degree per decade) in 1940-60s, wherein the model simulation exhibit a weak increasing trend (0.05 degree per decade) instead. MM results revealed a compromised spatial pattern of the linear trend of surface temperature during a typical period (1601-1800 AD) in Little Ice Age, which basically accorded with the phase transitions of the Pacific decadal oscillation (PDO) and Atlantic multi-decadal oscillation (AMO). Through the empirical orthogonal functions and power spectrum analysis, it was demonstrated that, compared with the pure simulations of CCSM4, MM made significant improvement of decadal variability for the gridded temperature in North America by merging the temperature-sensitive tree ring records.

Simulation-Based Evaluation of Hybridization Network Reconstruction Methods in the Presence of Incomplete Lineage Sorting

PubMed Central

Kamneva, Olga K; Rosenberg, Noah A

2017-01-01

Hybridization events generate reticulate species relationships, giving rise to species networks rather than species trees. We report a comparative study of consensus, maximum parsimony, and maximum likelihood methods of species network reconstruction using gene trees simulated assuming a known species history. We evaluate the role of the divergence time between species involved in a hybridization event, the relative contributions of the hybridizing species, and the error in gene tree estimation. When gene tree discordance is mostly due to hybridization and not due to incomplete lineage sorting (ILS), most of the methods can detect even highly skewed hybridization events between highly divergent species. For recent divergences between hybridizing species, when the influence of ILS is sufficiently high, likelihood methods outperform parsimony and consensus methods, which erroneously identify extra hybridizations. The more sophisticated likelihood methods, however, are affected by gene tree errors to a greater extent than are consensus and parsimony. PMID:28469378

Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction.

PubMed

Mai, Uyen; Sayyari, Erfan; Mirarab, Siavash

2017-01-01

Phylogenetic trees inferred using commonly-used models of sequence evolution are unrooted, but the root position matters both for interpretation and downstream applications. This issue has been long recognized; however, whether the potential for discordance between the species tree and gene trees impacts methods of rooting a phylogenetic tree has not been extensively studied. In this paper, we introduce a new method of rooting a tree based on its branch length distribution; our method, which minimizes the variance of root to tip distances, is inspired by the traditional midpoint rerooting and is justified when deviations from the strict molecular clock are random. Like midpoint rerooting, the method can be implemented in a linear time algorithm. In extensive simulations that consider discordance between gene trees and the species tree, we show that the new method is more accurate than midpoint rerooting, but its relative accuracy compared to using outgroups to root gene trees depends on the size of the dataset and levels of deviations from the strict clock. We show high levels of error for all methods of rooting estimated gene trees due to factors that include effects of gene tree discordance, deviations from the clock, and gene tree estimation error. Our simulations, however, did not reveal significant differences between two equivalent methods for species tree estimation that use rooted and unrooted input, namely, STAR and NJst. Nevertheless, our results point to limitations of existing scalable rooting methods.

Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction

PubMed Central

Sayyari, Erfan; Mirarab, Siavash

2017-01-01

Phylogenetic trees inferred using commonly-used models of sequence evolution are unrooted, but the root position matters both for interpretation and downstream applications. This issue has been long recognized; however, whether the potential for discordance between the species tree and gene trees impacts methods of rooting a phylogenetic tree has not been extensively studied. In this paper, we introduce a new method of rooting a tree based on its branch length distribution; our method, which minimizes the variance of root to tip distances, is inspired by the traditional midpoint rerooting and is justified when deviations from the strict molecular clock are random. Like midpoint rerooting, the method can be implemented in a linear time algorithm. In extensive simulations that consider discordance between gene trees and the species tree, we show that the new method is more accurate than midpoint rerooting, but its relative accuracy compared to using outgroups to root gene trees depends on the size of the dataset and levels of deviations from the strict clock. We show high levels of error for all methods of rooting estimated gene trees due to factors that include effects of gene tree discordance, deviations from the clock, and gene tree estimation error. Our simulations, however, did not reveal significant differences between two equivalent methods for species tree estimation that use rooted and unrooted input, namely, STAR and NJst. Nevertheless, our results point to limitations of existing scalable rooting methods. PMID:28800608

Dating young geomorphic surfaces using age of colonizing Douglas fir in southwestern Washington and northwestern Oregon, USA

USGS Publications Warehouse

Pierson, T.C.

2007-01-01

Dating of dynamic, young (<500 years) geomorphic landforms, particularly volcanofluvial features, requires higher precision than is possible with radiocarbon dating. Minimum ages of recently created landforms have long been obtained from tree-ring ages of the oldest trees growing on new surfaces. But to estimate the year of landform creation requires that two time corrections be added to tree ages obtained from increment cores: (1) the time interval between stabilization of the new landform surface and germination of the sampled trees (germination lag time or GLT); and (2) the interval between seedling germination and growth to sampling height, if the trees are not cored at ground level. The sum of these two time intervals is the colonization time gap (CTG). Such time corrections have been needed for more precise dating of terraces and floodplains in lowland river valleys in the Cascade Range, where significant eruption-induced lateral shifting and vertical aggradation of channels can occur over years to decades, and where timing of such geomorphic changes can be critical to emergency planning. Earliest colonizing Douglas fir (Pseudotsuga menziesii) were sampled for tree-ring dating at eight sites on lowland (<750 m a.s.l.), recently formed surfaces of known age near three Cascade volcanoes - Mount Rainier, Mount St. Helens and Mount Hood - in southwestern Washington and northwestern Oregon. Increment cores or stem sections were taken at breast height and, where possible, at ground level from the largest, oldest-looking trees at each study site. At least ten trees were sampled at each site unless the total of early colonizers was less. Results indicate that a correction of four years should be used for GLT and 10 years for CTG if the single largest (and presumed oldest) Douglas fir growing on a surface of unknown age is sampled. This approach would have a potential error of up to 20 years. Error can be reduced by sampling the five largest Douglas fir instead of the single largest. A GLT correction of 5 years should be added to the mean ring-count age of the five largest trees growing on the surface being dated, if the trees are cored at ground level. This correction would have an approximate error of ??5 years. If the trees are cored at about 1.4 m above the round surface (breast height), a CTG correction of 11 years should be added to the mean age of the five sampled trees (with an error of about ??7 years).

Height-diameter equations for thirteen midwestern bottomland hardwood species

Treesearch

Kenneth C. Colbert; David R. Larsen; James R. Lootens

2002-01-01

Height-diameter equations are often used to predict the mean total tree height for trees when only diameter at breast height (dbh) is measured. Measuring dbh is much easier and is subject to less measurement error than total tree height. However, predicted heights only reflect the average height for trees of a particular diameter. In this study, we present a set of...

Using traveling salesman problem algorithms for evolutionary tree construction.

PubMed

Korostensky, C; Gonnet, G H

2000-07-01

The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree

NASA Astrophysics Data System (ADS)

Kang, Q.; Huang, G.; Yang, S.

2018-04-01

Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

An Approach for Implementing a Microcomputer Based Report Origination System in the Ada Programming Language

DTIC Science & Technology

1983-03-01

Decision Tree -------------------- 62 4-E. PACKAGE unitrep Action/Area Selection flow Chart 82 4-7. PACKAGE unitrep Control Flow Chart...the originetor wculd manually draft simple, readable, formatted iressages using "-i predef.ined forms and decision logic trees . This alternative was...Study Analysis DATA CCNTENT ERRORS PERCENT OF ERRORS Character Type 2.1 Calcvlations/Associations 14.3 Message Identification 4.? Value Pisiratch 22.E

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models

NASA Astrophysics Data System (ADS)

Alexander, Cici; Korstjens, Amanda H.; Hill, Ross A.

2018-03-01

Tree or canopy height is an important attribute for carbon stock estimation, forest management and habitat quality assessment. Airborne Laser Scanning (ALS) based on Light Detection and Ranging (LiDAR) has advantages over other remote sensing techniques for describing the structure of forests. However, sloped terrain can be challenging for accurate estimation of tree locations and heights based on a Canopy Height Model (CHM) generated from ALS data; a CHM is a height-normalised Digital Surface Model (DSM) obtained by subtracting a Digital Terrain Model (DTM) from a DSM. On sloped terrain, points at the same elevation on a tree crown appear to increase in height in the downhill direction, based on the ground elevations at these points. A point will be incorrectly identified as the treetop by individual tree crown (ITC) recognition algorithms if its height is greater than that of the actual treetop in the CHM, which will be recorded as the tree height. In this study, the influence of terrain slope and crown characteristics on the detection of treetops and estimation of tree heights is assessed using ALS data in a tropical forest with complex terrain (i.e. micro-topography) and tree crown characteristics. Locations and heights of 11,442 trees based on a DSM are compared with those based on a CHM. The horizontal (DH) and vertical displacements (DV) increase with terrain slope (r = 0.47 and r = 0.54 respectively, p < 0.001). The overestimations in tree height are up to 16.6 m on slopes greater than 50° in our study area in Sumatra. The errors in locations (DH) and tree heights (DV) are modelled for trees with conical and spherical tree crowns. For a spherical tree crown, DH can be modelled as R sin θ, and DV as R (sec θ - 1). In this study, a model is developed for an idealised conical tree crown, DV = R (tan θ - tan ψ), where R is the crown radius, and θ and ψ are terrain and crown angles respectively. It is shown that errors occur only when terrain angle exceeds the crown angle, with the horizontal displacement equal to the crown radius. Errors in location are seen to be greater for spherical than conical trees on slopes where crown angles of conical trees are less than the terrain angle. The results are especially relevant for biomass and carbon stock estimations in tropical forests where there are trees with large crown radii on slopes.

Data quality in citizen science urban tree inventories

Treesearch

Lara A. Roman; Bryant C. Scharenbroch; Johan P.A. Ostberg; Lee S. Mueller; Jason G. Henning; Andrew K. Koeser; Jessica R. Sanders; Daniel R. Betz; Rebecca C. Jordan

2017-01-01

Citizen science has been gaining popularity in ecological research and resource management in general and in urban forestry specifically. As municipalities and nonprofits engage volunteers in tree data collection, it is critical to understand data quality. We investigated observation error by comparing street tree data collected by experts to data collected by less...

Comprehensive database of diameter-based biomass regressions for North American tree species

Treesearch

Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

2004-01-01

A database consisting of 2,640 equations compiled from the literature for predicting the biomass of trees and tree components from diameter measurements of species found in North America. Bibliographic information, geographic locations, diameter limits, diameter and biomass units, equation forms, statistical errors, and coefficients are provided for each equation,...

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Estimating water use by sugar maple trees: considerations when using heat-pulse methods in trees with deep functional sapwood.

PubMed

Pausch, Roman C.; Grote, Edmund E.; Dawson, Todd E.

2000-03-01

Accurate estimates of sapwood properties (including radial depth of functional xylem and wood water content) are critical when using the heat pulse velocity (HPV) technique to estimate tree water use. Errors in estimating the volumetric water content (V(h)) of the sapwood, especially in tree species with a large proportion of sapwood, can cause significant errors in the calculations ofsap velocity and sap flow through tree boles. Scaling to the whole-stand level greatly inflates these errors. We determined the effects of season, tree size and radial wood depth on V(h) of wood cores removed from Acer saccharum Marsh. trees throughout 3 years in upstate New York. We also determined the effects of variation in V(h) on sap velocity and sap flow calculations based on HPV data collected from sap flow gauges inserted at four depths. In addition, we compared two modifications of Hatton's weighted average technique, the zero-step and zero-average methods, for determining sap velocity and sap flow at depths beyond those penetrated by the sap flow gauges. Parameter V(h) varied significantly with time of year (DOY), tree size (S), and radial wood depth (RD), and there were significant DOY x S and DOY x RD interactions. Use of a mean whole-tree V(h) value resulted in differences ranging from -6 to +47% for both sap velocity and sap flow for individual sapwood annuli compared with use of the V(h) value determined at the specific depth where a probe was placed. Whole-tree sap flow was 7% higher when calculated on the basis of the individual V(h) value compared with the mean whole-tree V(h) value. Calculated total sap flow for a tree with a DBH of 48.8 cm was 13 and 19% less using the zero-step and the zero-average velocity techniques, respectively, than the value obtained with Hatton's weighted average technique. Smaller differences among the three methods were observed for a tree with a DBH of 24.4 cm. We conclude that, for Acer saccharum: (1) mean V(h) changes significantly during the year and can range from nearly 50% during winter and early spring, to 20% during the growing season;(2) large trees have a significantly greater V(h) than small trees; (3) overall, V(h) decreases and then increases significantly with radial wood depth, suggesting that radial water movement and storage are highly dynamic; and (4) V(h) estimates can vary greatly and influence subsequent water use calculations depending on whether an average or an individual V(h) value for a wood core is used. For large diameter trees in which sapwood comprises a large fraction of total stem cross-sectional area (where sap flow gauges cannot be inserted across the entire cross-sectional area), the zero-average modification of Hatton's weighted average method reduces the potential for large errors in whole-tree and landscape water balance estimates based on the HPV method.

Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System

NASA Astrophysics Data System (ADS)

Wang, Hongcui; Kawahara, Tatsuya

CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

Microscopic saw mark analysis: an empirical approach.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2015-01-01

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.

Bayesian models for comparative analysis integrating phylogenetic uncertainty.

PubMed

de Villemereuil, Pierre; Wells, Jessie A; Edwards, Robert D; Blomberg, Simon P

2012-06-28

Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language.

Bayesian models for comparative analysis integrating phylogenetic uncertainty

PubMed Central

2012-01-01

Background Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language. PMID:22741602

Estimating tree bole volume using artificial neural network models for four species in Turkey.

PubMed

Ozçelik, Ramazan; Diamantopoulou, Maria J; Brooks, John R; Wiant, Harry V

2010-01-01

Tree bole volumes of 89 Scots pine (Pinus sylvestris L.), 96 Brutian pine (Pinus brutia Ten.), 107 Cilicica fir (Abies cilicica Carr.) and 67 Cedar of Lebanon (Cedrus libani A. Rich.) trees were estimated using Artificial Neural Network (ANN) models. Neural networks offer a number of advantages including the ability to implicitly detect complex nonlinear relationships between input and output variables, which is very helpful in tree volume modeling. Two different neural network architectures were used and produced the Back propagation (BPANN) and the Cascade Correlation (CCANN) Artificial Neural Network models. In addition, tree bole volume estimates were compared to other established tree bole volume estimation techniques including the centroid method, taper equations, and existing standard volume tables. An overview of the features of ANNs and traditional methods is presented and the advantages and limitations of each one of them are discussed. For validation purposes, actual volumes were determined by aggregating the volumes of measured short sections (average 1 meter) of the tree bole using Smalian's formula. The results reported in this research suggest that the selected cascade correlation artificial neural network (CCANN) models are reliable for estimating the tree bole volume of the four examined tree species since they gave unbiased results and were superior to almost all methods in terms of error (%) expressed as the mean of the percentage errors. 2009 Elsevier Ltd. All rights reserved.

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

The sensitivity of derived estimates to the measurment quality objectives for independent variables

Treesearch

Francis A. Roesch

2002-01-01

The effect of varying the allowed measurement error for individual tree variables upon county estimates of gross cubic-foot volume was examined. Measurement Quality Ob~ectives (MQOs) for three forest tree variables (biological identity, diameter, and height) used in individual tree gross cubic-foot volume equations were varied from the current USDA Forest Service...

The Sensitivity of Derived Estimates to the Measurement Quality Objectives for Independent Variables

Treesearch

Francis A. Roesch

2005-01-01

The effect of varying the allowed measurement error for individual tree variables upon county estimates of gross cubic-foot volume was examined. Measurement Quality Objectives (MQOs) for three forest tree variables (biological identity, diameter, and height) used in individual tree gross cubic-foot volume equations were varied from the current USDA Forest Service...

Pre-Modeling Ensures Accurate Solid Models

ERIC Educational Resources Information Center

Gow, George

2010-01-01

Successful solid modeling requires a well-organized design tree. The design tree is a list of all the object's features and the sequential order in which they are modeled. The solid-modeling process is faster and less prone to modeling errors when the design tree is a simple and geometrically logical definition of the modeled object. Few high…

Implementation of Tree and Butterfly Barriers with Optimistic Time Management Algorithms for Discrete Event Simulation

NASA Astrophysics Data System (ADS)

Rizvi, Syed S.; Shah, Dipali; Riasat, Aasia

The Time Wrap algorithm [3] offers a run time recovery mechanism that deals with the causality errors. These run time recovery mechanisms consists of rollback, anti-message, and Global Virtual Time (GVT) techniques. For rollback, there is a need to compute GVT which is used in discrete-event simulation to reclaim the memory, commit the output, detect the termination, and handle the errors. However, the computation of GVT requires dealing with transient message problem and the simultaneous reporting problem. These problems can be dealt in an efficient manner by the Samadi's algorithm [8] which works fine in the presence of causality errors. However, the performance of both Time Wrap and Samadi's algorithms depends on the latency involve in GVT computation. Both algorithms give poor latency for large simulation systems especially in the presence of causality errors. To improve the latency and reduce the processor ideal time, we implement tree and butterflies barriers with the optimistic algorithm. Our analysis shows that the use of synchronous barriers such as tree and butterfly with the optimistic algorithm not only minimizes the GVT latency but also minimizes the processor idle time.

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient.

PubMed

Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

2015-01-28

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAI(D)), which was compared with LAI estimated by the proposed digital photography method (LAI(M)). Results showed that the LAI(M) was able to estimate LAI(D) with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (f(f)) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.

Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

PubMed Central

Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

2015-01-01

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions. PMID:25635411

Efficiency of the neighbor-joining method in reconstructing deep and shallow evolutionary relationships in large phylogenies.

PubMed

Kumar, S; Gadagkar, S R

2000-12-01

The neighbor-joining (NJ) method is widely used in reconstructing large phylogenies because of its computational speed and the high accuracy in phylogenetic inference as revealed in computer simulation studies. However, most computer simulation studies have quantified the overall performance of the NJ method in terms of the percentage of branches inferred correctly or the percentage of replications in which the correct tree is recovered. We have examined other aspects of its performance, such as the relative efficiency in correctly reconstructing shallow (close to the external branches of the tree) and deep branches in large phylogenies; the contribution of zero-length branches to topological errors in the inferred trees; and the influence of increasing the tree size (number of sequences), evolutionary rate, and sequence length on the efficiency of the NJ method. Results show that the correct reconstruction of deep branches is no more difficult than that of shallower branches. The presence of zero-length branches in realized trees contributes significantly to the overall error observed in the NJ tree, especially in large phylogenies or slowly evolving genes. Furthermore, the tree size does not influence the efficiency of NJ in reconstructing shallow and deep branches in our simulation study, in which the evolutionary process is assumed to be homogeneous in all lineages.

Detecting change in advance tree regeneration using forest inventory data: the implications of type II error

Treesearch

James A. Westfall; William H. McWilliams

2012-01-01

Achieving adequate and desirable forest regeneration is necessary for maintaining native tree species and forest composition. Advance tree seedling and sapling regeneration is the basis of the next stand and serves as an indicator of future composition. The Pennsylvania Regeneration Study was implemented statewide to monitor regeneration on a subset of Forest Inventory...

Adjustments of individual-tree survival and diameter-growth equations to match whole-stand attributes

Treesearch

Quang V. Cao

2010-01-01

Individual-tree models are flexible and can perform well in predicting tree survival and diameter growth for a certain growing period. However, the resulting stand-level outputs often suffer from accumulation of errors and subsequently cannot compete with predictions from whole-stand models, especially when the projection period lengthens. Evaluated in this study were...

Quantifying allometric model uncertainty for plot-level live tree biomass stocks with a data-driven, hierarchical framework

Treesearch

Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall

2016-01-01

Accurate uncertainty assessments of plot-level live tree biomass stocks are an important precursor to estimating uncertainty in annual national greenhouse gas inventories (NGHGIs) developed from forest inventory data. However, current approaches employed within the United States’ NGHGI do not specifically incorporate methods to address error in tree-scale biomass...

Integrating LIDAR and forest inventories to fill the trees outside forests data gap

Treesearch

Kristofer D. Johnson; Richard Birdsey; Jason Cole; Anu Swatantran; Jarlath O' Neil-Dunne; Ralph Dubayah; Andrew Lister

2015-01-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data....

Tree and impervious cover in the United States

Treesearch

David J. Nowak; Eric J. Greenfield

2012-01-01

Using aerial photograph interpretation of circa 2005 imagery, percent tree canopy and impervious surface cover in the conterminous United States are estimated at 34.2% (standard error (SE) = 0.2%) and 2.4% (SE = 0.1%), respectively. Within urban/community areas, percent tree cover (35.1%, SE = 0.4%) is similar to the national value, but percent impervious cover is...

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

PubMed

Deo, Ravinesh C; Downs, Nathan; Parisi, Alfio V; Adamowski, Jan F; Quilty, John M

2017-05-01

Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θ s ) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θ s as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (E NS ), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model's absolute errors were small in magnitude (±0.25), whereas the MARS and M5 Model Tree models generated 53% and 48% of such errors, respectively, indicating the latter models' errors to be distributed in larger magnitude error range. In terms of peak global UVI forecasting, with half the level of error, the ELM model outperformed MARS and M5 Model Tree. A comparison of the magnitude of hourly-cumulated errors of 10-min lead time forecasts for diffuse and global UVI highlighted ELM model's greater accuracy compared to MARS, M5 Model Tree or Pro6UV models. This confirmed the versatility of an ELM model drawing on θ s data for VSTR forecasting of UVI at near real-time horizon. When applied to the goal of enhancing expert systems, ELM-based accurate forecasts capable of reacting quickly to measured conditions can enhance real-time exposure advice for the public, mitigating the potential for solar UV-exposure-related disease. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

NASA Astrophysics Data System (ADS)

Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

2016-12-01

Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Merging Multi-model CMIP5/PMIP3 Past-1000 Ensemble Simulations with Tree Ring Proxy Data by Optimal Interpolation Approach

NASA Astrophysics Data System (ADS)

Chen, Xin; Luo, Yong; Xing, Pei; Nie, Suping; Tian, Qinhua

2015-04-01

Two sets of gridded annual mean surface air temperature in past millennia over the Northern Hemisphere was constructed employing optimal interpolation (OI) method so as to merge the tree ring proxy records with the simulations from CMIP5 (the fifth phase of the Climate Model Intercomparison Project). Both the uncertainties in proxy reconstruction and model simulations can be taken into account applying OI algorithm. For better preservation of physical coordinated features and spatial-temporal completeness of climate variability in 7 copies of model results, we perform the Empirical Orthogonal Functions (EOF) analysis to truncate the ensemble mean field as the first guess (background field) for OI. 681 temperature sensitive tree-ring chronologies are collected and screened from International Tree Ring Data Bank (ITRDB) and Past Global Changes (PAGES-2k) project. Firstly, two methods (variance matching and linear regression) are employed to calibrate the tree ring chronologies with instrumental data (CRUTEM4v) individually. In addition, we also remove the bias of both the background field and proxy records relative to instrumental dataset. Secondly, time-varying background error covariance matrix (B) and static "observation" error covariance matrix (R) are calculated for OI frame. In our scheme, matrix B was calculated locally, and "observation" error covariance are partially considered in R matrix (the covariance value between the pairs of tree ring sites that are very close to each other would be counted), which is different from the traditional assumption that R matrix should be diagonal. Comparing our results, it turns out that regional averaged series are not sensitive to the selection for calibration methods. The Quantile-Quantile plots indicate regional climatologies based on both methods are tend to be more agreeable with regional reconstruction of PAGES-2k in 20th century warming period than in little ice age (LIA). Lager volcanic cooling response over Asia and Europe in context of recent millennium are detected in our datasets than that revealed in regional reconstruction from PAGES-2k network. Verification experiments have showed that the merging approach really reconcile the proxy data and model ensemble simulations in an optimal way (with smaller errors than both of them). Further research is needed to improve the error estimation on them.

Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses

PubMed Central

Bayzid, Md Shamsuzzoha; Mirarab, Siavash; Boussau, Bastien; Warnow, Tandy

2015-01-01

Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically consistent under the multi-species coalescent model. New data used in this study are available at DOI: http://dx.doi.org/10.6084/m9.figshare.1411146, and the software is available at https://github.com/smirarab/binning. PMID:26086579

Human Factors Risk Analyses of a Doffing Protocol for Ebola-Level Personal Protective Equipment: Mapping Errors to Contamination.

PubMed

Mumma, Joel M; Durso, Francis T; Ferguson, Ashley N; Gipson, Christina L; Casanova, Lisa; Erukunuakpor, Kimberly; Kraft, Colleen S; Walsh, Victoria L; Zimring, Craig; DuBose, Jennifer; Jacob, Jesse T

2018-03-05

Doffing protocols for personal protective equipment (PPE) are critical for keeping healthcare workers (HCWs) safe during care of patients with Ebola virus disease. We assessed the relationship between errors and self-contamination during doffing. Eleven HCWs experienced with doffing Ebola-level PPE participated in simulations in which HCWs donned PPE marked with surrogate viruses (ɸ6 and MS2), completed a clinical task, and were assessed for contamination after doffing. Simulations were video recorded, and a failure modes and effects analysis and fault tree analyses were performed to identify errors during doffing, quantify their risk (risk index), and predict contamination data. Fifty-one types of errors were identified, many having the potential to spread contamination. Hand hygiene and removing the powered air purifying respirator (PAPR) hood had the highest total risk indexes (111 and 70, respectively) and number of types of errors (9 and 13, respectively). ɸ6 was detected on 10% of scrubs and the fault tree predicted a 10.4% contamination rate, likely occurring when the PAPR hood inadvertently contacted scrubs during removal. MS2 was detected on 10% of hands, 20% of scrubs, and 70% of inner gloves and the predicted rates were 7.3%, 19.4%, 73.4%, respectively. Fault trees for MS2 and ɸ6 contamination suggested similar pathways. Ebola-level PPE can both protect and put HCWs at risk for self-contamination throughout the doffing process, even among experienced HCWs doffing with a trained observer. Human factors methodologies can identify error-prone steps, delineate the relationship between errors and self-contamination, and suggest remediation strategies.

Evaluation of an urban canopy model in a tropical city: the role of tree evapotranspiration

NASA Astrophysics Data System (ADS)

Liu, Xuan; Li, Xian-Xiang; Harshan, Suraj; Roth, Matthias; Velasco, Erik

2017-09-01

A single layer urban canopy model (SLUCM) with enhanced hydrologic processes, is evaluated in a tropical city, Singapore. The evaluation was performed using an 11 month offline simulation with the coupled Noah land surface model/SLUCM over a compact low-rise residential area. Various hydrological processes are considered, including anthropogenic latent heat release, and evaporation from impervious urban facets. Results show that the prediction of energy fluxes, in particular latent heat flux, is improved when these processes were included. However, the simulated latent heat flux is still underestimated by ∼40%. Considering Singapore’s high green cover ratio, the tree evapotranspiration process is introduced into the model, which significantly improves the simulated latent heat flux. In particular, the systematic error of the model is greatly reduced, and becomes lower than the unsystematic error in some seasons. The effect of tree evapotranspiration on the urban surface energy balance is further demonstrated during an unusual dry spell. The present study demonstrates that even at sites with relatively low (11%) tree coverage, ignoring evapotranspiration from trees may cause serious underestimation of the latent heat flux and atmospheric humidity. The improved model is also transferable to other tropical or temperate regions to study the impact of tree evapotranspiration on urban climate.

MrEnt: an editor for publication-quality phylogenetic tree illustrations.

PubMed

Zuccon, Alessandro; Zuccon, Dario

2014-09-01

We developed MrEnt, a Windows-based, user-friendly software that allows the production of complex, high-resolution, publication-quality phylogenetic trees in few steps, directly from the analysis output. The program recognizes the standard Nexus tree format and the annotated tree files produced by BEAST and MrBayes. MrEnt combines in a single software a large suite of tree manipulation functions (e.g. handling of multiple trees, tree rotation, character mapping, node collapsing, compression of large clades, handling of time scale and error bars for chronograms) with drawing tools typical of standard graphic editors, including handling of graphic elements and images. The tree illustration can be printed or exported in several standard formats suitable for journal publication, PowerPoint presentation or Web publication. © 2014 John Wiley & Sons Ltd.

Pollen flow in the wildservice tree, Sorbus torminalis (L.) Crantz. I. Evaluating the paternity analysis procedure in continuous populations.

PubMed

Oddou-Muratorio, S; Houot, M-L; Demesure-Musch, B; Austerlitz, F

2003-12-01

The joint development of polymorphic molecular markers and paternity analysis methods provides new approaches to investigate ongoing patterns of pollen flow in natural plant populations. However, paternity studies are hindered by false paternity assignment and the nondetection of true fathers. To gauge the risk of these two types of errors, we performed a simulation study to investigate the impact on paternity analysis of: (i) the assumed values for the size of the breeding male population (NBMP), and (ii) the rate of scoring error in genotype assessment. Our simulations were based on microsatellite data obtained from a natural population of the entomophilous wild service tree, Sorbus torminalis (L.) Crantz. We show that an accurate estimate of NBMP is required to minimize both types of errors, and we assess the reliability of a technique used to estimate NBMP based on parent-offspring genetic data. We then show that scoring errors in genotype assessment only slightly affect the assessment of paternity relationships, and conclude that it is generally better to neglect the scoring error rate in paternity analyses within a nonisolated population.

Estimating merchantable tree volume in Oregon and Washington using stem profile models

Treesearch

Raymond L. Czaplewski; Amy S. Brown; Dale G. Guenther

1989-01-01

The profile model of Max and Burkhart was fit to eight tree species in the Pacific Northwest Region (Oregon and Washington) of the Forest Service. Most estimates of merchantable volume had an average error less than 10% when applied to independent test data for three national forests.

Error analysis of leaf area estimates made from allometric regression models

NASA Technical Reports Server (NTRS)

Feiveson, A. H.; Chhikara, R. S.

1986-01-01

Biological net productivity, measured in terms of the change in biomass with time, affects global productivity and the quality of life through biochemical and hydrological cycles and by its effect on the overall energy balance. Estimating leaf area for large ecosystems is one of the more important means of monitoring this productivity. For a particular forest plot, the leaf area is often estimated by a two-stage process. In the first stage, known as dimension analysis, a small number of trees are felled so that their areas can be measured as accurately as possible. These leaf areas are then related to non-destructive, easily-measured features such as bole diameter and tree height, by using a regression model. In the second stage, the non-destructive features are measured for all or for a sample of trees in the plots and then used as input into the regression model to estimate the total leaf area. Because both stages of the estimation process are subject to error, it is difficult to evaluate the accuracy of the final plot leaf area estimates. This paper illustrates how a complete error analysis can be made, using an example from a study made on aspen trees in northern Minnesota. The study was a joint effort by NASA and the University of California at Santa Barbara known as COVER (Characterization of Vegetation with Remote Sensing).

Constancy and asynchrony of Osmoderma eremita populations in tree hollows.

PubMed

Ranius, Thomas

2001-01-01

A species rich beetle fauna is associated with old, hollow trees. Many of these species are regarded as endangered, but there is little understanding of the population structure and extinction risks of these species. In this study I show that one of the most endangered beetles, Osmoderma eremita, has a population structure which conforms to that of a metapopulation, with each tree possibly sustaining a local population. This was revealed by performing a mark-release-recapture experiment in 26 trees over a 5-year period. The spatial variability between trees was much greater than temporal variability between years. The population size was on average 11 adults tree -1 year -1 , but differed widely between trees (0-85 adults tree -1 year -1 ). The population size in each tree varied moderately between years [mean coefficient of variation (C.V.)=0.51], but more widely than from sampling errors alone (P=0.008, Monte Carlo simulation). The population size variability in all trees combined, however, was not larger than expected from sampling errors alone in a constant population (C.V.=0.15, P=0.335, Monte Carlo simulation). Thus, the fluctuations of local populations cancel each other out when they are added together. This pattern can arise only when the fluctuations occur asynchronously between trees. The asynchrony of the fluctuations justifies the assumption usually made in metapopulation modelling, that local populations within a metapopulation fluctuate independently of one another. The asynchrony might greatly increase persistence time at the metapopulation level (per stand), compared to the local population level (per tree). The total population size of O. eremita in the study area was estimated to be 3,900 individuals. Other localities sustaining O. eremita are smaller in area, and most of these must be enlarged to allow long-term metapopulation persistence and to satisfy genetic considerations of the O. eremita populations.

Factors affecting the concordance between orthologous gene trees and species tree in bacteria.

PubMed

Castillo-Ramírez, Santiago; González, Víctor

2008-10-30

As originally defined, orthologous genes implied a reflection of the history of the species. In recent years, many studies have examined the concordance between orthologous gene trees and species trees in bacteria. These studies have produced contradictory results that may have been influenced by orthologous gene misidentification and artefactual phylogenetic reconstructions. Here, using a method that allows the detection and exclusion of false positives during identification of orthologous genes, we address the question of whether putative orthologous genes within bacteria really reflect the history of the species. We identified a set of 370 orthologous genes from the bacterial order Rhizobiales. Although manifesting strong vertical signal, almost every orthologous gene had a distinct phylogeny, and the most common topology among the orthologous gene trees did not correspond with the best estimate of the species tree. However, each orthologous gene tree shared an average of 70% of its bipartitions with the best estimate of the species tree. Stochastic error related to gene size affected the concordance between the best estimated of the species tree and the orthologous gene trees, although this effect was weak and distributed unevenly among the functional categories. The nodes showing the greatest discordance were those defined by the shortest internal branches in the best estimated of the species tree. Moreover, a clear bias was evident with respect to the function of the orthologous genes, and the degree of divergence among the orthologous genes appeared to be related to their functional classification. Orthologous genes do not reflect the history of the species when taken as individual markers, but they do when taken as a whole. Stochastic error affected the concordance of orthologous genes with the species tree, albeit weakly. We conclude that two important biological causes of discordance among orthologous genes are incomplete lineage sorting and functional restriction.

Scaling up and error analysis of transpiration for Populus euphratica in a desert riparian forest

NASA Astrophysics Data System (ADS)

Si, J.; Li, W.; Feng, Q.

2013-12-01

Water consumption information of the forest stand is the most important factor for regional water resources management. However, water consumption of individual trees are usually measured based on the limited sample trees , so, it is an important issue how to realize eventual scaling up of data from a series of sample trees to entire stand. Estimation of sap flow flux density (Fd) and stand sapwood area (AS-stand) are among the most critical factors for determining forest stand transpiration using sap flow measurement. To estimate Fd, the various links in sap flow technology have great impact on the measurement of sap flow, to estimate AS-stand, an appropriate indirect technique for measuring each tree sapwood area (AS-tree) is required, because it is impossible to measure the AS-tree of all trees in a forest stand. In this study, Fd was measured in 2 mature P. euphratic trees at several radial depths, 0~10, 10~30mm, using sap flow sensors with the heat ratio method, the relationship model between AS-tree and stem diameter (DBH), growth model of AS-tree were established, using investigative original data of DBH, tree-age, and AS-tree. The results revealed that it can achieve scaling up of transpiration from sample trees to entire forest stand using AS-tree and Fd, however, the transpiration of forest stand (E) will be overvalued by 12.6% if using Fd of 0~10mm, and it will be underestimated by 25.3% if using Fd of 10~30mm, it implied that major uncertainties in mean stand Fd estimations are caused by radial variations in Fd. E will be obviously overvalued when the AS-stand is constant, this result imply that it is the key to improve the prediction accuracy that how to simulate the AS-stand changes in the day scale; They also showed that the potential errors in transpiration with a sample size of approximately ≥30 were almost stable for P.euphrtica, this suggests that to make an allometric equation it might be necessary to sample at least 30 trees.

Local concurrent error detection and correction in data structures using virtual backpointers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, C.C.J.; Chen, P.P.; Fuchs, W.K.

1989-11-01

A new technique, based on virtual backpointers, is presented in this paper for local concurrent error detection and correction in linked data structures. Two new data structures utilizing virtual backpointers, the Virtual Double-Linked List and the B-Tree and Virtual Backpointers, are described. For these structures, double errors within a fixed-size checking window can be detected in constant time and single errors detected during forward moves can be corrected in constant time.

Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China

PubMed Central

Gao, Huilin; Dong, Lihu; Li, Fengri; Zhang, Lianjun

2015-01-01

A total of 89 trees of Korean pine (Pinus koraiensis) were destructively sampled from the plantations in Heilongjiang Province, P.R. China. The sample trees were measured and calculated for the biomass and carbon stocks of tree components (i.e., stem, branch, foliage and root). Both compatible biomass and carbon stock models were developed with the total biomass and total carbon stocks as the constraints, respectively. Four methods were used to evaluate the carbon stocks of tree components. The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). The other three methods indirectly predicted the carbon stocks in two steps: (1) estimating the biomass by the compatible biomass models, and (2) multiplying the estimated biomass by three different carbon conversion factors (i.e., carbon conversion factor 0.5 (Method 2), average carbon concentration of the sample trees (Method 3), and average carbon concentration of each tree component (Method 4)). The prediction errors of estimating the carbon stocks were compared and tested for the differences between the four methods. The results showed that the compatible biomass and carbon models with tree diameter (D) as the sole independent variable performed well so that Method 1 was the best method for predicting the carbon stocks of tree components and total. There were significant differences among the four methods for the carbon stock of stem. Method 2 produced the largest error, especially for stem and total. Methods 3 and Method 4 were slightly worse than Method 1, but the differences were not statistically significant. In practice, the indirect method using the mean carbon concentration of individual trees was sufficient to obtain accurate carbon stocks estimation if carbon stocks models are not available. PMID:26659257

[Rapid prediction of annual ring density of Paulownia elongate standing tress using near infrared spectroscopy].

PubMed

Jiang, Ze-Hui; Wang, Yu-Rong; Fei, Ben-Hua; Fu, Feng; Hse, Chung-Yun

2007-06-01

Rapid prediction of annual ring density of Paulownia elongate standing trees using near infrared spectroscopy was studied. It was non-destructive to collect the samples for trees, that is, the wood cores 5 mm in diameter were unthreaded at the breast height of standing trees instead of fallen trees. Then the spectra data were collected by autoscan method of NIR. The annual ring density was determined by mercury immersion. And the models were made and analyzed by the partial least square (PLS) and full cross validation in the 350-2 500 nm wavelength range. The results showed that high coefficients were obtained between the annual ring and the NIR fitted data. The correlation coefficient of prediction model was 0.88 and 0.91 in the middle diameter and bigger diameter, respectively. Moreover, high coefficients of correlation were also obtained between annual ring density laboratory-determined and the NIR fitted data in the middle diameter of Paulownia elongate standing trees, the correlation coefficient of calibration model and prediction model were 0.90 and 0.83, and the standard errors of calibration (SEC) and standard errors of prediction(SEP) were 0.012 and 0.016, respectively. The method can simply, rapidly and non-destructively estimate the annual ring density of the Paulownia elongate standing trees close to the cutting age.

30 CFR 817.116 - Revegetation: Standards for success.

Code of Federal Regulations, 2011 CFR

2011-07-01

... confidence interval (i.e., a one-sided test with a 0.10 alpha error). (b) Standards for success shall be... tree and shrub stocking and vegetative ground cover. Such parameters are described as follows: (i... either a programwide or a permit-specific basis. (ii) Trees and shrubs that will be used in determining...

30 CFR 816.116 - Revegetation: Standards for success.

Code of Federal Regulations, 2011 CFR

2011-07-01

... confidence interval (i.e., one-sided test with a 0.10 alpha error). (b) Standards for success shall be... tree and shrub stocking and vegetative ground cover. Such parameters are described as follows: (i... either a programwide or a permit-specific basis. (ii) Trees and shrubs that will be used in determining...

Surface temperature dataset for North America obtained by application of optimal interpolation algorithm merging tree-ring chronologies and climate model output

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Wang, Shaowu; Tian, Qinhua

2017-02-01

A new dataset of surface temperature over North America has been constructed by merging climate model results and empirical tree-ring data through the application of an optimal interpolation algorithm. Errors of both the Community Climate System Model version 4 (CCSM4) simulation and the tree-ring reconstruction were considered to optimize the combination of the two elements. Variance matching was used to reconstruct the surface temperature series. The model simulation provided the background field, and the error covariance matrix was estimated statistically using samples from the simulation results with a running 31-year window for each grid. Thus, the merging process could continue with a time-varying gain matrix. This merging method (MM) was tested using two types of experiment, and the results indicated that the standard deviation of errors was about 0.4 °C lower than the tree-ring reconstructions and about 0.5 °C lower than the model simulation. Because of internal variabilities and uncertainties in the external forcing data, the simulated decadal warm-cool periods were readjusted by the MM such that the decadal variability was more reliable (e.g., the 1940-1960s cooling). During the two centuries (1601-1800 AD) of the preindustrial period, the MM results revealed a compromised spatial pattern of the linear trend of surface temperature, which is in accordance with the phase transition of the Pacific decadal oscillation and Atlantic multidecadal oscillation. Compared with pure CCSM4 simulations, it was demonstrated that the MM brought a significant improvement to the decadal variability of the gridded temperature via the merging of temperature-sensitive tree-ring records.

Rewriting evolution--"been there, done that".

PubMed

Penny, David

2013-01-01

A recent paper by a science journalist in Nature shows major errors in understanding phylogenies, in this case of placental mammals. The underlying unrooted tree is probably correct, but the placement of the root just reflects a well-known error from the acceleration in the rate of evolution among some myomorph rodents.

Highly improved staggered quarks on the lattice with applications to charm physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Follana, E.; Davies, C.; Wong, K.

2007-03-01

We use perturbative Symanzik improvement to create a new staggered-quark action (HISQ) that has greatly reduced one-loop taste-exchange errors, no tree-level order a{sup 2} errors, and no tree-level order (am){sup 4} errors to leading order in the quark's velocity v/c. We demonstrate with simulations that the resulting action has taste-exchange interactions that are 3-4 times smaller than the widely used ASQTAD action. We show how to bound errors due to taste exchange by comparing ASQTAD and HISQ simulations, and demonstrate with simulations that such errors are likely no more than 1% when HISQ is used for light quarks at latticemore » spacings of 1/10 fm or less. The suppression of (am){sup 4} errors also makes HISQ the most accurate discretization currently available for simulating c quarks. We demonstrate this in a new analysis of the {psi}-{eta}{sub c} mass splitting using the HISQ action on lattices where am{sub c}=0.43 and 0.66, with full-QCD gluon configurations (from MILC). We obtain a result of 111(5) MeV which compares well with the experiment. We discuss applications of this formalism to D physics and present our first high-precision results for D{sub s} mesons.« less

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Density variations and their influence on carbon stocks: case-study on two Biosphere Reserves in the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

De Ridder, Maaike; De Haulleville, Thalès; Kearsley, Elizabeth; Van den Bulcke, Jan; Van Acker, Joris; Beeckman, Hans

2014-05-01

It is commonly acknowledged that allometric equations for aboveground biomass and carbon stock estimates are improved significantly if density is included as a variable. However, not much attention is given to this variable in terms of exact, measured values and density profiles from pith to bark. Most published case-studies obtain density values from literature sources or databases, this way using large ranges of density values and possible causing significant errors in carbon stock estimates. The use of one single fixed value for density is also not recommended if carbon stock increments are estimated. Therefore, our objective is to measure and analyze a large number of tree species occurring in two Biosphere Reserves (Luki and Yangambi). Nevertheless, the diversity of tree species in these tropical forests is too high to perform this kind of detailed analysis on all tree species (> 200/ha). Therefore, we focus on the most frequently encountered tree species with high abundance (trees/ha) and dominance (basal area/ha) for this study. Increment cores were scanned with a helical X-ray protocol to obtain density profiles from pith to bark. This way, we aim at dividing the tree species with a distinct type of density profile into separate groups. If, e.g., slopes in density values from pith to bark remain stable over larger samples of one tree species, this slope could also be used to correct for errors in carbon (increment) estimates, caused by density values from simplified density measurements or density values from literature. In summary, this is most likely the first study in the Congo Basin that focuses on density patterns in order to check their influence on carbon stocks and differences in carbon stocking based on species composition (density profiles ~ temperament of tree species).

Perception of Pine Trees among Citizens of the Balearic Islands: Analysis and Description of Some Mistaken Ideas

ERIC Educational Resources Information Center

Sureda-Negre, Jaume; Catalan-Fernandez, Albert; Comas-Forgas, Ruben; Fagan, Geoffrey; Llabres-Bernat, Antonia

2011-01-01

In this article, the authors analyze evidence regarding the dissemination of mistaken ideas concerning the presence and function of pine trees ("Pinus halepensis") in a Mediterranean archipelago: the Balearic Islands (Spain). The main errors concerning the natural vegetation that are disseminated among citizens by the forest management…

Biomass Determination Using Wood Specific Gravity from Increment Cores

Treesearch

Michael C. Wiemann; G. Bruce Williamson

2013-01-01

Wood specific gravity (SG) is one of the most important variables used to determine biomass. Measurement of SG is problematic because it requires tedious, and often difficult, sampling of wood from standing trees. Sampling is complicated because the SG usually varies nonrandomly within trees, resulting in systematic errors. Off-center pith and hollow or decayed stems...

Characterization and visualization of the accuracy of FIA's CONUS-wide tree species datasets

Treesearch

Rachel Riemann; Barry T. Wilson

2014-01-01

Modeled geospatial datasets have been created for 325 tree species across the contiguous United States (CONUS). Effective application of all geospatial datasets depends on their accuracy. Dataset error can be systematic (bias) or unsystematic (scatter), and their magnitude can vary by region and scale. Each of these characteristics affects the locations, scales, uses,...

A potential quantitative method for assessing individual tree performance

Treesearch

Lance A. Vickers; David R. Larsen; Daniel C. Dey; John M. Kabrick; Benjamin O. Knapp

2014-01-01

By what standard should a tree be judged? This question, perhaps unknowingly, is posed almost daily by practicing foresters. Unfortunately, there are few cases in which clearly defined quantitative (i.e., directly measurable) references have been established in forestry. A lack of common references may be an unnecessary source of error in silvicultural application and...

Batch reporting of forest inventory statistics using the EVALIDator

Treesearch

Patrick D. Miles

2015-01-01

The EVALIDator Web application, developed in 2007, provides estimates and sampling errors of forest statistics (e.g., forest area, number of trees, tree biomass) from data stored in the Forest Inventory and Analysis database. In response to user demand, new features have been added to the EVALIDator. The most recent additions are 1) the ability to generate multiple...

Interception loss, throughfall and stemflow in a maritime pine stand. I. Variability of throughfall and stemflow beneath the pine canopy

NASA Astrophysics Data System (ADS)

Loustau, D.; Berbigier, P.; Granier, A.; Moussa, F. El Hadj

1992-10-01

Patterns of spatial variability of throughfall and stemflow were determined in a maritime pine ( Pinus pinaster Ait.) stand for two consecutive years. Data were obtained from 52 fixed rain gauges and 12 stemflow measuring devices located in a 50m × 50m plot at the centre of an 18-year-old stand. The pine trees had been sown in rows 4m apart and had reached an average height of 12.6m. The spatial distribution of stems had a negligible effect on the throughfall partitioning beneath the canopy. Variograms of throughfall computed for a sample of storms did not reveal any spatial autocorrelation of throughfall for the sampling design used. Differences in throughfall, in relation to the distance from the rows, were not consistently significant. In addition, the distance from the tree stem did not influence the amount of throughfall. The confidence interval on the amount of throughfall per storm was between 3 and 8%. The stemflow was highly variable between trees. The effect of individual trees on stemflow was significant but the amount of stemflow per tree was not related to tree size (i.e. height, trunk diameter, etc.). The cumulative sampling errors on stemflow and throughfall for a single storm created a confidence interval of between ±7 and ±51% on interception. This resulted mainly from the low interception rate and sampling error on throughfall.

Mars Science Laboratory Frame Manager for Centralized Frame Tree Database and Target Pointing

NASA Technical Reports Server (NTRS)

Kim, Won S.; Leger, Chris; Peters, Stephen; Carsten, Joseph; Diaz-Calderon, Antonio

2013-01-01

The FM (Frame Manager) flight software module is responsible for maintaining the frame tree database containing coordinate transforms between frames. The frame tree is a proper tree structure of directed links, consisting of surface and rover subtrees. Actual frame transforms are updated by their owner. FM updates site and saved frames for the surface tree. As the rover drives to a new area, a new site frame with an incremented site index can be created. Several clients including ARM and RSM (Remote Sensing Mast) update their related rover frames that they own. Through the onboard centralized FM frame tree database, client modules can query transforms between any two frames. Important applications include target image pointing for RSM-mounted cameras and frame-referenced arm moves. The use of frame tree eliminates cumbersome, error-prone calculations of coordinate entries for commands and thus simplifies flight operations significantly.

Rewriting Evolution—“Been There, Done That”

PubMed Central

Penny, David

2013-01-01

A recent paper by a science journalist in Nature shows major errors in understanding phylogenies, in this case of placental mammals. The underlying unrooted tree is probably correct, but the placement of the root just reflects a well-known error from the acceleration in the rate of evolution among some myomorph rodents. PMID:23558594

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, R.; Beaudet, P.

1982-01-01

An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

Methods for estimating aboveground biomass and its components for Douglas-fir and lodgepole pine trees

Treesearch

K.P. Poudel; H. Temesgen

2016-01-01

Estimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and (or) its components based on the bias and root mean squared error (RMSE) that...

Ground-based digital imagery for tree stem analysis

Treesearch

Neil Clark; Daniel L. Schmoldt; Randolph H. Wynne; Matthew F. Winn; Philip A. Araman

2000-01-01

In the USA, a subset of permanent forest sample plots within each geographic region are intensively measured to obtain estimates of tree volume and products. The detailed field measurements required for this type of sampling are both time consuming and error prone. We are attempting to reduce both of these factors with the aid of a commercially-available solid-state...

Sampling plantations to determine white-pine weevil injury

Treesearch

Robert L. Talerico; Robert W., Jr. Wilson

1973-01-01

Use of 1/10-acre square plots to obtain estimates of the proportion of never-weeviled trees necessary for evaluating and scheduling white-pine weevil control is described. The optimum number of trees to observe per plot is estimated from data obtained from sample plantations in the Northeast and a table is given. Of sample size required to achieve a standard error of...

LIDAR forest inventory with single-tree, double- and single-phase procedures

Treesearch

Robert C. Parker; David L. Evans

2009-01-01

Light Detection and Ranging (LIDAR) data at 0.5- to 2-m postings were used with doublesample, stratified inventory procedures involving single-tree attribute relationships in mixed, natural, and planted species stands to yield sampling errors (one-half the confidence interval expressed as a percentage of the mean) ranging from ±2.1 percent to ±11.5...

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

PubMed

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

A dual growing method for the automatic extraction of individual trees from mobile laser scanning data

NASA Astrophysics Data System (ADS)

Li, Lin; Li, Dalin; Zhu, Haihong; Li, You

2016-10-01

Street trees interlaced with other objects in cluttered point clouds of urban scenes inhibit the automatic extraction of individual trees. This paper proposes a method for the automatic extraction of individual trees from mobile laser scanning data, according to the general constitution of trees. Two components of each individual tree - a trunk and a crown can be extracted by the dual growing method. This method consists of coarse classification, through which most of artifacts are removed; the automatic selection of appropriate seeds for individual trees, by which the common manual initial setting is avoided; a dual growing process that separates one tree from others by circumscribing a trunk in an adaptive growing radius and segmenting a crown in constrained growing regions; and a refining process that draws a singular trunk from the interlaced other objects. The method is verified by two datasets with over 98% completeness and over 96% correctness. The low mean absolute percentage errors in capturing the morphological parameters of individual trees indicate that this method can output individual trees with high precision.

[Individual tree diameter increment model for natural Betula platyphylla forests based on meteorological factors].

PubMed

Zhang, Hai Ping; Li, Feng Ri; Dong, Li Hu; Liu, Qiang

2017-06-18

Based on the 212 re-measured permanent plots for natural Betula platyphylla fore-sts in Daxing'an Mountains and Xiaoxing'an Mountains and 30 meteorological stations data, an individual tree growth model based on meteorological factors was constructed. The differences of stand and meteorological factors between Daxing'an Mountains and Xiaoxing'an Mountains were analyzed and the diameter increment model including the regional effects was developed by dummy variable approach. The results showed that the minimum temperature (T g min ) and mean precipitation (P g m ) in growing season were the main meteorological factors which affected the diameter increment in the two study areas. T g min and P g m were positively correlated with the diameter increment, but the influence strength of T g min was obviously different between the two research areas. The adjusted coefficient of determination (R a 2 ) of the diameter increment model with meteorological factors was 0.56 and had an 11% increase compared to the one without meteorological factors. It was concluded that meteorological factors could well explain the diameter increment of B. platyphylla. R a 2 of the model with regional effects was 0.59, and increased by 18% compared to the one without regional effects, and effectively solved the incompatible problem of parameters between the two research areas. The validation results showed that the individual tree diameter growth model with regional effect had the best prediction accuracy in estimating the diameter increment of B. platyphylla. The mean error, mean absolute error, mean error percent and mean prediction error percent were 0.0086, 0.4476, 5.8% and 20.0%, respectively. Overall, dummy variable model of individual tree diameter increment based on meteorological factors could well describe the diameter increment process of natural B. platyphylla in Daxing'an Mountains and Xiaoxing'an Mountains.

Soil respiration patterns in root gaps 27 years after small scale experimental disturbance in Pinus contorta forests

NASA Astrophysics Data System (ADS)

Baker, S.; Berryman, E.; Hawbaker, T. J.; Ewers, B. E.

2015-12-01

While much attention has been focused on large scale forest disturbances such as fire, harvesting, drought and insect attacks, small scale forest disturbances that create gaps in forest canopies and below ground root and mycorrhizal networks may accumulate to impact regional scale carbon budgets. In a lodgepole pine (Pinus contorta) forest near Fox Park, WY, clusters of 15 and 30 trees were removed in 1988 to assess the effect of tree gap disturbance on fine root density and nitrogen transformation. Twenty seven years later the gaps remain with limited regeneration present only in the center of the 30 tree plots, beyond the influence of roots from adjacent intact trees. Soil respiration was measured in the summer of 2015 to assess the influence of these disturbances on carbon cycling in Pinus contorta forests. Positions at the centers of experimental disturbances were found to have the lowest respiration rates (mean 2.45 μmol C/m2/s, standard error 0.17 C/m2/s), control plots in the undisturbed forest were highest (mean 4.15 μmol C/m2/s, standard error 0.63 C/m2/s), and positions near the margin of the disturbance were intermediate (mean 3.7 μmol C/m2/s, standard error 0.34 C/m2/s). Fine root densities, soil nitrogen, and microclimate changes were also measured and played an important role in respiration rates of disturbed plots. This demonstrates that a long-term effect on carbon cycling occurs when gaps are created in the canopy and root network of lodgepole forests.

New Splitting Criteria for Decision Trees in Stationary Data Streams.

PubMed

Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

2018-06-01

The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

Combining airborne laser scanning and Landsat data for statistical modeling of soil carbon and tree biomass in Tanzanian Miombo woodlands.

PubMed

Egberth, Mikael; Nyberg, Gert; Næsset, Erik; Gobakken, Terje; Mauya, Ernest; Malimbwi, Rogers; Katani, Josiah; Chamuya, Nurudin; Bulenga, George; Olsson, Håkan

2017-12-01

Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations. Cross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon. The results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.

Weighted linear regression using D2H and D2 as the independent variables

Treesearch

Hans T. Schreuder; Michael S. Williams

1998-01-01

Several error structures for weighted regression equations used for predicting volume were examined for 2 large data sets of felled and standing loblolly pine trees (Pinus taeda L.). The generally accepted model with variance of error proportional to the value of the covariate squared ( D2H = diameter squared times height or D...

Detecting and overcoming systematic errors in genome-scale phylogenies.

PubMed

Rodríguez-Ezpeleta, Naiara; Brinkmann, Henner; Roure, Béatrice; Lartillot, Nicolas; Lang, B Franz; Philippe, Hervé

2007-06-01

Genome-scale data sets result in an enhanced resolution of the phylogenetic inference by reducing stochastic errors. However, there is also an increase of systematic errors due to model violations, which can lead to erroneous phylogenies. Here, we explore the impact of systematic errors on the resolution of the eukaryotic phylogeny using a data set of 143 nuclear-encoded proteins from 37 species. The initial observation was that, despite the impressive amount of data, some branches had no significant statistical support. To demonstrate that this lack of resolution is due to a mutual annihilation of phylogenetic and nonphylogenetic signals, we created a series of data sets with slightly different taxon sampling. As expected, these data sets yielded strongly supported but mutually exclusive trees, thus confirming the presence of conflicting phylogenetic and nonphylogenetic signals in the original data set. To decide on the correct tree, we applied several methods expected to reduce the impact of some kinds of systematic error. Briefly, we show that (i) removing fast-evolving positions, (ii) recoding amino acids into functional categories, and (iii) using a site-heterogeneous mixture model (CAT) are three effective means of increasing the ratio of phylogenetic to nonphylogenetic signal. Finally, our results allow us to formulate guidelines for detecting and overcoming phylogenetic artefacts in genome-scale phylogenetic analyses.

Combining task analysis and fault tree analysis for accident and incident analysis: a case study from Bulgaria.

PubMed

Doytchev, Doytchin E; Szwillus, Gerd

2009-11-01

Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident - the flooding of the plant's basement - was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.

Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

NASA Astrophysics Data System (ADS)

Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

2015-10-01

Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species' soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53 % of felled, 39 % of drilled, and 28 % of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1-82.8 %) and averaged 9 % across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13 % in trees 10-30 cm DBH to 54 % in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7 % relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation, but also that it strongly covaries with tree size, taxonomy, habitat association, and soil resources, underscoring the need to account for tree community composition and edaphic variation in estimating carbon storage in tropical forests.

Wood Made from Water?: An Introduction to Photosynthesis Based on a Historical Error

ERIC Educational Resources Information Center

Wrigley, Colin

2012-01-01

Three and a half centuries ago, a five-year experiment was conducted involving the growth of a willow tree in a pot which received only water. The conclusion, that a tree is therefore made solely from water, was not so ridiculous when there was still general acceptance of the Aristotelian view of only four "elements": water, earth, fire and air.…

Crown-rise and crown-length dynamics: applications to loblolly pine

Treesearch

Harry T. Valentine; Ralph L. Amateis; Jeffrey H. Gove; Annikki Makela

2013-01-01

The original crown-rise model estimates the average height of a crown-base in an even-aged mono-species stand of trees. We have elaborated this model to reduce bias and prediction error, and to also provide crown-base estimates for individual trees. Results for the latter agree with a theory of branch death based on resource availability and allocation.We use the...

MulRF: a software package for phylogenetic analysis using multi-copy gene trees.

PubMed

Chaudhary, Ruchi; Fernández-Baca, David; Burleigh, John Gordon

2015-02-01

MulRF is a platform-independent software package for phylogenetic analysis using multi-copy gene trees. It seeks the species tree that minimizes the Robinson-Foulds (RF) distance to the input trees using a generalization of the RF distance to multi-labeled trees. The underlying generic tree distance measure and fast running time make MulRF useful for inferring phylogenies from large collections of gene trees, in which multiple evolutionary processes as well as phylogenetic error may contribute to gene tree discord. MulRF implements several features for customizing the species tree search and assessing the results, and it provides a user-friendly graphical user interface (GUI) with tree visualization. The species tree search is implemented in C++ and the GUI in Java Swing. MulRF's executable as well as sample datasets and manual are available at http://genome.cs.iastate.edu/CBL/MulRF/, and the source code is available at https://github.com/ruchiherself/MulRFRepo. ruchic@ufl.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Measurements of stem diameter: implications for individual- and stand-level errors.

PubMed

Paul, Keryn I; Larmour, John S; Roxburgh, Stephen H; England, Jacqueline R; Davies, Micah J; Luck, Hamish D

2017-08-01

Stem diameter is one of the most common measurements made to assess the growth of woody vegetation, and the commercial and environmental benefits that it provides (e.g. wood or biomass products, carbon sequestration, landscape remediation). Yet inconsistency in its measurement is a continuing source of error in estimates of stand-scale measures such as basal area, biomass, and volume. Here we assessed errors in stem diameter measurement through repeated measurements of individual trees and shrubs of varying size and form (i.e. single- and multi-stemmed) across a range of contrasting stands, from complex mixed-species plantings to commercial single-species plantations. We compared a standard diameter tape with a Stepped Diameter Gauge (SDG) for time efficiency and measurement error. Measurement errors in diameter were slightly (but significantly) influenced by size and form of the tree or shrub, and stem height at which the measurement was made. Compared to standard tape measurement, the mean systematic error with SDG measurement was only -0.17 cm, but varied between -0.10 and -0.52 cm. Similarly, random error was relatively large, with standard deviations (and percentage coefficients of variation) averaging only 0.36 cm (and 3.8%), but varying between 0.14 and 0.61 cm (and 1.9 and 7.1%). However, at the stand scale, sampling errors (i.e. how well individual trees or shrubs selected for measurement of diameter represented the true stand population in terms of the average and distribution of diameter) generally had at least a tenfold greater influence on random errors in basal area estimates than errors in diameter measurements. This supports the use of diameter measurement tools that have high efficiency, such as the SDG. Use of the SDG almost halved the time required for measurements compared to the diameter tape. Based on these findings, recommendations include the following: (i) use of a tape to maximise accuracy when developing allometric models, or when monitoring relatively small changes in permanent sample plots (e.g. National Forest Inventories), noting that care is required in irregular-shaped, large-single-stemmed individuals, and (ii) use of a SDG to maximise efficiency when using inventory methods to assess basal area, and hence biomass or wood volume, at the stand scale (i.e. in studies of impacts of management or site quality) where there are budgetary constraints, noting the importance of sufficient sample sizes to ensure that the population sampled represents the true population.

GIZMO: Multi-method magneto-hydrodynamics+gravity code

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2014-10-01

GIZMO is a flexible, multi-method magneto-hydrodynamics+gravity code that solves the hydrodynamic equations using a variety of different methods. It introduces new Lagrangian Godunov-type methods that allow solving the fluid equations with a moving particle distribution that is automatically adaptive in resolution and avoids the advection errors, angular momentum conservation errors, and excessive diffusion problems that seriously limit the applicability of “adaptive mesh” (AMR) codes, while simultaneously avoiding the low-order errors inherent to simpler methods like smoothed-particle hydrodynamics (SPH). GIZMO also allows the use of SPH either in “traditional” form or “modern” (more accurate) forms, or use of a mesh. Self-gravity is solved quickly with a BH-Tree (optionally a hybrid PM-Tree for periodic boundaries) and on-the-fly adaptive gravitational softenings. The code is descended from P-GADGET, itself descended from GADGET-2 (ascl:0003.001), and many of the naming conventions remain (for the sake of compatibility with the large library of GADGET work and analysis software).

Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

NASA Technical Reports Server (NTRS)

Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)

2000-01-01

This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

Phylesystem: a git-based data store for community-curated phylogenetic estimates.

PubMed

McTavish, Emily Jane; Hinchliff, Cody E; Allman, James F; Brown, Joseph W; Cranston, Karen A; Holder, Mark T; Rees, Jonathan A; Smith, Stephen A

2015-09-01

Phylogenetic estimates from published studies can be archived using general platforms like Dryad (Vision, 2010) or TreeBASE (Sanderson et al., 1994). Such services fulfill a crucial role in ensuring transparency and reproducibility in phylogenetic research. However, digital tree data files often require some editing (e.g. rerooting) to improve the accuracy and reusability of the phylogenetic statements. Furthermore, establishing the mapping between tip labels used in a tree and taxa in a single common taxonomy dramatically improves the ability of other researchers to reuse phylogenetic estimates. As the process of curating a published phylogenetic estimate is not error-free, retaining a full record of the provenance of edits to a tree is crucial for openness, allowing editors to receive credit for their work and making errors introduced during curation easier to correct. Here, we report the development of software infrastructure to support the open curation of phylogenetic data by the community of biologists. The backend of the system provides an interface for the standard database operations of creating, reading, updating and deleting records by making commits to a git repository. The record of the history of edits to a tree is preserved by git's version control features. Hosting this data store on GitHub (http://github.com/) provides open access to the data store using tools familiar to many developers. We have deployed a server running the 'phylesystem-api', which wraps the interactions with git and GitHub. The Open Tree of Life project has also developed and deployed a JavaScript application that uses the phylesystem-api and other web services to enable input and curation of published phylogenetic statements. Source code for the web service layer is available at https://github.com/OpenTreeOfLife/phylesystem-api. The data store can be cloned from: https://github.com/OpenTreeOfLife/phylesystem. A web application that uses the phylesystem web services is deployed at http://tree.opentreeoflife.org/curator. Code for that tool is available from https://github.com/OpenTreeOfLife/opentree. mtholder@gmail.com. © The Author 2015. Published by Oxford University Press.

A Sensitivity Analysis of a Map of Habitat Quality for the California Spotted Owl (Strix occidentalis occidentalis) in southern California

Treesearch

Ellen M. Hines; Janet Franklin

1997-01-01

Using a Geographic Information System (GIS), a sensitivity analysis was performed on estimated mapping errors in vegetation type, forest canopy cover percentage, and tree crown size to determine the possible effects error in these data might have on delineating suitable habitat for the California Spotted Owl (Strix occidentalis occidentalis) in...

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Calibration and Validation of Landsat Tree Cover in the Taiga-Tundra Ecotone

NASA Technical Reports Server (NTRS)

Montesano, Paul Mannix; Neigh, Christopher S. R.; Sexton, Joseph; Feng, Min; Channan, Saurabh; Ranson, Kenneth J.; Townshend, John R.

2016-01-01

Monitoring current forest characteristics in the taiga-tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover greater than 80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

Land surveys show regional variability of historical fire regimes and dry forest structure of the western United States.

PubMed

Baker, William L; Williams, Mark A

2018-03-01

An understanding of how historical fire and structure in dry forests (ponderosa pine, dry mixed conifer) varied across the western United States remains incomplete. Yet, fire strongly affects ecosystem services, and forest restoration programs are underway. We used General Land Office survey reconstructions from the late 1800s across 11 landscapes covering ~1.9 million ha in four states to analyze spatial variation in fire regimes and forest structure. We first synthesized the state of validation of our methods using 20 modern validations, 53 historical cross-validations, and corroborating evidence. These show our method creates accurate reconstructions with low errors. One independent modern test reported high error, but did not replicate our method and made many calculation errors. Using reconstructed parameters of historical fire regimes and forest structure from our validated methods, forests were found to be non-uniform across the 11 landscapes, but grouped together in three geographical areas. Each had a mixture of fire severities, but dominated by low-severity fire and low median tree density in Arizona, mixed-severity fire and intermediate to high median tree density in Oregon-California, and high-severity fire and intermediate median tree density in Colorado. Programs to restore fire and forest structure could benefit from regional frameworks, rather than one size fits all. © 2018 by the Ecological Society of America.

Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

NASA Astrophysics Data System (ADS)

Chen, Qi

2015-08-01

Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

Digital terrestrial photogrammetric methods for tree stem analysis

Treesearch

Neil A. Clark; Randolph H. Wynne; Daniel L. Schmoldt; Matt Winn

2000-01-01

A digital camera was used to measure diameters at various heights along the stem on 20 red oak trees. Diameter at breast height ranged from 16 to over 60 cm, and height to a 10-cm top ranged from 12 to 20 m. The chi-square maximum anticipated error of geometric mean diameter estimates at the 95 percent confidence level was within ±4 cm for all heights when...

Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data

USGS Publications Warehouse

Wright, C.; Gallant, Alisa L.

2007-01-01

The U.S. Fish and Wildlife Service uses the term palustrine wetland to describe vegetated wetlands traditionally identified as marsh, bog, fen, swamp, or wet meadow. Landsat TM imagery was combined with image texture and ancillary environmental data to model probabilities of palustrine wetland occurrence in Yellowstone National Park using classification trees. Model training and test locations were identified from National Wetlands Inventory maps, and classification trees were built for seven years spanning a range of annual precipitation. At a coarse level, palustrine wetland was separated from upland. At a finer level, five palustrine wetland types were discriminated: aquatic bed (PAB), emergent (PEM), forested (PFO), scrub–shrub (PSS), and unconsolidated shore (PUS). TM-derived variables alone were relatively accurate at separating wetland from upland, but model error rates dropped incrementally as image texture, DEM-derived terrain variables, and other ancillary GIS layers were added. For classification trees making use of all available predictors, average overall test error rates were 7.8% for palustrine wetland/upland models and 17.0% for palustrine wetland type models, with consistent accuracies across years. However, models were prone to wetland over-prediction. While the predominant PEM class was classified with omission and commission error rates less than 14%, we had difficulty identifying the PAB and PSS classes. Ancillary vegetation information greatly improved PSS classification and moderately improved PFO discrimination. Association with geothermal areas distinguished PUS wetlands. Wetland over-prediction was exacerbated by class imbalance in likely combination with spatial and spectral limitations of the TM sensor. Wetland probability surfaces may be more informative than hard classification, and appear to respond to climate-driven wetland variability. The developed method is portable, relatively easy to implement, and should be applicable in other settings and over larger extents.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Application of the FTA and ETA Method for Gas Hazard Identification for the Performance of Safety Systems in the Industrial Department

NASA Astrophysics Data System (ADS)

Ignac-Nowicka, Jolanta

2018-03-01

The paper analyzes the conditions of safe use of industrial gas systems and factors influencing gas hazards. Typical gas installation and its basic features have been characterized. The results of gas threat analysis in an industrial enterprise using FTA error tree method and ETA event tree method are presented. Compares selected methods of identifying hazards gas industry with respect to the scope of their use. The paper presents an analysis of two exemplary hazards: an industrial gas catastrophe (FTA) and an explosive gas explosion (ETA). In both cases, technical risks and human errors (human factor) were taken into account. The cause-effect relationships of hazards and their causes are presented in the form of diagrams in the drawings.

Multistage classification of multispectral Earth observational data: The design approach

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Muasher, M. J.; Landgrebe, D. A.

1981-01-01

An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

Standard error of estimated average timber volume per acre under point sampling when trees are measured for volume on a subsample of all points.

Treesearch

Floyd A. Johnson

1961-01-01

This report assumes a knowledge of the principles of point sampling as described by Grosenbaugh, Bell and Alexander, and others. Whenever trees are counted at every point in a sample of points (large sample) and measured for volume at a portion (small sample) of these points, the sampling design could be called ratio double sampling. If the large...

A Tree Locality-Sensitive Hash for Secure Software Testing

DTIC Science & Technology

2017-09-14

errors, or to look for vulnerabilities that could allow a nefarious actor to use our software against us. Ultimately, all testing is designed to find...and an equivalent number of feasible paths discovered by Klee. 1.5 Summary This document the Tree Locality-Sensitive Hash (TLSH), a locality-senstive...performing two groups of tests that verify the accuracy and usefulness of TLSH. Chapter 5 summarizes the contents of the dissertation and lists avenues

Self-Configuration and Localization in Ad Hoc Wireless Sensor Networks

DTIC Science & Technology

2010-08-31

Goddard I. SUMMARY OF CONTRIBUTIONS We explored the error mechanisms of iterative decoding of low-density parity-check ( LDPC ) codes . This work has resulted...important problems in the area of channel coding , as their unpredictable behavior has impeded the deployment of LDPC codes in many real-world applications. We...tree-based decoders of LDPC codes , including the extrinsic tree decoder, and an investigation into their performance and bounding capabilities [5], [6

Optimum Array Processing for Detecting Binary Signals Corrupted by Directional Interference.

DTIC Science & Technology

1972-12-01

specific cases. Two different series representations of a vector random process are discussed in Van Trees [3]. These two methods both require the... spaci ~ng d, etc.) its detection error represents a lower bound for the performance that might be obtained with other types of array processing (such...Middleton, Introduction to Statistical Communication Theory, New York: McGraw-Hill, 1960. 3. H.L. Van Trees , Detection, Estimation, and Modulation Theory

Automated construction of arterial and venous trees in retinal images.

PubMed

Hu, Qiao; Abràmoff, Michael D; Garvin, Mona K

2015-10-01

While many approaches exist to segment retinal vessels in fundus photographs, only a limited number focus on the construction and disambiguation of arterial and venous trees. Previous approaches are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to large vessels. We propose a more global framework to generate arteriovenous trees in retinal images, given a vessel segmentation. In particular, our approach consists of three stages. The first stage is to generate an overconnected vessel network, named the vessel potential connectivity map (VPCM), consisting of vessel segments and the potential connectivity between them. The second stage is to disambiguate the VPCM into multiple anatomical trees, using a graph-based metaheuristic algorithm. The third stage is to classify these trees into arterial or venous (A/V) trees. We evaluated our approach with a ground truth built based on a public database, showing a pixel-wise classification accuracy of 88.15% using a manual vessel segmentation as input, and 86.11% using an automatic vessel segmentation as input.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, C. C.; Chen, P. P.; Fuchs, W. K.

1987-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data structures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared databased of Virtual Double Linked Lists.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, Chung-Chi Jim; Chen, Paul Peichuan; Fuchs, W. Kent

1989-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data strutures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared database of Virtual Double Linked Lists.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Predictive models for radial sap flux variation in coniferous, diffuse-porous and ring-porous temperate trees.

PubMed

Berdanier, Aaron B; Miniat, Chelcy F; Clark, James S

2016-08-01

Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Consequences of Secondary Calibrations on Divergence Time Estimates.

PubMed

Schenk, John J

2016-01-01

Secondary calibrations (calibrations based on the results of previous molecular dating studies) are commonly applied in divergence time analyses in groups that lack fossil data; however, the consequences of applying secondary calibrations in a relaxed-clock approach are not fully understood. I tested whether applying the posterior estimate from a primary study as a prior distribution in a secondary study results in consistent age and uncertainty estimates. I compared age estimates from simulations with 100 randomly replicated secondary trees. On average, the 95% credible intervals of node ages for secondary estimates were significantly younger and narrower than primary estimates. The primary and secondary age estimates were significantly different in 97% of the replicates after Bonferroni corrections. Greater error in magnitude was associated with deeper than shallower nodes, but the opposite was found when standardized by median node age, and a significant positive relationship was determined between the number of tips/age of secondary trees and the total amount of error. When two secondary calibrated nodes were analyzed, estimates remained significantly different, and although the minimum and median estimates were associated with less error, maximum age estimates and credible interval widths had greater error. The shape of the prior also influenced error, in which applying a normal, rather than uniform, prior distribution resulted in greater error. Secondary calibrations, in summary, lead to a false impression of precision and the distribution of age estimates shift away from those that would be inferred by the primary analysis. These results suggest that secondary calibrations should not be applied as the only source of calibration in divergence time analyses that test time-dependent hypotheses until the additional error associated with secondary calibrations is more properly modeled to take into account increased uncertainty in age estimates.

Random forests of interaction trees for estimating individualized treatment effects in randomized trials.

PubMed

Su, Xiaogang; Peña, Annette T; Liu, Lei; Levine, Richard A

2018-04-29

Assessing heterogeneous treatment effects is a growing interest in advancing precision medicine. Individualized treatment effects (ITEs) play a critical role in such an endeavor. Concerning experimental data collected from randomized trials, we put forward a method, termed random forests of interaction trees (RFIT), for estimating ITE on the basis of interaction trees. To this end, we propose a smooth sigmoid surrogate method, as an alternative to greedy search, to speed up tree construction. The RFIT outperforms the "separate regression" approach in estimating ITE. Furthermore, standard errors for the estimated ITE via RFIT are obtained with the infinitesimal jackknife method. We assess and illustrate the use of RFIT via both simulation and the analysis of data from an acupuncture headache trial. Copyright © 2018 John Wiley & Sons, Ltd.

Learning to classify in large committee machines

NASA Astrophysics Data System (ADS)

O'kane, Dominic; Winther, Ole

1994-10-01

The ability of a two-layer neural network to learn a specific non-linearly-separable classification task, the proximity problem, is investigated using a statistical mechanics approach. Both the tree and fully connected architectures are investigated in the limit where the number K of hidden units is large, but still much smaller than the number N of inputs. Both have continuous weights. Within the replica symmetric ansatz, we find that for zero temperature training, the tree architecture exhibits a strong overtraining effect. For nonzero temperature the asymptotic error is lowered, but it is still higher than the corresponding value for the simple perceptron. The fully connected architecture is considered for two regimes. First, for a finite number of examples we find a symmetry among the hidden units as each performs equally well. The asymptotic generalization error is finite, and minimal for T-->∞ where it goes to the same value as for the simple perceptron. For a large number of examples we find a continuous transition to a phase with broken hidden-unit symmetry, which has an asymptotic generalization error equal to zero.

Analyzing contentious relationships and outlier genes in phylogenomics.

PubMed

Walker, Joseph F; Brown, Joseph W; Smith, Stephen A

2018-06-08

Recent studies have demonstrated that conflict is common among gene trees in phylogenomic studies, and that less than one percent of genes may ultimately drive species tree inference in supermatrix analyses. Here, we examined two datasets where supermatrix and coalescent-based species trees conflict. We identified two highly influential "outlier" genes in each dataset. When removed from each dataset, the inferred supermatrix trees matched the topologies obtained from coalescent analyses. We also demonstrate that, while the outlier genes in the vertebrate dataset have been shown in a previous study to be the result of errors in orthology detection, the outlier genes from a plant dataset did not exhibit any obvious systematic error and therefore may be the result of some biological process yet to be determined. While topological comparisons among a small set of alternate topologies can be helpful in discovering outlier genes, they can be limited in several ways, such as assuming all genes share the same topology. Coalescent species tree methods relax this assumption but do not explicitly facilitate the examination of specific edges. Coalescent methods often also assume that conflict is the result of incomplete lineage sorting (ILS). Here we explored a framework that allows for quickly examining alternative edges and support for large phylogenomic datasets that does not assume a single topology for all genes. For both datasets, these analyses provided detailed results confirming the support for coalescent-based topologies. This framework suggests that we can improve our understanding of the underlying signal in phylogenomic datasets by asking more targeted edge-based questions.

Uncertainty in sap flow-based transpiration due to xylem properties

NASA Astrophysics Data System (ADS)

Looker, N. T.; Hu, J.; Martin, J. T.; Jencso, K. G.

2014-12-01

Transpiration, the evaporative loss of water from plants through their stomata, is a key component of the terrestrial water balance, influencing streamflow as well as regional convective systems. From a plant physiological perspective, transpiration is both a means of avoiding destructive leaf temperatures through evaporative cooling and a consequence of water loss through stomatal uptake of carbon dioxide. Despite its hydrologic and ecological significance, transpiration remains a notoriously challenging process to measure in heterogeneous landscapes. Sap flow methods, which estimate transpiration by tracking the velocity of a heat pulse emitted into the tree sap stream, have proven effective for relating transpiration dynamics to climatic variables. To scale sap flow-based transpiration from the measured domain (often <5 cm of tree cross-sectional area) to the whole-tree level, researchers generally assume constancy of scale factors (e.g., wood thermal diffusivity (k), radial and azimuthal distributions of sap velocity, and conducting sapwood area (As)) through time, across space, and within species. For the widely used heat-ratio sap flow method (HRM), we assessed the sensitivity of transpiration estimates to uncertainty in k (a function of wood moisture content and density) and As. A sensitivity analysis informed by distributions of wood moisture content, wood density and As sampled across a gradient of water availability indicates that uncertainty in these variables can impart substantial error when scaling sap flow measurements to the whole tree. For species with variable wood properties, the application of the HRM assuming a spatially constant k or As may systematically over- or underestimate whole-tree transpiration rates, resulting in compounded error in ecosystem-scale estimates of transpiration.

Accuracy in estimation of timber assortments and stem distribution - A comparison of airborne and terrestrial laser scanning techniques

NASA Astrophysics Data System (ADS)

Kankare, Ville; Vauhkonen, Jari; Tanhuanpää, Topi; Holopainen, Markus; Vastaranta, Mikko; Joensuu, Marianna; Krooks, Anssi; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto

2014-11-01

Detailed information about timber assortments and diameter distributions is required in forest management. Forest owners can make better decisions concerning the timing of timber sales and forest companies can utilize more detailed information to optimize their wood supply chain from forest to factory. The objective here was to compare the accuracies of high-density laser scanning techniques for the estimation of tree-level diameter distribution and timber assortments. We also introduce a method that utilizes a combination of airborne and terrestrial laser scanning in timber assortment estimation. The study was conducted in Evo, Finland. Harvester measurements were used as a reference for 144 trees within a single clear-cut stand. The results showed that accurate tree-level timber assortments and diameter distributions can be obtained, using terrestrial laser scanning (TLS) or a combination of TLS and airborne laser scanning (ALS). Saw log volumes were estimated with higher accuracy than pulpwood volumes. The saw log volumes were estimated with relative root-mean-squared errors of 17.5% and 16.8% with TLS and a combination of TLS and ALS, respectively. The respective accuracies for pulpwood were 60.1% and 59.3%. The differences in the bucking method used also caused some large errors. In addition, tree quality factors highly affected the bucking accuracy, especially with pulpwood volume.

Applying fault tree analysis to the prevention of wrong-site surgery.

PubMed

Abecassis, Zachary A; McElroy, Lisa M; Patel, Ronak M; Khorzad, Rebeca; Carroll, Charles; Mehrotra, Sanjay

2015-01-01

Wrong-site surgery (WSS) is a rare event that occurs to hundreds of patients each year. Despite national implementation of the Universal Protocol over the past decade, development of effective interventions remains a challenge. We performed a systematic review of the literature reporting root causes of WSS and used the results to perform a fault tree analysis to assess the reliability of the system in preventing WSS and identifying high-priority targets for interventions aimed at reducing WSS. Process components where a single error could result in WSS were labeled with OR gates; process aspects reinforced by verification were labeled with AND gates. The overall redundancy of the system was evaluated based on prevalence of AND gates and OR gates. In total, 37 studies described risk factors for WSS. The fault tree contains 35 faults, most of which fall into five main categories. Despite the Universal Protocol mandating patient verification, surgical site signing, and a brief time-out, a large proportion of the process relies on human transcription and verification. Fault tree analysis provides a standardized perspective of errors or faults within the system of surgical scheduling and site confirmation. It can be adapted by institutions or specialties to lead to more targeted interventions to increase redundancy and reliability within the preoperative process. Copyright © 2015 Elsevier Inc. All rights reserved.

Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification.

PubMed

Ramírez, J; Górriz, J M; Segovia, F; Chaves, R; Salas-Gonzalez, D; López, M; Alvarez, I; Padilla, P

2010-03-19

This letter shows a computer aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The proposed method is based on partial least squares (PLS) regression model and a random forest (RF) predictor. The challenge of the curse of dimensionality is addressed by reducing the large dimensionality of the input data by downscaling the SPECT images and extracting score features using PLS. A RF predictor then forms an ensemble of classification and regression tree (CART)-like classifiers being its output determined by a majority vote of the trees in the forest. A baseline principal component analysis (PCA) system is also developed for reference. The experimental results show that the combined PLS-RF system yields a generalization error that converges to a limit when increasing the number of trees in the forest. Thus, the generalization error is reduced when using PLS and depends on the strength of the individual trees in the forest and the correlation between them. Moreover, PLS feature extraction is found to be more effective for extracting discriminative information from the data than PCA yielding peak sensitivity, specificity and accuracy values of 100%, 92.7%, and 96.9%, respectively. Moreover, the proposed CAD system outperformed several other recently developed AD CAD systems. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Improving estimation of tree carbon stocks by harvesting aboveground woody biomass within airborne LiDAR flight areas

NASA Astrophysics Data System (ADS)

Colgan, M.; Asner, G. P.; Swemmer, A. M.

2011-12-01

The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since harvesting of trees is not possible within KNP, this was a unique opportunity to fell trees already scheduled to be cleared for mining operations. The area was first flown by the Carnegie Airborne Observatory in early May, prior to harvest, to enable correlation of LiDAR-measured tree height and crown diameter to harvested tree mass. Results include over 4,000 harvested stems and 13 species-specific biomass equations, including seven Kruger woody species previously without allometry. We found existing biomass stem allometry over-estimates ACD in the field, whereas airborne estimates based on harvest data avoid this bias while maintaining similar precision to field-based estimates. Lastly, a new airborne algorithm estimating biomass at the tree-level reduced error from tree canopies "leaning" into field plots but whose stems are outside plot boundaries. These advances pave the way to better understanding of savanna and forest carbon density at landscape and regional scales.

[Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].

PubMed

Han, Zhao-ying; Zhu, Xi-cun; Fang, Xian-yi; Wang, Zhuo-yuan; Wang, Ling; Zhao, Geng-Xing; Jiang, Yuan-mao

2016-03-01

Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation. The Red Fuji apple trees of full bearing fruit are the researching objects. Ninety apple trees canopies spectral reflectance and LAI values were measured by the ASD Fieldspec3 spectrometer and LAI-2200 in thirty orchards in constant two years in Qixia research area of Shandong Province. The optimal vegetation indices were selected by the method of correlation analysis of the original spectral reflectance and vegetation indices. The models of predicting the LAI were built with the multivariate regression analysis method of support vector machine (SVM) and random forest (RF). The new vegetation indices, GNDVI527, ND-VI676, RVI682, FD-NVI656 and GRVI517 and the previous two main vegetation indices, NDVI670 and NDVI705, are in accordance with LAI. In the RF regression model, the calibration set decision coefficient C-R2 of 0.920 and validation set decision coefficient V-R2 of 0.889 are higher than the SVM regression model by 0.045 and 0.033 respectively. The root mean square error of calibration set C-RMSE of 0.249, the root mean square error validation set V-RMSE of 0.236 are lower than that of the SVM regression model by 0.054 and 0.058 respectively. Relative analysis of calibrating error C-RPD and relative analysis of validation set V-RPD reached 3.363 and 2.520, 0.598 and 0.262, respectively, which were higher than the SVM regression model. The measured and predicted the scatterplot trend line slope of the calibration set and validation set C-S and V-S are close to 1. The estimation result of RF regression model is better than that of the SVM. RF regression model can be used to estimate the LAI of red Fuji apple trees in full fruit period.

A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits.

PubMed

Czech, Lucas; Huerta-Cepas, Jaime; Stamatakis, Alexandros

2017-06-01

Phylogenetic trees are routinely visualized to present and interpret the evolutionary relationships of species. Most empirical evolutionary data studies contain a visualization of the inferred tree with branch support values. Ambiguous semantics in tree file formats can lead to erroneous tree visualizations and therefore to incorrect interpretations of phylogenetic analyses. Here, we discuss problems that arise when displaying branch values on trees after rerooting. Branch values are typically stored as node labels in the widely-used Newick tree format. However, such values are attributes of branches. Storing them as node labels can therefore yield errors when rerooting trees. This depends on the mostly implicit semantics that tools deploy to interpret node labels. We reviewed ten tree viewers and ten bioinformatics toolkits that can display and reroot trees. We found that 14 out of 20 of these tools do not permit users to select the semantics of node labels. Thus, unaware users might obtain incorrect results when rooting trees. We illustrate such incorrect mappings for several test cases and real examples taken from the literature. This review has already led to improvements in eight tools. We suggest tools should provide options that explicitly force users to define the semantics of node labels. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Calibration of the Diameter Distribution Derived from the Area-based Approach with Individual Tree-based Diameter Estimates Using the Airborne Laser Scanning

NASA Astrophysics Data System (ADS)

Xu, Q.; Hou, Z.; Maltamo, M.; Tokola, T.

2015-12-01

Diameter distributions of trees are important indicators of current forest stand structure and future dynamics. A new method was proposed in the study to combine the diameter distributions derived from the area-based approach (ABA) and the diameter distribution derived from the individual tree detection (ITD) in order to obtain more accurate forest stand attributes. Since dominant trees can be reliably detected and measured by the Lidar data via the ITD, the focus of the study is to retrieve the suppressed trees (trees that were missed by the ITD) from the ABA. Replacement and histogram matching were respectively employed at the plot level to retrieve the suppressed trees. Cut point was detected from the ITD-derived diameter distribution for each sample plot to distinguish dominant trees from the suppressed trees. The results showed that calibrated diameter distributions were more accurate in terms of error index and the entire growing stock estimates. Compared with the best performer between the ABA and the ITD, calibrated diameter distributions decreased the relative RMSE of the estimated entire growing stock, saw log and pulpwood fractions by 2.81%, 3.05% and 7.73% points respectively. Calibration improved the estimation of pulpwood fraction significantly, resulting in a negligible bias of the estimated entire growing stock.

Indigenous Community Tree Inventory: Assessment of Data Quality

NASA Astrophysics Data System (ADS)

Fauzi, M. F.; Idris, N. H.; Din, A. H. M.; Osman, M. J.; Idris, N. H.; Ishak, M. H. I.

2016-09-01

The citizen science program to supplement authoritative data in tree inventory has been well implemented in various countries. However, there is a lack of study that assesses correctness and accuracy of tree data supplied by citizens. This paper addresses the issue of tree data quality supplied by semi-literate indigenous group. The aim of this paper is to assess the correctness of attributes (tree species name, height and diameter at breast height) and the accuracy of tree horizontal positioning data supplied by indigenous people. The accuracy of the tree horizontal position recorded by GNSS-enable smart phone was found to have a RMSE value of ± 8m which is not suitable to accurately locate individual tree position in tropical rainforest such as the Royal Belum State Park. Consequently, the tree species names contributed by indigenous people were only 20 to 30 percent correct as compared with the reference data. However, the combination of indigenous respondents comprising of different ages, experience and knowledge working in a group influence less attribute error in data entry and increase the use of free text rather than audio methods. The indigenous community has a big potential to engage with scientific study due to their local knowledge with the research area, however intensive training must be given to empower their skills and several challenges need to be addressed.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

The Phylogeny of Rickettsia Using Different Evolutionary Signatures: How Tree-Like is Bacterial Evolution?

PubMed Central

Murray, Gemma G. R.; Weinert, Lucy A.; Rhule, Emma L.; Welch, John J.

2016-01-01

Rickettsia is a genus of intracellular bacteria whose hosts and transmission strategies are both impressively diverse, and this is reflected in a highly dynamic genome. Some previous studies have described the evolutionary history of Rickettsia as non-tree-like, due to incongruity between phylogenetic reconstructions using different portions of the genome. Here, we reconstruct the Rickettsia phylogeny using whole-genome data, including two new genomes from previously unsampled host groups. We find that a single topology, which is supported by multiple sources of phylogenetic signal, well describes the evolutionary history of the core genome. We do observe extensive incongruence between individual gene trees, but analyses of simulations over a single topology and interspersed partitions of sites show that this is more plausibly attributed to systematic error than to horizontal gene transfer. Some conflicting placements also result from phylogenetic analyses of accessory genome content (i.e., gene presence/absence), but we argue that these are also due to systematic error, stemming from convergent genome reduction, which cannot be accommodated by existing phylogenetic methods. Our results show that, even within a single genus, tests for gene exchange based on phylogenetic incongruence may be susceptible to false positives. PMID:26559010

The systematic component of phylogenetic error as a function of taxonomic sampling under parsimony.

PubMed

Debry, Ronald W

2005-06-01

The effect of taxonomic sampling on phylogenetic accuracy under parsimony is examined by simulating nucleotide sequence evolution. Random error is minimized by using very large numbers of simulated characters. This allows estimation of the consistency behavior of parsimony, even for trees with up to 100 taxa. Data were simulated on 8 distinct 100-taxon model trees and analyzed as stratified subsets containing either 25 or 50 taxa, in addition to the full 100-taxon data set. Overall accuracy decreased in a majority of cases when taxa were added. However, the magnitude of change in the cases in which accuracy increased was larger than the magnitude of change in the cases in which accuracy decreased, so, on average, overall accuracy increased as more taxa were included. A stratified sampling scheme was used to assess accuracy for an initial subsample of 25 taxa. The 25-taxon analyses were compared to 50- and 100-taxon analyses that were pruned to include only the original 25 taxa. On average, accuracy for the 25 taxa was improved by taxon addition, but there was considerable variation in the degree of improvement among the model trees and across different rates of substitution.

Tree crown mapping in managed woodlands (parklands) of semi-arid West Africa using WorldView-2 imagery and geographic object based image analysis.

PubMed

Karlson, Martin; Reese, Heather; Ostwald, Madelene

2014-11-28

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35-100 m(2)) and large (≥100 m(2)) trees compared to small (<35 m(2)) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas.

Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis

PubMed Central

Karlson, Martin; Reese, Heather; Ostwald, Madelene

2014-01-01

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35–100 m2) and large (≥100 m2) trees compared to small (<35 m2) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas. PMID:25460815

A scalable approach for tree segmentation within small-footprint airborne LiDAR data

NASA Astrophysics Data System (ADS)

Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun

2017-05-01

This paper presents a distributed approach that scales up to segment tree crowns within a LiDAR point cloud representing an arbitrarily large forested area. The approach uses a single-processor tree segmentation algorithm as a building block in order to process the data delivered in the shape of tiles in parallel. The distributed processing is performed in a master-slave manner, in which the master maintains the global map of the tiles and coordinates the slaves that segment tree crowns within and across the boundaries of the tiles. A minimal bias was introduced to the number of detected trees because of trees lying across the tile boundaries, which was quantified and adjusted for. Theoretical and experimental analyses of the runtime of the approach revealed a near linear speedup. The estimated number of trees categorized by crown class and the associated error margins as well as the height distribution of the detected trees aligned well with field estimations, verifying that the distributed approach works correctly. The approach enables providing information of individual tree locations and point cloud segments for a forest-level area in a timely manner, which can be used to create detailed remotely sensed forest inventories. Although the approach was presented for tree segmentation within LiDAR point clouds, the idea can also be generalized to scale up processing other big spatial datasets.

Assessing visual green effects of individual urban trees using airborne Lidar data.

PubMed

Chen, Ziyue; Xu, Bing; Gao, Bingbo

2015-12-01

Urban trees benefit people's daily life in terms of air quality, local climate, recreation and aesthetics. Among these functions, a growing number of studies have been conducted to understand the relationship between residents' preference towards local environments and visual green effects of urban greenery. However, except for on-site photography, there are few quantitative methods to calculate green visibility, especially tree green visibility, from viewers' perspectives. To fill this research gap, a case study was conducted in the city of Cambridge, which has a diversity of tree species, sizes and shapes. Firstly, a photograph-based survey was conducted to approximate the actual value of visual green effects of individual urban trees. In addition, small footprint airborne Lidar (Light detection and ranging) data was employed to measure the size and shape of individual trees. Next, correlations between visual tree green effects and tree structural parameters were examined. Through experiments and gradual refinement, a regression model with satisfactory R2 and limited large errors is proposed. Considering the diversity of sample trees and the result of cross-validation, this model has the potential to be applied to other study sites. This research provides urban planners and decision makers with an innovative method to analyse and evaluate landscape patterns in terms of tree greenness. Copyright © 2015 Elsevier B.V. All rights reserved.

Automated construction of arterial and venous trees in retinal images

PubMed Central

Hu, Qiao; Abràmoff, Michael D.; Garvin, Mona K.

2015-01-01

Abstract. While many approaches exist to segment retinal vessels in fundus photographs, only a limited number focus on the construction and disambiguation of arterial and venous trees. Previous approaches are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to large vessels. We propose a more global framework to generate arteriovenous trees in retinal images, given a vessel segmentation. In particular, our approach consists of three stages. The first stage is to generate an overconnected vessel network, named the vessel potential connectivity map (VPCM), consisting of vessel segments and the potential connectivity between them. The second stage is to disambiguate the VPCM into multiple anatomical trees, using a graph-based metaheuristic algorithm. The third stage is to classify these trees into arterial or venous (A/V) trees. We evaluated our approach with a ground truth built based on a public database, showing a pixel-wise classification accuracy of 88.15% using a manual vessel segmentation as input, and 86.11% using an automatic vessel segmentation as input. PMID:26636114

Modeling of Water Flow Processes in the Soil-Plant-Atmosphere System: The Soil-Tree-Atmosphere Continuum Model

NASA Astrophysics Data System (ADS)

Massoud, E. C.; Vrugt, J. A.

2015-12-01

Trees and forests play a key role in controlling the water and energy balance at the land-air surface. This study reports on the calibration of an integrated soil-tree-atmosphere continuum (STAC) model using Bayesian inference with the DREAM algorithm and temporal observations of soil moisture content, matric head, sap flux, and leaf water potential from the King's River Experimental Watershed (KREW) in the southern Sierra Nevada mountain range in California. Water flow through the coupled system is described using the Richards' equation with both the soil and tree modeled as a porous medium with nonlinear soil and tree water relationships. Most of the model parameters appear to be reasonably well defined by calibration against the observed data. The posterior mean simulation reproduces the observed soil and tree data quite accurately, but a systematic mismatch is observed between early afternoon measured and simulated sap fluxes. We will show how this points to a structural error in the STAC-model and suggest and test an alternative hypothesis for root water uptake that alleviates this problem.

Faults Discovery By Using Mined Data

NASA Technical Reports Server (NTRS)

Lee, Charles

2005-01-01

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis.

PubMed

Wallace, Meredith L; Anderson, Stewart J; Mazumdar, Sati

2010-12-20

Missing covariate data present a challenge to tree-structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree-based single imputation method presented by Conversano and Siciliano (Technical Report, University of Naples, 2003). Unlike previously proposed techniques for accommodating missing covariate data in tree-structured analyses, our methodology allows the modeling of complex and nonlinear covariate structures while still resulting in a single tree model. We perform a simulation study to evaluate our stochastic multiple imputation algorithm when covariate data are missing at random and compare it to other currently used methods. Our algorithm is advantageous for identifying the true underlying covariate structure when complex data and larger percentages of missing covariate observations are present. It is competitive with other current methods with respect to prediction accuracy. To illustrate our algorithm, we create a tree-structured survival model for predicting time to treatment response in older, depressed adults. Copyright © 2010 John Wiley & Sons, Ltd.

Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

NASA Astrophysics Data System (ADS)

Prasad, Ramendra; Deo, Ravinesh C.; Li, Yan; Maraseni, Tek

2017-11-01

Forecasting streamflow is vital for strategically planning, utilizing and redistributing water resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated with iterative input selection (IIS) algorithm (IIS-W-ANN) is evaluated for its statistical preciseness in forecasting monthly streamflow, and it is then benchmarked against M5 Tree model. To develop hybrid IIS-W-ANN model, a global predictor matrix is constructed for three local hydrological sites (Richmond, Gwydir, and Darling River) in Australia's agricultural (Murray-Darling) Basin. Model inputs comprised of statistically significant lagged combination of streamflow water level, are supplemented by meteorological data (i.e., precipitation, maximum and minimum temperature, mean solar radiation, vapor pressure and evaporation) as the potential model inputs. To establish robust forecasting models, iterative input selection (IIS) algorithm is applied to screen the best data from the predictor matrix and is integrated with the non-decimated maximum overlap discrete wavelet transform (MODWT) applied on the IIS-selected variables. This resolved the frequencies contained in predictor data while constructing a wavelet-hybrid (i.e., IIS-W-ANN and IIS-W-M5 Tree) model. Forecasting ability of IIS-W-ANN is evaluated via correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe Efficiency (ENS), root-mean-square-error (RMSE), and mean absolute error (MAE), including the percentage RMSE and MAE. While ANN models are seen to outperform M5 Tree executed for all hydrological sites, the IIS variable selector was efficient in determining the appropriate predictors, as stipulated by the better performance of the IIS coupled (ANN and M5 Tree) models relative to the models without IIS. When IIS-coupled models are integrated with MODWT, the wavelet-hybrid IIS-W-ANN and IIS-W-M5 Tree are seen to attain significantly accurate performance relative to their standalone counterparts. Importantly, IIS-W-ANN model accuracy outweighs IIS-ANN, as evidenced by a larger r and WI (by 7.5% and 3.8%, respectively) and a lower RMSE (by 21.3%). In comparison to the IIS-W-M5 Tree model, IIS-W-ANN model yielded larger values of WI = 0.936-0.979 and ENS = 0.770-0.920. Correspondingly, the errors (RMSE and MAE) ranged from 0.162-0.487 m and 0.139-0.390 m, respectively, with relative errors, RRMSE = (15.65-21.00) % and MAPE = (14.79-20.78) %. Distinct geographic signature is evident where the most and least accurately forecasted streamflow data is attained for the Gwydir and Darling River, respectively. Conclusively, this study advocates the efficacy of iterative input selection, allowing the proper screening of model predictors, and subsequently, its integration with MODWT resulting in enhanced performance of the models applied in streamflow forecasting.

A Structured Light Sensor System for Tree Inventory

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong; Zemek, Michael C.

2000-01-01

Tree Inventory is referred to measurement and estimation of marketable wood volume in a piece of land or forest for purposes such as investment or for loan applications. Exist techniques rely on trained surveyor conducting measurements manually using simple optical or mechanical devices, and hence are time consuming subjective and error prone. The advance of computer vision techniques makes it possible to conduct automatic measurements that are more efficient, objective and reliable. This paper describes 3D measurements of tree diameters using a uniquely designed ensemble of two line laser emitters rigidly mounted on a video camera. The proposed laser camera system relies on a fixed distance between two parallel laser planes and projections of laser lines to calculate tree diameters. Performance of the laser camera system is further enhanced by fusion of information induced from structured lighting and that contained in video images. Comparison will be made between the laser camera sensor system and a stereo vision system previously developed for measurements of tree diameters.

Uav-Based Photogrammetric Point Clouds and Hyperspectral Imaging for Mapping Biodiversity Indicators in Boreal Forests

NASA Astrophysics Data System (ADS)

Saarinen, N.; Vastaranta, M.; Näsi, R.; Rosnell, T.; Hakala, T.; Honkavaara, E.; Wulder, M. A.; Luoma, V.; Tommaselli, A. M. G.; Imai, N. N.; Ribeiro, E. A. W.; Guimarães, R. B.; Holopainen, M.; Hyyppä, J.

2017-10-01

Biodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level.

Carbon Sequestration Estimation of Street Trees Based on Point Cloud from Vehicle-Borne Laser Scanning System

NASA Astrophysics Data System (ADS)

Zhao, Y.; Hu, Q.

2017-09-01

Continuous development of urban road traffic system requests higher standards of road ecological environment. Ecological benefits of street trees are getting more attention. Carbon sequestration of street trees refers to the carbon stocks of street trees, which can be a measurement for ecological benefits of street trees. Estimating carbon sequestration in a traditional way is costly and inefficient. In order to solve above problems, a carbon sequestration estimation approach for street trees based on 3D point cloud from vehicle-borne laser scanning system is proposed in this paper. The method can measure the geometric parameters of a street tree, including tree height, crown width, diameter at breast height (DBH), by processing and analyzing point cloud data of an individual tree. Four Chinese scholartree trees and four camphor trees are selected for experiment. The root mean square error (RMSE) of tree height is 0.11m for Chinese scholartree and 0.02m for camphor. Crown widths in X direction and Y direction, as well as the average crown width are calculated. And the RMSE of average crown width is 0.22m for Chinese scholartree and 0.10m for camphor. The last calculated parameter is DBH, the RMSE of DBH is 0.5cm for both Chinese scholartree and camphor. Combining the measured geometric parameters and an appropriate carbon sequestration calculation model, the individual tree's carbon sequestration will be estimated. The proposed method can help enlarge application range of vehicle-borne laser point cloud data, improve the efficiency of estimating carbon sequestration, construct urban ecological environment and manage landscape.

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

PubMed

Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

2015-01-01

Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change

PubMed Central

Ashraf, M. Irfan; Meng, Fan-Rui; Bourque, Charles P.-A.; MacLean, David A.

2015-01-01

Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm2 5-year-1 and volume: 0.0008 m3 5-year-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm2 5-year-1 and 0.0393 m3 5-year-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling. PMID:26173081

Towards a Next-Generation Catalogue Cross-Match Service

NASA Astrophysics Data System (ADS)

Pineau, F.; Boch, T.; Derriere, S.; Arches Consortium

2015-09-01

We have been developing in the past several catalogue cross-match tools. On one hand the CDS XMatch service (Pineau et al. 2011), able to perform basic but very efficient cross-matches, scalable to the largest catalogues on a single regular server. On the other hand, as part of the European project ARCHES1, we have been developing a generic and flexible tool which performs potentially complex multi-catalogue cross-matches and which computes probabilities of association based on a novel statistical framework. Although the two approaches have been managed so far as different tracks, the need for next generation cross-match services dealing with both efficiency and complexity is becoming pressing with forthcoming projects which will produce huge high quality catalogues. We are addressing this challenge which is both theoretical and technical. In ARCHES we generalize to N catalogues the candidate selection criteria - based on the chi-square distribution - described in Pineau et al. (2011). We formulate and test a number of Bayesian hypothesis which necessarily increases dramatically with the number of catalogues. To assign a probability to each hypotheses, we rely on estimated priors which account for local densities of sources. We validated our developments by comparing the theoretical curves we derived with the results of Monte-Carlo simulations. The current prototype is able to take into account heterogeneous positional errors, object extension and proper motion. The technical complexity is managed by OO programming design patterns and SQL-like functionalities. Large tasks are split into smaller independent pieces for scalability. Performances are achieved resorting to multi-threading, sequential reads and several tree data-structures. In addition to kd-trees, we account for heterogeneous positional errors and object's extension using M-trees. Proper-motions are supported using a modified M-tree we developed, inspired from Time Parametrized R-trees (TPR-tree). Quantitative tests in comparison with the basic cross-match will be presented.

Assessment of imperfect detection of blister rust in whitebark pine within the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Wright, Wilson J.; Irvine, Kathryn M.

2017-01-01

We examined data on white pine blister rust (blister rust) collected during the monitoring of whitebark pine trees in the Greater Yellowstone Ecosystem (from 2004-2015). Summaries of repeat observations performed by multiple independent observers are reviewed and discussed. These summaries show variability among observers and the potential for errors being made in blister rust status. Based on this assessment, we utilized occupancy models to analyze blister rust prevalence while explicitly accounting for imperfect detection. Available covariates were used to model both the probability of a tree being infected with blister rust and the probability of an observer detecting the infection. The fitted model provided strong evidence that the probability of blister rust infection increases as tree diameter increases and decreases as site elevation increases. Most importantly, we found evidence of heterogeneity in detection probabilities related to tree size and average slope of a transect. These results suggested that detecting the presence of blister rust was more difficult in larger trees. Also, there was evidence that blister rust was easier to detect on transects located on steeper slopes. Our model accounted for potential impacts of observer experience on blister rust detection probabilities and also showed moderate variability among the different observers in their ability to detect blister rust. Based on these model results, we suggest that multiple observer sampling continue in future field seasons in order to allow blister rust prevalence estimates to be corrected for imperfect detection. We suggest that the multiple observer effort be spread out across many transects (instead of concentrated at a few each field season) while retaining the overall proportion of trees with multiple observers around 5-20%. Estimates of prevalence are confounded with detection unless it is explicitly accounted for in an analysis and we demonstrate how an occupancy model can be used to do account for this source of observation error.

Comparative analysis of techniques for evaluating the effectiveness of aircraft computing systems

NASA Technical Reports Server (NTRS)

Hitt, E. F.; Bridgman, M. S.; Robinson, A. C.

1981-01-01

Performability analysis is a technique developed for evaluating the effectiveness of fault-tolerant computing systems in multiphase missions. Performability was evaluated for its accuracy, practical usefulness, and relative cost. The evaluation was performed by applying performability and the fault tree method to a set of sample problems ranging from simple to moderately complex. The problems involved as many as five outcomes, two to five mission phases, permanent faults, and some functional dependencies. Transient faults and software errors were not considered. A different analyst was responsible for each technique. Significantly more time and effort were required to learn performability analysis than the fault tree method. Performability is inherently as accurate as fault tree analysis. For the sample problems, fault trees were more practical and less time consuming to apply, while performability required less ingenuity and was more checkable. Performability offers some advantages for evaluating very complex problems.

Computational efficiency of parallel combinatorial OR-tree searches

NASA Technical Reports Server (NTRS)

Li, Guo-Jie; Wah, Benjamin W.

1990-01-01

The performance of parallel combinatorial OR-tree searches is analytically evaluated. This performance depends on the complexity of the problem to be solved, the error allowance function, the dominance relation, and the search strategies. The exact performance may be difficult to predict due to the nondeterminism and anomalies of parallelism. The authors derive the performance bounds of parallel OR-tree searches with respect to the best-first, depth-first, and breadth-first strategies, and verify these bounds by simulation. They show that a near-linear speedup can be achieved with respect to a large number of processors for parallel OR-tree searches. Using the bounds developed, the authors derive sufficient conditions for assuring that parallelism will not degrade performance and necessary conditions for allowing parallelism to have a speedup greater than the ratio of the numbers of processors. These bounds and conditions provide the theoretical foundation for determining the number of processors required to assure a near-linear speedup.

ESTimating plant phylogeny: lessons from partitioning

PubMed Central

de la Torre, Jose EB; Egan, Mary G; Katari, Manpreet S; Brenner, Eric D; Stevenson, Dennis W; Coruzzi, Gloria M; DeSalle, Rob

2006-01-01

Background While Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies. Results A maximum parsimony (MP) analysis resulted in a single tree with relatively high support at all nodes in the tree despite rampant conflict among trees generated from the separate analysis of individual partitions. In a comparison of broader-scale groupings based on cellular compartment (ie: chloroplast, mitochondrial or nuclear) or function, only the nuclear partition tree (based largely on EST data) was found to be topologically identical to the tree based on the simultaneous analysis of all data. Despite topological conflict among the broader-scale groupings examined, only the tree based on morphological data showed statistically significant differences. Conclusion Based on the amount of character support contributed by EST data which make up a majority of the nuclear data set, and the lack of conflict of the nuclear data set with the simultaneous analysis tree, we conclude that the inclusion of EST data does provide a viable and efficient approach to address phylogenetic questions within a parsimony framework on a genomic scale, if problems of orthology determination and potential sequencing errors can be overcome. In addition, approaches that examine conflict and support in a simultaneous analysis framework allow for a more precise understanding of the evolutionary history of individual process partitions and may be a novel way to understand functional aspects of different kinds of cellular classes of gene products. PMID:16776834

Influence of tree size, taxonomy, and edaphic conditions on heart rot in mixed-dipterocarp Bornean rainforests: implications for aboveground biomass estimates

NASA Astrophysics Data System (ADS)

Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

2015-05-01

Fungal decay of heartwood creates hollows and areas of reduced wood density within the stems of living trees known as heart rot. Although heart rot is acknowledged as a source of error in forest aboveground biomass estimates, there are few datasets available to evaluate the environmental controls over heart rot infection and severity in tropical forests. Using legacy and recent data from drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of heart rot, and used generalized linear mixed effect models to characterize the association of heart rot with tree size, wood density, taxonomy, and edaphic conditions. Heart rot was detected in 55% of felled stems > 30 cm DBH, while the detection frequency was lower for stems of the same size evaluated by non-destructive drilling (45%) and coring (23%) methods. Heart rot severity, defined as the percent stem volume lost in infected stems, ranged widely from 0.1-82.8%. Tree taxonomy explained the greatest proportion of variance in heart rot frequency and severity among the fixed and random effects evaluated in our models. Heart rot frequency, but not severity, increased sharply with tree diameter, ranging from 56% infection across all datasets in stems > 50 cm DBH to 11% in trees 10-30 cm DBH. The frequency and severity of heart rot increased significantly in soils with low pH and cation concentrations in topsoil, and heart rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the percent of stem biomass lost to heart rot varied significantly with soil properties, and we estimate that 7% of the forest biomass is in some stage of heart rot decay. This study demonstrates not only that heart rot is a significant source of error in forest carbon estimates, but also that it strongly covaries with soil resources, underscoring the need to account for edaphic variation in estimating carbon storage in tropical forests.

Double Density Dual Tree Discrete Wavelet Transform implementation for Degraded Image Enhancement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

Wavelet transform is a main tool for image processing applications in modern existence. A Double Density Dual Tree Discrete Wavelet Transform is used and investigated for image denoising. Images are considered for the analysis and the performance is compared with discrete wavelet transform and the Double Density DWT. Peak Signal to Noise Ratio values and Root Means Square error are calculated in all the three wavelet techniques for denoised images and the performance has evaluated. The proposed techniques give the better performance when comparing other two wavelet techniques.

Genes with minimal phylogenetic information are problematic for coalescent analyses when gene tree estimation is biased.

PubMed

Xi, Zhenxiang; Liu, Liang; Davis, Charles C

2015-11-01

The development and application of coalescent methods are undergoing rapid changes. One little explored area that bears on the application of gene-tree-based coalescent methods to species tree estimation is gene informativeness. Here, we investigate the accuracy of these coalescent methods when genes have minimal phylogenetic information, including the implementation of the multilocus bootstrap approach. Using simulated DNA sequences, we demonstrate that genes with minimal phylogenetic information can produce unreliable gene trees (i.e., high error in gene tree estimation), which may in turn reduce the accuracy of species tree estimation using gene-tree-based coalescent methods. We demonstrate that this problem can be alleviated by sampling more genes, as is commonly done in large-scale phylogenomic analyses. This applies even when these genes are minimally informative. If gene tree estimation is biased, however, gene-tree-based coalescent analyses will produce inconsistent results, which cannot be remedied by increasing the number of genes. In this case, it is not the gene-tree-based coalescent methods that are flawed, but rather the input data (i.e., estimated gene trees). Along these lines, the commonly used program PhyML has a tendency to infer one particular bifurcating topology even though it is best represented as a polytomy. We additionally corroborate these findings by analyzing the 183-locus mammal data set assembled by McCormack et al. (2012) using ultra-conserved elements (UCEs) and flanking DNA. Lastly, we demonstrate that when employing the multilocus bootstrap approach on this 183-locus data set, there is no strong conflict between species trees estimated from concatenation and gene-tree-based coalescent analyses, as has been previously suggested by Gatesy and Springer (2014). Copyright © 2015 Elsevier Inc. All rights reserved.

Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees.

PubMed

Giraldo, Paula Jimena Ramos; Aguirre, Álvaro Guerrero; Muñoz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

2017-04-06

Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: ( i ) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and ( ii ) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.

Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees

PubMed Central

Ramos Giraldo, Paula Jimena; Guerrero Aguirre, Álvaro; Muñoz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

2017-01-01

Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases. PMID:28383494

iGLASS: An Improvement to the GLASS Method for Estimating Species Trees from Gene Trees

PubMed Central

Rosenberg, Noah A.

2012-01-01

Abstract Several methods have been designed to infer species trees from gene trees while taking into account gene tree/species tree discordance. Although some of these methods provide consistent species tree topology estimates under a standard model, most either do not estimate branch lengths or are computationally slow. An exception, the GLASS method of Mossel and Roch, is consistent for the species tree topology, estimates branch lengths, and is computationally fast. However, GLASS systematically overestimates divergence times, leading to biased estimates of species tree branch lengths. By assuming a multispecies coalescent model in which multiple lineages are sampled from each of two taxa at L independent loci, we derive the distribution of the waiting time until the first interspecific coalescence occurs between the two taxa, considering all loci and measuring from the divergence time. We then use the mean of this distribution to derive a correction to the GLASS estimator of pairwise divergence times. We show that our improved estimator, which we call iGLASS, consistently estimates the divergence time between a pair of taxa as the number of loci approaches infinity, and that it is an unbiased estimator of divergence times when one lineage is sampled per taxon. We also show that many commonly used clustering methods can be combined with the iGLASS estimator of pairwise divergence times to produce a consistent estimator of the species tree topology. Through simulations, we show that iGLASS can greatly reduce the bias and mean squared error in obtaining estimates of divergence times in a species tree. PMID:22216756

Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm

NASA Astrophysics Data System (ADS)

Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.

This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).

Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry

PubMed Central

Stein, Madeleine; Bargoti, Suchet; Underwood, James

2016-01-01

This paper presents a novel multi-sensor framework to efficiently identify, track, localise and map every piece of fruit in a commercial mango orchard. A multiple viewpoint approach is used to solve the problem of occlusion, thus avoiding the need for labour-intensive field calibration to estimate actual yield. Fruit are detected in images using a state-of-the-art faster R-CNN detector, and pair-wise correspondences are established between images using trajectory data provided by a navigation system. A novel LiDAR component automatically generates image masks for each canopy, allowing each fruit to be associated with the corresponding tree. The tracked fruit are triangulated to locate them in 3D, enabling a number of spatial statistics per tree, row or orchard block. A total of 522 trees and 71,609 mangoes were scanned on a Calypso mango orchard near Bundaberg, Queensland, Australia, with 16 trees counted by hand for validation, both on the tree and after harvest. The results show that single, dual and multi-view methods can all provide precise yield estimates, but only the proposed multi-view approach can do so without calibration, with an error rate of only 1.36% for individual trees. PMID:27854271

Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data.

PubMed

Kim, So-Ra; Kwak, Doo-Ahn; Lee, Woo-Kyun; oLee, Woo-Kyun; Son, Yowhan; Bae, Sang-Won; Kim, Choonsig; Yoo, Seongjin

2010-07-01

The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging (LiDAR) data. A digital canopy model (DCM), generated from the LiDAR data, was combined with aerial photography for segmenting crowns of individual trees. To eliminate errors in over and under-segmentation, the combined image was smoothed using a Gaussian filtering method. The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method. After measuring the crown area from the segmented individual trees, the individual tree diameter at breast height (DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area. The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute. The carbon storage, based on individual trees, was estimated by simple multiplication using the carbon conversion index (0.5), as suggested in guidelines from the Intergovernmental Panel on Climate Change. The mean carbon storage per individual tree was estimated and then compared with the field-measured value. This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.

Large tree diameter distribution modelling using sparse airborne laser scanning data in a subtropical forest in Nepal

NASA Astrophysics Data System (ADS)

Rana, Parvez; Vauhkonen, Jari; Junttila, Virpi; Hou, Zhengyang; Gautam, Basanta; Cawkwell, Fiona; Tokola, Timo

2017-12-01

Large-diameter trees (taking DBH > 30 cm to define large trees) dominate the dynamics, function and structure of a forest ecosystem. The aim here was to employ sparse airborne laser scanning (ALS) data with a mean point density of 0.8 m-2 and the non-parametric k-most similar neighbour (k-MSN) to predict tree diameter at breast height (DBH) distributions in a subtropical forest in southern Nepal. The specific objectives were: (1) to evaluate the accuracy of the large-tree fraction of the diameter distribution; and (2) to assess the effect of the number of training areas (sample size, n) on the accuracy of the predicted tree diameter distribution. Comparison of the predicted distributions with empirical ones indicated that the large tree diameter distribution can be derived in a mixed species forest with a RMSE% of 66% and a bias% of -1.33%. It was also feasible to downsize the sample size without losing the interpretability capacity of the model. For large-diameter trees, even a reduction of half of the training plots (n = 250), giving a marginal increase in the RMSE% (1.12-1.97%) was reported compared with the original training plots (n = 500). To be consistent with these outcomes, the sample areas should capture the entire range of spatial and feature variability in order to reduce the occurrence of error.

Abundance of large old trees in wood-pastures of Transylvania (Romania).

PubMed

Hartel, Tibor; Hanspach, Jan; Moga, Cosmin I; Holban, Lucian; Szapanyos, Árpád; Tamás, Réka; Hováth, Csaba; Réti, Kinga-Olga

2018-02-01

Wood-pastures are special types of agroforestry systems that integrate trees with livestock grazing. Wood pastures can be hotspots for large old tree abundance and have exceptional natural values; but they are declining all over Europe. While presence of large old trees in wood-pastures can provide arguments for their maintenance, actual data on their distribution and abundance are sparse. Our study is the first to survey large old trees in Eastern Europe over such a large area. We surveyed 97 wood-pastures in Transylvania (Romania) in order to (i) provide a descriptive overview of the large old tree abundance; and (ii) to explore the environmental determinants of the abundance and persistence of large old trees in wood-pastures. We identified 2520 large old trees belonging to 16 taxonomic groups. Oak was present in 66% of the wood-pastures, followed by beech (33%), hornbeam (24%) and pear (22%). For each of these four species we constructed a generalized linear model with quasi-Poisson error distribution to explain individual tree abundance. Oak trees were most abundant in large wood-pastures and in wood-pastures from the Saxon cultural region of Transylvania. Beech abundance related positively to elevation and to proximity of human settlements. Abundance of hornbeam was highest in large wood-pastures, in wood-pastures from the Saxon cultural region, and in places with high cover of adjacent forest and a low human population density. Large old pear trees were most abundant in large wood-pastures that were close to paved roads. The maintenance of large old trees in production landscapes is a challenge for science, policy and local people, but it also can serve as an impetus for integrating economic, ecological and social goals within a landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of Sediment Transport for Rivers in South Korea based on Data Mining technique

NASA Astrophysics Data System (ADS)

Jang, Eun-kyung; Ji, Un; Yeo, Woonkwang

2017-04-01

The purpose of this study is to calculate of sediment discharge assessment using data mining in South Korea. The Model Tree was selected for this study which is the most suitable technique to explicitly analyze the relationship between input and output variables in various and diverse databases among the Data Mining. In order to derive the sediment discharge equation using the Model Tree of Data Mining used the dimensionless variables used in Engelund and Hansen, Ackers and White, Brownlie and van Rijn equations as the analytical condition. In addition, total of 14 analytical conditions were set considering the conditions dimensional variables and the combination conditions of the dimensionless variables and the dimensional variables according to the relationship between the flow and the sediment transport. For each case, the analysis results were analyzed by mean of discrepancy ratio, root mean square error, mean absolute percent error, correlation coefficient. The results showed that the best fit was obtained by using five dimensional variables such as velocity, depth, slope, width and Median Diameter. And closest approximation to the best goodness-of-fit was estimated from the depth, slope, width, main grain size of bed material and dimensionless tractive force and except for the slope in the single variable. In addition, the three types of Model Tree that are most appropriate are compared with the Ackers and White equation which is the best fit among the existing equations, the mean discrepancy ration and the correlation coefficient of the Model Tree are improved compared to the Ackers and White equation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarrack, A.G.

The purpose of this report is to document fault tree analyses which have been completed for the Defense Waste Processing Facility (DWPF) safety analysis. Logic models for equipment failures and human error combinations that could lead to flammable gas explosions in various process tanks, or failure of critical support systems were developed for internal initiating events and for earthquakes. These fault trees provide frequency estimates for support systems failures and accidents that could lead to radioactive and hazardous chemical releases both on-site and off-site. Top event frequency results from these fault trees will be used in further APET analyses tomore » calculate accident risk associated with DWPF facility operations. This report lists and explains important underlying assumptions, provides references for failure data sources, and briefly describes the fault tree method used. Specific commitments from DWPF to provide new procedural/administrative controls or system design changes are listed in the ''Facility Commitments'' section. The purpose of the ''Assumptions'' section is to clarify the basis for fault tree modeling, and is not necessarily a list of items required to be protected by Technical Safety Requirements (TSRs).« less

Effects of plant phenology and vertical height on accuracy of radio-telemetry locations

USGS Publications Warehouse

Grovenburg, Troy W.; Jacques, Christopher N.; Klaver, Robert W.; DePerno, Christopher S.; Lehman, Chad P.; Brinkman, Todd J.; Robling, Kevin A.; Rupp, Susan P.; Jenks, Jonathan A.

2013-01-01

The use of very high frequency (VHF) radio-telemetry remains wide-spread in studies of wildlife ecology and management. However, few studies have evaluated the influence of vegetative obstruction on accuracy in differing habitats with varying transmitter types and heights. Using adult and fawn collars at varying heights above the ground (0, 33, 66 and 100 cm) to simulate activities (bedded, feeding and standing) and ages (neonate, juvenile and adult) of deer Odocoileus spp., we collected 5,767 bearings and estimated 1,424 locations (28-30 for each of 48 subsamples) in three habitat types (pasture, grassland and forest), during two stages of vegetative growth (spring and late summer). Bearing error was approximately twice as large at a distance of 900 m for fawn (9.9°) than for adult deer collars (4.9°). Of 12 models developed to explain the variation in location error, the analysis of covariance model (HT*D + C*D + HT*TBA + C*TBA) containing interactions of height of collar above ground (HT), collar type (C), vertical height of understory vegetation (D) and tree basal area (TBA) was the best model (wi = 0.92) and explained ∼ 71% of the variation in location error. Location error was greater for both collar types at 0 and 33 cm above the ground compared to 66 and 100 cm above the ground; however, location error was less for adult than fawn collars. Vegetation metrics influenced location error, which increased with greater vertical height of understory vegetation and tree basal area. Further, interaction of vegetation metrics and categorical variables indicated significant effects on location error. Our results indicate that researchers need to consider study objectives, life history of the study animal, signal strength of collar (collar type), distance from transmitter to receiver, topographical changes in elevation, habitat composition and season when designing telemetry protocols. Bearing distances in forested habitat should be decreased (approximately 23% in our study) compared to bearing distances in open habitat to maintain a consistent bearing error across habitats. Additionally, we believe that field biologists monitoring neonate ungulates for habitat selection should rely on visual locations rather than using VHF-collars and triangulation.

A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting

PubMed Central

Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao

2014-01-01

We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813

Quantifying the impact of daily and seasonal variation in sap pH on xylem dissolved inorganic carbon estimates in plum trees.

PubMed

Erda, F G; Bloemen, J; Steppe, K

2014-01-01

In studies on internal CO2 transport, average xylem sap pH (pH(x)) is one of the factors used for calculation of the concentration of dissolved inorganic carbon in the xylem sap ([CO2 *]). Lack of detailed pH(x) measurements at high temporal resolution could be a potential source of error when evaluating [CO2*] dynamics. In this experiment, we performed continuous measurements of CO2 concentration ([CO2]) and stem temperature (T(stem)), complemented with pH(x) measurements at 30-min intervals during the day at various stages of the growing season (Day of the Year (DOY): 86 (late winter), 128 (mid-spring) and 155 (early summer)) on a plum tree (Prunus domestica L. cv. Reine Claude d'Oullins). We used the recorded pH(x) to calculate [CO2*] based on T(stem) and the corresponding measured [CO2]. No statistically significant difference was found between mean [CO2*] calculated with instantaneous pH(x) and daily average pH(x). However, using an average pH(x) value from a different part of the growing season than the measurements of [CO2] and T(stem) to estimate [CO2*] led to a statistically significant error. The error varied between 3.25 ± 0.01% under-estimation and 3.97 ± 0.01% over-estimation, relative to the true [CO2*] data. Measured pH(x) did not show a significant daily variation, unlike [CO2], which increased during the day and declined at night. As the growing season progressed, daily average [CO2] (3.4%, 5.3%, 7.4%) increased and average pH(x) (5.43, 5.29, 5.20) decreased. Increase in [CO2] will increase its solubility in xylem sap according to Henry's law, and the dissociation of [CO2*] will negatively affect pH(x). Our results are the first quantifying the error in [CO2*] due to the interaction between [CO2] and pH(x) on a seasonal time scale. We found significant changes in pH(x) across the growing season, but overall the effect on the calculation of [CO2*] remained within an error range of 4%. However, it is possible that the error could be more substantial for other tree species, particularly if pH(x) is in the more sensitive range (pH(x) > 6.5). © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

The Early Detection of the Emerald Ash Borer (EAB) Using Advanced Geospacial Technologies

NASA Astrophysics Data System (ADS)

Hu, B.; Li, J.; Wang, J.; Hall, B.

2014-11-01

The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, individual trees were first extracted and then classified into different species based on their spectral information derived from hyperspectral imagery, spatial information from VHR imagery, and for each ash tree its health state and EAB infestation stage were determined based on hyperspectral imagery. The developed framework and methods were demonstrated to be effective according to the results obtained on two study sites in the city of Toronto, Ontario Canada. The individual tree delineation method provided satisfactory results with an overall accuracy of 78 % and 19 % commission and 23 % omission errors when used on the combined very high-spatial resolution imagery and LiDAR data. In terms of the identification of ash trees, given sufficient representative training data, our classification model was able to predict tree species with above 75 % overall accuracy, and mis-classification occurred mainly between ash and maple trees. The hypothesis that a strong correlation exists between general tree stress and EAB infestation was confirmed. Vegetation indices sensitive to leaf chlorophyll content derived from hyperspectral imagery can be used to predict the EAB infestation levels for each ash tree.

A lognormal distribution of the lengths of terminal twigs on self-similar branches of elm trees.

PubMed

Koyama, Kohei; Yamamoto, Ken; Ushio, Masayuki

2017-01-11

Lognormal distributions and self-similarity are characteristics associated with a wide range of biological systems. The sequential breakage model has established a link between lognormal distributions and self-similarity and has been used to explain species abundance distributions. To date, however, there has been no similar evidence in studies of multicellular organismal forms. We tested the hypotheses that the distribution of the lengths of terminal stems of Japanese elm trees (Ulmus davidiana), the end products of a self-similar branching process, approaches a lognormal distribution. We measured the length of the stem segments of three elm branches and obtained the following results: (i) each occurrence of branching caused variations or errors in the lengths of the child stems relative to their parent stems; (ii) the branches showed statistical self-similarity; the observed error distributions were similar at all scales within each branch and (iii) the multiplicative effect of these errors generated variations of the lengths of terminal twigs that were well approximated by a lognormal distribution, although some statistically significant deviations from strict lognormality were observed for one branch. Our results provide the first empirical evidence that statistical self-similarity of an organismal form generates a lognormal distribution of organ sizes. © 2017 The Author(s).

The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis

PubMed Central

2011-01-01

Background CADM is a statistical test used to estimate the level of Congruence Among Distance Matrices. It has been shown in previous studies to have a correct rate of type I error and good power when applied to dissimilarity matrices and to ultrametric distance matrices. Contrary to most other tests of incongruence used in phylogenetic analysis, the null hypothesis of the CADM test assumes complete incongruence of the phylogenetic trees instead of congruence. In this study, we performed computer simulations to assess the type I error rate and power of the test. It was applied to additive distance matrices representing phylogenies and to genetic distance matrices obtained from nucleotide sequences of different lengths that were simulated on randomly generated trees of varying sizes, and under different evolutionary conditions. Results Our results showed that the test has an accurate type I error rate and good power. As expected, power increased with the number of objects (i.e., taxa), the number of partially or completely congruent matrices and the level of congruence among distance matrices. Conclusions Based on our results, we suggest that CADM is an excellent candidate to test for congruence and, when present, to estimate its level in phylogenomic studies where numerous genes are analysed simultaneously. PMID:21388552

The origin and diversification of eukaryotes: problems with molecular phylogenetics and molecular clock estimation

PubMed Central

Roger, Andrew J; Hug, Laura A

2006-01-01

Determining the relationships among and divergence times for the major eukaryotic lineages remains one of the most important and controversial outstanding problems in evolutionary biology. The sequencing and phylogenetic analyses of ribosomal RNA (rRNA) genes led to the first nearly comprehensive phylogenies of eukaryotes in the late 1980s, and supported a view where cellular complexity was acquired during the divergence of extant unicellular eukaryote lineages. More recently, however, refinements in analytical methods coupled with the availability of many additional genes for phylogenetic analysis showed that much of the deep structure of early rRNA trees was artefactual. Recent phylogenetic analyses of a multiple genes and the discovery of important molecular and ultrastructural phylogenetic characters have resolved eukaryotic diversity into six major hypothetical groups. Yet relationships among these groups remain poorly understood because of saturation of sequence changes on the billion-year time-scale, possible rapid radiations of major lineages, phylogenetic artefacts and endosymbiotic or lateral gene transfer among eukaryotes. Estimating the divergence dates between the major eukaryote lineages using molecular analyses is even more difficult than phylogenetic estimation. Error in such analyses comes from a myriad of sources including: (i) calibration fossil dates, (ii) the assumed phylogenetic tree, (iii) the nucleotide or amino acid substitution model, (iv) substitution number (branch length) estimates, (v) the model of how rates of evolution change over the tree, (vi) error inherent in the time estimates for a given model and (vii) how multiple gene data are treated. By reanalysing datasets from recently published molecular clock studies, we show that when errors from these various sources are properly accounted for, the confidence intervals on inferred dates can be very large. Furthermore, estimated dates of divergence vary hugely depending on the methods used and their assumptions. Accurate dating of divergence times among the major eukaryote lineages will require a robust tree of eukaryotes, a much richer Proterozoic fossil record of microbial eukaryotes assignable to extant groups for calibration, more sophisticated relaxed molecular clock methods and many more genes sampled from the full diversity of microbial eukaryotes. PMID:16754613

How Prediction Errors Shape Perception, Attention, and Motivation

PubMed Central

den Ouden, Hanneke E. M.; Kok, Peter; de Lange, Floris P.

2012-01-01

Prediction errors (PE) are a central notion in theoretical models of reinforcement learning, perceptual inference, decision-making and cognition, and prediction error signals have been reported across a wide range of brain regions and experimental paradigms. Here, we will make an attempt to see the forest for the trees and consider the commonalities and differences of reported PE signals in light of recent suggestions that the computation of PE forms a fundamental mode of brain function. We discuss where different types of PE are encoded, how they are generated, and the different functional roles they fulfill. We suggest that while encoding of PE is a common computation across brain regions, the content and function of these error signals can be very different and are determined by the afferent and efferent connections within the neural circuitry in which they arise. PMID:23248610

Evolution of proteins.

NASA Technical Reports Server (NTRS)

Dayhoff, M. O.

1971-01-01

The amino acid sequences of proteins from living organisms are dealt with. The structure of proteins is first discussed; the variation in this structure from one biological group to another is illustrated by the first halves of the sequences of cytochrome c, and a phylogenetic tree is derived from the cytochrome c data. The relative geological times associated with the events of this tree are discussed. Errors which occur in the duplication of cells during the evolutionary process are examined. Particular attention is given to evolution of mutant proteins, globins, ferredoxin, and transfer ribonucleic acids (tRNA's). Finally, a general outline of biological evolution is presented.

Hierarchical Poly Tree Configurations for the Solution of Dynamically Refined Finte Element Models

NASA Technical Reports Server (NTRS)

Gute, G. D.; Padovan, J.

1993-01-01

This paper demonstrates how a multilevel substructuring technique, called the Hierarchical Poly Tree (HPT), can be used to integrate a localized mesh refinement into the original finite element model more efficiently. The optimal HPT configurations for solving isoparametrically square h-, p-, and hp-extensions on single and multiprocessor computers is derived. In addition, the reduced number of stiffness matrix elements that must be stored when employing this type of solution strategy is quantified. Moreover, the HPT inherently provides localize 'error-trapping' and a logical, efficient means with which to isolate physically anomalous and analytically singular behavior.

Wood Specific Gravity Variations and Biomass of Central African Tree Species: The Simple Choice of the Outer Wood

PubMed Central

Bastin, Jean-François; Fayolle, Adeline; Tarelkin, Yegor; Van den Bulcke, Jan; de Haulleville, Thales; Mortier, Frederic; Beeckman, Hans; Van Acker, Joris; Serckx, Adeline; Bogaert, Jan; De Cannière, Charles

2015-01-01

Context Wood specific gravity is a key element in tropical forest ecology. It integrates many aspects of tree mechanical properties and functioning and is an important predictor of tree biomass. Wood specific gravity varies widely among and within species and also within individual trees. Notably, contrasted patterns of radial variation of wood specific gravity have been demonstrated and related to regeneration guilds (light demanding vs. shade-bearing). However, although being repeatedly invoked as a potential source of error when estimating the biomass of trees, both intraspecific and radial variations remain little studied. In this study we characterized detailed pith-to-bark wood specific gravity profiles among contrasted species prominently contributing to the biomass of the forest, i.e., the dominant species, and we quantified the consequences of such variations on the biomass. Methods Radial profiles of wood density at 8% moisture content were compiled for 14 dominant species in the Democratic Republic of Congo, adapting a unique 3D X-ray scanning technique at very high spatial resolution on core samples. Mean wood density estimates were validated by water displacement measurements. Wood density profiles were converted to wood specific gravity and linear mixed models were used to decompose the radial variance. Potential errors in biomass estimation were assessed by comparing the biomass estimated from the wood specific gravity measured from pith-to-bark profiles, from global repositories, and from partial information (outer wood or inner wood). Results Wood specific gravity profiles from pith-to-bark presented positive, neutral and negative trends. Positive trends mainly characterized light-demanding species, increasing up to 1.8 g.cm-3 per meter for Piptadeniastrum africanum, and negative trends characterized shade-bearing species, decreasing up to 1 g.cm-3 per meter for Strombosia pustulata. The linear mixed model showed the greater part of wood specific gravity variance was explained by species only (45%) followed by a redundant part between species and regeneration guilds (36%). Despite substantial variation in wood specific gravity profiles among species and regeneration guilds, we found that values from the outer wood were strongly correlated to values from the whole profile, without any significant bias. In addition, we found that wood specific gravity from the DRYAD global repository may strongly differ depending on the species (up to 40% for Dialium pachyphyllum). Main Conclusion Therefore, when estimating forest biomass in specific sites, we recommend the systematic collection of outer wood samples on dominant species. This should prevent the main errors in biomass estimations resulting from wood specific gravity and allow for the collection of new information to explore the intraspecific variation of mechanical properties of trees. PMID:26555144

Wood Specific Gravity Variations and Biomass of Central African Tree Species: The Simple Choice of the Outer Wood.

PubMed

Bastin, Jean-François; Fayolle, Adeline; Tarelkin, Yegor; Van den Bulcke, Jan; de Haulleville, Thales; Mortier, Frederic; Beeckman, Hans; Van Acker, Joris; Serckx, Adeline; Bogaert, Jan; De Cannière, Charles

2015-01-01

Wood specific gravity is a key element in tropical forest ecology. It integrates many aspects of tree mechanical properties and functioning and is an important predictor of tree biomass. Wood specific gravity varies widely among and within species and also within individual trees. Notably, contrasted patterns of radial variation of wood specific gravity have been demonstrated and related to regeneration guilds (light demanding vs. shade-bearing). However, although being repeatedly invoked as a potential source of error when estimating the biomass of trees, both intraspecific and radial variations remain little studied. In this study we characterized detailed pith-to-bark wood specific gravity profiles among contrasted species prominently contributing to the biomass of the forest, i.e., the dominant species, and we quantified the consequences of such variations on the biomass. Radial profiles of wood density at 8% moisture content were compiled for 14 dominant species in the Democratic Republic of Congo, adapting a unique 3D X-ray scanning technique at very high spatial resolution on core samples. Mean wood density estimates were validated by water displacement measurements. Wood density profiles were converted to wood specific gravity and linear mixed models were used to decompose the radial variance. Potential errors in biomass estimation were assessed by comparing the biomass estimated from the wood specific gravity measured from pith-to-bark profiles, from global repositories, and from partial information (outer wood or inner wood). Wood specific gravity profiles from pith-to-bark presented positive, neutral and negative trends. Positive trends mainly characterized light-demanding species, increasing up to 1.8 g.cm-3 per meter for Piptadeniastrum africanum, and negative trends characterized shade-bearing species, decreasing up to 1 g.cm-3 per meter for Strombosia pustulata. The linear mixed model showed the greater part of wood specific gravity variance was explained by species only (45%) followed by a redundant part between species and regeneration guilds (36%). Despite substantial variation in wood specific gravity profiles among species and regeneration guilds, we found that values from the outer wood were strongly correlated to values from the whole profile, without any significant bias. In addition, we found that wood specific gravity from the DRYAD global repository may strongly differ depending on the species (up to 40% for Dialium pachyphyllum). Therefore, when estimating forest biomass in specific sites, we recommend the systematic collection of outer wood samples on dominant species. This should prevent the main errors in biomass estimations resulting from wood specific gravity and allow for the collection of new information to explore the intraspecific variation of mechanical properties of trees.

Development and validation of techniques for improving software dependability

NASA Technical Reports Server (NTRS)

Knight, John C.

1992-01-01

A collection of document abstracts are presented on the topic of improving software dependability through NASA grant NAG-1-1123. Specific topics include: modeling of error detection; software inspection; test cases; Magnetic Stereotaxis System safety specifications and fault trees; and injection of synthetic faults into software.

Dendritic tree extraction from noisy maximum intensity projection images in C. elegans.

PubMed

Greenblum, Ayala; Sznitman, Raphael; Fua, Pascal; Arratia, Paulo E; Oren, Meital; Podbilewicz, Benjamin; Sznitman, Josué

2014-06-12

Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting dendritic trees from noisy images remains however a strenuous process that has traditionally relied on manual approaches. Here, we focus on automated and reliable 2D segmentations of dendritic trees following a statistical learning framework. Our dendritic tree extraction (DTE) method uses small amounts of labelled training data on MIPs to learn noise models of texture-based features from the responses of tree structures and image background. Our strategy lies in evaluating statistical models of noise that account for both the variability generated from the imaging process and from the aggregation of information in the MIP images. These noisy models are then used within a probabilistic, or Bayesian framework to provide a coarse 2D dendritic tree segmentation. Finally, some post-processing is applied to refine the segmentations and provide skeletonized trees using a morphological thinning process. Following a Leave-One-Out Cross Validation (LOOCV) method for an MIP databse with available "ground truth" images, we demonstrate that our approach provides significant improvements in tree-structure segmentations over traditional intensity-based methods. Improvements for MIPs under various imaging conditions are both qualitative and quantitative, as measured from Receiver Operator Characteristic (ROC) curves and the yield and error rates in the final segmentations. In a final step, we demonstrate our DTE approach on previously unseen MIP samples including the extraction of skeletonized structures, and compare our method to a state-of-the art dendritic tree tracing software. Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity-based methods. Such approach provides a useable segmentation framework, ultimately delivering a speed-up for dendritic tree identification on the user end and a reliable first step towards further morphological characterizations of tree arborization.

Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

PubMed

Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

2015-07-01

Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved the performance of the generic equation only for stem biomass and had no apparent effect on aboveground, branch, leaf, and root biomass at the site level. The development of a generic allometric equation taking account of interspecific differences is an effective approach for accurately estimating aboveground and component biomass in boreal, temperate, and subtropical natural forests.

Quantifying Proxy Influence in the Last Millennium Reanalysis

NASA Astrophysics Data System (ADS)

Hakim, G. J.; Anderson, D. N.; Emile-Geay, J.; Noone, D.; Tardif, R.

2017-12-01

We examine the influence of proxies in the climate field reconstruction known as the Last Millennium Reanalysis (Hakim et al. 2016; JGR-A). This data assimilation framework uses the CCSM4 Last Millennium simulation as an agnostic prior, proxies from the PAGES 2k Consortium (2017; Sci. Data), and an offline ensemble square-root filter for assimilation. Proxies are forward modeled using an observation model ("proxy system model") that maps from the prior space to the proxy space. We assess proxy impact using the method of Cardinali et al. (2004; QJRMS), where influence is measured in observation space; that is, at the location of observations. Influence is determined by three components: the prior at the location, the proxy at the location, and remote proxies as mediated by the spatial covariance information in the prior. Consequently, on a per-proxy basis, influence is higher for spatially isolated proxies having small error, and influence is lower for spatially dense proxies having large error. Results show that proxy influence depends strongly on the observation model. Assuming the proxies depend linearly on annual mean temperature yields the largest per-proxy influence for coral d18O and coral Sr/Ca records, and smallest influence for tree-ring width. On a global basis (summing over all proxies of a given type), tree-ring width and coral d18O have the largest influence. A seasonal model for the proxies yields very different results. In this case we model the proxies linearly on objectively determined seasonal temperature, except for tree proxies, which are fit to a bivariate model on seasonal temperature and precipitation. In this experiment, on a per-proxy basis, tree-ring density has by far the greatest influence. Total proxy influence is dominated by tree-ring width followed by tree-ring density. Compared to the results for the annual-mean observation model, the experiment where proxies are measured seasonally has more than double the total influence (sum over all proxies); this experiment also has higher verification scores when measured against other 20th century temperature reconstructions. These results underscore the importance of improving proxy system models, since they increase the amount of information available for data-assimilation-based reconstructions.

Influence of Wind Speed on RGB-D Images in Tree Plantations

PubMed Central

Andújar, Dionisio; Dorado, José; Bengochea-Guevara, José María; Conesa-Muñoz, Jesús; Fernández-Quintanilla, César; Ribeiro, Ángela

2017-01-01

Weather conditions can affect sensors’ readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and other related uses. However, the use of these devices is still challenged by prevailing field conditions. Although the influence of lighting conditions on the performance of these cameras has already been established, the effect of wind is still unknown. This study establishes the associated errors when modeling some tree characteristics at different wind speeds. A system using a Kinect v2 sensor and a custom software was tested from null wind speed up to 10 m·s−1. Two tree species with contrasting architecture, poplars and plums, were used as model plants. The results showed different responses depending on tree species and wind speed. Estimations of Leaf Area (LA) and tree volume were generally more consistent at high wind speeds in plum trees. Poplars were particularly affected by wind speeds higher than 5 m·s−1. On the contrary, height measurements were more consistent for poplars than for plum trees. These results show that the use of depth cameras for tree characterization must take into consideration wind conditions in the field. In general, 5 m·s−1 (18 km·h−1) could be established as a conservative limit for good estimations. PMID:28430119

Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning

NASA Astrophysics Data System (ADS)

Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.

2017-12-01

Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: < -0.4 C, -0.4 C ≤ residual ≤ 0.4 C, and > 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the < -0.4 C and -0.4 C ≤ residual ≤ 0.4 C categories. Spatial homogeneity in BTs consistently appears as a very important variable for classification, suggesting that unidentified cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree classifier are enhanced using this knowledge.

Using phylogenomics to understand the link between biogeographic origins and regional diversification in ratsnakes.

PubMed

Chen, Xin; Lemmon, Alan R; Lemmon, Emily Moriarty; Pyron, R Alexander; Burbrink, Frank T

2017-06-01

Globally distributed groups may show regionally distinct rates of diversification, where speciation is elevated given timing and sources of ecological opportunity. However, for most organisms, nearly complete sampling at genomic-data scales to reduce topological error in all regions is unattainable, thus hampering conclusions related to biogeographic origins and rates of diversification. We explore processes leading to the diversity of global ratsnakes and test several important hypotheses related to areas of origin and enhanced diversification upon colonizing new continents. We estimate species trees inferred from phylogenomic scale data (304 loci) while exploring several strategies that consider topological error from each individual gene tree. With a dated species tree, we examine taxonomy and test previous hypotheses that suggest the ratsnakes originated in the Old World (OW) and dispersed to New World (NW). Furthermore, we determine if dispersal to the NW represented a source of ecological opportunity, which should show elevated rates of species diversification. We show that ratsnakes originated in the OW during the mid-Oligocene and subsequently dispersed to the NW by the mid-Miocene; diversification was also elevated in a subclade of NW taxa. Finally, the optimal biogeographic region-dependent speciation model shows that the uptick in ratsnake diversification was associated with colonization of the NW. We consider several alternative explanations that account for regionally distinct diversification rates. Copyright © 2017 Elsevier Inc. All rights reserved.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

2017-01-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

PubMed

Liu, Feng; Tan, Chang; Lei, Pi-Feng

2014-11-01

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.

PubMed

Khalkhali, Hamid Reza; Lotfnezhad Afshar, Hadi; Esnaashari, Omid; Jabbari, Nasrollah

2016-01-01

Breast cancer survival has been analyzed by many standard data mining algorithms. A group of these algorithms belonged to the decision tree category. Ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied already. The classification and regression trees (CART) was applied to a breast cancer database contained information on 569 patients in 2007-2010. The measurement of Gini impurity used for categorical target variables was utilized. The classification error that is a function of tree size was measured by 10-fold cross-validation experiments. The performance of created model was evaluated by the criteria as accuracy, sensitivity and specificity. The CART model produced a decision tree with 17 nodes, 9 of which were associated with a set of rules. The rules were meaningful clinically. They showed in the if-then format that Stage was the most important variable for predicting breast cancer survival. The scores of accuracy, sensitivity and specificity were: 80.3%, 93.5% and 53%, respectively. The current study model as the first one created by the CART was able to extract useful hidden rules from a relatively small size dataset.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

2017-12-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Welsh Bilinguals' English Spelling: An Error Analysis.

ERIC Educational Resources Information Center

James, Carl; And Others

1993-01-01

The extent to which the second-language English spelling of young Welsh-English bilinguals is systematically idiosyncratic was examined from free compositions written by 10- to 11-year-old children. A model is presented of the second-language spelling process in the form of a "decision tree." (Contains 29 references.) (Author/LB)

Digging Deeper into Helmont's Famous Willow Tree Experiment.

ERIC Educational Resources Information Center

Hershey, David R.

1991-01-01

Author provides details about Helmont's experiment that was a milestone in the history of plant biology since it marked the start of experimental plant physiology. Concludes that Jean Baptista van Helmont's supposedly simple experiment becomes complex when trying to determine the methods he used, evaluate his sources of experimental error, and…

Accuracy of band dendrometers

Treesearch

L. R. Auchmoody

1976-01-01

A study to determine the reliability of first-year growth measurements obtained from aluminum band dendrometers showed that growth was underestimated for black cherry trees growing less than 0.5 inch in diameter or accumulating less than 0.080 square foot of basal area. Prediction equations to correct for these errors are given.

Infrared thermometry for deficit irrigation of peach trees

USDA-ARS?s Scientific Manuscript database

Water shortage has been a major concern for crop production in the western states of the USA and other arid regions in the world. Deficit irrigation can be used in some cropping systems as a potential water saving strategy to alleviate water shortage, however, the margin of error in irrigation manag...

[Evaluation of Sugar Content of Huanghua Pear on Trees by Visible/Near Infrared Spectroscopy].

PubMed

Liu, Hui-jun; Ying, Yi-bin

2015-11-01

A method of ambient light correction was proposed to evaluate the sugar content of Huanghua pears on tree by visible/near infrared diffuse reflectance spectroscopy (Vis/NIRS). Due to strong interference of ambient light, it was difficult to collect the efficient spectral of pears on tree. In the field, covering the fruits with a bag blocking ambient light can get better results, but the efficiency is fairly low, the instrument corrections of dark and reference spectra may help to reduce the error of the model, however, the interference of the ambient light cannot be eliminated effectively. In order to reduce the effect of ambient light, a shutter was attached to the front of probe. When opening shutter, the spot spectrum were obtained, on which instrument light and ambient light acted at the same time. While closing shutter, background spectra were obtained, on which only ambient light acted, then the ambient light spectra was subtracted from spot spectra. Prediction models were built using data on tree (before and after ambient light correction) and after harvesting by partial least square (PLS). The results of the correlation coefficient (R) are 0.1, 0.69, 0.924; the root mean square error of prediction (SEP) are 0. 89°Brix, 0.42°Brix, 0.27°Brix; ratio of standard deviation (SD) to SEP (RPD) are 0.79, 1.69, 2.58, respectively. The results indicate that, method of background correction used in the experiment can reduce the effect of ambient lighting on spectral acquisition of Huanghua pears in field, efficiently. This method can be used to collect the visible/near infrared spectrum of fruits in field, and may give full play to visible/near-infrared spectroscopy in preharvest management and maturity testing of fruits in the field.

Accounting for Uncertainty in Gene Tree Estimation: Summary-Coalescent Species Tree Inference in a Challenging Radiation of Australian Lizards.

PubMed

Blom, Mozes P K; Bragg, Jason G; Potter, Sally; Moritz, Craig

2017-05-01

Accurate gene tree inference is an important aspect of species tree estimation in a summary-coalescent framework. Yet, in empirical studies, inferred gene trees differ in accuracy due to stochastic variation in phylogenetic signal between targeted loci. Empiricists should, therefore, examine the consistency of species tree inference, while accounting for the observed heterogeneity in gene tree resolution of phylogenomic data sets. Here, we assess the impact of gene tree estimation error on summary-coalescent species tree inference by screening ${\\sim}2000$ exonic loci based on gene tree resolution prior to phylogenetic inference. We focus on a phylogenetically challenging radiation of Australian lizards (genus Cryptoblepharus, Scincidae) and explore effects on topology and support. We identify a well-supported topology based on all loci and find that a relatively small number of high-resolution gene trees can be sufficient to converge on the same topology. Adding gene trees with decreasing resolution produced a generally consistent topology, and increased confidence for specific bipartitions that were poorly supported when using a small number of informative loci. This corroborates coalescent-based simulation studies that have highlighted the need for a large number of loci to confidently resolve challenging relationships and refutes the notion that low-resolution gene trees introduce phylogenetic noise. Further, our study also highlights the value of quantifying changes in nodal support across locus subsets of increasing size (but decreasing gene tree resolution). Such detailed analyses can reveal anomalous fluctuations in support at some nodes, suggesting the possibility of model violation. By characterizing the heterogeneity in phylogenetic signal among loci, we can account for uncertainty in gene tree estimation and assess its effect on the consistency of the species tree estimate. We suggest that the evaluation of gene tree resolution should be incorporated in the analysis of empirical phylogenomic data sets. This will ultimately increase our confidence in species tree estimation using summary-coalescent methods and enable us to exploit genomic data for phylogenetic inference. [Coalescence; concatenation; Cryptoblepharus; exon capture; gene tree; phylogenomics; species tree.]. © The authors 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Instruction-matrix-based genetic programming.

PubMed

Li, Gang; Wang, Jin Feng; Lee, Kin Hong; Leung, Kwong-Sak

2008-08-01

In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In this paper, we propose a new GP framework, namely, instruction-matrix (IM)-based GP (IMGP), to handle their interactions. IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from an IM and updates the IM with the information of the extracted program trees. As the IM actually keeps most of the information of the schemata of GP and evolves the schemata directly, IMGP is effective and efficient. Our experimental results on benchmark problems have verified that IMGP is not only better than those of canonical GP in terms of the qualities of the solutions and the number of program evaluations, but they are also better than some of the related GP algorithms. IMGP can also be used to evolve programs for classification problems. The classifiers obtained have higher classification accuracies than four other GP classification algorithms on four benchmark classification problems. The testing errors are also comparable to or better than those obtained with well-known classifiers. Furthermore, an extended version, called condition matrix for rule learning, has been used successfully to handle multiclass classification problems.

A one-dimensional model of flow in a junction of thin channels, including arterial trees

NASA Astrophysics Data System (ADS)

Kozlov, V. A.; Nazarov, S. A.

2017-08-01

We study a Stokes flow in a junction of thin channels (of diameter O(h)) for fixed flows of the fluid at the inlet cross-sections and fixed peripheral pressure at the outlet cross-sections. On the basis of the idea of the pressure drop matrix, apart from Neumann conditions (fixed flow) and Dirichlet conditions (fixed pressure) at the outer vertices, the ordinary one-dimensional Reynolds equations on the edges of the graph are equipped with transmission conditions containing a small parameter h at the inner vertices, which are transformed into the classical Kirchhoff conditions as h\\to+0. We establish that the pre-limit transmission conditions ensure an exponentially small error O(e-ρ/h), ρ>0, in the calculation of the three-dimensional solution, but the Kirchhoff conditions only give polynomially small error. For the arterial tree, under the assumption that the walls of the blood vessels are rigid, for every bifurcation node a ( 2×2)-pressure drop matrix appears, and its influence on the transmission conditions is taken into account by means of small variations of the lengths of the graph and by introducing effective lengths of the one-dimensional description of blood vessels whilst keeping the Kirchhoff conditions and exponentially small approximation errors. We discuss concrete forms of arterial bifurcation and available generalizations of the results, in particular, the Navier-Stokes system of equations. Bibliography: 59 titles.

Joint Denoising/Compression of Image Contours via Shape Prior and Context Tree

NASA Astrophysics Data System (ADS)

Zheng, Amin; Cheung, Gene; Florencio, Dinei

2018-07-01

With the advent of depth sensing technologies, the extraction of object contours in images---a common and important pre-processing step for later higher-level computer vision tasks like object detection and human action recognition---has become easier. However, acquisition noise in captured depth images means that detected contours suffer from unavoidable errors. In this paper, we propose to jointly denoise and compress detected contours in an image for bandwidth-constrained transmission to a client, who can then carry out aforementioned application-specific tasks using the decoded contours as input. We first prove theoretically that in general a joint denoising / compression approach can outperform a separate two-stage approach that first denoises then encodes contours lossily. Adopting a joint approach, we first propose a burst error model that models typical errors encountered in an observed string y of directional edges. We then formulate a rate-constrained maximum a posteriori (MAP) problem that trades off the posterior probability p(x'|y) of an estimated string x' given y with its code rate R(x'). We design a dynamic programming (DP) algorithm that solves the posed problem optimally, and propose a compact context representation called total suffix tree (TST) that can reduce complexity of the algorithm dramatically. Experimental results show that our joint denoising / compression scheme outperformed a competing separate scheme in rate-distortion performance noticeably.

Conversion from Tree to Graph Representation of Requirements

NASA Technical Reports Server (NTRS)

Mayank, Vimal; Everett, David Frank; Shmunis, Natalya; Austin, Mark

2009-01-01

A procedure and software to implement the procedure have been devised to enable conversion from a tree representation to a graph representation of the requirements governing the development and design of an engineering system. The need for this procedure and software and for other requirements-management tools arises as follows: In systems-engineering circles, it is well known that requirements- management capability improves the likelihood of success in the team-based development of complex systems involving multiple technological disciplines. It is especially desirable to be able to visualize (in order to identify and manage) requirements early in the system- design process, when errors can be corrected most easily and inexpensively.

A hierarchical structure for automatic meshing and adaptive FEM analysis

NASA Technical Reports Server (NTRS)

Kela, Ajay; Saxena, Mukul; Perucchio, Renato

1987-01-01

A new algorithm for generating automatically, from solid models of mechanical parts, finite element meshes that are organized as spatially addressable quaternary trees (for 2-D work) or octal trees (for 3-D work) is discussed. Because such meshes are inherently hierarchical as well as spatially addressable, they permit efficient substructuring techniques to be used for both global analysis and incremental remeshing and reanalysis. The global and incremental techniques are summarized and some results from an experimental closed loop 2-D system in which meshing, analysis, error evaluation, and remeshing and reanalysis are done automatically and adaptively are presented. The implementation of 3-D work is briefly discussed.

Predicting Error Bars for QSAR Models

NASA Astrophysics Data System (ADS)

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches.

Aspen, climate, and sudden decline in western USA

Treesearch

Gerald E. Rehfeldt; Dennis E. Ferguson; Nicholas L. Crookston

2009-01-01

A bioclimate model predicting the presence or absence of aspen, Populus tremuloides, in western USA from climate variables was developed by using the Random Forests classification tree on Forest Inventory data from about 118,000 permanent sample plots. A reasonably parsimonious model used eight predictors to describe aspen's climate profile. Classification errors...

Adjusting STEMS growth model for Wisconsin forests.

Treesearch

Margaret R. Holdaway

1985-01-01

Describes a simple procedure for adjusting growth in the STEMS regional tree growth model to compensate for subregional differences. Coefficients are reported to adjust Lake States STEMS to the forests of Northern and Central Wisconsin--an area of essentially uniform climate and similar broad physiographic features. Errors are presented for various combinations of...

Post-Modeling Histogram Matching of Maps Produced Using Regression Trees

Treesearch

Andrew J. Lister; Tonya W. Lister

2006-01-01

Spatial predictive models often use statistical techniques that in some way rely on averaging of values. Estimates from linear modeling are known to be susceptible to truncation of variance when the independent (predictor) variables are measured with error. A straightforward post-processing technique (histogram matching) for attempting to mitigate this effect is...

Tetrazolium chloride as an indicator of pine pollen germinability

Treesearch

Stanton A. Cook; Robert G. Stanley

1960-01-01

Controlled pollination in forest tree breeding requires pollen of known germination capacity. Methods of determining pollen viability include germination in a hanging drop, in a moist atmosphere, on agar gel, or in a sugar solution (DUFFIELD, 1954; DILLON et al., 1957). Errors commonly arise in the application of these techniques because maximum...

Testing for Independence between Evolutionary Processes.

PubMed

Behdenna, Abdelkader; Pothier, Joël; Abby, Sophie S; Lambert, Amaury; Achaz, Guillaume

2016-09-01

Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Monitoring small pioneer trees in the forest-tundra ecotone: using multi-temporal airborne laser scanning data to model height growth.

PubMed

Hauglin, Marius; Bollandsås, Ole Martin; Gobakken, Terje; Næsset, Erik

2017-12-08

Monitoring of forest resources through national forest inventory programmes is carried out in many countries. The expected climate changes will affect trees and forests and might cause an expansion of trees into presently treeless areas, such as above the current alpine tree line. It is therefore a need to develop methods that enable the inclusion of also these areas into monitoring programmes. Airborne laser scanning (ALS) is an established tool in operational forest inventories, and could be a viable option for monitoring tasks. In the present study, we used multi-temporal ALS data with point density of 8-15 points per m 2 , together with field measurements from single trees in the forest-tundra ecotone along a 1500-km-long transect in Norway. The material comprised 262 small trees with an average height of 1.78 m. The field-measured height growth was derived from height measurements at two points in time. The elapsed time between the two measurements was 4 years. Regression models were then used to model the relationship between ALS-derived variables and tree heights as well as the height growth. Strong relationships between ALS-derived variables and tree heights were found, with R 2 values of 0.93 and 0.97 for the two points in time. The relationship between the ALS data and the field-derived height growth was weaker, with R 2 values of 0.36-0.42. A cross-validation gave corresponding results, with root mean square errors of 19 and 11% for the ALS height models and 60% for the model relating ALS data to single-tree height growth.

Individual variation of sap-flow rate in large pine and spruce trees and stand transpiration: a pilot study at the central NOPEX site

NASA Astrophysics Data System (ADS)

Čermák, J.; Cienciala, E.; Kučera, J.; Lindroth, A.; Bednářová, E.

1995-06-01

Transpiration in a mixed old stand of sub-boreal forest in the Norunda region (central Sweden) was estimated on the basis of direct measurement of sap flow rate in 24 large Scots pine and Norway spruce trees in July and August 1993. Sap flow rate was measured using the trunk tissue heat balance method based on internal (electric) heating and sensing of temperature. Transpiration was only 0.7 mm day -1 in a relatively dry period in July (i.e. about 20% of potential evaporation) and substantially higher after a rainy period in August. The error of the estimates of transpiration was higher during a dry period (about 13% and 22% in pine and spruce, respectively) and significantly lower (about 9% in both species) during a period of sufficient water supply. Shallow-rooted spruce trees responded much faster to precipitation than deeply rooted pines.

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil

PubMed Central

Nunes, Matheus Henrique

2016-01-01

Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects. PMID:27187074

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

PubMed

Nunes, Matheus Henrique; Görgens, Eric Bastos

2016-01-01

Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects.

Tree mortality from fires, bark beetles, and timber harvest during a hot and dry decade in the western United States (2003-2012)

NASA Astrophysics Data System (ADS)

Berner, Logan T.; Law, Beverly E.; Meddens, Arjan J. H.; Hicke, Jeffrey A.

2017-06-01

High temperatures and severe drought contributed to extensive tree mortality from fires and bark beetles during the 2000s in parts of the western continental United States. Several states in this region have greenhouse gas (GHG) emission targets and would benefit from information on the amount of carbon stored in tree biomass killed by disturbance. We quantified mean annual tree mortality from fires, bark beetles, and timber harvest from 2003-2012 for each state in this region. We estimated tree mortality from fires and beetles using tree aboveground carbon (AGC) stock and disturbance data sets derived largely from remote sensing. We quantified tree mortality from harvest using data from US Forest Service reports. In both cases, we used Monte Carlo analyses to track uncertainty associated with parameter error and temporal variability. Regional tree mortality from harvest, beetles, and fires (MORTH+B+F) together averaged 45.8 ± 16.0 Tg AGC yr-1 (±95% confidence interval), indicating a mortality rate of 1.10 ± 0.38% yr-1. Harvest accounted for the largest percentage of MORTH+B+F (˜50%), followed by beetles (˜32%), and fires (˜18%). Tree mortality from harvest was concentrated in Washington and Oregon, where harvest accounted for ˜80% of MORTH+B+F in each state. Tree mortality from beetles occurred widely at low levels across the region, yet beetles had pronounced impacts in Colorado and Montana, where they accounted for ˜80% of MORTH+B+F. Tree mortality from fires was highest in California, though fires accounted for the largest percentage of MORTH+B+F in Arizona and New Mexico (˜50%). Drought and human activities shaped regional variation in tree mortality, highlighting opportunities and challenges to managing GHG emissions from forests. Rising temperatures and greater risk of drought will likely increase tree mortality from fires and bark beetles during coming decades in this region. Thus, sustained monitoring and mapping of tree mortality is necessary to inform forest and GHG management.

A soil map of a large watershed in China: applying digital soil mapping in a data sparse region

NASA Astrophysics Data System (ADS)

Barthold, F.; Blank, B.; Wiesmeier, M.; Breuer, L.; Frede, H.-G.

2009-04-01

Prediction of soil classes in data sparse regions is a major research challenge. With the advent of machine learning the possibilities to spatially predict soil classes have increased tremendously and given birth to new possibilities in soil mapping. Digital soil mapping is a research field that has been established during the last decades and has been accepted widely. We now need to develop tools to reduce the uncertainty in soil predictions. This is especially challenging in data sparse regions. One approach to do this is to implement soil taxonomic distance as a classification error criterion in classification and regression trees (CART) as suggested by Minasny et al. (Geoderma 142 (2007) 285-293). This approach assumes that the classification error should be larger between soils that are more dissimilar, i.e. differ in a larger number of soil properties, and smaller between more similar soils. Our study area is the Xilin River Basin, which is located in central Inner Mongolia in China. It is characterized by semi arid climate conditions and is representative for the natural occurring steppe ecosystem. The study area comprises 3600 km2. We applied a random, stratified sampling design after McKenzie and Ryan (Geoderma 89 (1999) 67-94) with landuse and topography as stratifying variables. We defined 10 sampling classes, from each class 14 replicates were randomly drawn and sampled. The dataset was split into 100 soil profiles for training and 40 soil profiles for validation. We then applied classification and regression trees (CART) to quantify the relationships between soil classes and environmental covariates. The classification tree explained 75.5% of the variance with land use and geology as most important predictor variables. Among the 8 soil classes that we predicted, the Kastanozems cover most of the area. They are predominantly found in steppe areas. However, even some of the soils at sand dune sites, which were thought to show only little soil formation, can be classified as Kastanozems. Besides the Kastanozems, Regosols are most common at the sand dune sites as well as at sites that are defined as bare soil which are characterized by little or no vegetation. Gleysols are mostly found at sites in the vicinity of the Xilin river, which are connected to the groundwater. They can also be found in small valleys or depressions where sub-surface waters from neighboring areas collect. The richest soils are found in mountain meadow areas. Pedogenetic conditions here are most favorable and lead to the formation of Chernozems with deep humic Ah horizons. Other soil types that occur in the study area are Arenosols, Calcisols, Cambisol and Phaeozems. In addition, soil taxonomic distance is implemented into the decision tree procedure as a measure of classification error. The results of incorporating taxonomic distance as a loss function in the decision tree will be compared with the standard application of the decision tree.

Short communication: Prediction of retention pay-off using a machine learning algorithm.

PubMed

Shahinfar, Saleh; Kalantari, Afshin S; Cabrera, Victor; Weigel, Kent

2014-05-01

Replacement decisions have a major effect on dairy farm profitability. Dynamic programming (DP) has been widely studied to find the optimal replacement policies in dairy cattle. However, DP models are computationally intensive and might not be practical for daily decision making. Hence, the ability of applying machine learning on a prerun DP model to provide fast and accurate predictions of nonlinear and intercorrelated variables makes it an ideal methodology. Milk class (1 to 5), lactation number (1 to 9), month in milk (1 to 20), and month of pregnancy (0 to 9) were used to describe all cows in a herd in a DP model. Twenty-seven scenarios based on all combinations of 3 levels (base, 20% above, and 20% below) of milk production, milk price, and replacement cost were solved with the DP model, resulting in a data set of 122,716 records, each with a calculated retention pay-off (RPO). Then, a machine learning model tree algorithm was used to mimic the evaluated RPO with DP. The correlation coefficient factor was used to observe the concordance of RPO evaluated by DP and RPO predicted by the model tree. The obtained correlation coefficient was 0.991, with a corresponding value of 0.11 for relative absolute error. At least 100 instances were required per model constraint, resulting in 204 total equations (models). When these models were used for binary classification of positive and negative RPO, error rates were 1% false negatives and 9% false positives. Applying this trained model from simulated data for prediction of RPO for 102 actual replacement records from the University of Wisconsin-Madison dairy herd resulted in a 0.994 correlation with 0.10 relative absolute error rate. Overall results showed that model tree has a potential to be used in conjunction with DP to assist farmers in their replacement decisions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessing stand water use in four coastal wetland forests using sapflow techniques: annual estimates, errors and associated uncertainties

USGS Publications Warehouse

Krauss, Ken W.; Duberstein, Jamie A.; Conner, William H.

2015-01-01

Forests comprise approximately 37% of the terrestrial land surface and influence global water cycling. However, very little attention has been directed towards understanding environmental impacts on stand water use (S) or in identifying rates of S from specific forested wetlands. Here, we use sapflow techniques to address two separate but linked objectives: (1) determine S in four, hydrologically distinctive South Carolina (USA) wetland forests from 2009–2010 and (2) describe potential error, uncertainty and stand-level variation associated with these assessments. Sapflow measurements were made from a number of tree species for approximately 2–8 months over 2 years to initiate the model, which was applied to canopy trees (DBH > 10–20 cm). We determined that S in three healthy forested wetlands varied from 1.97–3.97 mm day−1 or 355–687 mm year−1 when scaled. In contrast, saltwater intrusion impacted individual tree physiology and size class distributions on a fourth site, which decreased S to 0.61–1.13 mm day−1 or 110–196 mm year−1. The primary sources of error in estimations using sapflow probes would relate to calibration of probes and standardization relative to no flow periods and accounting for accurate sapflow attenuation with radial depth into the sapwood by species and site. Such inherent variation in water use among wetland forest stands makes small differences in S (<200 mm year−1) difficult to detect statistically through modelling, even though small differences may be important to local water cycling. These data also represent some of the first assessments of S from temperate, coastal forested wetlands along the Atlantic coast of the USA.

Real-time monitoring and fault locating using amplified spontaneous emission noise reflection for tree-structured Ethernet passive optical networks

NASA Astrophysics Data System (ADS)

Naim, Nani Fadzlina; Ab-Rahman, Mohammad Syuhaimi; Kamaruddin, Nur Hasiba; Bakar, Ahmad Ashrif A.

2013-09-01

Nowadays, optical networks are becoming dense while detecting faulty branches in the tree-structured networks has become problematic. Conventional methods are inconvenient as they require an engineer to visit the failure site to check the optical fiber using an optical time-domain reflectometer. An innovative monitoring technique for tree-structured network topology in Ethernet passive optical networks (EPONs) by using the erbium-doped fiber amplifier to amplify the traffic signal is demonstrated, and in the meantime, a residual amplified spontaneous emission spectrum is used as the input signal to monitor the optical cable from the central office. Fiber Bragg gratings with distinct center wavelengths are employed to reflect the monitoring signals. Faulty branches of the tree-structured EPONs can be identified using a simple and low-cost receiver. We will show that this technique is capable of providing monitoring range up to 32 optical network units using a power meter with a sensitivity of -65 dBm while maintaining the bit error rate of 10-13.

Seeing Central African forests through their largest trees

PubMed Central

Bastin, J.-F.; Barbier, N.; Réjou-Méchain, M.; Fayolle, A.; Gourlet-Fleury, S.; Maniatis, D.; de Haulleville, T.; Baya, F.; Beeckman, H.; Beina, D.; Couteron, P.; Chuyong, G.; Dauby, G.; Doucet, J.-L.; Droissart, V.; Dufrêne, M.; Ewango, C.; Gillet, J.F.; Gonmadje, C.H.; Hart, T.; Kavali, T.; Kenfack, D.; Libalah, M.; Malhi, Y.; Makana, J.-R.; Pélissier, R.; Ploton, P.; Serckx, A.; Sonké, B.; Stevart, T.; Thomas, D.W.; De Cannière, C.; Bogaert, J.

2015-01-01

Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies. PMID:26279193

Seeing Central African forests through their largest trees.

PubMed

Bastin, J-F; Barbier, N; Réjou-Méchain, M; Fayolle, A; Gourlet-Fleury, S; Maniatis, D; de Haulleville, T; Baya, F; Beeckman, H; Beina, D; Couteron, P; Chuyong, G; Dauby, G; Doucet, J-L; Droissart, V; Dufrêne, M; Ewango, C; Gillet, J F; Gonmadje, C H; Hart, T; Kavali, T; Kenfack, D; Libalah, M; Malhi, Y; Makana, J-R; Pélissier, R; Ploton, P; Serckx, A; Sonké, B; Stevart, T; Thomas, D W; De Cannière, C; Bogaert, J

2015-08-17

Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

PubMed

Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

2018-06-15

Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical tree model of hematopoesis

NASA Astrophysics Data System (ADS)

Krappe, Sebastian; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

2016-03-01

The morphological differentiation of bone marrow is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually under the use of bright field microscopy. This is a time-consuming, subjective, tedious and error-prone process. Furthermore, repeated examinations of a slide may yield intra- and inter-observer variances. For that reason a computer assisted diagnosis system for bone marrow differentiation is pursued. In this work we focus (a) on a new method for the separation of nucleus and plasma parts and (b) on a knowledge-based hierarchical tree classifier for the differentiation of bone marrow cells in 16 different classes. Classification trees are easily interpretable and understandable and provide a classification together with an explanation. Using classification trees, expert knowledge (i.e. knowledge about similar classes and cell lines in the tree model of hematopoiesis) is integrated in the structure of the tree. The proposed segmentation method is evaluated with more than 10,000 manually segmented cells. For the evaluation of the proposed hierarchical classifier more than 140,000 automatically segmented bone marrow cells are used. Future automated solutions for the morphological analysis of bone marrow smears could potentially apply such an approach for the pre-classification of bone marrow cells and thereby shortening the examination time.

Imaging phased telescope array study

NASA Technical Reports Server (NTRS)

Harvey, James E.

1989-01-01

The problems encountered in obtaining a wide field-of-view with large, space-based direct imaging phased telescope arrays were considered. After defining some of the critical systems issues, previous relevant work in the literature was reviewed and summarized. An extensive list was made of potential error sources and the error sources were categorized in the form of an error budget tree including optical design errors, optical fabrication errors, assembly and alignment errors, and environmental errors. After choosing a top level image quality requirment as a goal, a preliminary tops-down error budget allocation was performed; then, based upon engineering experience, detailed analysis, or data from the literature, a bottoms-up error budget reallocation was performed in an attempt to achieve an equitable distribution of difficulty in satisfying the various allocations. This exercise provided a realistic allocation for residual off-axis optical design errors in the presence of state-of-the-art optical fabrication and alignment errors. Three different computational techniques were developed for computing the image degradation of phased telescope arrays due to aberrations of the individual telescopes. Parametric studies and sensitivity analyses were then performed for a variety of subaperture configurations and telescope design parameters in an attempt to determine how the off-axis performance of a phased telescope array varies as the telescopes are scaled up in size. The Air Force Weapons Laboratory (AFWL) multipurpose telescope testbed (MMTT) configuration was analyzed in detail with regard to image degradation due to field curvature and distortion of the individual telescopes as they are scaled up in size.

Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Kisi, Ozgur; Singh, Vijay P.

2017-02-01

Drought forecasting using standardized metrics of rainfall is a core task in hydrology and water resources management. Standardized Precipitation Index (SPI) is a rainfall-based metric that caters for different time-scales at which the drought occurs, and due to its standardization, is well-suited for forecasting drought at different periods in climatically diverse regions. This study advances drought modelling using multivariate adaptive regression splines (MARS), least square support vector machine (LSSVM), and M5Tree models by forecasting SPI in eastern Australia. MARS model incorporated rainfall as mandatory predictor with month (periodicity), Southern Oscillation Index, Pacific Decadal Oscillation Index and Indian Ocean Dipole, ENSO Modoki and Nino 3.0, 3.4 and 4.0 data added gradually. The performance was evaluated with root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (r2). Best MARS model required different input combinations, where rainfall, sea surface temperature and periodicity were used for all stations, but ENSO Modoki and Pacific Decadal Oscillation indices were not required for Bathurst, Collarenebri and Yamba, and the Southern Oscillation Index was not required for Collarenebri. Inclusion of periodicity increased the r2 value by 0.5-8.1% and reduced RMSE by 3.0-178.5%. Comparisons showed that MARS superseded the performance of the other counterparts for three out of five stations with lower MAE by 15.0-73.9% and 7.3-42.2%, respectively. For the other stations, M5Tree was better than MARS/LSSVM with lower MAE by 13.8-13.4% and 25.7-52.2%, respectively, and for Bathurst, LSSVM yielded more accurate result. For droughts identified by SPI ≤ - 0.5, accurate forecasts were attained by MARS/M5Tree for Bathurst, Yamba and Peak Hill, whereas for Collarenebri and Barraba, M5Tree was better than LSSVM/MARS. Seasonal analysis revealed disparate results where MARS/M5Tree was better than LSSVM. The results highlight the importance of periodicity in drought forecasting and also ascertains that model accuracy scales with geographic/seasonal factors due to complexity of drought and its relationship with inputs and data attributes that can affect the evolution of drought events.

Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data.

PubMed

Luo, Laiping; Zhai, Qiuping; Su, Yanjun; Ma, Qin; Kelly, Maggi; Guo, Qinghua

2018-05-14

Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurate and automatic estimation of CBH for individual trees is still a challenging task. Airborne light detection and ranging (LiDAR) provides reliable and promising data for estimating CBH. Various methods have been developed to calculate CBH indirectly using regression-based means from airborne LiDAR data and field measurements. However, little attention has been paid to directly calculate CBH at the individual tree scale in mixed-species forests without field measurements. In this study, we propose a new method for directly estimating individual-tree CBH from airborne LiDAR data. Our method involves two main strategies: 1) removing noise and understory vegetation for each tree; and 2) estimating CBH by generating percentile ranking profile for each tree and using a spline curve to identify its inflection points. These two strategies lend our method the advantages of no requirement of field measurements and being efficient and effective in mixed-species forests. The proposed method was applied to a mixed conifer forest in the Sierra Nevada, California and was validated by field measurements. The results showed that our method can directly estimate CBH at individual tree level with a root-mean-squared error of 1.62 m, a coefficient of determination of 0.88 and a relative bias of 3.36%. Furthermore, we systematically analyzed the accuracies among different height groups and tree species by comparing with field measurements. Our results implied that taller trees had relatively higher uncertainties than shorter trees. Our findings also show that the accuracy for CBH estimation was the highest for black oak trees, with an RMSE of 0.52 m. The conifer species results were also good with uniformly high R 2 ranging from 0.82 to 0.93. In general, our method has demonstrated high accuracy for individual tree CBH estimation and strong potential for applications in mixed species over large areas.

Vertical variations in wood CO2 efflux for live emergent trees in a Bornean tropical rainforest.

PubMed

Katayama, Ayumi; Kume, Tomonori; Komatsu, Hikaru; Ohashi, Mizue; Matsumoto, Kazuho; Ichihashi, Ryuji; Kumagai, Tomo'omi; Otsuki, Kyoichi

2014-05-01

Difficult access to 40-m-tall emergent trees in tropical rainforests has resulted in a lack of data related to vertical variations in wood CO2 efflux, even though significant variations in wood CO2 efflux are an important source of errors when estimating whole-tree total wood CO2 efflux. This study aimed to clarify vertical variations in wood CO2 efflux for emergent trees and to document the impact of the variations on the whole-tree estimates of stem and branch CO2 efflux. First, we measured wood CO2 efflux and factors related to tree morphology and environment for seven live emergent trees of two dipterocarp species at four to seven heights of up to ∼ 40 m for each tree using ladders and a crane. No systematic tendencies in vertical variations were observed for all the trees. Wood CO2 efflux was not affected by stem and air temperature, stem diameter, stem height or stem growth. The ratios of wood CO2 efflux at the treetop to that at breast height were larger in emergent trees with relatively smaller diameters at breast height. Second, we compared whole-tree stem CO2 efflux estimates using vertical measurements with those based on solely breast height measurements. We found similar whole-tree stem CO2 efflux estimates regardless of the patterns of vertical variations in CO2 efflux because the surface area in the canopy, where wood CO2 efflux often differed from that at breast height, was very small compared with that at low stem heights, resulting in little effect of the vertical variations on the estimate. Additionally, whole-tree branch CO2 efflux estimates using measured wood CO2 efflux in the canopy were considerably different from those measured using only breast height measurements. Uncertainties in wood CO2 efflux in the canopy did not cause any bias in stem CO2 efflux scaling, but affected branch CO2 efflux. © The Author 2014. Published by Oxford University Press. All rights reserved.

A cognitive model for multidigit number reading: Inferences from individuals with selective impairments.

PubMed

Dotan, Dror; Friedmann, Naama

2018-04-01

We propose a detailed cognitive model of multi-digit number reading. The model postulates separate processes for visual analysis of the digit string and for oral production of the verbal number. Within visual analysis, separate sub-processes encode the digit identities and the digit order, and additional sub-processes encode the number's decimal structure: its length, the positions of 0, and the way it is parsed into triplets (e.g., 314987 → 314,987). Verbal production consists of a process that generates the verbal structure of the number, and another process that retrieves the phonological forms of each number word. The verbal number structure is first encoded in a tree-like structure, similarly to syntactic trees of sentences, and then linearized to a sequence of number-word specifiers. This model is based on an investigation of the number processing abilities of seven individuals with different selective deficits in number reading. We report participants with impairment in specific sub-processes of the visual analysis of digit strings - in encoding the digit order, in encoding the number length, or in parsing the digit string to triplets. Other participants were impaired in verbal production, making errors in the number structure (shifts of digits to another decimal position, e.g., 3,040 → 30,004). Their selective deficits yielded several dissociations: first, we found a double dissociation between visual analysis deficits and verbal production deficits. Second, several dissociations were found within visual analysis: a double dissociation between errors in digit order and errors in the number length; a dissociation between order/length errors and errors in parsing the digit string into triplets; and a dissociation between the processing of different digits - impaired order encoding of the digits 2-9, without errors in the 0 position. Third, within verbal production, a dissociation was found between digit shifts and substitutions of number words. A selective deficit in any of the processes described by the model would cause difficulties in number reading, which we propose to term "dysnumeria". Copyright © 2017 Elsevier Ltd. All rights reserved.

Profile models for estimating log end diameters in the Rocky Mountain Region

Treesearch

Raymond L. Czaplewski; Amy S. Brown; Raymond C. Walker

1989-01-01

The segmented polynomial stem profile model of Max and Burkhart was applied to seven tree species in the Rocky Mountain Region of the Forest Service. Errors were reduced over the entire data set by use of second-stage models that adjust for transformation bias and explained weak patterns in the residual diameter predictions.

New features added to EVALIDator: ratio estimation and county choropleth maps

Treesearch

Patrick D. Miles; Mark H. Hansen

2012-01-01

The EVALIDator Web application, developed in 2007, provides estimates and sampling errors for many user selected forest statistics from the Forest Inventory and Analysis Database (FIADB). Among the statistics estimated are forest area, number of trees, biomass, volume, growth, removals, and mortality. A new release of EVALIDator, developed in 2012, has an option to...

A whole stand basal area projection model for Appalachian hardwoods

Treesearch

John R. Brooks; Lichun Jiang; Matthew Perkowski; Benktesh Sharma

2008-01-01

Two whole-stand basal area projection models were developed for Appalachian hardwood stands. The proposed equations are an algebraic difference projection form based on existing basal area and the change in age, trees per acre, and/or dominant height. Average equation error was less than 10 square feet per acre and residuals exhibited no irregular trends.

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Improving the prediction of going concern of Taiwanese listed companies using a hybrid of LASSO with data mining techniques.

PubMed

Goo, Yeung-Ja James; Chi, Der-Jang; Shen, Zong-De

2016-01-01

The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO-NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO-CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO-SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).

Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

PubMed

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.

Multi-scale clustering by building a robust and self correcting ultrametric topology on data points.

PubMed

Fushing, Hsieh; Wang, Hui; Vanderwaal, Kimberly; McCowan, Brenda; Koehl, Patrice

2013-01-01

The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets.

Impact of an antiretroviral stewardship strategy on medication error rates.

PubMed

Shea, Katherine M; Hobbs, Athena Lv; Shumake, Jason D; Templet, Derek J; Padilla-Tolentino, Eimeira; Mondy, Kristin E

2018-05-02

The impact of an antiretroviral stewardship strategy on medication error rates was evaluated. This single-center, retrospective, comparative cohort study included patients at least 18 years of age infected with human immunodeficiency virus (HIV) who were receiving antiretrovirals and admitted to the hospital. A multicomponent approach was developed and implemented and included modifications to the order-entry and verification system, pharmacist education, and a pharmacist-led antiretroviral therapy checklist. Pharmacists performed prospective audits using the checklist at the time of order verification. To assess the impact of the intervention, a retrospective review was performed before and after implementation to assess antiretroviral errors. Totals of 208 and 24 errors were identified before and after the intervention, respectively, resulting in a significant reduction in the overall error rate ( p < 0.001). In the postintervention group, significantly lower medication error rates were found in both patient admissions containing at least 1 medication error ( p < 0.001) and those with 2 or more errors ( p < 0.001). Significant reductions were also identified in each error type, including incorrect/incomplete medication regimen, incorrect dosing regimen, incorrect renal dose adjustment, incorrect administration, and the presence of a major drug-drug interaction. A regression tree selected ritonavir as the only specific medication that best predicted more errors preintervention ( p < 0.001); however, no antiretrovirals reliably predicted errors postintervention. An antiretroviral stewardship strategy for hospitalized HIV patients including prospective audit by staff pharmacists through use of an antiretroviral medication therapy checklist at the time of order verification decreased error rates. Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Predicting Error Bars for QSAR Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schroeter, Timon; Technische Universitaet Berlin, Department of Computer Science, Franklinstrasse 28/29, 10587 Berlin; Schwaighofer, Anton

2007-09-18

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D{sub 7} models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniquesmore » for the other modelling approaches.« less

A Root water uptake model to compensate disease stress in citrus trees

NASA Astrophysics Data System (ADS)

Peddinti, S. R.; Kambhammettu, B. P.; Lad, R. S.; Suradhaniwar, S.

2017-12-01

Plant root water uptake (RWU) controls a number of hydrologic fluxes in simulating unsaturated flow and transport processes. Variable saturated models that simulate soil-water-plant interactions within the rizhosphere do not account for the health of the tree. This makes them difficult to analyse RWU patterns for diseased trees. Improper irrigation management activities on diseased (Phytopthora spp. affected) citrus trees of central India has resulted in a significant reduction in crop yield accompanied by disease escalation. This research aims at developing a quantitative RWU model that accounts for the reduction in water stress as a function of plant disease level (hereafter called as disease stress). A total of four research plots with varying disease severity were considered for our field experimentation. A three-dimensional electrical resistivity tomography (ERT) was performed to understand spatio-temporal distribution in soil moisture following irrigation. Evaporation and transpiration were monitored daily using micro lysimeter and sap flow meters respectively. Disease intensity was quantified (on 0 to 9 scale) using pathological analysis on soil samples. Pedo-physocal and pedo-electric relations were established under controlled laboratory conditions. A non-linear disease stress response function for citrus trees was derived considering phonological, hydrological, and pathological parameters. Results of numerical simulations conclude that the propagation of error in RWU estimates by ignoring the health condition of the tree is significant. The developed disease stress function was then validated in the presence of deficit water and nutrient stress conditions. Results of numerical analysis showed a good agreement with experimental data, corroborating the need for alternate management practices for disease citrus trees.

Tree-based solvers for adaptive mesh refinement code FLASH - I: gravity and optical depths

NASA Astrophysics Data System (ADS)

Wünsch, R.; Walch, S.; Dinnbier, F.; Whitworth, A.

2018-04-01

We describe an OctTree algorithm for the MPI parallel, adaptive mesh refinement code FLASH, which can be used to calculate the gas self-gravity, and also the angle-averaged local optical depth, for treating ambient diffuse radiation. The algorithm communicates to the different processors only those parts of the tree that are needed to perform the tree-walk locally. The advantage of this approach is a relatively low memory requirement, important in particular for the optical depth calculation, which needs to process information from many different directions. This feature also enables a general tree-based radiation transport algorithm that will be described in a subsequent paper, and delivers excellent scaling up to at least 1500 cores. Boundary conditions for gravity can be either isolated or periodic, and they can be specified in each direction independently, using a newly developed generalization of the Ewald method. The gravity calculation can be accelerated with the adaptive block update technique by partially re-using the solution from the previous time-step. Comparison with the FLASH internal multigrid gravity solver shows that tree-based methods provide a competitive alternative, particularly for problems with isolated or mixed boundary conditions. We evaluate several multipole acceptance criteria (MACs) and identify a relatively simple approximate partial error MAC which provides high accuracy at low computational cost. The optical depth estimates are found to agree very well with those of the RADMC-3D radiation transport code, with the tree-solver being much faster. Our algorithm is available in the standard release of the FLASH code in version 4.0 and later.

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

PubMed

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

A Simple Model for the Earthquake Cycle Combining Self-Organized Criticality with Critical Point Behavior

NASA Astrophysics Data System (ADS)

Newman, W. I.; Turcotte, D. L.

2002-12-01

We have studied a hybrid model combining the forest-fire model with the site-percolation model in order to better understand the earthquake cycle. We consider a square array of sites. At each time step, a "tree" is dropped on a randomly chosen site and is planted if the site is unoccupied. When a cluster of "trees" spans the site (a percolating cluster), all the trees in the cluster are removed ("burned") in a "fire." The removal of the cluster is analogous to a characteristic earthquake and planting "trees" is analogous to increasing the regional stress. The clusters are analogous to the metastable regions of a fault over which an earthquake rupture can propagate once triggered. We find that the frequency-area statistics of the metastable regions are power-law with a negative exponent of two (as in the forest-fire model). This is analogous to the Gutenberg-Richter distribution of seismicity. This "self-organized critical behavior" can be explained in terms of an inverse cascade of clusters. Individual trees move from small to larger clusters until they are destroyed. This inverse cascade of clusters is self-similar and the power-law distribution of cluster sizes has been shown to have an exponent of two. We have quantified the forecasting of the spanning fires using error diagrams. The assumption that "fires" (earthquakes) are quasi-periodic has moderate predictability. The density of trees gives an improved degree of predictability, while the size of the largest cluster of trees provides a substantial improvement in forecasting a "fire."

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

PubMed Central

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

Depositional characteristics of atmospheric polybrominated diphenyl ethers on tree barks

PubMed Central

Chun, Man Young

2014-01-01

Objectives This study was conducted to determine the depositional characteristics of several tree barks, including Ginkgo (Ginkgo biloba), Pine (Pinus densiflora), Platanus (Platanus), and Metasequoia (Metasequoia glyptostroboides). These were used as passive air sampler (PAS) of atmospheric polybrominated diphenyl ethers (PBDEs). Methods Tree barks were sampled from the same site. PBDEs were analyzed by highresolution gas chromatography/high-resolution mass spectrometer, and the lipid content was measured using the gravimetric method by n-hexane extraction. Results Gingko contained the highest lipid content (7.82 mg/g dry), whereas pine (4.85 mg/g dry), Platanus (3.61 mg/g dry), and Metasequoia (0.97 mg/g dry) had relatively lower content. The highest total PBDEs concentration was observed in Metasequoia (83,159.0 pg/g dry), followed by Ginkgo (53,538.4 pg/g dry), Pine (20,266.4 pg/g dry), and Platanus (12,572.0 pg/g dry). There were poor correlations between lipid content and total PBDE concentrations in tree barks (R2=0.1011, p =0.682). Among the PBDE congeners, BDE 206, 207 and 209 were highly brominated PBDEs that are sorbed to particulates in ambient air, which accounted for 90.5% (84.3-95.6%) of the concentration and were therefore identified as the main PBDE congener. The concentrations of particulate PBDEs deposited on tree barks were dependent on morphological characteristics such as surface area or roughness of barks. Conclusions Therefore, when using the tree barks as the PAS of the atmospheric PBDEs, samples belonging to same tree species should be collected to reduce errors and to obtain reliable data. PMID:25116365

Depositional characteristics of atmospheric polybrominated diphenyl ethers on tree barks.

PubMed

Chun, Man Young

2014-07-17

This study was conducted to determine the depositional characteristics of several tree barks, including Ginkgo (Ginkgo biloba), Pine (Pinus densiflora), Platanus (Platanus), and Metasequoia (Metasequoia glyptostroboides). These were used as passive air sampler (PAS) of atmospheric polybrominated diphenyl ethers (PBDEs). Tree barks were sampled from the same site. PBDEs were analyzed by highresolution gas chromatography/high-resolution mass spectrometer, and the lipid content was measured using the gravimetric method by n-hexane extraction. Gingko contained the highest lipid content (7.82 mg/g dry), whereas pine (4.85 mg/g dry), Platanus (3.61 mg/g dry), and Metasequoia (0.97 mg/g dry) had relatively lower content. The highest total PBDEs concentration was observed in Metasequoia (83,159.0 pg/g dry), followed by Ginkgo (53,538.4 pg/g dry), Pine (20,266.4 pg/g dry), and Platanus (12,572.0 pg/g dry). There were poor correlations between lipid content and total PBDE concentrations in tree barks (R(2)=0.1011, p =0.682). Among the PBDE congeners, BDE 206, 207 and 209 were highly brominated PBDEs that are sorbed to particulates in ambient air, which accounted for 90.5% (84.3-95.6%) of the concentration and were therefore identified as the main PBDE congener. The concentrations of particulate PBDEs deposited on tree barks were dependent on morphological characteristics such as surface area or roughness of barks. Therefore, when using the tree barks as the PAS of the atmospheric PBDEs, samples belonging to same tree species should be collected to reduce errors and to obtain reliable data.

Clustering Genes of Common Evolutionary History

PubMed Central

Gori, Kevin; Suchan, Tomasz; Alvarez, Nadir; Goldman, Nick; Dessimoz, Christophe

2016-01-01

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent—due to events such as incomplete lineage sorting or horizontal gene transfer—it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modeling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by 1) identifying errors in a previous phylogenetic analysis of yeast species and 2) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history (http://git.io/treeCl). PMID:26893301

MERIT DEM: A new high-accuracy global digital elevation model and its merit to global hydrodynamic modeling

NASA Astrophysics Data System (ADS)

Yamazaki, D.; Ikeshima, D.; Neal, J. C.; O'Loughlin, F.; Sampson, C. C.; Kanae, S.; Bates, P. D.

2017-12-01

Digital Elevation Models (DEM) are fundamental data for flood modelling. While precise airborne DEMs are available in developed regions, most parts of the world rely on spaceborne DEMs which include non-negligible height errors. Here we show the most accurate global DEM to date at 90m resolution by eliminating major error components from the SRTM and AW3D DEMs. Using multiple satellite data and multiple filtering techniques, we addressed absolute bias, stripe noise, speckle noise and tree height bias from spaceborne DEMs. After the error removal, significant improvements were found in flat regions where height errors were larger than topography variability, and landscapes features such as river networks and hill-valley structures became clearly represented. We found the topography slope of the previous DEMs was largely distorted in most of world major floodplains (e.g. Ganges, Nile, Niger, Mekong) and swamp forests (e.g. Amazon, Congo, Vasyugan). The developed DEM will largely reduce the uncertainty in both global and regional flood modelling.

[A site index model for Larix principis-rupprechtii plantation in Saihanba, north China].

PubMed

Wang, Dong-zhi; Zhang, Dong-yan; Jiang, Feng-ling; Bai, Ye; Zhang, Zhi-dong; Huang, Xuan-rui

2015-11-01

It is often difficult to estimate site indices for different types of plantation by using an ordinary site index model. The objective of this paper was to establish a site index model for plantations in varied site conditions, and assess the site qualities. In this study, a nonlinear mixed site index model was constructed based on data from the second class forest resources inventory and 173 temporary sample plots. The results showed that the main limiting factors for height growth of Larix principis-rupprechtii were elevation, slope, soil thickness and soil type. A linear regression model was constructed for the main constraining site factors and dominant tree height, with the coefficient of determination being 0.912, and the baseline age of Larix principis-rupprechtii determined as 20 years. The nonlinear mixed site index model parameters for the main site types were estimated (R2 > 0.85, the error between the predicted value and the actual value was in the range of -0.43 to 0.45, with an average root mean squared error (RMSE) in the range of 0.907 to 1.148). The estimation error between the predicted value and the actual value of dominant tree height for the main site types was in the confidence interval of [-0.95, 0.95]. The site quality of the high altitude-shady-sandy loam-medium soil layer was the highest and that of low altitude-sunny-sandy loam-medium soil layer was the lowest, while the other two sites were moderate.

Dry borax applicator operator's manual.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karsky, Richard, J.

1999-01-01

Annosum root rot affects conifers throughout the Northern Hemisphere, infecting their roots and eventually killing the trees. The fungus Heterobasidion annosum causes annosum root rot. The fungus colonizes readily on freshly cut stumps. Partially cut stands have a high risk of infestation because the fungus can colonize on each of the stumps and potentially infect the neighboring trees. Wind and rain carry the annosum spores. Spores that land on freshly cut stumps grow down the stump's root system where they can infect living trees through root grafts or root contacts. Once annosum becomes established, it can remain active for manymore » years in the Southern United States and for several decades in the north. About 7% of the trees that become infected die. When thinning, stumps can be treated successfully using a competing fungus, Phlebia gigantea, and with ''Tim-Bor'' in liquid formulations. These liquid products are no longer approved in the United States. Only the dry powder form is registered and approved by the EPA. Stumps can be treated with a dry formula of borax, (Sporax), significantly reducing one of the primary routes by which Heterobasidion annosum infects a stand of trees. Sporax is used by the USDA Forest Service to control annosum root rot. Sporax is now applied by hand, but once the felled trees are skidded it becomes very hard to locate the stumps. A stump applicator will reduce error, labor costs, and hazards to workers.« less

Seasonal trends in separability of leaf reflectance spectra for Ailanthus altissima and four other tree species

NASA Astrophysics Data System (ADS)

Burkholder, Aaron

This project investigated the spectral separability of the invasive species Ailanthus altissima, commonly called tree of heaven, and four other native species. Leaves were collected from Ailanthus and four native tree species from May 13 through August 24, 2008, and spectral reflectance factor measurements were gathered for each tree using an ASD (Boulder, Colorado) FieldSpec Pro full-range spectroradiometer. The original data covered the range from 350-2500 nm, with one reflectance measurement collected per one nm wavelength. To reduce dimensionality, the measurements were resampled to the actual resolution of the spectrometer's sensors, and regions of atmospheric absorption were removed. Continuum removal was performed on the reflectance data, resulting in a second dataset. For both the reflectance and continuum removed datasets, least angle regression (LARS) and random forest classification were used to identify a single set of optimal wavelengths across all sampled dates, a set of optimal wavelengths for each date, and the dates for which Ailanthus is most separable from other species. It was found that classification accuracy varies both with dates and bands used. Contrary to expectations that early spring would provide the best separability, the lowest classification error was observed on July 22 for the reflectance data, and on May 13, July 11 and August 1 for the continuum removed data. This suggests that July and August are also potentially good months for species differentiation. Applying continuum removal in many cases reduced classification error, although not consistently. Band selection seems to be more important for reflectance data in that it results in greater improvement in classification accuracy, and LARS appears to be an effective band selection tool. The optimal spectral bands were selected from across the spectrum, often with bands from the blue (401-431 nm), NIR (1115 nm) and SWIR (1985-1995 nm), suggesting that hyperspectral sensors with broad wavelength sensitivity are important for mapping and identification of Ailanthus.

Biomechanical deformable image registration of longitudinal lung CT images using vessel information

NASA Astrophysics Data System (ADS)

Cazoulat, Guillaume; Owen, Dawn; Matuszak, Martha M.; Balter, James M.; Brock, Kristy K.

2016-07-01

Spatial correlation of lung tissue across longitudinal images, as the patient responds to treatment, is a critical step in adaptive radiotherapy. The goal of this work is to expand a biomechanical model-based deformable registration algorithm (Morfeus) to achieve accurate registration in the presence of significant anatomical changes. Six lung cancer patients previously treated with conventionally fractionated radiotherapy were retrospectively evaluated. Exhale CT scans were obtained at treatment planning and following three weeks of treatment. For each patient, the planning CT was registered to the follow-up CT using Morfeus, a biomechanical model-based deformable registration algorithm. To model the complex response of the lung, an extension to Morfeus has been developed: an initial deformation was estimated with Morfeus consisting of boundary conditions on the chest wall and incorporating a sliding interface with the lungs. It was hypothesized that the addition of boundary conditions based on vessel tree matching would provide a robust reduction of the residual registration error. To achieve this, the vessel trees were segmented on the two images by thresholding a vesselness image based on the Hessian matrix’s eigenvalues. For each point on the reference vessel tree centerline, the displacement vector was estimated by applying a variant of the Demons registration algorithm between the planning CT and the deformed follow-up CT. An expert independently identified corresponding landmarks well distributed in the lung to compute target registration errors (TRE). The TRE was: 5.8+/- 2.9 , 3.4+/- 2.3 and 1.6+/- 1.3 mm after rigid registration, Morfeus and Morfeus with boundary conditions on the vessel tree, respectively. In conclusion, the addition of boundary conditions on the vessels significantly improved the accuracy in modeling the response of the lung and tumor over the course of radiotherapy. Minimizing and modeling these geometrical uncertainties will enable future plan adaptation strategies.

So many genes, so little time: A practical approach to divergence-time estimation in the genomic era

PubMed Central

2018-01-01

Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. “Gene shopping”, wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated lognormal (UCLN) models. However, this overlap was often due to imprecise estimates from the UCLN model. We find that “gene shopping” can be an efficient approach to divergence-time inference for phylogenomic datasets that may otherwise be characterized by extensive gene tree heterogeneity. PMID:29772020

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

So many genes, so little time: A practical approach to divergence-time estimation in the genomic era.

PubMed

Smith, Stephen A; Brown, Joseph W; Walker, Joseph F

2018-01-01

Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated lognormal (UCLN) models. However, this overlap was often due to imprecise estimates from the UCLN model. We find that "gene shopping" can be an efficient approach to divergence-time inference for phylogenomic datasets that may otherwise be characterized by extensive gene tree heterogeneity.

Resin distribution in second-growth ponderosa pine

Treesearch

B.H. Paul

1955-01-01

In a study of specific gravity of second-growth ponderosa pine, there was visible evidence of resin in a part of the specific gravity specimens. Each specimen contained 10 annual growth rings in cross sections taken at 4 heights in the merchantable length of the trees. Since the presence of resin introduced an uncertain amount of error in the specific gravity values,...

Partitioning the Uncertainty in Estimates of Mean Basal Area Obtained from 10-year Diameter Growth Model Predictions

Treesearch

Ronald E. McRoberts

2005-01-01

Uncertainty in model-based predictions of individual tree diameter growth is attributed to three sources: measurement error for predictor variables, residual variability around model predictions, and uncertainty in model parameter estimates. Monte Carlo simulations are used to propagate the uncertainty from the three sources through a set of diameter growth models to...

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

NASA Technical Reports Server (NTRS)

Wilhelms, Jane; vanGelder, Allen

1999-01-01

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

A genotyping protocol for multiple tissue types from the polyploid tree species Sequoia sempervirens (Cupressaceae)1

PubMed Central

Narayan, Lakshmi; Dodd, Richard S.; O’Hara, Kevin L.

2015-01-01

Premise of the study: Identifying clonal lineages in asexually reproducing plants using microsatellite markers is complicated by the possibility of nonidentical genotypes from the same clonal lineage due to somatic mutations, null alleles, and scoring errors. We developed and tested a clonal identification protocol that is robust to these issues for the asexually reproducing hexaploid tree species coast redwood (Sequoia sempervirens). Methods: Microsatellite data from four previously published and two newly developed primers were scored using a modified protocol, and clones were identified using Bruvo genetic distances. The effectiveness of this clonal identification protocol was assessed using simulations and by genotyping a test set of paired samples of different tissue types from the same trees. Results: Data from simulations showed that our protocol allowed us to accurately identify clonal lineages. Multiple test samples from the same trees were identified correctly, although certain tissue type pairs had larger genetic distances on average. Discussion: The methods described in this paper will allow for the accurate identification of coast redwood clones, facilitating future studies of the reproductive ecology of this species. The techniques used in this paper can be applied to studies of other clonal organisms as well. PMID:25798341

A genotyping protocol for multiple tissue types from the polyploid tree species Sequoia sempervirens (Cupressaceae).

PubMed

Narayan, Lakshmi; Dodd, Richard S; O'Hara, Kevin L

2015-03-01

Identifying clonal lineages in asexually reproducing plants using microsatellite markers is complicated by the possibility of nonidentical genotypes from the same clonal lineage due to somatic mutations, null alleles, and scoring errors. We developed and tested a clonal identification protocol that is robust to these issues for the asexually reproducing hexaploid tree species coast redwood (Sequoia sempervirens). Microsatellite data from four previously published and two newly developed primers were scored using a modified protocol, and clones were identified using Bruvo genetic distances. The effectiveness of this clonal identification protocol was assessed using simulations and by genotyping a test set of paired samples of different tissue types from the same trees. Data from simulations showed that our protocol allowed us to accurately identify clonal lineages. Multiple test samples from the same trees were identified correctly, although certain tissue type pairs had larger genetic distances on average. The methods described in this paper will allow for the accurate identification of coast redwood clones, facilitating future studies of the reproductive ecology of this species. The techniques used in this paper can be applied to studies of other clonal organisms as well.

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich

2017-05-01

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Parmar, Kulwinder Singh

2016-03-01

This study investigates the accuracy of least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in modeling river water pollution. Various combinations of water quality parameters, Free Ammonia (AMM), Total Kjeldahl Nitrogen (TKN), Water Temperature (WT), Total Coliform (TC), Fecal Coliform (FC) and Potential of Hydrogen (pH) monitored at Nizamuddin, Delhi Yamuna River in India were used as inputs to the applied models. Results indicated that the LSSVM and MARS models had almost same accuracy and they performed better than the M5Tree model in modeling monthly chemical oxygen demand (COD). The average root mean square error (RMSE) of the LSSVM and M5Tree models was decreased by 1.47% and 19.1% using MARS model, respectively. Adding TC input to the models did not increase their accuracy in modeling COD while adding FC and pH inputs to the models generally decreased the accuracy. The overall results indicated that the MARS and LSSVM models could be successfully used in estimating monthly river water pollution level by using AMM, TKN and WT parameters as inputs.

Estimating tree species diversity in the savannah using NDVI and woody canopy cover

NASA Astrophysics Data System (ADS)

Madonsela, Sabelo; Cho, Moses Azong; Ramoelo, Abel; Mutanga, Onisimo; Naidoo, Laven

2018-04-01

Remote sensing applications in biodiversity research often rely on the establishment of relationships between spectral information from the image and tree species diversity measured in the field. Most studies have used normalized difference vegetation index (NDVI) to estimate tree species diversity on the basis that it is sensitive to primary productivity which defines spatial variation in plant diversity. The NDVI signal is influenced by photosynthetically active vegetation which, in the savannah, includes woody canopy foliage and grasses. The question is whether the relationship between NDVI and tree species diversity in the savanna depends on the woody cover percentage. This study explored the relationship between woody canopy cover (WCC) and tree species diversity in the savannah woodland of southern Africa and also investigated whether there is a significant interaction between seasonal NDVI and WCC in the factorial model when estimating tree species diversity. To fulfil our aim, we followed stratified random sampling approach and surveyed tree species in 68 plots of 90 m × 90 m across the study area. Within each plot, all trees with diameter at breast height of >10 cm were sampled and Shannon index - a common measure of species diversity which considers both species richness and abundance - was used to quantify tree species diversity. We then extracted WCC in each plot from existing fractional woody cover product produced from Synthetic Aperture Radar (SAR) data. Factorial regression model was used to determine the interaction effect between NDVI and WCC when estimating tree species diversity. Results from regression analysis showed that (i) WCC has a highly significant relationship with tree species diversity (r2 = 0.21; p < 0.01), (ii) the interaction between the NDVI and WCC is not significant, however, the factorial model significantly reduced the error of prediction (RMSE = 0.47, p < 0.05) compared to NDVI (RMSE = 0.49) or WCC (RMSE = 0.49) model during the senescence period. The result justifies our assertion that combining NDVI with WCC will be optimal for biodiversity estimation during the senescence period.

Design of Software for Design of Finite Element for Structural Analysis. Ph.D. Thesis - Stuttgart Univ., 22 Nov. 1983

NASA Technical Reports Server (NTRS)

Helfrich, Reinhard

1987-01-01

The concepts of software engineering which allow a user of the finite element method to describe a model, to collect and to check the model data in a data base as well as to form the matrices required for a finite element calculation are examined. Next the components of the model description are conceived including the mesh tree, the topology, the configuration, the kinematic boundary conditions, the data for each element, and the loads. The possibilities for description and review of the data are considered. The concept of the segments for the modularization of the programs follows the components of the model description. The significance of the mesh tree as a globular guiding structure will be understood in view of the principle of the unity of the model, the mesh tree, and the data base. The user-friendly aspects of the software system will be summarized: the principle of language communication, the data generators, error processing, and data security.

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClanahan, Richard; De Leon, Phillip L.

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

DOE PAGES

McClanahan, Richard; De Leon, Phillip L.

2014-08-20

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Assessment of the relative merits of a few methods to detect evolutionary trends.

PubMed

Laurin, Michel

2010-12-01

Some of the most basic questions about the history of life concern evolutionary trends. These include determining whether or not metazoans have become more complex over time, whether or not body size tends to increase over time (the Cope-Depéret rule), or whether or not brain size has increased over time in various taxa, such as mammals and birds. Despite the proliferation of studies on such topics, assessment of the reliability of results in this field is hampered by the variability of techniques used and the lack of statistical validation of these methods. To solve this problem, simulations are performed using a variety of evolutionary models (gradual Brownian motion, speciational Brownian motion, and Ornstein-Uhlenbeck), with or without a drift of variable amplitude, with variable variance of tips, and with bounds placed close or far from the starting values and final means of simulated characters. These are used to assess the relative merits (power, Type I error rate, bias, and mean absolute value of error on slope estimate) of several statistical methods that have recently been used to assess the presence of evolutionary trends in comparative data. Results show widely divergent performance of the methods. The simple, nonphylogenetic regression (SR) and variance partitioning using phylogenetic eigenvector regression (PVR) with a broken stick selection procedure have greatly inflated Type I error rate (0.123-0.180 at a 0.05 threshold), which invalidates their use in this context. However, they have the greatest power. Most variants of Felsenstein's independent contrasts (FIC; five of which are presented) have adequate Type I error rate, although two have a slightly inflated Type I error rate with at least one of the two reference trees (0.064-0.090 error rate at a 0.05 threshold). The power of all contrast-based methods is always much lower than that of SR and PVR, except under Brownian motion with a strong trend and distant bounds. Mean absolute value of error on slope of all FIC methods is slightly higher than that of phylogenetic generalized least squares (PGLS), SR, and PVR. PGLS performs well, with low Type I error rate, low error on regression coefficient, and power comparable with some FIC methods. Four variants of skewness analysis are examined, and a new method to assess significance of results is presented. However, all have consistently low power, except in rare combinations of trees, trend strength, and distance between final means and bounds. Globally, the results clearly show that FIC-based methods and PGLS are globally better than nonphylogenetic methods and variance partitioning with PVR. FIC methods and PGLS are sensitive to the model of evolution (and, hence, to branch length errors). Our results suggest that regressing raw character contrasts against raw geological age contrasts yields a good combination of power and Type I error rate. New software to facilitate batch analysis is presented.

PhySIC_IST: cleaning source trees to infer more informative supertrees

PubMed Central

Scornavacca, Celine; Berry, Vincent; Lefort, Vincent; Douzery, Emmanuel JP; Ranwez, Vincent

2008-01-01

Background Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. Results To overcome this problem, we propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly differs among source trees or for which insufficient information is provided. We detail a variant of the PhySIC veto method called PhySIC_IST that can infer non-plenary supertrees. PhySIC_IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally, we propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that significantly conflict with other source trees. Combining STC with a veto method allows an explicit trade-off between veto and liberal approaches, tuned by a single parameter. Performing large-scale simulations, we observe that STC+PhySIC_IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the well-known MRP method. Two biological case studies on animals confirm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC_IST provides well-resolved supertrees agreeing with current knowledge in systematics. Conclusion The paper introduces and tests two new methodologies, PhySIC_IST and STC, that demonstrate the interest in inferring non-plenary supertrees as well as preprocessing the source trees. An implementation of the methods is available at: . PMID:18834542

Voxel-Based 3-D Tree Modeling from Lidar Images for Extracting Tree Structual Information

NASA Astrophysics Data System (ADS)

Hosoi, F.

2014-12-01

Recently, lidar (light detection and ranging) has been used to extracting tree structural information. Portable scanning lidar systems can capture the complex shape of individual trees as a 3-D point-cloud image. 3-D tree models reproduced from the lidar-derived 3-D image can be used to estimate tree structural parameters. We have proposed the voxel-based 3-D modeling for extracting tree structural parameters. One of the tree parameters derived from the voxel modeling is leaf area density (LAD). We refer to the method as the voxel-based canopy profiling (VCP) method. In this method, several measurement points surrounding the canopy and optimally inclined laser beams are adopted for full laser beam illumination of whole canopy up to the internal. From obtained lidar image, the 3-D information is reproduced as the voxel attributes in the 3-D voxel array. Based on the voxel attributes, contact frequency of laser beams on leaves is computed and LAD in each horizontal layer is obtained. This method offered accurate LAD estimation for individual trees and woody canopy trees. For more accurate LAD estimation, the voxel model was constructed by combining airborne and portable ground-based lidar data. The profiles obtained by the two types of lidar complemented each other, thus eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. Based on the estimation results, we proposed an index named laser beam coverage index, Ω, which relates to the lidar's laser beam settings and a laser beam attenuation factor. It was shown that this index can be used for adjusting measurement set-up of lidar systems and also used for explaining the LAD estimation error using different types of lidar systems. Moreover, we proposed a method to estimate woody material volume as another application of the voxel tree modeling. In this method, voxel solid model of a target tree was produced from the lidar image, which is composed of consecutive voxels that filled the outer surface and the interior of the stem and large branches. From the model, the woody material volume of any part of the target tree can be directly calculated easily by counting the number of corresponding voxels and multiplying the result by the per-voxel volume.

PhySIC_IST: cleaning source trees to infer more informative supertrees.

PubMed

Scornavacca, Celine; Berry, Vincent; Lefort, Vincent; Douzery, Emmanuel J P; Ranwez, Vincent

2008-10-04

Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. To overcome this problem, we propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly differs among source trees or for which insufficient information is provided. We detail a variant of the PhySIC veto method called PhySIC_IST that can infer non-plenary supertrees. PhySIC_IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally, we propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that significantly conflict with other source trees. Combining STC with a veto method allows an explicit trade-off between veto and liberal approaches, tuned by a single parameter.Performing large-scale simulations, we observe that STC+PhySIC_IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the well-known MRP method. Two biological case studies on animals confirm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC_IST provides well-resolved supertrees agreeing with current knowledge in systematics. The paper introduces and tests two new methodologies, PhySIC_IST and STC, that demonstrate the interest in inferring non-plenary supertrees as well as preprocessing the source trees. An implementation of the methods is available at: http://www.atgc-montpellier.fr/physic_ist/.

Condition trees as a mechanism for communicating the meaning of uncertainties

NASA Astrophysics Data System (ADS)

Beven, Keith

2015-04-01

Uncertainty communication for environmental problems is fraught with difficulty for good epistemic reasons. The fact that most sources of uncertainty are subject to, and often dominated by, epistemic uncertainties means that the unthinking use of probability theory might actually be misleading and lead to false inference (even in some cases where the assumptions of a probabilistic error model might seem to be reasonably valid). This therefore creates problems in communicating the meaning of probabilistic uncertainties of model predictions to potential users (there are many examples in hydrology, hydraulics, climate change and other domains). It is suggested that one way of being more explicit about the meaning of uncertainties is to associate each type of application with a condition tree of assumptions that need to be made in producing an estimate of uncertainty. The condition tree then provides a basis for discussion and communication of assumptions about uncertainties with users. Agreement of assumptions (albeit generally at some institutional level) will provide some buy-in on the part of users, and a basis for commissioning of future studies. Even in some relatively well-defined problems, such as mapping flood risk, such a condition tree can be rather extensive, but by making each step in the tree explicit then an audit trail is established for future reference. This can act to provide focus in the exercise of agreeing more realistic assumptions.

LiDAR-based TWI and terrain attributes in improving parametric predictor for tree growth in southeast Finland

NASA Astrophysics Data System (ADS)

Mohamedou, Cheikh; Tokola, Timo; Eerikäinen, Kalle

2017-10-01

The effect of soil moisture content on vegetation and therefore on growth is well known. Information about the growth of forest stands is key in forest planning and management, and is the concern of various stakeholders. One way to assess moisture content and its impacts on forest growth is to apply the Topographic Wetness Index (TWI) and the derived terrain attributes from the Digital Terrain Model (DTM). The TWI is an important terrain attribute, used in various ecological studies. In the current study, a total of 9987 tally trees within 197 sample plots in southeastern Finland and LiDAR (Light Detection and Ranging) -based TWI were selected to examine: 1) the effect of cell resolutions and focal statistics of neighborhood cells of DTM, on tree diameter increment, and 2) possibilities to improve the prediction accuracy of an existing single-tree growth model using the terrain attributes and TWI with the combined effects of three characteristics (i.e., cell resolutions, neighborhood cells and terrain attributes). The results suggest that the TWI with terrain attributes improved the growth estimation significantly, and within different site types the Root Mean Square Errors (RMSE) were lowered substantially. The best results were obtained for birch trees. The higher resolution of the DTM and the lower focal neighborhood cells were found to be the best alternative in computing the TWI.

[Biomass allometric equations of nine common tree species in an evergreen broadleaved forest of subtropical China].

PubMed

Zuo, Shu-di; Ren, Yin; Weng, Xian; Ding, Hong-feng; Luo, Yun-jian

2015-02-01

Biomass allometric equation (BAE) considered as a simple and reliable method in the estimation of forest biomass and carbon was used widely. In China, numerous studies focused on the BAEs for coniferous forest and pure broadleaved forest, and generalized BAEs were frequently used to estimate the biomass and carbon of mixed broadleaved forest, although they could induce large uncertainty in the estimates. In this study, we developed the species-specific and generalized BAEs using biomass measurement for 9 common broadleaved trees (Castanopsis fargesii, C. lamontii, C. tibetana, Lithocarpus glaber, Sloanea sinensis, Daphniphyllum oldhami, Alniphyllum fortunei, Manglietia yuyuanensis, and Engelhardtia fenzlii) of subtropical evergreen broadleaved forest, and compared differences in species-specific and generalized BAEs. The results showed that D (diameter at breast height) was a better independent variable in estimating the biomass of branch, leaf, root, aboveground section and total tree than a combined variable (D2 H) of D and H (tree height) , but D2H was better than D in estimating stem biomass. R2 (coefficient of determination) values of BAEs for 6 species decreased when adding H as the second independent variable into D- only BAEs, where R2 value for S. sinensis decreased by 5.6%. Compared with generalized D- and D2H-based BAEs, standard errors of estimate (SEE) of BAEs for 8 tree species decreased, and similar decreasing trend was observed for different components, where SEEs of the branch decreased by 13.0% and 20.3%. Therefore, the biomass carbon storage and its dynamic estimates were influenced largely by tree species and model types. In order to improve the accuracy of the estimates of biomass and carbon, we should consider the differences in tree species and model types.

Validating Community-Led Forest Biomass Assessments.

PubMed

Venter, Michelle; Venter, Oscar; Edwards, Will; Bird, Michael I

2015-01-01

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha(-1), which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50 cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.

Validating Community-Led Forest Biomass Assessments

PubMed Central

Venter, Michelle; Venter, Oscar; Edwards, Will; Bird, Michael I.

2015-01-01

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha-1, which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees. PMID:26126186

Technical note: tree truthing: how accurate are substrate estimates in primate field studies?

PubMed

Bezanson, Michelle; Watts, Sean M; Jobin, Matthew J

2012-04-01

Field studies of primate positional behavior typically rely on ground-level estimates of substrate size, angle, and canopy location. These estimates potentially influence the identification of positional modes by the observer recording behaviors. In this study we aim to test ground-level estimates against direct measurements of support angles, diameters, and canopy heights in trees at La Suerte Biological Research Station in Costa Rica. After reviewing methods that have been used by past researchers, we provide data collected within trees that are compared to estimates obtained from the ground. We climbed five trees and measured 20 supports. Four observers collected measurements of each support from different locations on the ground. Diameter estimates varied from the direct tree measures by 0-28 cm (Mean: 5.44 ± 4.55). Substrate angles varied by 1-55° (Mean: 14.76 ± 14.02). Height in the tree was best estimated using a clinometer as estimates with a two-meter reference placed by the tree varied by 3-11 meters (Mean: 5.31 ± 2.44). We determined that the best support size estimates were those generated relative to the size of the focal animal and divided into broader categories. Support angles were best estimated in 5° increments and then checked using a Haglöf clinometer in combination with a laser pointer. We conclude that three major factors should be addressed when estimating support features: observer error (e.g., experience and distance from the target), support deformity, and how support size and angle influence the positional mode selected by a primate individual. individual. Copyright © 2012 Wiley Periodicals, Inc.

Genetic diversity and mating type distribution of Tuber melanosporum and their significance to truffle cultivation in artificially planted truffieres in Australia.

PubMed

Linde, C C; Selmes, H

2012-09-01

Tuber melanosporum is a truffle native to Europe and is cultivated in countries such as Australia for the gastronomic market, where production yields are often lower than expected. We assessed the genetic diversity of T. melanosporum with six microsatellite loci to assess the effect of genetic drift on truffle yield in Australia. Genetic diversity as assessed on 210 ascocarps revealed a higher allelic diversity compared to previous studies from Europe, suggesting a possible genetic expansion and/or multiple and diverse source populations for inoculum. The results also suggest that the single sequence repeat diversity of locus ME2 is adaptive and that, for example, the probability of replication errors is increased for this locus. Loss of genetic diversity in Australian populations is therefore not a likely factor in limiting ascocarp production. A survey of nursery seedlings and trees inoculated with T. melanosporum revealed that <70% of seedlings and host trees were colonized with T. melanosporum and that some trees had been contaminated by Tuber brumale, presumably during the inoculation process. Mating type (MAT1-1-1 and MAT1-2-1) analyses on seedling and four- to ten-year-old host trees found that 100% of seedlings but only approximately half of host trees had both mating types present. Furthermore, MAT1-1-1 was detected significantly more commonly than MAT1-2-1 in established trees, suggesting a competitive advantage for MAT1-1-1 strains. This study clearly shows that there are more factors involved in ascocarp production than just the presence of both mating types on host trees.

Genetic Diversity and Mating Type Distribution of Tuber melanosporum and Their Significance to Truffle Cultivation in Artificially Planted Truffiéres in Australia

PubMed Central

Selmes, H.

2012-01-01

Tuber melanosporum is a truffle native to Europe and is cultivated in countries such as Australia for the gastronomic market, where production yields are often lower than expected. We assessed the genetic diversity of T. melanosporum with six microsatellite loci to assess the effect of genetic drift on truffle yield in Australia. Genetic diversity as assessed on 210 ascocarps revealed a higher allelic diversity compared to previous studies from Europe, suggesting a possible genetic expansion and/or multiple and diverse source populations for inoculum. The results also suggest that the single sequence repeat diversity of locus ME2 is adaptive and that, for example, the probability of replication errors is increased for this locus. Loss of genetic diversity in Australian populations is therefore not a likely factor in limiting ascocarp production. A survey of nursery seedlings and trees inoculated with T. melanosporum revealed that <70% of seedlings and host trees were colonized with T. melanosporum and that some trees had been contaminated by Tuber brumale, presumably during the inoculation process. Mating type (MAT1-1-1 and MAT1-2-1) analyses on seedling and four- to ten-year-old host trees found that 100% of seedlings but only approximately half of host trees had both mating types present. Furthermore, MAT1-1-1 was detected significantly more commonly than MAT1-2-1 in established trees, suggesting a competitive advantage for MAT1-1-1 strains. This study clearly shows that there are more factors involved in ascocarp production than just the presence of both mating types on host trees. PMID:22773652

A New Method to Compare Statistical Tree Growth Curves: The PL-GMANOVA Model and Its Application with Dendrochronological Data

PubMed Central

Ricker, Martin; Peña Ramírez, Víctor M.; von Rosen, Dietrich

2014-01-01

Growth curves are monotonically increasing functions that measure repeatedly the same subjects over time. The classical growth curve model in the statistical literature is the Generalized Multivariate Analysis of Variance (GMANOVA) model. In order to model the tree trunk radius (r) over time (t) of trees on different sites, GMANOVA is combined here with the adapted PL regression model Q = A·T+E, where for and for , A =  initial relative growth to be estimated, , and E is an error term for each tree and time point. Furthermore, Ei[–b·r]  = , , with TPR being the turning point radius in a sigmoid curve, and at is an estimated calibrating time-radius point. Advantages of the approach are that growth rates can be compared among growth curves with different turning point radiuses and different starting points, hidden outliers are easily detectable, the method is statistically robust, and heteroscedasticity of the residuals among time points is allowed. The model was implemented with dendrochronological data of 235 Pinus montezumae trees on ten Mexican volcano sites to calculate comparison intervals for the estimated initial relative growth . One site (at the Popocatépetl volcano) stood out, with being 3.9 times the value of the site with the slowest-growing trees. Calculating variance components for the initial relative growth, 34% of the growth variation was found among sites, 31% among trees, and 35% over time. Without the Popocatépetl site, the numbers changed to 7%, 42%, and 51%. Further explanation of differences in growth would need to focus on factors that vary within sites and over time. PMID:25402427

Tree Circumference Dynamics in Four Forests Characterized Using Automated Dendrometer Bands

PubMed Central

McMahon, Sean M.; Detto, Matteo; Lutz, James A.; Davies, Stuart J.; Chang-Yang, Chia-Hao; Anderson-Teixeira, Kristina J.

2016-01-01

Stem diameter is one of the most commonly measured attributes of trees, forming the foundation of forest censuses and monitoring. Changes in tree stem circumference include both irreversible woody stem growth and reversible circumference changes related to water status, yet these fine-scale dynamics are rarely leveraged to understand forest ecophysiology and typically ignored in plot- or stand-scale estimates of tree growth and forest productivity. Here, we deployed automated dendrometer bands on 12–40 trees at four different forested sites—two temperate broadleaf deciduous, one temperate conifer, and one tropical broadleaf semi-deciduous—to understand how tree circumference varies on time scales of hours to months, how these dynamics relate to environmental conditions, and whether the structure of these variations might introduce substantive error into estimates of woody growth. Diurnal stem circumference dynamics measured over the bark commonly—but not consistently—exhibited daytime shrinkage attributable to transpiration-driven changes in stem water storage. The amplitude of this shrinkage was significantly correlated with climatic variables (daily temperature range, vapor pressure deficit, and radiation), sap flow and evapotranspiration. Diurnal variations were typically <0.5 mm circumference in amplitude and unlikely to be of concern to most studies of tree growth. Over time scales of multiple days, the bands captured circumference increases in response to rain events, likely driven by combinations of increased stem water storage and bark hydration. Particularly at the tropical site, these rain responses could be quite substantial, ranging up to 1.5 mm circumference expansion within 48 hours following a rain event. We conclude that over-bark measurements of stem circumference change sometimes correlate with but have limited potential for directly estimating daily transpiration, but that they can be valuable on time scales of days to weeks for characterizing changes in stem growth and hydration. PMID:28030646

ListingAnalyst: A program for analyzing the main output file from MODFLOW

USGS Publications Warehouse

Winston, Richard B.; Paulinski, Scott

2014-01-01

ListingAnalyst is a Windows® program for viewing the main output file from MODFLOW-2005, MODFLOW-NWT, or MODFLOW-LGR. It organizes and displays large files quickly without using excessive memory. The sections and subsections of the file are displayed in a tree-view control, which allows the user to navigate quickly to desired locations in the files. ListingAnalyst gathers error and warning messages scattered throughout the main output file and displays them all together in an error and a warning tab. A grid view displays tables in a readable format and allows the user to copy the table into a spreadsheet. The user can also search the file for terms of interest.

A complete representation of uncertainties in layer-counted paleoclimatic archives

NASA Astrophysics Data System (ADS)

Boers, Niklas; Goswami, Bedartha; Ghil, Michael

2017-09-01

Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5-52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval.

Decision support system for determining the contact lens for refractive errors patients with classification ID3

NASA Astrophysics Data System (ADS)

Situmorang, B. H.; Setiawan, M. P.; Tosida, E. T.

2017-01-01

Refractive errors are abnormalities of the refraction of light so that the shadows do not focus precisely on the retina resulting in blurred vision [1]. Refractive errors causing the patient should wear glasses or contact lenses in order eyesight returned to normal. The use of glasses or contact lenses in a person will be different from others, it is influenced by patient age, the amount of tear production, vision prescription, and astigmatic. Because the eye is one organ of the human body is very important to see, then the accuracy in determining glasses or contact lenses which will be used is required. This research aims to develop a decision support system that can produce output on the right contact lenses for refractive errors patients with a value of 100% accuracy. Iterative Dichotomize Three (ID3) classification methods will generate gain and entropy values of attributes that include code sample data, age of the patient, astigmatic, the ratio of tear production, vision prescription, and classes that will affect the outcome of the decision tree. The eye specialist test result for the training data obtained the accuracy rate of 96.7% and an error rate of 3.3%, the result test using confusion matrix obtained the accuracy rate of 96.1% and an error rate of 3.1%; for the data testing obtained accuracy rate of 100% and an error rate of 0.

AGILE: Autonomous Global Integrated Language Exploitation

DTIC Science & Technology

2009-12-01

combination, including METEOR-based alignment (with stemming and WordNet synonym matching) and GIZA ++ based alignment. So far, we have not seen any...parse trees and a detailed analysis of how function words operate in translation. This program lets us fix alignment errors that systems like GIZA ...correlates better with Pyramid than with Responsiveness scoring (i.e., it is a more precise, careful, measure) • BE generally outperforms ROUGE

North American vegetation model for land-use planning in a changing climate: A solution to large classification problems

Treesearch

Gerald E. Rehfeldt; Nicholas L. Crookston; Cuauhtemoc Saenz-Romero; Elizabeth M. Campbell

2012-01-01

Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of...

Comparison of estimates of snow input to a small alpine watershed

Treesearch

R. A. Sommerfeld; R. C. Musselman; G. L. Wooldridge

1990-01-01

We have used five methods to estimate the snow water equivalent input to the Glacier Lakes Ecosystem Experiments Site (GLEES) in south-central Wyoming during the winter 1987-1988 and to obtain an estimate of the errors. The methods are: (1) the Martinec and Rango degree-day method; (2) Wooldridge et al. method of determining the average yearly snowfall from tree...

Throughfall in a Puerto Rican lower montane rain forest: A comparison of sampling strategies

Treesearch

F. Holwerda; F.N. Scatena; L.A. Bruijnzeel

2006-01-01

During a one-year period, the variability of throughfall and the standard errors of the means associated with different gauge arrangements were studied in a lower montane rain forest in Puerto Rico. The following gauge arrangements were used: (1) 60 fixed gauges, (2) 30 fixed gauges, and (3) 30 roving gauges. Stemflow was measured on 22 trees of four different species...

Temperature variation and distribution of living cells within tree stems: implications for stem respiration modeling and scale-up.

PubMed

Stockfors, J

2000-09-01

Few studies have examined variation in respiration rates within trees, and even fewer studies have focused on variation caused by within-stem temperature differences. In this study, stem temperatures at 40 positions in the stem of one 30-year-old Norway spruce (Picea abies (L.) Karst.) were measured during 40 days between July 1994 and June 1995. The temperature data were used to simulate variations in respiration rate within the stem. The simulations assumed that the temperature-respiration relationship was constant (Q10 = 2) for all days and all stem positions. Total respiration for the whole stem was calculated by interpolating the temperature between the thermocouples and integrating the respiration rates in three dimensions. Total respiration rate of the stem was then compared to respiration rate scaled up from horizontal planes at the thermocouple heights (40, 140, 240 and 340 cm) on a surface area and on a sapwood volume basis. Simulations were made for three distributions of living cells in the stems: one with a constant 5% fraction of living cells, disregarding depth into the stem; one with a living cell fraction decreasing linearly with depth into the stem; and one with an exponentially decreasing fraction of living cells. Mean temperature variation within the stem was 3.7 degrees C, and was more than 10 degrees C for 8% of the time. The maximum measured temperature difference was 21.5 degrees C. The corresponding mean variation in respiration was 35% and was more than 50% for 24% of the time. Scaling up respiration rates from different heights between 40 and 240 cm to the whole stem produced an error of 2 to 58% for the whole year. For a single sunny day, the error was between 2 and 72%. Thus, within-stem variations in temperature may significantly affect the accuracy of scaling respiration data obtained from small samples to whole trees. A careful choice of chamber position and basis for scaling is necessary to minimize errors from variation in temperature.

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

USGS Publications Warehouse

Moisen, Gretchen G.; Freeman, E.A.; Blackard, J.A.; Frescino, T.S.; Zimmermann, N.E.; Edwards, T.C.

2006-01-01

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's?? See5 and Cubist (for binary and continuous responses, respectively) are the tools of choice in many of these applications. These tools are widely used in large remote sensing applications, but are not easily interpretable, do not have ties with survey estimation methods, and use proprietary unpublished algorithms. Consequently, three alternative modelling techniques were compared for mapping presence and basal area of 13 species located in the mountain ranges of Utah, USA. The modelling techniques compared included the widely used See5/Cubist, generalized additive models (GAMs), and stochastic gradient boosting (SGB). Model performance was evaluated using independent test data sets. Evaluation criteria for mapping species presence included specificity, sensitivity, Kappa, and area under the curve (AUC). Evaluation criteria for the continuous basal area variables included correlation and relative mean squared error. For predicting species presence (setting thresholds to maximize Kappa), SGB had higher values for the majority of the species for specificity and Kappa, while GAMs had higher values for the majority of the species for sensitivity. In evaluating resultant AUC values, GAM and/or SGB models had significantly better results than the See5 models where significant differences could be detected between models. For nine out of 13 species, basal area prediction results for all modelling techniques were poor (correlations less than 0.5 and relative mean squared errors greater than 0.8), but SGB provided the most stable predictions in these instances. SGB and Cubist performed equally well for modelling basal area for three species with moderate prediction success, while all three modelling tools produced comparably good predictions (correlation of 0.68 and relative mean squared error of 0.56) for one species. ?? 2006 Elsevier B.V. All rights reserved.

Scoring-and-unfolding trimmed tree assembler: concepts, constructs and comparisons.

PubMed

Narzisi, Giuseppe; Mishra, Bud

2011-01-15

Mired by its connection to a well-known -complete combinatorial optimization problem-namely, the Shortest Common Superstring Problem (SCSP)-historically, the whole-genome sequence assembly (WGSA) problem has been assumed to be amenable only to greedy and heuristic methods. By placing efficiency as their first priority, these methods opted to rely only on local searches, and are thus inherently approximate, ambiguous or error prone, especially, for genomes with complex structures. Furthermore, since choice of the best heuristics depended critically on the properties of (e.g. errors in) the input data and the available long range information, these approaches hindered designing an error free WGSA pipeline. We dispense with the idea of limiting the solutions to just the approximated ones, and instead favor an approach that could potentially lead to an exhaustive (exponential-time) search of all possible layouts. Its computational complexity thus must be tamed through a constrained search (Branch-and-Bound) and quick identification and pruning of implausible overlays. For his purpose, such a method necessarily relies on a set of score functions (oracles) that can combine different structural properties (e.g. transitivity, coverage, physical maps, etc.). We give a detailed description of this novel assembly framework, referred to as Scoring-and-Unfolding Trimmed Tree Assembler (SUTTA), and present experimental results on several bacterial genomes using next-generation sequencing technology data. We also report experimental evidence that the assembly quality strongly depends on the choice of the minimum overlap parameter k. SUTTA's binaries are freely available to non-profit institutions for research and educational purposes at http://www.bioinformatics.nyu.edu.

Sentinel node status prediction by four statistical models: results from a large bi-institutional series (n = 1132).

PubMed

Mocellin, Simone; Thompson, John F; Pasquali, Sandro; Montesco, Maria C; Pilati, Pierluigi; Nitti, Donato; Saw, Robyn P; Scolyer, Richard A; Stretch, Jonathan R; Rossi, Carlo R

2009-12-01

To improve selection for sentinel node (SN) biopsy (SNB) in patients with cutaneous melanoma using statistical models predicting SN status. About 80% of patients currently undergoing SNB are node negative. In the absence of conclusive evidence of a SNBassociated survival benefit, these patients may be over-treated. Here, we tested the efficiency of 4 different models in predicting SN status. The clinicopathologic data (age, gender, tumor thickness, Clark level, regression, ulceration, histologic subtype, and mitotic index) of 1132 melanoma patients who had undergone SNB at institutions in Italy and Australia were analyzed. Logistic regression, classification tree, random forest, and support vector machine models were fitted to the data. The predictive models were built with the aim of maximizing the negative predictive value (NPV) and reducing the rate of SNB procedures though minimizing the error rate. After cross-validation logistic regression, classification tree, random forest, and support vector machine predictive models obtained clinically relevant NPV (93.6%, 94.0%, 97.1%, and 93.0%, respectively), SNB reduction (27.5%, 29.8%, 18.2%, and 30.1%, respectively), and error rates (1.8%, 1.8%, 0.5%, and 2.1%, respectively). Using commonly available clinicopathologic variables, predictive models can preoperatively identify a proportion of patients ( approximately 25%) who might be spared SNB, with an acceptable (1%-2%) error. If validated in large prospective series, these models might be implemented in the clinical setting for improved patient selection, which ultimately would lead to better quality of life for patients and optimization of resource allocation for the health care system.

Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery

USGS Publications Warehouse

Roach, Jennifer K.; Griffith, Brad; Verbyla, David

2012-01-01

Programs to monitor lake area change are becoming increasingly important in high latitude regions, and their development often requires evaluating tradeoffs among different approaches in terms of accuracy of measurement, consistency across multiple users over long time periods, and efficiency. We compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction). The accuracy of lake area and number estimates was evaluated relative to high-resolution aerial photography acquired within two days of satellite overpasses. The shortwave infrared band 5 was better at separating surface water from nonwater when used alone than when combined with other spectral bands. The simplest of the three methods, density slicing, performed best overall. The classification tree method resulted in the most omission errors (approx. 2x), feature extraction resulted in the most commission errors (approx. 4x), and density slicing had the least directional bias (approx. half of the lakes with overestimated area and half of the lakes with underestimated area). Feature extraction was the least consistent across training sets (i.e., large standard error among different training sets). Density slicing was the best of the three at classifying small lakes as evidenced by its lower optimal minimum lake size criterion of 5850 m2 compared with the other methods (8550 m2). Contrary to conventional wisdom, the use of additional spectral bands and a more sophisticated method not only required additional processing effort but also had a cost in terms of the accuracy and consistency of lake classifications.

Error properties of Argos satellite telemetry locations using least squares and Kalman filtering.

PubMed

Boyd, Janice D; Brightsmith, Donald J

2013-01-01

Study of animal movements is key for understanding their ecology and facilitating their conservation. The Argos satellite system is a valuable tool for tracking species which move long distances, inhabit remote areas, and are otherwise difficult to track with traditional VHF telemetry and are not suitable for GPS systems. Previous research has raised doubts about the magnitude of position errors quoted by the satellite service provider CLS. In addition, no peer-reviewed publications have evaluated the usefulness of the CLS supplied error ellipses nor the accuracy of the new Kalman filtering (KF) processing method. Using transmitters hung from towers and trees in southeastern Peru, we show the Argos error ellipses generally contain <25% of the true locations and therefore do not adequately describe the true location errors. We also find that KF processing does not significantly increase location accuracy. The errors for both LS and KF processing methods were found to be lognormally distributed, which has important repercussions for error calculation, statistical analysis, and data interpretation. In brief, "good" positions (location codes 3, 2, 1, A) are accurate to about 2 km, while 0 and B locations are accurate to about 5-10 km. However, due to the lognormal distribution of the errors, larger outliers are to be expected in all location codes and need to be accounted for in the user's data processing. We evaluate five different empirical error estimates and find that 68% lognormal error ellipses provided the most useful error estimates. Longitude errors are larger than latitude errors by a factor of 2 to 3, supporting the use of elliptical error ellipses. Numerous studies over the past 15 years have also found fault with the CLS-claimed error estimates yet CLS has failed to correct their misleading information. We hope this will be reversed in the near future.

MODIS Tree Cover Validation for the Circumpolar Taiga-Tundra Transition Zone

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Nelson, R.; Sun, G.; Margolis, H.; Kerber, A.; Ranson, K. J.

2009-01-01

A validation of the 2005 500m MODIS vegetation continuous fields (VCF) tree cover product in the circumpolar taiga-tundra ecotone was performed using high resolution Quickbird imagery. Assessing the VCF's performance near the northern limits of the boreal forest can help quantify the accuracy of the product within this vegetation transition area. The circumpolar region was divided into longitudinal zones and validation sites were selected in areas of varying tree cover where Quickbird imagery is available in Google Earth. Each site was linked to the corresponding VCF pixel and overlaid with a regular dot grid within the VCF pixel's boundary to estimate percent tree crown cover in the area. Percent tree crown cover was estimated using Quickbird imagery for 396 sites throughout the circumpolar region and related to the VCF's estimates of canopy cover for 2000-2005. Regression results of VCF inter-annual comparisons (2000-2005) and VCF-Quickbird image-interpreted estimates indicate that: (1) Pixel-level, inter-annual comparisons of VCF estimates of percent canopy cover were linearly related (mean R(sup 2) = 0.77) and exhibited an average root mean square error (RMSE) of 10.1 % and an average root mean square difference (RMSD) of 7.3%. (2) A comparison of image-interpreted percent tree crown cover estimates based on dot counts on Quickbird color images by two different interpreters were more variable (R(sup 2) = 0.73, RMSE = 14.8%, RMSD = 18.7%) than VCF inter-annual comparisons. (3) Across the circumpolar boreal region, 2005 VCF-Quickbird comparisons were linearly related, with an R(sup 2) = 0.57, a RMSE = 13.4% and a RMSD = 21.3%, with a tendency to over-estimate areas of low percent tree cover and anomalous VCF results in Scandinavia. The relationship of the VCF estimates and ground reference indicate to potential users that the VCF's tree cover values for individual pixels, particularly those below 20% tree cover, may not be precise enough to monitor 500m pixel-level tree cover in the taiga-tundra transition zone.

Estimation of 3D reconstruction errors in a stereo-vision system

NASA Astrophysics Data System (ADS)

Belhaoua, A.; Kohler, S.; Hirsch, E.

2009-06-01

The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.

Suppression of long-branch attraction artefacts in the animal phylogeny using a site-heterogeneous model

PubMed Central

Lartillot, Nicolas; Brinkmann, Henner; Philippe, Hervé

2007-01-01

Background Thanks to the large amount of signal contained in genome-wide sequence alignments, phylogenomic analyses are converging towards highly supported trees. However, high statistical support does not imply that the tree is accurate. Systematic errors, such as the Long Branch Attraction (LBA) artefact, can be misleading, in particular when the taxon sampling is poor, or the outgroup is distant. In an otherwise consistent probabilistic framework, systematic errors in genome-wide analyses can be traced back to model mis-specification problems, which suggests that better models of sequence evolution should be devised, that would be more robust to tree reconstruction artefacts, even under the most challenging conditions. Methods We focus on a well characterized LBA artefact analyzed in a previous phylogenomic study of the metazoan tree, in which two fast-evolving animal phyla, nematodes and platyhelminths, emerge either at the base of all other Bilateria, or within protostomes, depending on the outgroup. We use this artefactual result as a case study for comparing the robustness of two alternative models: a standard, site-homogeneous model, based on an empirical matrix of amino-acid replacement (WAG), and a site-heterogeneous mixture model (CAT). In parallel, we propose a posterior predictive test, allowing one to measure how well a model acknowledges sequence saturation. Results Adopting a Bayesian framework, we show that the LBA artefact observed under WAG disappears when the site-heterogeneous model CAT is used. Using cross-validation, we further demonstrate that CAT has a better statistical fit than WAG on this data set. Finally, using our statistical goodness-of-fit test, we show that CAT, but not WAG, correctly accounts for the overall level of saturation, and that this is due to a better estimation of site-specific amino-acid preferences. Conclusion The CAT model appears to be more robust than WAG against LBA artefacts, essentially because it correctly anticipates the high probability of convergences and reversions implied by the small effective size of the amino-acid alphabet at each site of the alignment. More generally, our results provide strong evidence that site-specificities in the substitution process need be accounted for in order to obtain more reliable phylogenetic trees. PMID:17288577

Branch-Based Model for the Diameters of the Pulmonary Airways: Accounting for Departures From Self-Consistency and Registration Errors

PubMed Central

Neradilek, Moni B.; Polissar, Nayak L.; Einstein, Daniel R.; Glenny, Robb W.; Minard, Kevin R.; Carson, James P.; Jiao, Xiangmin; Jacob, Richard E.; Cox, Timothy C.; Postlethwait, Edward M.; Corley, Richard A.

2017-01-01

We examine a previously published branch-based approach for modeling airway diameters that is predicated on the assumption of self-consistency across all levels of the tree. We mathematically formulate this assumption, propose a method to test it and develop a more general model to be used when the assumption is violated. We discuss the effect of measurement error on the estimated models and propose methods that take account of error. The methods are illustrated on data from MRI and CT images of silicone casts of two rats, two normal monkeys, and one ozone-exposed monkey. Our results showed substantial departures from self-consistency in all five subjects. When departures from self-consistency exist, we do not recommend using the self-consistency model, even as an approximation, as we have shown that it may likely lead to an incorrect representation of the diameter geometry. The new variance model can be used instead. Measurement error has an important impact on the estimated morphometry models and needs to be addressed in the analysis. PMID:22528468

Lightweight GPS-tags, one giant leap for wildlife tracking? An assessment approach.

PubMed

Recio, Mariano R; Mathieu, Renaud; Denys, Paul; Sirguey, Pascal; Seddon, Philip J

2011-01-01

Recent technological improvements have made possible the development of lightweight GPS-tagging devices suitable to track medium-to-small sized animals. However, current inferences concerning GPS performance are based on heavier designs, suitable only for large mammals. Lightweight GPS-units are deployed close to the ground, on species selecting micro-topographical features and with different behavioural patterns in comparison to larger mammal species. We assessed the effects of vegetation, topography, motion, and behaviour on the fix success rate for lightweight GPS-collar across a range of natural environments, and at the scale of perception of feral cats (Felis catus). Units deployed at 20 cm above the ground in sites of varied vegetation and topography showed that trees (native forest) and shrub cover had the largest influence on fix success rate (89% on average); whereas tree cover, sky availability, number of satellites and horizontal dilution of position (HDOP) were the main variables affecting location error (±39.5 m and ±27.6 m before and after filtering outlier fixes). Tests on HDOP or number of satellites-based screening methods to remove inaccurate locations achieved only a small reduction of error and discarded many accurate locations. Mobility tests were used to simulate cats' motion, revealing a slightly lower performance as compared to the fixed sites. GPS-collars deployed on 43 cats showed no difference in fix success rate by sex or season. Overall, fix success rate and location error values were within the range of previous tests carried out with collars designed for larger species. Lightweight GPS-tags are a suitable method to track medium to small size species, hence increasing the range of opportunities for spatial ecology research. However, the effects of vegetation, topography and behaviour on location error and fix success rate need to be evaluated prior to deployment, for the particular study species and their habitats.

Annual global tree cover estimated by fusing optical and SAR satellite observations

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2017-12-01

Tree cover defined structurally as the proportional, vertically projected area of vegetation (including leaves, stems, branches, etc.) of woody plants above a given height affects terrestrial energy and water exchanges, photosynthesis and transpiration, net primary production, and carbon and nutrient fluxes. Tree cover provides a measurable attribute upon which forest cover may be defined. Changes in tree cover over time can be used to monitor and retrieve site-specific histories of forest disturbance, succession, and degradation. Measurements of Earth's tree cover have been produced at regional, national, and global extents. However, most representations are static, and those for which multiple time periods have been produced are neither intended nor adequate for consistent, long-term monitoring. Moreover, although a substantial proportion of change has been shown to occur at resolutions below 250 m, existing long-term, Landsat-resolution datasets are either produced as static layers or with annual, five- or ten-year temporal resolution. We have developed an algorithms to retrieve seamless and consistent, sub-hectare resolution estimates of tree-canopy from optical and radar satellite data sources (e.g., Landsat, Sentinel-2, and ALOS-PALSAR). Our approach to estimation enables assimilation of multiple data sources and produces estimates of both cover and its uncertainty at the scale of pixels. It has generated the world's first Landsat-based percent tree cover dataset in 2013. Our previous algorithms are being adapted to produce prototype percent-tree and water-cover layers globally in 2000, 2005, and 2010—as well as annually over North and South America from 2010 to 2015—from passive-optical (Landsat and Sentinel-2) and SAR measurements. Generating a global, annual dataset is beyond the scope of this support; however, North and South America represent all of the world's major biomes and so offer the complete global range of environmental sources of error and uncertainty.

Development of a CFD Model Including Tree's Drag Parameterizations: Application to Pedestrian's Wind Comfort in an Urban Area

NASA Astrophysics Data System (ADS)

Kang, G.; Kim, J.

2017-12-01

This study investigated the tree's effect on wind comfort at pedestrian height in an urban area using a computational fluid dynamics (CFD) model. We implemented the tree's drag parameterization scheme to the CFD model and validated the simulated results against the wind-tunnel measurement data as well as LES data via several statistical methods. The CFD model underestimated (overestimated) the concentrations on the leeward (windward) walls inside the street canyon in the presence of trees, because the CFD model can't resolve the latticed cage and can't reflect the concentration increase and decrease caused by the latticed cage in the simulations. However, the scalar pollutants' dispersion simulated by the CFD model was quite similar to that in the wind-tunnel measurement in pattern and magnitude, on the whole. The CFD model overall satisfied the statistical validation indices (root normalized mean square error, geometric mean variance, correlation coefficient, and FAC2) but failed to satisfy the fractional bias and geometric mean bias due to the underestimation on the leeward wall and overestimation on the windward wall, showing that its performance was comparable to the LES's performance. We applied the CFD model to evaluation of the trees' effect on the pedestrian's wind-comfort in an urban area. To investigate sensory levels for human activities, the wind-comfort criteria based on Beaufort wind-force scales (BWSs) were used. In the tree-free scenario, BWS 4 and 5 (unpleasant condition for sitting long and sitting short, respectively) appeared in the narrow spaces between buildings, in the upwind side of buildings, and the unobstructed areas. In the tree scenario, BWSs decreased by 1 3 grade inside the campus of Pukyong National University located in the target area, which indicated that trees planted in the campus effectively improved pedestrian's wind comfort.

Tree-based modeling of complex interactions of phosphorus loadings and environmental factors.

PubMed

Grunwald, S; Daroub, S H; Lang, T A; Diaz, O A

2009-06-01

Phosphorus (P) enrichment has been observed in the historic oligotrophic Greater Everglades in Florida mainly due to P influx from upstream, agriculturally dominated, low relief drainage basins of the Everglades Agricultural Area (EAA). Our specific objectives were to: (1) investigate relationships between various environmental factors and P loads in 10 farm basins within the EAA, (2) identify those environmental factors that impart major effects on P loads using three different tree-based modeling approaches, and (3) evaluate predictive models to assess P loads. We assembled thirteen environmental variable sets for all 10 sub-basins characterizing water level management, cropping practices, soils, hydrology, and farm-specific properties. Drainage flow and P concentrations were measured at each sub-basin outlet from 1992-2002 and aggregated to derive monthly P loads. We used three different tree-based models including single regression trees (ST), committee trees in Bagging (CTb) and ARCing (CTa) modes and ten-fold cross-validation to test prediction performances. The monthly P loads (MPL) during the monitoring period showed a maximum of 2528 kg (mean: 103 kg) and maximum monthly unit area P loads (UAL) of 4.88 kg P ha(-1) (mean: 0.16 kg P ha(-1)). Our results suggest that hydrologic/water management properties are the major controlling variables to predict MPL and UAL in the EAA. Tree-based modeling was successful in identifying relationships between P loads and environmental predictor variables on 10 farms in the EAA indicated by high R(2) (>0.80) and low prediction errors. Committee trees in ARCing mode generated the best performing models to predict P loads and P loads per unit area. Tree-based models had the ability to analyze complex, non-linear relationships between P loads and multiple variables describing hydrologic/water management, cropping practices, soil and farm-specific properties within the EAA.

Using high-resolution topography and hyperspectral data to classify tree species at the San Joaquin Experimental Range

NASA Astrophysics Data System (ADS)

Dibb, S. D.; Ustin, S.; Grigsby, S.

2015-12-01

Air- and space-borne remote sensing instruments allow for rapid and precise study of the diversity of the Earth's ecosystems. After atmospheric correction and ground validation are performed, the gathered hyperspectral and topographic data can be assembled into a stack of layers for land cover classification. Data for this project were collected in multiple field campaigns, including the 2013 NSF NEON California campaign and 2015 NASA SARP campaign. Using hyperspectral and high resolution topography data, 25 discriminatory attributes were processed in Exelis' ENVI software and collected for use in a decision forest to classify the four major tree species (Blue Oak, Live Oak, California Buckeye, and Foothill Pine) at the San Joaquin Experimental Range near Fresno, CA. These attributes include 21 classic vegetation indices and a number of other spectral characteristics, such as color and albedo, and four topographic layers, including slope, aspect, elevation, and tree height. Additionally, a number of nearby terrain classes, including bare earth, asphalt, water, rock, shadow, structures, and grass were created. Fifty training pixels were used for each class. The training pixels for each tree species came from collected GPS points in the field. Ensemble bootstrap aggregation of decision trees was performed in MATLAB, and an arbitrary number of 500 trees were selected to be grown. The tree that produced the minimum out-of-bag classification error (4.65%) was selected to classify the entire scene. Classification results accurately distinguished between oak species, but was suboptimal in dense areas. The entire San Joaquin Experimental Range was mapped with an overall accuracy of 94.7% and a Kappa coefficient 0.94. Finally, the Commission and Omission percentage averages were 5.3% each. A highly accurate map of tree species at this scale supports studies on drought effects, disease, and species-specific growth traits.

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

NASA Astrophysics Data System (ADS)

Liu, Jingbin; Liang, Xinlian; Hyyppä, Juha; Yu, Xiaowei; Lehtomäki, Matti; Pyörälä, Jiri; Zhu, Lingli; Wang, Yunsheng; Chen, Ruizhi

2017-04-01

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.

2HOT: An Improved Parallel Hashed Oct-Tree N-Body Algorithm for Cosmological Simulation

DOE PAGES

Warren, Michael S.

2014-01-01

We report on improvements made over the past two decades to our adaptive treecode N-body method (HOT). A mathematical and computational approach to the cosmological N-body problem is described, with performance and scalability measured up to 256k (2 18 ) processors. We present error analysis and scientific application results from a series of more than ten 69 billion (4096 3 ) particle cosmological simulations, accounting for 4×10 20 floating point operations. These results include the first simulations using the new constraints on the standard model of cosmology from the Planck satellite. Our simulations set a new standard for accuracy andmore » scientific throughput, while meeting or exceeding the computational efficiency of the latest generation of hybrid TreePM N-body methods.« less

A novel method of fuzzy fault tree analysis combined with VB program to identify and assess the risk of coal dust explosions

PubMed Central

Li, Jia; Wang, Deming; Huang, Zonghou

2017-01-01

Coal dust explosions (CDE) are one of the main threats to the occupational safety of coal miners. Aiming to identify and assess the risk of CDE, this paper proposes a novel method of fuzzy fault tree analysis combined with the Visual Basic (VB) program. In this methodology, various potential causes of the CDE are identified and a CDE fault tree is constructed. To overcome drawbacks from the lack of exact probability data for the basic events, fuzzy set theory is employed and the probability data of each basic event is treated as intuitionistic trapezoidal fuzzy numbers. In addition, a new approach for calculating the weighting of each expert is also introduced in this paper to reduce the error during the expert elicitation process. Specifically, an in-depth quantitative analysis of the fuzzy fault tree, such as the importance measure of the basic events and the cut sets, and the CDE occurrence probability is given to assess the explosion risk and acquire more details of the CDE. The VB program is applied to simplify the analysis process. A case study and analysis is provided to illustrate the effectiveness of this proposed method, and some suggestions are given to take preventive measures in advance and avoid CDE accidents. PMID:28793348

The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference.

PubMed

Serang, Oliver

2014-01-01

Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called "causal independence"). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to O(k log(k)2) and the space to O(k log(k)) where k is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions.

The Probabilistic Convolution Tree: Efficient Exact Bayesian Inference for Faster LC-MS/MS Protein Inference

PubMed Central

Serang, Oliver

2014-01-01

Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called “causal independence”). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to and the space to where is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions. PMID:24626234

A novel method of fuzzy fault tree analysis combined with VB program to identify and assess the risk of coal dust explosions.

PubMed

Wang, Hetang; Li, Jia; Wang, Deming; Huang, Zonghou

2017-01-01

Coal dust explosions (CDE) are one of the main threats to the occupational safety of coal miners. Aiming to identify and assess the risk of CDE, this paper proposes a novel method of fuzzy fault tree analysis combined with the Visual Basic (VB) program. In this methodology, various potential causes of the CDE are identified and a CDE fault tree is constructed. To overcome drawbacks from the lack of exact probability data for the basic events, fuzzy set theory is employed and the probability data of each basic event is treated as intuitionistic trapezoidal fuzzy numbers. In addition, a new approach for calculating the weighting of each expert is also introduced in this paper to reduce the error during the expert elicitation process. Specifically, an in-depth quantitative analysis of the fuzzy fault tree, such as the importance measure of the basic events and the cut sets, and the CDE occurrence probability is given to assess the explosion risk and acquire more details of the CDE. The VB program is applied to simplify the analysis process. A case study and analysis is provided to illustrate the effectiveness of this proposed method, and some suggestions are given to take preventive measures in advance and avoid CDE accidents.

An evaluation of three growth and yield simulators for even-aged hardwood forests of the mid-Appalachian region

Treesearch

John R. Brooks; Gary W. Miller

2011-01-01

Data from even-aged hardwood stands in four ecoregions across the mid-Appalachian region were used to test projection accuracy for three available growth and yield software systems: SILVAH, the Forest Vegetation Simulator, and the Stand Damage Model. Average root mean squared error (RMSE) ranged from 20 to 140 percent of actual trees per acre while RMSE ranged from 2...

Small Area Variance Estimation for the Siuslaw NF in Oregon and Some Results

Treesearch

S. Lin; D. Boes; H.T. Schreuder

2006-01-01

The results of a small area prediction study for the Siuslaw National Forest in Oregon are presented. Predictions were made for total basal area, number of trees and mortality per ha on a 0.85 mile grid using data on a 1.7 mile grid and additional ancillary information from TM. A reliable method of estimating prediction errors for individual plot predictions called the...

Forest pests and home values: The importance of accuracy in damage assessment and geocoding of properties

Treesearch

Klaus Moeltner; Christine E. Blinn; Thomas P. Holmes

2017-01-01

We examine the impact of measurement errors in geocoding of property locations and in the assessment of Mountain Pine Beetle-induced tree damage within the proximity of a given residence on estimated losses in home values. For our sample of homes in the wildland-urban interface of the Colorado front range and using a novel matching estimator with Bayesian regression...

Toward Adversarial Online Learning and the Science of Deceptive Machines

DTIC Science & Technology

2015-11-14

noise . Adver- saries can take advantage of this inherent blind spot to avoid detection (mimicry). Adversarial label noise is the intentional switching...of classification labels leading to de- terministic noise , error that the model cannot capture due to its generalization bias. An experiment in user...potentially infinite and with imperfect information. We will combine Monte-Carlo tree search ( MCTS ) with rein- forcement learning because the manipulation

Prediction of healthy blood with data mining classification by using Decision Tree, Naive Baysian and SVM approaches

NASA Astrophysics Data System (ADS)

Khalilinezhad, Mahdieh; Minaei, Behrooz; Vernazza, Gianni; Dellepiane, Silvana

2015-03-01

Data mining (DM) is the process of discovery knowledge from large databases. Applications of data mining in Blood Transfusion Organizations could be useful for improving the performance of blood donation service. The aim of this research is the prediction of healthiness of blood donors in Blood Transfusion Organization (BTO). For this goal, three famous algorithms such as Decision Tree C4.5, Naïve Bayesian classifier, and Support Vector Machine have been chosen and applied to a real database made of 11006 donors. Seven fields such as sex, age, job, education, marital status, type of donor, results of blood tests (doctors' comments and lab results about healthy or unhealthy blood donors) have been selected as input to these algorithms. The results of the three algorithms have been compared and an error cost analysis has been performed. According to this research and the obtained results, the best algorithm with low error cost and high accuracy is SVM. This research helps BTO to realize a model from blood donors in each area in order to predict the healthy blood or unhealthy blood of donors. This research could be useful if used in parallel with laboratory tests to better separate unhealthy blood.

Satellite Telemetry and Long-Range Bat Movements

PubMed Central

Smith, Craig S.; Epstein, Jonathan H.; Breed, Andrew C.; Plowright, Raina K.; Olival, Kevin J.; de Jong, Carol; Daszak, Peter; Field, Hume E.

2011-01-01

Background Understanding the long-distance movement of bats has direct relevance to studies of population dynamics, ecology, disease emergence, and conservation. Methodology/Principal Findings We developed and trialed several collar and platform terminal transmitter (PTT) combinations on both free-living and captive fruit bats (Family Pteropodidae: Genus Pteropus). We examined transmitter weight, size, profile and comfort as key determinants of maximized transmitter activity. We then tested the importance of bat-related variables (species size/weight, roosting habitat and behavior) and environmental variables (day-length, rainfall pattern) in determining optimal collar/PTT configuration. We compared battery- and solar-powered PTT performance in various field situations, and found the latter more successful in maintaining voltage on species that roosted higher in the tree canopy, and at lower density, than those that roost more densely and lower in trees. Finally, we trialed transmitter accuracy, and found that actual distance errors and Argos location class error estimates were in broad agreement. Conclusions/Significance We conclude that no single collar or transmitter design is optimal for all bat species, and that species size/weight, species ecology and study objectives are key design considerations. Our study provides a strategy for collar and platform choice that will be applicable to a larger number of bat species as transmitter size and weight continue to decrease in the future. PMID:21358823

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

NASA Technical Reports Server (NTRS)

Otterstatter, Matthew R.

2005-01-01

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

M5 model tree based predictive modeling of road accidents on non-urban sections of highways in India.

PubMed

Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh

2016-11-01

This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multilocus inference of species trees and DNA barcoding.

PubMed

Mallo, Diego; Posada, David

2016-09-05

The unprecedented amount of data resulting from next-generation sequencing has opened a new era in phylogenetic estimation. Although large datasets should, in theory, increase phylogenetic resolution, massive, multilocus datasets have uncovered a great deal of phylogenetic incongruence among different genomic regions, due both to stochastic error and to the action of different evolutionary process such as incomplete lineage sorting, gene duplication and loss and horizontal gene transfer. This incongruence violates one of the fundamental assumptions of the DNA barcoding approach, which assumes that gene history and species history are identical. In this review, we explain some of the most important challenges we will have to face to reconstruct the history of species, and the advantages and disadvantages of different strategies for the phylogenetic analysis of multilocus data. In particular, we describe the evolutionary events that can generate species tree-gene tree discordance, compare the most popular methods for species tree reconstruction, highlight the challenges we need to face when using them and discuss their potential utility in barcoding. Current barcoding methods sacrifice a great amount of statistical power by only considering one locus, and a transition to multilocus barcodes would not only improve current barcoding methods, but also facilitate an eventual transition to species-tree-based barcoding strategies, which could better accommodate scenarios where the barcode gap is too small or inexistent.This article is part of the themed issue 'From DNA barcodes to biomes'. © 2016 The Authors.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

Fuzzy risk analysis of a modern γ-ray industrial irradiator.

PubMed

Castiglia, F; Giardina, M

2011-06-01

Fuzzy fault tree analyses were used to investigate accident scenarios that involve radiological exposure to operators working in industrial γ-ray irradiation facilities. The HEART method, a first generation human reliability analysis method, was used to evaluate the probability of adverse human error in these analyses. This technique was modified on the basis of fuzzy set theory to more directly take into account the uncertainties in the error-promoting factors on which the methodology is based. Moreover, with regard to some identified accident scenarios, fuzzy radiological exposure risk, expressed in terms of potential annual death, was evaluated. The calculated fuzzy risks for the examined plant were determined to be well below the reference risk suggested by International Commission on Radiological Protection.

A feasibility study on the measurement of tree trunks in forests using multi-scale vertical images

NASA Astrophysics Data System (ADS)

Berveglieri, A.; Oliveira, R. O.; Tommaselli, A. M. G.

2014-06-01

The determination of the Diameter at Breast Height (DBH) is an important variable that contributes to several studies on forest, e.g., environmental monitoring, tree growth, volume of wood, and biomass estimation. This paper presents a preliminary technique for the measurement of tree trunks using terrestrial images collected with a panoramic camera in nadir view. A multi-scale model is generated with these images. Homologue points on the trunk surface are measured over the images and their ground coordinates are determined by intersection of rays. The resulting XY coordinates of each trunk, defining an arc shape, can be used as observations in a circle fitting by least squares. Then, the DBH of each trunk is calculated using an estimated radius. Experiments were performed in two urban forest areas to assess the approach. In comparison with direct measurements on the trunks taken with a measuring tape, the discrepancies presented a Root Mean Square Error (RMSE) of 1.8 cm with a standard deviation of 0.7 cm. These results demonstrate compatibility with manual measurements and confirm the feasibility of the proposed technique.

The evolutionary rate dynamically tracks changes in HIV-1 epidemics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maljkovic-berry, Irina; Athreya, Gayathri; Daniels, Marcus

Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changedmore » over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.« less

Error analysis for creating 3D face templates based on cylindrical quad-tree structure

NASA Astrophysics Data System (ADS)

Gutfeter, Weronika

2015-09-01

Development of new biometric algorithms is parallel to advances in technology of sensing devices. Some of the limitations of the current face recognition systems may be eliminated by integrating 3D sensors into these systems. Depth sensing devices can capture a spatial structure of the face in addition to the texture and color. This kind of data is yet usually very voluminous and requires large amount of computer resources for being processed (face scans obtained with typical depth cameras contain more than 150 000 points per face). That is why defining efficient data structures for processing spatial images is crucial for further development of 3D face recognition methods. The concept described in this work fulfills the aforementioned demands. Modification of the quad-tree structure was chosen because it can be easily transformed into less dimensional data structures and maintains spatial relations between data points. We are able to interpret data stored in the tree as a pyramid of features which allow us to analyze face images using coarse-to-fine strategy, often exploited in biometric recognition systems.

Analysis of local scale tree-atmosphere interaction on pollutant concentration in idealized street canyons and application to a real urban junction

NASA Astrophysics Data System (ADS)

Buccolieri, Riccardo; Salim, Salim Mohamed; Leo, Laura Sandra; Di Sabatino, Silvana; Chan, Andrew; Ielpo, Pierina; de Gennaro, Gianluigi; Gromke, Christof

2011-03-01

This paper first discusses the aerodynamic effects of trees on local scale flow and pollutant concentration in idealized street canyon configurations by means of laboratory experiments and Computational Fluid Dynamics (CFD). These analyses are then used as a reference modelling study for the extension a the neighbourhood scale by investigating a real urban junction of a medium size city in southern Italy. A comparison with previous investigations shows that street-level concentrations crucially depend on the wind direction and street canyon aspect ratio W/H (with W and H the width and the height of buildings, respectively) rather than on tree crown porosity and stand density. It is usually assumed in the literature that larger concentrations are associated with perpendicular approaching wind. In this study, we demonstrate that while for tree-free street canyons under inclined wind directions the larger the aspect ratio the lower the street-level concentration, in presence of trees the expected reduction of street-level concentration with aspect ratio is less pronounced. Observations made for the idealized street canyons are re-interpreted in real case scenario focusing on the neighbourhood scale in proximity of a complex urban junction formed by street canyons of similar aspect ratios as those investigated in the laboratory. The aim is to show the combined influence of building morphology and vegetation on flow and dispersion and to assess the effect of vegetation on local concentration levels. To this aim, CFD simulations for two typical winter/spring days show that trees contribute to alter the local flow and act to trap pollutants. This preliminary study indicates that failing to account for the presence of vegetation, as typically practiced in most operational dispersion models, would result in non-negligible errors in the predictions.

Heat dissipation sensors of variable length for the measurement of sap flow in trees with deep sapwood.

PubMed

James, Shelley A; Clearwater, Michael J; Meinzer, Frederick C; Goldstein, Guillermo

2002-03-01

Robust thermal dissipation sensors of variable length (3 to 30 cm) were developed to overcome limitations to the measurement of radial profiles of sap flow in large-diameter tropical trees with deep sapwood. The effective measuring length of the custom-made sensors was reduced to 1 cm at the tip of a thermally nonconducting shaft, thereby minimizing the influence of nonuniform sap flux density profiles across the sapwood. Sap flow was measured at different depths and circumferential positions in the trunks of four trees at the Parque Natural Metropolitano canopy crane site, Panama City, Republic of Panama. Sap flow was detected to a depth of 24 cm in the trunks of a 1-m-diameter Anacardium excelsum (Bertero & Balb. ex Kunth) Skeels tree and a 0.65-m-diameter Ficus insipida Willd. tree, and to depths of 7 cm in a 0.34-m-diameter Cordia alliodora (Ruiz & Pav.) Cham. trunk, and 17 cm in a 0.47-m-diameter Schefflera morototoni (Aubl.) Maguire, Steyerm. & Frodin trunk. Sap flux density was maximal in the outermost 4 cm of sapwood and declined with increasing sapwood depth. Considerable variation in sap flux density profiles was observed both within and among the trees. In S. morototoni, radial variation in sap flux density was associated with radial variation in wood properties, particularly vessel lumen area and distribution. High variability in radial and circumferential sap flux density resulted in large errors when measurements of sap flow at a single depth, or a single radial profile, were used to estimate whole-plant water use. Diurnal water use ranged from 750 kg H2O day-1 for A. excelsum to 37 kg H2O day-1 for C. alliodora.

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

On the Reality of Illusory Conjunctions.

PubMed

Botella, Juan; Suero, Manuel; Durán, Juan I

2017-01-01

The reality of illusory conjunctions in perception has been sometimes questioned, arguing that they can be explained by other mechanisms. Most relevant experiments are based on migrations along the space dimension. But the low rate of illusory conjunctions along space can easily hide them among other types of errors. As migrations over time are a more frequent phenomenon, illusory conjunctions can be disentangled from other errors. We report an experiment in which series of colored letters were presented in several spatial locations, allowing for migrations over both space and time. The distribution of frequencies were fit by several multinomial tree models based on alternative hypothesis about illusory conjunctions and the potential sources of free-floating features. The best-fit model acknowledges that most illusory conjunctions are migrations in the time domain. Migrations in space are probably present, but the rate is very low. Other conjunction errors, as those produced by guessing or miscategorizations of the to-be-reported feature, are also present in the experiment. The main conclusion is that illusory conjunctions do exist.

Analysis of Compression Algorithm in Ground Collision Avoidance Systems (Auto-GCAS)

NASA Technical Reports Server (NTRS)

Schmalz, Tyler; Ryan, Jack

2011-01-01

Automatic Ground Collision Avoidance Systems (Auto-GCAS) utilizes Digital Terrain Elevation Data (DTED) stored onboard a plane to determine potential recovery maneuvers. Because of the current limitations of computer hardware on military airplanes such as the F-22 and F-35, the DTED must be compressed through a lossy technique called binary-tree tip-tilt. The purpose of this study is to determine the accuracy of the compressed data with respect to the original DTED. This study is mainly interested in the magnitude of the error between the two as well as the overall distribution of the errors throughout the DTED. By understanding how the errors of the compression technique are affected by various factors (topography, density of sampling points, sub-sampling techniques, etc.), modifications can be made to the compression technique resulting in better accuracy. This, in turn, would minimize unnecessary activation of A-GCAS during flight as well as maximizing its contribution to fighter safety.

FIA data and species diversity—successes and failures using multivariate analysis techniques, spatial lag and error models and hot-spot analysis

Treesearch

Andrew J. Hartsell

2015-01-01

This study will investigate how global and local predictors differ with varying spatial scale in relation to species evenness and richness in the gulf coastal plain. Particularly, all-live trees >= one-inch d.b.h. Forest Inventory and Analysis (FIA) data was used as the basis for the study. Watersheds are defined by the USGS 12 digit hydrologic units. The...

A new method to compare statistical tree growth curves: the PL-GMANOVA model and its application with dendrochronological data.

PubMed

Ricker, Martin; Peña Ramírez, Víctor M; von Rosen, Dietrich

2014-01-01

Growth curves are monotonically increasing functions that measure repeatedly the same subjects over time. The classical growth curve model in the statistical literature is the Generalized Multivariate Analysis of Variance (GMANOVA) model. In order to model the tree trunk radius (r) over time (t) of trees on different sites, GMANOVA is combined here with the adapted PL regression model Q = A · T+E, where for b ≠ 0 : Q = Ei[-b · r]-Ei[-b · r1] and for b = 0 : Q  = Ln[r/r1], A =  initial relative growth to be estimated, T = t-t1, and E is an error term for each tree and time point. Furthermore, Ei[-b · r]  = ∫(Exp[-b · r]/r)dr, b = -1/TPR, with TPR being the turning point radius in a sigmoid curve, and r1 at t1 is an estimated calibrating time-radius point. Advantages of the approach are that growth rates can be compared among growth curves with different turning point radiuses and different starting points, hidden outliers are easily detectable, the method is statistically robust, and heteroscedasticity of the residuals among time points is allowed. The model was implemented with dendrochronological data of 235 Pinus montezumae trees on ten Mexican volcano sites to calculate comparison intervals for the estimated initial relative growth A. One site (at the Popocatépetl volcano) stood out, with A being 3.9 times the value of the site with the slowest-growing trees. Calculating variance components for the initial relative growth, 34% of the growth variation was found among sites, 31% among trees, and 35% over time. Without the Popocatépetl site, the numbers changed to 7%, 42%, and 51%. Further explanation of differences in growth would need to focus on factors that vary within sites and over time.

Extensions and applications of ensemble-of-trees methods in machine learning

NASA Astrophysics Data System (ADS)

Bleich, Justin

Ensemble-of-trees algorithms have emerged to the forefront of machine learning due to their ability to generate high forecasting accuracy for a wide array of regression and classification problems. Classic ensemble methodologies such as random forests (RF) and stochastic gradient boosting (SGB) rely on algorithmic procedures to generate fits to data. In contrast, more recent ensemble techniques such as Bayesian Additive Regression Trees (BART) and Dynamic Trees (DT) focus on an underlying Bayesian probability model to generate the fits. These new probability model-based approaches show much promise versus their algorithmic counterparts, but also offer substantial room for improvement. The first part of this thesis focuses on methodological advances for ensemble-of-trees techniques with an emphasis on the more recent Bayesian approaches. In particular, we focus on extensions of BART in four distinct ways. First, we develop a more robust implementation of BART for both research and application. We then develop a principled approach to variable selection for BART as well as the ability to naturally incorporate prior information on important covariates into the algorithm. Next, we propose a method for handling missing data that relies on the recursive structure of decision trees and does not require imputation. Last, we relax the assumption of homoskedasticity in the BART model to allow for parametric modeling of heteroskedasticity. The second part of this thesis returns to the classic algorithmic approaches in the context of classification problems with asymmetric costs of forecasting errors. First we consider the performance of RF and SGB more broadly and demonstrate its superiority to logistic regression for applications in criminology with asymmetric costs. Next, we use RF to forecast unplanned hospital readmissions upon patient discharge with asymmetric costs taken into account. Finally, we explore the construction of stable decision trees for forecasts of violence during probation hearings in court systems.

Explicit area-based accuracy assessment for mangrove tree crown delineation using Geographic Object-Based Image Analysis (GEOBIA)

NASA Astrophysics Data System (ADS)

Kamal, Muhammad; Johansen, Kasper

2017-10-01

Effective mangrove management requires spatially explicit information of mangrove tree crown map as a basis for ecosystem diversity study and health assessment. Accuracy assessment is an integral part of any mapping activities to measure the effectiveness of the classification approach. In geographic object-based image analysis (GEOBIA) the assessment of the geometric accuracy (shape, symmetry and location) of the created image objects from image segmentation is required. In this study we used an explicit area-based accuracy assessment to measure the degree of similarity between the results of the classification and reference data from different aspects, including overall quality (OQ), user's accuracy (UA), producer's accuracy (PA) and overall accuracy (OA). We developed a rule set to delineate the mangrove tree crown using WorldView-2 pan-sharpened image. The reference map was obtained by visual delineation of the mangrove tree crowns boundaries form a very high-spatial resolution aerial photograph (7.5cm pixel size). Ten random points with a 10 m radius circular buffer were created to calculate the area-based accuracy assessment. The resulting circular polygons were used to clip both the classified image objects and reference map for area comparisons. In this case, the area-based accuracy assessment resulted 64% and 68% for the OQ and OA, respectively. The overall quality of the calculation results shows the class-related area accuracy; which is the area of correctly classified as tree crowns was 64% out of the total area of tree crowns. On the other hand, the overall accuracy of 68% was calculated as the percentage of all correctly classified classes (tree crowns and canopy gaps) in comparison to the total class area (an entire image). Overall, the area-based accuracy assessment was simple to implement and easy to interpret. It also shows explicitly the omission and commission error variations of object boundary delineation with colour coded polygons.

Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

NASA Astrophysics Data System (ADS)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

A Multi-Encoding Approach for LTL Symbolic Satisfiability Checking

NASA Technical Reports Server (NTRS)

Rozier, Kristin Y.; Vardi, Moshe Y.

2011-01-01

Formal behavioral specifications written early in the system-design process and communicated across all design phases have been shown to increase the efficiency, consistency, and quality of the system under development. To prevent introducing design or verification errors, it is crucial to test specifications for satisfiability. Our focus here is on specifications expressed in linear temporal logic (LTL). We introduce a novel encoding of symbolic transition-based Buchi automata and a novel, "sloppy," transition encoding, both of which result in improved scalability. We also define novel BDD variable orders based on tree decomposition of formula parse trees. We describe and extensively test a new multi-encoding approach utilizing these novel encoding techniques to create 30 encoding variations. We show that our novel encodings translate to significant, sometimes exponential, improvement over the current standard encoding for symbolic LTL satisfiability checking.

Logic flowgraph methodology - A tool for modeling embedded systems

NASA Technical Reports Server (NTRS)

Muthukumar, C. T.; Guarro, S. B.; Apostolakis, G. E.

1991-01-01

The logic flowgraph methodology (LFM), a method for modeling hardware in terms of its process parameters, has been extended to form an analytical tool for the analysis of integrated (hardware/software) embedded systems. In the software part of a given embedded system model, timing and the control flow among different software components are modeled by augmenting LFM with modified Petrinet structures. The objective of the use of such an augmented LFM model is to uncover possible errors and the potential for unanticipated software/hardware interactions. This is done by backtracking through the augmented LFM mode according to established procedures which allow the semiautomated construction of fault trees for any chosen state of the embedded system (top event). These fault trees, in turn, produce the possible combinations of lower-level states (events) that may lead to the top event.

Concurrent error detecting codes for arithmetic processors

NASA Technical Reports Server (NTRS)

Lim, R. S.

1979-01-01

A method of concurrent error detection for arithmetic processors is described. Low-cost residue codes with check-length l and checkbase m = 2 to the l power - 1 are described for checking arithmetic operations of addition, subtraction, multiplication, division complement, shift, and rotate. Of the three number representations, the signed-magnitude representation is preferred for residue checking. Two methods of residue generation are described: the standard method of using modulo m adders and the method of using a self-testing residue tree. A simple single-bit parity-check code is described for checking the logical operations of XOR, OR, and AND, and also the arithmetic operations of complement, shift, and rotate. For checking complement, shift, and rotate, the single-bit parity-check code is simpler to implement than the residue codes.

Growth process and model simulation of three different classes of Schima superba in a natural subtropical forest in China

NASA Astrophysics Data System (ADS)

Wei, Hui; Deng, Xiangwen; Ouyang, Shuai; Chen, Lijun; Chu, Yonghe

2017-01-01

Schima superba is an important fire-resistant, high-quality timber species in southern China. Growth in height, diameter at breast height (DBH), and volume of the three different classes (overtopped, average and dominant) of S. superba were examined in a natural subtropical forest. Four growth models (Richards, edited Weibull, Logistic and Gompertz) were selected to fit the growth of the three different classes of trees. The results showed that there was a fluctuation phenomenon in height and DBH current annual growth process of all three classes. Multiple intersections were found between current annual increment (CAI) and mean annual increment (MAI) curves of both height and DBH, but there was no intersection between volume CAI and MAI curves. All selected models could be used to fit the growth of the three classes of S. superba, with determinant coefficients above 0.9637. However, the edited Weibull model performed best with the highest R2 and the lowest root of mean square error (RMSE). S. superba is a fast-growing tree with a higher growth rate during youth. The height and DBH CAIs of overtopped, average and dominant trees reached growth peaks at ages 5-10, 10-15 and 15-20 years, respectively. According to model simulation, the volume CAIs of overtopped, average and dominant trees reached growth peaks at ages 17, 55 and 76 years, respectively. The biological rotation ages of the overtopped, average and dominant trees of S. superba were 29, 85 and 128 years, respectively.

Estimation of Sub Hourly Glacier Albedo Values Using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Moya Quiroga, Vladimir; Mano, Akira; Asaoka, Yoshihiro; Udo, Keiko; Kure, Shuichi; Mendoza, Javier

2013-04-01

Glaciers are the most important fresh water reservoirs storing about 67% of total fresh water. Unfortunately, they are retreating and some small glaciers have already disappeared. Thus, snow glacier melt (SGM) estimation plays an important role in water resources management. Whether SGM is estimated by complete energy balance or a simplified method, albedo is an important data present in most of the methods. However, this is a variable value depending on the ground surface and local conditions. The present research presents a new approach for estimating sub hourly albedo values using different artificial intelligence techniques such as artificial neural networks and decision trees along with measured and easy to obtain data. . The models were developed using measured data from the Zongo-Ore station located in the Bolivian tropical glacier Zongo (68°10' W, 16°15' S). This station automatically records every 30 minutes several meteorological parameters such as incoming short wave radiation, outgoing short wave radiation, temperature or relative humidity. The ANN model used was the Multi Layer Perceptron, while the decision tree used was the M5 model. Both models were trained using the WEKA software and validated using the cross validation method. After analysing the model performances, it was concluded that the decision tree models have a better performance. The model with the best performance was then validated with measured data from the Equatorian tropical glacier Antizana (78°09'W, 0°28'S). The model predicts the sub hourly albedo with an overall mean absolute error of 0.103. The highest errors occur for albedo measured values higher than 0.9. Considering that this is an extreme value coincident with low measured values of incoming short wave radiation, it is reasonable to assume that such values include errors due to censored data. Assuming a maximum albedo of 0.9 improved the accuracy of the model reducing the MAE to less than 0.1. Considering that the model was successfully verified both in the inner tropics and the outer tropics, this model is a valuable contribution that may be used to project future scenarios in tropical glaciers. This research is developed within the GRANDE project (Glacier Retreat impact Assessment and National policy Development), financed by SATREPS from JST-JICA.

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic

PubMed Central

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals. PMID:27413364

Identification of Amazonian trees with DNA barcodes.

PubMed

Gonzalez, Mailyn Adriana; Baraloto, Christopher; Engel, Julien; Mori, Scott A; Pétronelli, Pascal; Riéra, Bernard; Roger, Aurélien; Thébaud, Christophe; Chave, Jérôme

2009-10-16

Large-scale plant diversity inventories are critical to develop informed conservation strategies. However, the workload required for classic taxonomic surveys remains high and is particularly problematic for megadiverse tropical forests. Based on a comprehensive census of all trees in two hectares of a tropical forest in French Guiana, we examined whether plant DNA barcoding could contribute to increasing the quality and the pace of tropical plant biodiversity surveys. Of the eight plant DNA markers we tested (rbcLa, rpoC1, rpoB, matK, ycf5, trnL, psbA-trnH, ITS), matK and ITS had a low rate of sequencing success. More critically, none of the plastid markers achieved a rate of correct plant identification greater than 70%, either alone or combined. The performance of all barcoding markers was noticeably low in few species-rich clades, such as the Laureae, and the Sapotaceae. A field test of the approach enabled us to detect 130 molecular operational taxonomic units in a sample of 252 juvenile trees. Including molecular markers increased the identification rate of juveniles from 72% (morphology alone) to 96% (morphology and molecular) of the individuals assigned to a known tree taxon. We conclude that while DNA barcoding is an invaluable tool for detecting errors in identifications and for identifying plants at juvenile stages, its limited ability to identify collections will constrain the practical implementation of DNA-based tropical plant biodiversity programs.

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic.

PubMed

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals.

A Robust Semi-Parametric Test for Detecting Trait-Dependent Diversification.

PubMed

Rabosky, Daniel L; Huang, Huateng

2016-03-01

Rates of species diversification vary widely across the tree of life and there is considerable interest in identifying organismal traits that correlate with rates of speciation and extinction. However, it has been challenging to develop methodological frameworks for testing hypotheses about trait-dependent diversification that are robust to phylogenetic pseudoreplication and to directionally biased rates of character change. We describe a semi-parametric test for trait-dependent diversification that explicitly requires replicated associations between character states and diversification rates to detect effects. To use the method, diversification rates are reconstructed across a phylogenetic tree with no consideration of character states. A test statistic is then computed to measure the association between species-level traits and the corresponding diversification rate estimates at the tips of the tree. The empirical value of the test statistic is compared to a null distribution that is generated by structured permutations of evolutionary rates across the phylogeny. The test is applicable to binary discrete characters as well as continuous-valued traits and can accommodate extremely sparse sampling of character states at the tips of the tree. We apply the test to several empirical data sets and demonstrate that the method has acceptable Type I error rates. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes.

PubMed

Moustakas, Aristides; Evans, Matthew R

2015-02-28

Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose. We investigate the survival rates of ten tree species in a dataset designed to monitor growth rates. As some individuals were not included in the census at some time points we use capture-mark-recapture methods both to allow us to account for missing individuals, and to estimate relocation probabilities. Growth rates, size, and light availability were included as covariates in the model predicting survival rates. The study demonstrates that tree mortality is best described as constant between years and size-dependent at early life stages and size independent at later life stages for most species of UK hardwood. We have demonstrated that even with a twenty-year dataset it is possible to discern variability both between individuals and between species. Our work illustrates the potential utility of the method applied here for calculating plant population dynamics parameters in time replicated datasets with small sample sizes and missing individuals without any loss of sample size, and including explanatory covariates.

[Compatible biomass models of natural spruce (Picea asperata)].

PubMed

Wang, Jin Chi; Deng, Hua Feng; Huang, Guo Sheng; Wang, Xue Jun; Zhang, Lu

2017-10-01

By using nonlinear measurement error method, the compatible tree volume and above ground biomass equations were established based on the volume and biomass data of 150 sampling trees of natural spruce (Picea asperata). Two approaches, controlling directly under total aboveground biomass and controlling jointly from level to level, were used to design the compatible system for the total aboveground biomass and the biomass of four components (stem, bark, branch and foliage), and the total ground biomass could be estimated independently or estimated simultaneously in the system. The results showed that the R 2 of the one variable and bivariate compatible tree volume and aboveground biomass equations were all above 0.85, and the maximum value reached 0.99. The prediction effect of the volume equations could be improved significantly when tree height was included as predictor, while it was not significant in biomass estimation. For the compatible biomass systems, the one variable model based on controlling jointly from level to level was better than the model using controlling directly under total above ground biomass, but the bivariate models of the two methods were similar. Comparing the imitative effects of the one variable and bivariate compatible biomass models, the results showed that the increase of explainable variables could significantly improve the fitness of branch and foliage biomass, but had little effect on other components. Besides, there was almost no difference between the two methods of estimation based on the comparison.

Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

NASA Astrophysics Data System (ADS)

Gao, Jing; Burt, James E.

2017-12-01

This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States

USGS Publications Warehouse

Gesch, Dean B.; Oimoen, Michael J.; Zhang, Zheng; Meyer, David J.; Danielson, Jeffrey J.

2012-01-01

The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of -0.20 meters is a significant improvement over the GDEM v1 mean error of -3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.

Apoplastic water fraction and rehydration techniques introduce significant errors in measurements of relative water content and osmotic potential in plant leaves.

PubMed

Arndt, Stefan K; Irawan, Andi; Sanders, Gregor J

2015-12-01

Relative water content (RWC) and the osmotic potential (π) of plant leaves are important plant traits that can be used to assess drought tolerance or adaptation of plants. We estimated the magnitude of errors that are introduced by dilution of π from apoplastic water in osmometry methods and the errors that occur during rehydration of leaves for RWC and π in 14 different plant species from trees, grasses and herbs. Our data indicate that rehydration technique and length of rehydration can introduce significant errors in both RWC and π. Leaves from all species were fully turgid after 1-3 h of rehydration and increasing the rehydration time resulted in a significant underprediction of RWC. Standing rehydration via the petiole introduced the least errors while rehydration via floating disks and submerging leaves for rehydration led to a greater underprediction of RWC. The same effect was also observed for π. The π values following standing rehydration could be corrected by applying a dilution factor from apoplastic water dilution using an osmometric method but not by using apoplastic water fraction (AWF) from pressure volume (PV) curves. The apoplastic water dilution error was between 5 and 18%, while the two other rehydration methods introduced much greater errors. We recommend the use of the standing rehydration method because (1) the correct rehydration time can be evaluated by measuring water potential, (2) overhydration effects were smallest, and (3) π can be accurately corrected by using osmometric methods to estimate apoplastic water dilution. © 2015 Scandinavian Plant Physiology Society.

Tree-ring reconstructions of hydroclimatic variability in the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Hidalgo-Leon, Hugo

Three major sources of improvements in tree-ring analysis and reconstruction of hydroclimatic variables are presented for the Upper Colorado River Basin (UCRB) in the southwestern U.S.: (1) Cross validation statistics are used for identifying optimal reconstruction models based on different alternatives of PCA-based regression. Results showed that a physically-consistent parsimonious model with low mean square error can be obtained by using strict rules for principal component selection and cross validation statistics. The improved methods were used to produce a ˜500 year high-resolution reconstruction of the UCRB's streamflow and compared with results of a previous reconstruction based on traditional procedures. (2) Tree-species' type was found to be a factor for determining chronology selection from dendrohydroclimatic models. The relative sensitivity of six tree species (Pinus edulis, Pseudotsuga menziesii, Pinus ponderosa, Pinus flexilis, Pinus aristata, and Picea engelmanni) to hydroclimatic extreme variations was determined using contingency table scores of tree-ring growth (at different lags) against hydroclimatic observations. Pinus edulis and Pseudotsuga menziesii were found to be the species most sensitive to low water. Results showed that tree-rings are biased towards greater sensitivity to hot-dry conditions and less responsive to cool-moist conditions. Resulted also showed higher streamflow response scores compared to precipitation implying a good integration and persistence representation of the basin through normal hydrological processes. (3) Previous reconstructions on the basin used data extending only up to 1963. This is an important limitation since hydroclimatic records from 1963 to the present show significantly different variation than prior to 1963. The changes are caused by variations in the strength of forcing mechanisms from the Pacific Ocean. A comparative analysis of the influence of North Pacific variation and El Nino/Southern Oscillation (ENSO) showed that the responses of Tropical and North Pacific forcing in UCRB's hydroclimate are different for annual precipitation and total streamflow and that these relationships have changed at decadal time scales. Furthermore, most of the few tree-rings available up to 1985, present the same shifts as the hydroclimatic variables studied. To capture the full range of variability observed in instrumental data is necessary to collect new tree-ring samples.

Effects of excluding goat herbivory on Acacia tortilis woodland around pastoralist settlements in northwest Kenya

NASA Astrophysics Data System (ADS)

Oba, Gufu

1998-08-01

Browsing by goats is considered to cause poor tree regeneration and reduced tree growth around settlements throughout the arid zones of sub-Saharan Africa. This study investigated whether excluding goats from Acacia tortilis woodlands increased tree regeneration, current season's shoot growth rates and browse production over a period of 52 months between 1986 and 1990. The study also investigated the effects of climatic variability on tree growth and browse production. Excluding goat herbivory provided no advantage over continuous browsing for juvenile A. tortilis. Trees on the unbrowsed and on browsed transects increased by 22.2 (standard error [SE] ± 0.53) cm·yr -1 and 25.0 (SE ± 0.58) cm·yr -1, respectively. Fewer but longer shoots were produced by trees on the unbrowsed transects, while trees on the browsed transects invested more in shorter shoots. Net total browse production was lower on unbrowsed (1.73 [standard deviation (SD) ± 4.3] t·ha -1·yr -1) than on the browsed (3.03 [SD ± 3.6] t·ha -1 ·yr -1) transects. Biomass production on unbrowsed and browsed transects was closely correlated with rainfall and presumably soil moisture during wet seasons. Relative growth rates (RGR) of current season's shoots in the two treatments did not differ, implying goat herbivory at moderate stocking density (i.e. 13.0 tropical livestock units [TLU]·km -2) stimulated shoot growth. RGR remained positive except on the browsed transects during 1990, a dry year. Goat browsing pressure was moderate. Total biomass loss on unbrowsed transects was 15.5 %·yr -1 compared with 27.7 %·yr -1 on the browsed transects. These findings do not support the notion that goats always destroy young trees around settlements. Goat herbivory at moderate intensity stimulated shoot productivity. However, the results should not be used to generalize all conditions throughout sub-Saharan Africa, let alone the arid zones of northern Kenya. Rather, there is a need to emphasize individual case studies that ultimately can be used for managing degraded woodlands near pastoralist settlements.

Application of Dual-Tree Complex Wavelet Transforms to Burst Detection and RF Fingerprint Classification

DTIC Science & Technology

2009-09-01

prior to Traditional VT pro- iv cessing. This proves to be effective and provides more robust burst detection for −3 ≤ SNR ≤ 10 dB. Performance of a...TD and WD Dimensionality . . . . . 74 4.4 Performance Sensitivity Analysis . . . . . . . . . . . . . 77 4.4.1 Effect of Burst Location Error...78 4.4.2 Effect of Dissimilar Signal SNRs . . . . . . . . . 84 4.4.3 Effect of Dissimilar Signal Types . . . . . . . . 86 V. Conclusion

Effective one-dimensional images of arterial trees in the cardiovascular system

NASA Astrophysics Data System (ADS)

Kozlov, V. A.; Nazarov, S. A.

2017-03-01

An exponential smallness of the errors in the one-dimensional model of the Stokes flow in a branching thin vessel with rigid walls is achieved by introducing effective lengths of the one-dimensional image of internodal fragments of vessels. Such lengths are eluated through the pressure-drop matrix at each node describing the boundary-layer phenomenon. The medical interpretation and the accessible generalizations of the result, in particular, for the Navier-Stokes equations are presented.

A Scale-Independent Clustering Method with Automatic Variable Selection Based on Trees

DTIC Science & Technology

2014-03-01

veterans fought. They then clustered the data and were able to identify three distinct post-combat syndromes associated with different eras...granting some legitimacy to proposed medical conditions such as the Gulf War Syndrome (Jones et al., 2002, pp. 321–324) D. MEASURING DISTANCES BETWEEN...chosen so as to minimize the sum of squared errors of the response across the two regions (Equation 2.1). The average y for the left and right child

A low-cost GPS/INS integrated vehicle heading angle measurement system

NASA Astrophysics Data System (ADS)

Wu, Ye; Gao, Tongyue; Ding, Yi

2018-04-01

GPS can provide continuous heading information, but the accuracy is easily affected by the velocity and shelter from buildings or trees. For vehicle systems, we propose a low-cost heading angle update algorithm. Based on the GPS/INS integrated navigation kalman filter, we add the GPS heading angle to the measurement vector, and establish its error model. The experiment results show that this algorithm can effectively improve the accuracy of GPS heading angle.

Phylogenomics of Lophotrochozoa with Consideration of Systematic Error.

PubMed

Kocot, Kevin M; Struck, Torsten H; Merkel, Julia; Waits, Damien S; Todt, Christiane; Brannock, Pamela M; Weese, David A; Cannon, Johanna T; Moroz, Leonid L; Lieb, Bernhard; Halanych, Kenneth M

2017-03-01

Phylogenomic studies have improved understanding of deep metazoan phylogeny and show promise for resolving incongruences among analyses based on limited numbers of loci. One region of the animal tree that has been especially difficult to resolve, even with phylogenomic approaches, is relationships within Lophotrochozoa (the animal clade that includes molluscs, annelids, and flatworms among others). Lack of resolution in phylogenomic analyses could be due to insufficient phylogenetic signal, limitations in taxon and/or gene sampling, or systematic error. Here, we investigated why lophotrochozoan phylogeny has been such a difficult question to answer by identifying and reducing sources of systematic error. We supplemented existing data with 32 new transcriptomes spanning the diversity of Lophotrochozoa and constructed a new set of Lophotrochozoa-specific core orthologs. Of these, 638 orthologous groups (OGs) passed strict screening for paralogy using a tree-based approach. In order to reduce possible sources of systematic error, we calculated branch-length heterogeneity, evolutionary rate, percent missing data, compositional bias, and saturation for each OG and analyzed increasingly stricter subsets of only the most stringent (best) OGs for these five variables. Principal component analysis of the values for each factor examined for each OG revealed that compositional heterogeneity and average patristic distance contributed most to the variance observed along the first principal component while branch-length heterogeneity and, to a lesser extent, saturation contributed most to the variance observed along the second. Missing data did not strongly contribute to either. Additional sensitivity analyses examined effects of removing taxa with heterogeneous branch lengths, large amounts of missing data, and compositional heterogeneity. Although our analyses do not unambiguously resolve lophotrochozoan phylogeny, we advance the field by reducing the list of viable hypotheses. Moreover, our systematic approach for dissection of phylogenomic data can be applied to explore sources of incongruence and poor support in any phylogenomic data set. [Annelida; Brachiopoda; Bryozoa; Entoprocta; Mollusca; Nemertea; Phoronida; Platyzoa; Polyzoa; Spiralia; Trochozoa.]. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers.

PubMed

Luo, Xiongbiao

2014-06-01

Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model was designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0-10 min(-1). The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. An electromagnetically navigated bronchoscopy system was constructed with accurate registration of an electromagnetic tracker and the CT volume on the basis of an improved marker-free registration approach that uses the bronchial centerlines and bronchoscope tip center information. The fiducial and target registration errors of our electromagnetic navigation system were about 6.6 and 4.5 mm in dynamic bronchial phantom validation.

A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Xiongbiao, E-mail: xiongbiao.luo@gmail.com

2014-06-15

Purpose: Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. Methods: The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model wasmore » designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. Results: The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0–10 min{sup −1}. The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. Conclusions: An electromagnetically navigated bronchoscopy system was constructed with accurate registration of an electromagnetic tracker and the CT volume on the basis of an improved marker-free registration approach that uses the bronchial centerlines and bronchoscope tip center information. The fiducial and target registration errors of our electromagnetic navigation system were about 6.6 and 4.5 mm in dynamic bronchial phantom validation.« less

Chemodiversity of a Scots pine stand and implications for terpene air concentrations

NASA Astrophysics Data System (ADS)

Bäck, J.; Aalto, J.; Henriksson, M.; Hakola, H.; He, Q.; Boy, M.

2012-02-01

Atmospheric chemistry in background areas is strongly influenced by natural vegetation. Coniferous forests are known to produce large quantities of volatile vapors, especially terpenes. These compounds are reactive in the atmosphere, and contribute to the formation and growth of atmospheric new particles. Our aim was to analyze the variability of mono- and sesquiterpene emissions between Scots pine trees, in order to clarify the potential errors caused by using emission data obtained from only a few trees in atmospheric chemistry models. We also aimed at testing if stand history and seed origin has an influence on the chemotypic diversity. The inherited, chemotypic variability in mono- and sesquiterpene emission was studied in a seemingly homogeneous 48 yr-old stand in Southern Finland, where two areas differing in their stand regeneration history could be distinguished. Sampling was conducted in August 2009. Terpene concentrations in the air had been measured at the same site for seven years prior to branch sampling for chemotypes. Two main compounds, α-pinene and Δ3-carene formed together 40-97% of the monoterpene proportions in both the branch emissions and in the air concentrations. The data showed a bimodal distribution in emission composition, in particular in Δ3-carene emission within the studied population. 10% of the trees emitted mainly α-pinene and no Δ3-carene at all, whereas 20% of the trees where characterized as high Δ3-carene emitters (Δ3-carene forming >80% of total emitted monoterpene spectrum). An intermediate group of trees emitted equal amounts of both α-pinene and Δ3-carene. The emission pattern of trees at the area established using seeding as the artificial regeneration method differed from the naturally regenerated or planted trees, being mainly high Δ3-carene emitters. Some differences were also seen in e.g. camphene and limonene emissions between chemotypes, but sesquiterpene emissions did not differ significantly between trees. The atmospheric concentrations at the site were found to reflect the species and/or chemodiversity rather than the emissions measured from any single tree, and were strongly dominated by α-pinene. We also tested the effect of chemodiversity on modeled monoterpene concentrations at the site and found out that since it significantly influences the distributions and hence the chemical reactions in the atmosphere, it should be taken into account in atmospheric modeling.

Chemodiversity in terpene emissions at a boreal Scots pine stand

NASA Astrophysics Data System (ADS)

Bäck, J.; Aalto, J.; Henriksson, M.; Hakola, H.; He, Q.; Boy, M.

2011-10-01

Atmospheric chemistry in background areas is strongly influenced by natural vegetation. Coniferous forests are known to produce large quantities of volatile vapors, especially terpenes to the surrounding air. These compounds are reactive in the atmosphere, and contribute to the formation and growth of atmospheric new particles. Our aim was to analyze the variability of mono- and sesquiterpene emissions between Scots pine trees, in order to clarify the potential errors caused by using emission data obtained from only a few trees in atmospheric chemistry models. We also aimed at testing if stand history and seed origin has an influence on the chemotypic diversity. The inherited, chemotypic variability in mono- and sesquiterpene emission was studied in a seemingly homogeneous 47-yr-old stand in Southern Finland, where two areas differing in their stand regeneration history could be distinguished. Sampling was conducted in August 2009. Terpene concentrations in the air had been measured at the same site for seven years prior to branch sampling for chemotypes. Two main compounds, α-pinene and Δ3-carene formed together 40-97% of the monoterpene proportions in both the branch emissions and in the air concentrations. The data showed a bimodal distribution in emission composition, in particular in Δ3-carene emission within the studied population. 10% of the trees emitted mainly α-pinene and no Δ3-carene at all, whereas 20% of the trees where characterized as high Δ3-carene emitters (Δ3-carene forming >80% of total emitted monoterpene spectrum). An intermediate group of trees emitted equal amounts of both α-pinene and Δ3-carene. The emission pattern of trees at the area established using seeding as the artificial regeneration method differed from the naturally regenerated or planted trees, being mainly high Δ3-carene emitters. Some differences were also seen in e.g. camphene and limonene emissions between chemotypes, but sesquiterpene emissions did not differ significantly between trees. The atmospheric concentrations at the site were found to reflect the species and/or chemodiversity rather than the emissions measured from any single tree, and were strongly dominated by α-pinene. We also tested the effect of chemodiversity on modeled monoterpene concentrations at the site and found out that since it significantly influences the distributions and hence the chemical reactions in the atmosphere, it should be taken into account in atmospheric modeling.

Proposed Hydrodynamic Model Increases the Ability of Land-Surface Models to Capture Intra-Daily Dynamics of Transpiration and Canopy Structure Effects

NASA Astrophysics Data System (ADS)

Matheny, A. M.; Bohrer, G.; Mirfenderesgi, G.; Schafer, K. V.; Ivanov, V. Y.

2014-12-01

Hydraulic limitations are known to control transpiration in forest ecosystems when the soil is drying or when the vapor pressure deficit between the air and stomata is very large, but they can also impact stomatal apertures under conditions of adequate soil moisture and lower evaporative demand. We use the NACP dataset of latent heat flux measurements and model observations for multiple sites and models to demonstrate models' difficulties in capturing intra-daily hysteresis. We hypothesize that this is a result of un-resolved afternoon stomata closure due to hydrodynamic stresses. The current formulations for stomatal conductance and the empirical coupling between stomatal conductance and soil moisture used by these models does not resolve the hydrodynamic process of water movement from the soil to the leaves. This approach does not take advantage of advances in our understanding of water flow and storage in the trees, or of tree and canopy structure. A more thorough representation of the tree-hydrodynamic processes could potentially remedy this significant source of model error. In a forest plot at the University of Michigan Biological Station, we use measurements of sap flux and leaf water potential to demonstrate that trees of similar type - late successional deciduous trees - have very different hydrodynamic strategies that lead to differences in their temporal patterns of stomatal conductance and thus hysteretic cycles of transpiration. These differences will lead to large differences in conductance and water use based on the species composition of the forest. We also demonstrate that the size and shape of the tree branching system leads to differences in extent of hydrodynamic stress, which may change the forest respiration patterns as the forest grows and ages. We propose a framework to resolve tree hydrodynamics in global and regional models based on the Finite-Elements Tree-Crown Hydrodynamics model (FETCH) -a hydrodynamic model that can resolve the fast dynamics of stomatal conductance. FETCH simulates water flow through a tree as a system of porous media conduits and calculates the amount of hydraulic limitation to stomatal conductance, given the atmospheric and biological variables from the global model, and could replace the current empirical formulation for stomatal adjustment based on soil moisture.

Individual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon

NASA Astrophysics Data System (ADS)

Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.

2017-12-01

The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.

A method of alignment masking for refining the phylogenetic signal of multiple sequence alignments.

PubMed

Rajan, Vaibhav

2013-03-01

Inaccurate inference of positional homologies in multiple sequence alignments and systematic errors introduced by alignment heuristics obfuscate phylogenetic inference. Alignment masking, the elimination of phylogenetically uninformative or misleading sites from an alignment before phylogenetic analysis, is a common practice in phylogenetic analysis. Although masking is often done manually, automated methods are necessary to handle the much larger data sets being prepared today. In this study, we introduce the concept of subsplits and demonstrate their use in extracting phylogenetic signal from alignments. We design a clustering approach for alignment masking where each cluster contains similar columns-similarity being defined on the basis of compatible subsplits; our approach then identifies noisy clusters and eliminates them. Trees inferred from the columns in the retained clusters are found to be topologically closer to the reference trees. We test our method on numerous standard benchmarks (both synthetic and biological data sets) and compare its performance with other methods of alignment masking. We find that our method can eliminate sites more accurately than other methods, particularly on divergent data, and can improve the topologies of the inferred trees in likelihood-based analyses. Software available upon request from the author.

Early detection of emerald ash borer infestation using multisourced data: a case study in the town of Oakville, Ontario, Canada

NASA Astrophysics Data System (ADS)

Zhang, Kongwen; Hu, Baoxin; Robinson, Justin

2014-01-01

The emerald ash borer (EAB) poses a significant economic and environmental threat to ash trees in southern Ontario, Canada, and the northern states of the USA. It is critical that effective technologies are urgently developed to detect, monitor, and control the spread of EAB. This paper presents a methodology using multisourced data to predict potential infestations of EAB in the town of Oakville, Ontario, Canada. The information combined in this study includes remotely sensed data, such as high spatial resolution aerial imagery, commercial ground and airborne hyperspectral data, and Google Earth imagery, in addition to nonremotely sensed data, such as archived paper maps and documents. This wide range of data provides extensive information that can be used for early detection of EAB, yet their effective employment and use remain a significant challenge. A prediction function was developed to estimate the EAB infestation states of individual ash trees using three major attributes: leaf chlorophyll content, tree crown spatial pattern, and prior knowledge. Comparison between these predicted values and a ground-based survey demonstrated an overall accuracy of 62.5%, with 22.5% omission and 18.5% commission errors.

LEGO-MM: LEarning structured model by probabilistic loGic Ontology tree for MultiMedia.

PubMed

Tang, Jinhui; Chang, Shiyu; Qi, Guo-Jun; Tian, Qi; Rui, Yong; Huang, Thomas S

2016-09-22

Recent advances in Multimedia ontology have resulted in a number of concept models, e.g., LSCOM and Mediamill 101, which are accessible and public to other researchers. However, most current research effort still focuses on building new concepts from scratch, very few work explores the appropriate method to construct new concepts upon the existing models already in the warehouse. To address this issue, we propose a new framework in this paper, termed LEGO1-MM, which can seamlessly integrate both the new target training examples and the existing primitive concept models to infer the more complex concept models. LEGOMM treats the primitive concept models as the lego toy to potentially construct an unlimited vocabulary of new concepts. Specifically, we first formulate the logic operations to be the lego connectors to combine existing concept models hierarchically in probabilistic logic ontology trees. Then, we incorporate new target training information simultaneously to efficiently disambiguate the underlying logic tree and correct the error propagation. Extensive experiments are conducted on a large vehicle domain data set from ImageNet. The results demonstrate that LEGO-MM has significantly superior performance over existing state-of-the-art methods, which build new concept models from scratch.

Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits.

PubMed

Dessimoz, Christophe; Boeckmann, Brigitte; Roth, Alexander C J; Gonnet, Gaston H

2006-01-01

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.

Analysis of data mining classification by comparison of C4.5 and ID algorithms

NASA Astrophysics Data System (ADS)

Sudrajat, R.; Irianingsih, I.; Krisnawan, D.

2017-01-01

The rapid development of information technology, triggered by the intensive use of information technology. For example, data mining widely used in investment. Many techniques that can be used assisting in investment, the method that used for classification is decision tree. Decision tree has a variety of algorithms, such as C4.5 and ID3. Both algorithms can generate different models for similar data sets and different accuracy. C4.5 and ID3 algorithms with discrete data provide accuracy are 87.16% and 99.83% and C4.5 algorithm with numerical data is 89.69%. C4.5 and ID3 algorithms with discrete data provides 520 and 598 customers and C4.5 algorithm with numerical data is 546 customers. From the analysis of the both algorithm it can classified quite well because error rate less than 15%.

Five centuries of Southern Moravian drought variations revealed from living and historic tree rings

NASA Astrophysics Data System (ADS)

Büntgen, Ulf; Brázdil, Rudolf; Dobrovolný, Petr; Trnka, Mirek; Kyncl, Tomáš

2011-08-01

Past, present, and projected fluctuations of the hydrological cycle, associated to anthropogenic climate change, describe a pending challenge for natural ecosystems and human civilizations. Here, we compile and analyze long meteorological records from Brno, Czech Republic and nearby tree-ring measurements of living and historic firs from Southern Moravia. This unique paleoclimatic compilation together with innovative reconstruction methods and error estimates allows regional-scale May-June drought variability to be estimated back to ad 1500. Driest and wettest conditions occurred in 1653 and 1713, respectively. The ten wettest decades are evenly distributed throughout time, whereas the driest episodes occurred in the seventeenth century and from the 1840s onward. Discussion emphasizes agreement between the new reconstruction and documentary evidence, and stresses possible sources of reconstruction uncertainty including station inhomogeneity, limited frequency preservation, reduced climate sensitivity, and large-scale constraints.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Characterization and detection of Anopheles vestitipennis and Anopheles punctimacula (Diptera: Culicidae) larval habitats in Belize with field survey and SPOT satellite imagery

NASA Technical Reports Server (NTRS)

Rejmankova, E.; Pope, K. O.; Roberts, D. R.; Lege, M. G.; Andre, R.; Greico, J.; Alonzo, Y.

1998-01-01

Surveys of larval habitats of Anopheles vestitipennis and Anopheles punctimacula were conducted in Belize, Central America. Habitat analysis and classification resulted in delineation of eight habitat types defined by dominant life forms and hydrology. Percent cover of tall dense macrophytes, shrubs, open water, and pH were significantly different between sites with and without An. vestitipennis. For An. punctimacula, percent cover of tall dense macrophytes, trees, detritus, open water, and water depth were significantly different between larvae positive and negative sites. The discriminant function for An. vestitipennis correctly predicted the presence of larvae in 65% of sites and correctly predicted the absence of larvae in 88% of sites. The discriminant function for An. punctimacula correctly predicted 81% of sites for the presence of larvae and 45% for the absence of larvae. Canonical discriminant analysis of the three groups of habitats (An. vestitipennis positive; An. punctimacula positive; all negative) confirmed that while larval habitats of An. punctimacula are clustered in the tree dominated area, larval habitats of An. vestitipennis were found in both tree dominated and tall dense macrophyte dominated environments. The forest larval habitats of An. vestitipennis and An. punctimacula seem to be randomly distributed among different forest types. Both species tend to occur in denser forests with more detritus, shallower water, and slightly higher pH. Classification of dry season (February) SPOT multispectral satellite imagery produced 10 land cover types with the swamp forest and tall dense marsh classes being of particular interest. The accuracy assessment showed that commission errors for the tall, dense marsh and swamp forest appeared to be minor; but omission errors were significant, especially for the swamp forest (perhaps because no swamp forests are flooded in February). This means that where the classification indicates there are An. vestitipennis breeding sites, they probably do exist; but breeding sites in many locations are not identified and could be more abundant than indicated.

Reconstruction and analysis of a deciduous sapling using digital photographs or terrestrial-LiDAR technology.

PubMed

Delagrange, Sylvain; Rochon, Pascal

2011-10-01

To meet the increasing need for rapid and non-destructive extraction of canopy traits, two methods were used and compared with regard to their accuracy in estimating 2-D and 3-D parameters of a hybrid poplar sapling. The first method consisted of the analysis of high definition photographs in Tree Analyser (TA) software (PIAF-INRA/Kasetsart University). TA allowed the extraction of individual traits using a space carving approach. The second method utilized 3-D point clouds acquired from terrestrial light detection and ranging (T-LiDAR) scans. T-LiDAR scans were performed on trees without leaves to reconstruct the lignified structure of the sapling. From this skeleton, foliage was added using simple modelling rules extrapolated from field measurements. Validation of the estimated dimension and the accuracy of reconstruction was then achieved by comparison with an empirical data set. TA was found to be slightly less precise than T-LiDAR for estimating tree height, canopy height and mean canopy diameter, but for 2-D traits both methods were, however, fully satisfactory. TA tended to over-estimate total leaf area (error up to 50 %), but better estimates were obtained by reducing the size of the voxels used for calculations. In contrast, T-LiDAR estimated total leaf area with an error of <6 %. Finally, both methods led to an over-estimation of canopy volume. With respect to this trait, T-LiDAR (14·5 % deviation) greatly surpassed the accuracy of TA (up to 50 % deviation), even if the voxels used were reduced in size. Taking into account their magnitude of data acquisition and analysis and their accuracy in trait estimations, both methods showed contrasting potential future uses. Specifically, T-LiDAR is a particularly promising tool for investigating the development of large perennial plants, by itself or in association with plant modelling.

Epistemic-based investigation of the probability of hazard scenarios using Bayesian network for the lifting operation of floating objects

NASA Astrophysics Data System (ADS)

Toroody, Ahmad Bahoo; Abaiee, Mohammad Mahdi; Gholamnia, Reza; Ketabdari, Mohammad Javad

2016-09-01

Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method (SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.

Leaf Morphology, Taxonomy and Geometric Morphometrics: A Simplified Protocol for Beginners

PubMed Central

Viscosi, Vincenzo; Cardini, Andrea

2011-01-01

Taxonomy relies greatly on morphology to discriminate groups. Computerized geometric morphometric methods for quantitative shape analysis measure, test and visualize differences in form in a highly effective, reproducible, accurate and statistically powerful way. Plant leaves are commonly used in taxonomic analyses and are particularly suitable to landmark based geometric morphometrics. However, botanists do not yet seem to have taken advantage of this set of methods in their studies as much as zoologists have done. Using free software and an example dataset from two geographical populations of sessile oak leaves, we describe in detailed but simple terms how to: a) compute size and shape variables using Procrustes methods; b) test measurement error and the main levels of variation (population and trees) using a hierachical design; c) estimate the accuracy of group discrimination; d) repeat this estimate after controlling for the effect of size differences on shape (i.e., allometry). Measurement error was completely negligible; individual variation in leaf morphology was large and differences between trees were generally bigger than within trees; differences between the two geographic populations were small in both size and shape; despite a weak allometric trend, controlling for the effect of size on shape slighly increased discrimination accuracy. Procrustes based methods for the analysis of landmarks were highly efficient in measuring the hierarchical structure of differences in leaves and in revealing very small-scale variation. In taxonomy and many other fields of botany and biology, the application of geometric morphometrics contributes to increase scientific rigour in the description of important aspects of the phenotypic dimension of biodiversity. Easy to follow but detailed step by step example studies can promote a more extensive use of these numerical methods, as they provide an introduction to the discipline which, for many biologists, is less intimidating than the often inaccessible specialistic literature. PMID:21991324

Noninvasive calculation of the aortic blood pressure waveform from the flow velocity waveform: a proof of concept

PubMed Central

Vennin, Samuel; Mayer, Alexia; Li, Ye; Fok, Henry; Clapp, Brian; Alastruey, Jordi

2015-01-01

Estimation of aortic and left ventricular (LV) pressure usually requires measurements that are difficult to acquire during the imaging required to obtain concurrent LV dimensions essential for determination of LV mechanical properties. We describe a novel method for deriving aortic pressure from the aortic flow velocity. The target pressure waveform is divided into an early systolic upstroke, determined by the water hammer equation, and a diastolic decay equal to that in the peripheral arterial tree, interposed by a late systolic portion described by a second-order polynomial constrained by conditions of continuity and conservation of mean arterial pressure. Pulse wave velocity (PWV, which can be obtained through imaging), mean arterial pressure, diastolic pressure, and diastolic decay are required inputs for the algorithm. The algorithm was tested using 1) pressure data derived theoretically from prespecified flow waveforms and properties of the arterial tree using a single-tube 1-D model of the arterial tree, and 2) experimental data acquired from a pressure/Doppler flow velocity transducer placed in the ascending aorta in 18 patients (mean ± SD: age 63 ± 11 yr, aortic BP 136 ± 23/73 ± 13 mmHg) at the time of cardiac catheterization. For experimental data, PWV was calculated from measured pressures/flows, and mean and diastolic pressures and diastolic decay were taken from measured pressure (i.e., were assumed to be known). Pressure reconstructed from measured flow agreed well with theoretical pressure: mean ± SD root mean square (RMS) error 0.7 ± 0.1 mmHg. Similarly, for experimental data, pressure reconstructed from measured flow agreed well with measured pressure (mean RMS error 2.4 ± 1.0 mmHg). First systolic shoulder and systolic peak pressures were also accurately rendered (mean ± SD difference 1.4 ± 2.0 mmHg for peak systolic pressure). This is the first noninvasive derivation of aortic pressure based on fluid dynamics (flow and wave speed) in the aorta itself. PMID:26163442

Theoretical foundations for a quantitative approach to paleogenetics. I, II.

NASA Technical Reports Server (NTRS)

Holmquist, R.

1972-01-01

It is shown that by neglecting the phenomena of multiple hits, back mutation, and chance coincidence errors larger than 100% can be introduced in the calculated value of the average number of nucleotide base differences to be expected between two homologous polynucleotides. Mathematical formulas are derived to correct quantitatively for these effects. It is pointed out that the effects change materially the quantitative aspects of phylogenics, such as the length of the legs of the trees. A number of problems are solved without approximation.-

A Literature Review of Millimeter and Submillimeter Radiation Absorption and Scattering in the Atmosphere

DTIC Science & Technology

1978-10-01

N0 #»T TIONAL P ECTRUM A SICAL PR EROMETER ECORD TH 15 CM.-l K.P. ; S PLICATIO INEERING ENSITY 0 EnUENClE F TREE T BILITY 0 AVE RADI D...NECESSARY, BUT THAT EXPERIMENTS AT SEVERAL SPECI - MEN THICKNESSES IS OBLIGATORY. IT IS SHOWN THAT THE ERROR DUE TO THE VAPOR PHASE ABOVE THE LIQUID...THIS IS A COMPILATION OF ION-NEUTRAL REACTIONS 166 RATE CONSTANTS OF ATMOSPHERICALLY IMPORTANT SPECIES THE REACTIONS REPORTED ARE POSITIVE AND

Precision of the calibration of the AXAF engineering test article (VETA) mirrors

NASA Technical Reports Server (NTRS)

Schwartz, D. A.; Chartas, G.; Hughes, John P.; Kellogg, Edwin M.; Zhao, Ping

1992-01-01

Measurements of the VETA encircled energies have been performed at 5 energies within 16 radii ranging from 0.05 to 200 arcseconds. We report here on the analysis of the accuracy of those measurements. A common 'error tree' structure applies, and we present representative numbers for the larger terms. At 0.277, 1.5, and 2.07 keV, and for radii of 3 arcsec and larger, our measurements have estimated 1 sigma errors of 0.6 to 1.5 percent. Effects of measurement statistics and of the VETA test mount limit the accuracy at smaller angles, and modulation by the counter window support structure together with the imperfect position repeatability limit the accuracy for the 0.93 and 2.3 keV energies. We expect to mitigate these limitations when calibrating the complete AXAF flight mirror assembly.

Precision of the calibration of the AXAF Engineering Test Article (VETA) mirrors

NASA Technical Reports Server (NTRS)

Schwartz, D. A.; Chartas, G.; Hughes, J. P.; Kellogg, E. M.; Zhao, Ping

1993-01-01

Measurements of the VETA encircled energies have been performed at 5 energies within 16 radii ranging from 0.05 to 200 arcseconds. We report here on the analysis of the accuracy of those measurements. A common 'error tree' structure applies, and we present representative numbers for the larger terms. At 0.277, 1.5, and 2.07 keV, and for radii of 3 arcsec and larger, our measurements have estimated 1 sigma errors of 0.6 to 1.5 percent. Effects of measurement statistics and of the VETA test mount limit the accuracy at smaller angles, and modulation by the counter window support structure together with the imperfect position repeatability limit the accuracy for the 0.93 and 2.3 keV energies. We expect to mitigate these limitations when calibrating the complete AXAF flight mirror assembly.

Error minimizing algorithms for nearest eighbor classifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porter, Reid B; Hush, Don; Zimmer, G. Beate

2011-01-03

Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. Wemore » use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.« less

Efficient automatic OCR word validation using word partial format derivation and language model

NASA Astrophysics Data System (ADS)

Chen, Siyuan; Misra, Dharitri; Thoma, George R.

2010-01-01

In this paper we present an OCR validation module, implemented for the System for Preservation of Electronic Resources (SPER) developed at the U.S. National Library of Medicine.1 The module detects and corrects suspicious words in the OCR output of scanned textual documents through a procedure of deriving partial formats for each suspicious word, retrieving candidate words by partial-match search from lexicons, and comparing the joint probabilities of N-gram and OCR edit transformation corresponding to the candidates. The partial format derivation, based on OCR error analysis, efficiently and accurately generates candidate words from lexicons represented by ternary search trees. In our test case comprising a historic medico-legal document collection, this OCR validation module yielded the correct words with 87% accuracy and reduced the overall OCR word errors by around 60%.

Fluctuations in Tree Ring Cellulose d18O during the Little Ice Age Correlate with Solar Activity

NASA Astrophysics Data System (ADS)

Yamaguchi, Y. T.; Yokoyama, Y.; Miyahara, H.; Nakatsuka, T.

2008-12-01

The Maunder Minimum (AD1645-1715), when sunspots became exceedingly rare, is known to coincide with the coldest period during the Little Ice Age. This is a useful period to investigate possible linkage between solar activity and climate because variation in solar activity was different from that of today. The solar cycle length was longer (14 and 28 years) than that of today (11 and 22 years) hence any climate archives that have similar periodic changes could be separated from other internal climate forcing. We have reported that Greenland temperature variations coincided with decadal-scale variability in solar activity during the Maunder Minimum (Miyahara et al. 2008). Here we report interannual and intra-annual relative humidity (RH) variations in central Japan during that period, using tree ring cellulose d18O in a 382-year-old Japanese cedar tree (Cryptomeria japonica). The isotopic composition of tree rings can be a powerful tool to study the relationship between solar activity and climate, because we can directly compare solar activity (D14C) and climate (d18O) with little dating error. The climate proxy obtained using tree ring cellulose d18O is correlated both negatively and positively with RH and d18O in precipitation, respectively. Since d18O in precipitation is negatively correlated with the amount of precipitation in the monsoon area, tree ring cellulose d18O can be a reliable proxy for past RH and/or amount of precipitation in the area of the interest. Tree ring cellulose d18O of the cedar tree during AD1938-1998 in fact correlates significantly with the mean RH in June in central Japan. Tree ring d18O inferred RH variability during the Maunder Minimum shows distinct high RH spikes with an approximate 14-year quasiperiodicity. All nine solar minima during AD1640-1756 deduced from tree ring D14C coincided with high RH spikes, and seven of which coincided within 1-year. Interannual RH variations also coincided with Greenland temperature during this period. These results suggest that weakening of solar activity at solar minima caused distinct hemispheric scale climate change during the Maunder Minimum. We discuss the mechanism in which the solar activity variation caused the climate change, based on intra-annual RH variability and further data analysis of interannual RH variability. H. Miyahara et al., Earth Planet. Sci. Lett. 272, 1-2, 290-295 (2008).

Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements.

PubMed

Chavana-Bryant, Cecilia; Malhi, Yadvinder; Wu, Jin; Asner, Gregory P; Anastasiou, Athanasios; Enquist, Brian J; Cosio Caravasi, Eric G; Doughty, Christopher E; Saleska, Scott R; Martin, Roberta E; Gerard, France F

2017-05-01

Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (P mass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (N mass ) and carbon (C mass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R 2  = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R 2  = 0.07-0.73; %RMSE = 7-38) and multiple (R 2  = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment

NASA Astrophysics Data System (ADS)

Sankey, Temuulen; Shrestha, Rupesh; Sankey, Joel B.; Hardegree, Stuart; Strand, Eva

2013-07-01

encroachment is a globally occurring phenomenon that contributes to the global carbon sink. The magnitude of this contribution needs to be estimated at regional and local scales to address uncertainties present in the global- and continental-scale estimates, and guide regional policy and management in balancing restoration activities, including removal of woody plants, with greenhouse gas mitigation goals. The objective of this study was to estimate carbon stored in various successional phases of woody encroachment. Using lidar measurements of individual trees, we present high-resolution estimates of aboveground carbon storage in juniper woodlands. Segmentation analysis of lidar point cloud data identified a total of 60,628 juniper tree crowns across four watersheds. Tree heights, canopy cover, and density derived from lidar were strongly correlated with field measurements of 2613 juniper stems measured in 85 plots (30 × 30 m). Aboveground total biomass of individual trees was estimated using a regression model with lidar-derived height and crown area as predictors (Adj. R2 = 0.76, p < 0.001, RMSE = 0.58 kg). The predicted mean aboveground woody carbon storage for the study area was 677 g/m2. Uncertainty in carbon storage estimates was examined with a Monte Carlo approach that addressed major error sources. Ranges predicted with uncertainty analysis in the mean, individual tree, aboveground woody C, and associated standard deviation were 0.35 - 143.6 kg and 0.5 - 1.25 kg, respectively. Later successional phases of woody encroachment had, on average, twice the aboveground carbon relative to earlier phases. Woody encroachment might be more successfully managed and balanced with carbon storage goals by identifying priority areas in earlier phases of encroachment where intensive treatments are most effective.

Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment

USGS Publications Warehouse

Sankey, Temuulen; Shrestha, Rupesh; Sankey, Joel B.; Hardgree, Stuart; Strand, Eva

2013-01-01

Woody encroachment is a globally occurring phenomenon that contributes to the global carbon sink. The magnitude of this contribution needs to be estimated at regional and local scales to address uncertainties present in the global- and continental-scale estimates, and guide regional policy and management in balancing restoration activities, including removal of woody plants, with greenhouse gas mitigation goals. The objective of this study was to estimate carbon stored in various successional phases of woody encroachment. Using lidar measurements of individual trees, we present high-resolution estimates of aboveground carbon storage in juniper woodlands. Segmentation analysis of lidar point cloud data identified a total of 60,628 juniper tree crowns across four watersheds. Tree heights, canopy cover, and density derived from lidar were strongly correlated with field measurements of 2613 juniper stems measured in 85 plots (30 × 30 m). Aboveground total biomass of individual trees was estimated using a regression model with lidar-derived height and crown area as predictors (Adj. R2 = 0.76, p 2. Uncertainty in carbon storage estimates was examined with a Monte Carlo approach that addressed major error sources. Ranges predicted with uncertainty analysis in the mean, individual tree, aboveground woody C, and associated standard deviation were 0.35 – 143.6 kg and 0.5 – 1.25 kg, respectively. Later successional phases of woody encroachment had, on average, twice the aboveground carbon relative to earlier phases. Woody encroachment might be more successfully managed and balanced with carbon storage goals by identifying priority areas in earlier phases of encroachment where intensive treatments are most effective.

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province, China

PubMed Central

Zhuo, Lin; Tao, Hong; Wei, Hong; Chengzhen, Wu

2016-01-01

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D2H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D2H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well. PMID:26982054

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

Simulating spatiotemporal variation in full-flowering dates for tree peonies (1955-2011) in the middle and lower reaches of the Yellow River, China: using a panel data model

NASA Astrophysics Data System (ADS)

Liu, H.

2015-12-01

In China, the tree peony (Paeonia suffruticosa) is well known as the "king of flowers" since ancient times. The springtime flowering of it attracts a great number of tourists every year. Under the current background of rapid climate change, the flowering time of the tree peony has changed accordingly, which affected the travel arrangements of tourists. This paper is concerned with developing a panel data model to describe the relationship between full-flowering date (FFD) of the tree peony (Zhongyuan cultivar group) and relevant temperature change in the middle and lower reaches of the Yellow River. Then FFD time series at 24 sites in the period 1955-2011 were reconstructed using the above-mentioned model. At last, spatial and temporal variations in FFD were analysed. The results showed that the panel data model could simulate the FFDs of the tree peony accurately, with explained variance (R2)>0.65 and the root-mean-square error (RMSE)＜4.0 in the steps of double cross-validation. The simulated 57-year mean FFDs in the distribution area generally followed the latitudinal gradient. The FFDs in this area have advanced by 6 to 9 days over the past 57 years, at the rate of 0.8 to 1.8 days/decade. Compared with the other sub-areas in this area, the eastern forelands of Taihang Mountains and Luliang Mountains showed clearer advances of FFD. These conclusions reflected the comprehensive impact of climate change and the foehn on phenophases and are helpful for historical climate studies and festival events management

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

Analysis of a hardware and software fault tolerant processor for critical applications

NASA Technical Reports Server (NTRS)

Dugan, Joanne B.

1993-01-01

Computer systems for critical applications must be designed to tolerate software faults as well as hardware faults. A unified approach to tolerating hardware and software faults is characterized by classifying faults in terms of duration (transient or permanent) rather than source (hardware or software). Errors arising from transient faults can be handled through masking or voting, but errors arising from permanent faults require system reconfiguration to bypass the failed component. Most errors which are caused by software faults can be considered transient, in that they are input-dependent. Software faults are triggered by a particular set of inputs. Quantitative dependability analysis of systems which exhibit a unified approach to fault tolerance can be performed by a hierarchical combination of fault tree and Markov models. A methodology for analyzing hardware and software fault tolerant systems is applied to the analysis of a hypothetical system, loosely based on the Fault Tolerant Parallel Processor. The models consider both transient and permanent faults, hardware and software faults, independent and related software faults, automatic recovery, and reconfiguration.

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks

PubMed Central

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X.; Li, Huailiang; Shi, Rui

2017-01-01

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring. PMID:28471418

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks.

PubMed

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X; Li, Huailiang; Shi, Rui

2017-05-04

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring.

Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction.

PubMed

Kuhn, Stefan; Egert, Björn; Neumann, Steffen; Steinbeck, Christoph

2008-09-25

Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

Branch-Based Model for the Diameters of the Pulmonary Airways: Accounting for Departures From Self-Consistency and Registration Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neradilek, Moni B.; Polissar, Nayak L.; Einstein, Daniel R.

2012-04-24

We examine a previously published branch-based approach to modeling airway diameters that is predicated on the assumption of self-consistency across all levels of the tree. We mathematically formulate this assumption, propose a method to test it and develop a more general model to be used when the assumption is violated. We discuss the effect of measurement error on the estimated models and propose methods that account for it. The methods are illustrated on data from MRI and CT images of silicone casts of two rats, two normal monkeys and one ozone-exposed monkey. Our results showed substantial departures from self-consistency inmore » all five subjects. When departures from selfconsistency exist we do not recommend using the self-consistency model, even as an approximation, as we have shown that it may likely lead to an incorrect representation of the diameter geometry. Measurement error has an important impact on the estimated morphometry models and needs to be accounted for in the analysis.« less

Spectral mixture analyses of hyperspectral data acquired using a tethered balloon

USGS Publications Warehouse

Chen, Xuexia; Vierling, Lee

2006-01-01

Tethered balloon remote sensing platforms can be used to study radiometric issues in terrestrial ecosystems by effectively bridging the spatial gap between measurements made on the ground and those acquired via airplane or satellite. In this study, the Short Wave Aerostat-Mounted Imager (SWAMI) tethered balloon-mounted platform was utilized to evaluate linear and nonlinear spectral mixture analysis (SMA) for a grassland-conifer forest ecotone during the summer of 2003. Hyperspectral measurement of a 74-m diameter ground instantaneous field of view (GIFOV) attained by the SWAMI was studied. Hyperspectral spectra of four common endmembers, bare soil, grass, tree, and shadow, were collected in situ, and images captured via video camera were interpreted into accurate areal ground cover fractions for evaluating the mixture models. The comparison between the SWAMI spectrum and the spectrum derived by combining in situ spectral data with video-derived areal fractions indicated that nonlinear effects occurred in the near infrared (NIR) region, while nonlinear influences were minimal in the visible region. The evaluation of hyperspectral and multispectral mixture models indicated that nonlinear mixture model-derived areal fractions were sensitive to the model input data, while the linear mixture model performed more stably. Areal fractions of bare soil were overestimated in all models due to the increased radiance of bare soil resulting from side scattering of NIR radiation by adjacent grass and trees. Unmixing errors occurred mainly due to multiple scattering as well as close endmember spectral correlation. In addition, though an apparent endmember assemblage could be derived using linear approaches to yield low residual error, the tree and shade endmember fractions calculated using this technique were erroneous and therefore separate treatment of endmembers subject to high amounts of multiple scattering (i.e. shadows and trees) must be done with caution. Including the short wave infrared (SWIR) region in the hyperspectral and multispectral endmember data significantly reduced the Pearson correlation coefficient values among endmember spectra. Therefore, combination of visible, NIR, and SWIR information is likely to further improve the utility of SMA in understanding ecosystem structure and function and may help narrow uncertainties when utilizing remotely sensed data to extrapolate trace glas flux measurements from the canopy scale to the landscape scale.

Error in geometric morphometric data collection: Combining data from multiple sources.

PubMed

Robinson, Chris; Terhune, Claire E

2017-09-01

This study compares two- and three-dimensional morphometric data to determine the extent to which intra- and interobserver and intermethod error influence the outcomes of statistical analyses. Data were collected five times for each method and observer on 14 anthropoid crania using calipers, a MicroScribe, and 3D models created from NextEngine and microCT scans. ANOVA models were used to examine variance in the linear data at the level of genus, species, specimen, observer, method, and trial. Three-dimensional data were analyzed using geometric morphometric methods; principal components analysis was employed to examine how trials of all specimens were distributed in morphospace and Procrustes distances among trials were calculated and used to generate UPGMA trees to explore whether all trials of the same individual grouped together regardless of observer or method. Most variance in the linear data was at the genus level, with greater variance at the observer than method levels. In the 3D data, interobserver and intermethod error were similar to intraspecific distances among Callicebus cupreus individuals, with interobserver error being higher than intermethod error. Generally, taxa separate well in morphospace, with different trials of the same specimen typically grouping together. However, trials of individuals in the same species overlapped substantially with one another. Researchers should be cautious when compiling data from multiple methods and/or observers, especially if analyses are focused on intraspecific variation or closely related species, as in these cases, patterns among individuals may be obscured by interobserver and intermethod error. Conducting interobserver and intermethod reliability assessments prior to the collection of data is recommended. © 2017 Wiley Periodicals, Inc.

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time.

PubMed

Martínez-Martínez, F; Rupérez-Moreno, M J; Martínez-Sober, M; Solves-Llorens, J A; Lorente, D; Serrano-López, A J; Martínez-Sanchis, S; Monserrat, C; Martín-Guerrero, J D

2017-11-01

This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely randomized trees and random forest). Two different experimental setups were designed to validate and study the performance of these models under different conditions. The mean 3D Euclidean distance between nodes predicted by the models and those extracted from the FE simulations was calculated to assess the performance of the models in the validation set. The experiments proved that extremely randomized trees performed better than the other two models. The mean error committed by the three models in the prediction of the nodal displacements was under 2 mm, a threshold usually set for clinical applications. The time needed for breast compression prediction is sufficiently short to allow its use in real-time (<0.2 s). Copyright © 2017 Elsevier Ltd. All rights reserved.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China.

PubMed

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.

Hydrochemical analysis of groundwater using a tree-based model

NASA Astrophysics Data System (ADS)

Litaor, M. Iggy; Brielmann, H.; Reichmann, O.; Shenker, M.

2010-06-01

SummaryHydrochemical indices are commonly used to ascertain aquifer characteristics, salinity problems, anthropogenic inputs and resource management, among others. This study was conducted to test the applicability of a binary decision tree model to aquifer evaluation using hydrochemical indices as input. The main advantage of the tree-based model compared to other commonly used statistical procedures such as cluster and factor analyses is the ability to classify groundwater samples with assigned probability and the reduction of a large data set into a few significant variables without creating new factors. We tested the model using data sets collected from headwater springs of the Jordan River, Israel. The model evaluation consisted of several levels of complexity, from simple separation between the calcium-magnesium-bicarbonate water type of karstic aquifers to the more challenging separation of calcium-sodium-bicarbonate water type flowing through perched and regional basaltic aquifers. In all cases, the model assigned measures for goodness of fit in the form of misclassification errors and singled out the most significant variable in the analysis. The model proceeded through a sequence of partitions providing insight into different possible pathways and changing lithology. The model results were extremely useful in constraining the interpretation of geological heterogeneity and constructing a conceptual flow model for a given aquifer. The tree model clearly identified the hydrochemical indices that were excluded from the analysis, thus providing information that can lead to a decrease in the number of routinely analyzed variables and a significant reduction in laboratory cost.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China

PubMed Central

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia. PMID:27002822

Identification of Amazonian Trees with DNA Barcodes

PubMed Central

Gonzalez, Mailyn Adriana; Baraloto, Christopher; Engel, Julien; Mori, Scott A.; Pétronelli, Pascal; Riéra, Bernard; Roger, Aurélien; Thébaud, Christophe; Chave, Jérôme

2009-01-01

Background Large-scale plant diversity inventories are critical to develop informed conservation strategies. However, the workload required for classic taxonomic surveys remains high and is particularly problematic for megadiverse tropical forests. Methodology/Principal Findings Based on a comprehensive census of all trees in two hectares of a tropical forest in French Guiana, we examined whether plant DNA barcoding could contribute to increasing the quality and the pace of tropical plant biodiversity surveys. Of the eight plant DNA markers we tested (rbcLa, rpoC1, rpoB, matK, ycf5, trnL, psbA-trnH, ITS), matK and ITS had a low rate of sequencing success. More critically, none of the plastid markers achieved a rate of correct plant identification greater than 70%, either alone or combined. The performance of all barcoding markers was noticeably low in few species-rich clades, such as the Laureae, and the Sapotaceae. A field test of the approach enabled us to detect 130 molecular operational taxonomic units in a sample of 252 juvenile trees. Including molecular markers increased the identification rate of juveniles from 72% (morphology alone) to 96% (morphology and molecular) of the individuals assigned to a known tree taxon. Conclusion/Significance We conclude that while DNA barcoding is an invaluable tool for detecting errors in identifications and for identifying plants at juvenile stages, its limited ability to identify collections will constrain the practical implementation of DNA-based tropical plant biodiversity programs. PMID:19834612

Genomic Data Quality Impacts Automated Detection of Lateral Gene Transfer in Fungi

PubMed Central

Dupont, Pierre-Yves; Cox, Murray P.

2017-01-01

Lateral gene transfer (LGT, also known as horizontal gene transfer), an atypical mechanism of transferring genes between species, has almost become the default explanation for genes that display an unexpected composition or phylogeny. Numerous methods of detecting LGT events all rely on two fundamental strategies: primary structure composition or gene tree/species tree comparisons. Discouragingly, the results of these different approaches rarely coincide. With the wealth of genome data now available, detection of laterally transferred genes is increasingly being attempted in large uncurated eukaryotic datasets. However, detection methods depend greatly on the quality of the underlying genomic data, which are typically complex for eukaryotes. Furthermore, given the automated nature of genomic data collection, it is typically impractical to manually verify all protein or gene models, orthology predictions, and multiple sequence alignments, requiring researchers to accept a substantial margin of error in their datasets. Using a test case comprising plant-associated genomes across the fungal kingdom, this study reveals that composition- and phylogeny-based methods have little statistical power to detect laterally transferred genes. In particular, phylogenetic methods reveal extreme levels of topological variation in fungal gene trees, the vast majority of which show departures from the canonical species tree. Therefore, it is inherently challenging to detect LGT events in typical eukaryotic genomes. This finding is in striking contrast to the large number of claims for laterally transferred genes in eukaryotic species that routinely appear in the literature, and questions how many of these proposed examples are statistically well supported. PMID:28235827

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing

PubMed Central

Niknafs, Noushin; Beleva-Guthrie, Violeta; Naiman, Daniel Q.; Karchin, Rachel

2015-01-01

Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones—cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (≥ 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors’ preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing. PMID:26436540

Water-Tree Modelling and Detection for Underground Cables

NASA Astrophysics Data System (ADS)

Chen, Qi

In recent years, aging infrastructure has become a major concern for the power industry. Since its inception in early 20th century, the electrical system has been the cornerstone of an industrial society. Stable and uninterrupted delivery of electrical power is now a base necessity for the modern world. As the times march-on, however, the electrical infrastructure ages and there is the inevitable need to renew and replace the existing system. Unfortunately, due to time and financial constraints, many electrical systems today are forced to operate beyond their original design and power utilities must find ways to prolong the lifespan of older equipment. Thus, the concept of preventative maintenance arises. Preventative maintenance allows old equipment to operate longer and at better efficiency, but in order to implement preventative maintenance, the operators must know minute details of the electrical system, especially some of the harder to assess issues such water-tree. Water-tree induced insulation degradation is a problem typically associated with older cable systems. It is a very high impedance phenomenon and it is difficult to detect using traditional methods such as Tan-Delta or Partial Discharge. The proposed dissertation studies water-tree development in underground cables, potential methods to detect water-tree location and water-tree severity estimation. The dissertation begins by developing mathematical models of water-tree using finite element analysis. The method focuses on surface-originated vented tree, the most prominent type of water-tree fault in the field. Using the standard operation parameters of North American electrical systems, the water-tree boundary conditions are defined. By applying finite element analysis technique, the complex water-tree structure is broken down to homogeneous components. The result is a generalized representation of water-tree capacitance at different stages of development. The result from the finite element analysis is used to model water-tree in large system. Both empirical measurements and the mathematical model show that the impedance of early-stage water-tree is extremely large. As the result, traditional detection methods such Tan-Delta or Partial Discharge are not effective due to the excessively high accuracy requirement. A high-frequency pulse detection method is developed instead. The water-tree impedance is capacitive in nature and it can be reduced to manageable level by high-frequency inputs. The method is able to determine the location of early-stage water-tree in long-distance cables using economically feasible equipment. A pattern recognition method is developed to estimate the severity of water-tree using its pulse response from the high-frequency test method. The early-warning system for water-tree appearance is a tool developed to assist the practical implementation of the high-frequency pulse detection method. Although the equipment used by the detection method is economically feasible, it is still a specialized test and not designed for constant monitoring of the system. The test also place heavy stress on the cable and it is most effective when the cable is taken offline. As the result, utilities need a method to estimate the likelihood of water-tree presence before subjecting the cable to the specialized test. The early-warning system takes advantage of naturally occurring high-frequency events in the system and uses a deviation-comparison method to estimate the probability of water-tree presence on the cable. If the likelihood is high, then the utility can use the high-frequency pulse detection method to obtain accurate results. Specific pulse response patterns can be used to calculate the capacitance of water-tree. The calculated result, however, is subjected to margins of error due to limitations from the real system. There are both long-term and short-term methods to improve the accuracy. Computation algorithm improvement allows immediate improvement on accuracy of the capacitance estimation. The probability distribution of the calculation solution showed that improvements in waveform time-step measurement allow fundamental improves to the overall result.

The value of crossdating to retain high-frequency variability, climate signals, and extreme events in environmental proxies.

PubMed

Black, Bryan A; Griffin, Daniel; van der Sleen, Peter; Wanamaker, Alan D; Speer, James H; Frank, David C; Stahle, David W; Pederson, Neil; Copenheaver, Carolyn A; Trouet, Valerie; Griffin, Shelly; Gillanders, Bronwyn M

2016-07-01

High-resolution biogenic and geologic proxies in which one increment or layer is formed per year are crucial to describing natural ranges of environmental variability in Earth's physical and biological systems. However, dating controls are necessary to ensure temporal precision and accuracy; simple counts cannot ensure that all layers are placed correctly in time. Originally developed for tree-ring data, crossdating is the only such procedure that ensures all increments have been assigned the correct calendar year of formation. Here, we use growth-increment data from two tree species, two marine bivalve species, and a marine fish species to illustrate sensitivity of environmental signals to modest dating error rates. When falsely added or missed increments are induced at one and five percent rates, errors propagate back through time and eliminate high-frequency variability, climate signals, and evidence of extreme events while incorrectly dating and distorting major disturbances or other low-frequency processes. Our consecutive Monte Carlo experiments show that inaccuracies begin to accumulate in as little as two decades and can remove all but decadal-scale processes after as little as two centuries. Real-world scenarios may have even greater consequence in the absence of crossdating. Given this sensitivity to signal loss, the fundamental tenets of crossdating must be applied to fully resolve environmental signals, a point we underscore as the frontiers of growth-increment analysis continue to expand into tropical, freshwater, and marine environments. © 2016 John Wiley & Sons Ltd.

Age, allocation, and availability of nonstructural carbohydrates in red maple

NASA Astrophysics Data System (ADS)

Carbone, Mariah; Keenan, Trevor; Czimczik, Claudia; Murakami, Paula; O'Keefe, John; Pederson, Neil; Schaberg, Paul; Xu, Xiaomei; Richardson, Andrew

2013-04-01

Nonstructural carbohydrates (NSC) are the primary products of photosynthesis, composed mostly of sugars and starch. Recent studies show that NSC pools in mature trees can be quite large and on average a decade old. Thus, NSC pools integrate years of carbon assimilation and represent significant ecological memory at the whole plant and ecosystem level. However, we know very little about how older stored NSC versus newly assimilated NSC are used to support growth and metabolism, or how available older NSC are to trees during stress or following disturbance. To better understand these potential lags in NSC allocation, we studied mature red maple (Acer rubrum) trees in New England temperate forests. Applying the radiocarbon (14C) "bomb spike" approach, we estimated the age of carbon in stemwood NSC, ring cellulose, bole respiration, and stump sprouts regenerated following harvesting. These measurements allowed us to compare the NSC used for metabolic demands, annual growth, and the NSC available for regrowth following disturbance to the NSC actually present in the stemwood. Finally, tree ring widths were analyzed to determine the annual autocorrelation in radial wood increment. We found that the mean age of stemwood sugars was 9.8 ± 5 y. The age of NSC used to support metabolism (bole respiration) was much younger than the mean age of stemwood sugars, indicating preferential use of more recently assimilated NSC. In the spring before leaves emerged, bole respiration was between 1-2 y, whereas it was composed of newly assimilated NSC in the late summer. The ring cellulose 14C age was on average 0.8 y older than direct ring counts (within error of 14C measurement) which may or may not indicate a stored NSC contribution. Tree ring width analyses indicate strong autocorrelation between ring growth in one year and in the following year, in agreement with ring cellulose 14C ages. However, autocorrelation weakened over the following 10 years, consistent with the measured mean age of the NSC pool. The stump sprouts were formed from NSC 1-17 y old, (mean 5.8 ± 5 y), with older trees using older NSC to produce stump sprouts, indicating that some of the older NSC reserves are available to the tree for use following major disturbance. These results highlight the importance of ecological memory in NSC pools for understanding tree carbon allocation and overall ecosystem carbon balance.

Updating older forest inventory data with a growth model and satellite records to improve the responsiveness and currency of national carbon monitoring

NASA Astrophysics Data System (ADS)

Healey, S. P.; Zhao, F. R.; McCarter, J. B.; Frescino, T.; Goeking, S.

2017-12-01

International reporting of American forest carbon trends depends upon the Forest Service's nationally consistent network of inventory plots. Plots are measured on a rolling basis over a 5- to 10-year cycle, so estimates related to any variable, including carbon storage, reflect conditions over a 5- to 10-year window. This makes it difficult to identify the carbon impact of discrete events (e.g., a bad fire year; extraction rates related to home-building trends), particularly if the events are recent.We report an approach to make inventory estimates more sensitive to discrete and recent events. We use a growth model (the Forest Vegetation Simulator - FVS) that is maintained by the Forest Service to annually update the tree list for every plot, allowing all plots to contribute to a series of single-year estimates. Satellite imagery from the Landsat platform guides the FVS simulations by providing information about which plots have been disturbed, which are recovering from disturbance, and which are undergoing undisturbed growth. The FVS model is only used to "update" plot tree lists until the next field measurement is made (maximum of 9 years). As a result, predicted changes are usually small and error rates are low. We present a pilot study of this system in Idaho, which has experienced several major fire events in the last decade. Empirical estimates of uncertainty, accounting for both plot sampling error and FVS model error, suggest that this approach greatly increases temporal specificity and sensitivity to discrete events without sacrificing much estimate precision at the level of a US state. This approach has the potential to take better advantage of the Forest Service's rolling plot measurement schedule to report carbon storage in the US, and it offers the basis of a system that might allow near-term, forward-looking analysis of the effects of hypothetical forest disturbance patterns.

DFACS - DATABASE, FORMS AND APPLICATIONS FOR CABLING AND SYSTEMS, VERSION 3.30

NASA Technical Reports Server (NTRS)

Billitti, J. W.

1994-01-01

DFACS is an interactive multi-user computer-aided engineering tool for system level electrical integration and cabling engineering. The purpose of the program is to provide the engineering community with a centralized database for entering and accessing system functional definitions, subsystem and instrument-end circuit pinout details, and harnessing data. The primary objective is to provide an instantaneous single point of information interchange, thus avoiding error-prone, time-consuming, and costly multiple-path data shuttling. The DFACS program, which is centered around a single database, has built-in menus that provide easy data input and access for all involved system, subsystem, and cabling personnel. The DFACS program allows parallel design of circuit data sheets and harness drawings. It also recombines raw information to automatically generate various project documents and drawings including the Circuit Data Sheet Index, the Electrical Interface Circuits List, Assembly and Equipment Lists, Electrical Ground Tree, Connector List, Cable Tree, Cabling Electrical Interface and Harness Drawings, Circuit Data Sheets, and ECR List of Affected Interfaces/Assemblies. Real time automatic production of harness drawings and circuit data sheets from the same data reservoir ensures instant system and cabling engineering design harmony. DFACS also contains automatic wire routing procedures and extensive error checking routines designed to minimize the possibility of engineering error. DFACS is designed to run on DEC VAX series computers under VMS using Version 6.3/01 of INGRES QUEL/OSL, a relational database system which is available through Relational Technology, Inc. The program is available in VAX BACKUP format on a 1600 BPI 9-track magnetic tape (standard media) or a TK50 tape cartridge. DFACS was developed in 1987 and last updated in 1990. DFACS is a copyrighted work with all copyright vested in NASA. DEC, VAX and VMS are trademarks of Digital Equipment Corporation. INGRES QUEL/OSL is a trademark of Relational Technology, Inc.

Content-based multiple bitstream image transmission over noisy channels.

PubMed

Cao, Lei; Chen, Chang Wen

2002-01-01

In this paper, we propose a novel combined source and channel coding scheme for image transmission over noisy channels. The main feature of the proposed scheme is a systematic decomposition of image sources so that unequal error protection can be applied according to not only bit error sensitivity but also visual content importance. The wavelet transform is adopted to hierarchically decompose the image. The association between the wavelet coefficients and what they represent spatially in the original image is fully exploited so that wavelet blocks are classified based on their corresponding image content. The classification produces wavelet blocks in each class with similar content and statistics, therefore enables high performance source compression using the set partitioning in hierarchical trees (SPIHT) algorithm. To combat the channel noise, an unequal error protection strategy with rate-compatible punctured convolutional/cyclic redundancy check (RCPC/CRC) codes is implemented based on the bit contribution to both peak signal-to-noise ratio (PSNR) and visual quality. At the receiving end, a postprocessing method making use of the SPIHT decoding structure and the classification map is developed to restore the degradation due to the residual error after channel decoding. Experimental results show that the proposed scheme is indeed able to provide protection both for the bits that are more sensitive to errors and for the more important visual content under a noisy transmission environment. In particular, the reconstructed images illustrate consistently better visual quality than using the single-bitstream-based schemes.

Data mining: Potential applications in research on nutrition and health.

PubMed

Batterham, Marijka; Neale, Elizabeth; Martin, Allison; Tapsell, Linda

2017-02-01

Data mining enables further insights from nutrition-related research, but caution is required. The aim of this analysis was to demonstrate and compare the utility of data mining methods in classifying a categorical outcome derived from a nutrition-related intervention. Baseline data (23 variables, 8 categorical) on participants (n = 295) in an intervention trial were used to classify participants in terms of meeting the criteria of achieving 10 000 steps per day. Results from classification and regression trees (CARTs), random forests, adaptive boosting, logistic regression, support vector machines and neural networks were compared using area under the curve (AUC) and error assessments. The CART produced the best model when considering the AUC (0.703), overall error (18%) and within class error (28%). Logistic regression also performed reasonably well compared to the other models (AUC 0.675, overall error 23%, within class error 36%). All the methods gave different rankings of variables' importance. CART found that body fat, quality of life using the SF-12 Physical Component Summary (PCS) and the cholesterol: HDL ratio were the most important predictors of meeting the 10 000 steps criteria, while logistic regression showed the SF-12PCS, glucose levels and level of education to be the most significant predictors (P ≤ 0.01). Differing outcomes suggest caution is required with a single data mining method, particularly in a dataset with nonlinear relationships and outliers and when exploring relationships that were not the primary outcomes of the research. © 2017 Dietitians Association of Australia.

A framework for incorporating the effects of hydrodynamic stresses on forest photosynthesis and evaporation

NASA Astrophysics Data System (ADS)

Matheny, A. M.; Bohrer, G.; Thompsen, J.; Frasson, R.; Frasson, C. D.; Ivanov, V. Y.

2012-12-01

Hydraulic limitations are known to control transpiration in forest ecosystems when the soil is drying or when the vapor pressure deficit between the air and stomata (VPD) is very large, but they can also impact stomatal apertures under conditions of adequate soil moisture and lower evaporative demand. We use the NACP flux measurements and models dataset for multiple site/model intercomparisons to evaluate the degree to which currently un-resolved high-frequency (sub-daily) hydrodynamic stresses affect the error in model prediction of latent heat flux. We find that many site-model combinations are characterized by a typical pattern of overestimation of afternoon flux and a corresponding underestimation of pre-noon flux. We hypothesize that this pattern is a result of un-resolved afternoon stomata closure due to hydrodynamic stresses. In a forest plot at the University of Michigan Biological Station, we use measurements of leaf-level stomata conductance and water potential to demonstrate that trees of similar type - mid-late successional deciduous trees - have very different hydrodynamic strategies that lead to differences in their temporal patterns of stomata conductance. We found that red oak trees continue transpiring despite a large stem-water deficit while red maple trees regulate stomata to maintain a high water potential. Red oaks, which are ring porous, are also able to access more soil water, assumingly from deeper ground layers and have higher conductivity, compared with the maples, which are diffuse porous. These differences will lead to large differences in stomata conductance and water use based on the species composition of the forest. We also demonstrate that the size and shape of the tree stem-branch system may lead to differences in the extent of hydrodynamic stress, which may change the forest respiration patterns as the forest grows and ages. We propose a framework to resolve tree hydrodynamics in global and regional models. It is based on the Finite-Elements Tree-Crown Hydrodynamics model (FETCH) combined with a statistical functional-type/hydraulic-type/size representation of the trees in the forest. Lidar and multi-spectral images of the forest can be used to obtain numerical distributions of species and size of individual tree crowns needed to initialize such simulations. FETCH simulates water flow through the tree as a simplified system of porous media conduits. It explicitly resolves spatiotemporal hydraulic stresses throughout the tree's hydraulic system that cannot be easily represented using other stomatal-conductance models. It uses a physical representation of water flow in a 3-D tree-stem-branch system assuming the xylem is a porous media. Empirical equations relate water potential at the branch-tips to stomata conductance at leaves connected to these branches. FETCH calculates the hydrodynamic stress related closure of stomata, provided the atmospheric and biological variables from the global model, and could replace the current empirical formulation for stomata adjustment based on soil moisture.

A new method for separating the climatic and biological trend components from tree ring series, with implications for paleoclimate reconstructions

NASA Astrophysics Data System (ADS)

Bouldin, J.

2010-12-01

In the reconstruction of past climates from tree rings multi-decadal to multi-centennial periods, one longstanding problem is the confounding of the natural biological growth trend of the tree with any existing long term trends in the climate. No existing analytical method is capable of resolving these two change components, so it remains unclear how accurate existing ring series standardizations are, and by implication, climate reconstructions based upon them. For example, dendrochronological at the ITRDB are typically standardized by detrending, at each site, each individual tree core, using a relatively stiff deterministic function such as a negative exponential curve or smoothing spline. Another approach, referred to as RCS (Regional Curve Standardization) attempts to solve some problems of the individual series detrending, by constructing a single growth curve from the aggregated cambial ages of the rings of the cores at a site (or collection of sites). This curve is presumed to represent the “ideal” or expected growth of the trees from which it is derived. Although an improvement in some respects, this method will be degraded in direct proportion to the lack of a mixture of tree sizes or ages throughout the span of the chronology. I present a new method of removing the biological curve from tree ring series, such that temporal changes better represent the environmental variation captured by the tree rings. The method institutes several new approaches, such as the correction for the estimated number of missed rings near the pith, and the use of tree size and ring area relationships instead of the traditional tree ages and ring widths. The most important innovation is a careful extraction of the existing information on the relationship between tree size (basal area) and ring area that exists within each single year of the chronology. This information is, by definition, not contaminated by temporal climatic changes, and so when removed, leaves the climatically caused, and random error components of the chronology. A sophisticated algorithm, based on pair-wise ring comparisons in which tree size is standardized both within and between years, forms the basis of the method. Evaluations of the method are underway with both simulated and actual (ITRDB) data, to evaluate the potentials and drawbacks of the method relative to existing methods. The ITRDB test data consists of a set of about 50 primarily high elevation sites from across western North America. Most of these sites show a pronounced 20th Century warming relative to earlier centuries, in accordance with current understanding, albeit at a non-global scale. A relative minority show cooling, occasionally strongly. Current and future work emphasizes evaluation of the method with varying, simulated data, and more thorough empirical evaluations of the method in situations where the type, and intensity, of the primary environmentally limiting factor varies (e.g temperature versus soil moisture limited sites).

Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aman, Saima; Simmhan, Yogesh; Prasanna, Viktor K.

2011-12-11

The rising global demand for energy is best addressed by adopting and promoting sustainable methods of power consumption. We employ an informatics approach towards forecasting the energy consumption patterns in a university campus micro-grid which can be used for energy use planning and conservation. We use novel indirect indicators of energy that are commonly available to train regression tree models that can predict campus and building energy use for coarse (daily) and fine (15-min) time intervals, utilizing 3 years of sensor data collected at 15min intervals from 170 smart power meters. We analyze the impact of individual features used inmore » the models to identify the ones best suited for the application. Our models show a high degree of accuracy with CV-RMSE errors ranging from 7.45% to 19.32%, and a reduction in error from baseline models by up to 53%.« less

Validation of tool mark analysis of cut costal cartilage.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2012-03-01

This study was designed to establish the potential error rate associated with the generally accepted method of tool mark analysis of cut marks in costal cartilage. Three knives with different blade types were used to make experimental cut marks in costal cartilage of pigs. Each cut surface was cast, and each cast was examined by three analysts working independently. The presence of striations, regularity of striations, and presence of a primary and secondary striation pattern were recorded for each cast. The distance between each striation was measured. The results showed that striations were not consistently impressed on the cut surface by the blade's cutting edge. Also, blade type classification by the presence or absence of striations led to a 65% misclassification rate. Use of the classification tree and cross-validation methods and inclusion of the mean interstriation distance decreased the error rate to c. 50%. © 2011 American Academy of Forensic Sciences.

pKa prediction of monoprotic small molecules the SMARTS way.

PubMed

Lee, Adam C; Yu, Jing-Yu; Crippen, Gordon M

2008-10-01

Realizing favorable absorption, distribution, metabolism, elimination, and toxicity profiles is a necessity due to the high attrition rate of lead compounds in drug development today. The ability to accurately predict bioavailability can help save time and money during the screening and optimization processes. As several robust programs already exist for predicting logP, we have turned our attention to the fast and robust prediction of pK(a) for small molecules. Using curated data from the Beilstein Database and Lange's Handbook of Chemistry, we have created a decision tree based on a novel set of SMARTS strings that can accurately predict the pK(a) for monoprotic compounds with R(2) of 0.94 and root mean squared error of 0.68. Leave-some-out (10%) cross-validation achieved Q(2) of 0.91 and root mean squared error of 0.80.

Bayes classification of terrain cover using normalized polarimetric data

NASA Technical Reports Server (NTRS)

Yueh, H. A.; Swartz, A. A.; Kong, J. A.; Shin, R. T.; Novak, L. M.

1988-01-01

The normalized polarimetric classifier (NPC) which uses only the relative magnitudes and phases of the polarimetric data is proposed for discrimination of terrain elements. The probability density functions (PDFs) of polarimetric data are assumed to have a complex Gaussian distribution, and the marginal PDF of the normalized polarimetric data is derived by adopting the Euclidean norm as the normalization function. The general form of the distance measure for the NPC is also obtained. It is demonstrated that for polarimetric data with an arbitrary PDF, the distance measure of NPC will be independent of the normalization function selected even when the classifier is mistrained. A complex Gaussian distribution is assumed for the polarimetric data consisting of grass and tree regions. The probability of error for the NPC is compared with those of several other single-feature classifiers. The classification error of NPCs is shown to be independent of the normalization function.

Multiple nuclear genes and retroposons support vicariance and dispersal of the palaeognaths, and an Early Cretaceous origin of modern birds.

PubMed

Haddrath, Oliver; Baker, Allan J

2012-11-22

The origin and timing of the diversification of modern birds remains controversial, primarily because phylogenetic relationships are incompletely resolved and uncertainty persists in molecular estimates of lineage ages. Here, we present a species tree for the major palaeognath lineages using 27 nuclear genes and 27 archaic retroposon insertions. We show that rheas are sister to the kiwis, emu and cassowaries, and confirm ratite paraphyly because tinamous are sister to moas. Divergence dating using 10 genes with broader taxon sampling, including emu, cassowary, ostrich, five kiwis, two rheas, three tinamous, three extinct moas and 15 neognath lineages, suggests that three vicariant events and possibly two dispersals are required to explain their historical biogeography. The age of crown group birds was estimated at 131 Ma (95% highest posterior density 122-138 Ma), similar to previous molecular estimates. Problems associated with gene tree discordance and incomplete lineage sorting in birds will require much larger gene sets to increase species tree accuracy and improve error in divergence times. The relatively rapid branching within neoaves pre-dates the extinction of dinosaurs, suggesting that the genesis of the radiation within this diverse clade of birds was not in response to the Cretaceous-Paleogene extinction event.

Spatial modeling and classification of corneal shape.

PubMed

Marsolo, Keith; Twa, Michael; Bullimore, Mark A; Parthasarathy, Srinivasan

2007-03-01

One of the most promising applications of data mining is in biomedical data used in patient diagnosis. Any method of data analysis intended to support the clinical decision-making process should meet several criteria: it should capture clinically relevant features, be computationally feasible, and provide easily interpretable results. In an initial study, we examined the feasibility of using Zernike polynomials to represent biomedical instrument data in conjunction with a decision tree classifier to distinguish between the diseased and non-diseased eyes. Here, we provide a comprehensive follow-up to that work, examining a second representation, pseudo-Zernike polynomials, to determine whether they provide any increase in classification accuracy. We compare the fidelity of both methods using residual root-mean-square (rms) error and evaluate accuracy using several classifiers: neural networks, C4.5 decision trees, Voting Feature Intervals, and Naïve Bayes. We also examine the effect of several meta-learning strategies: boosting, bagging, and Random Forests (RFs). We present results comparing accuracy as it relates to dataset and transformation resolution over a larger, more challenging, multi-class dataset. They show that classification accuracy is similar for both data transformations, but differs by classifier. We find that the Zernike polynomials provide better feature representation than the pseudo-Zernikes and that the decision trees yield the best balance of classification accuracy and interpretability.

NMR structure calculation for all small molecule ligands and non-standard residues from the PDB Chemical Component Dictionary.

PubMed

Yilmaz, Emel Maden; Güntert, Peter

2015-09-01

An algorithm, CYLIB, is presented for converting molecular topology descriptions from the PDB Chemical Component Dictionary into CYANA residue library entries. The CYANA structure calculation algorithm uses torsion angle molecular dynamics for the efficient computation of three-dimensional structures from NMR-derived restraints. For this, the molecules have to be represented in torsion angle space with rotations around covalent single bonds as the only degrees of freedom. The molecule must be given a tree structure of torsion angles connecting rigid units composed of one or several atoms with fixed relative positions. Setting up CYANA residue library entries therefore involves, besides straightforward format conversion, the non-trivial step of defining a suitable tree structure of torsion angles, and to re-order the atoms in a way that is compatible with this tree structure. This can be done manually for small numbers of ligands but the process is time-consuming and error-prone. An automated method is necessary in order to handle the large number of different potential ligand molecules to be studied in drug design projects. Here, we present an algorithm for this purpose, and show that CYANA structure calculations can be performed with almost all small molecule ligands and non-standard amino acid residues in the PDB Chemical Component Dictionary.

Using single cell sequencing data to model the evolutionary history of a tumor.

PubMed

Kim, Kyung In; Simon, Richard

2014-01-24

The introduction of next-generation sequencing (NGS) technology has made it possible to detect genomic alterations within tumor cells on a large scale. However, most applications of NGS show the genetic content of mixtures of cells. Recently developed single cell sequencing technology can identify variation within a single cell. Characterization of multiple samples from a tumor using single cell sequencing can potentially provide information on the evolutionary history of that tumor. This may facilitate understanding how key mutations accumulate and evolve in lineages to form a heterogeneous tumor. We provide a computational method to infer an evolutionary mutation tree based on single cell sequencing data. Our approach differs from traditional phylogenetic tree approaches in that our mutation tree directly describes temporal order relationships among mutation sites. Our method also accommodates sequencing errors. Furthermore, we provide a method for estimating the proportion of time from the earliest mutation event of the sample to the most recent common ancestor of the sample of cells. Finally, we discuss current limitations on modeling with single cell sequencing data and possible improvements under those limitations. Inferring the temporal ordering of mutational sites using current single cell sequencing data is a challenge. Our proposed method may help elucidate relationships among key mutations and their role in tumor progression.

Setting good practices to assess the efficiency of iron fertilizers.

PubMed

El-Jendoubi, Hamdi; Melgar, Juan Carlos; Alvarez-Fernández, Ana; Sanz, Manuel; Abadía, Anunciación; Abadía, Javier

2011-05-01

The most prevalent nutritional disorder in fruit tree crops growing in calcareous soils is Fe deficiency chlorosis. Iron-deficient, chlorotic tree orchards require Fe-fertilization, since chlorosis causes decreases in tree vegetative growth as well as fruit yield and quality losses. When assessing the effectiveness of Fe-fertilizers, it is necessary to use sound practices based in the state-of-the art knowledge on the physiology and biochemistry of Fe deficiency. This review provides an overview on how to carry out the assessment of the efficiency of Fe-fertilizers, discussing common errors found in the literature, outlining adequate procedures and giving real examples of practical studies carried out in our laboratory in the past decade. The review focuses on: i) the design of Fe-fertilization experiments, discussing several issues such as the convenience of using controlled conditions or field experiments, whether fertilizer assessment experiments should mimic usual fertilization practices, as well as aspects regarding product formulations, dosages, control references and number of replicates; ii) the assessment of chlorosis recovery upon Fe-fertilization by monitoring leaf chlorophyll, and iii) the analysis of the plant responses upon Fe-fertilization, discussing the phases of leaf chlorosis recovery and the control of other leaf nutritional parameters. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

An AI-based approach to structural damage identification by modal analysis

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1990-01-01

Flexible-structure damage is presently addressed by a combined model- and parameter-identification approach which employs the AI methodologies of classification, heuristic search, and object-oriented model knowledge representation. The conditions for model-space search convergence to the best model are discussed in terms of search-tree organization and initial model parameter error. In the illustrative example of a truss structure presented, the use of both model and parameter identification is shown to lead to smaller parameter corrections than would be required by parameter identification alone.

A finite-difference method for the variable coefficient Poisson equation on hierarchical Cartesian meshes

NASA Astrophysics Data System (ADS)

Raeli, Alice; Bergmann, Michel; Iollo, Angelo

2018-02-01

We consider problems governed by a linear elliptic equation with varying coefficients across internal interfaces. The solution and its normal derivative can undergo significant variations through these internal boundaries. We present a compact finite-difference scheme on a tree-based adaptive grid that can be efficiently solved using a natively parallel data structure. The main idea is to optimize the truncation error of the discretization scheme as a function of the local grid configuration to achieve second-order accuracy. Numerical illustrations are presented in two and three-dimensional configurations.

Empirical Analysis and Refinement of Expert System Knowledge Bases

DTIC Science & Technology

1990-03-31

the number of hidden units and the error rates is listed in Figure 6. 3.3. Cancer Data A data qet for eva!ukting th.- Frognosis of breast cancer ...Alternative Rule Induction Methods A data set for evaluating the prognosis of breast cancer recurrence was analyzed by Michalski’s AQI5 rule induction program...AQ15 7 2 32% PVM 2 1 23% Figure 6-3: Comparative Summa-y for AQI5 and PVM on Breast Cancer Data 6.2.2. Alternative Decision Tree Induction Methods

i-LOVE: ISS-JEM lidar for observation of vegetation environment

NASA Astrophysics Data System (ADS)

Asai, Kazuhiro; Sawada, Haruo; Sugimoto, Nobuo; Mizutani, Kohei; Ishii, Shoken; Nishizawa, Tomoaki; Shimoda, Haruhisa; Honda, Yoshiaki; Kajiwara, Koji; Takao, Gen; Hirata, Yasumasa; Saigusa, Nobuko; Hayashi, Masatomo; Oguma, Hiroyuki; Saito, Hideki; Awaya, Yoshio; Endo, Takahiro; Imai, Tadashi; Murooka, Jumpei; Kobatashi, Takashi; Suzuki, Keiko; Sato, Ryota

2012-11-01

It is very important to watch the spatial distribution of vegetation biomass and changes in biomass over time, representing invaluable information to improve present assessments and future projections of the terrestrial carbon cycle. A space lidar is well known as a powerful remote sensing technology for measuring the canopy height accurately. This paper describes the ISS(International Space Station)-JEM(Japanese Experimental Module)-EF(Exposed Facility) borne vegetation lidar using a two dimensional array detector in order to reduce the root mean square error (RMSE) of tree height due to sloped surface.

Potential of two submontane broadleaved species (Acer opalus, Quercus pubescens) to reveal spatiotemporal patterns of rockfall activity

NASA Astrophysics Data System (ADS)

Favillier, Adrien; Lopez-Saez, Jérôme; Corona, Christophe; Trappmann, Daniel; Toe, David; Stoffel, Markus; Rovéra, Georges; Berger, Frédéric

2015-10-01

Long-term records of rockfalls have proven to be scarce and typically incomplete, especially in increasingly urbanized areas where inventories are largely absent and the risk associated with rockfall events rises proportionally with urbanization. On forested slopes, tree-ring analyses may help to fill this gap, as they have been demonstrated to provide annually-resolved data on past rockfall activity over long periods. Yet, the reconstruction of rockfall chronologies has been hampered in the past by the paucity of studies that include broadleaved tree species, which are, in fact, quite common in various rockfall-prone environments. In this study, we test the sensitivity of two common, yet unstudied, broadleaved species - Quercus pubescens Willd. (Qp) and Acer opalus Mill. (Ao) - to record rockfall impacts. The approach is based on a systematic mapping of trees and the counting of visible scars on the stem surface of both species. Data are presented from a site in the Vercors massif (French Alps) where rocks are frequently detached from Valanginian limestone and marl cliffs. We compare recurrence interval maps obtained from both species and from two different sets of tree structures (i.e., single trees vs. coppice stands) based on Cohen's k coefficient and the mean absolute error. A total of 1230 scars were observed on the stem surface of 847 A. opalus and Q. pubescens trees. Both methods yield comparable results on the spatial distribution of relative rockfall activity with similar downslope decreasing recurrence intervals. Yet recurrence intervals vary significantly according to tree species and tree structure. The recurrence interval observed on the stem surface of Q. pubescens exceeds that of A. opalus by > 20 years in the lower part of the studied plot. Similarly, the recurrence interval map derived from A. opalus coppice stands, dominant at the stand scale, does not exhibit a clear spatial pattern. Differences between species may be explained by the bark thickness of Q. pubescens, which has been demonstrated to grow at twice the rate of A. opalus, thus constituting a mechanical barrier that is able to buffer low energy rockfalls and thus can avoid damage to the underlying tissues. The reasons for differences between tree structures are related to the clustered coppice-specific spatial stem distribution in clumps that could result on one hand in bigger gaps between clumps, which in turn decreases the probability of tree impacts for traveling blocks. On the other hand, data also indicate that several scars on the bark of coppice stands may stem from the same impact and thus may lead to an overestimation of rockfall activity.

Tree allometry and improved estimation of carbon stocks and balance in tropical forests.

PubMed

Chave, J; Andalo, C; Brown, S; Cairns, M A; Chambers, J Q; Eamus, D; Fölster, H; Fromard, F; Higuchi, N; Kira, T; Lescure, J-P; Nelson, B W; Ogawa, H; Puig, H; Riéra, B; Yamakura, T

2005-08-01

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.

A multispecies tree ring reconstruction of Potomac River streamflow (950-2001)

NASA Astrophysics Data System (ADS)

Maxwell, R. Stockton; Hessl, Amy E.; Cook, Edward R.; Pederson, Neil

2011-05-01

Mean May-September Potomac River streamflow was reconstructed from 950-2001 using a network of tree ring chronologies (n = 27) representing multiple species. We chose a nested principal components reconstruction method to maximize use of available chronologies backward in time. Explained variance during the period of calibration ranged from 20% to 53% depending on the number and species of chronologies available in each 25 year time step. The model was verified by two goodness of fit tests, the coefficient of efficiency (CE) and the reduction of error statistic (RE). The RE and CE never fell below zero, suggesting the model had explanatory power over the entire period of reconstruction. Beta weights indicated a loss of explained variance during the 1550-1700 period that we hypothesize was caused by the reduction in total number of predictor chronologies and loss of important predictor species. Thus, the reconstruction is strongest from 1700-2001. Frequency, intensity, and duration of drought and pluvial events were examined to aid water resource managers. We found that the instrumental period did not represent adequately the full range of annual to multidecadal variability present in the reconstruction. Our reconstruction of mean May-September Potomac River streamflow was a significant improvement over the Cook and Jacoby (1983) reconstruction because it expanded the seasonal window, lengthened the record by 780 years, and better replicated the mean and variance of the instrumental record. By capitalizing on variable phenologies and tree growth responses to climate, multispecies reconstructions may provide significantly more information about past hydroclimate, especially in regions with low aridity and high tree species diversity.

Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran.

PubMed

Ramezankhani, Roghieh; Sajjadi, Nooshin; Nezakati Esmaeilzadeh, Roya; Jozi, Seyed Ali; Shirzadi, Mohammad Reza

2018-05-08

Cutaneous Leishmaniasis (CL) is a neglected tropical disease that continues to be a health problem in Iran. Nearly 350 million people are thought to be at risk. We investigated the impact of the environmental factors on CL incidence during the period 2007- 2015 in a known endemic area for this disease in Isfahan Province, Iran. After collecting data with regard to the climatic, topographic, vegetation coverage and CL cases in the study area, a decision tree model was built using the classification and regression tree algorithm. CL data for the years 2007 until 2012 were used for model construction and the data for the years 2013 until 2015 were used for testing the model. The Root Mean Square error and the correlation factor were used to evaluate the predictive performance of the decision tree model. We found that wind speeds less than 14 m/s, altitudes between 1234 and 1810 m above the mean sea level, vegetation coverage according to the normalized difference vegetation index (NDVI) less than 0.12, rainfall less than 1.6 mm and air temperatures higher than 30°C would correspond to a seasonal incidence of 163.28 per 100,000 persons, while if wind speed is less than 14 m/s, altitude less than 1,810 m and NDVI higher than 0.12, then the mean seasonal incidence of the disease would be 2.27 per 100,000 persons. Environmental factors were found to be important predictive variables for CL incidence and should be considered in surveillance and prevention programmes for CL control.

Applications of LIBS for determination of ionic species (NaCl) in electrical cables for investigation of electrical breakdown

NASA Astrophysics Data System (ADS)

Gondal, M. A.; Shwehdi, M. H.; Khalil, A. A. I.

2011-12-01

The formation of water trees in high-voltage cables can wreak havoc to power systems. The water tree is produced within the high voltage cable insulator when impurities like sodium and magnesium present in the insulating material react with moist soil to form chlorides. This water tree causes electrical breakdown by short circuiting the metallic conductor and the earth. In this paper we use laser-induced breakdown spectroscopy (LIBS) to detect the potentially dangerous elements that form the water tree in the insulating cable. The LIBS system used for this work consists of the fundamental (1064 nm) of a Nd:YAG laser, four spectrometer modules that cover the visible and near-UV spectral ranges and an ICCD camera with proper delay and gating sequence. With this arrangement we were able to measure the elemental concentrations of trace metals present in the insulating cable. The concentrations measured with our LIBS system were counter checked by a standard technique like inductively coupled plasma (ICP) emission spectrometry. The maximum concentrations for ionic species such as Ba (455.40 nm), Ca (393.36 nm), Cr (267.71 nm), Fe (259.94 nm), Cl (542.3 nm), Mg (516.7 nm), Mn (257.61 nm), Na (589.59 nm) and Ti (334.18 nm) are 20.6, 43.2, 1.6, 148.4, 24.2, 22.1, 4.2, 39.56 and 4.35 ppm, respectively. The relative accuracy of our LIBS system for various elements as compared with the ICP method is in the range of 0.03-0.6 at 2.5% error confidence.

Improving LiDAR Biomass Model Uncertainty through Non-Destructive Allometry and Plot-level 3D Reconstruction with Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Stovall, A. E.; Shugart, H. H., Jr.

2017-12-01

Future NASA and ESA satellite missions plan to better quantify global carbon through detailed observations of forest structure, but ultimately rely on uncertain ground measurement approaches for calibration and validation. A significant amount of the uncertainty in estimating plot-level biomass can be attributed to inadequate and unrepresentative allometric relationships used to convert plot-level tree measurements to estimates of aboveground biomass. These allometric equations are known to have high errors and biases, particularly in carbon rich forests because they were calibrated with small and often biased samples of destructively harvested trees. To overcome this issue, a non-destructive methodology for estimating tree and plot-level biomass has been proposed through the use of Terrestrial Laser Scanning (TLS). We investigated the potential for using TLS as a ground validation approach in LiDAR-based biomass mapping though virtual plot-level tree volume reconstruction and biomass estimation. Plot-level biomass estimates were compared on the Virginia-based Smithsonian Conservation Biology Institute's SIGEO forest with full 3D reconstruction, TLS allometry, and Jenkins et al. (2003) allometry. On average, full 3D reconstruction ultimately provided the lowest uncertainty estimate of plot-level biomass (9.6%), followed by TLS allometry (16.9%) and the national equations (20.2%). TLS offered modest improvements to the airborne LiDAR empirical models, reducing RMSE from 16.2% to 14%. Our findings suggest TLS plot acquisitions and non-destructive allometry can play a vital role for reducing uncertainty in calibration and validation data for biomass mapping in the upcoming NASA and ESA missions.

Design of tree structured matched wavelet for HRV signals of menstrual cycle.

PubMed

Rawal, Kirti; Saini, B S; Saini, Indu

2016-07-01

An algorithm is presented for designing a new class of wavelets matched to the Heart Rate Variability (HRV) signals of the menstrual cycle. The proposed wavelets are used to find HRV variations between phases of menstrual cycle. The method finds the signal matching characteristics by minimising the shape feature error using Least Mean Square method. The proposed filter banks are used for the decomposition of the HRV signal. For reconstructing the original signal, the tree structure method is used. In this approach, decomposed sub-bands are selected based upon their energy in each sub-band. Thus, instead of using all sub-bands for reconstruction, sub-bands having high energy content are used for the reconstruction of signal. Thus, a lower number of sub-bands are required for reconstruction of the original signal which shows the effectiveness of newly created filter coefficients. Results show that proposed wavelets are able to differentiate HRV variations between phases of the menstrual cycle accurately than standard wavelets.

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

A New Framework for Adptive Sampling and Analysis During Long-Term Monitoring and Remedial Action Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minsker, Barbara

2005-06-01

Yonas Demissie, a research assistant supported by the project, has successfully created artificial data and assimilated it into coupled Modflow and artificial neural network models. His initial findings show that the neural networks help correct errors in the Modflow models. Abhishek Singh has used test cases from the literature to show that performing model calibration with an interactive genetic algorithm results in significantly improved parameter values. Meghna Babbar, the third research assistant supported by the project, has found similar results when applying an interactive genetic algorithms to long-term monitoring design. She has also developed new types of interactive genetic algorithmsmore » that significantly improve performance. Gayathri Gopalakrishnan, the last research assistant who is partially supported by the project, has shown that sampling branches of phytoremediation trees is an accurate approach to estimating soil and groundwater contaminations in areas surrounding the trees at the Argonne 317/319 site.« less

Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures

PubMed Central

Moore, Brian R.; Höhna, Sebastian; May, Michael R.; Rannala, Bruce; Huelsenbeck, John P.

2016-01-01

Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM. PMID:27512038

Paleo Data Assimilation of Pseudo-Tree-Ring-Width Chronologies in a Climate Model

NASA Astrophysics Data System (ADS)

Fallah Hassanabadi, B.; Acevedo, W.; Reich, S.; Cubasch, U.

2016-12-01

Using the Time-Averaged Ensemble Kalman Filter (EnKF) and a forward model, we assimilate the pseudo Tree-Ring-Width (TRW) chronologies into an Atmospheric Global Circulation model. This study investigates several aspects of Paleo-Data Assimilation (PDA) within a perfect-model set-up: (i) we test the performance of several forward operators in the framework of a PDA-based climate reconstruction, (ii) compare the PDA-based simulations' skill against the free ensemble runs and (iii) inverstigate the skill of the "online" (with cycling) DA and the "off-line" (no-cycling) DA. In our experiments, the "online" (with cycling) PDA approach did not outperform the "off-line" (no-cycling) one, despite its considerable additional implementation complexity. On the other hand, it was observed that the error reduction achieved by assimilating a particular pseudo-TRW chronology is modulated by the strength of the yearly internal variability of the model at the chronology site. This result might help the dendrochronology community to optimize their sampling efforts.

Models for H₃ receptor antagonist activity of sulfonylurea derivatives.

PubMed

Khatri, Naveen; Madan, A K

2014-03-01

The histamine H₃ receptor has been perceived as an auspicious target for the treatment of various central and peripheral nervous system diseases. In present study, a wide variety of 60 2D and 3D molecular descriptors (MDs) were successfully utilized for the development of models for the prediction of antagonist activity of sulfonylurea derivatives for histamine H₃ receptors. Models were developed through decision tree (DT), random forest (RF) and moving average analysis (MAA). Dragon software version 6.0.28 was employed for calculation of values of diverse MDs of each analogue involved in the data set. The DT classified and correctly predicted the input data with an impressive non-error rate of 94% in the training set and 82.5% during cross validation. RF correctly classified the analogues into active and inactive with a non-error rate of 79.3%. The MAA based models predicted the antagonist histamine H₃ receptor activity with non-error rate up to 90%. Active ranges of the proposed MAA based models not only exhibited high potency but also showed improved safety as indicated by relatively high values of selectivity index. The statistical significance of the models was assessed through sensitivity, specificity, non-error rate, Matthew's correlation coefficient and intercorrelation analysis. Proposed models offer vast potential for providing lead structures for development of potent but safe H₃ receptor antagonist sulfonylurea derivatives. Copyright © 2013 Elsevier Inc. All rights reserved.

NIR spectroscopic measurement of moisture content in Scots pine seeds.

PubMed

Lestander, Torbjörn A; Geladi, Paul

2003-04-01

When tree seeds are used for seedling production it is important that they are of high quality in order to be viable. One of the factors influencing viability is moisture content and an ideal quality control system should be able to measure this factor quickly for each seed. Seed moisture content within the range 3-34% was determined by near-infrared (NIR) spectroscopy on Scots pine (Pinus sylvestris L.) single seeds and on bulk seed samples consisting of 40-50 seeds. The models for predicting water content from the spectra were made by partial least squares (PLS) and ordinary least squares (OLS) regression. Different conditions were simulated involving both using less wavelengths and going from samples to single seeds. Reflectance and transmission measurements were used. Different spectral pretreatment methods were tested on the spectra. Including bias, the lowest prediction errors for PLS models based on reflectance within 780-2280 nm from bulk samples and single seeds were 0.8% and 1.9%, respectively. Reduction of the single seed reflectance spectrum to 850-1048 nm gave higher biases and prediction errors in the test set. In transmission (850-1048 nm) the prediction error was 2.7% for single seeds. OLS models based on simulated 4-sensor single seed system consisting of optical filters with Gaussian transmission indicated more than 3.4% error in prediction. A practical F-test based on test sets to differentiate models is introduced.

Systems engineering analysis of five 'as-manufactured' SXI telescopes

NASA Astrophysics Data System (ADS)

Harvey, James E.; Atanassova, Martina; Krywonos, Andrey

2005-09-01

Four flight models and a spare of the Solar X-ray Imager (SXI) telescope mirrors have been fabricated. The first of these is scheduled to be launched on the NOAA GOES- N satellite on July 29, 2005. A complete systems engineering analysis of the "as-manufactured" telescope mirrors has been performed that includes diffraction effects, residual design errors (aberrations), surface scatter effects, and all of the miscellaneous errors in the mirror manufacturer's error budget tree. Finally, a rigorous analysis of mosaic detector effects has been included. SXI is a staring telescope providing full solar disc images at X-ray wavelengths. For wide-field applications such as this, a field-weighted-average measure of resolution has been modeled. Our performance predictions have allowed us to use metrology data to model the "as-manufactured" performance of the X-ray telescopes and to adjust the final focal plane location to optimize the number of spatial resolution elements in a given operational field-of-view (OFOV) for either the aerial image or the detected image. The resulting performance predictions from five separate mirrors allow us to evaluate and quantify the optical fabrication process for producing these very challenging grazing incidence X-ray optics.

Tadpole-improved SU(2) lattice gauge theory

NASA Astrophysics Data System (ADS)

Shakespeare, Norman H.; Trottier, Howard D.

1999-01-01

A comprehensive analysis of tadpole-improved SU(2) lattice gauge theory is made. Simulations are done on isotropic and anisotropic lattices, with and without improvement. Two tadpole renormalization schemes are employed, one using average plaquettes, the other using mean links in the Landau gauge. Simulations are done with spatial lattice spacings as in the range of about 0.1-0.4 fm. Results are presented for the static quark potential, the renormalized lattice anisotropy at/as (where at is the ``temporal'' lattice spacing), and for the scalar and tensor glueball masses. Tadpole improvement significantly reduces discretization errors in the static quark potential and in the scalar glueball mass, and results in very little renormalization of the bare anisotropy that is input to the action. We also find that tadpole improvement using mean links in the Landau gauge results in smaller discretization errors in the scalar glueball mass (as well as in the static quark potential), compared to when average plaquettes are used. The possibility is also raised that further improvement in the scalar glueball mass may result when the coefficients of the operators which correct for discretization errors in the action are computed beyond the tree level.

The Extended HANDS Characterization and Analysis of Metric Biases

NASA Astrophysics Data System (ADS)

Kelecy, T.; Knox, R.; Cognion, R.

The Extended High Accuracy Network Determination System (Extended HANDS) consists of a network of low cost, high accuracy optical telescopes designed to support space surveillance and development of space object characterization technologies. Comprising off-the-shelf components, the telescopes are designed to provide sub arc-second astrometric accuracy. The design and analysis team are in the process of characterizing the system through development of an error allocation tree whose assessment is supported by simulation, data analysis, and calibration tests. The metric calibration process has revealed 1-2 arc-second biases in the right ascension and declination measurements of reference satellite position, and these have been observed to have fairly distinct characteristics that appear to have some dependence on orbit geometry and tracking rates. The work presented here outlines error models developed to aid in development of the system error budget, and examines characteristic errors (biases, time dependence, etc.) that might be present in each of the relevant system elements used in the data collection and processing, including the metric calibration processing. The relevant reference frames are identified, and include the sensor (CCD camera) reference frame, Earth-fixed topocentric frame, topocentric inertial reference frame, and the geocentric inertial reference frame. The errors modeled in each of these reference frames, when mapped into the topocentric inertial measurement frame, reveal how errors might manifest themselves through the calibration process. The error analysis results that are presented use satellite-sensor geometries taken from periods where actual measurements were collected, and reveal how modeled errors manifest themselves over those specific time periods. These results are compared to the real calibration metric data (right ascension and declination residuals), and sources of the bias are hypothesized. In turn, the actual right ascension and declination calibration residuals are also mapped to other relevant reference frames in an attempt to validate the source of the bias errors. These results will serve as the basis for more focused investigation into specific components embedded in the system and system processes that might contain the source of the observed biases.

Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

NASA Astrophysics Data System (ADS)

Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.

2017-12-01

Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. Since sub-daily streamflow information is unavailable for most small basins in China, one of the main challenges is finding appropriate parameter values for simulating flash floods in ungauged catchments. In this study, we use decision tree learning to explore parameter set transferability between different catchments. For this purpose, the physically-based, semi-distributed rainfall-runoff model PRMS-OMS is set up for 35 catchments in ten Chinese provinces. Hourly data from more than 800 storm runoff events are used to calibrate the model and evaluate the performance of parameter set transfers between catchments. For each catchment, 58 catchment attributes are extracted from several data sets available for whole China. We then use a data mining technique (decision tree learning) to identify catchment similarities that can be related to good transfer performance. Finally, we use the splitting rules of decision trees for finding suitable donor catchments for ungauged target catchments. We show that decision tree learning allows to optimally utilize the information content of available catchment descriptors and outperforms regionalization based on a conventional measure of physiographic-climatic similarity by 15%-20%. Similar performance can be achieved with a regionalization method based on spatial proximity, but decision trees offer flexible rules for selecting suitable donor catchments, not relying on the vicinity of gauged catchments. This flexibility makes the method particularly suitable for implementation in sparsely gauged environments. We evaluate the probability to detect flood events exceeding a given return period, considering measured discharge and PRMS-OMS simulated flows with regionalized parameters. Overall, the probability of detection of an event with a return period of 10 years is 62%. 44% of all 10-year flood peaks can be detected with a timing error of 2 hours or less. These results indicate that the modeling system can provide useful information about the timing and magnitude of flood events at ungauged sites.

Application of DNA Barcodes in Asian Tropical Trees--A Case Study from Xishuangbanna Nature Reserve, Southwest China.

PubMed

Huang, Xiao-cui; Ci, Xiu-qin; Conran, John G; Li, Jie

2015-01-01

Within a regional floristic context, DNA barcoding is more useful to manage plant diversity inventories on a large scale and develop valuable conservation strategies. However, there are no DNA barcode studies from tropical areas of China, which represents one of the biodiversity hotspots around the world. A DNA barcoding database of an Asian tropical trees with high diversity was established at Xishuangbanna Nature Reserve, Yunnan, southwest China using rbcL and matK as standard barcodes, as well as trnH-psbA and ITS as supplementary barcodes. The performance of tree species identification success was assessed using 2,052 accessions from four plots belonging to two vegetation types in the region by three methods: Neighbor-Joining, Maximum-Likelihood and BLAST. We corrected morphological field identification errors (9.6%) for the three plots using rbcL and matK based on Neighbor-Joining tree. The best barcode region for PCR and sequencing was rbcL (97.6%, 90.8%), followed by trnH-psbA (93.6%, 85.6%), while matK and ITS obtained relative low PCR and sequencing success rates. However, ITS performed best for both species (44.6-58.1%) and genus (72.8-76.2%) identification. With trnH-psbA slightly less effective for species identification. The two standard barcode rbcL and matK gave poor results for species identification (24.7-28.5% and 31.6-35.3%). Compared with other studies from comparable tropical forests (e.g. Cameroon, the Amazon and India), the overall performance of the four barcodes for species identification was lower for the Xishuangbanna Nature Reserve, possibly because of species/genus ratios and species composition between these tropical areas. Although the core barcodes rbcL and matK were not suitable for species identification of tropical trees from Xishuangbanna Nature Reserve, they could still help with identification at the family and genus level. Considering the relative sequence recovery and the species identification performance, we recommend the use of trnH-psbA and ITS in combination as the preferred barcodes for tropical tree species identification in China.

A combined M5P tree and hazard-based duration model for predicting urban freeway traffic accident durations.

PubMed

Lin, Lei; Wang, Qian; Sadek, Adel W

2016-06-01

The duration of freeway traffic accidents duration is an important factor, which affects traffic congestion, environmental pollution, and secondary accidents. Among previous studies, the M5P algorithm has been shown to be an effective tool for predicting incident duration. M5P builds a tree-based model, like the traditional classification and regression tree (CART) method, but with multiple linear regression models as its leaves. The problem with M5P for accident duration prediction, however, is that whereas linear regression assumes that the conditional distribution of accident durations is normally distributed, the distribution for a "time-to-an-event" is almost certainly nonsymmetrical. A hazard-based duration model (HBDM) is a better choice for this kind of a "time-to-event" modeling scenario, and given this, HBDMs have been previously applied to analyze and predict traffic accidents duration. Previous research, however, has not yet applied HBDMs for accident duration prediction, in association with clustering or classification of the dataset to minimize data heterogeneity. The current paper proposes a novel approach for accident duration prediction, which improves on the original M5P tree algorithm through the construction of a M5P-HBDM model, in which the leaves of the M5P tree model are HBDMs instead of linear regression models. Such a model offers the advantage of minimizing data heterogeneity through dataset classification, and avoids the need for the incorrect assumption of normality for traffic accident durations. The proposed model was then tested on two freeway accident datasets. For each dataset, the first 500 records were used to train the following three models: (1) an M5P tree; (2) a HBDM; and (3) the proposed M5P-HBDM, and the remainder of data were used for testing. The results show that the proposed M5P-HBDM managed to identify more significant and meaningful variables than either M5P or HBDMs. Moreover, the M5P-HBDM had the lowest overall mean absolute percentage error (MAPE). Copyright © 2016 Elsevier Ltd. All rights reserved.

Using certification trails to achieve software fault tolerance

NASA Technical Reports Server (NTRS)

Sullivan, Gregory F.; Masson, Gerald M.

1993-01-01

A conceptually novel and powerful technique to achieve fault tolerance in hardware and software systems is introduced. When used for software fault tolerance, this new technique uses time and software redundancy and can be outlined as follows. In the initial phase, a program is run to solve a problem and store the result. In addition, this program leaves behind a trail of data called a certification trail. In the second phase, another program is run which solves the original problem again. This program, however, has access to the certification trail left by the first program. Because of the availability of the certification trail, the second phase can be performed by a less complex program and can execute more quickly. In the final phase, the two results are accepted as correct; otherwise an error is indicated. An essential aspect of this approach is that the second program must always generate either an error indication or a correct output even when the certification trail it receives from the first program is incorrect. The certification trail approach to fault tolerance was formalized and it was illustrated by applying it to the fundamental problem of finding a minimum spanning tree. Cases in which the second phase can be run concorrectly with the first and act as a monitor are discussed. The certification trail approach was compared to other approaches to fault tolerance. Because of space limitations we have omitted examples of our technique applied to the Huffman tree, and convex hull problems. These can be found in the full version of this paper.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

Inspection and Verification of Domain Models with PlanWorks and Aver

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Frank, Jeremy; Iatauro, Michael; McGann, Conor

2006-01-01

When developing a domain model, it seems natural to bring the traditional informal tools of inspection and verification, debuggers and automated test suites, to bear upon the problems that will inevitably arise. Debuggers that allow inspection of registers and memory and stepwise execution have been a staple of software development of all sorts from the very beginning. Automated testing has repeatedly proven its considerable worth, to the extent that an entire design philosophy (Test Driven Development) has been developed around the writing of tests. Unfortunately, while not entirely without their uses, the limitations of these tools and the nature of the complexity of models and the underlying planning systems make the diagnosis of certain classes of problems and the verification of their solutions difficult or impossible. Debuggers provide a good local view of executing code, allowing a fine-grained look at algorithms and data. This view is, however, usually only at the level of the current scope in the implementation language, and the data-inspection capabilities of most debuggers usually consist of on-line print statements. More modem graphical debuggers offer a sort of tree view of data structures, but even this is too low-level and is often inappropriate for the kinds of structures created by planning systems. For instance, god or constraint networks are at best awkward when visualized as trees. Any any non-structural link between data structures, as through a lookup table, isn't captured at all. Further, while debuggers have powerful breakpointing facilities that are suitable for finding specific algorithmic errors, they have little use in the diagnosis of modeling errors.

Barcoding Neotropical birds: assessing the impact of nonmonophyly in a highly diverse group.

PubMed

Chaves, Bárbara R N; Chaves, Anderson V; Nascimento, Augusto C A; Chevitarese, Juliana; Vasconcelos, Marcelo F; Santos, Fabrício R

2015-07-01

In this study, we verified the power of DNA barcodes to discriminate Neotropical birds using Bayesian tree reconstructions of a total of 7404 COI sequences from 1521 species, including 55 Brazilian species with no previous barcode data. We found that 10.4% of species were nonmonophyletic, most likely due to inaccurate taxonomy, incomplete lineage sorting or hybridization. At least 0.5% of the sequences (2.5% of the sampled species) retrieved from GenBank were associated with database errors (poor-quality sequences, NuMTs, misidentification or unnoticed hybridization). Paraphyletic species (5.8% of the total) can be related to rapid speciation events leading to nonreciprocal monophyly between recently diverged sister species, or to absence of synapomorphies in the small COI region analysed. We also performed two series of genetic distance calculations under the K2P model for intraspecific and interspecific comparisons: the first included all COI sequences, and the second included only monophyletic taxa observed in the Bayesian trees. As expected, the mean and median pairwise distances were smaller for intraspecific than for interspecific comparisons. However, there was no precise 'barcode gap', which was shown to be larger in the monophyletic taxon data set than for the data from all species, as expected. Our results indicated that although database errors may explain some of the difficulties in the species discrimination of Neotropical birds, distance-based barcode assignment may also be compromised because of the high diversity of bird species and more complex speciation events in the Neotropics. © 2014 John Wiley & Sons Ltd.

Simulation of Longwave Enhancement beneath Montane and Boreal Forests in CLM4.5

NASA Astrophysics Data System (ADS)

Todt, M.; Rutter, N.; Fletcher, C. G.; Wake, L. M.; Loranty, M. M.

2017-12-01

CMIP5 models have been shown to underestimate both trend and variability in northern hemisphere spring snow cover extent. A substantial fraction of this area is covered by boreal forests, in which the snow energy balance is dominated by radiation. Forest coverage impacts the surface radiation budget by shading the ground and enhancing longwave radiation. Longwave enhancement in boreal forests is a potential mechanism that contributes to uncertainty in snowmelt modelling, however, its impact on snowmelt in global land models has not been analysed yet. This study assesses the simulation of sub-canopy longwave radiation and longwave enhancement by CLM4.5, the land component of the NCAR Community Earth System Model, in which boreal forests are represented by three plant functional types (PFT): evergreen needleleaf trees (ENT), deciduous needleleaf trees (DNT), and deciduous broadleaf trees (DBT). Simulation of sub-canopy longwave enhancement is evaluated at boreal forest sites covering the three boreal PFT in CLM4.5 to assess the dependence of simulation errors on meteorological forcing, vegetation type and vegetation density. ENT are evaluated over a total of six snowmelt seasons in Swiss alpine and subalpine forests, as well as a single season at a Finnish arctic site with varying vegetation density. A Swedish artic site features varying vegetation density for DBT for a single winter, and two sites in Eastern Siberia are included covering a total of four snowmelt seasons in DNT forests. CLM4.5 overestimates the diurnal range of sub-canopy longwave radiation and consequently longwave enhancement, overestimating daytime values and underestimating nighttime values. Simulation errors result mainly from clear sky conditions, due to high absorption of shortwave radiation during daytime and radiative cooling during nighttime. Using recent improvements to the canopy parameterisations of SNOWPACK as a guideline, CLM4.5 simulations of sub-canopy longwave radiation improved through the implementation of a heat mass parameterisation, i.e. including thermal inertia due to biomass. However, this improvement does not substantially reduce the amplitude of the diurnal cycle, a result also found during the development of SNOWPACK.

Noninvasive calculation of the aortic blood pressure waveform from the flow velocity waveform: a proof of concept.

PubMed

Vennin, Samuel; Mayer, Alexia; Li, Ye; Fok, Henry; Clapp, Brian; Alastruey, Jordi; Chowienczyk, Phil

2015-09-01

Estimation of aortic and left ventricular (LV) pressure usually requires measurements that are difficult to acquire during the imaging required to obtain concurrent LV dimensions essential for determination of LV mechanical properties. We describe a novel method for deriving aortic pressure from the aortic flow velocity. The target pressure waveform is divided into an early systolic upstroke, determined by the water hammer equation, and a diastolic decay equal to that in the peripheral arterial tree, interposed by a late systolic portion described by a second-order polynomial constrained by conditions of continuity and conservation of mean arterial pressure. Pulse wave velocity (PWV, which can be obtained through imaging), mean arterial pressure, diastolic pressure, and diastolic decay are required inputs for the algorithm. The algorithm was tested using 1) pressure data derived theoretically from prespecified flow waveforms and properties of the arterial tree using a single-tube 1-D model of the arterial tree, and 2) experimental data acquired from a pressure/Doppler flow velocity transducer placed in the ascending aorta in 18 patients (mean ± SD: age 63 ± 11 yr, aortic BP 136 ± 23/73 ± 13 mmHg) at the time of cardiac catheterization. For experimental data, PWV was calculated from measured pressures/flows, and mean and diastolic pressures and diastolic decay were taken from measured pressure (i.e., were assumed to be known). Pressure reconstructed from measured flow agreed well with theoretical pressure: mean ± SD root mean square (RMS) error 0.7 ± 0.1 mmHg. Similarly, for experimental data, pressure reconstructed from measured flow agreed well with measured pressure (mean RMS error 2.4 ± 1.0 mmHg). First systolic shoulder and systolic peak pressures were also accurately rendered (mean ± SD difference 1.4 ± 2.0 mmHg for peak systolic pressure). This is the first noninvasive derivation of aortic pressure based on fluid dynamics (flow and wave speed) in the aorta itself. Copyright © 2015 the American Physiological Society.

An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS-CTEM modelling framework

NASA Astrophysics Data System (ADS)

Shrestha, Rudra K.; Arora, Vivek K.; Melton, Joe R.; Sushama, Laxmi

2017-10-01

The performance of the competition module of the CLASS-CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model) modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs) with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200-300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI) values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD) reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of permafrost will help improve model performance.

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

PubMed

Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny

2016-06-01

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). © 2015 John Wiley & Sons Ltd.

Forest structures retrieval from LiDAR onboard ULA

NASA Astrophysics Data System (ADS)

Shang, Xiaoxia; Chazette, Patrick; Totems, Julien; Marnas, Fabien; Sanak, Joseph

2013-04-01

Following the United Nations Framework Convention on Climate Change, the assessment of forest carbon stock is one of the main elements for a better understanding of the carbon cycle and its evolution following the climate change. The forests sequester 80% of the continental biospheric carbon and this efficiency is a function of the tree species and the tree health. The airborne backscatter LiDAR onboard the ultra light aircraft (ULA) can provide the key information on the forest vertical structures and evolution in the time. The most important structural parameter is the tree top height, which is directly linked to the above-ground biomass using non-linear relationships. In order to test the LiDAR capability for retrieving the tree top height, the LiDAR ULICE (Ultraviolet LIdar for Canopy Experiment) has been used over different forest types, from coniferous (maritime pins) to deciduous (oaks, hornbeams ...) trees. ULICE works at the wavelength of 355 nm with a sampling along the line-of-sight between 15 and 75 cm. According to the LiDAR signal to noise ratio (SNR), two different algorithms have been used in our study. The first algorithm is a threshold method directly based on the comparison between the LiDAR signal and the noise distributions, while the second one used a low pass filter by fitting a Gaussian curve family. In this paper, we will present these two algorithms and their evolution as a function of the SNR. The main error sources will be also discussed and assessed for each algorithm. The results show that these algorithms have great potential for ground-segment of future space borne LiDAR missions dedicated to the forest survey at the global scale. Acknowledgements: the canopy LiDAR system ULICE has been developed by CEA (Commissariat à l'Energie Atomique). It has been deployed with the support of CNES (Centre National d'Etude Spariales) and ANR (Agence Nationale de la Recherche). We acknowledge the ULA pilots Franck Toussaint for logistical help during the ULA campaign.

The timing of bud burst and its effect on tree growth.

PubMed

Rötzer, T; Grote, R; Pretzsch, H

2004-02-01

A phenology model for estimating the timings of bud burst--one of the most influential phenological phases for the simulation of tree growth--is presented in this study. The model calculates the timings of the leafing of beech (Fagus sylvatica L.) and oak (Quercus robur L.) and the May shoot of Norway spruce (Picea abies L.) and Scots pine (Pinus sylvestris L.) on the basis of the daily maximum temperature. The data for parameterisation and validation of the model have been taken from 40 climate and 120 phenological stations in southern Germany with time series for temperature and bud burst of up to 30 years. The validation of the phenology module by means of an independent data set showed correlation coefficients for comparisons between observed and simulated values of 54% (beech), 55% (oak), 59% (spruce) and 56% (pine) with mean absolute errors varying from 4.4 days (spruce) to 5.0 days (pine). These results correspond well with the results of other--often more complex--phenology models. After the phenology module had been implemented in the tree-growth model BALANCE, the growth of a mixed forest stand with the former static and the new dynamic timings for the bud burst was simulated. The results of the two simulation runs showed that phenology has to be taken into account when simulating forest growth, particularly in mixed stands.

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller

NASA Astrophysics Data System (ADS)

Perdikis, S.; Leeb, R.; Williamson, J.; Ramsay, A.; Tavella, M.; Desideri, L.; Hoogerwerf, E.-J.; Al-Khodairy, A.; Murray-Smith, R.; Millán, J. d. R.

2014-06-01

Objective. While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. Approach. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. Main results. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. Significance. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller.

PubMed

Perdikis, S; Leeb, R; Williamson, J; Ramsay, A; Tavella, M; Desideri, L; Hoogerwerf, E-J; Al-Khodairy, A; Murray-Smith, R; Millán, J D R

2014-06-01

While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Windthrows increase soil carbon stocks in a Central Amazon forest

NASA Astrophysics Data System (ADS)

dos Santos, L. T.; Magnabosco Marra, D.; Trumbore, S.; Camargo, P. B.; Chambers, J. Q.; Negrón-Juárez, R. I.; Lima, A. J. N.; Ribeiro, G. H. P. M.; dos Santos, J.; Higuchi, N.

2015-12-01

Windthrows change forest structure and species composition in Central Amazon forests. However, the effects of widespread tree mortality associated with wind-disturbances on soil properties have not yet been described. In this study, we investigated short-term effects (seven years after disturbance) of a windthrow event on soil carbon stocks and concentrations in a Central Amazon terra firme forest. The soil carbon stock (averaged over a 0-30 cm depth profile) in disturbed plots (61.4 ± 4.18 Mg ha-1, mean ± standard error) was marginally higher (p = 0.009) than that from undisturbed plots (47.7 ± 6.95 Mg ha-1). The soil organic carbon concentration in disturbed plots (2.0 ± 0.08 %) was significantly higher (p < 0.001) than that from undisturbed plots (1.36 ± 0.12 %). Moreover, soil carbon stocks were positively correlated with soil clay content (r = 0.575 and p = 0.019) and with tree mortality intensity (r = 0.493 and p = 0.045). Our results indicate that large inputs of plant litter associated with large windthrow events cause a short-term increase in soil carbon content, and the degree of increase is related to soil clay content and tree mortality intensity. Higher nutrient availability in soils from large canopy gaps created by wind disturbance may increase vegetation resilience and favor forest recovery.

Data compression of discrete sequence: A tree based approach using dynamic programming

NASA Technical Reports Server (NTRS)

Shivaram, Gurusrasad; Seetharaman, Guna; Rao, T. R. N.

1994-01-01

A dynamic programming based approach for data compression of a ID sequence is presented. The compression of an input sequence of size N to that of a smaller size k is achieved by dividing the input sequence into k subsequences and replacing the subsequences by their respective average values. The partitioning of the input sequence is carried with the intention of reducing the mean squared error in the reconstructed sequence. The complexity involved in finding the partitions which would result in such an optimal compressed sequence is reduced by using the dynamic programming approach, which is presented.

A precise determination of α using B0 →ρ+ρ- and B+ →K∗0ρ+

NASA Astrophysics Data System (ADS)

Beneke, M.; Gronau, M.; Rohrer, J.; Spranger, M.

2006-06-01

The effect of the penguin amplitude on extracting α from CP asymmetries in B0 →ρ+ρ- decays is studied using information on the SU(3)-related penguin amplitude in B+ →K∗0ρ+. Conservative bounds on non-factorizable SU(3) breaking, small amplitudes, and the strong phase difference between tree and penguin amplitudes, are shown to reduce the error in α in comparison with the one obtained using isospin symmetry in B → ρρ. Current measurements imply α = [ 90 ± 7 (exp)-5+2 (th) ] °.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robison, W L; Hamilton, T F; Bogen, K

Inter-plant concentration ratios (IPCR), [Bq g{sup -1} {sup 137}Cs in coral atoll tree food-crops/Bq g{sup -1} {sup 137}Cs in leaves of native plant species whose roots share a common soil volume], can replace transfer factors (TF) to predict {sup 137}Cs concentration in tree food-crops in a contaminated area with an aged source term. The IPCR strategy has significant benefits relative to TF strategy for such purposes in the atoll ecosystem. IPCR strategy applied to specific assessments takes advantage of the fact tree roots naturally integrate 137Cs over large volumes of soil. Root absorption of {sup 137}Cs replaces large-scale, expensive soilmore » sampling schemes to reduce variability in {sup 137}Cs concentration due to inhomogeneous radionuclide distribution. IPCR [drinking-coconut meat (DCM)/Scaevola (SCA) and Tournefortia (TOU) leaves (native trees growing on all atoll islands)] are log normally distributed (LND) with geometric standard deviation (GSD) = 1.85. TF for DCM from Enewetak, Eneu, Rongelap and Bikini Atolls are LND with GSD's of 3.5, 3.0, 2.7, and 2.1, respectively. TF GSD for Rongelap copra coconut meat is 2.5. IPCR of Pandanus fruit to SCA and TOU leaves are LND with GSD = 1.7 while TF GSD is 2.1. Because IPCR variability is much lower than TF variability, relative sampling error of an IPCR field sample mean is up 6- to 10-fold lower than that of a TF sample mean if sample sizes are small (10 to 20). Other IPCR advantages are that plant leaf samples are collected and processed in far less time with much less effort and cost than soil samples.« less

Convergence properties of halo merger trees; halo and substructure merger rates across cosmic history

NASA Astrophysics Data System (ADS)

Poole, Gregory B.; Mutch, Simon J.; Croton, Darren J.; Wyithe, Stuart

2017-12-01

We introduce GBPTREES: an algorithm for constructing merger trees from cosmological simulations, designed to identify and correct for pathological cases introduced by errors or ambiguities in the halo finding process. GBPTREES is built upon a halo matching method utilizing pseudo-radial moments constructed from radially sorted particle ID lists (no other information is required) and a scheme for classifying merger tree pathologies from networks of matches made to-and-from haloes across snapshots ranging forward-and-backward in time. Focusing on SUBFIND catalogues for this work, a sweep of parameters influencing our merger tree construction yields the optimal snapshot cadence and scanning range required for converged results. Pathologies proliferate when snapshots are spaced by ≲0.128 dynamical times; conveniently similar to that needed for convergence of semi-analytical modelling, as established by Benson et al. Total merger counts are converged at the level of ∼5 per cent for friends-of-friends (FoF) haloes of size np ≳ 75 across a factor of 512 in mass resolution, but substructure rates converge more slowly with mass resolution, reaching convergence of ∼10 per cent for np ≳ 100 and particle mass mp ≲ 109 M⊙. We present analytic fits to FoF and substructure merger rates across nearly all observed galactic history (z ≤ 8.5). While we find good agreement with the results presented by Fakhouri et al. for FoF haloes, a slightly flatter dependence on merger ratio and increased major merger rates are found, reducing previously reported discrepancies with extended Press-Schechter estimates. When appropriately defined, substructure merger rates show a similar mass ratio dependence as FoF rates, but with stronger mass and redshift dependencies for their normalization.

CFD simulation of pesticide spray from air-assisted sprayers in an apple orchard: Tree deposition and off-target losses

NASA Astrophysics Data System (ADS)

Hong, Se-Woon; Zhao, Lingying; Zhu, Heping

2018-02-01

The ultimate goal of a pesticide spraying system is to provide adequate coverage on intended canopies with a minimum amount of spray materials and off-target waste. Better spray coverage requires an understanding of the fate and transport of spray droplets carried by turbulent airflows in orchards. In this study, an integrated computational fluid dynamics (CFD) model was developed to predict displacement of pesticide spray droplets discharged from an air-assisted sprayer, depositions onto tree canopies, and off-target deposition and airborne drift in an apple orchard. Pesticide droplets discharged from a moving sprayer were tracked using the Lagrangian particle transport model, and the deposition model was applied to droplets entering porous canopy zones. Measurements of the droplet deposition and drift in the same orchard were used to validate the model simulations. Good agreement was found between the measured and simulated spray concentrations inside tree canopies and off-target losses (ground deposition and airborne drifts) with the overall relative errors of 22.1% and 40.6%, respectively, under three growth stages. The CFD model was able to estimate the mass balance of pesticide droplets in the orchard, which was practically difficult to investigate by measurements in field conditions. As the foliage of trees became denser, spray deposition inside canopies increased from 8.5% to 65.8% and airborne drift and ground deposition decreased from 25.8% to 7.0% and 47.8% to 21.2%, respectively. Higher wind speed also increased the spray airborne drift downwind of the orchard. This study demonstrates that CFD model can be used to evaluate spray application performance and design and operate sprayers with increased spray efficiencies and reduced drift potentials.

After more than a decade of soil moisture deficit, tropical rainforest trees maintain photosynthetic capacity, despite increased leaf respiration.

PubMed

Rowland, Lucy; Lobo-do-Vale, Raquel L; Christoffersen, Bradley O; Melém, Eliane A; Kruijt, Bart; Vasconcelos, Steel S; Domingues, Tomas; Binks, Oliver J; Oliveira, Alex A R; Metcalfe, Daniel; da Costa, Antonio C L; Mencuccini, Maurizio; Meir, Patrick

2015-12-01

Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more than 12 years of experimental soil moisture deficit, via a through-fall exclusion experiment (TFE) in an eastern Amazonian rainforest. We find that experimentally drought-stressed trees and taxa maintain the same maximum leaf photosynthetic capacity as trees in corresponding control forest, independent of their susceptibility to drought-induced mortality. We hypothesize that photosynthetic capacity is maintained across all treatments and taxa to take advantage of short-lived periods of high moisture availability, when stomatal conductance (gs ) and photosynthesis can increase rapidly, potentially compensating for reduced assimilate supply at other times. Average leaf dark respiration (Rd ) was elevated in the TFE-treated forest trees relative to the control by 28.2 ± 2.8% (mean ± one standard error). This mean Rd value was dominated by a 48.5 ± 3.6% increase in the Rd of drought-sensitive taxa, and likely reflects the need for additional metabolic support required for stress-related repair, and hydraulic or osmotic maintenance processes. Following soil moisture deficit that is maintained for several years, our data suggest that changes in respiration drive greater shifts in the canopy carbon balance, than changes in photosynthetic capacity. © 2015 John Wiley & Sons Ltd.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

PubMed

Ratcliffe, Blaise; El-Dien, Omnia Gamal; Cappa, Eduardo P; Porth, Ilga; Klápště, Jaroslav; Chen, Charles; El-Kassaby, Yousry A

2017-03-10

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm. Copyright © 2017 Ratcliffe et al.

Prediction of forest canopy and surface fuels from Lidar and satellite time series data in a bark beetle-affected forest

USGS Publications Warehouse

Bright, Benjamin C.; Hudak, Andrew T.; Meddens, Arjan J.H.; Hawbaker, Todd J.; Briggs, Jenny S.; Kennedy, Robert E.

2017-01-01

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and surface fuels from light detection and ranging (lidar) and Landsat time series explanatory variables via random forest (RF) modeling across a coniferous montane forest in Colorado, USA, which was affected by mountain pine beetles (Dendroctonus ponderosae Hopkins) approximately six years prior. We examined relationships between mapped fuels and the severity of tree mortality with correlation tests. RF models explained 59%, 48%, 35%, and 70% of the variation in available canopy fuel, canopy bulk density, canopy base height, and canopy height, respectively (percent root-mean-square error (%RMSE) = 12–54%). Surface fuels were predicted less accurately, with models explaining 24%, 28%, 32%, and 30% of the variation in litter and duff, 1 to 100-h, 1000-h, and total surface fuels, respectively (%RMSE = 37–98%). Fuel metrics were negatively correlated with the severity of tree mortality, except canopy base height, which increased with greater tree mortality. Our results showed how bark beetle-caused tree mortality significantly reduced canopy fuels in our study area. We demonstrated that lidar and Landsat time series data contain substantial information about canopy and surface fuels and can be used for large-scale efforts to monitor and map fuel loads for fire behavior modeling at a landscape scale.

A novel multiple description scalable coding scheme for mobile wireless video transmission

NASA Astrophysics Data System (ADS)

Zheng, Haifeng; Yu, Lun; Chen, Chang Wen

2005-03-01

We proposed in this paper a novel multiple description scalable coding (MDSC) scheme based on in-band motion compensation temporal filtering (IBMCTF) technique in order to achieve high video coding performance and robust video transmission. The input video sequence is first split into equal-sized groups of frames (GOFs). Within a GOF, each frame is hierarchically decomposed by discrete wavelet transform. Since there is a direct relationship between wavelet coefficients and what they represent in the image content after wavelet decomposition, we are able to reorganize the spatial orientation trees to generate multiple bit-streams and employed SPIHT algorithm to achieve high coding efficiency. We have shown that multiple bit-stream transmission is very effective in combating error propagation in both Internet video streaming and mobile wireless video. Furthermore, we adopt the IBMCTF scheme to remove the redundancy for inter-frames along the temporal direction using motion compensated temporal filtering, thus high coding performance and flexible scalability can be provided in this scheme. In order to make compressed video resilient to channel error and to guarantee robust video transmission over mobile wireless channels, we add redundancy to each bit-stream and apply error concealment strategy for lost motion vectors. Unlike traditional multiple description schemes, the integration of these techniques enable us to generate more than two bit-streams that may be more appropriate for multiple antenna transmission of compressed video. Simulate results on standard video sequences have shown that the proposed scheme provides flexible tradeoff between coding efficiency and error resilience.

Estimating forest and woodland aboveground biomass using active and passive remote sensing

USGS Publications Warehouse

Wu, Zhuoting; Dye, Dennis G.; Vogel, John M.; Middleton, Barry R.

2016-01-01

Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.

A 6-bit 4 GS/s pseudo-thermometer segmented CMOS DAC

NASA Astrophysics Data System (ADS)

Yijun, Song; Wenyuan, Li

2014-06-01

A 6-bit 4 GS/s, high-speed and power-efficient DAC for ultra-high-speed transceivers in 60 GHz band millimeter wave technology is presented. A novel pseudo-thermometer architecture is proposed to realize a good compromise between the fast conversion speed and the chip area. Symmetrical and compact floor planning and layout techniques including tree-like routing, cross-quading and common-centroid method are adopted to guarantee the chip is fully functional up to near-Nyquist frequency in a standard 0.18 μm CMOS process. Post simulation results corroborate the feasibility of the designed DAC, which canperform good static and dynamic linearity without calibration. DNL errors and INL errors can be controlled within ±0.28 LSB and ±0.26 LSB, respectively. SFDR at 4 GHz clock frequency for a 1.9 GHz near-Nyquist sinusoidal output signal is 40.83 dB and the power dissipation is less than 37 mW.

Measuring exertion time, duty cycle and hand activity level for industrial tasks using computer vision.

PubMed

Akkas, Oguz; Lee, Cheng Hsien; Hu, Yu Hen; Harris Adamson, Carisa; Rempel, David; Radwin, Robert G

2017-12-01

Two computer vision algorithms were developed to automatically estimate exertion time, duty cycle (DC) and hand activity level (HAL) from videos of workers performing 50 industrial tasks. The average DC difference between manual frame-by-frame analysis and the computer vision DC was -5.8% for the Decision Tree (DT) algorithm, and 1.4% for the Feature Vector Training (FVT) algorithm. The average HAL difference was 0.5 for the DT algorithm and 0.3 for the FVT algorithm. A sensitivity analysis, conducted to examine the influence that deviations in DC have on HAL, found it remained unaffected when DC error was less than 5%. Thus, a DC error less than 10% will impact HAL less than 0.5 HAL, which is negligible. Automatic computer vision HAL estimates were therefore comparable to manual frame-by-frame estimates. Practitioner Summary: Computer vision was used to automatically estimate exertion time, duty cycle and hand activity level from videos of workers performing industrial tasks.

Machine learning models for lipophilicity and their domain of applicability.

PubMed

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Laak, Antonius Ter; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-01-01

Unfavorable lipophilicity and water solubility cause many drug failures; therefore these properties have to be taken into account early on in lead discovery. Commercial tools for predicting lipophilicity usually have been trained on small and neutral molecules, and are thus often unable to accurately predict in-house data. Using a modern Bayesian machine learning algorithm--a Gaussian process model--this study constructs a log D7 model based on 14,556 drug discovery compounds of Bayer Schering Pharma. Performance is compared with support vector machines, decision trees, ridge regression, and four commercial tools. In a blind test on 7013 new measurements from the last months (including compounds from new projects) 81% were predicted correctly within 1 log unit, compared to only 44% achieved by commercial software. Additional evaluations using public data are presented. We consider error bars for each method (model based error bars, ensemble based, and distance based approaches), and investigate how well they quantify the domain of applicability of each model.

6-Hydroxy dopamine does not affect lens-induced refractive errors but suppresses deprivation myopia.

PubMed

Schaeffel, F; Hagel, G; Bartmann, M; Kohler, K; Zrenner, E

1994-01-01

Degradation of the retinal image by translucent occluders during postnatal development induces axial myopia in chickens, tree shrews and monkeys. Local visual deprivation produces myopia even in local regions of the eye and neither accommodation nor intact connection between the eye and the brain are necessary. Therefore, it is an important question whether a similar local-retinal pathway translating visual information into growth or stretch signals to the underlying sclera is acting to emmetropize the growing eye. It is not known until now whether occluder deprivation triggers similar eye growth (or scleral stretch) mechanisms that are also responsible for visual guidance of normal refractive development. We here report that, in chickens, 6-hydroxy dopamine suppresses deprivation-induced myopia but has no effect on the magnitude of changes in axial eye elongation that are induced by spectacle lenses. The result suggests that, in chickens with normal accommodation, two pharmacologically different feedback loops may be responsible for deprivation myopia and lens-induced refractive errors.

The use of automatic programming techniques for fault tolerant computing systems

NASA Technical Reports Server (NTRS)

Wild, C.

1985-01-01

It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.

Forecasting air quality time series using deep learning.

PubMed

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.

Inferring biogeochemistry past: a millennial-scale multimodel assimilation of multiple paleoecological proxies.

NASA Astrophysics Data System (ADS)

Dietze, M.; Raiho, A.; Fer, I.; Dawson, A.; Heilman, K.; Hooten, M.; McLachlan, J. S.; Moore, D. J.; Paciorek, C. J.; Pederson, N.; Rollinson, C.; Tipton, J.

2017-12-01

The pre-industrial period serves as an essential baseline against which we judge anthropogenic impacts on the earth's systems. However, direct measurements of key biogeochemical processes, such as carbon, water, and nutrient cycling, are absent for this period and there is no direct way to link paleoecological proxies, such as pollen and tree rings, to these processes. Process-based terrestrial ecosystem models provide a way to make inferences about the past, but have large uncertainties and by themselves often fail to capture much of the observed variability. Here we investigate the ability to improve inferences about pre-industrial biogeochemical cycles through the formal assimilation of proxy data into multiple process-based models. A Tobit ensemble filter with explicit estimation of process error was run at five sites across the eastern US for three models (LINKAGES, ED2, LPJ-GUESS). In addition to process error, the ensemble accounted for parameter uncertainty, estimated through the assimilation of the TRY and BETY trait databases, and driver uncertainty, accommodated by probabilistically downscaling and debiasing CMIP5 GCM output then filtering based on paleoclimate reconstructions. The assimilation was informed by four PalEON data products, each of which includes an explicit Bayesian error estimate: (1) STEPPS forest composition estimated from fossil pollen; (2) REFAB aboveground biomass (AGB) estimated from fossil pollen; (3) tree ring AGB and woody net primary productivity (wNPP); and (4) public land survey composition, stem density, and AGB. By comparing ensemble runs with and without data assimilation we are able to assess the information contribution of the proxy data to constraining biogeochemical fluxes, which is driven by the combination of model uncertainty, data uncertainty, and the strength of correlation between observed and unobserved quantities in the model ensemble. To our knowledge this is the first attempt at multi-model data assimilation with terrestrial ecosystem models. Results from the data-model assimilation allow us to assess the consistency across models in post-assimilation inferences about indirectly inferred quantities, such as GPP, soil carbon, and the water budget.

Alignment methods: strategies, challenges, benchmarking, and comparative overview.

PubMed

Löytynoja, Ari

2012-01-01

Comparative evolutionary analyses of molecular sequences are solely based on the identities and differences detected between homologous characters. Errors in this homology statement, that is errors in the alignment of the sequences, are likely to lead to errors in the downstream analyses. Sequence alignment and phylogenetic inference are tightly connected and many popular alignment programs use the phylogeny to divide the alignment problem into smaller tasks. They then neglect the phylogenetic tree, however, and produce alignments that are not evolutionarily meaningful. The use of phylogeny-aware methods reduces the error but the resulting alignments, with evolutionarily correct representation of homology, can challenge the existing practices and methods for viewing and visualising the sequences. The inter-dependency of alignment and phylogeny can be resolved by joint estimation of the two; methods based on statistical models allow for inferring the alignment parameters from the data and correctly take into account the uncertainty of the solution but remain computationally challenging. Widely used alignment methods are based on heuristic algorithms and unlikely to find globally optimal solutions. The whole concept of one correct alignment for the sequences is questionable, however, as there typically exist vast numbers of alternative, roughly equally good alignments that should also be considered. This uncertainty is hidden by many popular alignment programs and is rarely correctly taken into account in the downstream analyses. The quest for finding and improving the alignment solution is complicated by the lack of suitable measures of alignment goodness. The difficulty of comparing alternative solutions also affects benchmarks of alignment methods and the results strongly depend on the measure used. As the effects of alignment error cannot be predicted, comparing the alignments' performance in downstream analyses is recommended.

Integrated modeling environment for systems-level performance analysis of the Next-Generation Space Telescope

NASA Astrophysics Data System (ADS)

Mosier, Gary E.; Femiano, Michael; Ha, Kong; Bely, Pierre Y.; Burg, Richard; Redding, David C.; Kissil, Andrew; Rakoczy, John; Craig, Larry

1998-08-01

All current concepts for the NGST are innovative designs which present unique systems-level challenges. The goals are to outperform existing observatories at a fraction of the current price/performance ratio. Standard practices for developing systems error budgets, such as the 'root-sum-of- squares' error tree, are insufficient for designs of this complexity. Simulation and optimization are the tools needed for this project; in particular tools that integrate controls, optics, thermal and structural analysis, and design optimization. This paper describes such an environment which allows sub-system performance specifications to be analyzed parametrically, and includes optimizing metrics that capture the science requirements. The resulting systems-level design trades are greatly facilitated, and significant cost savings can be realized. This modeling environment, built around a tightly integrated combination of commercial off-the-shelf and in-house- developed codes, provides the foundation for linear and non- linear analysis on both the time and frequency-domains, statistical analysis, and design optimization. It features an interactive user interface and integrated graphics that allow highly-effective, real-time work to be done by multidisciplinary design teams. For the NGST, it has been applied to issues such as pointing control, dynamic isolation of spacecraft disturbances, wavefront sensing and control, on-orbit thermal stability of the optics, and development of systems-level error budgets. In this paper, results are presented from parametric trade studies that assess requirements for pointing control, structural dynamics, reaction wheel dynamic disturbances, and vibration isolation. These studies attempt to define requirements bounds such that the resulting design is optimized at the systems level, without attempting to optimize each subsystem individually. The performance metrics are defined in terms of image quality, specifically centroiding error and RMS wavefront error, which directly links to science requirements.

Energy efficient data representation and aggregation with event region detection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Banerjee, Torsha

Unlike conventional networks, wireless sensor networks (WSNs) are limited in power, have much smaller memory buffers, and possess relatively slower processing speeds. These characteristics necessitate minimum transfer and storage of information in order to prolong the network lifetime. In this dissertation, we exploit the spatio-temporal nature of sensor data to approximate the current values of the sensors based on readings obtained from neighboring sensors and itself. We propose a Tree based polynomial REGression algorithm, (TREG) that addresses the problem of data compression in wireless sensor networks. Instead of aggregated data, a polynomial function (P) is computed by the regression function, TREG. The coefficients of P are then passed to achieve the following goals: (i) The sink can get attribute values in the regions devoid of sensor nodes, and (ii) Readings over any portion of the region can be obtained at one time by querying the root of the tree. As the size of the data packet from each tree node to its parent remains constant, the proposed scheme scales very well with growing network density or increased coverage area. Since physical attributes exhibit a gradual change over time, we propose an iterative scheme, UPDATE_COEFF, which obviates the need to perform the regression function repeatedly and uses approximations based on previous readings. Extensive simulations are performed on real world data to demonstrate the effectiveness of our proposed aggregation algorithm, TREG. Results reveal that for a network density of 0.0025 nodes/m2, a complete binary tree of depth 4 could provide the absolute error to be less than 6%. A data compression ratio of about 0.02 is achieved using our proposed algorithm, which is almost independent of the tree depth. In addition, our proposed updating scheme makes the aggregation process faster while maintaining the desired error bounds. We also propose a Polynomial-based scheme that addresses the problem of Event Region Detection (PERD) for WSNs. When a single event occurs, a child of the tree sends a Flagged Polynomial (FP) to its parent, if the readings approximated by it falls outside the data range defining the existing phenomenon. After the aggregation process is over, the root having the two polynomials, P and FP can be queried for FP (approximating the new event region) instead of flooding the whole network. For multiple such events, instead of computing a polynomial corresponding to each new event, areas with same data range are combined by the corresponding tree nodes and the aggregated coefficients are passed on. Results reveal that a new event can be detected by PERD while error in detection remains constant and is less than a threshold of 10%. As the node density increases, accuracy and delay for event detection are found to remain almost constant, making PERD highly scalable. Whenever an event occurs in a WSN, data is generated by closeby sensors and relaying the data to the base station (BS) make sensors closer to the BS run out of energy at a much faster rate than sensors in other parts of the network. This gives rise to an unequal distribution of residual energy in the network and makes those sensors with lower remaining energy level die at much faster rate than others. We propose a scheme for enhancing network Lifetime using mobile cluster heads (CH) in a WSN. To maintain remaining energy more evenly, some energy-rich nodes are designated as CHs which move in a controlled manner towards sensors rich in energy and data. This eliminates multihop transmission required by the static sensors and thus increases the overall lifetime of the WSN. We combine the idea of clustering and mobile CH to first form clusters of static sensor nodes. A collaborative strategy among the CHs further increases the lifetime of the network. Time taken for transmitting data to the BS is reduced further by making the CHs follow a connectivity strategy that always maintain a connected path to the BS. Spatial correlation of sensor data can be further exploited for dynamic channel selection in Cellular Communication. In such a scenario within a licensed band, wireless sensors can be deployed (each sensor tuned to a frequency of the channel at a particular time) to sense the interference power of the frequency band. In an ideal channel, interference temperature (IT) which is directly proportional to the interference power, can be assumed to vary spatially with the frequency of the sub channel. We propose a scheme for fitting the sub channel frequencies and corresponding ITs to a regression model for calculating the IT of a random sub channel for further analysis of the channel interference at the base station. Our scheme, based on the readings reported by Sensors helps in Dynamic Channel Selection (S-DCS) in extended C-band for assignment to unlicensed secondary users. S-DCS proves to be economic from energy consumption point of view and it also achieves accuracy with error bound within 6.8%. Again, users are assigned empty sub channels without actually probing them, incurring minimum delay in the process. The overall channel throughput is maximized along with fairness to individual users.

Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

2017-09-01

In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

Enhanced protocol for real-time transmission of echocardiograms over wireless channels.

PubMed

Cavero, Eva; Alesanco, Alvaro; García, Jose

2012-11-01

This paper presents a methodology to transmit clinical video over wireless networks in real-time. A 3-D set partitioning in hierarchical trees compression prior to transmission is proposed. In order to guarantee the clinical quality of the compressed video, a clinical evaluation specific to each video modality has to be made. This evaluation indicates the minimal transmission rate necessary for an accurate diagnosis. However, the channel conditions produce errors and distort the video. A reliable application protocol is therefore proposed using a hybrid solution in which either retransmission or retransmission combined with forward error correction (FEC) techniques are used, depending on the channel conditions. In order to analyze the proposed methodology, the 2-D mode of an echocardiogram has been assessed. A bandwidth of 200 kbps is necessary to guarantee its clinical quality. The transmission using the proposed solution and retransmission and FEC techniques working separately have been simulated and compared in high-speed uplink packet access (HSUPA) and worldwide interoperability for microwave access (WiMAX) networks. The proposed protocol achieves guaranteed clinical quality for bit error rates higher than with the other protocols, being for a mobile speed of 60 km/h up to 3.3 times higher for HSUPA and 10 times for WiMAX.

Uncertainty Analysis in Large Area Aboveground Biomass Mapping

NASA Astrophysics Data System (ADS)

Baccini, A.; Carvalho, L.; Dubayah, R.; Goetz, S. J.; Friedl, M. A.

2011-12-01

Satellite and aircraft-based remote sensing observations are being more frequently used to generate spatially explicit estimates of aboveground carbon stock of forest ecosystems. Because deforestation and forest degradation account for circa 10% of anthropogenic carbon emissions to the atmosphere, policy mechanisms are increasingly recognized as a low-cost mitigation option to reduce carbon emission. They are, however, contingent upon the capacity to accurately measures carbon stored in the forests. Here we examine the sources of uncertainty and error propagation in generating maps of aboveground biomass. We focus on characterizing uncertainties associated with maps at the pixel and spatially aggregated national scales. We pursue three strategies to describe the error and uncertainty properties of aboveground biomass maps, including: (1) model-based assessment using confidence intervals derived from linear regression methods; (2) data-mining algorithms such as regression trees and ensembles of these; (3) empirical assessments using independently collected data sets.. The latter effort explores error propagation using field data acquired within satellite-based lidar (GLAS) acquisitions versus alternative in situ methods that rely upon field measurements that have not been systematically collected for this purpose (e.g. from forest inventory data sets). A key goal of our effort is to provide multi-level characterizations that provide both pixel and biome-level estimates of uncertainties at different scales.

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

Development of virtual environments for training skills and reducing errors in laparoscopic surgery

NASA Astrophysics Data System (ADS)

Tendick, Frank; Downes, Michael S.; Cavusoglu, Murat C.; Gantert, Walter A.; Way, Lawrence W.

1998-06-01

In every surgical procedure there are key steps and skills that, if performed incorrectly, can lead to complications. In conjunction with efforts, based on task and error analysis, in the Videoscopic Training Center at UCSF to identify these key elements in laparoscopic surgical procedures, the authors are developing virtual environments and modeling methods to train the elements. Laparoscopic surgery is particularly demanding of the surgeon's spatial skills, requiring the ability to create 3D mental models and plans while viewing a 2D image. For example, operating a laparoscope with the objective lens angled from the scope axis is a skill that some surgeons have difficulty mastering, even after using the instrument in many procedures. Virtual environments are a promising medium for teaching spatial skills. A kinematically accurate model of an angled laparoscope in an environment of simple targets is being tested in courses for novice and experienced surgeons. Errors in surgery are often due to a misinterpretation of local anatomy compounded with inadequate procedural knowledge. Methods to avoid bile duct injuries in cholecystectomy are being integrated into a deformable environment consisting of the liver, gallbladder, and biliary tree. Novel deformable tissue modeling algorithms based on finite element methods will be used to improve the response of the anatomical models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petiteau, Antoine; Babak, Stanislav; Sesana, Alberto

Gravitational wave (GW) signals from coalescing massive black hole (MBH) binaries could be used as standard sirens to measure cosmological parameters. The future space-based GW observatory Laser Interferometer Space Antenna (LISA) will detect up to a hundred of those events, providing very accurate measurements of their luminosity distances. To constrain the cosmological parameters, we also need to measure the redshift of the galaxy (or cluster of galaxies) hosting the merger. This requires the identification of a distinctive electromagnetic event associated with the binary coalescence. However, putative electromagnetic signatures may be too weak to be observed. Instead, we study here themore » possibility of constraining the cosmological parameters by enforcing statistical consistency between all the possible hosts detected within the measurement error box of a few dozen of low-redshift (z < 3) events. We construct MBH populations using merger tree realizations of the dark matter hierarchy in a {Lambda}CDM universe, and we use data from the Millennium simulation to model the galaxy distribution in the LISA error box. We show that, assuming that all the other cosmological parameters are known, the parameter w describing the dark energy equation of state can be constrained to a 4%-8% level (2{sigma} error), competitive with current uncertainties obtained by type Ia supernovae measurements, providing an independent test of our cosmological model.« less