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.

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

Hide and vanish: data sets where the most parsimonious tree is known but hard to find, and their implications for tree search methods.

PubMed

Goloboff, Pablo A

2014-10-01

Three different types of data sets, for which the uniquely most parsimonious tree can be known exactly but is hard to find with heuristic tree search methods, are studied. Tree searches are complicated more by the shape of the tree landscape (i.e. the distribution of homoplasy on different trees) than by the sheer abundance of homoplasy or character conflict. Data sets of Type 1 are those constructed by Radel et al. (2013). Data sets of Type 2 present a very rugged landscape, with narrow peaks and valleys, but relatively low amounts of homoplasy. For such a tree landscape, subjecting the trees to TBR and saving suboptimal trees produces much better results when the sequence of clipping for the tree branches is randomized instead of fixed. An unexpected finding for data sets of Types 1 and 2 is that starting a search from a random tree instead of a random addition sequence Wagner tree may increase the probability that the search finds the most parsimonious tree; a small artificial example where these probabilities can be calculated exactly is presented. Data sets of Type 3, the most difficult data sets studied here, comprise only congruent characters, and a single island with only one most parsimonious tree. Even if there is a single island, missing entries create a very flat landscape which is difficult to traverse with tree search algorithms because the number of equally parsimonious trees that need to be saved and swapped to effectively move around the plateaus is too large. Minor modifications of the parameters of tree drifting, ratchet, and sectorial searches allow travelling around these plateaus much more efficiently than saving and swapping large numbers of equally parsimonious trees with TBR. For these data sets, two new related criteria for selecting taxon addition sequences in Wagner trees (the "selected" and "informative" addition sequences) produce much better results than the standard random or closest addition sequences. These new methods for Wagner trees and for moving around plateaus can be useful when analyzing phylogenomic data sets formed by concatenation of genes with uneven taxon representation ("sparse" supermatrices), which are likely to present a tree landscape with extensive plateaus. Copyright © 2014 Elsevier Inc. All rights reserved.

Point-Sampling and Line-Sampling Probability Theory, Geometric Implications, Synthesis

Treesearch

L.R. Grosenbaugh

1958-01-01

Foresters concerned with measuring tree populations on definite areas have long employed two well-known methods of representative sampling. In list or enumerative sampling the entire tree population is tallied with a known proportion being randomly selected and measured for volume or other variables. In area sampling all trees on randomly located plots or strips...

Using multi-locus allelic sequence data to estimate genetic divergence among four Lilium (Liliaceae) cultivars

PubMed Central

Shahin, Arwa; Smulders, Marinus J. M.; van Tuyl, Jaap M.; Arens, Paul; Bakker, Freek T.

2014-01-01

Next Generation Sequencing (NGS) may enable estimating relationships among genotypes using allelic variation of multiple nuclear genes simultaneously. We explored the potential and caveats of this strategy in four genetically distant Lilium cultivars to estimate their genetic divergence from transcriptome sequences using three approaches: POFAD (Phylogeny of Organisms from Allelic Data, uses allelic information of sequence data), RAxML (Randomized Accelerated Maximum Likelihood, tree building based on concatenated consensus sequences) and Consensus Network (constructing a network summarizing among gene tree conflicts). Twenty six gene contigs were chosen based on the presence of orthologous sequences in all cultivars, seven of which also had an orthologous sequence in Tulipa, used as out-group. The three approaches generated the same topology. Although the resolution offered by these approaches is high, in this case there was no extra benefit in using allelic information. We conclude that these 26 genes can be widely applied to construct a species tree for the genus Lilium. PMID:25368628

Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data.

PubMed

Schmidt-Lebuhn, Alexander N; Aitken, Nicola C; Chuah, Aaron

2017-11-01

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

[Functional diversity characteristics of canopy tree species of Jianfengling tropical montane rainforest on Hainan Island, China.

PubMed

Xu, Ge Xi; Shi, Zuo Min; Tang, Jing Chao; Liu, Shun; Ma, Fan Qiang; Xu, Han; Liu, Shi Rong; Li, Yi de

2016-11-18

Based on three 1-hm 2 plots of Jianfengling tropical montane rainforest on Hainan Island, 11 commom used functional traits of canopy trees were measured. After combining with topographical factors and trees census data of these three plots, we compared the impacts of weighted species abundance on two functional dispersion indices, mean pairwise distance (MPD) and mean nearest taxon distance (MNTD), by using single- and multi-dimensional traits, respectively. The relationship between functional richness of the forest canopies and species abundance was analyzed. We used a null model approach to explore the variations in standardized size effects of MPD and MNTD, which were weighted by species abundance and eliminated the influences of species richness diffe-rences among communities, and assessed functional diversity patterns of the forest canopies and their responses to local habitat heterogeneity at community's level. The results showed that variation in MPD was greatly dependent on the dimensionalities of functional traits as well as species abundance. The correlations between weighted and non-weighted MPD based on different dimensional traits were relatively weak (R=0.359-0.628). On the contrary, functional traits and species abundance had relatively weak effects on MNTD, which brought stronger correlations between weighted and non-weighted MNTD based on different dimensional traits (R=0.746-0.820). Functional dispersion of the forest canopies were generally overestimated when using non-weighted MPD and MNTD. Functional richness of the forest canopies showed an exponential relationship with species abundance (F=128.20; R 2 =0.632; AIC=97.72; P＜0.001), which might exist a species abundance threshold value. Patterns of functional diversity of the forest canopies based on different dimensional functional traits and their habitat responses showed variations in some degree. Forest canopies in the valley usually had relatively stronger biological competition, and functional diversity was higher than expected functional diversity randomized by null model, which indicated dispersed distribution of functional traits among canopy tree species in this habitat. However, the functional diversity of the forest canopies tended to be close or lower than randomization in the other habitat types, which demonstrated random or clustered distribution of the functional traits among canopy tree species.

The data-driven null models for information dissemination tree in social networks

NASA Astrophysics Data System (ADS)

Zhang, Zhiwei; Wang, Zhenyu

2017-10-01

For the purpose of detecting relatedness and co-occurrence between users, as well as the distribution features of nodes in spreading path of a social network, this paper explores topological characteristics of information dissemination trees (IDT) that can be employed indirectly to probe the information dissemination laws within social networks. Hence, three different null models of IDT are presented in this article, including the statistical-constrained 0-order IDT null model, the random-rewire-broken-edge 0-order IDT null model and the random-rewire-broken-edge 2-order IDT null model. These null models firstly generate the corresponding randomized copy of an actual IDT; then the extended significance profile, which is developed by adding the cascade ratio of information dissemination path, is exploited not only to evaluate degree correlation of two nodes associated with an edge, but also to assess the cascade ratio of different length of information dissemination paths. The experimental correspondences of the empirical analysis for several SinaWeibo IDTs and Twitter IDTs indicate that the IDT null models presented in this paper perform well in terms of degree correlation of nodes and dissemination path cascade ratio, which can be better to reveal the features of information dissemination and to fit the situation of real social networks.

Spectrum of walk matrix for Koch network and its application

NASA Astrophysics Data System (ADS)

Xie, Pinchen; Lin, Yuan; Zhang, Zhongzhi

2015-06-01

Various structural and dynamical properties of a network are encoded in the eigenvalues of walk matrix describing random walks on the network. In this paper, we study the spectra of walk matrix of the Koch network, which displays the prominent scale-free and small-world features. Utilizing the particular architecture of the network, we obtain all the eigenvalues and their corresponding multiplicities. Based on the link between the eigenvalues of walk matrix and random target access time defined as the expected time for a walker going from an arbitrary node to another one selected randomly according to the steady-state distribution, we then derive an explicit solution to the random target access time for random walks on the Koch network. Finally, we corroborate our computation for the eigenvalues by enumerating spanning trees in the Koch network, using the connection governing eigenvalues and spanning trees, where a spanning tree of a network is a subgraph of the network, that is, a tree containing all the nodes.

Rumor Processes in Random Environment on and on Galton-Watson Trees

NASA Astrophysics Data System (ADS)

Bertacchi, Daniela; Zucca, Fabio

2013-11-01

The aim of this paper is to study rumor processes in random environment. In a rumor process a signal starts from the stations of a fixed vertex (the root) and travels on a graph from vertex to vertex. We consider two rumor processes. In the firework process each station, when reached by the signal, transmits it up to a random distance. In the reverse firework process, on the other hand, stations do not send any signal but they “listen” for it up to a random distance. The first random environment that we consider is the deterministic 1-dimensional tree with a random number of stations on each vertex; in this case the root is the origin of . We give conditions for the survival/extinction on almost every realization of the sequence of stations. Later on, we study the processes on Galton-Watson trees with random number of stations on each vertex. We show that if the probability of survival is positive, then there is survival on almost every realization of the infinite tree such that there is at least one station at the root. We characterize the survival of the process in some cases and we give sufficient conditions for survival/extinction.

Random trinomial tree models and vanilla options

NASA Astrophysics Data System (ADS)

Ganikhodjaev, Nasir; Bayram, Kamola

2013-09-01

In this paper we introduce and study random trinomial model. The usual trinomial model is prescribed by triple of numbers (u, d, m). We call the triple (u, d, m) an environment of the trinomial model. A triple (Un, Dn, Mn), where {Un}, {Dn} and {Mn} are the sequences of independent, identically distributed random variables with 0 < Dn < 1 < Un and Mn = 1 for all n, is called a random environment and trinomial tree model with random environment is called random trinomial model. The random trinomial model is considered to produce more accurate results than the random binomial model or usual trinomial model.

Disentangling the diversity of arboreal ant communities in tropical forest trees.

PubMed

Klimes, Petr; Fibich, Pavel; Idigel, Cliffson; Rimandai, Maling

2015-01-01

Tropical canopies are known for their high abundance and diversity of ants. However, the factors which enable coexistence of so many species in trees, and in particular, the role of foragers in determining local diversity, are not well understood. We censused nesting and foraging arboreal ant communities in two 0.32 ha plots of primary and secondary lowland rainforest in New Guinea and explored their species diversity and composition. Null models were used to test if the records of species foraging (but not nesting) in a tree were dependent on the spatial distribution of nests in surrounding trees. In total, 102 ant species from 389 trees occurred in the primary plot compared with only 50 species from 295 trees in the secondary forest plot. However, there was only a small difference in mean ant richness per tree between primary and secondary forest (3.8 and 3.3 sp. respectively) and considerably lower richness per tree was found only when nests were considered (1.5 sp. in both forests). About half of foraging individuals collected in a tree belonged to species which were not nesting in that tree. Null models showed that the ants foraging but not nesting in a tree are more likely to nest in nearby trees than would be expected at random. The effects of both forest stage and tree size traits were similar regardless of whether only foragers, only nests, or both datasets combined were considered. However, relative abundance distributions of species differed between foraging and nesting communities. The primary forest plot was dominated by native ant species, whereas invasive species were common in secondary forest. This study demonstrates the high contribution of foragers to arboreal ant diversity, indicating an important role of connectivity between trees, and also highlights the importance of primary vegetation for the conservation of native ant communities.

Disentangling the Diversity of Arboreal Ant Communities in Tropical Forest Trees

PubMed Central

Klimes, Petr; Fibich, Pavel; Idigel, Cliffson; Rimandai, Maling

2015-01-01

Tropical canopies are known for their high abundance and diversity of ants. However, the factors which enable coexistence of so many species in trees, and in particular, the role of foragers in determining local diversity, are not well understood. We censused nesting and foraging arboreal ant communities in two 0.32 ha plots of primary and secondary lowland rainforest in New Guinea and explored their species diversity and composition. Null models were used to test if the records of species foraging (but not nesting) in a tree were dependent on the spatial distribution of nests in surrounding trees. In total, 102 ant species from 389 trees occurred in the primary plot compared with only 50 species from 295 trees in the secondary forest plot. However, there was only a small difference in mean ant richness per tree between primary and secondary forest (3.8 and 3.3 sp. respectively) and considerably lower richness per tree was found only when nests were considered (1.5 sp. in both forests). About half of foraging individuals collected in a tree belonged to species which were not nesting in that tree. Null models showed that the ants foraging but not nesting in a tree are more likely to nest in nearby trees than would be expected at random. The effects of both forest stage and tree size traits were similar regardless of whether only foragers, only nests, or both datasets combined were considered. However, relative abundance distributions of species differed between foraging and nesting communities. The primary forest plot was dominated by native ant species, whereas invasive species were common in secondary forest. This study demonstrates the high contribution of foragers to arboreal ant diversity, indicating an important role of connectivity between trees, and also highlights the importance of primary vegetation for the conservation of native ant communities. PMID:25714831

Computer simulations of melts of randomly branching polymers

NASA Astrophysics Data System (ADS)

Rosa, Angelo; Everaers, Ralf

2016-10-01

Randomly branching polymers with annealed connectivity are model systems for ring polymers and chromosomes. In this context, the branched structure represents transient folding induced by topological constraints. Here we present computer simulations of melts of annealed randomly branching polymers of 3 ≤ N ≤ 1800 segments in d = 2 and d = 3 dimensions. In all cases, we perform a detailed analysis of the observed tree connectivities and spatial conformations. Our results are in excellent agreement with an asymptotic scaling of the average tree size of R ˜ N1/d, suggesting that the trees behave as compact, territorial fractals. The observed swelling relative to the size of ideal trees, R ˜ N1/4, demonstrates that excluded volume interactions are only partially screened in melts of annealed trees. Overall, our results are in good qualitative agreement with the predictions of Flory theory. In particular, we find that the trees swell by the combination of modified branching and path stretching. However, the former effect is subdominant and difficult to detect in d = 3 dimensions.

New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

Treesearch

L.R. Iverson; A.M. Prasad; A. Liaw

2004-01-01

More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen; John W. Coulston; Barry T. (Ty) Wilson

2015-01-01

As part of the development of the 2011 National Land Cover Database (NLCD) tree canopy cover layer, a pilot project was launched to test the use of high-resolution photography coupled with extensive ancillary data to map the distribution of tree canopy cover over four study regions in the conterminous US. Two stochastic modeling techniques, random forests (RF...

MTVis: tree exploration using a multitouch interface

NASA Astrophysics Data System (ADS)

Andrews, David; Teoh, Soon Tee

2010-01-01

We present MTVis, a multi-touch interactive tree visualization system. The multi-touch interface display hardware is built using the LED-LP technology, and the tree layout is based on RINGS, but enhanced with multitouch interactions. We describe the features of the system, and how the multi-touch interface enhances the user's experience in exploring the tree data structure. In particular, the multi-touch interface allows the user to simultaneously control two child nodes of the root, and rotate them so that some nodes are magnified, while preserving the layout of the tree. We also describe the other meaninful touch screen gestures the users can use to intuitively explore the tree.

Cavity tree selection by red-cockaded woodpeckers in relation to tree age

Treesearch

D. Craig Rudolph; Richard N. Conner

1991-01-01

We aged over 1350 Red-cockaded Woodpecker (Picoides borealis) cavity trees and a comparable number of randomly selected trees. Resulting data strongly support the hypothesis that Red-cockaded Woodpeckers preferentially select older trees. Ages of recently initiated cavity trees in the Texas study areas generally were similar to those of cavity trees...

Tree growth rates in an Amazonian evergreen forest: seasonal patterns and correlations with leaf phenology

NASA Astrophysics Data System (ADS)

Wu, J.; Silva Campos, K.; Prohaska, N.; Ferreira, M. L.; Nelson, B. W.; Saleska, S. R.; da Silva, R.

2014-12-01

Metabolism and phenology of tropical forests significantly influence global dynamics of climate, carbon and water. However, there is still lack of mechanistic understanding of the controls on tropical forest metabolism, particularly at individual tree level. In this study, we are interested in investigating (1) what is the seasonal pattern of woody growth for tropical trees and (2) what is the mechanistic controls onwoody growth at individual level?To explore the above questions,we use two data sources from an evergreen tropical forest KM67 site (near Santarem, Brazil). They are: (1) image time series from a tower mounted RGB imaging system, with images recordedin10 minutes interval since October 2013.Images near local noon homogeneous diffuse lighting were selectedfor leaf phenologymonitoring; (2) ground based bi-weekly biometry survey (via dendrometry band technique) for 25 trees from random sampling since September 2013. 12 among 25 trees are within the tower mounted camera image view. Our preliminary resultsdemonstrate that 20 trees among 25 trees surveyed significantly increase woody growth (or "green up") in dry season. Our results also find thatamong those 20 trees, 12 trees reaches the maximum woody increment rate in late dry season with a mean DBH (Diameter at Breast Height) around 30 cm,while 8 trees reaching the maximum in the middle of wet season, with a mean DBH around 90 cm. This study,though limited in the sample size, mightprovide another line of evidence that Amazon rainforests "green up" in dry season. As for mechanistic controls on tropical tree woody control, we hypothesize both climate and leaf phenology control individual woody growth. We would like to link both camera based leaf phenology and climate data in the next to explorethe reason as to the pattern found in this study that bigger trees might have different seasonal growth pattern as smaller trees.

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence.

PubMed

Mi, Chunrong; Huettmann, Falk; Guo, Yumin; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane ( Grus monacha , n  = 33), White-naped Crane ( Grus vipio , n  = 40), and Black-necked Crane ( Grus nigricollis , n  = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid assessments and decisions for efficient conservation.

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence

PubMed Central

Mi, Chunrong; Huettmann, Falk; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33), White-naped Crane (Grus vipio, n = 40), and Black-necked Crane (Grus nigricollis, n = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid assessments and decisions for efficient conservation. PMID:28097060

The contribution of competition to tree mortality in old-growth coniferous forests

USGS Publications Warehouse

Das, A.; Battles, J.; Stephenson, N.L.; van Mantgem, P.J.

2011-01-01

Competition is a well-documented contributor to tree mortality in temperate forests, with numerous studies documenting a relationship between tree death and the competitive environment. Models frequently rely on competition as the only non-random mechanism affecting tree mortality. However, for mature forests, competition may cease to be the primary driver of mortality.We use a large, long-term dataset to study the importance of competition in determining tree mortality in old-growth forests on the western slope of the Sierra Nevada of California, U.S.A. We make use of the comparative spatial configuration of dead and live trees, changes in tree spatial pattern through time, and field assessments of contributors to an individual tree's death to quantify competitive effects.Competition was apparently a significant contributor to tree mortality in these forests. Trees that died tended to be in more competitive environments than trees that survived, and suppression frequently appeared as a factor contributing to mortality. On the other hand, based on spatial pattern analyses, only three of 14 plots demonstrated compelling evidence that competition was dominating mortality. Most of the rest of the plots fell within the expectation for random mortality, and three fit neither the random nor the competition model. These results suggest that while competition is often playing a significant role in tree mortality processes in these forests it only infrequently governs those processes. In addition, the field assessments indicated a substantial presence of biotic mortality agents in trees that died.While competition is almost certainly important, demographics in these forests cannot accurately be characterized without a better grasp of other mortality processes. In particular, we likely need a better understanding of biotic agents and their interactions with one another and with competition. ?? 2011.

Anderson localization for radial tree-like random quantum graphs

NASA Astrophysics Data System (ADS)

Hislop, Peter D.; Post, Olaf

We prove that certain random models associated with radial, tree-like, rooted quantum graphs exhibit Anderson localization at all energies. The two main examples are the random length model (RLM) and the random Kirchhoff model (RKM). In the RLM, the lengths of each generation of edges form a family of independent, identically distributed random variables (iid). For the RKM, the iid random variables are associated with each generation of vertices and moderate the current flow through the vertex. We consider extensions to various families of decorated graphs and prove stability of localization with respect to decoration. In particular, we prove Anderson localization for the random necklace model.

K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method

NASA Astrophysics Data System (ADS)

Sirait, Kamson; Tulus; Budhiarti Nababan, Erna

2017-12-01

Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

Randomized branch sampling

Treesearch

Harry T. Valentine

2002-01-01

Randomized branch sampling (RBS) is a special application of multistage probability sampling (see Sampling, environmental), which was developed originally by Jessen [3] to estimate fruit counts on individual orchard trees. In general, the method can be used to obtain estimates of many different attributes of trees or other branched plants. The usual objective of RBS is...

Random Forest Application for NEXRAD Radar Data Quality Control

NASA Astrophysics Data System (ADS)

Keem, M.; Seo, B. C.; Krajewski, W. F.

2017-12-01

Identification and elimination of non-meteorological radar echoes (e.g., returns from ground, wind turbines, and biological targets) are the basic data quality control steps before radar data use in quantitative applications (e.g., precipitation estimation). Although WSR-88Ds' recent upgrade to dual-polarization has enhanced this quality control and echo classification, there are still challenges to detect some non-meteorological echoes that show precipitation-like characteristics (e.g., wind turbine or anomalous propagation clutter embedded in rain). With this in mind, a new quality control method using Random Forest is proposed in this study. This classification algorithm is known to produce reliable results with less uncertainty. The method introduces randomness into sampling and feature selections and integrates consequent multiple decision trees. The multidimensional structure of the trees can characterize the statistical interactions of involved multiple features in complex situations. The authors explore the performance of Random Forest method for NEXRAD radar data quality control. Training datasets are selected using several clear cases of precipitation and non-precipitation (but with some non-meteorological echoes). The model is structured using available candidate features (from the NEXRAD data) such as horizontal reflectivity, differential reflectivity, differential phase shift, copolar correlation coefficient, and their horizontal textures (e.g., local standard deviation). The influence of each feature on classification results are quantified by variable importance measures that are automatically estimated by the Random Forest algorithm. Therefore, the number and types of features in the final forest can be examined based on the classification accuracy. The authors demonstrate the capability of the proposed approach using several cases ranging from distinct to complex rain/no-rain events and compare the performance with the existing algorithms (e.g., MRMS). They also discuss operational feasibility based on the observed strength and weakness of the method.

Tree mortality rates and tree population projections in Baltimore, Maryland, USA

Treesearch

David J. Nowak; Miki Kuroda; Daniel E. Crane

2004-01-01

Based on re-measurements (1999 and 2001) of randomly-distributed permanent plots within the city boundaries of Baltimore, Maryland, trees are estimated to have an annual mortality rate of 6.6% with an overall annual net change in the number of live trees of -4.2%. Tree mortality rates were significantly different based on tree size, condition, species, and Land use....

SUNPLIN: Simulation with Uncertainty for Phylogenetic Investigations

PubMed Central

2013-01-01

Background Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability. Results In this paper, we present efficient algorithms and implementations for randomly expanding and processing phylogenetic trees so that simulations involved in comparative phylogenetic analysis with uncertainty can be conducted in a reasonable time. We propose algorithms for both randomly expanding trees and calculating distance matrices. We made available the source code, which was written in the C++ language. The code may be used as a standalone program or as a shared object in the R system. The software can also be used as a web service through the link: http://purl.oclc.org/NET/sunplin/. Conclusion We compare our implementations to similar solutions and show that significant performance gains can be obtained. Our results open up the possibility of accounting for phylogenetic uncertainty in evolutionary and ecological analyses of large datasets. PMID:24229408

SUNPLIN: simulation with uncertainty for phylogenetic investigations.

PubMed

Martins, Wellington S; Carmo, Welton C; Longo, Humberto J; Rosa, Thierson C; Rangel, Thiago F

2013-11-15

Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability. In this paper, we present efficient algorithms and implementations for randomly expanding and processing phylogenetic trees so that simulations involved in comparative phylogenetic analysis with uncertainty can be conducted in a reasonable time. We propose algorithms for both randomly expanding trees and calculating distance matrices. We made available the source code, which was written in the C++ language. The code may be used as a standalone program or as a shared object in the R system. The software can also be used as a web service through the link: http://purl.oclc.org/NET/sunplin/. We compare our implementations to similar solutions and show that significant performance gains can be obtained. Our results open up the possibility of accounting for phylogenetic uncertainty in evolutionary and ecological analyses of large datasets.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Cosmic string detection with tree-based machine learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-07-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9'-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Cosmic String Detection with Tree-Based Machine Learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-05-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9΄-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Universal artifacts affect the branching of phylogenetic trees, not universal scaling laws.

PubMed

Altaba, Cristian R

2009-01-01

The superficial resemblance of phylogenetic trees to other branching structures allows searching for macroevolutionary patterns. However, such trees are just statistical inferences of particular historical events. Recent meta-analyses report finding regularities in the branching pattern of phylogenetic trees. But is this supported by evidence, or are such regularities just methodological artifacts? If so, is there any signal in a phylogeny? In order to evaluate the impact of polytomies and imbalance on tree shape, the distribution of all binary and polytomic trees of up to 7 taxa was assessed in tree-shape space. The relationship between the proportion of outgroups and the amount of imbalance introduced with them was assessed applying four different tree-building methods to 100 combinations from a set of 10 ingroup and 9 outgroup species, and performing covariance analyses. The relevance of this analysis was explored taking 61 published phylogenies, based on nucleic acid sequences and involving various taxa, taxonomic levels, and tree-building methods. All methods of phylogenetic inference are quite sensitive to the artifacts introduced by outgroups. However, published phylogenies appear to be subject to a rather effective, albeit rather intuitive control against such artifacts. The data and methods used to build phylogenetic trees are varied, so any meta-analysis is subject to pitfalls due to their uneven intrinsic merits, which translate into artifacts in tree shape. The binary branching pattern is an imposition of methods, and seldom reflects true relationships in intraspecific analyses, yielding artifactual polytomies in short trees. Above the species level, the departure of real trees from simplistic random models is caused at least by two natural factors--uneven speciation and extinction rates; and artifacts such as choice of taxa included in the analysis, and imbalance introduced by outgroups and basal paraphyletic taxa. This artifactual imbalance accounts for tree shape convergence of large trees. There is no evidence for any universal scaling in the tree of life. Instead, there is a need for improved methods of tree analysis that can be used to discriminate the noise due to outgroups from the phylogenetic signal within the taxon of interest, and to evaluate realistic models of evolution, correcting the retrospective perspective and explicitly recognizing extinction as a driving force. Artifacts are pervasive, and can only be overcome through understanding the structure and biological meaning of phylogenetic trees. Catalan Abstract in Translation S1.

Generalized and synthetic regression estimators for randomized branch sampling

Treesearch

David L. R. Affleck; Timothy G. Gregoire

2015-01-01

In felled-tree studies, ratio and regression estimators are commonly used to convert more readily measured branch characteristics to dry crown mass estimates. In some cases, data from multiple trees are pooled to form these estimates. This research evaluates the utility of both tactics in the estimation of crown biomass following randomized branch sampling (...

A Genetic Linkage Map of Longleaf Pine (Pinus palustris Mill.) Based on Random Amplified Polymorphic DNAs

Treesearch

C.D. Nelson; Thomas L. Kubisiak; M. Stine; W.L. Nance

1994-01-01

Eight megagametophyte DNA samples from a single longleaf pine (Pinus palustris Mill.) tree were used to screen 576 oligonucleotide primers for random amplified polymorphic DNA (RAPD) fragments. Primers amplifying repeatable polymorphic fragments were further characterized within a sample of 72 megagametophytes from the same tree. Fragments...

Summer Roost Tree Selection by Eastern Red, Seminole, and Evening Bats in the Upper Coastal Plain of South Carolina

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

Menzel, M.A.; Carter, T.C.; Ford, W.M.

Radiotraction of six eastern red bats, six seminole bats and twenty-four evening bats to 55, 61, and 65 day roosts during 1996 to 1997 in the Upper Coastal Plain of South Carolina. For each species, testing was done for differences between used roost trees and randomly located trees. Also tested for differences between habitat characteristics surrounding roost trees and randomly located trees. Eastern Red and Seminole bats generally roosted in canopies of hardwood and pine while clinging to foilage and small branches. Evening bats roosted in cavities or under exfoliating bark in pines and dead snags. Forest management strategies namedmore » within the study should be beneficial for providing roosts in the Upper Coastal Plain of South Carolina.« less

Visual exploration of parameter influence on phylogenetic trees.

PubMed

Hess, Martin; Bremm, Sebastian; Weissgraeber, Stephanie; Hamacher, Kay; Goesele, Michael; Wiemeyer, Josef; von Landesberger, Tatiana

2014-01-01

Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.

Contemporary pollen flow, characterization of the maternal ecological neighbourhood and mating patterns in wild cherry (Prunus avium L.).

PubMed

Cottrell, J E; Vaughan, S P; Connolly, T; Sing, L; Moodley, D J; Russell, K

2009-08-01

Conversion of lowland woodland to agricultural land and resulting fragmentation in Britain has been ongoing since Neolithic times. To counteract this decline, plantations of native species, often based on non-British planting stock, have been established. This may ultimately be detrimental to the integrity of the native gene pool. We explore the genetic and ecological factors influencing the success of components of the local pollen pool, including the effect of a non-native planting on an ancient woodland population of wild cherry. Wild cherry exhibits gametophytic self-incompatibility (GSI) and vegetative reproduction, both of which may be determinants of paternal success. The majority (61%) of the successful pollen originated from within the study site with a maximum pollen transfer distance of 694 m. There was a distinct departure from random mating, with over half the successful pollen originating from trees which occur within 100 m of the mother tree. Self-incompatibility, clonality, tree size and proximity to the mother tree were all found to influence paternal success. Kinship of pollen gametes within a maternal progeny was highest when a mother tree was surrounded by a large number of ramets of a single, compatible clone consisting of large, adult trees. Although the contribution from the non-native plantation is currently low, it is likely that this will increasingly contribute to the progeny of the adjacent ancient population as it matures. The results clearly show that in self-incompatible species, such as P. avium, close neighbours may be pollinated by very different components of the local pollen pool.

Random sampling of constrained phylogenies: conducting phylogenetic analyses when the phylogeny is partially known.

PubMed

Housworth, E A; Martins, E P

2001-01-01

Statistical randomization tests in evolutionary biology often require a set of random, computer-generated trees. For example, earlier studies have shown how large numbers of computer-generated trees can be used to conduct phylogenetic comparative analyses even when the phylogeny is uncertain or unknown. These methods were limited, however, in that (in the absence of molecular sequence or other data) they allowed users to assume that no phylogenetic information was available or that all possible trees were known. Intermediate situations where only a taxonomy or other limited phylogenetic information (e.g., polytomies) are available are technically more difficult. The current study describes a procedure for generating random samples of phylogenies while incorporating limited phylogenetic information (e.g., four taxa belong together in a subclade). The procedure can be used to conduct comparative analyses when the phylogeny is only partially resolved or can be used in other randomization tests in which large numbers of possible phylogenies are needed.

Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

PubMed Central

Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

2015-01-01

Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

Predictive equations for dimensions and leaf area of coastal Southern California street trees

Treesearch

P.J. Peper; E.G. McPherson; S.M. Mori

2001-01-01

Tree height, crown height, crown width, diameter at breast height (dbh), and leaf area were measured for 16 species of commonly planted street trees in the coastal southern California city of Santa Monica, USA. The randomly sampled trees were planted from 1 to 44 years ago. Using number of years after planting or dbh as explanatory variables, mean values of dbh, tree...

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

PubMed

Esmaily, Habibollah; Tayefi, Maryam; Doosti, Hassan; Ghayour-Mobarhan, Majid; Nezami, Hossein; Amirabadizadeh, Alireza

2018-04-24

We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. A cross-sectional study. The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

Disassortativity of random critical branching trees

NASA Astrophysics Data System (ADS)

Kim, J. S.; Kahng, B.; Kim, D.

2009-06-01

Random critical branching trees (CBTs) are generated by the multiplicative branching process, where the branching number is determined stochastically, independent of the degree of their ancestor. Here we show analytically that despite this stochastic independence, there exists the degree-degree correlation (DDC) in the CBT and it is disassortative. Moreover, the skeletons of fractal networks, the maximum spanning trees formed by the edge betweenness centrality, behave similarly to the CBT in the DDC. This analytic solution and observation support the argument that the fractal scaling in complex networks originates from the disassortativity in the DDC.

Object-oriented fault tree evaluation program for quantitative analyses

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1988-01-01

Object-oriented programming can be combined with fault free techniques to give a significantly improved environment for evaluating the safety and reliability of large complex systems for space missions. Deep knowledge about system components and interactions, available from reliability studies and other sources, can be described using objects that make up a knowledge base. This knowledge base can be interrogated throughout the design process, during system testing, and during operation, and can be easily modified to reflect design changes in order to maintain a consistent information source. An object-oriented environment for reliability assessment has been developed on a Texas Instrument (TI) Explorer LISP workstation. The program, which directly evaluates system fault trees, utilizes the object-oriented extension to LISP called Flavors that is available on the Explorer. The object representation of a fault tree facilitates the storage and retrieval of information associated with each event in the tree, including tree structural information and intermediate results obtained during the tree reduction process. Reliability data associated with each basic event are stored in the fault tree objects. The object-oriented environment on the Explorer also includes a graphical tree editor which was modified to display and edit the fault trees.

Effect of tree nuts on glycemic control in diabetes: a systematic review and meta-analysis of randomized controlled dietary trials.

PubMed

Viguiliouk, Effie; Kendall, Cyril W C; Blanco Mejia, Sonia; Cozma, Adrian I; Ha, Vanessa; Mirrahimi, Arash; Jayalath, Viranda H; Augustin, Livia S A; Chiavaroli, Laura; Leiter, Lawrence A; de Souza, Russell J; Jenkins, David J A; Sievenpiper, John L

2014-01-01

Tree nut consumption has been associated with reduced diabetes risk, however, results from randomized trials on glycemic control have been inconsistent. To provide better evidence for diabetes guidelines development, we conducted a systematic review and meta-analysis of randomized controlled trials to assess the effects of tree nuts on markers of glycemic control in individuals with diabetes. MEDLINE, EMBASE, CINAHL, and Cochrane databases through 6 April 2014. Randomized controlled trials ≥3 weeks conducted in individuals with diabetes that compare the effect of diets emphasizing tree nuts to isocaloric diets without tree nuts on HbA1c, fasting glucose, fasting insulin, and HOMA-IR. Two independent reviewer's extracted relevant data and assessed study quality and risk of bias. Data were pooled by the generic inverse variance method and expressed as mean differences (MD) with 95% CI's. Heterogeneity was assessed (Cochran Q-statistic) and quantified (I2). Twelve trials (n = 450) were included. Diets emphasizing tree nuts at a median dose of 56 g/d significantly lowered HbA1c (MD = -0.07% [95% CI:-0.10, -0.03%]; P = 0.0003) and fasting glucose (MD = -0.15 mmol/L [95% CI: -0.27, -0.02 mmol/L]; P = 0.03) compared with control diets. No significant treatment effects were observed for fasting insulin and HOMA-IR, however the direction of effect favoured tree nuts. Majority of trials were of short duration and poor quality. Pooled analyses show that tree nuts improve glycemic control in individuals with type 2 diabetes, supporting their inclusion in a healthy diet. Owing to the uncertainties in our analyses there is a need for longer, higher quality trials with a focus on using nuts to displace high-glycemic index carbohydrates. ClinicalTrials.gov NCT01630980.

Effect of Tree Nuts on Glycemic Control in Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Dietary Trials

PubMed Central

Viguiliouk, Effie; Kendall, Cyril W. C.; Blanco Mejia, Sonia; Cozma, Adrian I.; Ha, Vanessa; Mirrahimi, Arash; Jayalath, Viranda H.; Augustin, Livia S. A.; Chiavaroli, Laura; Leiter, Lawrence A.; de Souza, Russell J.; Jenkins, David J. A.; Sievenpiper, John L.

2014-01-01

Background Tree nut consumption has been associated with reduced diabetes risk, however, results from randomized trials on glycemic control have been inconsistent. Objective To provide better evidence for diabetes guidelines development, we conducted a systematic review and meta-analysis of randomized controlled trials to assess the effects of tree nuts on markers of glycemic control in individuals with diabetes. Data Sources MEDLINE, EMBASE, CINAHL, and Cochrane databases through 6 April 2014. Study Selection Randomized controlled trials ≥3 weeks conducted in individuals with diabetes that compare the effect of diets emphasizing tree nuts to isocaloric diets without tree nuts on HbA1c, fasting glucose, fasting insulin, and HOMA-IR. Data Extraction and Synthesis Two independent reviewer’s extracted relevant data and assessed study quality and risk of bias. Data were pooled by the generic inverse variance method and expressed as mean differences (MD) with 95% CI’s. Heterogeneity was assessed (Cochran Q-statistic) and quantified (I2). Results Twelve trials (n = 450) were included. Diets emphasizing tree nuts at a median dose of 56 g/d significantly lowered HbA1c (MD = −0.07% [95% CI:−0.10, −0.03%]; P = 0.0003) and fasting glucose (MD = −0.15 mmol/L [95% CI: −0.27, −0.02 mmol/L]; P = 0.03) compared with control diets. No significant treatment effects were observed for fasting insulin and HOMA-IR, however the direction of effect favoured tree nuts. Limitations Majority of trials were of short duration and poor quality. Conclusions Pooled analyses show that tree nuts improve glycemic control in individuals with type 2 diabetes, supporting their inclusion in a healthy diet. Owing to the uncertainties in our analyses there is a need for longer, higher quality trials with a focus on using nuts to displace high-glycemic index carbohydrates. Trial Registration ClinicalTrials.gov NCT01630980 PMID:25076495

Red-shouldered hawk nesting habitat preference in south Texas

USGS Publications Warehouse

Strobel, Bradley N.; Boal, Clint W.

2010-01-01

We examined nesting habitat preference by red-shouldered hawks Buteo lineatus using conditional logistic regression on characteristics measured at 27 occupied nest sites and 68 unused sites in 2005–2009 in south Texas. We measured vegetation characteristics of individual trees (nest trees and unused trees) and corresponding 0.04-ha plots. We evaluated the importance of tree and plot characteristics to nesting habitat selection by comparing a priori tree-specific and plot-specific models using Akaike's information criterion. Models with only plot variables carried 14% more weight than models with only center tree variables. The model-averaged odds ratios indicated red-shouldered hawks selected to nest in taller trees and in areas with higher average diameter at breast height than randomly available within the forest stand. Relative to randomly selected areas, each 1-m increase in nest tree height and 1-cm increase in the plot average diameter at breast height increased the probability of selection by 85% and 10%, respectively. Our results indicate that red-shouldered hawks select nesting habitat based on vegetation characteristics of individual trees as well as the 0.04-ha area surrounding the tree. Our results indicate forest management practices resulting in tall forest stands with large average diameter at breast height would benefit red-shouldered hawks in south Texas.

Where to plant urban trees? A spatially explicit methodology to explore ecosystem service tradeoffs

Treesearch

E.W. Bodnaruk; C.N. Kroll; Y. Yang; S. Hirabayashi; David Nowak; T.A. Endreny

2017-01-01

Urban trees can help mitigate some of the environmental degradation linked to the rapid urbanization of humanity. Many municipalities are implementing ambitious tree planting programs to help remove air pollution, mitigate urban heat island effects, and provide other ecosystem services and benefits but lack quantitative tools to explore priority planting locations and...

Analyzing and synthesizing phylogenies using tree alignment graphs.

PubMed

Smith, Stephen A; Brown, Joseph W; Hinchliff, Cody E

2013-01-01

Phylogenetic trees are used to analyze and visualize evolution. However, trees can be imperfect datatypes when summarizing multiple trees. This is especially problematic when accommodating for biological phenomena such as horizontal gene transfer, incomplete lineage sorting, and hybridization, as well as topological conflict between datasets. Additionally, researchers may want to combine information from sets of trees that have partially overlapping taxon sets. To address the problem of analyzing sets of trees with conflicting relationships and partially overlapping taxon sets, we introduce methods for aligning, synthesizing and analyzing rooted phylogenetic trees within a graph, called a tree alignment graph (TAG). The TAG can be queried and analyzed to explore uncertainty and conflict. It can also be synthesized to construct trees, presenting an alternative to supertrees approaches. We demonstrate these methods with two empirical datasets. In order to explore uncertainty, we constructed a TAG of the bootstrap trees from the Angiosperm Tree of Life project. Analysis of the resulting graph demonstrates that areas of the dataset that are unresolved in majority-rule consensus tree analyses can be understood in more detail within the context of a graph structure, using measures incorporating node degree and adjacency support. As an exercise in synthesis (i.e., summarization of a TAG constructed from the alignment trees), we also construct a TAG consisting of the taxonomy and source trees from a recent comprehensive bird study. We synthesized this graph into a tree that can be reconstructed in a repeatable fashion and where the underlying source information can be updated. The methods presented here are tractable for large scale analyses and serve as a basis for an alternative to consensus tree and supertree methods. Furthermore, the exploration of these graphs can expose structures and patterns within the dataset that are otherwise difficult to observe.

Analyzing and Synthesizing Phylogenies Using Tree Alignment Graphs

PubMed Central

Smith, Stephen A.; Brown, Joseph W.; Hinchliff, Cody E.

2013-01-01

Phylogenetic trees are used to analyze and visualize evolution. However, trees can be imperfect datatypes when summarizing multiple trees. This is especially problematic when accommodating for biological phenomena such as horizontal gene transfer, incomplete lineage sorting, and hybridization, as well as topological conflict between datasets. Additionally, researchers may want to combine information from sets of trees that have partially overlapping taxon sets. To address the problem of analyzing sets of trees with conflicting relationships and partially overlapping taxon sets, we introduce methods for aligning, synthesizing and analyzing rooted phylogenetic trees within a graph, called a tree alignment graph (TAG). The TAG can be queried and analyzed to explore uncertainty and conflict. It can also be synthesized to construct trees, presenting an alternative to supertrees approaches. We demonstrate these methods with two empirical datasets. In order to explore uncertainty, we constructed a TAG of the bootstrap trees from the Angiosperm Tree of Life project. Analysis of the resulting graph demonstrates that areas of the dataset that are unresolved in majority-rule consensus tree analyses can be understood in more detail within the context of a graph structure, using measures incorporating node degree and adjacency support. As an exercise in synthesis (i.e., summarization of a TAG constructed from the alignment trees), we also construct a TAG consisting of the taxonomy and source trees from a recent comprehensive bird study. We synthesized this graph into a tree that can be reconstructed in a repeatable fashion and where the underlying source information can be updated. The methods presented here are tractable for large scale analyses and serve as a basis for an alternative to consensus tree and supertree methods. Furthermore, the exploration of these graphs can expose structures and patterns within the dataset that are otherwise difficult to observe. PMID:24086118

Summer roosting by adult male seminole bats in the Ouachita Mountains, Arkansas

Treesearch

Roger W. Perry; Ronald E. Thill

2007-01-01

We used radiotelemetry to locate 51 diurnal roosts for 17 male Seminole bats (Lasiurus seminolus) during late spring and early summer, 2000–2005. We quantified characteristics of roost trees and sites surrounding roosts and compared those measurements with random trees and random locations. All but two roosts were located in the foliage of large...

Urban tree cover change in Detroit and Atlanta, USA, 1951-2010

Treesearch

Krista Merry; Jacek Siry; Pete Bettinger; J.M. Bowker

2014-01-01

We assessed tree cover using random points and polygons distributed within the administrative boundaries of Detroit, MI and Atlanta, GA. Two approaches were tested, a point-based approach using 1000 randomly located sample points, and polygon-based approach using 250 circular areas, 200 m in radius (12.56 ha). In the case of Atlanta, both approaches arrived at similar...

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.

On Tree-Based Phylogenetic Networks.

PubMed

Zhang, Louxin

2016-07-01

A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.

How mutation affects evolutionary games on graphs

PubMed Central

Allen, Benjamin; Traulsen, Arne; Tarnita, Corina E.; Nowak, Martin A.

2011-01-01

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory, specifically the analysis of coalescing random walks via generating functions. These techniques allow us to derive exact identity-by-descent (IBD) probabilities, which characterize spatial assortment on lattices and Cayley trees. From these IBD probabilities we obtain exact conditions for the evolution of cooperation and other game strategies, showing the dual effects of graph topology and mutation rate. High mutation rates diminish the clustering of cooperators, hindering their evolutionary success. Our model can represent either genetic evolution with mutation, or social imitation processes with random strategy exploration. PMID:21473871

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.

Methods in Symbolic Computation and p-Adic Valuations of Polynomials

NASA Astrophysics Data System (ADS)

Guan, Xiao

Symbolic computation has widely appear in many mathematical fields such as combinatorics, number theory and stochastic processes. The techniques created in the area of experimental mathematics provide us efficient ways of symbolic computing and verification of complicated relations. Part I consists of three problems. The first one focuses on a unimodal sequence derived from a quartic integral. Many of its properties are explored with the help of hypergeometric representations and automatic proofs. The second problem tackles the generating function of the reciprocal of Catalan number. It springs from the closed form given by Mathematica. Furthermore, three methods in special functions are used to justify this result. The third issue addresses the closed form solutions for the moments of products of generalized elliptic integrals , which combines the experimental mathematics and classical analysis. Part II concentrates on the p-adic valuations of polynomials from the perspective of trees. For a given polynomial f( n) indexed in positive integers, the package developed in Mathematica will create certain tree structure following a couple of rules. The evolution of such trees are studied both rigorously and experimentally from the view of field extension, nonparametric statistics and random matrix.

Seeing the forest for the trees: utilizing modified random forests imputation of forest plot data for landscape-level analyses

Treesearch

Karin L. Riley; Isaac C. Grenfell; Mark A. Finney

2015-01-01

Mapping the number, size, and species of trees in forests across the western United States has utility for a number of research endeavors, ranging from estimation of terrestrial carbon resources to tree mortality following wildfires. For landscape fire and forest simulations that use the Forest Vegetation Simulator (FVS), a tree-level dataset, or “tree list”, is a...

Efficient Exploration of the Space of Reconciled Gene Trees

PubMed Central

Szöllősi, Gergely J.; Rosikiewicz, Wojciech; Boussau, Bastien; Tannier, Eric; Daubin, Vincent

2013-01-01

Gene trees record the combination of gene-level events, such as duplication, transfer and loss (DTL), and species-level events, such as speciation and extinction. Gene tree–species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species-level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees, the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree–species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of gene trees. We implement the ALE approach in the context of a reconciliation model (Szöllősi et al. 2013), which allows for the DTL of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood among all such trees. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic gene tree topologies, branch lengths, and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with respectively. 24%, 59%, and 46% reductions in the mean numbers of duplications, transfers, and losses per gene family. The open source implementation of ALE is available from https://github.com/ssolo/ALE.git. [amalgamation; gene tree reconciliation; gene tree reconstruction; lateral gene transfer; phylogeny.] PMID:23925510

Exploring diversity in ensemble classification: Applications in large area land cover mapping

NASA Astrophysics Data System (ADS)

Mellor, Andrew; Boukir, Samia

2017-07-01

Ensemble classifiers, such as random forests, are now commonly applied in the field of remote sensing, and have been shown to perform better than single classifier systems, resulting in reduced generalisation error. Diversity across the members of ensemble classifiers is known to have a strong influence on classification performance - whereby classifier errors are uncorrelated and more uniformly distributed across ensemble members. The relationship between ensemble diversity and classification performance has not yet been fully explored in the fields of information science and machine learning and has never been examined in the field of remote sensing. This study is a novel exploration of ensemble diversity and its link to classification performance, applied to a multi-class canopy cover classification problem using random forests and multisource remote sensing and ancillary GIS data, across seven million hectares of diverse dry-sclerophyll dominated public forests in Victoria Australia. A particular emphasis is placed on analysing the relationship between ensemble diversity and ensemble margin - two key concepts in ensemble learning. The main novelty of our work is on boosting diversity by emphasizing the contribution of lower margin instances used in the learning process. Exploring the influence of tree pruning on diversity is also a new empirical analysis that contributes to a better understanding of ensemble performance. Results reveal insights into the trade-off between ensemble classification accuracy and diversity, and through the ensemble margin, demonstrate how inducing diversity by targeting lower margin training samples is a means of achieving better classifier performance for more difficult or rarer classes and reducing information redundancy in classification problems. Our findings inform strategies for collecting training data and designing and parameterising ensemble classifiers, such as random forests. This is particularly important in large area remote sensing applications, for which training data is costly and resource intensive to collect.

The coalescent of a sample from a binary branching process.

PubMed

Lambert, Amaury

2018-04-25

At time 0, start a time-continuous binary branching process, where particles give birth to a single particle independently (at a possibly time-dependent rate) and die independently (at a possibly time-dependent and age-dependent rate). A particular case is the classical birth-death process. Stop this process at time T>0. It is known that the tree spanned by the N tips alive at time T of the tree thus obtained (called a reduced tree or coalescent tree) is a coalescent point process (CPP), which basically means that the depths of interior nodes are independent and identically distributed (iid). Now select each of the N tips independently with probability y (Bernoulli sample). It is known that the tree generated by the selected tips, which we will call the Bernoulli sampled CPP, is again a CPP. Now instead, select exactly k tips uniformly at random among the N tips (a k-sample). We show that the tree generated by the selected tips is a mixture of Bernoulli sampled CPPs with the same parent CPP, over some explicit distribution of the sampling probability y. An immediate consequence is that the genealogy of a k-sample can be obtained by the realization of k random variables, first the random sampling probability Y and then the k-1 node depths which are iid conditional on Y=y. Copyright © 2018. Published by Elsevier Inc.

What is the danger of the anomaly zone for empirical phylogenetics?

PubMed

Huang, Huateng; Knowles, L Lacey

2009-10-01

The increasing number of observations of gene trees with discordant topologies in phylogenetic studies has raised awareness about the problems of incongruence between species trees and gene trees. Moreover, theoretical treatments focusing on the impact of coalescent variance on phylogenetic study have also identified situations where the most probable gene trees are ones that do not match the underlying species tree (i.e., anomalous gene trees [AGTs]). However, although the theoretical proof of the existence of AGTs is alarming, the actual risk that AGTs pose to empirical phylogenetic study is far from clear. Establishing the conditions (i.e., the branch lengths in a species tree) for which AGTs are possible does not address the critical issue of how prevalent they might be. Furthermore, theoretical characterization of the species trees for which AGTs may pose a problem (i.e., the anomaly zone or the species histories for which AGTs are theoretically possible) is based on consideration of just one source of variance that contributes to species tree and gene tree discord-gene lineage coalescence. Yet, empirical data contain another important stochastic component-mutational variance. Estimated gene trees will differ from the underlying gene trees (i.e., the actual genealogy) because of the random process of mutation. Here, we take a simulation approach to investigate the prevalence of AGTs, among estimated gene trees, thereby characterizing the boundaries of the anomaly zone taking into account both coalescent and mutational variances. We also determine the frequency of realized AGTs, which is critical to putting the theoretical work on AGTs into a realistic biological context. Two salient results emerge from this investigation. First, our results show that mutational variance can indeed expand the parameter space (i.e., the relative branch lengths in a species tree) where AGTs might be observed in empirical data. By exploring the underlying cause for the expanded anomaly zone, we identify aspects of empirical data relevant to avoiding the problems that AGTs pose for species tree inference from multilocus data. Second, for the empirical species histories where AGTs are possible, unresolved trees-not AGTs-predominate the pool of estimated gene trees. This result suggests that the risk of AGTs, while they exist in theory, may rarely be realized in practice. By considering the biological realities of both mutational and coalescent variances, the study has refined, and redefined, what the actual challenges are for empirical phylogenetic study of recently diverged taxa that have speciated rapidly-AGTs themselves are unlikely to pose a significant danger to empirical phylogenetic study.

Tree species exhibit complex patterns of distribution in bottomland hardwood forests

Treesearch

Luben D Dimov; Jim L Chambers; Brian R. Lockhart

2013-01-01

& Context Understanding tree interactions requires an insight into their spatial distribution. & Aims We looked for presence and extent of tree intraspecific spatial point pattern (random, aggregated, or overdispersed) and interspecific spatial point pattern (independent, aggregated, or segregated). & Methods We established twelve 0.64-ha plots in natural...

Use of DNA markers in forest tree improvement research

Treesearch

D.B. Neale; M.E. Devey; K.D. Jermstad; M.R. Ahuja; M.C. Alosi; K.A. Marshall

1992-01-01

DNA markers are rapidly being developed for forest trees. The most important markers are restriction fragment length polymorphisms (RFLPs), polymerase chain reaction- (PCR) based markers such as random amplified polymorphic DNA (RAPD), and fingerprinting markers. DNA markers can supplement isozyme markers for monitoring tree improvement activities such as; estimating...

Multispectral color photography for mineral exploration by the remote sensing of biogeochemical anomalies

NASA Technical Reports Server (NTRS)

Yost, E.

1975-01-01

Selected band multispectral photography was evaluated as a mineral exploration tool by detecting stress on trees caused by underground mineralization. Ground truth consisted of two test sites in the Prescott National Forest within which the mineralization had been established by a drilling program. Species of trees were categorized as background, intermediate, and anomalous based upon where they grew with respect to this underlying mineralization. Soil geochemistry and the metal content of ashed samples of the trees were studied in relation to the inferred locus of mineralization. Computer analysis of the reflectance spectra of mineralized trees confirmed that the relative percent reflectance differences of trees growing in anomalous areas was less than that of the same tree species growing in background areas.

An analysis of tree mortality using high resolution remotely-sensed data for mixed-conifer forests in San Diego county

NASA Astrophysics Data System (ADS)

Freeman, Mary Pyott

ABSTRACT An Analysis of Tree Mortality Using High Resolution Remotely-Sensed Data for Mixed-Conifer Forests in San Diego County by Mary Pyott Freeman The montane mixed-conifer forests of San Diego County are currently experiencing extensive tree mortality, which is defined as dieback where whole stands are affected. This mortality is likely the result of the complex interaction of many variables, such as altered fire regimes, climatic conditions such as drought, as well as forest pathogens and past management strategies. Conifer tree mortality and its spatial pattern and change over time were examined in three components. In component 1, two remote sensing approaches were compared for their effectiveness in delineating dead trees, a spatial contextual approach and an OBIA (object based image analysis) approach, utilizing various dates and spatial resolutions of airborne image data. For each approach transforms and masking techniques were explored, which were found to improve classifications, and an object-based assessment approach was tested. In component 2, dead tree maps produced by the most effective techniques derived from component 1 were utilized for point pattern and vector analyses to further understand spatio-temporal changes in tree mortality for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Results indicate that conifer mortality was significantly clustered, increased substantially between 2002 and 2005, and was non-random with respect to tree species and diameter class sizes. In component 3, multiple environmental variables were used in Generalized Linear Model (GLM-logistic regression) and decision tree classifier model development, revealing the importance of climate and topographic factors such as precipitation and elevation, in being able to predict areas of high risk for tree mortality. The results from this study highlight the importance of multi-scale spatial as well as temporal analyses, in order to understand mixed-conifer forest structure, dynamics, and processes of decline, which can lead to more sustainable management of forests with continued natural and anthropogenic disturbance.

Parallel Mitogenome Sequencing Alleviates Random Rooting Effect in Phylogeography.

PubMed

Hirase, Shotaro; Takeshima, Hirohiko; Nishida, Mutsumi; Iwasaki, Wataru

2016-04-28

Reliably rooted phylogenetic trees play irreplaceable roles in clarifying diversification in the patterns of species and populations. However, such trees are often unavailable in phylogeographic studies, particularly when the focus is on rapidly expanded populations that exhibit star-like trees. A fundamental bottleneck is known as the random rooting effect, where a distant outgroup tends to root an unrooted tree "randomly." We investigated whether parallel mitochondrial genome (mitogenome) sequencing alleviates this effect in phylogeography using a case study on the Sea of Japan lineage of the intertidal goby Chaenogobius annularis Eighty-three C. annularis individuals were collected and their mitogenomes were determined by high-throughput and low-cost parallel sequencing. Phylogenetic analysis of these mitogenome sequences was conducted to root the Sea of Japan lineage, which has a star-like phylogeny and had not been reliably rooted. The topologies of the bootstrap trees were investigated to determine whether the use of mitogenomes alleviated the random rooting effect. The mitogenome data successfully rooted the Sea of Japan lineage by alleviating the effect, which hindered phylogenetic analysis that used specific gene sequences. The reliable rooting of the lineage led to the discovery of a novel, northern lineage that expanded during an interglacial period with high bootstrap support. Furthermore, the finding of this lineage suggested the existence of additional glacial refugia and provided a new recent calibration point that revised the divergence time estimation between the Sea of Japan and Pacific Ocean lineages. This study illustrates the effectiveness of parallel mitogenome sequencing for solving the random rooting problem in phylogeographic studies. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Improving ensemble decision tree performance using Adaboost and Bagging

NASA Astrophysics Data System (ADS)

Hasan, Md. Rajib; Siraj, Fadzilah; Sainin, Mohd Shamrie

2015-12-01

Ensemble classifier systems are considered as one of the most promising in medical data classification and the performance of deceision tree classifier can be increased by the ensemble method as it is proven to be better than single classifiers. However, in a ensemble settings the performance depends on the selection of suitable base classifier. This research employed two prominent esemble s namely Adaboost and Bagging with base classifiers such as Random Forest, Random Tree, j48, j48grafts and Logistic Model Regression (LMT) that have been selected independently. The empirical study shows that the performance varries when different base classifiers are selected and even some places overfitting issue also been noted. The evidence shows that ensemble decision tree classfiers using Adaboost and Bagging improves the performance of selected medical data sets.

APHiD: Hierarchical Task Placement to Enable a Tapered Fat Tree Topology for Lower Power and Cost in HPC Networks

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

Michelogiannakis, George; Ibrahim, Khaled Z.; Shalf, John

The power and procurement cost of bandwidth in system-wide networks has forced a steady drop in the byte/flop ratio. This trend of computation becoming faster relative to the network is expected to hold. In this paper, we explore how cost-oriented task placement enables reducing the cost of system-wide networks by enabling high performance even on tapered topologies where more bandwidth is provisioned at lower levels. We describe APHiD, an efficient hierarchical placement algorithm that uses new techniques to improve the quality of heuristic solutions and reduces the demand on high-level, expensive bandwidth in hierarchical topologies. We apply APHiD to amore » tapered fat-tree, demonstrating that APHiD maintains application scalability even for severely tapered network configurations. Using simulation, we show that for tapered networks APHiD improves performance by more than 50% over random placement and even 15% in some cases over costlier, state-of-the-art placement algorithms.« less

Analysis of biweight site chronologies: relative weights of individual trees over time

Treesearch

Kurt H. Riitters

1990-01-01

The relative weights on individual trees in a biweight site chronology can indicate the consistency of tree growth responses to macroclimate and can be the basis for stratifying trees in climate-growth analyses. This was explored with 45 years of ring-width indices for 200 trees from five even-aged jack pine (Pinus hanksiana Lamb.) stands. Average individual-tree...

Pedological memory in forest soil development

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2004-01-01

Individual trees may have significant impacts on soil morphology. If these impacts are non-random such that some microsites are repeatedly preferentially affected by trees, complex local spatial variability of soils would result. A model of self-reinforcing pedologic influences of trees (SRPIT) is proposed to explain patterns of soil variability in the Ouachita...

Influence of tree spatial pattern and sample plot type and size on inventory

Treesearch

John-Pascall Berrill; Kevin L. O' Hara

2012-01-01

Sampling with different plot types and sizes was simulated using tree location maps and data collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius circular plots, belt transects, and variable-radius plots were installed by...

Fels-Rand: an Xlisp-Stat program for the comparative analysis of data under phylogenetic uncertainty.

PubMed

Blomberg, S

2000-11-01

Currently available programs for the comparative analysis of phylogenetic data do not perform optimally when the phylogeny is not completely specified (i.e. the phylogeny contains polytomies). Recent literature suggests that a better way to analyse the data would be to create random trees from the known phylogeny that are fully-resolved but consistent with the known tree. A computer program is presented, Fels-Rand, that performs such analyses. A randomisation procedure is used to generate trees that are fully resolved but whose structure is consistent with the original tree. Statistics are then calculated on a large number of these randomly-generated trees. Fels-Rand uses the object-oriented features of Xlisp-Stat to manipulate internal tree representations. Xlisp-Stat's dynamic graphing features are used to provide heuristic tools to aid in analysis, particularly outlier analysis. The usefulness of Xlisp-Stat as a system for phylogenetic computation is discussed. Available from the author or at http://www.uq.edu.au/~ansblomb/Fels-Rand.sit.hqx. Xlisp-Stat is available from http://stat.umn.edu/~luke/xls/xlsinfo/xlsinfo.html. s.blomberg@abdn.ac.uk

Process model simulations of the divergence effect

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Evans, M. N.; D'Arrigo, R. D.; Smerdon, J. E.; Hughes, M. K.; Kaplan, A.; Vaganov, E. A.

2007-12-01

We explore the extent to which the Vaganov-Shashkin (VS) model of conifer tree-ring formation can explain evidence for changing relationships between climate and tree growth over recent decades. The VS model is driven by daily environmental forcing (temperature, soil moisture, and solar radiation), and simulates tree-ring growth cell-by-cell as a function of the most limiting environmental control. This simplified representation of tree physiology allows us to examine using a selection of case studies whether instances of divergence may be explained in terms of changes in limiting environmental dependencies or transient climate change. Identification of model-data differences permits further exploration of the effects of tree-ring standardization, atmospheric composition, and additional non-climatic factors.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon.

PubMed

Rifai, Sami W; Urquiza Muñoz, José D; Negrón-Juárez, Robinson I; Ramírez Arévalo, Fredy R; Tello-Espinoza, Rodil; Vanderwel, Mark C; Lichstein, Jeremy W; Chambers, Jeffrey Q; Bohlman, Stephanie A

2016-10-01

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality. © 2016 by the Ecological Society of America.

Local random configuration-tree theory for string repetition and facilitated dynamics of glass

NASA Astrophysics Data System (ADS)

Lam, Chi-Hang

2018-02-01

We derive a microscopic theory of glassy dynamics based on the transport of voids by micro-string motions, each of which involves particles arranged in a line hopping simultaneously displacing one another. Disorder is modeled by a random energy landscape quenched in the configuration space of distinguishable particles, but transient in the physical space as expected for glassy fluids. We study the evolution of local regions with m coupled voids. At a low temperature, energetically accessible local particle configurations can be organized into a random tree with nodes and edges denoting configurations and micro-string propagations respectively. Such trees defined in the configuration space naturally describe systems defined in two- or three-dimensional physical space. A micro-string propagation initiated by a void can facilitate similar motions by other voids via perturbing the random energy landscape, realizing path interactions between voids or equivalently string interactions. We obtain explicit expressions of the particle diffusion coefficient and a particle return probability. Under our approximation, as temperature decreases, random trees of energetically accessible configurations exhibit a sequence of percolation transitions in the configuration space, with local regions containing fewer coupled voids entering the non-percolating immobile phase first. Dynamics is dominated by coupled voids of an optimal group size, which increases as temperature decreases. Comparison with a distinguishable-particle lattice model (DPLM) of glass shows very good quantitative agreements using only two adjustable parameters related to typical energy fluctuations and the interaction range of the micro-strings.

Exploration of a rare population of Chinese chestnut in North America: stand dynamics, health and genetic relationships

PubMed Central

Miller, Amy C.; Woeste, Keith E.; Anagnostakis, Sandra L.; Jacobs, Douglass F.

2014-01-01

With the transport of plants around the globe, exotic species can readily spread disease to their native relatives; however, they can also provide genetic resistance to those relatives through hybrid breeding programmes. American chestnut (Castanea dentata) was an abundant tree species in North America until its decimation by introduced chestnut blight. To restore chestnut in North America, efforts are ongoing to test putative blight-resistant hybrids of Castanea dentata and Chinese chestnut (Castanea mollissima), but little is known about the ecology of C. mollissima. In a forest in northeastern USA in which C. mollissima has become established, we explored questions of stand dynamics, health and genetic relationships of C. mollissima offspring to an adjacent parent orchard. We found that C. mollissima was adapted and randomly distributed among native species in this relatively young forest. The genetics of the C. mollissima population compared with its parents indicated little effect of selection pressure as each of the parent trees contributed at least one offspring. The ease with which this exotic species proliferated calls to question why C. mollissima is rare elsewhere in forests of North America. It is likely that a time window of low animal predation allowed seedlings to establish, and the shallow soil at this site limited the maximum forest canopy height, permitting the characteristically short-statured C. mollissima to avoid suppression. Our results indicate that because C. mollissima exhibited pioneer species characteristics, hybrids between C. mollissima and C. dentata have the potential to be successful pioneer species of future forests in North America, and we challenge the paradigm that exotic tree species are wholly detrimental to native biodiversity. We contend that exotic tree species should be assessed not only by their level of threat to native species, but also by their potential positive impacts on ecosystems via hybrid breeding programmes. PMID:25336337

Exploration of a rare population of Chinese chestnut in North America: stand dynamics, health and genetic relationships.

PubMed

Miller, Amy C; Woeste, Keith E; Anagnostakis, Sandra L; Jacobs, Douglass F

2014-10-20

With the transport of plants around the globe, exotic species can readily spread disease to their native relatives; however, they can also provide genetic resistance to those relatives through hybrid breeding programmes. American chestnut (Castanea dentata) was an abundant tree species in North America until its decimation by introduced chestnut blight. To restore chestnut in North America, efforts are ongoing to test putative blight-resistant hybrids of Castanea dentata and Chinese chestnut (Castanea mollissima), but little is known about the ecology of C. mollissima. In a forest in northeastern USA in which C. mollissima has become established, we explored questions of stand dynamics, health and genetic relationships of C. mollissima offspring to an adjacent parent orchard. We found that C. mollissima was adapted and randomly distributed among native species in this relatively young forest. The genetics of the C. mollissima population compared with its parents indicated little effect of selection pressure as each of the parent trees contributed at least one offspring. The ease with which this exotic species proliferated calls to question why C. mollissima is rare elsewhere in forests of North America. It is likely that a time window of low animal predation allowed seedlings to establish, and the shallow soil at this site limited the maximum forest canopy height, permitting the characteristically short-statured C. mollissima to avoid suppression. Our results indicate that because C. mollissima exhibited pioneer species characteristics, hybrids between C. mollissima and C. dentata have the potential to be successful pioneer species of future forests in North America, and we challenge the paradigm that exotic tree species are wholly detrimental to native biodiversity. We contend that exotic tree species should be assessed not only by their level of threat to native species, but also by their potential positive impacts on ecosystems via hybrid breeding programmes. Published by Oxford University Press on behalf of the Annals of Botany Company.

A Randomized Controlled Trial of Interventions to Impede Date Palm Sap Contamination by Bats to Prevent Nipah Virus Transmission in Bangladesh

PubMed Central

Khan, Salah Uddin; Gurley, Emily S.; Hossain, M. Jahangir; Nahar, Nazmun; Sharker, M. A. Yushuf; Luby, Stephen P.

2012-01-01

Background Drinking raw date palm sap is a risk factor for human Nipah virus (NiV) infection. Fruit bats, the natural reservoir of NiV, commonly contaminate raw sap with saliva by licking date palm’s sap producing surface. We evaluated four types of physical barriers that may prevent bats from contacting sap. Methods During 2009, we used a crossover design and randomly selected 20 date palm sap producing trees and observed each tree for 2 nights: one night with a bamboo skirt intervention applied and one night without the intervention. During 2010, we selected 120 trees and randomly assigned four types of interventions to 15 trees each: bamboo, dhoincha (local plant), jute stick and polythene skirts covering the shaved part, sap stream, tap and collection pot. We enrolled the remaining 60 trees as controls. We used motion sensor activated infrared cameras to examine bat contact with sap. Results During 2009 bats contacted date palm sap in 85% of observation nights when no intervention was used compared with 35% of nights when the intervention was used [p<0.001]. Bats were able to contact the sap when the skirt did not entirely cover the sap producing surface. Therefore, in 2010 we requested the sap harvesters to use larger skirts. During 2010 bats contacted date palm sap [2% vs. 83%, p<0.001] less frequently in trees protected with skirts compared to control trees. No bats contacted sap in trees with bamboo (p<0.001 compared to control), dhoincha skirt (p<0.001) or polythene covering (p<0.001), but bats did contact sap during one night (7%) with the jute stick skirt (p<0.001). Conclusion Bamboo, dhoincha, jute stick and polythene skirts covering the sap producing areas of a tree effectively prevented bat-sap contact. Community interventions should promote applying these skirts to prevent occasional Nipah spillovers to human. PMID:22905160

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

PubMed

Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

2018-01-19

OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

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.

Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses

Treesearch

Karin L. Riley; Isaac C. Grenfell; Mark A. Finney; Nicholas L. Crookston

2014-01-01

Maps of the number, size, and species of trees in forests across the United States are desirable for a number of applications. For landscape-level fire and forest simulations that use the Forest Vegetation Simulator (FVS), a spatial tree-level dataset, or “tree list”, is a necessity. FVS is widely used at the stand level for simulating fire effects on tree mortality,...

Trees: Dead or Alive. 4-H Leader's Guide 147-L-22.

ERIC Educational Resources Information Center

Krasny, Marianne E.

This illustrated leader's guide to exploring trees and forests provides activities which emphasize careful observation of trees and the living things associated with them for youths age 9 and older. Introductory information for leaders explains the uses for trees and the role of trees in the ecosystem. It also gives suggestions for leaders to…

Taper models for commercial tree species in the northeastern United States

Treesearch

James A. Westfall; Charles T. Scott

2010-01-01

A new taper model was developed based on the switching taper model of Valentine and Gregoire; the most substantial changes were reformulation to incorporate estimated join points and modification of a switching function. Random-effects parameters were included that account for within-tree correlations and allow for customized calibration to each individual tree. The...

Lifemap: Exploring the Entire Tree of Life.

PubMed

de Vienne, Damien M

2016-12-01

The Tree of Life (ToL) is meant to be a unique representation of the evolutionary relationships between all species on earth. Huge efforts are made to assemble such a large tree, helped by the decrease of sequencing costs and improved methods to reconstruct and combine phylogenies, but no tool exists today to explore the ToL in its entirety in a satisfying manner. By combining methods used in modern cartography, such as OpenStreetMap, with a new way of representing tree-like structures, I created Lifemap, a tool allowing the exploration of a complete representation of the ToL (between 800,000 and 2.2 million species depending on the data source) in a zoomable interface. A server version of Lifemap also allows users to visualize their own trees. This should help researchers in ecology and evolutionary biology in their everyday work, but may also permit the diffusion to a broader audience of our current knowledge of the evolutionary relationships linking all organisms.

Advanced Subspace Techniques for Modeling Channel and Session Variability in a Speaker Recognition System

DTIC Science & Technology

2012-03-01

with each SVM discriminating between a pair of the N total speakers in the data set. The (( + 1))/2 classifiers then vote on the final...classification of a test sample. The Random Forest classifier is an ensemble classifier that votes amongst decision trees generated with each node using...Forest vote , and the effects of overtraining will be mitigated by the fact that each decision tree is overtrained differently (due to the random

Inverted Signature Trees and Text Searching on CD-ROMs.

ERIC Educational Resources Information Center

Cooper, Lorraine K. D.; Tharp, Alan L.

1989-01-01

Explores the new storage technology of optical data disks and introduces a data structure, the inverted signature tree, for storing data on optical data disks for efficient text searching. The inverted signature tree approach is compared to the use of text signatures and the B+ tree. (22 references) (Author/CLB)

A Spring Playscape Project: Building a Tree Circle

ERIC Educational Resources Information Center

Keeler, Rusty

2009-01-01

The Tree Circle is a green gathering area for children made by planting trees in a circle. For children, the Tree Circle becomes a magical place for dramatic play, quiet retreat, or lively nature exploration. For teachers and parents it becomes a shady grove for snacks and stories. The trees create a sweet spot that changes during the seasons and…

Chip and truck: Comparing the cost of using trees to heat buildings

Treesearch

Robin Silverstein; Dan Loeffler; J. Greg Jones; Dave Calkin; Hans Zuuring; Martin Twer

2009-01-01

In the Western United States, many of the forests have too many small trees (figure 1). These small trees increase the risk of wildfire. Forest managers, therefore, want to remove the small trees. Some scientists believe these small trees may be a good source of fuel. To explore this possibility, a program called "Fuels for Schools" was created in...

Habitat relationships and nest site characteristics of cavity-nesting birds in cottonwood floodplains

USGS Publications Warehouse

Sedgwick, James A.; Knopf, Fritz L.

1990-01-01

We examined habitat relationships and nest site characteristics for 6 species of cavity-nesting birds--American kestrel (Falco sparverius), northern flicker (Colaptes auratus), red-headed woodpecker (Melanerpes erythrocephalus), black-capped chickadee (Parus atricapillus), house wren (Troglodytes aedon), and European starling (Sturnus vulgaris)--in a mature plains cottonwood (Populus sargentii) bottomland along the South Platte River in northeastern Colorado in 1985 and 1986. We examined characteristics of cavities, nest trees, and the habitat surrounding nest trees. Density of large trees (>69 cm dbh), total length of dead limbs ≥10 cm diameter (TDLL), and cavity density were the most important habitat variables; dead limb length (DLL), dbh, and species were the most important tree variables; and cavity height, cavity entrance diameter, and substrate condition at the cavity (live vs. dead) were the most important cavity variables in segregating cavity nesters along habitat, tree, and cavity dimensions, respectively. Random sites differed most from cavity-nesting bird sites on the basis of dbh, DLL, limb tree density (trees with ≥1 m dead limbs ≥10 cm diameter), and cavity density. Habitats of red-headed woodpeckers and American kestrels were the most unique, differing most from random sites. Based on current trends in cottonwood demography, densities of cavity-nesting birds will probably decline gradually along the South Platte River, paralleling a decline in DLL, limb tree density, snag density, and the concurrent lack of cottonwood regeneration.

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning

PubMed Central

Ichnowski, Jeffrey; Prins, Jan F.; Alterovitz, Ron

2014-01-01

We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU’s cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot’s configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot. PMID:25419474

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning.

PubMed

Ichnowski, Jeffrey; Prins, Jan F; Alterovitz, Ron

2014-05-01

We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU's cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot's configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot.

Predictors of suicidal ideation in older people: a decision tree analysis.

PubMed

Handley, Tonelle E; Hiles, Sarah A; Inder, Kerry J; Kay-Lambkin, Frances J; Kelly, Brian J; Lewin, Terry J; McEvoy, Mark; Peel, Roseanne; Attia, John R

2014-11-01

Suicide among older adults is a major public health issue worldwide. Although studies have identified psychological, physical, and social contributors to suicidal thoughts in older adults, few have explored the specific interactions between these factors. This article used a novel statistical approach to explore predictors of suicidal ideation in a community-based sample of older adults. Prospective cohort study. Participants aged 55-85 years were randomly selected from the Hunter Region, a large regional center in New South Wales, Australia. Baseline psychological, physical, and social factors, including psychological distress, physical functioning, and social support, were used to predict suicidal ideation at the 5-year follow-up. Classification and regression tree modeling was used to determine specific risk profiles for participants depending on their individual well-being in each of these key areas. Psychological distress was the strongest predictor, with 25% of people with high distress reporting suicidal ideation. Within high psychological distress, lower physical functioning significantly increased the likelihood of suicidal ideation, with high distress and low functioning being associated with ideation in 50% of cases. A substantial subgroup reported suicidal ideation in the absence of psychological distress; dissatisfaction with social support was the most important predictor among this group. The performance of the model was high (area under the curve: 0.81). Decision tree modeling enabled individualized "risk" profiles for suicidal ideation to be determined. Although psychological factors are important for predicting suicidal ideation, both physical and social factors significantly improved the predictive ability of the model. Assessing these factors may enhance identification of older people at risk of suicidal ideation. Copyright © 2014. Published by Elsevier Inc.

Contrasting natural regeneration and tree planting in fourteen North American cities

Treesearch

David J. Nowak

2012-01-01

Field data from randomly located plots in 12 cities in the United States and Canada were used to estimate the proportion of the existing tree population that was planted or occurred via natural regeneration. In addition, two cities (Baltimore and Syracuse) were recently re-sampled to estimate the proportion of newly established trees that were planted. Results for the...

Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots

Treesearch

Karin Riley; Isaac C. Grenfell; Mark A. Finney

2016-01-01

Maps of the number, size, and species of trees in forests across the western United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical...

Urban forest structure, ecosystem services and change in Syracuse, NY

Treesearch

David J. Nowak; Robert E. Hoehn; Allison R. Bodine; Eric J. Greenfield; Jarlath O' Neil-Dunne

2013-01-01

The tree population within the City of Syracuse was assessed using a random sampling of plots in 1999, 2001 and 2009 to determine how the population and the ecosystem services these trees provide have changed over time. Ecosystem services and values for carbon sequestration, air pollution removal and changes in building energy use were derived using the i-Tree Eco...

Evaluation of Agrilus planipennis (Coleoptera: Buprestidae) control provided by emamectin benzoate and two neonicotinoid insecticides, one and two seasons after treatment

Treesearch

Deborah G. McCullough; Therese M. Poland; Andrea C. Anulewicz; Phillip Lewis; David. Cappaert

2011-01-01

Effective methods are needed to protect ash trees (Fraxinus spp.) from emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), an invasive buprestid that has killed millions of North American ash (Fraxinus spp.) trees. We randomly assigned 175 ash trees (11.5-48.1 cm in diameter) in 25 blocks...

Beyond Flory theory: Distribution functions for interacting lattice trees

NASA Astrophysics Data System (ADS)

Rosa, Angelo; Everaers, Ralf

2017-01-01

While Flory theories [J. Isaacson and T. C. Lubensky, J. Physique Lett. 41, 469 (1980), 10.1051/jphyslet:019800041019046900; M. Daoud and J. F. Joanny, J. Physique 42, 1359 (1981), 10.1051/jphys:0198100420100135900; A. M. Gutin et al., Macromolecules 26, 1293 (1993), 10.1021/ma00058a016] provide an extremely useful framework for understanding the behavior of interacting, randomly branching polymers, the approach is inherently limited. Here we use a combination of scaling arguments and computer simulations to go beyond a Gaussian description. We analyze distribution functions for a wide variety of quantities characterizing the tree connectivities and conformations for the four different statistical ensembles, which we have studied numerically in [A. Rosa and R. Everaers, J. Phys. A: Math. Theor. 49, 345001 (2016), 10.1088/1751-8113/49/34/345001 and J. Chem. Phys. 145, 164906 (2016), 10.1063/1.4965827]: (a) ideal randomly branching polymers, (b) 2 d and 3 d melts of interacting randomly branching polymers, (c) 3 d self-avoiding trees with annealed connectivity, and (d) 3 d self-avoiding trees with quenched ideal connectivity. In particular, we investigate the distributions (i) pN(n ) of the weight, n , of branches cut from trees of mass N by severing randomly chosen bonds; (ii) pN(l ) of the contour distances, l , between monomers; (iii) pN(r ⃗) of spatial distances, r ⃗, between monomers, and (iv) pN(r ⃗|l ) of the end-to-end distance of paths of length l . Data for different tree sizes superimpose, when expressed as functions of suitably rescaled observables x ⃗=r ⃗/√{ } or x =l / . In particular, we observe a generalized Kramers relation for the branch weight distributions (i) and find that all the other distributions (ii-iv) are of Redner-des Cloizeaux type, q (x ⃗) =C |x| θexp(-(K|x |) t) . We propose a coherent framework, including generalized Fisher-Pincus relations, relating most of the RdC exponents to each other and to the contact and Flory exponents for interacting trees.

Parametric and non-parametric masking of randomness in sequence alignments can be improved and leads to better resolved trees.

PubMed

Kück, Patrick; Meusemann, Karen; Dambach, Johannes; Thormann, Birthe; von Reumont, Björn M; Wägele, Johann W; Misof, Bernhard

2010-03-31

Methods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective. ALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict. Alignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

NASA Astrophysics Data System (ADS)

Yadav, B.; Hatfield, K.

2017-12-01

We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Considering both the accuracy and the computational complexity of these algorithms, we identify the extremely randomized trees as the best performing algorithm for BFI prediction in ungauged basins.

An application of quantile random forests for predictive mapping of forest attributes

Treesearch

E.A. Freeman; G.G. Moisen

2015-01-01

Increasingly, random forest models are used in predictive mapping of forest attributes. Traditional random forests output the mean prediction from the random trees. Quantile regression forests (QRF) is an extension of random forests developed by Nicolai Meinshausen that provides non-parametric estimates of the median predicted value as well as prediction quantiles. It...

Semiautomated landscape feature extraction and modeling

NASA Astrophysics Data System (ADS)

Wasilewski, Anthony A.; Faust, Nickolas L.; Ribarsky, William

2001-08-01

We have developed a semi-automated procedure for generating correctly located 3D tree objects form overhead imagery. Cross-platform software partitions arbitrarily large, geocorrected and geolocated imagery into management sub- images. The user manually selected tree areas from one or more of these sub-images. Tree group blobs are then narrowed to lines using a special thinning algorithm which retains the topology of the blobs, and also stores the thickness of the parent blob. Maxima along these thinned tree grous are found, and used as individual tree locations within the tree group. Magnitudes of the local maxima are used to scale the radii of the tree objects. Grossly overlapping trees are culled based on a comparison of tree-tree distance to combined radii. Tree color is randomly selected based on the distribution of sample tree pixels, and height is estimated form tree radius. The final tree objects are then inserted into a terrain database which can be navigated by VGIS, a high-resolution global terrain visualization system developed at Georgia Tech.

Finding paths in tree graphs with a quantum walk

NASA Astrophysics Data System (ADS)

Koch, Daniel; Hillery, Mark

2018-01-01

We analyze the potential for different types of searches using the formalism of scattering random walks on quantum computers. Given a particular type of graph consisting of nodes and connections, a "tree maze," we would like to find a selected final node as quickly as possible, faster than any classical search algorithm. We show that this can be done using a quantum random walk, both through numerical calculations as well as by using the eigenvectors and eigenvalues of the quantum system.

Feasibility of harvesting southern hardwood trees by extraction

Treesearch

Donald L. Sirois

1977-01-01

A Rome TXH Tree Extractor was used to explore the harvesting of four species of southern hardwoods by extraction. The test indicate that harvesting by extraction is feasible for harvestang, if tree size is limited to 9 inches DBH or less. Stump and below ground biomass averaged 18 percent of total tree biomass.

Genetic relatedness among developing seeds and intra fruit seed abortion in Dalbergia sissoo (Fabaceae).

PubMed

Mohana, G S; Shaanker, R U; Ganeshaiah, K N; Dayanandan, S

2001-07-01

Dalbergia sissoo, a wind-dispersed tropical tree, exhibits high intrafruit seed abortion. Of the four to five ovules in the flower, generally one and occasionally two or three develop to maturity. It has been proposed that the seed abortion is a consequence of intense sibling competition for maternal resources and that this competition occurs as an inverse function of the genetic relatedness among the developing seeds. Accordingly, developing seeds compete intensely when they are genetically less related but tend to develop together when genetically more related. We tested this hypothesis by comparing the genetic similarity among the pairs of seeds developing within a pod with that among (a) random pairs from the pool of all seeds, (b) random pairs from single-seeded pods, and (c) random pairs from two-seeded pods, using both randomly amplified polymorphic DNA (RAPD) and isozymes in five trees. We found that the pairs of seeds developing within a pod are genetically more similar than any random pairs of seeds in a tree. Thus the formation of two-seeded pods appear to be associated with increased genetic relatedness among the developing seeds. We discuss the results in the context of possible fitness advantages and then discuss the possible mechanisms that promote tolerance among related seeds.

Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana.

PubMed

Berens, D G; Braun, C; González-Martínez, S C; Griebeler, E M; Nathan, R; Böhning-Gaese, K

2014-11-01

Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.

Anomalous scaling in an age-dependent branching model.

PubMed

Keller-Schmidt, Stephanie; Tuğrul, Murat; Eguíluz, Víctor M; Hernández-García, Emilio; Klemm, Konstantin

2015-02-01

We introduce a one-parametric family of tree growth models, in which branching probabilities decrease with branch age τ as τ(-α). Depending on the exponent α, the scaling of tree depth with tree size n displays a transition between the logarithmic scaling of random trees and an algebraic growth. At the transition (α=1) tree depth grows as (logn)(2). This anomalous scaling is in good agreement with the trend observed in evolution of biological species, thus providing a theoretical support for age-dependent speciation and associating it to the occurrence of a critical point.

TreePlus: interactive exploration of networks with enhanced tree layouts.

PubMed

Lee, Bongshin; Parr, Cynthia S; Plaisant, Catherine; Bederson, Benjamin B; Veksler, Vladislav D; Gray, Wayne D; Kotfila, Christopher

2006-01-01

Despite extensive research, it is still difficult to produce effective interactive layouts for large graphs. Dense layout and occlusion make food webs, ontologies, and social networks difficult to understand and interact with. We propose a new interactive Visual Analytics component called TreePlus that is based on a tree-style layout. TreePlus reveals the missing graph structure with visualization and interaction while maintaining good readability. To support exploration of the local structure of the graph and gathering of information from the extensive reading of labels, we use a guiding metaphor of "Plant a seed and watch it grow." It allows users to start with a node and expand the graph as needed, which complements the classic overview techniques that can be effective at (but often limited to) revealing clusters. We describe our design goals, describe the interface, and report on a controlled user study with 28 participants comparing TreePlus with a traditional graph interface for six tasks. In general, the advantage of TreePlus over the traditional interface increased as the density of the displayed data increased. Participants also reported higher levels of confidence in their answers with TreePlus and most of them preferred TreePlus.

A Metric on Phylogenetic Tree Shapes

PubMed Central

Plazzotta, G.

2018-01-01

Abstract The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees’ branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes. PMID:28472435

Vitex agnus-castus (Chaste-Tree/Berry) in the treatment of menopause-related complaints.

PubMed

van Die, Margaret Diana; Burger, Henry G; Teede, Helena J; Bone, Kerry M

2009-08-01

The origin of the current practice of administering Vitex agnus-castus in menopause-related complaints is uncertain, but appears to be relatively recent. Here we review the evidence for this application of Vitex based on evidence from pharmacological studies and clinical research. The mechanisms of potential relevance in the context of menopause are explored with reference to the current understanding of the endocrinology and neuroendocrinology of menopause and associated symptoms. We conclude that, while evidence from rigorous randomized controlled trials is lacking for the individual herb in this context, emerging pharmacological evidence supports a role for V. agnus-castus in the alleviation of menopausal symptoms and suggests that further investigation may be appropriate.

Frequency and severity of decay in street tree maples in four upstate New York cities Arboric

Treesearch

Christopher Luley; David Nowak; Eric Greenfield

2009-01-01

A proportional random selection of street tree Norway, silver, and sugar maples, and other species among four diameter classes were surveyed in the U.S. New York cities of Albany, Buffalo, Rochester, and Syracuse for decay incidence and severity. Decay was determined by drilling sampled trees with a Resistograph and calculating the ratio of sound wood to radius....

Sensitivity of a Riparian Large Woody Debris Recruitment Model to the Number of Contributing Banks and Tree Fall Pattern

Treesearch

Don C. Bragg; Jeffrey L. Kershner

2004-01-01

Riparian large woody debris (LWD) recruitment simulations have traditionally applied a random angle of tree fall from two well-forested stream banks. We used a riparian LWD recruitment model (CWD, version 1.4) to test the validity these assumptions. Both the number of contributing forest banks and predominant tree fall direction significantly influenced simulated...

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

[Spectrum Variance Analysis of Tree Leaves Under the Condition of Different Leaf water Content].

PubMed

Wu, Jian; Chen, Tai-sheng; Pan, Li-xin

2015-07-01

Leaf water content is an important factor affecting tree spectral characteristics. So Exploring the leaf spectral characteristics change rule of the same tree under the condition of different leaf water content and the spectral differences of different tree leaves under the condition of the same leaf water content are not only the keys of hyperspectral vegetation remote sensing information identification but also the theoretical support of research on vegetation spectrum change as the differences in leaf water content. The spectrometer was used to observe six species of tree leaves, and the reflectivity and first order differential spectrum of different leaf water content were obtained. Then, the spectral characteristics of each tree species leaves under the condition of different leaf water content were analyzed, and the spectral differences of different tree species leaves under the condition of the same leaf water content were compared to explore possible bands of the leaf water content identification by hyperspectral remote sensing. Results show that the spectra of each tree leaf have changed a lot with the change of the leaf water content, but the change laws are different. Leaf spectral of different tree species has lager differences in some wavelength range under the condition of same leaf water content, and it provides some possibility for high precision identification of tree species.

Machine Learning Through Signature Trees. Applications to Human Speech.

ERIC Educational Resources Information Center

White, George M.

A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

Predictors of mortality for juvenile trees in a residential urban-to-rural cohort in Worcester, MA

Treesearch

Arthur Elmes; John Rogan; Lara A. Roman; Christopher A. Williams; Samuel J. Ratick; David J. Nowak; Deborah G. Martin

2018-01-01

This paper explores predictors of juvenile tree mortality in a newly planted cohort in Worcester, MA, following an episode of large-scale tree removal necessitated by an Asian Longhorned Beetle (Anoplophora glabripennis, ALB) eradication program. Trees are increasingly seen as important providers of ecosystem services for urban areas, including:...

Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment

NASA Astrophysics Data System (ADS)

Naidoo, L.; Cho, M. A.; Mathieu, R.; Asner, G.

2012-04-01

The accurate classification and mapping of individual trees at species level in the savanna ecosystem can provide numerous benefits for the managerial authorities. Such benefits include the mapping of economically useful tree species, which are a key source of food production and fuel wood for the local communities, and of problematic alien invasive and bush encroaching species, which can threaten the integrity of the environment and livelihoods of the local communities. Species level mapping is particularly challenging in African savannas which are complex, heterogeneous, and open environments with high intra-species spectral variability due to differences in geology, topography, rainfall, herbivory and human impacts within relatively short distances. Savanna vegetation are also highly irregular in canopy and crown shape, height and other structural dimensions with a combination of open grassland patches and dense woody thicket - a stark contrast to the more homogeneous forest vegetation. This study classified eight common savanna tree species in the Greater Kruger National Park region, South Africa, using a combination of hyperspectral and Light Detection and Ranging (LiDAR)-derived structural parameters, in the form of seven predictor datasets, in an automated Random Forest modelling approach. The most important predictors, which were found to play an important role in the different classification models and contributed to the success of the hybrid dataset model when combined, were species tree height; NDVI; the chlorophyll b wavelength (466 nm) and a selection of raw, continuum removed and Spectral Angle Mapper (SAM) bands. It was also concluded that the hybrid predictor dataset Random Forest model yielded the highest classification accuracy and prediction success for the eight savanna tree species with an overall classification accuracy of 87.68% and KHAT value of 0.843.

Incidence and effects of endemic populations of forest pests in young mixed-conifer forests of the Sierra Nevada

Treesearch

Carroll B. Williams; David L. Azuma; George T. Ferrell

1992-01-01

Approximately 3.200 trees in young mixed-conifer stands were examined for pest activity and human-caused or mechanical injuries, and approximately 25 percent of these trees were randomly selected for stem analyses. The examination of trees felled for stem analyses showed that 409 (47 percent) were free of pests and 466 (53 percent) had one or more pest categories....

ETE: a python Environment for Tree Exploration.

PubMed

Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni

2010-01-13

Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

ETE: a python Environment for Tree Exploration

PubMed Central

2010-01-01

Background Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Results Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. Conclusions ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org. PMID:20070885

A Metric on Phylogenetic Tree Shapes.

PubMed

Colijn, C; Plazzotta, G

2018-01-01

The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees' branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Multiple filters affect tree species assembly in mid-latitude forest communities.

PubMed

Kubota, Y; Kusumoto, B; Shiono, T; Ulrich, W

2018-05-01

Species assembly patterns of local communities are shaped by the balance between multiple abiotic/biotic filters and dispersal that both select individuals from species pools at the regional scale. Knowledge regarding functional assembly can provide insight into the relative importance of the deterministic and stochastic processes that shape species assembly. We evaluated the hierarchical roles of the α niche and β niches by analyzing the influence of environmental filtering relative to functional traits on geographical patterns of tree species assembly in mid-latitude forests. Using forest plot datasets, we examined the α niche traits (leaf and wood traits) and β niche properties (cold/drought tolerance) of tree species, and tested non-randomness (clustering/over-dispersion) of trait assembly based on null models that assumed two types of species pools related to biogeographical regions. For most plots, species assembly patterns fell within the range of random expectation. However, particularly for cold/drought tolerance-related β niche properties, deviation from randomness was frequently found; non-random clustering was predominant in higher latitudes with harsh climates. Our findings demonstrate that both randomness and non-randomness in trait assembly emerged as a result of the α and β niches, although we suggest the potential role of dispersal processes and/or species equalization through trait similarities in generating the prevalence of randomness. Clustering of β niche traits along latitudinal climatic gradients provides clear evidence of species sorting by filtering particular traits. Our results reveal that multiple filters through functional niches and stochastic processes jointly shape geographical patterns of species assembly across mid-latitude forests.

Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data.

PubMed

Li, Jiuyong; Liu, Lin; Liu, Jixue; Green, Ryan

2017-12-01

It is common that a trained classification model is applied to the operating data that is deviated from the training data because of noise. This paper will test an ensemble method, Diversified Multiple Tree (DMT), on its capability for classifying instances in a new laboratory using the classifier built on the instances of another laboratory. DMT is tested on three real world biomedical data sets from different laboratories in comparison with four benchmark ensemble methods, AdaBoost, Bagging, Random Forests, and Random Trees. Experiments have also been conducted on studying the limitation of DMT and its possible variations. Experimental results show that DMT is significantly more accurate than other benchmark ensemble classifiers on classifying new instances of a different laboratory from the laboratory where instances are used to build the classifier. This paper demonstrates that an ensemble classifier, DMT, is more robust in classifying noisy data than other widely used ensemble methods. DMT works on the data set that supports multiple simple trees.

Tree Growth Response to Drought Along a Depth to Groundwater Gradient in Northern Wisconsin

NASA Astrophysics Data System (ADS)

Ciruzzi, D. M.; Loheide, S. P., II

2017-12-01

Understanding complex spatial and temporal patterns of drought-induced forest stress requires knowledge of the physiological drivers and ecosystem attributes that lead to or inhibit tree mortality. Prevailing meteorological conditions leading to drought may have lesser effect on vegetation that has evolved to avoid drought by accessing deeper soil moisture reserves or shallow groundwater to meet evapotranspiration demand. This is especially true in arid and semi-arid regions, yet groundwater use by trees is rarely explored in temperate systems and the extent to which groundwater use reduces drought vulnerability in these climates and regions is unknown. We explored responses of radial growth in temperate tress to wet and dry years across a depth to groundwater gradient from 1 to 9 meters in sandy forests in northern Wisconsin. The spatial patterns of tree growth in this watershed show areas where tree growth is influenced by depth to groundwater. Preliminary results showed trees in areas of shallower groundwater with low variability in tree growth and indicated that tree growth remains consistent during both wet and dry years. Conversely, trees in areas of deeper groundwater showed higher variability in tree growth during wet and dry years. We hypothesize that even in this humid region, the sandy soils do not retain sufficient moisture leading to potentially frequent water stress in trees and reductions in productivity. However, where and when accessible, we suspect trees use shallow groundwater to sustain evapotranspiration and maintain consistent growth during dry periods.

Delayed conifer mortality after fuel reduction treatments: Interactive effects of fuel, fire intensity, and bark beetles

USGS Publications Warehouse

Youngblood, A.; Grace, J.B.; Mciver, J.D.

2009-01-01

Many low-elevation dry forests of the western United States contain more small trees and fewer large trees, more down woody debris, and less diverse and vigorous understory plant communities compared to conditions under historical fire regimes. These altered structural conditions may contribute to increased probability of unnaturally severe wildfires, susceptibility to uncharacteristic insect outbreaks, and drought-related mortality. Broad-scale fuel reduction and restoration treatments are proposed to promote stand development on trajectories toward more sustainable structures. Little research to date, however, has quantified the effects of these treatments on the ecosystem, especially delayed and latent tree mortality resulting directly or indirectly from treatments. In this paper, we explore complex hypotheses relating to the cascade of effects that influence ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) mortality using structural equation modeling (SEM). We used annual census and plot data through six growing seasons after thinning and four growing seasons after burning from a replicated, operational-scale, completely randomized experiment conducted in northeastern Oregon, USA, as part of the national Fire and Fire Surrogate study. Treatments included thin, burn, thin followed by burn (thin+burn), and control. Burn and thin+burn treatments increased the proportion of dead trees while the proportion of dead trees declined or remained constant in thin and control units, although the density of dead trees was essentially unchanged with treatment. Most of the new mortality (96%) occurred within two years of treatment and was attributed to bark beetles. Bark beetle-caused tree mortality, while low overall, was greatest in thin + burn treatments. SEM results indicate that the probability of mortality of large-diameter ponderosa pine from bark beetles and wood borers was directly related to surface fire severity and bole charring, which in turn depended on fire intensity, which was greater in units where thinning increased large woody fuels. These results have implications when deciding among management options for restoring ecosystem health in similar ponderosa pine and Douglas-fir forests. ?? 2009 by the Ecological Society of America.

Ponderosa pine mortality resulting from a mountain pine beetle outbreak

Treesearch

William F. McCambridge; Frank G. Hawksworth; Carleton B. Edminster; John G. Laut

1982-01-01

From 1965 to 1978, mountain pine beetles killed 25% of the pines taller than 4.5 feet in a study area in north-central Colorado. Average basal area was reduced from 92 to 58 square feet per acre. Mortality increased with tree diameter up to about 9 inches d.b.h. Larger trees appeared to be killed at random. Mortality was directly related to number of trees per acre and...

Growing quality of life: urban trees, birth weight, and crime

Treesearch

John Kirkland; Geoffrey Donovan

2011-01-01

City dwellers can find many reasons to value neighborhood trees. The urban greenery provides relief from the built environment that many find appealing. In fact, a previous study found that a tree in front of a home increased that home's sales price by more than $7,000. Two new studies explore the measurable effects that urban trees and green spaces have a human...

Simulated cavity tree dynamics under alternative timber harvest regimes

Treesearch

Zhaofei Fan; Stephen R Shifley; Frank R Thompson; David R Larsen

2004-01-01

We modeled cavity tree abundance on a landscape as a function of forest stand age classes and as a function of aggregate stand size classes.We explored the impact of five timber harvest regimes on cavity tree abundance on a 3261 ha landscape in southeast Missouri, USA, by linking the stand level cavity tree distribution model to the landscape age structure simulated by...

Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

PubMed

Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of more than 10% over the standard classification models, which can be translated to correct labeling of additional 400 - 500 readmissions for heart failure patients in the state of California over a year. Lastly, several key predictor identified from the HCUP data include the disposition location from discharge, the number of chronic conditions, and the number of acute procedures. It would be beneficial to apply simple decision rules obtained from the decision tree in an ad-hoc manner to guide the cohort stratification. It could be potentially beneficial to explore the effect of pairwise interactions between influential predictors when building the logistic regression models for different data strata. Judicious use of the ad-hoc CLR models developed offers insights into future development of prediction models for hospital readmissions, which can lead to better intuition in identifying high-risk patients and developing effective post-discharge care strategies. Lastly, this paper is expected to raise the awareness of collecting data on additional markers and developing necessary database infrastructure for larger-scale exploratory studies on readmission risk prediction.

Personalized Risk Prediction in Clinical Oncology Research: Applications and Practical Issues Using Survival Trees and Random Forests.

PubMed

Hu, Chen; Steingrimsson, Jon Arni

2018-01-01

A crucial component of making individualized treatment decisions is to accurately predict each patient's disease risk. In clinical oncology, disease risks are often measured through time-to-event data, such as overall survival and progression/recurrence-free survival, and are often subject to censoring. Risk prediction models based on recursive partitioning methods are becoming increasingly popular largely due to their ability to handle nonlinear relationships, higher-order interactions, and/or high-dimensional covariates. The most popular recursive partitioning methods are versions of the Classification and Regression Tree (CART) algorithm, which builds a simple interpretable tree structured model. With the aim of increasing prediction accuracy, the random forest algorithm averages multiple CART trees, creating a flexible risk prediction model. Risk prediction models used in clinical oncology commonly use both traditional demographic and tumor pathological factors as well as high-dimensional genetic markers and treatment parameters from multimodality treatments. In this article, we describe the most commonly used extensions of the CART and random forest algorithms to right-censored outcomes. We focus on how they differ from the methods for noncensored outcomes, and how the different splitting rules and methods for cost-complexity pruning impact these algorithms. We demonstrate these algorithms by analyzing a randomized Phase III clinical trial of breast cancer. We also conduct Monte Carlo simulations to compare the prediction accuracy of survival forests with more commonly used regression models under various scenarios. These simulation studies aim to evaluate how sensitive the prediction accuracy is to the underlying model specifications, the choice of tuning parameters, and the degrees of missing covariates.

Leonardo's Tree Theory.

ERIC Educational Resources Information Center

Werner, Suzanne K.

2003-01-01

Describes a series of activities exploring Leonardo da Vinci's tree theory that are designed to strengthen 8th grade students' data collection and problem solving skills in physical science classes. (KHR)

Analysis of landslide hazard area in Ludian earthquake based on Random Forests

NASA Astrophysics Data System (ADS)

Xie, J.-C.; Liu, R.; Li, H.-W.; Lai, Z.-L.

2015-04-01

With the development of machine learning theory, more and more algorithms are evaluated for seismic landslides. After the Ludian earthquake, the research team combine with the special geological structure in Ludian area and the seismic filed exploration results, selecting SLOPE(PODU); River distance(HL); Fault distance(DC); Seismic Intensity(LD) and Digital Elevation Model(DEM), the normalized difference vegetation index(NDVI) which based on remote sensing images as evaluation factors. But the relationships among these factors are fuzzy, there also exists heavy noise and high-dimensional, we introduce the random forest algorithm to tolerate these difficulties and get the evaluation result of Ludian landslide areas, in order to verify the accuracy of the result, using the ROC graphs for the result evaluation standard, AUC covers an area of 0.918, meanwhile, the random forest's generalization error rate decreases with the increase of the classification tree to the ideal 0.08 by using Out Of Bag(OOB) Estimation. Studying the final landslides inversion results, paper comes to a statistical conclusion that near 80% of the whole landslides and dilapidations are in areas with high susceptibility and moderate susceptibility, showing the forecast results are reasonable and adopted.

Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory

EPA Science Inventory

Efforts are increasingly being made to classify the world’s wetland resources, an important ecosystem and habitat that is diminishing in abundance. There are multiple remote sensing classification methods, including a suite of nonparametric classifiers such as decision-tree...

Measurement variability error for estimates of volume change

Treesearch

James A. Westfall; Paul L. Patterson

2007-01-01

Using quality assurance data, measurement variability distributions were developed for attributes that affect tree volume prediction. Random deviations from the measurement variability distributions were applied to 19381 remeasured sample trees in Maine. The additional error due to measurement variation and measurement bias was estimated via a simulation study for...

The fast algorithm of spark in compressive sensing

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

Compressed Sensing (CS) is an advanced theory on signal sampling and reconstruction. In CS theory, the reconstruction condition of signal is an important theory problem, and spark is a good index to study this problem. But the computation of spark is NP hard. In this paper, we study the problem of computing spark. For some special matrixes, for example, the Gaussian random matrix and 0-1 random matrix, we obtain some conclusions. Furthermore, for Gaussian random matrix with fewer rows than columns, we prove that its spark equals to the number of its rows plus one with probability 1. For general matrix, two methods are given to compute its spark. One is the method of directly searching and the other is the method of dual-tree searching. By simulating 24 Gaussian random matrixes and 18 0-1 random matrixes, we tested the computation time of these two methods. Numerical results showed that the dual-tree searching method had higher efficiency than directly searching, especially for those matrixes which has as much as rows and columns.

Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set.

PubMed

Adler, Werner; Gefeller, Olaf; Gul, Asma; Horn, Folkert K; Khan, Zardad; Lausen, Berthold

2016-12-07

Random forests are successful classifier ensemble methods consisting of typically 100 to 1000 classification trees. Ensemble pruning techniques reduce the computational cost, especially the memory demand, of random forests by reducing the number of trees without relevant loss of performance or even with increased performance of the sub-ensemble. The application to the problem of an early detection of glaucoma, a severe eye disease with low prevalence, based on topographical measurements of the eye background faces specific challenges. We examine the performance of ensemble pruning strategies for glaucoma detection in an unbalanced data situation. The data set consists of 102 topographical features of the eye background of 254 healthy controls and 55 glaucoma patients. We compare the area under the receiver operating characteristic curve (AUC), and the Brier score on the total data set, in the majority class, and in the minority class of pruned random forest ensembles obtained with strategies based on the prediction accuracy of greedily grown sub-ensembles, the uncertainty weighted accuracy, and the similarity between single trees. To validate the findings and to examine the influence of the prevalence of glaucoma in the data set, we additionally perform a simulation study with lower prevalences of glaucoma. In glaucoma classification all three pruning strategies lead to improved AUC and smaller Brier scores on the total data set with sub-ensembles as small as 30 to 80 trees compared to the classification results obtained with the full ensemble consisting of 1000 trees. In the simulation study, we were able to show that the prevalence of glaucoma is a critical factor and lower prevalence decreases the performance of our pruning strategies. The memory demand for glaucoma classification in an unbalanced data situation based on random forests could effectively be reduced by the application of pruning strategies without loss of performance in a population with increased risk of glaucoma.

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.

Unbiased feature selection in learning random forests for high-dimensional data.

PubMed

Nguyen, Thanh-Tung; Huang, Joshua Zhexue; Nguyen, Thuy Thi

2015-01-01

Random forests (RFs) have been widely used as a powerful classification method. However, with the randomization in both bagging samples and feature selection, the trees in the forest tend to select uninformative features for node splitting. This makes RFs have poor accuracy when working with high-dimensional data. Besides that, RFs have bias in the feature selection process where multivalued features are favored. Aiming at debiasing feature selection in RFs, we propose a new RF algorithm, called xRF, to select good features in learning RFs for high-dimensional data. We first remove the uninformative features using p-value assessment, and the subset of unbiased features is then selected based on some statistical measures. This feature subset is then partitioned into two subsets. A feature weighting sampling technique is used to sample features from these two subsets for building trees. This approach enables one to generate more accurate trees, while allowing one to reduce dimensionality and the amount of data needed for learning RFs. An extensive set of experiments has been conducted on 47 high-dimensional real-world datasets including image datasets. The experimental results have shown that RFs with the proposed approach outperformed the existing random forests in increasing the accuracy and the AUC measures.

Data management for urban tree monitoring -- software requirements

Treesearch

Deborah J. ​Boyer; Lara A. Roman; Jason G. Henning; Matthew McFarland; Dana Dentice; Sarah C. Low; Casey Thomas; Glen Abrams

2016-01-01

The creation of this report was organized by the Pennsylvania Horticultural Society (PHS) and the USDA Forest Service Philadelphia Field Station to explore how technology could be used to support the longterm systematic monitoring of urban trees by trained professionals, student interns and volunteers; assist with tree planting and maintenance data processes; and...

treespace: Statistical exploration of landscapes of phylogenetic trees.

PubMed

Jombart, Thibaut; Kendall, Michelle; Almagro-Garcia, Jacob; Colijn, Caroline

2017-11-01

The increasing availability of large genomic data sets as well as the advent of Bayesian phylogenetics facilitates the investigation of phylogenetic incongruence, which can result in the impossibility of representing phylogenetic relationships using a single tree. While sometimes considered as a nuisance, phylogenetic incongruence can also reflect meaningful biological processes as well as relevant statistical uncertainty, both of which can yield valuable insights in evolutionary studies. We introduce a new tool for investigating phylogenetic incongruence through the exploration of phylogenetic tree landscapes. Our approach, implemented in the R package treespace, combines tree metrics and multivariate analysis to provide low-dimensional representations of the topological variability in a set of trees, which can be used for identifying clusters of similar trees and group-specific consensus phylogenies. treespace also provides a user-friendly web interface for interactive data analysis and is integrated alongside existing standards for phylogenetics. It fills a gap in the current phylogenetics toolbox in R and will facilitate the investigation of phylogenetic results. © 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

Patterns and effects of GC3 heterogeneity and parsimony informative sites on the phylogenetic tree of genes.

PubMed

Ma, Shuai; Wu, Qi; Hu, Yibo; Wei, Fuwen

2018-05-20

The explosive growth in genomic data has provided novel insights into the conflicting signals hidden in phylogenetic trees. Although some studies have explored the effects of the GC content and parsimony informative sites (PIS) on the phylogenetic tree, the effect of the heterogeneity of the GC content at the first/second/third codon position on parsimony informative sites (GC1/2/3 PIS ) among different species and the effect of PIS on phylogenetic tree construction remain largely unexplored. Here, we used two different mammal genomic datasets to explore the patterns of GC1/2/3 PIS heterogeneity and the effect of PIS on the phylogenetic tree of genes: (i) all GC1/2/3 PIS have obvious heterogeneity between different mammals, and the levels of heterogeneity are GC3 PIS  > GC2 PIS  > GC1 PIS ; (ii) the number of PIS is positively correlated with the metrics of "good" gene tree topologies, and excluding the third codon position (C3) decreases the quality of gene trees by removing too many PIS. These results provide novel insights into the heterogeneity pattern of GC1/2/3 PIS in mammals and the relationship between GC3/PIS and gene trees. Additionally, it is necessary to carefully consider whether to exclude C3 to improve the quality of gene trees, especially in the super-tree method. Copyright © 2018 Elsevier B.V. All rights reserved.

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Logging utilization in Idaho: Current and past trends

Treesearch

Eric A. Simmons; Todd A. Morgan; Erik C. Berg; Stanley J. Zarnoch; Steven W. Hayes; Mike T. Thompson

2014-01-01

A study of commercial timber-harvesting activities in Idaho was conducted during 2008 and 2011 to characterize current tree utilization, logging operations, and changes from previous Idaho logging utilization studies. A two-stage simple random sampling design was used to select sites and felled trees for measurement within active logging sites. Thirty-three logging...

Adaptive economic and ecological forest management under risk

Treesearch

Joseph Buongiorno; Mo Zhou

2015-01-01

Background: Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape...

Natural cavities used by wood ducks in north-central Minnesota

USGS Publications Warehouse

Gilmer, D.S.; Ball, I.J.; Cowardin, L.M.; Mathisen, J.

1978-01-01

Radio telemetry was used to locate 31 wood duck (Aix sponsa) nest cavity sites in 16 forest stands. Stands were of 2 types: (1) mature (mean = 107 years) northern hardwoods (10 nest sites), and (2) mature (mean = 68 years) quaking aspen (Populus tremuloides) (21 nest sites). Aspen was the most important cavity-producing tree used by wood ducks and accounted for 57 percent of 28 cavities inspected. In stands used by wood ducks, the average density of suitable cavities was about 4 per hectare. Trees containing nests were closer to water areas (P < 0.05) and the nearest forest canopy openings (P < 0.01) than was a random sample of trees from the same stands. A significant (P < 0.005) relationship existed between the orientation of the cavity entrance and the nearest canopy opening. Potential wood duck cavities usually were clustered within a stand rather than randomly distributed. Selection of trees by woodpeckers for nest hole construction probably influenced the availability of cavities used by wood ducks. A plan for managing forests to benefit wood ducks and other wildlife dependent on old-growth timber is discussed.

Nesting habitat and productivity of Swainson's Hawks in southeastern Arizona

USGS Publications Warehouse

Nishida, Catherine; Boal, Clint W.; DeStefano, Stephen; Hobbs, Royden J.

2013-01-01

We studied Swainson's Hawks (Buteo swainsoni) in southeastern Arizona to assess the status of the local breeding population. Nest success (≥1 young fledged) was 44.4% in 1999 with an average of 1.43 ± 0.09 (SE) young produced per successful pair. Productivity was similar in 2000, with 58.2% nesting success and 1.83 ± 0.09 fledglings per successful pair. Mesquite (Prosopis velutina) and cottonwood (Populus fremontii) accounted for >50% of 167 nest trees. Nest trees were taller than surrounding trees and random trees, and overall there was more vegetative cover at nest sites than random sites. This apparent requirement for cover around nest sites could be important for management of the species in Arizona. However, any need for cover at nest sites must be balanced with the need for open areas for foraging. Density of nesting Swainson's Hawks was higher in agriculture than in grasslands and desert scrub. Breeding pairs had similar success in agricultural and nonagricultural areas, but the effect of rapid and widespread land-use change on breeding distribution and productivity continues to be a concern throughout the range of the species.

Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality

USGS Publications Warehouse

Foster, Jane R.; D'Amato, Anthony W.; Bradford, John B.

2014-01-01

Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.

SLE as a Mating of Trees in Euclidean Geometry

NASA Astrophysics Data System (ADS)

Holden, Nina; Sun, Xin

2018-05-01

The mating of trees approach to Schramm-Loewner evolution (SLE) in the random geometry of Liouville quantum gravity (LQG) has been recently developed by Duplantier et al. (Liouville quantum gravity as a mating of trees, 2014. arXiv:1409.7055). In this paper we consider the mating of trees approach to SLE in Euclidean geometry. Let {η} be a whole-plane space-filling SLE with parameter {κ > 4} , parameterized by Lebesgue measure. The main observable in the mating of trees approach is the contour function, a two-dimensional continuous process describing the evolution of the Minkowski content of the left and right frontier of {η} . We prove regularity properties of the contour function and show that (as in the LQG case) it encodes all the information about the curve {η} . We also prove that the uniform spanning tree on {Z^2} converges to SLE8 in the natural topology associated with the mating of trees approach.

Simple chained guide trees give high-quality protein multiple sequence alignments

PubMed Central

Boyce, Kieran; Sievers, Fabian; Higgins, Desmond G.

2014-01-01

Guide trees are used to decide the order of sequence alignment in the progressive multiple sequence alignment heuristic. These guide trees are often the limiting factor in making large alignments, and considerable effort has been expended over the years in making these quickly or accurately. In this article we show that, at least for protein families with large numbers of sequences that can be benchmarked with known structures, simple chained guide trees give the most accurate alignments. These also happen to be the fastest and simplest guide trees to construct, computationally. Such guide trees have a striking effect on the accuracy of alignments produced by some of the most widely used alignment packages. There is a marked increase in accuracy and a marked decrease in computational time, once the number of sequences goes much above a few hundred. This is true, even if the order of sequences in the guide tree is random. PMID:25002495

Applying species-tree analyses to deep phylogenetic histories: challenges and potential suggested from a survey of empirical phylogenetic studies.

PubMed

Lanier, Hayley C; Knowles, L Lacey

2015-02-01

Coalescent-based methods for species-tree estimation are becoming a dominant approach for reconstructing species histories from multi-locus data, with most of the studies examining these methodologies focused on recently diverged species. However, deeper phylogenies, such as the datasets that comprise many Tree of Life (ToL) studies, also exhibit gene-tree discordance. This discord may also arise from the stochastic sorting of gene lineages during the speciation process (i.e., reflecting the random coalescence of gene lineages in ancestral populations). It remains unknown whether guidelines regarding methodologies and numbers of loci established by simulation studies at shallow tree depths translate into accurate species relationships for deeper phylogenetic histories. We address this knowledge gap and specifically identify the challenges and limitations of species-tree methods that account for coalescent variance for deeper phylogenies. Using simulated data with characteristics informed by empirical studies, we evaluate both the accuracy of estimated species trees and the characteristics associated with recalcitrant nodes, with a specific focus on whether coalescent variance is generally responsible for the lack of resolution. By determining the proportion of coalescent genealogies that support a particular node, we demonstrate that (1) species-tree methods account for coalescent variance at deep nodes and (2) mutational variance - not gene-tree discord arising from the coalescent - posed the primary challenge for accurate reconstruction across the tree. For example, many nodes were accurately resolved despite predicted discord from the random coalescence of gene lineages and nodes with poor support were distributed across a range of depths (i.e., they were not restricted to a particular recent divergences). Given their broad taxonomic scope and large sampling of taxa, deep level phylogenies pose several potential methodological complications including difficulties with MCMC convergence and estimation of requisite population genetic parameters for coalescent-based approaches. Despite these difficulties, the findings generally support the utility of species-tree analyses for the estimation of species relationships throughout the ToL. We discuss strategies for successful application of species-tree approaches to deep phylogenies. Copyright © 2014 Elsevier Inc. All rights reserved.

Simulation of design-unbiased point-to-particle sampling compared to alternatives on plantation rows

Treesearch

Thomas B. Lynch; David Hamlin; Mark J. Ducey

2016-01-01

Total quantities of tree attributes can be estimated in plantations by sampling on plantation rows using several methods. At random sample points on a row, either fixed row lengths or variable row lengths with a fixed number of sample trees can be assessed. Ratio of means or mean of ratios estimators can be developed for the fixed number of trees option but are not...

Efficacy of ‘hack and squirt’ application of imazapyr, triclopyr, and glyphosate to control the invasive tree species Chinese tallowtree

Treesearch

Charles A. Gresham

2010-01-01

In May 2005, 12 plots approximately 21 by 27 m each were established on the exterior bank of a dredge spoil area in Georgetown, SC. The tree cover was primarily Chinese tallowtree, but there were also live oak trees in each plot. Also in May 2005, Chinese tallowtree s (d.b.h. > 2.4 cm) in three randomly selected plots received a ‘hack and squirt’ application of...

Topology of correlation-based minimal spanning trees in real and model markets

NASA Astrophysics Data System (ADS)

Bonanno, Giovanni; Caldarelli, Guido; Lillo, Fabrizio; Mantegna, Rosario N.

2003-10-01

We compare the topological properties of the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the widespread one-factor model.

TreeScaper: Visualizing and Extracting Phylogenetic Signal from Sets of Trees.

PubMed

Huang, Wen; Zhou, Guifang; Marchand, Melissa; Ash, Jeremy R; Morris, David; Van Dooren, Paul; Brown, Jeremy M; Gallivan, Kyle A; Wilgenbusch, Jim C

2016-12-01

Modern phylogenomic analyses often result in large collections of phylogenetic trees representing uncertainty in individual gene trees, variation across genes, or both. Extracting phylogenetic signal from these tree sets can be challenging, as they are difficult to visualize, explore, and quantify. To overcome some of these challenges, we have developed TreeScaper, an application for tree set visualization as well as the identification of distinct phylogenetic signals. GUI and command-line versions of TreeScaper and a manual with tutorials can be downloaded from https://github.com/whuang08/TreeScaper/releases TreeScaper is distributed under the GNU General Public License. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Phylogenetic mixtures and linear invariants for equal input models.

PubMed

Casanellas, Marta; Steel, Mike

2017-04-01

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).

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

Inferring Epidemic Contact Structure from Phylogenetic Trees

PubMed Central

Leventhal, Gabriel E.; Kouyos, Roger; Stadler, Tanja; von Wyl, Viktor; Yerly, Sabine; Böni, Jürg; Cellerai, Cristina; Klimkait, Thomas; Günthard, Huldrych F.; Bonhoeffer, Sebastian

2012-01-01

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing. PMID:22412361

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.

Exploring connections between trees and human health

Treesearch

Geoffrey Donovan; Marie Oliver

2014-01-01

Humans have intuitively understood the value of trees to their physical and mental health since the beginning of recorded time. A scientist with the Pacific Northwest Research Station wondered if such a link could be scientifically validated. His research team took advantage of an infestation of emerald ash borer, an invasive pest that kills ash trees, to conduct a...

Scab severity in relation to hedge pruning pecan trees in the Southeastern USA

USDA-ARS?s Scientific Manuscript database

Scab is the most damaging disease of pecan in the Southeastern USA. Pecan trees are tall (up to 30+ m), and managing disease in the upper canopy is problematic. Hedge pruning trees to ~12 m is being explored to facilitate efficacy of ground-based fungicide sprays, but resulting vigorous shoot growth...

The k-d Tree: A Hierarchical Model for Human Cognition.

ERIC Educational Resources Information Center

Vandendorpe, Mary M.

This paper discusses a model of information storage and retrieval, the k-d tree (Bentley, 1975), a binary, hierarchical tree with multiple associate terms, which has been explored in computer research, and it is suggested that this model could be useful for describing human cognition. Included are two models of human long-term memory--networks and…

Random forests as cumulative effects models: A case study of lakes and rivers in Muskoka, Canada.

PubMed

Jones, F Chris; Plewes, Rachel; Murison, Lorna; MacDougall, Mark J; Sinclair, Sarah; Davies, Christie; Bailey, John L; Richardson, Murray; Gunn, John

2017-10-01

Cumulative effects assessment (CEA) - a type of environmental appraisal - lacks effective methods for modeling cumulative effects, evaluating indicators of ecosystem condition, and exploring the likely outcomes of development scenarios. Random forests are an extension of classification and regression trees, which model response variables by recursive partitioning. Random forests were used to model a series of candidate ecological indicators that described lakes and rivers from a case study watershed (The Muskoka River Watershed, Canada). Suitability of the candidate indicators for use in cumulative effects assessment and watershed monitoring was assessed according to how well they could be predicted from natural habitat features and how sensitive they were to human land-use. The best models explained 75% of the variation in a multivariate descriptor of lake benthic-macroinvertebrate community structure, and 76% of the variation in the conductivity of river water. Similar results were obtained by cross-validation. Several candidate indicators detected a simulated doubling of urban land-use in their catchments, and a few were able to detect a simulated doubling of agricultural land-use. The paper demonstrates that random forests can be used to describe the combined and singular effects of multiple stressors and natural environmental factors, and furthermore, that random forests can be used to evaluate the performance of monitoring indicators. The numerical methods presented are applicable to any ecosystem and indicator type, and therefore represent a step forward for CEA. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Energy state affects exploratory behavior of tree sparrows in a group context under differential food-patch distributions.

PubMed

Lee, Ya-Fu; Kuo, Yen-Min; Chu, Wen-Chen

2016-01-01

When facing a novel situation, animals can retreat or leave to avoid risks, but will miss potential resources and opportunities. Alternatively they may reduce environmental uncertainty by exploration, while risking no energy rewards and exposure to hazards, and use the information retrieved for subsequent decision making. When exploring, however, animals may adopt different tactics according to individual states. We tested that energy states will affect exploratory behavior by experimenting with wild-caught untrained Eurasian tree sparrows ( Passer montanus ) in fasted or fed states exploring in a novel space with hidden food supply in different patch distribution patterns. Our data revealed that fasted sparrows risked being earlier explorers more often, initiated more exploratory bouts before patches were found, and stayed longer on the ground under both patch patterns. Fasted sparrows discovered more patches and consumed more food than fed sparrows in dispersed, but not necessary so in clumped, patch patterns; whereas fed birds also increased patch finding to a certain level in dispersed patterns. Sparrows of both energy states, however, did not differ in feeding rates in either patch pattern. Exploratory behavior of tree sparrows is state-dependent, which supports our prediction that birds with an energy shortage will be risk-prone and explore more readily. Our study also indicates a game nature of tree sparrow exploratory behavior in a group context when explorers are in different energy states and are exposed to different patch distributions. Birds of lower energy state adopting an active exploring tactic may be favored by obtaining higher energy gains in dispersed patch patterns with lower patch richness. More satiated birds, however, achieved a similar feeding rate by lowered exposure time.

Node degree distribution in spanning trees

NASA Astrophysics Data System (ADS)

Pozrikidis, C.

2016-03-01

A method is presented for computing the number of spanning trees involving one link or a specified group of links, and excluding another link or a specified group of links, in a network described by a simple graph in terms of derivatives of the spanning-tree generating function defined with respect to the eigenvalues of the Kirchhoff (weighted Laplacian) matrix. The method is applied to deduce the node degree distribution in a complete or randomized set of spanning trees of an arbitrary network. An important feature of the proposed method is that the explicit construction of spanning trees is not required. It is shown that the node degree distribution in the spanning trees of the complete network is described by the binomial distribution. Numerical results are presented for the node degree distribution in square, triangular, and honeycomb lattices.

[Effects of crop tree release on stand growth and stand structure of Cunninghamia lanceolata plantation].

PubMed

Wu, Jian-qiang; Wang, Yi-xiang; Yang, Yi; Zhu, Ting-ting; Zhu, Xu-dan

2015-02-01

Crop trees were selected in a 26-year-old even-aged Cunninghamia lanceolata plantation in Lin' an, and compared in plots that were released and unreleased to examine growth and structure responses for 3 years after thinning. Crop tree release significantly increased the mean increments of diameter and volume of individual tree by 1.30 and 1.25 times relative to trees in control stands, respectively. The increments of diameter and volume of crop trees were significantly higher than those of general trees in thinning plots, crop trees and general trees in control plots, which suggested that the responses from different tree types to crop tree release treatment were different. Crop tree release increased the average distances of crop trees to the nearest neighboring trees, reducing competition among crop trees by about 68.2%. 3-year stand volume increment for thinning stands had no significant difference with that of control stands although the number of trees was only 81.5% of the control. Crop trees in thinned plots with diameters over than 14 cm reached 18.0% over 3 years, compared with 12.0% for trees without thinning, suggesting that crop tree release benefited the larger individual trees. The pattern of tree locations in thinning plots tended to be random, complying with the rule that tree distribution pattern changes with growth. Crop tree release in C. lanceolata plantation not only promoted the stand growth, but also optimized the stand structure, benefiting crop trees sustained rapid growth and larger diameter trees production.

Assessing the relative importance of correlates of loneliness in later life. Gaining insight using recursive partitioning.

PubMed

Ejlskov, Linda; Wulff, Jesper; Bøggild, Henrik; Kuh, Diana; Stafford, Mai

2017-09-08

Improving the design and targeting of interventions is important for alleviating loneliness among older adults. This requires identifying which correlates are the most important predictors of loneliness. This study demonstrates the use of recursive partitioning in exploring the characteristics and assessing the relative importance of correlates of loneliness in older adults. Using exploratory regression trees and random forests, we examined combinations and the relative importance of 42 correlates in relation to loneliness at age 68 among 2453 participants from the birth cohort study the MRC National Survey of Health and Development. Positive mental well-being, personal mastery, identifying the spouse as the closest confidant, being extrovert and informal social contact were the most important correlates of lower loneliness levels. Participation in organised groups and demographic correlates were poor identifiers of loneliness. The regression tree suggested that loneliness was not raised among those with poor mental wellbeing if they identified their partner as closest confidante and had frequent social contact. Recursive partitioning can identify which combinations of experiences and circumstances characterise high-risk groups. Poor mental wellbeing and sparse social contact emerged as especially important and classical demographic factors as insufficient in identifying high loneliness levels among older adults.

Biodiversity mapping in a tropical West African forest with airborne hyperspectral data.

PubMed

Vaglio Laurin, Gaia; Cheung-Wai Chan, Jonathan; Chen, Qi; Lindsell, Jeremy A; Coomes, David A; Guerriero, Leila; Del Frate, Fabio; Miglietta, Franco; Valentini, Riccardo

2014-01-01

Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we explore whether airborne hyperspectral imagery can be used to predict the alpha diversity of upper canopy trees in a West African forest. The abundance of tree species were collected from 64 plots (each 1250 m(2) in size) within a Sierra Leonean national park, and Shannon-Wiener biodiversity indices were calculated. An airborne spectrometer measured reflectances of 186 bands in the visible and near-infrared spectral range at 1 m(2) resolution. The standard deviations of these reflectance values and their first-order derivatives were calculated for each plot from the c. 1250 pixels of hyperspectral information within them. Shannon-Wiener indices were then predicted from these plot-based reflectance statistics using a machine-learning algorithm (Random Forest). The regression model fitted the data well (pseudo-R(2) = 84.9%), and we show that standard deviations of green-band reflectances and infra-red region derivatives had the strongest explanatory powers. Our work shows that airborne hyperspectral sensing can be very effective at mapping canopy tree diversity, because its high spatial resolution allows within-plot heterogeneity in reflectance to be characterized, making it an effective tool for monitoring forest biodiversity over large geographic scales.

Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data

PubMed Central

Vaglio Laurin, Gaia; Chan, Jonathan Cheung-Wai; Chen, Qi; Lindsell, Jeremy A.; Coomes, David A.; Guerriero, Leila; Frate, Fabio Del; Miglietta, Franco; Valentini, Riccardo

2014-01-01

Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we explore whether airborne hyperspectral imagery can be used to predict the alpha diversity of upper canopy trees in a West African forest. The abundance of tree species were collected from 64 plots (each 1250 m2 in size) within a Sierra Leonean national park, and Shannon-Wiener biodiversity indices were calculated. An airborne spectrometer measured reflectances of 186 bands in the visible and near-infrared spectral range at 1 m2 resolution. The standard deviations of these reflectance values and their first-order derivatives were calculated for each plot from the c. 1250 pixels of hyperspectral information within them. Shannon-Wiener indices were then predicted from these plot-based reflectance statistics using a machine-learning algorithm (Random Forest). The regression model fitted the data well (pseudo-R2 = 84.9%), and we show that standard deviations of green-band reflectances and infra-red region derivatives had the strongest explanatory powers. Our work shows that airborne hyperspectral sensing can be very effective at mapping canopy tree diversity, because its high spatial resolution allows within-plot heterogeneity in reflectance to be characterized, making it an effective tool for monitoring forest biodiversity over large geographic scales. PMID:24937407

How Fast Do Trees Grow? Using Tables and Graphs to Explore Slope

ERIC Educational Resources Information Center

Joram, Elana; Oleson, Vicki

2007-01-01

This article describes a lesson unit in which students constructed tables and graphs to represent the growth of different trees. Students then compared the graphs to develop an understanding of slope.

Age structure and growth of California black oak (Quercus kelloggii) in the central Sierra Nevada, California

Treesearch

Barrett A. Garrison; Christopher D. otahal; Matthew L. Triggs

2002-01-01

Age structure and growth of California black oak (Quercus kelloggii) was determined from tagged trees at four 26.1-acre study stands in Placer County, California. Stands were dominated by large diameter (>20 inch dbh) California black oak and ponderosa pine (Pinus ponderosa). Randomly selected trees were tagged in June-August...

Greedy algorithms in disordered systems

NASA Astrophysics Data System (ADS)

Duxbury, P. M.; Dobrin, R.

1999-08-01

We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.

Demographic trends in Claremont California’s street tree population

Treesearch

Natalie S. van Doorn; E. Gregory McPherson

2018-01-01

The aim of this study was to quantify street tree population dynamics in the city of Claremont, CA. A repeated measures survey (2000 and 2014) based on a stratified random sampling approach across size classes and for the most abundant 21 species was analyzed to calculate removal, growth, and replacement planting rates. Demographic rates were estimated using a...

An individual-tree dbh-total height model with random plot effects for shortleaf pine

Treesearch

Chakra B. Budhathoki; Thomas B. Lynch; James M. Guldin

2007-01-01

Individual tree measurements were available from over 200 permanent plots established during 1985-1987 and later remeasured in naturally regenerated stands of shortleaf pine (Pinus echinata Mill.) in western Arkansas and eastern Oklahoma. The objective of this study was to model shortleaf pine growth in natural stands for the region. As a major...

Estimating potential habitat for 134 eastern US tree species under six climate scenarios

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew Peters

2008-01-01

We modeled and mapped, using the predictive data mining tool Random Forests, 134 tree species from the eastern United States for potential response to several scenarios of climate change. Each species was modeled individually to show current and potential future habitats according to two emission scenarios (high emissions on current trajectory and reasonable...

Quantitative Trait Inheritance in a Forty-Year-Old Longleaf Pine Partial Diallel Test

Treesearch

Michael Stine; Jim Roberds; C. Dana Nelson; David P. Gwaze; Todd Shupe; Les Groom

2002-01-01

A longleaf pine (Pinus palustris Mill.) 13 parent partial diallel field experiment was established at two locations on the Harrison Experimental Forest in 1960. Parent trees were randomly selected from a natural population growing on the Harrison Experimental Forest, near Gulfport, Miss. Distance between trees chosen as parents ranged from 13 to 357...

Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

PubMed Central

Czégel, Dániel; Palla, Gergely

2015-01-01

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology. PMID:26657012

Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

NASA Astrophysics Data System (ADS)

Czégel, Dániel; Palla, Gergely

2015-12-01

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.

Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

PubMed

Czégel, Dániel; Palla, Gergely

2015-12-10

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.

Coalescent methods for estimating phylogenetic trees.

PubMed

Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V

2009-10-01

We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.

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.

Ground States of Random Spanning Trees on a D-Wave 2X

NASA Astrophysics Data System (ADS)

Hall, J. S.; Hobl, L.; Novotny, M. A.; Michielsen, Kristel

The performances of two D-Wave 2 machines (476 and 496 qubits) and of a 1097-qubit D-Wave 2X were investigated. Each chip has a Chimera interaction graph calG . Problem input consists of values for the fields hj and for the two-qubit interactions Ji , j of an Ising spin-glass problem formulated on calG . Output is returned in terms of a spin configuration {sj } , with sj = +/- 1 . We generated random spanning trees (RSTs) uniformly distributed over all spanning trees of calG . On the 476-qubit D-Wave 2, RSTs were generated on the full chip with Ji , j = - 1 and hj = 0 and solved one thousand times. The distribution of solution energies and the average magnetization of each qubit were determined. On both the 476- and 1097-qubit machines, four identical spanning trees were generated on each quadrant of the chip. The statistical independence of these regions was investigated. In another study, on the D-Wave 2X, one hundred RSTs with random Ji , j ∈ { - 1 , 1 } and hj = 0 were generated on the full chip. Each RST problem was solved one hundred times and the number of times the ground state energy was found was recorded. This procedure was repeated for square subgraphs, with dimensions ranging from 7 ×7 to 11 ×11. Supported in part by NSF Grants DGE-0947419 and DMR-1206233. D-Wave time provided by D-Wave Systems and by the USRA Quantum Artificial Intelligence Laboratory Research Opportunity.

Slowdowns in diversification rates from real phylogenies may not be real.

PubMed

Cusimano, Natalie; Renner, Susanne S

2010-07-01

Studies of diversification patterns often find a slowing in lineage accumulation toward the present. This seemingly pervasive pattern of rate downturns has been taken as evidence for adaptive radiations, density-dependent regulation, and metacommunity species interactions. The significance of rate downturns is evaluated with statistical tests (the gamma statistic and Monte Carlo constant rates (MCCR) test; birth-death likelihood models and Akaike Information Criterion [AIC] scores) that rely on null distributions, which assume that the included species are a random sample of the entire clade. Sampling in real phylogenies, however, often is nonrandom because systematists try to include early-diverging species or representatives of previous intrataxon classifications. We studied the effects of biased sampling, structured sampling, and random sampling by experimentally pruning simulated trees (60 and 150 species) as well as a completely sampled empirical tree (58 species) and then applying the gamma statistic/MCCR test and birth-death likelihood models/AIC scores to assess rate changes. For trees with random species sampling, the true model (i.e., the one fitting the complete phylogenies) could be inferred in most cases. Oversampling deep nodes, however, strongly biases inferences toward downturns, with simulations of structured and biased sampling suggesting that this occurs when sampling percentages drop below 80%. The magnitude of the effect and the sensitivity of diversification rate models is such that a useful rule of thumb may be not to infer rate downturns from real trees unless they have >80% species sampling.

The Probabilistic Thinking of Primary School Pupils in Cyprus: The Case of Tree Diagrams

ERIC Educational Resources Information Center

Lamprianou, Iasonas; Lamprianou, Thekla Afantiti

2003-01-01

In this research work we explored the nature of 9-12 year old pupils' responses to probabilistic problems with tree diagrams. It was found that a large percentage of pupils failed to respond correctly even to very simple problems that demanded the identification of "possible routes/paths" in figures with tree diagrams/mazes. The results…

Visualizing Biological Data in Museums: Visitor Learning with an Interactive Tree of Life Exhibit

ERIC Educational Resources Information Center

Horn, Michael S.; Phillips, Brenda C.; Evans, Evelyn Margaret; Block, Florian; Diamond, Judy; Shen, Chia

2016-01-01

In this study, we investigate museum visitor learning and engagement at an interactive visualization of an evolutionary tree of life consisting of over 70,000 species. The study was conducted at two natural history museums where visitors collaboratively explored the tree of life using direct touch gestures on a multi-touch tabletop display. In the…

A Regional Simulation to Explore Impacts of Resource Use and Constraints

DTIC Science & Technology

2007-03-01

mountaintops. (10) Deciduous Forest - This class is composed of forests, which contain at least 75% deciduous trees in the canopy, deciduous ... trees , pine plantations, and evergreen woodlands. (12) Mixed Forest - This class includes forests with mixed deciduous /coniferous canopies, natural...reflective surfaces. Classification of forested wetlands dominated by deciduous trees is probably more accurate than that in areas with 104

Fault Tree Analysis: An Operations Research Tool for Identifying and Reducing Undesired Events in Training.

ERIC Educational Resources Information Center

Barker, Bruce O.; Petersen, Paul D.

This paper explores the fault-tree analysis approach to isolating failure modes within a system. Fault tree investigates potentially undesirable events and then looks for failures in sequence that would lead to their occurring. Relationships among these events are symbolized by AND or OR logic gates, AND used when single events must coexist to…

A field-to-desktop toolchain for X-ray CT densitometry enables tree ring analysis

PubMed Central

De Mil, Tom; Vannoppen, Astrid; Beeckman, Hans; Van Acker, Joris; Van den Bulcke, Jan

2016-01-01

Background and Aims Disentangling tree growth requires more than ring width data only. Densitometry is considered a valuable proxy, yet laborious wood sample preparation and lack of dedicated software limit the widespread use of density profiling for tree ring analysis. An X-ray computed tomography-based toolchain of tree increment cores is presented, which results in profile data sets suitable for visual exploration as well as density-based pattern matching. Methods Two temperate (Quercus petraea, Fagus sylvatica) and one tropical species (Terminalia superba) were used for density profiling using an X-ray computed tomography facility with custom-made sample holders and dedicated processing software. Key Results Density-based pattern matching is developed and able to detect anomalies in ring series that can be corrected via interactive software. Conclusions A digital workflow allows generation of structure-corrected profiles of large sets of cores in a short time span that provide sufficient intra-annual density information for tree ring analysis. Furthermore, visual exploration of such data sets is of high value. The dated profiles can be used for high-resolution chronologies and also offer opportunities for fast screening of lesser studied tropical tree species. PMID:27107414

TreeQ-VISTA: An Interactive Tree Visualization Tool withFunctional Annotation Query Capabilities

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

Gu, Shengyin; Anderson, Iain; Kunin, Victor

2007-05-07

Summary: We describe a general multiplatform exploratorytool called TreeQ-Vista, designed for presenting functional annotationsin a phylogenetic context. Traits, such as phenotypic and genomicproperties, are interactively queried from a relational database with auser-friendly interface which provides a set of tools for users with orwithout SQL knowledge. The query results are projected onto aphylogenetic tree and can be displayed in multiple color groups. A richset of browsing, grouping and query tools are provided to facilitatetrait exploration, comparison and analysis.Availability: The program,detailed tutorial and examples are available online athttp://genome-test.lbl.gov/vista/TreeQVista.

Plant DNA barcodes and assessment of phylogenetic community structure of a tropical mixed dipterocarp forest in Brunei Darussalam (Borneo)

PubMed Central

Abu Salim, Kamariah; Chase, Mark W.; Dexter, Kyle G.; Pennington, R. Toby; Tan, Sylvester; Kaye, Maria Ellen; Samuel, Rosabelle

2017-01-01

DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m) of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia). The combined matrix (rbcL + matK) comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016), making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI) and nearest taxon index (NTI). In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals into analyses. PMID:29049301

Does Gene Tree Discordance Explain the Mismatch between Macroevolutionary Models and Empirical Patterns of Tree Shape and Branching Times?

PubMed Central

Stadler, Tanja; Degnan, James H.; Rosenberg, Noah A.

2016-01-01

Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth–death and multispecies coalescent model can explain the difference in empirical trees and birth–death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion. PMID:26968785

The structure of tropical forests and sphere packings

PubMed Central

Jahn, Markus Wilhelm; Dobner, Hans-Jürgen; Wiegand, Thorsten; Huth, Andreas

2015-01-01

The search for simple principles underlying the complex architecture of ecological communities such as forests still challenges ecological theorists. We use tree diameter distributions—fundamental for deriving other forest attributes—to describe the structure of tropical forests. Here we argue that tree diameter distributions of natural tropical forests can be explained by stochastic packing of tree crowns representing a forest crown packing system: a method usually used in physics or chemistry. We demonstrate that tree diameter distributions emerge accurately from a surprisingly simple set of principles that include site-specific tree allometries, random placement of trees, competition for space, and mortality. The simple static model also successfully predicted the canopy structure, revealing that most trees in our two studied forests grow up to 30–50 m in height and that the highest packing density of about 60% is reached between the 25- and 40-m height layer. Our approach is an important step toward identifying a minimal set of processes responsible for generating the spatial structure of tropical forests. PMID:26598678

Residual stand damage from crop tree release felling operations in white oak stands

Treesearch

Jeffrey W. Stringer; Gary W. Miller; H. Clay Smith

1988-01-01

This study was conducted at the University of Kentucky's Robinson Forest located in Breathitt, Knott, and Perry counties in eastern Kentucky. Three treatments including two levels of croptree release, leaving 20 and 34 crop trees per acre, and a control treatment were replicated 4 times and randomly distributed among l.2 white oak (Quercus alba...

Sample-based estimation of tree species richness in a wet tropical forest compartment

Treesearch

Steen Magnussen; Raphael Pelissier

2007-01-01

Petersen's capture-recapture ratio estimator and the well-known bootstrap estimator are compared across a range of simulated low-intensity simple random sampling with fixed-area plots of 100 m? in a rich wet tropical forest compartment with 93 tree species in the Western Ghats of India. Petersen's ratio estimator was uniformly superior to the bootstrap...

Aspen succession and nitrogen loading: a case for epiphytic lichens as bioindicators in the Rocky Mountains, USA

Treesearch

Paul C. Rogers; Kori D. Moore; Ronald J. Ryel

2009-01-01

Forty-seven randomly selected mid-elevation aspen stands were sampled for lichens and stand conditions. Plots were characterized according to tree species cover, basal area, stand age, bole scarring, tree damage, and presence of lichen species. We also recorded ammonia emissions with passive sensors at 25 urban and agricultural sites throughout an adjacent populated...

A ground-based method of assessing urban forest structure and ecosystem services

Treesearch

David J. Nowak; Daniel E. Crane; Jack C. Stevens; Robert E. Hoehn; Jeffrey T. Walton; Jerry Bond

2008-01-01

To properly manage urban forests, it is essential to have data on this important resource. An efficient means to obtain this information is to randomly sample urban areas. To help assess the urban forest structure (e.g., number of trees, species composition, tree sizes, health) and several functions (e.g., air pollution removal, carbon storage and sequestration), the...

Spatially random mortality in old-growth red pine forests of northern Minnesota

Treesearch

Tuomas ​Aakala; Shawn Fraver; Brian J. Palik; Anthony W. D' Amato

2012-01-01

Characterizing the spatial distribution of tree mortality is critical to understanding forest dynamics, but empirical studies on these patterns under old-growth conditions are rare. This rarity is due in part to low mortality rates in old-growth forests, the study of which necessitates long observation periods, and the confounding influence of tree in-growth during...

'Pygmy' old-growth redwood characteristics on an edaphic ecotone in Mendocino County, California

Treesearch

Will Russell; Suzie. Woolhouse

2012-01-01

The 'pygmy forest' is a specialized community that is adapted to highly acidic, hydrophobic, nutrient deprived soils, and exists in pockets within the coast redwood forest in Mendocino County. While coast redwood is known as an exceptionally tall tree, stunted trees exhibit unusual growth-forms on pygmy soils. We used a stratified random sampling procedure to...

Inferring phylogenetic trees from the knowledge of rare evolutionary events.

PubMed

Hellmuth, Marc; Hernandez-Rosales, Maribel; Long, Yangjing; Stadler, Peter F

2018-06-01

Rare events have played an increasing role in molecular phylogenetics as potentially homoplasy-poor characters. In this contribution we analyze the phylogenetic information content from a combinatorial point of view by considering the binary relation on the set of taxa defined by the existence of a single event separating two taxa. We show that the graph-representation of this relation must be a tree. Moreover, we characterize completely the relationship between the tree of such relations and the underlying phylogenetic tree. With directed operations such as tandem-duplication-random-loss events in mind we demonstrate how non-symmetric information constrains the position of the root in the partially reconstructed phylogeny.

AceTree: a major update and case study in the long term maintenance of open-source scientific software.

PubMed

Katzman, Braden; Tang, Doris; Santella, Anthony; Bao, Zhirong

2018-04-04

AceTree, a software application first released in 2006, facilitates exploration, curation and editing of tracked C. elegans nuclei in 4-dimensional (4D) fluorescence microscopy datasets. Since its initial release, AceTree has been continuously used to interact with, edit and interpret C. elegans lineage data. In its 11 year lifetime, AceTree has been periodically updated to meet the technical and research demands of its community of users. This paper presents the newest iteration of AceTree which contains extensive updates, demonstrates the new applicability of AceTree in other developmental contexts, and presents its evolutionary software development paradigm as a viable model for maintaining scientific software. Large scale updates have been made to the user interface for an improved user experience. Tools have been grouped according to functionality and obsolete methods have been removed. Internal requirements have been changed that enable greater flexibility of use both in C. elegans contexts and in other model organisms. Additionally, the original 3-dimensional (3D) viewing window has been completely reimplemented. The new window provides a new suite of tools for data exploration. By responding to technical advancements and research demands, AceTree has remained a useful tool for scientific research for over a decade. The updates made to the codebase have extended AceTree's applicability beyond its initial use in C. elegans and enabled its usage with other model organisms. The evolution of AceTree demonstrates a viable model for maintaining scientific software over long periods of time.

Long term changes in Intrinsic Water Use Efficiency, the palaoe record derived from stable carbon isotope measurements from tree rings.

NASA Astrophysics Data System (ADS)

Gagen, Mary; McCarroll, Danny; Loader, Neil; Young, Giles; Robertson, Iain

2015-04-01

Stable carbon isotope (δ13C) measurements from the annual rings of trees are increasingly used to explore long term changes in plant-carbon-water relations, via changes in intrinsic water use efficiency (iWUE); the ratio of photosynthetic rate to stomatal conductance. Many studies report a significant increase in iWEU since industrialisation, which tracks rising global atmospheric CO2. Such changes are logical are trees are known to change their stomatal geometry, number and action in response to rising CO2. However, which increasing iWUE suggests physiological changes which should lead to increased growth increasing iWUE is rarely matched by enhanced tree growth when tree rings are measured, despite increases of up to 30% in iWUE over the recent past (van der Sleen et al 2015). Explanations for the mismatch between iWUE and tree growth records encompass questions over the veracity of δ13C records for recording physiological change (Silva and Howarth 2013), suggestions that moisture stress in warming climates becomes a limit to growth and prevents opportunistic use of rising CO2 by trees (Andreu-Hayles et al 2011) and questions regarding the use of tree ring width, which does not record tree height gain, to record growth. Here we present an extensive range of long term iWUE records, derived broadly from the temperate, high latitude and one tropical forest site to explore the palaeoclimatic perspective on the iWUE-fertilization conundrum in a spatio temporally extensive manner.

An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Boyte, Stephen; Picotte, Joshua J.; Howard, Danny; Smith, Kelcy; Nelson, Kurtis

2016-01-01

Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve its accuracy and robustness. Landsat 8 data and Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI) were used to develop regression tree models. A Python procedure was designed to generate random replications of model parameter options across a range of model development data sizes and rule number constraints. The mean absolute difference (MAD) between the predicted and actual NDVI (scaled NDVI, value from 0–200) and its variability across the different randomized replications were calculated to assess the accuracy and stability of the models. In our case study, a six-rule regression tree model developed from 80% of the sample data had the lowest MAD (MADtraining = 2.5 and MADtesting = 2.4), which was suggested as the optimal model. This study demonstrates how the training data and rule number selections impact model accuracy and provides important guidance for future remote-sensing-based ecosystem modeling.

[Spatial patterns of dominant tree species in sub-alpine Betula-Abies forest in West Sichuan of China].

PubMed

Miao, Ning; Liu, Shi-Rong; Shi, Zuo-Min; Yu, Hong; Liu, Xing-Liang

2009-06-01

Based on the investigation in a 4 hm2 Betula-Abies forest plot in sub-alpine area in West Sichuan of China, and by using point pattern analysis method in terms of O-ring statistics, the spatial patterns of dominant species Betula albo-sinensis and Abies faxoniana in different age classes in study area were analyzed, and the intra- and inter-species associations between these age classes were studied. B. albo-sinensis had a unimodal distribution of its DBH frequency, indicating a declining population, while A. faxoniana had a reverse J-shaped pattern, showing an increasing population. All the big trees of B. albo-sinensis and A. faxoniana were spatially in random at all scales, while the medium age and small trees were spatially clumped at small scales and tended to be randomly or evenly distributed with increasing spatial scale. The maximum aggregation degree decreased with increasing age class. Spatial association mainly occurred at small scales. A. faxoniana generally showed positive intra-specific association, while B. albo-sinensis generally showed negative intra-specific association. For the two populations, big and small trees had no significant spatial association, but middle age trees had negative spatial association. Negative inter-specific associations of the two populations were commonly found in different age classes. The larger the difference of age class, the stronger the negative inter-specific association.

Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

Treesearch

J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

2012-01-01

Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

Merger of three modeling approaches to assess potential effects of climate change on trees in the eastern United States

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2010-01-01

Climate change will likely cause impacts that are species specific and significant; modeling is critical to better understand potential changes in suitable habitat. We use empirical, abundance-based habitat models utilizing decision tree-based ensemble methods to explore potential changes of 134 tree species habitats in the eastern United States (http://www.nrs.fs.fed....

Correlation Between the System Capabilities Analytic Process (SCAP) and the Missions and Means Framework (MMF)

DTIC Science & Technology

2013-05-01

specifics of the correlation will be explored followed by discussion of new paradigms— the ordered event list (OEL) and the decision tree — that result from...4.2.1  Brief Overview of the Decision Tree Paradigm ................................................15  4.2.2  OEL Explained...6  Figure 3. A depiction of a notional fault/activation tree . ................................................................7

Random Forest as an Imputation Method for Education and Psychology Research: Its Impact on Item Fit and Difficulty of the Rasch Model

ERIC Educational Resources Information Center

Golino, Hudson F.; Gomes, Cristiano M. A.

2016-01-01

This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Measuring (bio)physical tree properties using accelerometers

NASA Astrophysics Data System (ADS)

van Emmerik, Tim; Steele-Dunne, Susan; Hut, Rolf; Gentine, Pierre; Selker, John; van de Giesen, Nick

2017-04-01

Trees play a crucial role in the water, carbon and nitrogen cycle on local, regional and global scales. Understanding the exchange of heat, water, and CO2 between trees and the atmosphere is important to assess the impact of drought, deforestation and climate change. Unfortunately, ground measurements of tree dynamics are often expensive, or difficult due to challenging environments. We demonstrate the potential of measuring (bio)physical properties of trees using robust and affordable acceleration sensors. Tree sway is dependent on e.g. mass and wind energy absorption of the tree. By measuring tree acceleration we can relate the tree motion to external loads (e.g. precipitation), and tree (bio)physical properties (e.g. mass). Using five months of acceleration data of 19 trees in the Brazilian Amazon, we show that the frequency spectrum of tree sway is related to mass, precipitation, and canopy drag. This presentation aims to show the concept of using accelerometers to measure tree dynamics, and we acknowledge that the presented example applications is not an exhaustive list. Further analyses are the scope of current research, and we hope to inspire others to explore additional applications.

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

Patterns of thinking about phylogenetic trees: A study of student learning and the potential of tree thinking to improve comprehension of biological concepts

NASA Astrophysics Data System (ADS)

Naegle, Erin

Evolution education is a critical yet challenging component of teaching and learning biology. There is frequently an emphasis on natural selection when teaching about evolution and conducting educational research. A full understanding of evolution, however, integrates evolutionary processes, such as natural selection, with the resulting evolutionary patterns, such as species divergence. Phylogenetic trees are models of evolutionary patterns. The perspective gained from understanding biology through phylogenetic analyses is referred to as tree thinking. Due to the increasing prevalence of tree thinking in biology, understanding how to read phylogenetic trees is an important skill for students to learn. Interpreting graphics is not an intuitive process, as graphical representations are semiotic objects. This is certainly true concerning phylogenetic tree interpretation. Previous research and anecdotal evidence report that students struggle to correctly interpret trees. The objective of this research was to describe and investigate the rationale underpinning the prior knowledge of introductory biology students' tree thinking Understanding prior knowledge is valuable as prior knowledge influences future learning. In Chapter 1, qualitative methods such as semi-structured interviews were used to explore patterns of student rationale in regard to tree thinking. Seven common tree thinking misconceptions are described: (1) Equating the degree of trait similarity with the extent of relatedness, (2) Environmental change is a necessary prerequisite to evolution, (3) Essentialism of species, (4) Evolution is inherently progressive, (5) Evolution is a linear process, (6) Not all species are related, and (7) Trees portray evolution through the hybridization of species. These misconceptions are based in students' incomplete or incorrect understanding of evolution. These misconceptions are often reinforced by the misapplication of cultural conventions to make sense of trees. Chapter 2 explores the construction, validity, and reliability of a tree thinking concept inventory. Concept inventories are research based instruments that diagnose faulty reasoning among students. Such inventories are tools for improving teaching and learning of concepts. Test scores indicate that tree thinking misconceptions are held by novice and intermediate biology students. Finally, Chapter 3 presents a tree thinking rubric. The rubric aids teachers in selecting and improving introductory tree thinking learning exercises that address students' tree thinking misconceptions.

A fully resolved consensus between fully resolved phylogenetic trees.

PubMed

Quitzau, José Augusto Amgarten; Meidanis, João

2006-03-31

Nowadays, there are many phylogeny reconstruction methods, each with advantages and disadvantages. We explored the advantages of each method, putting together the common parts of trees constructed by several methods, by means of a consensus computation. A number of phylogenetic consensus methods are already known. Unfortunately, there is also a taboo concerning consensus methods, because most biologists see them mainly as comparators and not as phylogenetic tree constructors. We challenged this taboo by defining a consensus method that builds a fully resolved phylogenetic tree based on the most common parts of fully resolved trees in a given collection. We also generated results showing that this consensus is in a way a kind of "median" of the input trees; as such it can be closer to the correct tree in many situations.

Pruning a minimum spanning tree

NASA Astrophysics Data System (ADS)

Sandoval, Leonidas

2012-04-01

This work employs various techniques in order to filter random noise from the information provided by minimum spanning trees obtained from the correlation matrices of international stock market indices prior to and during times of crisis. The first technique establishes a threshold above which connections are considered affected by noise, based on the study of random networks with the same probability density distribution of the original data. The second technique is to judge the strength of a connection by its survival rate, which is the amount of time a connection between two stock market indices endures. The idea is that true connections will survive for longer periods of time, and that random connections will not. That information is then combined with the information obtained from the first technique in order to create a smaller network, in which most of the connections are either strong or enduring in time.

A flooding algorithm for multirobot exploration.

PubMed

Cabrera-Mora, Flavio; Xiao, Jizhong

2012-06-01

In this paper, we present a multirobot exploration algorithm that aims at reducing the exploration time and to minimize the overall traverse distance of the robots by coordinating the movement of the robots performing the exploration. Modeling the environment as a tree, we consider a coordination model that restricts the number of robots allowed to traverse an edge and to enter a vertex during each step. This coordination is achieved in a decentralized manner by the robots using a set of active landmarks that are dropped by them at explored vertices. We mathematically analyze the algorithm on trees, obtaining its main properties and specifying its bounds on the exploration time. We also define three metrics of performance for multirobot algorithms. We simulate and compare the performance of this new algorithm with those of our multirobot depth first search (MR-DFS) approach presented in our recent paper and classic single-robot DFS.

A phylogenetic perspective on the individual species-area relationship in temperate and tropical tree communities.

PubMed

Yang, Jie; Swenson, Nathan G; Cao, Min; Chuyong, George B; Ewango, Corneille E N; Howe, Robert; Kenfack, David; Thomas, Duncan; Wolf, Amy; Lin, Luxiang

2013-01-01

Ecologists have historically used species-area relationships (SARs) as a tool to understand the spatial distribution of species. Recent work has extended SARs to focus on individual-level distributions to generate individual species area relationships (ISARs). The ISAR approach quantifies whether individuals of a species tend have more or less species richness surrounding them than expected by chance. By identifying richness 'accumulators' and 'repellers', respectively, the ISAR approach has been used to infer the relative importance of abiotic and biotic interactions and neutrality. A clear limitation of the SAR and ISAR approaches is that all species are treated as evolutionarily independent and that a large amount of work has now shown that local tree neighborhoods exhibit non-random phylogenetic structure given the species richness. Here, we use nine tropical and temperate forest dynamics plots to ask: (i) do ISARs change predictably across latitude?; (ii) is the phylogenetic diversity in the neighborhood of species accumulators and repellers higher or lower than that expected given the observed species richness?; and (iii) do species accumulators, repellers distributed non-randomly on the community phylogenetic tree? The results indicate no clear trend in ISARs from the temperate zone to the tropics and that the phylogenetic diversity surrounding the individuals of species is generally only non-random on very local scales. Interestingly the distribution of species accumulators and repellers was non-random on the community phylogenies suggesting the presence of phylogenetic signal in the ISAR across latitude.

Minimal spanning trees at the percolation threshold: A numerical calculation

NASA Astrophysics Data System (ADS)

Sweeney, Sean M.; Middleton, A. Alan

2013-09-01

The fractal dimension of minimal spanning trees on percolation clusters is estimated for dimensions d up to d=5. A robust analysis technique is developed for correlated data, as seen in such trees. This should be a robust method suitable for analyzing a wide array of randomly generated fractal structures. The trees analyzed using these techniques are built using a combination of Prim's and Kruskal's algorithms for finding minimal spanning trees. This combination reduces memory usage and allows for simulation of larger systems than would otherwise be possible. The path length fractal dimension ds of MSTs on critical percolation clusters is found to be compatible with the predictions of the perturbation expansion developed by T. S. Jackson and N. Read [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.81.021131 81, 021131 (2010)].

Root location in random trees: a polarity property of all sampling consistent phylogenetic models except one.

PubMed

Steel, Mike

2012-10-01

Neutral macroevolutionary models, such as the Yule model, give rise to a probability distribution on the set of discrete rooted binary trees over a given leaf set. Such models can provide a signal as to the approximate location of the root when only the unrooted phylogenetic tree is known, and this signal becomes relatively more significant as the number of leaves grows. In this short note, we show that among models that treat all taxa equally, and are sampling consistent (i.e. the distribution on trees is not affected by taxa yet to be included), all such models, except one (the so-called PDA model), convey some information as to the location of the ancestral root in an unrooted tree. Copyright © 2012 Elsevier Inc. All rights reserved.

IcyTree: rapid browser-based visualization for phylogenetic trees and networks

PubMed Central

2017-01-01

Abstract Summary: IcyTree is an easy-to-use application which can be used to visualize a wide variety of phylogenetic trees and networks. While numerous phylogenetic tree viewers exist already, IcyTree distinguishes itself by being a purely online tool, having a responsive user interface, supporting phylogenetic networks (ancestral recombination graphs in particular), and efficiently drawing trees that include information such as ancestral locations or trait values. IcyTree also provides intuitive panning and zooming utilities that make exploring large phylogenetic trees of many thousands of taxa feasible. Availability and Implementation: IcyTree is a web application and can be accessed directly at http://tgvaughan.github.com/icytree. Currently supported web browsers include Mozilla Firefox and Google Chrome. IcyTree is written entirely in client-side JavaScript (no plugin required) and, once loaded, does not require network access to run. IcyTree is free software, and the source code is made available at http://github.com/tgvaughan/icytree under version 3 of the GNU General Public License. Contact: tgvaughan@gmail.com PMID:28407035

IcyTree: rapid browser-based visualization for phylogenetic trees and networks.

PubMed

Vaughan, Timothy G

2017-08-01

IcyTree is an easy-to-use application which can be used to visualize a wide variety of phylogenetic trees and networks. While numerous phylogenetic tree viewers exist already, IcyTree distinguishes itself by being a purely online tool, having a responsive user interface, supporting phylogenetic networks (ancestral recombination graphs in particular), and efficiently drawing trees that include information such as ancestral locations or trait values. IcyTree also provides intuitive panning and zooming utilities that make exploring large phylogenetic trees of many thousands of taxa feasible. IcyTree is a web application and can be accessed directly at http://tgvaughan.github.com/icytree . Currently supported web browsers include Mozilla Firefox and Google Chrome. IcyTree is written entirely in client-side JavaScript (no plugin required) and, once loaded, does not require network access to run. IcyTree is free software, and the source code is made available at http://github.com/tgvaughan/icytree under version 3 of the GNU General Public License. tgvaughan@gmail.com. © The Author(s) 2017. Published by Oxford University Press.

A causal role for right frontopolar cortex in directed, but not random, exploration

PubMed Central

Zajkowski, Wojciech K; Kossut, Malgorzata

2017-01-01

The explore-exploit dilemma occurs anytime we must choose between exploring unknown options for information and exploiting known resources for reward. Previous work suggests that people use two different strategies to solve the explore-exploit dilemma: directed exploration, driven by information seeking, and random exploration, driven by decision noise. Here, we show that these two strategies rely on different neural systems. Using transcranial magnetic stimulation to inhibit the right frontopolar cortex, we were able to selectively inhibit directed exploration while leaving random exploration intact. This suggests a causal role for right frontopolar cortex in directed, but not random, exploration and that directed and random exploration rely on (at least partially) dissociable neural systems. PMID:28914605

Dynamic Event Tree advancements and control logic improvements

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

Alfonsi, Andrea; Rabiti, Cristian; Mandelli, Diego

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN is currently equipped with three different sampling categories: Forward samplers (Monte Carlo, Latin Hyper Cube, Stratified, Grid Sampler, Factorials, etc.), Adaptive Samplers (Limit Surface search, Adaptive Polynomial Chaos, etc.) and Dynamic Event Tree (DET) samplers (Deterministic and Adaptive Dynamic Event Trees). The main subject of this document is to report the activities that have been donemore » in order to: start the migration of the RAVEN/RELAP-7 control logic system into MOOSE, and develop advanced dynamic sampling capabilities based on the Dynamic Event Tree approach. In order to provide to all MOOSE-based applications a control logic capability, in this Fiscal Year an initial migration activity has been initiated, moving the control logic system, designed for RELAP-7 by the RAVEN team, into the MOOSE framework. In this document, a brief explanation of what has been done is going to be reported. The second and most important subject of this report is about the development of a Dynamic Event Tree (DET) sampler named “Hybrid Dynamic Event Tree” (HDET) and its Adaptive variant “Adaptive Hybrid Dynamic Event Tree” (AHDET). As other authors have already reported, among the different types of uncertainties, it is possible to discern two principle types: aleatory and epistemic uncertainties. The classical Dynamic Event Tree is in charge of treating the first class (aleatory) uncertainties; the dependence of the probabilistic risk assessment and analysis on the epistemic uncertainties are treated by an initial Monte Carlo sampling (MCDET). From each Monte Carlo sample, a DET analysis is run (in total, N trees). The Monte Carlo employs a pre-sampling of the input space characterized by epistemic uncertainties. The consequent Dynamic Event Tree performs the exploration of the aleatory space. In the RAVEN code, a more general approach has been developed, not limiting the exploration of the epistemic space through a Monte Carlo method but using all the forward sampling strategies RAVEN currently employs. The user can combine a Latin Hyper Cube, Grid, Stratified and Monte Carlo sampling in order to explore the epistemic space, without any limitation. From this pre-sampling, the Dynamic Event Tree sampler starts its aleatory space exploration. As reported by the authors, the Dynamic Event Tree is a good fit to develop a goal-oriented sampling strategy. The DET is used to drive a Limit Surface search. The methodology that has been developed by the authors last year, performs a Limit Surface search in the aleatory space only. This report documents how this approach has been extended in order to consider the epistemic space interacting with the Hybrid Dynamic Event Tree methodology.« less

Do Trees Have Personalities? Experiencing the Concepts of Texture and Form

ERIC Educational Resources Information Center

Kosta, Timothy J.

2012-01-01

Nature is all around, and can be the inspiration for some excellent creations in the classroom. How can a teacher bring these rich natural elements into the art class? As the author was exploring a hiking trail, he came across a large piece of bark from an old oak tree. A strong wind began to blow through the trees, the leaves began to rustle and…

Leaves to landscapes: using high performance computing to assess patch-scale forest response to regional temperature and trace gas gradients

Treesearch

George E. Host; Harlan W. Stech; Kathryn E. Lenz; Kyle Roskoski; Richard Mather; Michael Donahue

2007-01-01

ECOPHYS is one of the early FSTM's that integrated plant physiological and tree architectural models to assess the relative importance of genetic traits in tree growth, and explore the growth response to interacting environmental stresses (Host et al 1999, Isebrands et al 1999, Martin et al 2001). This paper will describe extensions of the ECOPHYS individual tree...

A scaleable methodology for assessing the impacts of urban shade on the summer electricity use of residential homes

NASA Astrophysics Data System (ADS)

Taylor, Robert Vanderlei

Our cities are experiencing unprecedented growth while net global temperatures continue to trend warmer making sustainable urban development and energy conservation pressing public issues. This research explores how urban landscaping -- in particular trees and buildings -- affect summer electricity use in residential homes. I studied the interactions of urban shade and temperature to explore how vegetation distribution and intensity could play a meaningful role in heat mitigation in urban environments. Only a few studies have reconciled modeled electricity savings from tree shade with actual electricity consumption data. This research proposes a methodology for modeling the isolated effects of urban shade (tree shade vs building shade) on buildings' summertime electricity consumption from micro to mesoscales, empirically validating the modeled shade with actual electricity billing data, and comparing the electric energetic impact of tree shade effects with building shade effects. This proposed methodology seeks to resolve three primary research questions: 1) What are the modeled quantities of urban shade associated with the area of interest (AOI)? 2) To what extent do the effects of shading from trees and buildings mitigate summertime heat in the AOI? 2) To what extent do the shade effects from trees and buildings reduce summertime electricity consumption in the AOI?

A field-to-desktop toolchain for X-ray CT densitometry enables tree ring analysis.

PubMed

De Mil, Tom; Vannoppen, Astrid; Beeckman, Hans; Van Acker, Joris; Van den Bulcke, Jan

2016-06-01

Disentangling tree growth requires more than ring width data only. Densitometry is considered a valuable proxy, yet laborious wood sample preparation and lack of dedicated software limit the widespread use of density profiling for tree ring analysis. An X-ray computed tomography-based toolchain of tree increment cores is presented, which results in profile data sets suitable for visual exploration as well as density-based pattern matching. Two temperate (Quercus petraea, Fagus sylvatica) and one tropical species (Terminalia superba) were used for density profiling using an X-ray computed tomography facility with custom-made sample holders and dedicated processing software. Density-based pattern matching is developed and able to detect anomalies in ring series that can be corrected via interactive software. A digital workflow allows generation of structure-corrected profiles of large sets of cores in a short time span that provide sufficient intra-annual density information for tree ring analysis. Furthermore, visual exploration of such data sets is of high value. The dated profiles can be used for high-resolution chronologies and also offer opportunities for fast screening of lesser studied tropical tree species. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predicting live and dead tree basal area of bark beetle affected forests from discrete-return lidar

Treesearch

Benjamin C. Bright; Andrew T. Hudak; Robert McGaughey; Hans-Erik Andersen; Jose Negron

2013-01-01

Bark beetle outbreaks have killed large numbers of trees across North America in recent years. Lidar remote sensing can be used to effectively estimate forest biomass, but prediction of both live and dead standing biomass in beetle-affected forests using lidar alone has not been demonstrated. We developed Random Forest (RF) models predicting total, live, dead, and...

Mapping quantitative trait loci controlling early growth in a (longleaf pine × slash pine) × slash pine BC1 family

Treesearch

C. Weng; Thomas L. Kubisiak; C. Dana Nelson; M. Stine

2002-01-01

Random amplified polymorphic DNA (RAPD) markers were employed to map the genome and quantitative trait loci controlling the early growth of a pine hybrid F1 tree (Pinus palustris Mill. × P. elliottii Engl.) and a recurrent slash pine tree (P. ellottii Engl.) in a (longleaf pine × slash pine...

Assessing the Potential of Land Use Modification to Mitigate Ambient NO₂ and Its Consequences for Respiratory Health.

PubMed

Rao, Meenakshi; George, Linda A; Shandas, Vivek; Rosenstiel, Todd N

2017-07-10

Understanding how local land use and land cover (LULC) shapes intra-urban concentrations of atmospheric pollutants-and thus human health-is a key component in designing healthier cities. Here, NO₂ is modeled based on spatially dense summer and winter NO₂ observations in Portland-Hillsboro-Vancouver (USA), and the spatial variation of NO₂ with LULC investigated using random forest, an ensemble data learning technique. The NO 2 random forest model, together with BenMAP, is further used to develop a better understanding of the relationship among LULC, ambient NO₂ and respiratory health. The impact of land use modifications on ambient NO₂, and consequently on respiratory health, is also investigated using a sensitivity analysis. We find that NO₂ associated with roadways and tree-canopied areas may be affecting annual incidence rates of asthma exacerbation in 4-12 year olds by +3000 per 100,000 and -1400 per 100,000, respectively. Our model shows that increasing local tree canopy by 5% may reduce local incidences rates of asthma exacerbation by 6%, indicating that targeted local tree-planting efforts may have a substantial impact on reducing city-wide incidence of respiratory distress. Our findings demonstrate the utility of random forest modeling in evaluating LULC modifications for enhanced respiratory health.

Return probabilities and hitting times of random walks on sparse Erdös-Rényi graphs.

PubMed

Martin, O C; Sulc, P

2010-03-01

We consider random walks on random graphs, focusing on return probabilities and hitting times for sparse Erdös-Rényi graphs. Using the tree approach, which is expected to be exact in the large graph limit, we show how to solve for the distribution of these quantities and we find that these distributions exhibit a form of self-similarity.

Random Forest-Based Recognition of Isolated Sign Language Subwords Using Data from Accelerometers and Surface Electromyographic Sensors.

PubMed

Su, Ruiliang; Chen, Xiang; Cao, Shuai; Zhang, Xu

2016-01-14

Sign language recognition (SLR) has been widely used for communication amongst the hearing-impaired and non-verbal community. This paper proposes an accurate and robust SLR framework using an improved decision tree as the base classifier of random forests. This framework was used to recognize Chinese sign language subwords using recordings from a pair of portable devices worn on both arms consisting of accelerometers (ACC) and surface electromyography (sEMG) sensors. The experimental results demonstrated the validity of the proposed random forest-based method for recognition of Chinese sign language (CSL) subwords. With the proposed method, 98.25% average accuracy was obtained for the classification of a list of 121 frequently used CSL subwords. Moreover, the random forests method demonstrated a superior performance in resisting the impact of bad training samples. When the proportion of bad samples in the training set reached 50%, the recognition error rate of the random forest-based method was only 10.67%, while that of a single decision tree adopted in our previous work was almost 27.5%. Our study offers a practical way of realizing a robust and wearable EMG-ACC-based SLR systems.

Primate-inspired vehicle navigation using optic flow and mental rotations

NASA Astrophysics Data System (ADS)

Arkin, Ronald C.; Dellaert, Frank; Srinivasan, Natesh; Kerwin, Ryan

2013-05-01

Robot navigation already has many relatively efficient solutions: reactive control, simultaneous localization and mapping (SLAM), Rapidly-Exploring Random Trees (RRTs), etc. But many primates possess an additional inherent spatial reasoning capability: mental rotation. Our research addresses the question of what role, if any, mental rotations can play in enhancing existing robot navigational capabilities. To answer this question we explore the use of optical flow as a basis for extracting abstract representations of the world, comparing these representations with a goal state of similar format and then iteratively providing a control signal to a robot to allow it to move in a direction consistent with achieving that goal state. We study a range of transformation methods to implement the mental rotation component of the architecture, including correlation and matching based on cognitive studies. We also include a discussion of how mental rotations may play a key role in understanding spatial advice giving, particularly from other members of the species, whether in map-based format, gestures, or other means of communication. Results to date are presented on our robotic platform.

Exploring the nature of the Lyman-α emitter CR7

NASA Astrophysics Data System (ADS)

Hartwig, Tilman; Latif, Muhammad A.; Magg, Mattis; Bromm, Volker; Klessen, Ralf S.; Glover, Simon C. O.; Whalen, Daniel J.; Pellegrini, Eric W.; Volonteri, Marta

2016-10-01

CR7 is the brightest Lyman-α emitter observed at z > 6, which shows very strong Lyman-α and He II 1640 Å line luminosities, but no metal-line emission. Previous studies suggest that CR7 hosts either young primordial stars with a total stellar mass of ˜107 M⊙ or a black hole of ≳106 M⊙. Here, we explore different formation scenarios for CR7 with a semi-analytical model, based on the random sampling of dark matter merger trees. We are unable to reproduce the observational constraints with a primordial stellar source, given our model assumptions, due to the short stellar lifetimes and the early metal enrichment. Black holes that are the remnants of the first stars are either not massive enough, or reside in metal-polluted haloes, ruling out this possible explanation of CR7. Our models instead suggest that direct collapse black holes, which form in metal-free haloes exposed to large Lyman-Werner fluxes, are more likely the origin of CR7. However, this result is derived under optimistic assumptions and future observations are necessary to further constrain the nature of CR7.

Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis.

PubMed

Ozçift, Akin

2011-05-01

Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. In this way, an RF ensemble classifier performs better than a single tree from classification performance point of view. In general, multiclass datasets having unbalanced distribution of sample sizes are difficult to analyze in terms of class discrimination. Cardiac arrhythmia is such a dataset that has multiple classes with small sample sizes and it is therefore adequate to test our resampling based training strategy. The dataset contains 452 samples in fourteen types of arrhythmias and eleven of these classes have sample sizes less than 15. Our diagnosis strategy consists of two parts: (i) a correlation based feature selection algorithm is used to select relevant features from cardiac arrhythmia dataset. (ii) RF machine learning algorithm is used to evaluate the performance of selected features with and without simple random sampling to evaluate the efficiency of proposed training strategy. The resultant accuracy of the classifier is found to be 90.0% and this is a quite high diagnosis performance for cardiac arrhythmia. Furthermore, three case studies, i.e., thyroid, cardiotocography and audiology, are used to benchmark the effectiveness of the proposed method. The results of experiments demonstrated the efficiency of random sampling strategy in training RF ensemble classification algorithm. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effect of Fault Parameter Uncertainties on PSHA explored by Monte Carlo Simulations: A case study for southern Apennines, Italy

NASA Astrophysics Data System (ADS)

Akinci, A.; Pace, B.

2017-12-01

In this study, we discuss the seismic hazard variability of peak ground acceleration (PGA) at 475 years return period in the Southern Apennines of Italy. The uncertainty and parametric sensitivity are presented to quantify the impact of the several fault parameters on ground motion predictions for 10% exceedance in 50-year hazard. A time-independent PSHA model is constructed based on the long-term recurrence behavior of seismogenic faults adopting the characteristic earthquake model for those sources capable of rupturing the entire fault segment with a single maximum magnitude. The fault-based source model uses the dimensions and slip rates of mapped fault to develop magnitude-frequency estimates for characteristic earthquakes. Variability of the selected fault parameter is given with a truncated normal random variable distribution presented by standard deviation about a mean value. A Monte Carlo approach, based on the random balanced sampling by logic tree, is used in order to capture the uncertainty in seismic hazard calculations. For generating both uncertainty and sensitivity maps, we perform 200 simulations for each of the fault parameters. The results are synthesized both in frequency-magnitude distribution of modeled faults as well as the different maps: the overall uncertainty maps provide a confidence interval for the PGA values and the parameter uncertainty maps determine the sensitivity of hazard assessment to variability of every logic tree branch. These branches of logic tree, analyzed through the Monte Carlo approach, are maximum magnitudes, fault length, fault width, fault dip and slip rates. The overall variability of these parameters is determined by varying them simultaneously in the hazard calculations while the sensitivity of each parameter to overall variability is determined varying each of the fault parameters while fixing others. However, in this study we do not investigate the sensitivity of mean hazard results to the consideration of different GMPEs. Distribution of possible seismic hazard results is illustrated by 95% confidence factor map, which indicates the dispersion about mean value, and coefficient of variation map, which shows percent variability. The results of our study clearly illustrate the influence of active fault parameters to probabilistic seismic hazard maps.

A Systematic Prediction of Drug-Target Interactions Using Molecular Fingerprints and Protein Sequences.

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing

2018-01-01

Drug-Target Interactions (DTI) play a crucial role in discovering new drug candidates and finding new proteins to target for drug development. Although the number of detected DTI obtained by high-throughput techniques has been increasing, the number of known DTI is still limited. On the other hand, the experimental methods for detecting the interactions among drugs and proteins are costly and inefficient. Therefore, computational approaches for predicting DTI are drawing increasing attention in recent years. In this paper, we report a novel computational model for predicting the DTI using extremely randomized trees model and protein amino acids information. More specifically, the protein sequence is represented as a Pseudo Substitution Matrix Representation (Pseudo-SMR) descriptor in which the influence of biological evolutionary information is retained. For the representation of drug molecules, a novel fingerprint feature vector is utilized to describe its substructure information. Then the DTI pair is characterized by concatenating the two vector spaces of protein sequence and drug substructure. Finally, the proposed method is explored for predicting the DTI on four benchmark datasets: Enzyme, Ion Channel, GPCRs and Nuclear Receptor. The experimental results demonstrate that this method achieves promising prediction accuracies of 89.85%, 87.87%, 82.99% and 81.67%, respectively. For further evaluation, we compared the performance of Extremely Randomized Trees model with that of the state-of-the-art Support Vector Machine classifier. And we also compared the proposed model with existing computational models, and confirmed 15 potential drug-target interactions by looking for existing databases. The experiment results show that the proposed method is feasible and promising for predicting drug-target interactions for new drug candidate screening based on sizeable features. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Dissecting the space-time structure of tree-ring datasets using the partial triadic analysis.

PubMed

Rossi, Jean-Pierre; Nardin, Maxime; Godefroid, Martin; Ruiz-Diaz, Manuela; Sergent, Anne-Sophie; Martinez-Meier, Alejandro; Pâques, Luc; Rozenberg, Philippe

2014-01-01

Tree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967-2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967-2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

NASA Astrophysics Data System (ADS)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

Can Children Read Evolutionary Trees?

ERIC Educational Resources Information Center

Ainsworth, Shaaron; Saffer, Jessica

2013-01-01

Representations of the "tree of life" such as cladograms show the history of lineages and their relationships. They are increasingly found in formal and informal learning settings. Unfortunately, there is evidence that these representations can be challenging to interpret correctly. This study explored the question of whether children…

Green Mansions: The Evergreen Forests of the Pacific Northwest.

ERIC Educational Resources Information Center

Philipek, Frances; Smith, Shelley; Brook, Richard

2000-01-01

Explores the ecosystem in Pacific Northwest Coastal America and investigates land management issues. Discusses the impact of canopy trees on temperature and the forest itself. Explains fungi's relationship with trees and presents activities on stream flow, wood, volcanoes, and plants for the classroom. (YDS)

Scenario tree model for animal disease freedom framed in the OIE context using the example of a generic swine model for Aujeszky's disease in commercial swine in Canada.

PubMed

Christensen, Jette; Vallières, André

2016-01-01

"Freedom from animal disease" is an ambiguous concept that may have a different meaning in trade and science. For trade alone, there are different levels of freedom from OIE listed diseases. A country can: be recognized by OIE to be "officially free"; self-declare freedom, with no official recognition by the OIE; or report animal disease as absent (no occurrence) in six-monthly reports. In science, we apply scenario tree models to calculate the probability of a population being free from disease at a given prevalence to provide evidence of freedom from animal disease. Here, we link science with application by describing how a scenario tree model may contribute to a country's claim of freedom from animal disease. We combine the idea of a standardized presentation of scenario tree models for disease freedom and having a similar model for two different animal diseases to suggest that a simple generic model may help veterinary authorities to build and evaluate scenario tree models for disease freedom. Here, we aim to develop a generic scenario tree model for disease freedom that is: animal species specific, population specific, and has a simple structure. The specific objectives were: to explore the levels of freedom described in the OIE Terrestrial Animal Health Code; to describe how scenario tree models may contribute to a country's claim of freedom from animal disease; and to present a generic swine scenario tree model for disease freedom in Canada's domestic (commercial) swine applied to Aujeszky's disease (AD). In particular, to explore how historical survey data, and data mining may affect the probability of freedom and to explore different sampling strategies. Finally, to frame the generic scenario tree model in the context of Canada's claim of freedom from AD. We found that scenario tree models are useful to support a country's claim of freedom either as "recognized officially free" or as part of a self-declaration but the models should not stand alone in a claim. The generic AD scenario tree model demonstrated the benefit of combining three sources of surveillance data and helped to design the surveillance for the next year. The generic AD scenario model is one piece in Canada's self-declaration of freedom from AD. The model is strongly supported by the fact that AD has never been detected in Canada. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Modelling tree dynamics to assess the implementation of EU policies related to afforestation in SW Spain rangelands

NASA Astrophysics Data System (ADS)

Herguido, Estela; Pulido, Manuel; Francisco Lavado Contador, Joaquín; Schnabel, Susanne

2017-04-01

In Iberian dehesas and montados, the lack of tree recruitment compromises its long-term sustainability. However, in marginal areas of dehesas shrub encroachment facilitates tree recruitment while altering the distinctive physiognomic and cultural characteristics of the system. These are ongoing processes that should be considered when designing afforestation measures and policies. Based on spatial variables, we modeled the proneness of a piece of land to undergo tree recruitment and the results were related with the afforestation measures carried out under the UE First Afforestation Agricultural Land Program between 1992 and 2008. We analyzed the temporal tree population dynamics in 800 randomly selected plots of 100 m radius (2,510 ha in total) in dehesas and treeless pasturelands of Extremadura (hereafter rangelands). Tree changes were revealed by comparing aerial images taken in 1956 with orthophotographs and infrared ones from 2012. Spatial models that predict the areas prone either to lack tree recruitment or with recruitment were developed and based on three data mining algorithms: MARS (Multivariate Adaptive Regression Splines), Random Forest (RF) and Stochastic Gradient Boosting (Tree-Net, TN). Recruited-tree locations (1) vs. locations of places with no recruitment (0) (randomly selected from the study areas) were used as the binary dependent variable. A 5% of the data were used as test data set. As candidate explanatory variables we used 51 different topographic, climatic, bioclimatic, land cover-related and edaphic ones. The statistical models developed were extrapolated to the spatial context of the afforested areas in the region and also to the whole Extremenian rangelands, and the percentage of area modelled as prone to tree recruitment was calculated for each case. A total of 46,674.63 ha were afforested with holm oak (Quercus ilex) or cork oak (Quercus suber) in the studied rangelands under the UE First Afforestation Agricultural Land Program. In the sampled plots, 16,747 trees were detected as recruited, while 47,058 and 12,803 were present in both dates and lost during the studied period, respectively. Based on the Area Under the ROC Curve (AUC), all the data mining models considered showed a high fitness (MARS AUC= 0.86; TN AUC= 0.92; RF AUC= 0.95) and low misclassification rates. Correctly predicted test samples for absence and presence of tree recruitment accounted respectively to 78.3% and 76.8% when using MARS, 90.8% and 90.8% using TN and 88.9% and 89.1% using RF. The spatial patterns of the different models were similar. However, attending only the percentage of area prone to tree recruitment, outstanding differences were observed among models considering the total surface of rangelands (36.03% in MARS, 22.88% in TN and 6.72 % in RF). Despite these differences, when comparing the results with those of the afforested surfaces (31.73% in MARS, 20.70% in TN and 5.63 % in RF) the three algorithms pointed to similar conclusions, i.e. the afforestations performed in rangelands of Extremadura under UE First Afforestation Agricultural Land Program, barely discriminate between areas with or without natural regeneration. In conclusion, data mining technics are suitable to develop high-performance spatial models of vegetation dynamics. These models could be useful for policy and decision makers aimed at assessing the implementation of afforestation measures and the selection of more adequate locations.

Folding and unfolding phylogenetic trees and networks.

PubMed

Huber, Katharina T; Moulton, Vincent; Steel, Mike; Wu, Taoyang

2016-12-01

Phylogenetic networks are rooted, labelled directed acyclic graphswhich are commonly used to represent reticulate evolution. There is a close relationship between phylogenetic networks and multi-labelled trees (MUL-trees). Indeed, any phylogenetic network N can be "unfolded" to obtain a MUL-tree U(N) and, conversely, a MUL-tree T can in certain circumstances be "folded" to obtain aphylogenetic network F(T) that exhibits T. In this paper, we study properties of the operations U and F in more detail. In particular, we introduce the class of stable networks, phylogenetic networks N for which F(U(N)) is isomorphic to N, characterise such networks, and show that they are related to the well-known class of tree-sibling networks. We also explore how the concept of displaying a tree in a network N can be related to displaying the tree in the MUL-tree U(N). To do this, we develop aphylogenetic analogue of graph fibrations. This allows us to view U(N) as the analogue of the universal cover of a digraph, and to establish a close connection between displaying trees in U(N) and reconciling phylogenetic trees with networks.

Big cat phylogenies, consensus trees, and computational thinking.

PubMed

Sul, Seung-Jin; Williams, Tiffani L

2011-07-01

Phylogenetics seeks to deduce the pattern of relatedness between organisms by using a phylogeny or evolutionary tree. For a given set of organisms or taxa, there may be many evolutionary trees depicting how these organisms evolved from a common ancestor. As a result, consensus trees are a popular approach for summarizing the shared evolutionary relationships in a group of trees. We examine these consensus techniques by studying how the pantherine lineage of cats (clouded leopard, jaguar, leopard, lion, snow leopard, and tiger) evolved, which is hotly debated. While there are many phylogenetic resources that describe consensus trees, there is very little information, written for biologists, regarding the underlying computational techniques for building them. The pantherine cats provide us with a small, relevant example to explore the computational techniques (such as sorting numbers, hashing functions, and traversing trees) for constructing consensus trees. Our hope is that life scientists enjoy peeking under the computational hood of consensus tree construction and share their positive experiences with others in their community.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

2011-10-01

Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

Habitat Preferences of Boros schneideri (Coleoptera: Boridae) in the Natural Tree Stands of the Białowieża Forest

PubMed Central

Gutowski, Jerzy M.; Sućko, Krzysztof; Zub, Karol; Bohdan, Adam

2014-01-01

Abstract We analyzed habitat requirements of Boros schneideri (Panzer, 1796) (Coleoptera: Boridae) in the natural forests of the continental biogeographical region, using data collected in the Białowieża Forest. This species has been found on the six host trees, but it preferred dead, standing pine trees, characterized by large diameter, moderately moist and moist phloem but avoided trees in sunny locations. It occurred mostly in mesic and wet coniferous forests. This species demonstrated preferences for old tree stands (over 140-yr old), and its occurrence in younger tree-stand age classes (minimum 31–40-yr old) was not significantly different from random distribution. B. schneideri occupied more frequently locations distant from the forest edge, which were less affected by logging. Considering habitat requirements, character of occurrence, and decreasing number of occupied locations in the whole range of distribution, this species can be treated as relict of primeval forests. PMID:25527586

Quantifying multi-dimensional functional trait spaces of trees: empirical versus theoretical approaches

NASA Astrophysics Data System (ADS)

Ogle, K.; Fell, M.; Barber, J. J.

2016-12-01

Empirical, field studies of plant functional traits have revealed important trade-offs among pairs or triplets of traits, such as the leaf (LES) and wood (WES) economics spectra. Trade-offs include correlations between leaf longevity (LL) vs specific leaf area (SLA), LL vs mass-specific leaf respiration rate (RmL), SLA vs RmL, and resistance to breakage vs wood density. Ordination analyses (e.g., PCA) show groupings of traits that tend to align with different life-history strategies or taxonomic groups. It is unclear, however, what underlies such trade-offs and emergent spectra. Do they arise from inherent physiological constraints on growth, or are they more reflective of environmental filtering? The relative importance of these mechanisms has implications for predicting biogeochemical cycling, which is influenced by trait distributions of the plant community. We address this question using an individual-based model of tree growth (ACGCA) to quantify the theoretical trait space of trees that emerges from physiological constraints. ACGCA's inputs include 32 physiological, anatomical, and allometric traits, many of which are related to the LES and WES. We fit ACGCA to 1.6 million USFS FIA observations of tree diameters and heights to obtain vectors of trait values that produce realistic growth, and we explored the structure of this trait space. No notable correlations emerged among the 496 trait pairs, but stepwise regressions revealed complicated multi-variate structure: e.g., relationships between pairs of traits (e.g., RmL and SLA) are governed by other traits (e.g., LL, radiation-use efficiency [RUE]). We also simulated growth under various canopy gap scenarios that impose varying degrees of environmental filtering to explore the multi-dimensional trait space (hypervolume) of trees that died vs survived. The centroid and volume of the hypervolumes differed among dead and live trees, especially under gap conditions leading to low mortality. Traits most predictive of tree-level mortality were maximum tree height, RUE, xylem conducting area, and branch turn-over rate. We are using these hypervolumes as priors to an emulator that approximates the ACGCA, which we are fitting to the FIA data to quantify species-specific trait spectra and to explore factors giving rise to species differences.

Analysis of the pattern of potential woody cover in Texas savanna

NASA Astrophysics Data System (ADS)

Yang, Xuebin; Crews, Kelley A.; Yan, Bowei

2016-10-01

While woody plant encroachment has been observed worldwide in savannas and adversely affected the ecosystem structure and function, a thorough understanding of the nature of this phenomenon is urgently required for savanna management and restoration. Among others, potential woody cover (the maximum realizable woody cover that a given site can support), especially its variation over environment has huge implication on the encroachment management in particular, and on tree-grass interactions in general. This project was designed to explore the pattern of potential woody cover in Texas savanna, an ecosystem with a large rainfall gradient in west-east direction. Substantial random pixels were sampled across the study area from MODIS Vegetation Continuous Fields (VCF) tree cover layer (250 m). Since potential woody cover is suggested to be limited by water availability, a nonlinear 99th quantile regression was performed between the observed woody cover and mean annual precipitation (MAP) to model the pattern of potential woody cover. Research result suggests a segmented relationship between potential woody cover and MAP at MODIS scale. Potential biases as well as the practical and theoretical implications were discussed. Through this study, the hypothesis about the primary role of water availability in determining savanna woody cover was further confirmed in a relatively understudied US-located savanna.

Mixed-up trees: the structure of phylogenetic mixtures.

PubMed

Matsen, Frederick A; Mossel, Elchanan; Steel, Mike

2008-05-01

In this paper, we apply new geometric and combinatorial methods to the study of phylogenetic mixtures. The focus of the geometric approach is to describe the geometry of phylogenetic mixture distributions for the two state random cluster model, which is a generalization of the two state symmetric (CFN) model. In particular, we show that the set of mixture distributions forms a convex polytope and we calculate its dimension; corollaries include a simple criterion for when a mixture of branch lengths on the star tree can mimic the site pattern frequency vector of a resolved quartet tree. Furthermore, by computing volumes of polytopes we can clarify how "common" non-identifiable mixtures are under the CFN model. We also present a new combinatorial result which extends any identifiability result for a specific pair of trees of size six to arbitrary pairs of trees. Next we present a positive result showing identifiability of rates-across-sites models. Finally, we answer a question raised in a previous paper concerning "mixed branch repulsion" on trees larger than quartet trees under the CFN model.

TreeNetViz: revealing patterns of networks over tree structures.

PubMed

Gou, Liang; Zhang, Xiaolong Luke

2011-12-01

Network data often contain important attributes from various dimensions such as social affiliations and areas of expertise in a social network. If such attributes exhibit a tree structure, visualizing a compound graph consisting of tree and network structures becomes complicated. How to visually reveal patterns of a network over a tree has not been fully studied. In this paper, we propose a compound graph model, TreeNet, to support visualization and analysis of a network at multiple levels of aggregation over a tree. We also present a visualization design, TreeNetViz, to offer the multiscale and cross-scale exploration and interaction of a TreeNet graph. TreeNetViz uses a Radial, Space-Filling (RSF) visualization to represent the tree structure, a circle layout with novel optimization to show aggregated networks derived from TreeNet, and an edge bundling technique to reduce visual complexity. Our circular layout algorithm reduces both total edge-crossings and edge length and also considers hierarchical structure constraints and edge weight in a TreeNet graph. These experiments illustrate that the algorithm can reduce visual cluttering in TreeNet graphs. Our case study also shows that TreeNetViz has the potential to support the analysis of a compound graph by revealing multiscale and cross-scale network patterns. © 2011 IEEE

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

Static terrestrial laser scanning of juvenile understory trees for field phenotyping

NASA Astrophysics Data System (ADS)

Wang, Huanhuan; Lin, Yi

2014-11-01

This study was to attempt the cutting-edge 3D remote sensing technique of static terrestrial laser scanning (TLS) for parametric 3D reconstruction of juvenile understory trees. The data for test was collected with a Leica HDS6100 TLS system in a single-scan way. The geometrical structures of juvenile understory trees are extracted by model fitting. Cones are used to model trunks and branches. Principal component analysis (PCA) is adopted to calculate their major axes. Coordinate transformation and orthogonal projection are used to estimate the parameters of the cones. Then, AutoCAD is utilized to simulate the morphological characteristics of the understory trees, and to add secondary branches and leaves in a random way. Comparison of the reference values and the estimated values gives the regression equation and shows that the proposed algorithm of extracting parameters is credible. The results have basically verified the applicability of TLS for field phenotyping of juvenile understory trees.

What contributes to perceived stress in later life? A recursive partitioning approach.

PubMed

Scott, Stacey B; Jackson, Brenda R; Bergeman, C S

2011-12-01

One possible explanation for the individual differences in outcomes of stress is the diversity of inputs that produce perceptions of being stressed. The current study examines how combinations of contextual features (e.g., social isolation, neighborhood quality, health problems, age discrimination, financial concerns, and recent life events) of later life contribute to overall feelings of stress. Recursive partitioning techniques (regression trees and random forests) were used to examine unique interrelations between predictors of perceived stress in a sample of 282 community-dwelling adults. Trees provided possible examples of equifinality (i.e., subsets of people with similar levels of perceived stress but different predictors) as well as identification both of contextual combinations that separated participants with very high and very low perceived stress. Random forest analyses aggregated across many trees based on permuted versions of the data and predictors; loneliness, financial strain, neighborhood strain, ageism, and to some extent life events emerged as important predictors. Interviews with a subsample of participants provided both thick description of the complex relationships identified in the trees, as well as additional risks not appearing in the survey results. Together, the analyses highlight what may be missed when stress is used as a simple unidimensional construct and can guide differential intervention efforts.

What contributes to perceived stress in later life? A recursive partitioning approach

PubMed Central

Scott, Stacey B.; Jackson, Brenda R.; Bergeman, C. S.

2011-01-01

One possible explanation for the individual differences in outcomes of stress is the diversity of inputs that produce perceptions of being stressed. The current study examines how combinations of contextual features (e.g., social isolation, neighborhood quality, health problems, age discrimination, financial concerns, and recent life events) of later life contribute to overall feelings of stress. Recursive partitioning techniques (regression trees and random forests) were used to examine unique interrelations between predictors of perceived stress in a sample of 282 community-dwelling adults. Trees provided possible examples of equifinality (i.e., subsets of people with similar levels of perceived stress but different predictors) as well as for the identification both of contextual combinations that separated participants with very high and very low perceived stress. Random forest analyses aggregated across many trees based on permuted versions of the data and predictors; loneliness, financial strain, neighborhood strain, ageism, and to some extent life events emerged as important predictors. Interviews with a subsample of participants provided both thick description of the complex relationships identified in the trees, as well as additional risks not appearing in the survey results. Together, the analyses highlight what may be missed when stress is used as a simple unidimensional construct and can guide differential intervention efforts. PMID:21604885

Using slides to test for changes in crown defoliation assessment methods. Part I: Visual assessment of slides.

PubMed

Dobbertin, Matthias; Hug, Christian; Mizoue, Nobuya

2004-11-01

In this study we used photographs of tree crowns to test whether the assessment methods for tree defoliation in Switzerland have changed over time. We randomly selected 24 series of slides of Norway spruce with field assessments made between 1986 and 1995. The slides were randomly arranged and assessed by three experts without prior knowledge of the year when the slide was taken or the tree number. Defoliation was assessed using the Swiss reference photo guide. Although the correlations between the field assessments and slide assessments were high (Spearman's rank correlation coefficient ranged between 0.79 and 0.83), we found significant differences between field and slide assessments (4.3 to 9% underprediction by the slide assessors) and between the slide assessments. However, no significant trends in field assessment methods could be detected. When the mean differences between field and slide assessments were subtracted, in some years, field assessors consistently underpredicted (1990, 1992) or overpredicted defoliation (1987, 1991). Defoliation tended to be overpredicted in slides taken against the light, and underpredicted for trees with more than 25% crown overlap. We conclude that slide series can be used to detect changes in assessment methods. However, potential observer bias calls for more objective methods of assessment.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Strategic conservation of orchard germplasm based on indigenous knowledge and genetic diversity: a case study of sour orange populations in China.

PubMed

Ming, Feng; Liu, Qi-Kun; Shi, Jin-Lei; Wang, Wei; Lu, Bao-Rong

2009-01-01

To effectively conserve sour orange (Citrus aurantium L.) germplasm on two islands at the estuary of the Yangtze River in China, we estimated genetic variation and relationships of the known parental trees and their proposed descendents (young trees) using the fingerprints of random amplified polymorphic DNA (RAPD). Results based on RAPD analyses showed considerable genetic diversity in the parental populations (H(e)=0.202). The overall populations including the parental and young trees showed slightly higher genetic diversity (H(e)=0.298) than the parents, with about 10% variation between populations. An unweighted pair group method with arithmetic mean analysis dendrogram based on cluster analysis of the Jaccard similarity among individuals demonstrated a more complicated relationship of the parental and young trees from the two islands, although the young trees showed a clear association with parental trees. This indicates a significant contribution of parental trees in establishing the sour orange populations on the two islands. According to farmers' knowledge, conservation of only one or two parental trees would be sufficient because they believed that the whole populations were generated from a single mother tree. However, this study suggests that preserving most parental trees and some selected young trees with distant genetic relationships should be an effective conservation strategy for sour orange germplasm on the two islands.

The Day the Children Found a Ghost.

ERIC Educational Resources Information Center

Kapur, Madhavi

1993-01-01

The headmistress of an English school in India explains how a group of eight year olds responded to finding a "ghost" in a tree in the school courtyard. First-hand observation, exploration, and hard evidence led students to a more objective interpretation of the elusive tree spirit. (MLH)

Beech root sprouts can be damaged by sodium arsenite treatment of parent tree

Treesearch

Frederick H. Berry

1956-01-01

American beech (Fagus grandifolia) can produce an abundance of root sprouts. In some cut-over woodlands, the sprouts occupy space that could be utilized by more desirable tree species. Therefore it seemed desirable to explore methods of destroying beech root sprouts.

Spatial Patterns between Regolith Thickness and Forest Productivity in the Southern Sierra CZO

NASA Astrophysics Data System (ADS)

Ferrell, R. M.; Ferrell, D. F.; Hartsough, P. C.; O'Geen, T. T.

2015-12-01

Soil in conjunction with underlying weathered bedrock make up what is referred to as regolith, which can be thought of as the substrate that actively contributes water and nutrients to above ground biomass. As a result, regolith thickness is an important regulating factor of forest health and drought tolerance in the Sierra Nevada. Our project examined the relationships between landscape position, regolith thickness, and tree productivity within a sub watershed of the Southern Sierra Critical Zone Observatory. We hypothesized that tree productivity will increase with increasing regolith thickness. Data was collected in the summer of 2015 at sixty-five sites within a 522-ha watershed averaging 1180m in elevation with a MAP of 80cm and a MAT of 11C. Sites were randomly selected from a grid and then stratified in the field to capture representative samples from different landscape positions. Regolith was sampled using a hand auger with attachable extensions. At each site we augered to hard bedrock or a maximum depth of 7.56 m, which ever was shallower. Biomass measurements were made for all conifer species (DBH>20cm) within a 10m radius of the primary auger hole. Tree age was measured from a representative tree for all species in the plots. Preliminary findings suggest that there is a weak correlation between landscape position/slope and regolith thickness, likely due to differences in lithology. It also appears that terrain shape can result in conflicting outcomes: 1. It can focus water to promote physical and chemical weathering and thick regolith; or, 2. water focusing can result in landscape scouring, removing soil and weathered bedrock to create shallow regolith. Productivity appears to be a function of regolith thickness, effective precipitation and landscape position. Water collecting areas in the lower watershed are shallow to bedrock, but typically receive high amounts of effective precipitation resulting in greater tree productivity. Moreover, thick regolith in uplands also supports high productivity. Future work will explore the application of terrain attributes computed from DEMs to characterize the contributions of terrain and effective precipitation. As climate change continues it will become increasingly important for land managers to evaluate forest health, productivity and drought tolerance.

The feasibility of using a universal Random Forest model to map tree height across different locations and vegetation types

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Jin, S.; Gao, S.; Hu, T.; Liu, J.; Xue, B. L.

2017-12-01

Tree height is an important forest structure parameter for understanding forest ecosystem and improving the accuracy of global carbon stock quantification. Light detection and ranging (LiDAR) can provide accurate tree height measurements, but its use in large-scale tree height mapping is limited by the spatial availability. Random Forest (RF) has been one of the most commonly used algorithms for mapping large-scale tree height through the fusion of LiDAR and other remotely sensed datasets. However, how the variances in vegetation types, geolocations and spatial scales of different study sites influence the RF results is still a question that needs to be addressed. In this study, we selected 16 study sites across four vegetation types in United States (U.S.) fully covered by airborne LiDAR data, and the area of each site was 100 km2. The LiDAR-derived canopy height models (CHMs) were used as the ground truth to train the RF algorithm to predict canopy height from other remotely sensed variables, such as Landsat TM imagery, terrain information and climate surfaces. To address the abovementioned question, 22 models were run under different combinations of vegetation types, geolocations and spatial scales. The results show that the RF model trained at one specific location or vegetation type cannot be used to predict tree height in other locations or vegetation types. However, by training the RF model using samples from all locations and vegetation types, a universal model can be achieved for predicting canopy height across different locations and vegetation types. Moreover, the number of training samples and the targeted spatial resolution of the canopy height product have noticeable influence on the RF prediction accuracy.

On the distribution of interspecies correlation for Markov models of character evolution on Yule trees.

PubMed

Mulder, Willem H; Crawford, Forrest W

2015-01-07

Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.

SDIA: A dynamic situation driven information fusion algorithm for cloud environment

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Tong; Wang, Jian

2017-09-01

Information fusion is an important issue in information integration domain. In order to form an extensive information fusion technology under the complex and diverse situations, a new information fusion algorithm is proposed. Firstly, a fuzzy evaluation model of tag utility was proposed that can be used to count the tag entropy. Secondly, a ubiquitous situation tag tree model is proposed to define multidimensional structure of information situation. Thirdly, the similarity matching between the situation models is classified into three types: the tree inclusion, the tree embedding, and the tree compatibility. Next, in order to reduce the time complexity of the tree compatible matching algorithm, a fast and ordered tree matching algorithm is proposed based on the node entropy, which is used to support the information fusion by ubiquitous situation. Since the algorithm revolve from the graph theory of disordered tree matching algorithm, it can improve the information fusion present recall rate and precision rate in the situation. The information fusion algorithm is compared with the star and the random tree matching algorithm, and the difference between the three algorithms is analyzed in the view of isomorphism, which proves the innovation and applicability of the algorithm.

Detection of dead standing Eucalyptus camaldulensis without tree delineation for managing biodiversity in native Australian forest

NASA Astrophysics Data System (ADS)

Miltiadou, Milto; Campbell, Neil D. F.; Gonzalez Aracil, Susana; Brown, Tony; Grant, Michael G.

2018-05-01

In Australia, many birds and arboreal animals use hollows for shelters, but studies predict shortage of hollows in near future. Aged dead trees are more likely to contain hollows and therefore automated detection of them plays a substantial role in preserving biodiversity and consequently maintaining a resilient ecosystem. For this purpose full-waveform LiDAR data were acquired from a native Eucalypt forest in Southern Australia. The structure of the forest significantly varies in terms of tree density, age and height. Additionally, Eucalyptus camaldulensis have multiple trunk splits making tree delineation very challenging. For that reason, this paper investigates automated detection of dead standing Eucalyptus camaldulensis without tree delineation. It also presents the new feature of the open source software DASOS, which extracts features for 3D object detection in voxelised FW LiDAR. A random forest classifier, a weighted-distance KNN algorithm and a seed growth algorithm are used to create a 2D probabilistic field and to then predict potential positions of dead trees. It is shown that tree health assessment is possible without tree delineation but since it is a new research directions there are many improvements to be made.

Tree cover in Central Africa: determinants and sensitivity under contrasted scenarios of global change.

PubMed

Aleman, Julie C; Blarquez, Olivier; Gourlet-Fleury, Sylvie; Bremond, Laurent; Favier, Charly

2017-01-30

Tree cover is a key variable for ecosystem functioning, and is widely used to study tropical ecosystems. But its determinants and their relative importance are still a matter of debate, especially because most regional and global analyses have not considered the influence of agricultural practices. More information is urgently needed regarding how human practices influence vegetation structure. Here we focused in Central Africa, a region still subjected to traditional agricultural practices with a clear vegetation gradient. Using remote sensing data and global databases, we calibrated a Random Forest model to correlatively link tree cover with climatic, edaphic, fire and agricultural practices data. We showed that annual rainfall and accumulated water deficit were the main drivers of the distribution of tree cover and vegetation classes (defined by the modes of tree cover density), but agricultural practices, especially pastoralism, were also important in determining tree cover. We simulated future tree cover with our model using different scenarios of climate and land-use (agriculture and population) changes. Our simulations suggest that tree cover may respond differently regarding the type of scenarios, but land-use change was an important driver of vegetation change even able to counterbalance the effect of climate change in Central Africa.

Tree cover in Central Africa: determinants and sensitivity under contrasted scenarios of global change

NASA Astrophysics Data System (ADS)

Aleman, Julie C.; Blarquez, Olivier; Gourlet-Fleury, Sylvie; Bremond, Laurent; Favier, Charly

2017-01-01

Tree cover is a key variable for ecosystem functioning, and is widely used to study tropical ecosystems. But its determinants and their relative importance are still a matter of debate, especially because most regional and global analyses have not considered the influence of agricultural practices. More information is urgently needed regarding how human practices influence vegetation structure. Here we focused in Central Africa, a region still subjected to traditional agricultural practices with a clear vegetation gradient. Using remote sensing data and global databases, we calibrated a Random Forest model to correlatively link tree cover with climatic, edaphic, fire and agricultural practices data. We showed that annual rainfall and accumulated water deficit were the main drivers of the distribution of tree cover and vegetation classes (defined by the modes of tree cover density), but agricultural practices, especially pastoralism, were also important in determining tree cover. We simulated future tree cover with our model using different scenarios of climate and land-use (agriculture and population) changes. Our simulations suggest that tree cover may respond differently regarding the type of scenarios, but land-use change was an important driver of vegetation change even able to counterbalance the effect of climate change in Central Africa.

A Maze Game on Android Using Growing Tree Method

NASA Astrophysics Data System (ADS)

Hendrawan, Y. F.

2018-01-01

A maze is a type of puzzle games where a player moves in complex and branched passages to find a particular target or location. One method to create a maze is the Growing Tree method. The method creates a tree that has branches which are the paths of a maze. This research explored three types of Growing Tree method implementations for maze generation on Android mobile devices. The layouts produced could be played in first and third-person perspectives. The experiment results showed that it took 17.3 seconds on average to generate 20 cells x 20 cells dynamic maze layouts.

Clustering Tree-structured Data on Manifold

PubMed Central

Lu, Na; Miao, Hongyu

2016-01-01

Tree-structured data usually contain both topological and geometrical information, and are necessarily considered on manifold instead of Euclidean space for appropriate data parameterization and analysis. In this study, we propose a novel tree-structured data parameterization, called Topology-Attribute matrix (T-A matrix), so the data clustering task can be conducted on matrix manifold. We incorporate the structure constraints embedded in data into the non-negative matrix factorization method to determine meta-trees from the T-A matrix, and the signature vector of each single tree can then be extracted by meta-tree decomposition. The meta-tree space turns out to be a cone space, in which we explore the distance metric and implement the clustering algorithm based on the concepts like Fréchet mean. Finally, the T-A matrix based clustering (TAMBAC) framework is evaluated and compared using both simulated data and real retinal images to illus trate its efficiency and accuracy. PMID:26660696

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.

Index Blood Tests and National Early Warning Scores within 24 Hours of Emergency Admission Can Predict the Risk of In-Hospital Mortality: A Model Development and Validation Study

PubMed Central

Mohammed, Mohammed A.; Rudge, Gavin; Watson, Duncan; Wood, Gordon; Smith, Gary B.; Prytherch, David R.; Girling, Alan; Stevens, Andrew

2013-01-01

Background We explored the use of routine blood tests and national early warning scores (NEWS) reported within ±24 hours of admission to predict in-hospital mortality in emergency admissions, using empirical decision Tree models because they are intuitive and may ultimately be used to support clinical decision making. Methodology A retrospective analysis of adult emergency admissions to a large acute hospital during April 2009 to March 2010 in the West Midlands, England, with a full set of index blood tests results (albumin, creatinine, haemoglobin, potassium, sodium, urea, white cell count and an index NEWS undertaken within ±24 hours of admission). We developed a Tree model by randomly splitting the admissions into a training (50%) and validation dataset (50%) and assessed its accuracy using the concordance (c-) statistic. Emergency admissions (about 30%) did not have a full set of index blood tests and/or NEWS and so were not included in our analysis. Results There were 23248 emergency admissions with a full set of blood tests and NEWS with an in-hospital mortality of 5.69%. The Tree model identified age, NEWS, albumin, sodium, white cell count and urea as significant (p<0.001) predictors of death, which described 17 homogeneous subgroups of admissions with mortality ranging from 0.2% to 60%. The c-statistic for the training model was 0.864 (95%CI 0.852 to 0.87) and when applied to the testing data set this was 0.853 (95%CI 0.840 to 0.866). Conclusions An easy to interpret validated risk adjustment Tree model using blood test and NEWS taken within ±24 hours of admission provides good discrimination and offers a novel approach to risk adjustment which may potentially support clinical decision making. Given the nature of the clinical data, the results are likely to be generalisable but further research is required to investigate this promising approach. PMID:23734195

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.

Minimizing the cost of translocation failure with decision-tree models that predict species' behavioral response in translocation sites.

PubMed

Ebrahimi, Mehregan; Ebrahimie, Esmaeil; Bull, C Michael

2015-08-01

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision-tree models for species' translocation, we used data on the short-term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision-tree algorithms (decision tree, decision-tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. © 2015 Society for Conservation Biology.

Exploring the Taxonomy of Oaks and Related Tree Species

ERIC Educational Resources Information Center

McMaster, Robert T.

2004-01-01

A lab in Eastern North America conducted a study to determine the taxonomic relationship between deciduous trees and several species of oaks by calculating the similarity index of all species to be studied. The study enabled students to classify the different species of oaks according to their distinct characteristics.

Dominant forest tree mycorrhizal type mediates understory plant invasions

Treesearch

Insu Jo; Kevin M. Potter; Grant M. Domke; Songlin Fei

2017-01-01

Forest mycorrhizal type mediates nutrient dynamics, which in turn can influence forest community structure and processes. Using forest inventory data, we explored how dominant forest tree mycorrhizal type affects understory plant invasions with consideration of forest structure and soil properties. We found that arbuscular mycorrhizal (AM) dominant forests, which are...

Activist or Terrorist? Negotiating Discourses of Eco-Terror in "If a Tree Falls"

ERIC Educational Resources Information Center

Olson, Jade

2018-01-01

Environmentalist voices like the Earth Liberation Front have been labeled "eco-terrorists." The 2011 documentary film "If a Tree Falls" explores how "eco-terrorism" troubles the unstable border between activism and terrorism. This essay offers a textual analysis of the film's negotiation of the activism/terrorism…

Bilingual approach to online cancer genetics education for deaf American Sign Language users produces greater knowledge and confidence than English text only: A randomized study

PubMed Central

Palmer, Christina G.S.; Boudreault, Patrick; Berman, Barbara A.; Wolfson, Alicia; Duarte, Lionel; Venne, Vickie L.; Sinsheimer, Janet S.

2016-01-01

Introduction Deaf American Sign Language-users (ASL) have limited access to cancer genetics information they can readily understand, increasing risk for health disparities. We compared effectiveness of online cancer genetics information presented using a bilingual approach (ASL with English closed captioning) and a monolingual approach (English text). Hypothesis Bilingual modality would increase cancer genetics knowledge and confidence to create a family tree; education would interact with modality. Methods We used a block 2:1 randomized pre-post study design stratified on education. 150 Deaf ASL-users ≥18 years old with computer and internet access participated online; 100 (70 high, 30 low education) and 50 (35 high, 15 low education) were randomized to the bilingual and monolingual modalities. Modalities provide virtually identical content on creating a family tree, using the family tree to identify inherited cancer risk factors, understanding how cancer predisposition can be inherited, and the role of genetic counseling and testing for prevention or treatment. 25 True/False items assessed knowledge; a Likert scale item assessed confidence. Data were collected within 2 weeks before and after viewing the information. Results Significant interaction of language modality, education, and change in knowledge scores was observed (p=.01). High education group increased knowledge regardless of modality (Bilingual: p<.001; d=.56; Monolingual: p<.001; d=1.08). Low education group increased knowledge with bilingual (p<.001; d=.85), but not monolingual (p=.79; d=.08) modality. Bilingual modality yielded greater confidence creating a family tree (p=.03). Conclusions Bilingual approach provides a better opportunity for lower educated Deaf ASL-users to access cancer genetics information than a monolingual approach. PMID:27594054

An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

ERIC Educational Resources Information Center

Strobl, Carolin; Malley, James; Tutz, Gerhard

2009-01-01

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…

Stability of the Markov operator and synchronization of Markovian random products

NASA Astrophysics Data System (ADS)

Díaz, Lorenzo J.; Matias, Edgar

2018-05-01

We study Markovian random products on a large class of ‘m-dimensional’ connected compact metric spaces (including products of closed intervals and trees). We introduce a splitting condition, generalizing the classical one by Dubins and Freedman, and prove that this condition implies the asymptotic stability of the corresponding Markov operator and (exponentially fast) synchronization.

Discerning environmental factors affecting current tree growth in Central Europe.

PubMed

Cienciala, Emil; Russ, Radek; Šantrůčková, Hana; Altman, Jan; Kopáček, Jiří; Hůnová, Iva; Štěpánek, Petr; Oulehle, Filip; Tumajer, Jan; Ståhl, Göran

2016-12-15

We examined the effect of individual environmental factors on the current spruce tree growth assessed from a repeated country-level statistical landscape (incl. forest) survey in the Czech Republic. An extensive set of variables related to tree size, competition, site characteristics including soil texture, chemistry, N deposition and climate was tested within a random-effect model to explain growth in the conditions of dominantly managed forest ecosystems. The current spruce basal area increment was assessed from two consecutive landscape surveys conducted in 2008/2009 and six years later in 2014/2015. Tree size, age and competition within forest stands were found to be the dominant explanatory variables, whereas the expression of site characteristics, environmental and climatic drives was weaker. The significant site variables affecting growth included soil C/N ratio and soil exchangeable acidity (pH KCl; positive response) reflecting soil chemistry, long-term N-deposition (averaged since 1975) in combination with soil texture (clay content) and Standardized Precipitation Index (SPI), a drought index expressing moisture conditions. Sensitivity of growth to N-deposition was positive, although weak. SPI was positively related to and significant in explaining tree growth when expressed for the growth season. Except SPI, no significant relation of growth was determined to altitude-related variables (temperature, growth season length). We identified the current spruce growth optimum at elevations about 800ma.s.l. or higher in the conditions of the country. This suggests that at lower elevations, limitation by a more pronounced water deficit dominates, whereas direct temperature limitation may concern the less frequent higher elevations. The mixed linear model of spruce tree growth explained 55 and 65% of the variability with fixed and random effects included, respectively, and provided new insights on the current spruce tree growth and factors affecting it within the environmental gradients of the country. Copyright © 2016 Elsevier B.V. All rights reserved.

Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation.

PubMed

Monserud, R A; Marshall, J D

2001-09-01

Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.

Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Climate-driven extinctions shape the phylogenetic structure of temperate tree floras.

PubMed

Eiserhardt, Wolf L; Borchsenius, Finn; Plum, Christoffer M; Ordonez, Alejandro; Svenning, Jens-Christian

2015-03-01

When taxa go extinct, unique evolutionary history is lost. If extinction is selective, and the intrinsic vulnerabilities of taxa show phylogenetic signal, more evolutionary history may be lost than expected under random extinction. Under what conditions this occurs is insufficiently known. We show that late Cenozoic climate change induced phylogenetically selective regional extinction of northern temperate trees because of phylogenetic signal in cold tolerance, leading to significantly and substantially larger than random losses of phylogenetic diversity (PD). The surviving floras in regions that experienced stronger extinction are phylogenetically more clustered, indicating that non-random losses of PD are of increasing concern with increasing extinction severity. Using simulations, we show that a simple threshold model of survival given a physiological trait with phylogenetic signal reproduces our findings. Our results send a strong warning that we may expect future assemblages to be phylogenetically and possibly functionally depauperate if anthropogenic climate change affects taxa similarly. © 2015 John Wiley & Sons Ltd/CNRS.

Effect of initial spacing on mechanical properties of lumber sawn from unthinned slash pine at age 40

Treesearch

Robert H. McAlister; Alexander Clark; Joseph R. Saucier

1997-01-01

The effect of initial planting density on strength and stiffness of slash pine (Pinus elliotti Engelm. var elliotti) from a 40-year-old plantation on the Georgia Coastal Plain was examined. A stratified random sample of trees with diameters at breast height ranging from 8 to 16 inches from replicated stands representing tree spacing of 6 by 8, 8 by 8, 10 by 10, and 15...

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

Stem Sinuosity, Tree Size, and Pest Injury of Machine-Planted Tress with and without Bent Taproots: A Comparison of Loblolly and Slash Pine

Treesearch

Jason A. Gatch; Timothy B. Harrington; Terry S. Price; M. Boyd Edwards

1999-01-01

Twenty-four maohine-planted stands each of slash (Pinus elliottii Engelm.) and loblolly pine (Pinus taeda L.) (between ages 3 to 10 years) were randomly selected in the Coastal Plain and Piedmont of Georgia, respectively. Ten points per site were located along a transect and two planted trees within a 10-m radius of each point were...

Assessing the Potential of Land Use Modification to Mitigate Ambient NO2 and Its Consequences for Respiratory Health

PubMed Central

Rao, Meenakshi; George, Linda A.; Shandas, Vivek; Rosenstiel, Todd N.

2017-01-01

Understanding how local land use and land cover (LULC) shapes intra-urban concentrations of atmospheric pollutants—and thus human health—is a key component in designing healthier cities. Here, NO2 is modeled based on spatially dense summer and winter NO2 observations in Portland-Hillsboro-Vancouver (USA), and the spatial variation of NO2 with LULC investigated using random forest, an ensemble data learning technique. The NO2 random forest model, together with BenMAP, is further used to develop a better understanding of the relationship among LULC, ambient NO2 and respiratory health. The impact of land use modifications on ambient NO2, and consequently on respiratory health, is also investigated using a sensitivity analysis. We find that NO2 associated with roadways and tree-canopied areas may be affecting annual incidence rates of asthma exacerbation in 4–12 year olds by +3000 per 100,000 and −1400 per 100,000, respectively. Our model shows that increasing local tree canopy by 5% may reduce local incidences rates of asthma exacerbation by 6%, indicating that targeted local tree-planting efforts may have a substantial impact on reducing city-wide incidence of respiratory distress. Our findings demonstrate the utility of random forest modeling in evaluating LULC modifications for enhanced respiratory health. PMID:28698523

Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789

Urban forest management in New England: Towards a contemporary understanding of tree wardens in Massachusetts communities

USGS Publications Warehouse

Harper, Richard W.; Bloniarz, David V.; DeStefano, Stephen; Nicolson, Craig

2017-01-01

In the New England states, tree wardens are local officials responsible for the preservation, maintenance and stewardship of municipal public trees. This study explores the emerging professional challenges, duties and responsibilities of tree wardens, from the subject’s point of view, by conducting in-person, semi-structured qualitative research interviews with 50 tree wardens throughout Massachusetts. Many of the findings corroborate previous literature, including that tree wardens are typically housed in a municipal department (often public works or highway), that tree wardens routinely interact with a wide variety of local organisations (representatives from other municipal departments, community volunteer associations) and that as community size increases, tree wardens typically have access to a greater pool of resources to carry out urban forest management. A newer finding is that the subject of urban forest health arose as a topic of great importance for tree wardens, as nearly all interviewees (n = 49) indicated that they monitor for urban forest pests and that they would like further continuing education concerning this subject.

Wind-Induced Reconfigurations in Flexible Branched Trees

NASA Astrophysics Data System (ADS)

Ojo, Oluwafemi; Shoele, Kourosh

2017-11-01

Wind induced stresses are the major mechanical cause of failure in trees. We know that the branching mechanism has an important effect on the stress distribution and stability of a tree in the wind. Eloy in PRL 2011, showed that Leonardo da Vinci's original observation which states the total cross section of branches is conserved across branching nodes is the best configuration for resisting wind-induced fracture in rigid trees. However, prediction of the fracture risk and pattern of a tree is also a function of their reconfiguration capabilities and how they mitigate large wind-induced stresses. In this studies through developing an efficient numerical simulation of flexible branched trees, we explore the role of the tree flexibility on the optimal branching. Our results show that the probability of a tree breaking at any point depends on both the cross-section changes in the branching nodes and the level of tree flexibility. It is found that the branching mechanism based on Leonardo da Vinci's original observation leads to a uniform stress distribution over a wide range of flexibilities but the pattern changes for more flexible systems.

Ensemble Feature Learning of Genomic Data Using Support Vector Machine

PubMed Central

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R.; Braytee, Ali; Kennedy, Paul J.

2016-01-01

The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the process of gene selection and classification. Testament to that is random forest which combines random decision trees with bagging to improve overall feature selection and classification accuracy. Surprisingly, the adoption of these methods in support vector machines has only recently received attention but mostly on classification not gene selection. This paper introduces an ensemble SVM-Recursive Feature Elimination (ESVM-RFE) for gene selection that follows the concepts of ensemble and bagging used in random forest but adopts the backward elimination strategy which is the rationale of RFE algorithm. The rationale behind this is, building ensemble SVM models using randomly drawn bootstrap samples from the training set, will produce different feature rankings which will be subsequently aggregated as one feature ranking. As a result, the decision for elimination of features is based upon the ranking of multiple SVM models instead of choosing one particular model. Moreover, this approach will address the problem of imbalanced datasets by constructing a nearly balanced bootstrap sample. Our experiments show that ESVM-RFE for gene selection substantially increased the classification performance on five microarray datasets compared to state-of-the-art methods. Experiments on the childhood leukaemia dataset show that an average 9% better accuracy is achieved by ESVM-RFE over SVM-RFE, and 5% over random forest based approach. The selected genes by the ESVM-RFE algorithm were further explored with Singular Value Decomposition (SVD) which reveals significant clusters with the selected data. PMID:27304923

A tree island approach to inferring phylogeny in the ant subfamily Formicinae, with especial reference to the evolution of weaving.

PubMed

Johnson, Rebecca N; Agapow, Paul-Michael; Crozier, Ross H

2003-11-01

The ant subfamily Formicinae is a large assemblage (2458 species (J. Nat. Hist. 29 (1995) 1037), including species that weave leaf nests together with larval silk and in which the metapleural gland-the ancestrally defining ant character-has been secondarily lost. We used sequences from two mitochondrial genes (cytochrome b and cytochrome oxidase 2) from 18 formicine and 4 outgroup taxa to derive a robust phylogeny, employing a search for tree islands using 10000 randomly constructed trees as starting points and deriving a maximum likelihood consensus tree from the ML tree and those not significantly different from it. Non-parametric bootstrapping showed that the ML consensus tree fit the data significantly better than three scenarios based on morphology, with that of Bolton (Identification Guide to the Ant Genera of the World, Harvard University Press, Cambridge, MA) being the best among these alternative trees. Trait mapping showed that weaving had arisen at least four times and possibly been lost once. A maximum likelihood analysis showed that loss of the metapleural gland is significantly associated with the weaver life-pattern. The graph of the frequencies with which trees were discovered versus their likelihood indicates that trees with high likelihoods have much larger basins of attraction than those with lower likelihoods. While this result indicates that single searches are more likely to find high- than low-likelihood tree islands, it also indicates that searching only for the single best tree may lose important information.

Decision trees in epidemiological research.

PubMed

Venkatasubramaniam, Ashwini; Wolfson, Julian; Mitchell, Nathan; Barnes, Timothy; JaKa, Meghan; French, Simone

2017-01-01

In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

Backward Channel Protection Based on Randomized Tree-Walking Algorithm and Its Analysis for Securing RFID Tag Information and Privacy

NASA Astrophysics Data System (ADS)

Choi, Wonjoon; Yoon, Myungchul; Roh, Byeong-Hee

Eavesdropping on backward channels in RFID environments may cause severe privacy problems because it means the exposure of personal information related to tags that each person has. However, most existing RFID tag security schemes are focused on the forward channel protections. In this paper, we propose a simple but effective method to solve the backward channel eavesdropping problem based on Randomized-tree walking algorithm for securing tag ID information and privacy in RFID-based applications. In order to show the efficiency of the proposed scheme, we derive two performance models for the cases when CRC is used and not used. It is shown that the proposed method can lower the probability of eavesdropping on backward channels near to ‘0.’

Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

PubMed

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J

2015-12-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. (c) 2015 APA, all rights reserved).

Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations

PubMed Central

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J.

2016-01-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. PMID:26389526

Exploration on Construction of Hospital "Talent Tree" Project.

PubMed

Yi, Lihua; Wei, Lei; Hao, Aimin; Hu, Minmin; Xu, Xinzhou

2015-05-01

Talent is the core competitive force of a hospital's development. Wuxi No. 2 People's Hospital followed the characteristics that medical talents mature slowly and their growth requires a long period. The innovated "talent tree" project, trained classified talents corresponding to "base-trunk-crown" of a tree, formed an individualized professional training plan with different levels and at different periods. We carried out a relay of the "talent tree" to bring their initiative into play. In practice, we gradually found this as a unique way of the talent construction, which conforms to our hospital's condition. This guarantees sustained development and innovative force of the hospital.

Exploring the Complexity of Tree Thinking Expertise in an Undergraduate Systematics Course

ERIC Educational Resources Information Center

Halverson, Kristy L.; Pires, Chris J.; Abell, Sandra K.

2011-01-01

Student understanding of biological representations has not been well studied. Yet, we know that to be efficient problem solvers in evolutionary biology and systematics, college students must develop expertise in thinking with a particular type of representation, phylogenetic trees. The purpose of this study was to understand how undergraduates…

A comparison of chronologies from tree rings

Treesearch

Kurt H. Riitters

1990-01-01

Forty-five-year ring width index chronologies were estimated by five mean-value functions applied to 183 ring width series from four similar sites. The effects of autocorrelation on the comparisons among mean-value functions were explored by fitting box-Jenkins models to individual-tree index services prior to pooling (prewhitening), and to the pooled chronologies...

Canopy disturbance and tree recruitment over two centuries in a managed longleaf pine landscape

Treesearch

Neil Pederson; J. Morgan Varner; Brian J. Palik

2008-01-01

Disturbance history was reconstructed across an 11300 ha managed longleaf pine (Pinus palustris Mill.) landscape in southwestern Georgia, USA. Our specific objectives were to: (i) determine forest age structure; (ii) reconstruct disturbance history through the relationship between canopy disturbance, tree recruitment and growth; and (iii) explore the...

House-Tree-Person Drawings and Sex Offenders: A Pilot Study.

ERIC Educational Resources Information Center

Lopez, Jennifer R.; Carolan, Richard

2001-01-01

Investigates whether or not specific indicators appear more frequently in the House-Tree-Person drawings of sex offenders when compared to drawings of a control group. The goal of the research is to explore the use of an art-based assessment as a tool for the early identification of sex offenders. (BF)

Dominant forest tree mycorrhizal type mediates understory plant invasions

Treesearch

Insu Jo; Kevin M. Potter; Grant M. Domke; Songlin Fei

2018-01-01

Forest mycorrhizal type mediates nutrient dynamics, which in turn can influence forest community structure and processes. Using forest inventory data, we explored how dominant forest tree myc- orrhizal type affects understory plant invasions with consideration of forest structure and soil properties. We found that arbuscular mycorrhizal (AM) dominant forests, which are...

Osage orange (Maclura pomifera L) seed oil poly-(-a-hydroxy dibutylamine) triglycerides: Synthesis and characterization

USDA-ARS?s Scientific Manuscript database

In exploring alternative vegetable oils for non-food industrial applications, especially in temperate climates, tree seed oils that are not commonly seen as competitors to soybean, peanut, and corn oils can become valuable sources of new oils. Many trees produce edible fruits and seeds while others ...

Hierarchical spatial models for predicting tree species assemblages across large domains

Treesearch

Andrew O. Finley; Sudipto Banerjee; Ronald E. McRoberts

2009-01-01

Spatially explicit data layers of tree species assemblages, referred to as forest types or forest type groups, are a key component in large-scale assessments of forest sustainability, biodiversity, timber biomass, carbon sinks and forest health monitoring. This paper explores the utility of coupling georeferenced national forest inventory (NFI) data with readily...

DNA typing of birch: Development of a forensic STR system for Betula pendula and Betula pubescens.

PubMed

Wesselink, Monique; Dragutinović, Aleksandar; Noordhoek, Jeroen W; Bergwerff, Leonie; Kuiper, Irene

2018-04-07

Although botanical trace evidence is often encountered in case investigations, the utilization of such traces in forensic investigations is still limited. Development of a forensic STR system for the two species of Betula (birch) indigenous to and abundant in North West Europe is a step in enhancing the applicability of traces from these species. We describe six microsatellite markers developed for birch species in detail, including repeat structure, and we propose a nomenclature for the encountered alleles. To assess the population characteristics, the genetic composition of wild, planted and intermediate populations of Betula pendula (a diploid species) and Betula pubescens (a tetraploid species) were investigated. The genetic differences between these two species were larger than the differences between populations of one species, even when both species co-occurred at one location. Therefore allele frequencies were estimated for both species separately. General, conservative random match probabilities were estimated for wild trees based on these allele frequencies (5∙10 -6 for the diploid B. pendula and 1∙10 -13 for the tetraploid B. pubescens), illustrating the potential relevance if trace evidence secured from a suspect is found to match a birch tree growing on or near a crime scene. Apart from wild trees, planted Betula trees also occur that may not originate from seeds, but may have been propagated through cloning. Based on the studied Betula trees, the random match probability of a potentially planted profile might be as high as 1.4∙10 -2 . Copyright © 2018 Elsevier B.V. All rights reserved.

Compass cues used by a nocturnal bull ant, Myrmecia midas.

PubMed

Freas, Cody A; Narendra, Ajay; Cheng, Ken

2017-05-01

Ants use both terrestrial landmarks and celestial cues to navigate to and from their nest location. These cues persist even as light levels drop during the twilight/night. Here, we determined the compass cues used by a nocturnal bull ant, Myrmecia midas , in which the majority of individuals begin foraging during the evening twilight period. Myrmecia midas foragers with vectors of ≤5   m when displaced to unfamiliar locations did not follow the home vector, but instead showed random heading directions. Foragers with larger home vectors (≥10   m) oriented towards the fictive nest, indicating a possible increase in cue strength with vector length. When the ants were displaced locally to create a conflict between the home direction indicated by the path integrator and terrestrial landmarks, foragers oriented using landmark information exclusively and ignored any accumulated home vector regardless of vector length. When the visual landmarks at the local displacement site were blocked, foragers were unable to orient to the nest direction and their heading directions were randomly distributed. Myrmecia midas ants typically nest at the base of the tree and some individuals forage on the same tree. Foragers collected on the nest tree during evening twilight were unable to orient towards the nest after small lateral displacements away from the nest. This suggests the possibility of high tree fidelity and an inability to extrapolate landmark compass cues from information collected on the tree and at the nest site to close displacement sites. © 2017. Published by The Company of Biologists Ltd.

Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project.

PubMed

Alghamdi, Manal; Al-Mallah, Mouaz; Keteyian, Steven; Brawner, Clinton; Ehrman, Jonathan; Sakr, Sherif

2017-01-01

Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE). The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree) and achieved high accuracy of prediction (AUC = 0.92). The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data.

The effect of an information and communication technology (ICT) on older adults' quality of life: study protocol for a randomized control trial.

PubMed

Gustafson, David H; McTavish, Fiona; Gustafson, David H; Mahoney, Jane E; Johnson, Roberta A; Lee, John D; Quanbeck, Andrew; Atwood, Amy K; Isham, Andrew; Veeramani, Raj; Clemson, Lindy; Shah, Dhavan

2015-04-25

This study investigates the use of an information and communication technology (Elder Tree) designed for older adults and their informal caregivers to improve older adult quality of life and address challenges older adults face in maintaining their independence (for example, loneliness and isolation, falling, managing medications, driving and transportation). This study, an unblinded randomized controlled trial, will evaluate the effectiveness and cost of Elder Tree. Older adults who are at risk for losing their independence - along with their informal caregivers, if they name them - are randomized to two groups. The intervention group has access to their usual sources of information and communication as well as to Elder Tree for 18 months while the control group uses only their usual sources of information and communication. The primary outcome of the study is older adult quality of life. Secondary outcomes are cost per Quality-Adjusted Life Year and the impact of the technology on independence, loneliness, falls, medication management, driving and transportation, and caregiver appraisal and mastery. We will also examine the mediating effect of self-determination theory. We will evaluate the effectiveness of Elder Tree by comparing intervention- and control-group participants at baseline and months 6, 12, and 18. We will use mixed-effect models to evaluate the primary and secondary outcomes, where pretest score functions as a covariate, treatment condition is a between-subjects factor, and the multivariate outcome reflects scores for a given assessment at the three time points. Separate analyses will be conducted for each outcome. Cost per Quality-Adjusted Life Year will be compared between the intervention and control groups. Additional analyses will examine the mediating effect of self-determination theory on each outcome. Elder Tree is a multifaceted intervention, making it a challenge to assess which services or combinations of services account for outcomes in which subsets of older adults. If Elder Tree can improve quality of life and reduce healthcare costs among older adults, it could suggest a promising way to ease the burden that advancing age can place on older adults, their families, and the healthcare system. ClinicalTrials.gov NCT02128789 . Registered on 26 March 2014.

The origin and functional transition of P34.

PubMed

Li, Q-G; Zhang, Y-M

2013-03-01

P34, a storage protein and major soybean allergen, has undergone a functional transition from a cysteine peptidase to a syringolide receptor. An exploration of the evolutionary mechanism of this functional transition is made. To identify homologous genes of P34, syntenic network was constructed using syntenic relationships from the Plant Genome Duplication Database. The collected homologous genes, along with SPE31, a highly homologous protein to P34 from the seeds of Pachyrhizus erosus, were used to construct a phylogenetic tree. The results show that multiple gene duplications, exon shuffling and following granulin domain loss and some critical point mutations are associated with the functional transition. Although some tests suggested the existence of positive selection, the possibility that random fixation under relaxation of purifying selection results in the functional transition is also supported. In addition, the genes Glyma08g12340 and Medtr8g086470 may belong to a new group within the papain family.

The origin and functional transition of P34

PubMed Central

Li, Q-G; Zhang, Y-M

2013-01-01

P34, a storage protein and major soybean allergen, has undergone a functional transition from a cysteine peptidase to a syringolide receptor. An exploration of the evolutionary mechanism of this functional transition is made. To identify homologous genes of P34, syntenic network was constructed using syntenic relationships from the Plant Genome Duplication Database. The collected homologous genes, along with SPE31, a highly homologous protein to P34 from the seeds of Pachyrhizus erosus, were used to construct a phylogenetic tree. The results show that multiple gene duplications, exon shuffling and following granulin domain loss and some critical point mutations are associated with the functional transition. Although some tests suggested the existence of positive selection, the possibility that random fixation under relaxation of purifying selection results in the functional transition is also supported. In addition, the genes Glyma08g12340 and Medtr8g086470 may belong to a new group within the papain family. PMID:23211789

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.

PubMed

Schmid, Matthias; Küchenhoff, Helmut; Hoerauf, Achim; Tutz, Gerhard

2016-02-28

Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Selective randomized load balancing and mesh networks with changing demands

NASA Astrophysics Data System (ADS)

Shepherd, F. B.; Winzer, P. J.

2006-05-01

We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

Eigenvalues of normalized Laplacian matrices of fractal trees and dendrimers: Analytical results and applications

NASA Astrophysics Data System (ADS)

Julaiti, Alafate; Wu, Bin; Zhang, Zhongzhi

2013-05-01

The eigenvalues of the normalized Laplacian matrix of a network play an important role in its structural and dynamical aspects associated with the network. In this paper, we study the spectra and their applications of normalized Laplacian matrices of a family of fractal trees and dendrimers modeled by Cayley trees, both of which are built in an iterative way. For the fractal trees, we apply the spectral decimation approach to determine analytically all the eigenvalues and their corresponding multiplicities, with the eigenvalues provided by a recursive relation governing the eigenvalues of networks at two successive generations. For Cayley trees, we show that all their eigenvalues can be obtained by computing the roots of several small-degree polynomials defined recursively. By using the relation between normalized Laplacian spectra and eigentime identity, we derive the explicit solution to the eigentime identity for random walks on the two treelike networks, the leading scalings of which follow quite different behaviors. In addition, we corroborate the obtained eigenvalues and their degeneracies through the link between them and the number of spanning trees.

Reinforcement Learning Trees

PubMed Central

Zhu, Ruoqing; Zeng, Donglin; Kosorok, Michael R.

2015-01-01

In this paper, we introduce a new type of tree-based method, reinforcement learning trees (RLT), which exhibits significantly improved performance over traditional methods such as random forests (Breiman, 2001) under high-dimensional settings. The innovations are three-fold. First, the new method implements reinforcement learning at each selection of a splitting variable during the tree construction processes. By splitting on the variable that brings the greatest future improvement in later splits, rather than choosing the one with largest marginal effect from the immediate split, the constructed tree utilizes the available samples in a more efficient way. Moreover, such an approach enables linear combination cuts at little extra computational cost. Second, we propose a variable muting procedure that progressively eliminates noise variables during the construction of each individual tree. The muting procedure also takes advantage of reinforcement learning and prevents noise variables from being considered in the search for splitting rules, so that towards terminal nodes, where the sample size is small, the splitting rules are still constructed from only strong variables. Last, we investigate asymptotic properties of the proposed method under basic assumptions and discuss rationale in general settings. PMID:26903687

Habitat preferences of Boros schneideri (Coleoptera: Boridae) in the natural tree stands of the Białowieża Forest.

PubMed

Gutowski, Jerzy M; Sućko, Krzysztof; Zub, Karol; Bohdan, Adam

2014-01-01

We analyzed habitat requirements of Boros schneideri (Panzer, 1796) (Coleoptera: Boridae) in the natural forests of the continental biogeographical region, using data collected in the Białowieża Forest. This species has been found on the six host trees, but it preferred dead, standing pine trees, characterized by large diameter, moderately moist and moist phloem but avoided trees in sunny locations. It occurred mostly in mesic and wet coniferous forests. This species demonstrated preferences for old tree stands (over 140-yr old), and its occurrence in younger tree-stand age classes (minimum 31-40-yr old) was not significantly different from random distribution. B. schneideri occupied more frequently locations distant from the forest edge, which were less affected by logging. Considering habitat requirements, character of occurrence, and decreasing number of occupied locations in the whole range of distribution, this species can be treated as relict of primeval forests. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

Utilization of humus-rich forest soil (mull) in geochemical exploration for gold

USGS Publications Warehouse

Curtin, Gary C.; Lakin, H.W.; Neuerburg, G.J.; Hubert, A.E.

1968-01-01

Distribution of gold in humus-rich forest soil (mull) reflects the known distribution of gold deposits in bedrock in the Empire district, Colorado. Gold from the bedrock is accumulated by pine and aspen trees and is concentrated in the mull by the decay of organic litter from the trees. Anomalies in mull which do not coincide with known gold deposits merit further exploration. The gold anomalies in soil (6- to 12-inch depth) and in float pebbles and cobbles poorly reflect the known distribution of gold deposits in bedrock beneath the extensive cover of colluvium and glacial drift.

Tree cover in Central Africa: determinants and sensitivity under contrasted scenarios of global change

PubMed Central

Aleman, Julie C.; Blarquez, Olivier; Gourlet-Fleury, Sylvie; Bremond, Laurent; Favier, Charly

2017-01-01

Tree cover is a key variable for ecosystem functioning, and is widely used to study tropical ecosystems. But its determinants and their relative importance are still a matter of debate, especially because most regional and global analyses have not considered the influence of agricultural practices. More information is urgently needed regarding how human practices influence vegetation structure. Here we focused in Central Africa, a region still subjected to traditional agricultural practices with a clear vegetation gradient. Using remote sensing data and global databases, we calibrated a Random Forest model to correlatively link tree cover with climatic, edaphic, fire and agricultural practices data. We showed that annual rainfall and accumulated water deficit were the main drivers of the distribution of tree cover and vegetation classes (defined by the modes of tree cover density), but agricultural practices, especially pastoralism, were also important in determining tree cover. We simulated future tree cover with our model using different scenarios of climate and land-use (agriculture and population) changes. Our simulations suggest that tree cover may respond differently regarding the type of scenarios, but land-use change was an important driver of vegetation change even able to counterbalance the effect of climate change in Central Africa. PMID:28134259

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

NASA Technical Reports Server (NTRS)

Fagan, Matthew E.; Defries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.

2015-01-01

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

An analytical model of stand dynamics as a function of tree growth, mortality and recruitment: the shade tolerance-stand structure hypothesis revisited.

PubMed

Zavala, Miguel A; Angulo, Oscar; Bravo de la Parra, Rafael; López-Marcos, Juan C

2007-02-07

Light competition and interspecific differences in shade tolerance are considered key determinants of forest stand structure and dynamics. Specifically two main stand diameter distribution types as a function of shade tolerance have been proposed based on empirical observations. All-aged stands of shade tolerant species tend to have steeply descending, monotonic diameter distributions (inverse J-shaped curves). Shade intolerant species in contrast typically exhibit normal (unimodal) tree diameter distributions due to high mortality rates of smaller suppressed trees. In this study we explore the generality of this hypothesis which implies a causal relationship between light competition or shade tolerance and stand structure. For this purpose we formulate a partial differential equation system of stand dynamics as a function of individual tree growth, recruitment and mortality which allows us to explore possible individual-based mechanisms--e.g. light competition-underlying observed patterns of stand structure--e.g. unimodal or inverse J-shaped equilibrium diameter curves. We find that contrary to expectations interspecific differences in growth patterns can result alone in any of the two diameter distributions types observed in the field. In particular, slow growing species can present unimodal equilibrium curves even in the absence of light competition. Moreover, light competition and shade intolerance evaluated both at the tree growth and mortality stages did not have a significant impact on stand structure that tended to converge systematically towards an inverse J-shaped curves for most tree growth scenarios. Realistic transient stand dynamics for even aged stands of shade intolerant species (unimodal curves) were only obtained when recruitment was completely suppressed, providing further evidence on the critical role played by juvenile stages of tree development (e.g. the sampling stage) on final forest structure and composition. The results also point out the relevance of partial differential equations systems as a tool for exploring the individual-level mechanisms underpinning forest structure, particularly in relation to more complex forest simulation models that are more difficult to analyze and to interpret from a biological point of view.

Birth-death models and coalescent point processes: the shape and probability of reconstructed phylogenies.

PubMed

Lambert, Amaury; Stadler, Tanja

2013-12-01

Forward-in-time models of diversification (i.e., speciation and extinction) produce phylogenetic trees that grow "vertically" as time goes by. Pruning the extinct lineages out of such trees leads to natural models for reconstructed trees (i.e., phylogenies of extant species). Alternatively, reconstructed trees can be modelled by coalescent point processes (CPPs), where trees grow "horizontally" by the sequential addition of vertical edges. Each new edge starts at some random speciation time and ends at the present time; speciation times are drawn from the same distribution independently. CPPs lead to extremely fast computation of tree likelihoods and simulation of reconstructed trees. Their topology always follows the uniform distribution on ranked tree shapes (URT). We characterize which forward-in-time models lead to URT reconstructed trees and among these, which lead to CPP reconstructed trees. We show that for any "asymmetric" diversification model in which speciation rates only depend on time and extinction rates only depend on time and on a non-heritable trait (e.g., age), the reconstructed tree is CPP, even if extant species are incompletely sampled. If rates additionally depend on the number of species, the reconstructed tree is (only) URT (but not CPP). We characterize the common distribution of speciation times in the CPP description, and discuss incomplete species sampling as well as three special model cases in detail: (1) the extinction rate does not depend on a trait; (2) rates do not depend on time; (3) mass extinctions may happen additionally at certain points in the past. Copyright © 2013 Elsevier Inc. All rights reserved.

Pacific island landbird monitoring annual report, National Park of American Samoa, Ta‘u and Tutuila units, 2011

USGS Publications Warehouse

Judge, Seth W.; Camp, Richard J.; Vaivai, Visa; Hart, Patrick J.

2013-01-01

NPSA canopy and understory composition was predominantly native, and trees formed a dense closed canopy at nearly 90% of the stations sampled. More than half of the tree heights in both units were taller than 5 m and the majority of slopes were steeper than 20 degrees. There were no clear dominant tree species in the mixed native forests. The most common tree species documented included Syzygium spp., Dysoxylum spp., Ficus spp., Hibiscus tiliaceus and Rhus taitensis (among others). There were significant differences in the distribution of bird densities between legacy and random transects. Determining differences in detection probabilities cannot be definitively assessed from a single survey. We recommend both panels be sampled in the future until bias in density and abundance can be evaluated, or if sampling may be reduced.

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.

SNP selection and classification of genome-wide SNP data using stratified sampling random forests.

PubMed

Wu, Qingyao; Ye, Yunming; Liu, Yang; Ng, Michael K

2012-09-01

For high dimensional genome-wide association (GWA) case-control data of complex disease, there are usually a large portion of single-nucleotide polymorphisms (SNPs) that are irrelevant with the disease. A simple random sampling method in random forest using default mtry parameter to choose feature subspace, will select too many subspaces without informative SNPs. Exhaustive searching an optimal mtry is often required in order to include useful and relevant SNPs and get rid of vast of non-informative SNPs. However, it is too time-consuming and not favorable in GWA for high-dimensional data. The main aim of this paper is to propose a stratified sampling method for feature subspace selection to generate decision trees in a random forest for GWA high-dimensional data. Our idea is to design an equal-width discretization scheme for informativeness to divide SNPs into multiple groups. In feature subspace selection, we randomly select the same number of SNPs from each group and combine them to form a subspace to generate a decision tree. The advantage of this stratified sampling procedure can make sure each subspace contains enough useful SNPs, but can avoid a very high computational cost of exhaustive search of an optimal mtry, and maintain the randomness of a random forest. We employ two genome-wide SNP data sets (Parkinson case-control data comprised of 408 803 SNPs and Alzheimer case-control data comprised of 380 157 SNPs) to demonstrate that the proposed stratified sampling method is effective, and it can generate better random forest with higher accuracy and lower error bound than those by Breiman's random forest generation method. For Parkinson data, we also show some interesting genes identified by the method, which may be associated with neurological disorders for further biological investigations.

Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics.

PubMed

Vaniya, Arpana; Fiehn, Oliver

2015-06-01

Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations.

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

PubMed

Nishio, Mizuho; Nishizawa, Mitsuo; Sugiyama, Osamu; Kojima, Ryosuke; Yakami, Masahiro; Kuroda, Tomohiro; Togashi, Kaori

2018-01-01

We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx system (hand-crafted imaging feature + machine learning algorithm), (ii) comparison between support vector machine (SVM) and gradient tree boosting (XGBoost) as machine learning algorithms, and (iii) effectiveness of parameter optimization using Bayesian optimization and random search. Data on 99 lung nodules (62 lung cancers and 37 benign lung nodules) were included from public databases of CT images. A variant of the local binary pattern was used for calculating a feature vector. SVM or XGBoost was trained using the feature vector and its corresponding label. Tree Parzen Estimator (TPE) was used as Bayesian optimization for parameters of SVM and XGBoost. Random search was done for comparison with TPE. Leave-one-out cross-validation was used for optimizing and evaluating the performance of our CADx system. Performance was evaluated using area under the curve (AUC) of receiver operating characteristic analysis. AUC was calculated 10 times, and its average was obtained. The best averaged AUC of SVM and XGBoost was 0.850 and 0.896, respectively; both were obtained using TPE. XGBoost was generally superior to SVM. Optimal parameters for achieving high AUC were obtained with fewer numbers of trials when using TPE, compared with random search. Bayesian optimization of SVM and XGBoost parameters was more efficient than random search. Based on observer study, AUC values of two board-certified radiologists were 0.898 and 0.822. The results show that diagnostic accuracy of our CADx system was comparable to that of radiologists with respect to classifying lung nodules.

Using convolutional neural networks to explore the microbiome.

PubMed

Reiman, Derek; Metwally, Ahmed; Yang Dai

2017-07-01

The microbiome has been shown to have an impact on the development of various diseases in the host. Being able to make an accurate prediction of the phenotype of a genomic sample based on its microbial taxonomic abundance profile is an important problem for personalized medicine. In this paper, we examine the potential of using a deep learning framework, a convolutional neural network (CNN), for such a prediction. To facilitate the CNN learning, we explore the structure of abundance profiles by creating the phylogenetic tree and by designing a scheme to embed the tree to a matrix that retains the spatial relationship of nodes in the tree and their quantitative characteristics. The proposed CNN framework is highly accurate, achieving a 99.47% of accuracy based on the evaluation on a dataset 1967 samples of three phenotypes. Our result demonstrated the feasibility and promising aspect of CNN in the classification of sample phenotype.

Recognition memory in tree shrew (Tupaia belangeri) after repeated familiarization sessions.

PubMed

Khani, Abbas; Rainer, Gregor

2012-07-01

Recognition memories are formed during perceptual experience and allow subsequent recognition of previously encountered objects as well as their distinction from novel objects. As a consequence, novel objects are generally explored longer than familiar objects by many species. This novelty preference has been documented in rodents using the novel object recognition (NOR) test, as well is in primates including humans using preferential looking time paradigms. Here, we examine novelty preference using the NOR task in tree shrew, a small animal species that is considered to be an intermediary between rodents and primates. Our paradigm consisted of three phases: arena familiarization, object familiarization sessions with two identical objects in the arena and finally a test session following a 24-h retention period with a familiar and a novel object in the arena. We employed two different object familiarization durations: one and three sessions on consecutive days. After three object familiarization sessions, tree shrews exhibited robust preference for novel objects on the test day. This was accompanied by significant reduction in familiar object exploration time, occurring largely between the first and second day of object familiarization. By contrast, tree shrews did not show a significant preference for the novel object after a one-session object familiarization. Nonetheless, they spent significantly less time exploring the familiar object on the test day compared to the object familiarization day, indicating that they did maintain a memory trace for the familiar object. Our study revealed different time courses for familiar object habituation and emergence of novelty preference, suggesting that novelty preference is dependent on well-consolidated memory of the competing familiar object. Taken together, our results demonstrate robust novelty preference of tree shrews, in general similarity to previous findings in rodents and primates. Copyright © 2012 Elsevier B.V. All rights reserved.

Terpenoid Variations within and among Half-Sibling Avocado Trees, Persea americana Mill. (Lauraceae)

PubMed Central

Niogret, Jerome; Epsky, Nancy D.; Schnell, Raymond J.; Boza, Edward J.; Kendra, Paul E.; Heath, Robert R.

2013-01-01

Chemical analyses were conducted to determine the qualitative and quantitative differences in monoterpenes and sesquiterpenes in plant material from avocado trees, Persea americana Mill. (Lauraceae). The initial study analyzed plant material sampled from the trunk to the leaves through different branch diameters to quantify proximo-distal spatial differences within a tree. All trees were seedlings initiated from a single maternal tree. Two-way analysis of variance was conducted on 34 chemicals that comprised at least 3% of the total chemical content of at least one tree and/or location within a tree. There were significant interactions between genotype and location sampled for most chemicals. Parentage analysis using microsatellite molecular markers (SSR's) determined that the four trees had three fathers and that they represented two full-siblings and two half-sibling trees. Descriptive discriminant analysis found that both genotype and location within a tree could be separated based on chemical content, and that the chemical content from full-siblings tended to be more similar than chemical content from half-siblings. To further explore the relationship between genetic background and chemical content, samples were analyzed from leaf material from 20 trees that included two sets of full-sibling seedling trees, the maternal tree and the surviving paternal tree. Descriptive discriminant analysis found good separation between the two full-sibling groups, and that the separation was associated with chemistry of the parental trees. Six groups of chemicals were identified that explained the variation among the trees. We discuss the results in relation to the discrimination process used by wood-boring insects for site-selection on host trees, for tree selection among potential host trees, and the potential use of terpenoid chemical content in chemotaxonomy of avocado trees. PMID:24039994

Terpenoid variations within and among half-sibling avocado trees, Persea americana Mill. (Lauraceae).

PubMed

Niogret, Jerome; Epsky, Nancy D; Schnell, Raymond J; Boza, Edward J; Kendra, Paul E; Heath, Robert R

2013-01-01

Chemical analyses were conducted to determine the qualitative and quantitative differences in monoterpenes and sesquiterpenes in plant material from avocado trees, Persea americana Mill. (Lauraceae). The initial study analyzed plant material sampled from the trunk to the leaves through different branch diameters to quantify proximo-distal spatial differences within a tree. All trees were seedlings initiated from a single maternal tree. Two-way analysis of variance was conducted on 34 chemicals that comprised at least 3% of the total chemical content of at least one tree and/or location within a tree. There were significant interactions between genotype and location sampled for most chemicals. Parentage analysis using microsatellite molecular markers (SSR's) determined that the four trees had three fathers and that they represented two full-siblings and two half-sibling trees. Descriptive discriminant analysis found that both genotype and location within a tree could be separated based on chemical content, and that the chemical content from full-siblings tended to be more similar than chemical content from half-siblings. To further explore the relationship between genetic background and chemical content, samples were analyzed from leaf material from 20 trees that included two sets of full-sibling seedling trees, the maternal tree and the surviving paternal tree. Descriptive discriminant analysis found good separation between the two full-sibling groups, and that the separation was associated with chemistry of the parental trees. Six groups of chemicals were identified that explained the variation among the trees. We discuss the results in relation to the discrimination process used by wood-boring insects for site-selection on host trees, for tree selection among potential host trees, and the potential use of terpenoid chemical content in chemotaxonomy of avocado trees.

Observations and analysis of self-similar branching topology in glacier networks

USGS Publications Warehouse

Bahr, D.B.; Peckham, S.D.

1996-01-01

Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

PubMed

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

Soil phosphorus heterogeneity promotes tree species diversity and phylogenetic clustering in a tropical seasonal rainforest.

PubMed

Xu, Wumei; Ci, Xiuqin; Song, Caiyun; He, Tianhua; Zhang, Wenfu; Li, Qiaoming; Li, Jie

2016-12-01

The niche theory predicts that environmental heterogeneity and species diversity are positively correlated in tropical forests, whereas the neutral theory suggests that stochastic processes are more important in determining species diversity. This study sought to investigate the effects of soil nutrient (nitrogen and phosphorus) heterogeneity on tree species diversity in the Xishuangbanna tropical seasonal rainforest in southwestern China. Thirty-nine plots of 400 m 2 (20 × 20 m) were randomly located in the Xishuangbanna tropical seasonal rainforest. Within each plot, soil nutrient (nitrogen and phosphorus) availability and heterogeneity, tree species diversity, and community phylogenetic structure were measured. Soil phosphorus heterogeneity and tree species diversity in each plot were positively correlated, while phosphorus availability and tree species diversity were not. The trees in plots with low soil phosphorus heterogeneity were phylogenetically overdispersed, while the phylogenetic structure of trees within the plots became clustered as heterogeneity increased. Neither nitrogen availability nor its heterogeneity was correlated to tree species diversity or the phylogenetic structure of trees within the plots. The interspecific competition in the forest plots with low soil phosphorus heterogeneity could lead to an overdispersed community. However, as heterogeneity increase, more closely related species may be able to coexist together and lead to a clustered community. Our results indicate that soil phosphorus heterogeneity significantly affects tree diversity in the Xishuangbanna tropical seasonal rainforest, suggesting that deterministic processes are dominant in this tropical forest assembly.

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.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Rene Saldana's "The Jumping Tree": Exploring Childhood Universals through a Hispanic Novel

ERIC Educational Resources Information Center

Newman, Beatrice Mendez

2006-01-01

In "The Jumping Tree", set in Nuevo Penitas, an actual South Texas town, 12-year-old Rey Castaneda recounts landmark events in his journey toward becoming a man. Rey's stories of his childhood escapades, adventures, and everyday experiences could be anyone's childhood stories. When readers have finished the last page, they have relived the…

Ecohydrological consequences of drought- and infestation-triggered tree die-off: Insights and hypotheses

Treesearch

Henry D. Adams; Charles H. Luce; David D. Breshears; Craig D. Allen; Markus Weiler; V. Cody Hale; Alistair M. S. Smith; Travis E. Huxman

2012-01-01

Widespread, rapid, drought-, and infestation-triggered tree mortality is emerging as a phenomenon affecting forests globally and may be linked to increasing temperatures and drought frequency and severity. The ecohydrological consequences of forest die-off have been little studied and remain highly uncertain. To explore this knowledge gap, we apply the extensive...

Identification of Sexually Abused Female Adolescents at Risk for Suicidal Ideations: A Classification and Regression Tree Analysis

ERIC Educational Resources Information Center

Brabant, Marie-Eve; Hebert, Martine; Chagnon, Francois

2013-01-01

This study explored the clinical profiles of 77 female teenager survivors of sexual abuse and examined the association of abuse-related and personal variables with suicidal ideations. Analyses revealed that 64% of participants experienced suicidal ideations. Findings from classification and regression tree analysis indicated that depression,…

Group opening outcomes, sustainable forest management, and the Menominee Nation lands

Treesearch

Christel C. Kern; Manfred Schoelch; Paul Crocker; Dean Fellman; Angela Marsh; Dave Mausel; Marshall Pecore; Joseph Phillippi; Ronald Waukau; Anthony Waupochick

2017-01-01

Ideally, variants of single-tree, group, and patch selection create new, spatially aggregated age classes and maintain a diversity of tree species and sizes in multiaged, mixed-species forests. We explored this notion in northern hardwood forests on the Menominee Nation, a forest ecosystem without the exploitive cutting history of most forests in the western Great...

Tree age and tree species shape positive and negative interactions in a montane meadow

Treesearch

Ryan D. Haugo; Charles Halpern

2010-01-01

Few studies have considered how interactions between woody and herbaceous species change in direction or magnitude over time or with traits of the dominant woody species. We used a chronosequence approach to explore these interactions in a montane meadow in which Pinus contorta Dougl. ex Loud. and Abies grandis (Dougl. ex. D....

[Factors influencing tree radial growth of three common species in broad-leaved Korean pine mixed forests in Changbai Mountains, China].

PubMed

Cai, Li Rong; Kuang, Xu; Fang, Shuai; Yuan, Zuo Qiang; Lin, Fei; Ye, Ji; Hao, Zhan Qing; Wang, Xu Gao

2017-05-18

To understand the factors influencing tree radial growth, we analyzed the seasonal dynamics of tree growth of 3 common species (Pinus koraiensis, Tilia amurensis, Quercus mongolica), compared interspecific growth rates and explored the effects of size, neighborhood competition, soil and topography based on five years dendrometer bands monitoring data of the 3 common species in a broad-leaved Korean pine (P. koraiensis) mixed forest plot in Changbai Mountain, Northeast China. The results showed that the growth dynamics of 3 species were consistent. Trees began to grow in late May, thrived in July, grew at declining rates from late August and stopped growing in late October. Annual relative growth rates were significantly different among the species. Q. mongolica tended to grow faster than the other two species, and the differences of growth rates among the 3 species were especially large for small and medium trees. Tree growth rates of P. koraiensis and Q. mongolica were strongly decreased by neighborhood competition, while tree growth rate of T. amurensis was significantly related to tree size, soil and topography.

Drivers’ Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving

PubMed Central

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-01

This paper describes a real-time motion planner based on the drivers’ visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers’ visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers’ visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms. PMID:26784203

Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving.

PubMed

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-15

This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers' visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

Drivers of aboveground wood production in a lowland tropical forest of West Africa: teasing apart the roles of tree density, tree diversity, soil phosphorus, and historical logging.

PubMed

Jucker, Tommaso; Sanchez, Aida Cuni; Lindsell, Jeremy A; Allen, Harriet D; Amable, Gabriel S; Coomes, David A

2016-06-01

Tropical forests currently play a key role in regulating the terrestrial carbon cycle and abating climate change by storing carbon in wood. However, there remains considerable uncertainty as to whether tropical forests will continue to act as carbon sinks in the face of increased pressure from expanding human activities. Consequently, understanding what drives productivity in tropical forests is critical. We used permanent forest plot data from the Gola Rainforest National Park (Sierra Leone) - one of the largest tracts of intact tropical moist forest in West Africa - to explore how (1) stand basal area and tree diversity, (2) past disturbance associated with past logging, and (3) underlying soil nutrient gradients interact to determine rates of aboveground wood production (AWP). We started by statistically modeling the diameter growth of individual trees and used these models to estimate AWP for 142 permanent forest plots. We then used structural equation modeling to explore the direct and indirect pathways which shape rates of AWP. Across the plot network, stand basal area emerged as the strongest determinant of AWP, with densely packed stands exhibiting the fastest rates of AWP. In addition to stand packing density, both tree diversity and soil phosphorus content were also positively related to productivity. By contrast, historical logging activities negatively impacted AWP through the removal of large trees, which contributed disproportionately to productivity. Understanding what determines variation in wood production across tropical forest landscapes requires accounting for multiple interacting drivers - with stand structure, tree diversity, and soil nutrients all playing a key role. Importantly, our results also indicate that logging activities can have a long-lasting impact on a forest's ability to sequester and store carbon, emphasizing the importance of safeguarding old-growth tropical forests.

Adequacy of different experimental designs for eucalyptus spacing trials in Portuguese environmental conditions

Treesearch

Paula Soares; Margarida Tome

2000-01-01

In Portugal, several eucalyptus spacing trials cover a relatively broad range of experimental designs: trials with a non-randomized block design with plots of different size and number of trees per plot; trials based on a non-systematic design in which spacings were randomized resulting in a factorial arrangement with plots of different size and shape and equal number...

[Research advances in dendrochronology].

PubMed

Fang, Ke-Yan; Chen, Qiu-Yan; Liu, Chang-Zhi; Cao, Chun-Fu; Chen, Ya-Jun; Zhou, Fei-Fei

2014-07-01

Tree-ring studies in China have achieved great advances since the 1990s, particularly for the dendroclimatological studies which have made some influence around the world. However, because of the uneven development, limited attention has been currently paid on the other branches of dendrochronology. We herein briefly compared the advances of dendrochronology in China and of the world and presented suggestions on future dendrochronological studies. Large-scale tree-ring based climate reconstructions in China are highly needed by employing mathematical methods and a high quality tree-ring network of the ring-width, density, stable isotope and wood anatomy. Tree-ring based field climate reconstructions provide potentials on explorations of climate forcings during the reconstructed periods via climate diagnosis and process simulation.

Autumn Algorithm-Computation of Hybridization Networks for Realistic Phylogenetic Trees.

PubMed

Huson, Daniel H; Linz, Simone

2018-01-01

A minimum hybridization network is a rooted phylogenetic network that displays two given rooted phylogenetic trees using a minimum number of reticulations. Previous mathematical work on their calculation has usually assumed the input trees to be bifurcating, correctly rooted, or that they both contain the same taxa. These assumptions do not hold in biological studies and "realistic" trees have multifurcations, are difficult to root, and rarely contain the same taxa. We present a new algorithm for computing minimum hybridization networks for a given pair of "realistic" rooted phylogenetic trees. We also describe how the algorithm might be used to improve the rooting of the input trees. We introduce the concept of "autumn trees", a nice framework for the formulation of algorithms based on the mathematics of "maximum acyclic agreement forests". While the main computational problem is hard, the run-time depends mainly on how different the given input trees are. In biological studies, where the trees are reasonably similar, our parallel implementation performs well in practice. The algorithm is available in our open source program Dendroscope 3, providing a platform for biologists to explore rooted phylogenetic networks. We demonstrate the utility of the algorithm using several previously studied data sets.

Ranking Mammal Species for Conservation and the Loss of Both Phylogenetic and Trait Diversity.

PubMed

Redding, David W; Mooers, Arne O

2015-01-01

The 'edge of existence' (EDGE) prioritisation scheme is a new approach to rank species for conservation attention that aims to identify species that are both isolated on the tree of life and at imminent risk of extinction as defined by the World Conservation Union (IUCN). The self-stated benefit of the EDGE system is that it effectively captures unusual 'unique' species, and doing so will preserve the total evolutionary history of a group into the future. Given the EDGE metric was not designed to capture total evolutionary history, we tested this claim. Our analyses show that the total evolutionary history of mammals preserved is indeed much higher if EDGE species are protected than if at-risk species are chosen randomly. More of the total tree is also protected by EDGE species than if solely threat status or solely evolutionary distinctiveness were used for prioritisation. When considering how much trait diversity is captured by IUCN and EDGE prioritisation rankings, interestingly, preserving the highest-ranked EDGE species, or indeed just the most threatened species, captures more total trait diversity compared to sets of randomly-selected at-risk species. These results suggest that, as advertised, EDGE mammal species contribute evolutionary history to the evolutionary tree of mammals non-randomly, and EDGE-style rankings among endangered species can also capture important trait diversity. If this pattern holds for other groups, the EDGE prioritisation scheme has greater potential to be an efficient method to allocate scarce conservation effort.

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

PubMed

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

The Efficiency of Random Forest Method for Shoreline Extraction from LANDSAT-8 and GOKTURK-2 Imageries

NASA Astrophysics Data System (ADS)

Bayram, B.; Erdem, F.; Akpinar, B.; Ince, A. K.; Bozkurt, S.; Catal Reis, H.; Seker, D. Z.

2017-11-01

Coastal monitoring plays a vital role in environmental planning and hazard management related issues. Since shorelines are fundamental data for environment management, disaster management, coastal erosion studies, modelling of sediment transport and coastal morphodynamics, various techniques have been developed to extract shorelines. Random Forest is one of these techniques which is used in this study for shoreline extraction.. This algorithm is a machine learning method based on decision trees. Decision trees analyse classes of training data creates rules for classification. In this study, Terkos region has been chosen for the proposed method within the scope of "TUBITAK Project (Project No: 115Y718) titled "Integration of Unmanned Aerial Vehicles for Sustainable Coastal Zone Monitoring Model - Three-Dimensional Automatic Coastline Extraction and Analysis: Istanbul-Terkos Example". Random Forest algorithm has been implemented to extract the shoreline of the Black Sea where near the lake from LANDSAT-8 and GOKTURK-2 satellite imageries taken in 2015. The MATLAB environment was used for classification. To obtain land and water-body classes, the Random Forest method has been applied to NIR bands of LANDSAT-8 (5th band) and GOKTURK-2 (4th band) imageries. Each image has been digitized manually and shorelines obtained for accuracy assessment. According to accuracy assessment results, Random Forest method is efficient for both medium and high resolution images for shoreline extraction studies.

A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees.

PubMed

Nattee, Cholwich; Khamsemanan, Nirattaya; Lawtrakul, Luckhana; Toochinda, Pisanu; Hannongbua, Supa

2017-01-01

Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, K i of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted K i values from the proposed model show a strong coefficient of determination, R 2 =0.996, to experimental K i values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low K i values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted K i should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low K i . Copyright © 2016 Elsevier Inc. All rights reserved.

Equality of Shapley value and fair proportion index in phylogenetic trees.

PubMed

Fuchs, Michael; Jin, Emma Yu

2015-11-01

The Shapley value and the fair proportion index of phylogenetic trees have been introduced recently for the purpose of making conservation decisions in genetics. Moreover, also very recently, Hartmann (J Math Biol 67:1163-1170, 2013) has presented data which shows that there is a strong correlation between a slightly modified version of the Shapley value (which we call the modified Shapley value) and the fair proportion index. He gave an explanation of this correlation by showing that the contribution of both indices to an edge of the tree becomes identical as the number of taxa tends to infinity. In this note, we show that the Shapley value and the fair proportion index are in fact the same. Moreover, we also consider the modified Shapley value and show that its covariance with the fair proportion index in random phylogenetic trees under the Yule-Harding model and uniform model is indeed close to one.

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

NASA Astrophysics Data System (ADS)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

Spatial Distribution and Site-Specific Spraying of Main Sucking Pests of Elm Trees.

PubMed

Karimzadeh, R; Iranipour, S

2017-06-01

Elm trees are important landscape trees and sucking insects weaken the elm trees and produce large amounts of honeydew. The main objectives of this study were to identify main honeydew-producing pests of elm trees and do site-specific spraying against these pests. To map the spatial distribution of the sucking pests in the large scale, the study area was divided into 40 × 40 m grids and one tree was chosen randomly from each grid (a total of 55 trees). These trees were sampled twice a year in 2011 and 2012. Each sample was a 30-cm branch terminal. Eight samples were taken from each tree in four cardinal directions and two canopy levels. The number of sucking insects and leaves of each sample were counted and recorded. Spatial analysis of the data was carried out using geostatistics. Kriging was used for producing prediction maps. Insecticide application was restricted to the regions with populations higher than threshold. To identify within-tree distribution of the honeydew-producing pests, six and four elm trees were chosen in 2011 and 2012 respectively, and sampled weekly. These trees were sampled as described previously. European elm scale (EES), Gossyparia spuria (Modeer) and two species of aphids were the dominant honeydew-producing pests. The results revealed that the effects of direction, canopy level and their interactions on insect populations were not statistically significant (P < 0.05). Site-specific spraying decreased the amount of insecticides used by ca. 20%, while satisfactory control of the sucking pests and honeydew excretion was obtained. Considering the environmental and economic benefits of site-specific spraying, it is worth doing more complementary works in this area.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

PubMed

Kadupitige, Sidath Randeni; Leung, Kin Chun; Sellmeier, Julia; Sivieng, Jane; Catchpoole, Daniel R; Bain, Michael E; Gaëta, Bruno A

2009-12-03

The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds

NASA Astrophysics Data System (ADS)

Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

2018-06-01

In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.

Nonverbal behavior correlated with the shaped verbal behavior of children

PubMed Central

Catania, A. Charles; Lowe, C. Fergus; Horne, Pauline

1990-01-01

Children under 6 years old pressed on response windows behind which stimuli appeared (star or tree). Presses occasionally lit lamps arranged in a column; a present was delivered when all lamps were lit. A random-ratio schedule in the presence of star alternated with a random-interval schedule in the presence of tree. These contingencies usually did not produce respective high and low response rates in the presence of star and tree, but the shaping of verbal behavior (e.g., “press a lot without stopping” or “press and wait”) was sometimes accompanied by corresponding changes in response rate. Verbal shaping was accomplished between schedule components during verbal interactions between the child and a hand-puppet, Garfield the Cat, and used social consequences such as enthusiastic reactions to what the child had said as well as concrete consequences such as delivery of extra presents. Variables that may constrain the shaping of verbal behavior in children seem to include the vocabulary available to the child and the functional properties of that vocabulary; the correlation between rates of pressing and what the child says about them may depend upon such variables. ImagesFig. 2 PMID:22477603

Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients

NASA Astrophysics Data System (ADS)

Tang, Jie; Liu, Rong; Zhang, Yue-Li; Liu, Mou-Ze; Hu, Yong-Fang; Shao, Ming-Jie; Zhu, Li-Jun; Xin, Hua-Wen; Feng, Gui-Wen; Shang, Wen-Jun; Meng, Xiang-Guang; Zhang, Li-Rong; Ming, Ying-Zi; Zhang, Wei

2017-02-01

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67-0.76)] and validation cohorts [0.73 (0.63-0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

Productivity and breeding habitat of loggerhead shrikes in a southwestern urban environment

USGS Publications Warehouse

Boal, C.W.; Estabrook, T.S.; Duerr, A.E.

2003-01-01

Declines in loggerhead shrike (Lanius ludovicianus) populations have been associated in part with habitat loss and degradation, including that resulting from urbanization. We monitored the productivity and examined nesting habitat of loggerhead shrikes nesting in an urban environment in Tucson, Arizona. We located 22 breeding pairs in 1997 and 26 breeding pairs in 1998, with a 72% breeding area reoccupancy between years. Mean fledgling numbers were 2.28/ nesting attempt and 3.11/successful nest. Although some pairs initially failed and renested, 91% and 73% of shrike pairs successfully fledged young in 1997 and 1998, respectively. Mayfield estimates of nesting success were 78% in 1997 and 65% in 1998. Nest sites were characterized by more trees >3 m in height, taller nest trees than those randomly available, and a greater proportion of bare ground surface than at random sites. Shrike breeding territories had lower proportions of residential and commercial development and greater proportions of open areas with low-growing vegetation than randomly available. Some shrikes nested in school playgrounds, residential front yards, and parking lots, if adjacent open space was available.

Lesser prairie-chicken avoidance of trees in a grassland landscape

USGS Publications Warehouse

Lautenbach, Joseph M.; Plumb, Reid T.; Robinson, Samantha G.; Hagen, Christian A.; Haukos, David A.; Pitman, James C.

2016-01-01

Grasslands are among the most imperiled ecosystems in North America. Reasons that grasslands are threatened include conversion to row-crop agriculture, fragmentation, and changes in fire regimes. The reduction of fire processes in remaining prairies has resulted in tree encroachment and establishment in grasslands, further reducing grassland quantity and quality. Grassland birds have been experiencing precipitous population declines in recent decades, commensurate with landscape changes to grasslands. The lesser prairie-chicken (Tympanuchus pallidicinctus Ridgway) is a declining species of prairie grouse of conservation concern. We used second- and third-order habitat selection metrics to test if female lesser prairie-chickens avoid grasslands where trees were present. Our results indicated that female lesser prairie-chickens selected habitats avoiding the nearest trees by 283 m on average, nearly twice as far as would be expected at random. Lesser prairie-chickens were 40 times more likely to use habitats with tree densities of 0 trees ∙ ha− 1 than habitats with 5 trees ∙ ha− 1. Probability of use indicated that lesser prairie-chickens were 19 times more likely to use habitats 1000 m from the nearest tree when compared with using habitats 0 m from the nearest tree. Nest survival was not affected at densities < 2 trees ∙ ha− 1; however, we could not test if nest survival was affected at greater tree densities as no nests were detected at densities > 2 trees ∙ ha− 1. Avoidance of trees could be due to perceived increased predation risk, reduced habitat quality, or a combination of these potentially confounding factors. Preventing further establishment and expansion of trees in landscapes occupied by lesser prairie-chickens could contribute to the continued persistence of the species. Additionally, restoring grasslands through tree removal may facilitate conservation efforts for grassland species such as the lesser prairie-chicken by improving habitat quality and promoting expansion of occupied range.

The Spatial Pattern and Interactions of Woody Plants on the Temperate Savanna of Inner Mongolia, China: The Effects of Alternating Seasonal Grazing-Mowing Regimes

PubMed Central

2015-01-01

Ulmus pumila tree-dominated temperate savanna, which is distributed widely throughout the forest-steppe ecotone on the Mongolian Plateau, is a relatively stable woody-herbaceous complex ecosystem in northern China. Relatively more attention has been paid to the degradation of typical steppe areas, whereas less focus has been placed on the succession of this typical temperate savanna under the present management regime. In this study, we established 3 sample plots 100 m×100 m in size along a gradient of fixed distances from one herder’s stationary site and then surveyed all the woody plants in these plots. A spatial point pattern analysis was employed to clarify the spatial distribution and interaction of these woody plants. The results indicated that old U. pumila trees (DBH ≥ 20 cm) showed a random distribution and that medium U. pumila trees (5 cm ≤ DBH < 20 cm) showed an aggregated distribution at a smaller scale and a random distribution at a larger scale; few or no juvenile trees (DBH < 5 cm) were present, and seedlings (without DBH) formed aggregations in all 3 plots. These findings can be explained by an alternate seasonal grazing-mowing regime (exclosure in summer, mowing in autumn and grazing in winter and spring); the shrubs in all 3 plots exist along a grazing gradient that harbors xerophytic and mesophytic shrubs. Of these shrubs, xerophytic shrubs show significant aggregation at a smaller scale (0-5.5 m), whereas mesophytic shrubs show significant aggregation at a larger scale (0-25 m), which may be the result of the dual effects of grazing pressure and climate change. Medium trees and seedlings significantly facilitate the distributions of xerophytic shrubs and compete significantly with mesophytic shrubs due to differences in water use strategies. We conclude that the implementation of an alternative grazing-mowing regime results in xerophytic shrub encroachment or existence, breaking the chain of normal succession in a U. pumila tree community in this typical temperate savanna ecosystem. This might eventually result in the degradation of the original tree-dominated savanna to a xerophytic shrub-dominated savanna. PMID:26196956

Spatial patterns of a tropical tree species growing under an eucalyptus plantation in South-East Brazil.

PubMed

Higuchi, P; Silva, A C; Louzada, J N C; Machado, E L M

2010-05-01

The objectives of this study were to evaluate the influence of propagules source and the implication of tree size class on the spatial pattern of Xylopia brasiliensis Spreng. individuals growing under the canopy of an experimental plantation of eucalyptus. To this end, all individuals of Xylopia brasiliensis with diameter at soil height (dsh) > 1 cm were mapped in the understory of a 3.16 ha Eucalyptus spp. and Corymbia spp. plantation, located in the municipality of Lavras, SE Brazil. The largest nearby mature tree of X. brasiliensis was considered as the propagules source. Linear regressions were used to assess the influence of the distance of propagules source on the population parameters (density, basal area and height). The spatial pattern of trees was assessed through the Ripley K function. The overall pattern showed that the propagules source distance had strong influence over spatial distribution of trees, mainly the small ones, indicating that the closer the distance from the propagules source, the higher the tree density and the lower the mean tree height. The population showed different spatial distribution patterns according to the spatial scale and diameter class considered. While small trees tended to be aggregated up to around 80 m, the largest individuals were randomly distributed in the area. A plausible explanation for observed patterns might be limited seed rain and intra-population competition.

Factors affecting spruce establishment and recruitment near western treeline, Alaska

NASA Astrophysics Data System (ADS)

Miller, A. E.; Sherriff, R.; Wilson, T. L.

2015-12-01

Regional warming and increases in tree growth are contributing to increased productivity near the western forest margin in Alaska. The effects of warming on seedling recruitment has received little attention, in spite of forecasted forest expansion near western treeline. Here, we used stand structure and environmental data from white spruce (Picea glauca) stands (n = 95) sampled across a longitudinal gradient to explore factors influencing white spruce growth, establishment and recruitment in southwest Alaska. Using tree-ring chronologies developed from a subset of the plots (n = 30), we estimated establishment dates and basal area increment (BAI) for trees of all age classes across a range of site conditions. We used GLMs (generalized linear models) to explore the relationship between tree growth and temperature in undisturbed, low elevation sites along the gradient, using BAI averaged over the years 1975-2000. In addition, we examined the relationship between growing degree days (GDD) and seedling establishment over the previous three decades. We used total counts of live seedlings, saplings and live and dead trees, representing four cohorts, to evaluate whether geospatial, climate, and measured plot covariates predicted abundance of the different size classes. We hypothesized that the relationship between abundance and longitude would vary by size class, and that this relationship would be mediated by growing season temperature. We found that mean BAI for trees in undisturbed, low elevation sites increased with July maximum temperature, and that the slope of the relationship with temperature changed with longitude (interaction significant with 90% confidence). White spruce establishment was positively associated with longer summers and/or greater heat accumulation, as inferred from GDD. Seedling, sapling and tree abundance were also positively correlated with temperature across the study area. The response to longitude was mixed, with smaller size classes (seedlings, small saplings) most abundant at the western end of the gradient, and larger size classes (trees) most abundant to the east, suggesting a moving front of white spruce establishment near western treeline.

Tree phylogenetic diversity promotes host-parasitoid interactions.

PubMed

Staab, Michael; Bruelheide, Helge; Durka, Walter; Michalski, Stefan; Purschke, Oliver; Zhu, Chao-Dong; Klein, Alexandra-Maria

2016-07-13

Evidence from grassland experiments suggests that a plant community's phylogenetic diversity (PD) is a strong predictor of ecosystem processes, even stronger than species richness per se This has, however, never been extended to species-rich forests and host-parasitoid interactions. We used cavity-nesting Hymenoptera and their parasitoids collected in a subtropical forest as a model system to test whether hosts, parasitoids, and their interactions are influenced by tree PD and a comprehensive set of environmental variables, including tree species richness. Parasitism rate and parasitoid abundance were positively correlated with tree PD. All variables describing parasitoids decreased with elevation, and were, except parasitism rate, dependent on host abundance. Quantitative descriptors of host-parasitoid networks were independent of the environment. Our study indicates that host-parasitoid interactions in species-rich forests are related to the PD of the tree community, which influences parasitism rates through parasitoid abundance. We show that effects of tree community PD are much stronger than effects of tree species richness, can cascade to high trophic levels, and promote trophic interactions. As during habitat modification phylogenetic information is usually lost non-randomly, even species-rich habitats may not be able to continuously provide the ecosystem process parasitism if the evolutionarily most distinct plant lineages vanish. © 2016 The Author(s).

Genetic distances and phylogenetic trees of different Awassi sheep populations based on DNA sequencing.

PubMed

Al-Atiyat, R M; Aljumaah, R S

2014-08-27

This study aimed to estimate evolutionary distances and to reconstruct phylogeny trees between different Awassi sheep populations. Thirty-two sheep individuals from three different geographical areas of Jordan and the Kingdom of Saudi Arabia (KSA) were randomly sampled. DNA was extracted from the tissue samples and sequenced using the T7 promoter universal primer. Different phylogenetic trees were reconstructed from 0.64-kb DNA sequences using the MEGA software with the best general time reverse distance model. Three methods of distance estimation were then used. The maximum composite likelihood test was considered for reconstructing maximum likelihood, neighbor-joining and UPGMA trees. The maximum likelihood tree indicated three major clusters separated by cytosine (C) and thymine (T). The greatest distance was shown between the South sheep and North sheep. On the other hand, the KSA sheep as an outgroup showed shorter evolutionary distance to the North sheep population than to the others. The neighbor-joining and UPGMA trees showed quite reliable clusters of evolutionary differentiation of Jordan sheep populations from the Saudi population. The overall results support geographical information and ecological types of the sheep populations studied. Summing up, the resulting phylogeny trees may contribute to the limited information about the genetic relatedness and phylogeny of Awassi sheep in nearby Arab countries.

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

English, Thomas

2005-01-01

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

Ecohydrologic separation of water between trees and streams in a Mediterranean climate

Treesearch

J. Renee Brooks; Holly R. Barnard; Rob Coulombe; Jeffrey J. McDonnell

2010-01-01

Here, we directly explore links between hydrology and transpiration at the small watershed scale in a seasonally dry climate. Our central questions were: to what extent do trees and streams return the same water pool to the hydrosphere and how does this vary spatially within a watershed? These questions are fundamental to testing watershed hydrology models and coupled...

Dominant height-based height-diameter equations for trees in southern Indiana

Treesearch

John A., Jr. Kershaw; Robert C. Morrissey; Douglass F. Jacobs; John R. Seifert; James B. McCarter

2008-01-01

Height-diameter equations are developed based on dominant tree data collected in 1986 in 8- to 17-year-old clearcuts and the phase 2 Forest Inventory and Analysis plots on the Hoosier National Forest in south central Indiana. Two equation forms are explored: the basic, three-parameter Chapman-Richards function, and a modification of the three-parameter equation...

Assessing alternative measures of tree canopy cover: Photo-interpreted NAIP and ground-based estimates

Treesearch

Chris Toney; Greg Liknes; Andy Lister; Dacia Meneguzzo

2012-01-01

In preparation for the development of the National Land Cover Database (NLCD) 2011 tree canopy cover layer, a pilot project for research and method development was completed in 2010 by the USDA Forest Service Forest Inventory and Analysis (FIA) program and Remote Sensing Applications Center (RSAC).This paper explores one of several topics investigated during the NLCD...

Global forest sector modeling: application to some impacts of climate change

Treesearch

Joseph Buongiorno

2016-01-01

This paper explored the potential long-term effects of a warming climate on the global wood sector, based on Way and Oren's synthesis (Tree Physiology 30,669-688) indicating positive responses of tree growth to higher temperature in boreal and temperative climates, and negative responses in the topics. Changes in forest productivity were introduced in the Global...

Genetic structure of the invasive tree Ailanthus altissima in eastern United States cities

Treesearch

Preston R. Aldrich; Joseph S. Briguglio; Shyam N. Kapadia; Minesh U. Morker; Ankit Rawal; Preeti Kalra; Cynthia D. Huebner; Gary K. Greer

2010-01-01

Ailanthus altissima is an invasive tree from Asia. It now occurs in most US states, and although primarily an urban weed, it has become a problem in forested areas especially in the eastern states. Little is known about its genetic structure. We explore its naturalized gene pool from 28 populations, mostly of the eastern US where infestations are...

Fuels planning: science synthesis and integration; economic uses fact sheet 02: log hauling cost

Treesearch

Rocky Mountain Research Station USDA Forest Service

2004-01-01

Knowing the cost of fuel reduction treatments and associated activities, such as hauling cut trees, is essential for fire and fuels planning. This fact sheet explores the main factors that determine the cost of hauling cut trees and points the user to an interactive tool that can help plan for those and other expenses.

Genetic and environmental influences on cold hardiness of native and introduced riparian trees

Treesearch

Jonathan M. Friedman; James E. Roelle; Brian S. Cade

2012-01-01

To explore latitudinal genetic variation in cold hardiness and leaf phenology, we planted a common garden of paired collections of native and introduced riparian trees sampled along a latitudinal gradient. The garden in Fort Collins, Colorado (latitude 40.6°N), included 681 native plains cottonwood (Populus deltoides subsp. monilifera) and introduced saltcedar (Tamarix...

Assessing the US Urban Forest Resources

Treesearch

David J. Nowak; Mary H. Noble; Susan M. Sisinni; John F. Dwyer

2001-01-01

Urban areas in the conterminous United States doubled in size between 1969 and 1994, and currently cover 3.5 percent of the total land area and contain more than 75 percent of the US population. Urban areas contain approximately 3.8 billion trees with an average tree canopy cover of 27 percent. The extent and variation of urban forests across the 48 states are explored...

Patterns and Drivers of Tree Mortality in Iberian Forests: Climatic Effects Are Modified by Competition

PubMed Central

Ruiz-Benito, Paloma; Lines, Emily R.; Gómez-Aparicio, Lorena; Zavala, Miguel A.; Coomes, David A.

2013-01-01

Tree mortality is a key process underlying forest dynamics and community assembly. Understanding how tree mortality is driven by simultaneous drivers is needed to evaluate potential effects of climate change on forest composition. Using repeat-measure information from c. 400,000 trees from the Spanish Forest Inventory, we quantified the relative importance of tree size, competition, climate and edaphic conditions on tree mortality of 11 species, and explored the combined effect of climate and competition. Tree mortality was affected by all of these multiple drivers, especially tree size and asymmetric competition, and strong interactions between climate and competition were found. All species showed L-shaped mortality patterns (i.e. showed decreasing mortality with tree size), but pines were more sensitive to asymmetric competition than broadleaved species. Among climatic variables, the negative effect of temperature on tree mortality was much larger than the effect of precipitation. Moreover, the effect of climate (mean annual temperature and annual precipitation) on tree mortality was aggravated at high competition levels for all species, but especially for broadleaved species. The significant interaction between climate and competition on tree mortality indicated that global change in Mediterranean regions, causing hotter and drier conditions and denser stands, could lead to profound effects on forest structure and composition. Therefore, to evaluate the potential effects of climatic change on tree mortality, forest structure must be considered, since two systems of similar composition but different structure could radically differ in their response to climatic conditions. PMID:23451096

Exploring the cosmic evolution of habitability with galaxy merger trees

NASA Astrophysics Data System (ADS)

Stanway, E. R.; Hoskin, M. J.; Lane, M. A.; Brown, G. C.; Childs, H. J. T.; Greis, S. M. L.; Levan, A. J.

2018-04-01

We combine inferred galaxy properties from a semi-analytic galaxy evolution model incorporating dark matter halo merger trees with new estimates of supernova and gamma-ray burst rates as a function of metallicity from stellar population synthesis models incorporating binary interactions. We use these to explore the stellar-mass fraction of galaxies irradiated by energetic astrophysical transients and its evolution over cosmic time, and thus the fraction which is potentially habitable by life like our own. We find that 18 per cent of the stellar mass in the Universe is likely to have been irradiated within the last 260 Myr, with GRBs dominating that fraction. We do not see a strong dependence of irradiated stellar-mass fraction on stellar mass or richness of the galaxy environment. We consider a representative merger tree as a Local Group analogue, and find that there are galaxies at all masses which have retained a high habitable fraction (>40 per cent) over the last 6 Gyr, but also that there are galaxies at all masses where the merger history and associated star formation have rendered galaxies effectively uninhabitable. This illustrates the need to consider detailed merger trees when evaluating the cosmic evolution of habitability.

Exact Asymptotics of the Freezing Transition of a Logarithmically Correlated Random Energy Model

NASA Astrophysics Data System (ADS)

Webb, Christian

2011-12-01

We consider a logarithmically correlated random energy model, namely a model for directed polymers on a Cayley tree, which was introduced by Derrida and Spohn. We prove asymptotic properties of a generating function of the partition function of the model by studying a discrete time analogy of the KPP-equation—thus translating Bramson's work on the KPP-equation into a discrete time case. We also discuss connections to extreme value statistics of a branching random walk and a rescaled multiplicative cascade measure beyond the critical point.

Using Random Forest Models to Predict Organizational Violence

NASA Technical Reports Server (NTRS)

Levine, Burton; Bobashev, Georgly

2012-01-01

We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"

An artifact caused by undersampling optimal trees in supermatrix analyses of locally sampled characters.

PubMed

Simmons, Mark P; Goloboff, Pablo A

2013-10-01

Empirical and simulated examples are used to demonstrate an artifact caused by undersampling optimal trees in data matrices that consist mostly or entirely of locally sampled (as opposed to globally, for most or all terminals) characters. The artifact is that unsupported clades consisting entirely of terminals scored for the same locally sampled partition may be resolved and assigned high resampling support-despite their being properly unsupported (i.e., not resolved in the strict consensus of all optimal trees). This artifact occurs despite application of random-addition sequences for stepwise terminal addition. The artifact is not necessarily obviated with thorough conventional branch swapping methods (even tree-bisection-reconnection) when just a single tree is held, as is sometimes implemented in parsimony bootstrap pseudoreplicates, and in every GARLI, PhyML, and RAxML pseudoreplicate and search for the most likely tree for the matrix as a whole. Hence GARLI, RAxML, and PhyML-based likelihood results require extra scrutiny, particularly when they provide high resolution and support for clades that are entirely unsupported by methods that perform more thorough searches, as in most parsimony analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Vernal freeze damage and genetic variation alter tree growth, chemistry, and insect interactions.

PubMed

Rubert-Nason, Kennedy F; Couture, John J; Gryzmala, Elizabeth A; Townsend, Philip A; Lindroth, Richard L

2017-11-01

Anticipated consequences of climate change in temperate regions include early spring warmup punctuated by intermittent hard freezes. Warm weather accelerates leaf flush in perennial woody species, potentially exposing vulnerable young tissues to damaging frosts. We employed a 2 × 6 randomized factorial design to examine how the interplay of vernal (springtime) freeze damage and genetic variation in a hardwood species (Populus tremuloides) influences tree growth, phytochemistry, and interactions with an insect herbivore (Chaitophorus stevensis). Acute effects of freezing included defoliation and mortality. Surviving trees exhibited reduced growth and altered biomass distribution. Reflushed leaves on these trees had lower mass per area, lower lignin concentrations, and higher nitrogen concentrations, altered chemical defence profiles, and supported faster aphid population growth. Many effects varied among plant genotypes and were related with herbivore performance. This study suggests that a single damaging vernal freeze event can alter tree-insect interactions through effects on plant growth and chemistry. Differential responses of various genotypes to freeze damage suggest that more frequent vernal freeze events could also influence natural selection, favouring trees with greater freeze hardiness, and more resistance or tolerance to herbivores following damage. © 2017 John Wiley & Sons Ltd.

Edge-related loss of tree phylogenetic diversity in the severely fragmented Brazilian Atlantic forest.

PubMed

Santos, Bráulio A; Arroyo-Rodríguez, Víctor; Moreno, Claudia E; Tabarelli, Marcelo

2010-09-08

Deforestation and forest fragmentation are known major causes of nonrandom extinction, but there is no information about their impact on the phylogenetic diversity of the remaining species assemblages. Using a large vegetation dataset from an old hyper-fragmented landscape in the Brazilian Atlantic rainforest we assess whether the local extirpation of tree species and functional impoverishment of tree assemblages reduce the phylogenetic diversity of the remaining tree assemblages. We detected a significant loss of tree phylogenetic diversity in forest edges, but not in core areas of small (<80 ha) forest fragments. This was attributed to a reduction of 11% in the average phylogenetic distance between any two randomly chosen individuals from forest edges; an increase of 17% in the average phylogenetic distance to closest non-conspecific relative for each individual in forest edges; and to the potential manifestation of late edge effects in the core areas of small forest remnants. We found no evidence supporting fragmentation-induced phylogenetic clustering or evenness. This could be explained by the low phylogenetic conservatism of key life-history traits corresponding to vulnerable species. Edge effects must be reduced to effectively protect tree phylogenetic diversity in the severely fragmented Brazilian Atlantic forest.

Effect of shade on Arabica coffee berry disease development: Toward an agroforestry system to reduce disease impact.

PubMed

Mouen Bedimo, J A; Njiayouom, I; Bieysse, D; Ndoumbè Nkeng, M; Cilas, C; Nottéghem, J L

2008-12-01

Coffee berry disease (CBD), caused by Colletotrichum kahawae, is a major constraint for Arabica coffee cultivation in Africa. The disease is specific to green berries and can lead to 60% harvest losses. In Cameroon, mixed cropping systems of coffee with other crops, such as fruit trees, are very widespread agricultural practices. Fruit trees are commonly planted at random on coffee farms, providing a heterogeneous shading pattern for coffee trees growing underneath. Based on a recent study of CBD, it is known that those plants can reduce disease incidence. To assess the specific effect of shade, in situ and in vitro disease development was compared between coffee trees shaded artificially by a net and trees located in full sunlight. In the field, assessments confirmed a reduction in CBD on trees grown under shade compared with those grown in full sunlight. Artificial inoculations in the laboratory showed that shade did not have any effect on the intrinsic susceptibility of coffee berries to CBD. Coffee shading mainly acts on environmental parameters in limiting disease incidence. In addition to reducing yield losses, agroforestry system may also be helpful in reducing chemical control of the disease and in diversifying coffee growers' incomes.

The limited contribution of large trees to annual biomass production in an old-growth tropical forest.

PubMed

Ligot, Gauthier; Gourlet-Fleury, Sylvie; Ouédraogo, Dakis-Yaoba; Morin, Xavier; Bauwens, Sébastien; Baya, Fidele; Brostaux, Yves; Doucet, Jean-Louis; Fayolle, Adeline

2018-04-16

Although the importance of large trees regarding biodiversity and carbon stock in old-growth forests is undeniable, their annual contribution to biomass production and carbon uptake remains poorly studied at the stand level. To clarify the role of large trees in biomass production, we used data of tree growth, mortality, and recruitment monitored during 20 yr in 10 4-ha plots in a species-rich tropical forest (Central African Republic). Using a random block design, three different silvicultural treatments, control, logged, and logged + thinned, were applied in the 10 plots. Annual biomass gains and losses were analyzed in relation to the relative biomass abundance of large trees and by tree size classes using a spatial bootstrap procedure. Although large trees had high individual growth rates and constituted a substantial amount of biomass, stand-level biomass production decreased with the abundance of large trees in all treatments and plots. The contribution of large trees to annual stand-level biomass production appeared limited in comparison to that of small trees. This pattern did not only originate from differences in abundance of small vs. large trees or differences in initial biomass stocks among tree size classes, but also from a reduced relative growth rate of large trees and a relatively constant mortality rate among tree size classes. In a context in which large trees are increasingly gaining attention as being a valuable and a key structural characteristic of natural forests, the present study brought key insights to better gauge the relatively limited role of large trees in annual stand-level biomass production. In terms of carbon uptake, these results suggest, as already demonstrated, a low net carbon uptake of old-growth forests in comparison to that of logged forests. Tropical forests that reach a successional stage with relatively high density of large trees progressively cease to be carbon sinks as large trees contribute sparsely or even negatively to the carbon uptake at the stand level. © 2018 by the Ecological Society of America.

Bilingual approach to online cancer genetics education for Deaf American Sign Language users produces greater knowledge and confidence than English text only: A randomized study.

PubMed

Palmer, Christina G S; Boudreault, Patrick; Berman, Barbara A; Wolfson, Alicia; Duarte, Lionel; Venne, Vickie L; Sinsheimer, Janet S

2017-01-01

Deaf American Sign Language-users (ASL) have limited access to cancer genetics information they can readily understand, increasing risk for health disparities. We compared effectiveness of online cancer genetics information presented using a bilingual approach (ASL with English closed captioning) and a monolingual approach (English text). Bilingual modality would increase cancer genetics knowledge and confidence to create a family tree; education would interact with modality. We used a parallel 2:1 randomized pre-post study design stratified on education. 150 Deaf ASL-users ≥18 years old with computer and internet access participated online; 100 (70 high, 30 low education) and 50 (35 high, 15 low education) were randomized to the bilingual and monolingual modalities. Modalities provide virtually identical content on creating a family tree, using the family tree to identify inherited cancer risk factors, understanding how cancer predisposition can be inherited, and the role of genetic counseling and testing for prevention or treatment. 25 true/false items assessed knowledge; a Likert scale item assessed confidence. Data were collected within 2 weeks before and after viewing the information. Significant interaction of language modality, education, and change in knowledge scores was observed (p = .01). High education group increased knowledge regardless of modality (Bilingual: p < .001; d = .56; Monolingual: p < .001; d = 1.08). Low education group increased knowledge with bilingual (p < .001; d = .85), but not monolingual (p = .79; d = .08) modality. Bilingual modality yielded greater confidence creating a family tree (p = .03). Bilingual approach provides a better opportunity for lower educated Deaf ASL-users to access cancer genetics information than a monolingual approach. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen; Tracy S. Frescino

2012-01-01

Random Forests is frequently used to model species distributions over large geographic areas. Complications arise when data used to train the models have been collected in stratified designs that involve different sampling intensity per stratum. The modeling process is further complicated if some of the target species are relatively rare on the landscape leading to an...

Allergy multivaccines created by DNA shuffling of tree pollen allergens.

PubMed

Wallner, Michael; Stöcklinger, Angelika; Thalhamer, Theresa; Bohle, Barbara; Vogel, Lothar; Briza, Peter; Breiteneder, Heimo; Vieths, Stefan; Hartl, Arnulf; Mari, Adriano; Ebner, Christof; Lackner, Peter; Hammerl, Peter; Thalhamer, Josef; Ferreira, Fatima

2007-08-01

The major allergens of trees belonging to the Fagales order are collectively known as the Bet v 1 family. Members of the Fagales order have distinct geographic distribution, and it is expected that depending on the exposure pattern of the individual, inclusion of other Bet v 1 family members might increase the efficacy of the treatment. We aimed to generate molecules that are suitable for specific immunotherapy not only against birch pollen allergy but also against allergies caused by other cross-reactive tree pollens. Fourteen genes of the Bet v 1 family were randomly recombined in vitro by means of DNA shuffling. This library of chimeric proteins was screened for molecules displaying low capacity to induce release of inflammatory mediators but with T-cell immunogenicity higher than that of the parental allergens. Two chimeric proteins were selected from the library of shuffled clones displaying low allergenicity and high immunogenicity, as determined in in vitro assays using human and animal cells and antibodies, as well as in vivo in animal models of allergy. Our results show that it is possible to randomly recombine in vitro T- and B-cell epitopes of a family of related allergens and to select chimeric proteins that perfectly match the criteria presently thought to be relevant for improving allergen-specific immunotherapy. The hypoallergenic chimeras described here recombine epitopes of the major Fagales pollen allergens and thus can efficiently substitute a mixture of extracts used for treating patients with tree pollen-induced spring pollinosis worldwide.

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran.

PubMed

Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Dixon, Barnali

2016-01-01

Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiographical (HGP) factors that influence locations of springs were considered in this research. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Subsequently, groundwater spring potential was modeled and mapped using CART, RF, and BRT algorithms. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 864 springs identified, 605 (≈70 %) locations were used for the spring potential mapping, while the remaining 259 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the BRT model was calculated as 0.8103 and for CART and RF the AUC were 0.7870 and 0.7119, respectively. Therefore, it was concluded that the BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively. Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.

Coexistence of Trees and Grass: Importance of climate and fire within the tropics

NASA Astrophysics Data System (ADS)

Shuman, J. K.; Fisher, R.; Koven, C.; Knox, R. G.; Andre, B.; Kluzek, E. B.

2017-12-01

Tropical forests are characterized by transition zones where dominance shifts between trees and grasses with some areas exhibiting bistability of the two. The cause of this transition and bistability has been linked to the interacting effects of climate, vegetation structure and fire behavior. Utilizing the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model, and the CESM ESM, we explore the coexistence of trees and grass across the tropics with an active fire regime. FATES has been updated to use a fire module based on Spitfire. FATES-Spitfire tracks fire ignition, spread and impact based on fuel state and combustion. Fire occurs within the model with variable intensity that kills trees according to the combined effects of cambial damage and crown scorch due to flame height and fire intensity. As a size-structured model, FATES allows for variable mortality based on the size of tree cohorts, where larger trees experience lower morality compared to small trees. Results for simulation scenarios where vegetation is represented by all trees, all grass, or a combination of competing trees and grass are compared to assess changes in biomass, fire regime and tree-grass coexistence. Within the forest-grass transition area there is a critical time during which grass fuels fire spread and prevents the establishment of trees. If trees are able to escape mortality a tree-grass bistable area is successful. The ability to simulate the bistability and transition of trees and grass throughout the tropics is critical to representing vegetation dynamics in response to changing climate and CO2.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Species trees for the tree swallows (Genus Tachycineta): an alternative phylogenetic hypothesis to the mitochondrial gene tree.

PubMed

Dor, Roi; Carling, Matthew D; Lovette, Irby J; Sheldon, Frederick H; Winkler, David W

2012-10-01

The New World swallow genus Tachycineta comprises nine species that collectively have a wide geographic distribution and remarkable variation both within- and among-species in ecologically important traits. Existing phylogenetic hypotheses for Tachycineta are based on mitochondrial DNA sequences, thus they provide estimates of a single gene tree. In this study we sequenced multiple individuals from each species at 16 nuclear intron loci. We used gene concatenated approaches (Bayesian and maximum likelihood) as well as coalescent-based species tree inference to reconstruct phylogenetic relationships of the genus. We examined the concordance and conflict between the nuclear and mitochondrial trees and between concatenated and coalescent-based inferences. Our results provide an alternative phylogenetic hypothesis to the existing mitochondrial DNA estimate of phylogeny. This new hypothesis provides a more accurate framework in which to explore trait evolution and examine the evolution of the mitochondrial genome in this group. Copyright © 2012 Elsevier Inc. All rights reserved.

Nitrogen nutrition of poplar trees.

PubMed

Rennenberg, H; Wildhagen, H; Ehlting, B

2010-03-01

Many forest ecosystems have evolved at sites with growth-limiting nitrogen (N) availability, low N input from external sources and high ecosystem internal cycling of N. By contrast, many poplar species are frequent constituents of floodplain forests where they are exposed to a significant ecosystem external supply of N, mainly nitrate, in the moving water table. Therefore, nitrate is much more important for N nutrition of these poplar species than for many other tree species. We summarise current knowledge of nitrate uptake and its regulation by tree internal signals, as well as acquisition of ammonium and organic N from the soil. Unlike herbaceous plants, N nutrition of trees is sustained by seasonal, tree internal cycling. Recent advances in the understanding of seasonal storage and mobilisation in poplar bark and regulation of these processes by temperature and daylength are addressed. To explore consequences of global climate change on N nutrition of poplar trees, responses of N uptake and metabolism to increased atmospheric CO(2) and O(3) concentrations, increased air and soil temperatures, drought and salt stress are highlighted.

How Hierarchical Topics Evolve in Large Text Corpora.

PubMed

Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

2014-12-01

Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

Effects of Phylogenetic Tree Style on Student Comprehension

NASA Astrophysics Data System (ADS)

Dees, Jonathan Andrew

Phylogenetic trees are powerful tools of evolutionary biology that have become prominent across the life sciences. Consequently, learning to interpret and reason from phylogenetic trees is now an essential component of biology education. However, students often struggle to understand these diagrams, even after explicit instruction. One factor that has been observed to affect student understanding of phylogenetic trees is style (i.e., diagonal or bracket). The goal of this dissertation research was to systematically explore effects of style on student interpretations and construction of phylogenetic trees in the context of an introductory biology course. Before instruction, students were significantly more accurate with bracket phylogenetic trees for a variety of interpretation and construction tasks. Explicit instruction that balanced the use of diagonal and bracket phylogenetic trees mitigated some, but not all, style effects. After instruction, students were significantly more accurate for interpretation tasks involving taxa relatedness and construction exercises when using the bracket style. Based on this dissertation research and prior studies on style effects, I advocate for introductory biology instructors to use only the bracket style. Future research should examine causes of style effects and variables other than style to inform the development of research-based instruction that best supports student understanding of phylogenetic trees.

Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

PubMed

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-09-18

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

Motion Planning for Autonomous Vehicle Based on Radial Basis Function Neural Network in Unstructured Environment

PubMed Central

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-01-01

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. PMID:25237902

Why do trees die? Characterizing the drivers of background tree mortality.

PubMed

Das, Adrian J; Stephenson, Nathan L; Davis, Kristin P

2016-10-01

The drivers of background tree mortality rates-the typical low rates of tree mortality found in forests in the absence of acute stresses like drought-are central to our understanding of forest dynamics, the effects of ongoing environmental changes on forests, and the causes and consequences of geographical gradients in the nature and strength of biotic interactions. To shed light on factors contributing to background tree mortality, we analyzed detailed pathological data from 200,668 tree-years of observation and 3,729 individual tree deaths, recorded over a 13-yr period in a network of old-growth forest plots in California's Sierra Nevada mountain range. We found that: (1) Biotic mortality factors (mostly insects and pathogens) dominated (58%), particularly in larger trees (86%). Bark beetles were the most prevalent (40%), even though there were no outbreaks during the study period; in contrast, the contribution of defoliators was negligible. (2) Relative occurrences of broad classes of mortality factors (biotic, 58%; suppression, 51%; and mechanical, 25%) are similar among tree taxa, but may vary with tree size and growth rate. (3) We found little evidence of distinct groups of mortality factors that predictably occur together on trees. Our results have at least three sets of implications. First, rather than being driven by abiotic factors such as lightning or windstorms, the "ambient" or "random" background mortality that many forest models presume to be independent of tree growth rate is instead dominated by biotic agents of tree mortality, with potentially critical implications for forecasting future mortality. Mechanistic models of background mortality, even for healthy, rapidly growing trees, must therefore include the insects and pathogens that kill trees. Second, the biotic agents of tree mortality, instead of occurring in a few predictable combinations, may generally act opportunistically and with a relatively large degree of independence from one another. Finally, beyond the current emphasis on folivory and leaf defenses, studies of broad-scale gradients in the nature and strength of biotic interactions should also include biotic attacks on, and defenses of, tree stems and roots. © 2016 by the Ecological Society of America.

Autumn frost hardiness in Norway spruce plus tree progeny and trees of the local and transferred provenances in central Sweden.

PubMed

Hannerz, Mats; Westin, Johan

2005-09-01

Reforestation with provenances from locations remote from the planting site (transferred provenances) or the progeny of trees of local provenances selected for superior form and vigor (plus trees) offer alternative means to increase yield over that obtained by the use of seed from unselected trees of the local provenance. Under Swedish conditions, Norway spruce (Picea abies (L.) Karst.) of certain transferred provenances generally has an advantage in productivity relative to the local provenance comparable to that of progeny of plus trees. The aim of this study was to explore the extent to which productivity gains achieved by provenance transfer or the use of plus tree progeny are associated with reductions in autumn frost hardiness, relative to that of trees of the local provenance. In a field trial with 19-year-old trees in central Sweden, bud hardiness was tested on four occasions during the autumn of 2002. Trees of the local provenance were compared with trees of a south Swedish provenance originating 3 degrees of latitude to the south, a Belarusian provenance and the progeny of plus trees of local origin. The Belarusian provenance was the least hardy and the local provenance the most hardy, with plus tree progeny and the south Swedish provenance being intermediate in hardiness. Both the Belarusian provenance and the plus tree progeny were significantly taller than trees of the other populations. Within provenances, tree height was negatively correlated with autumn frost hardiness. Among the plus tree progeny, however, no such correlation between tree height and autumn frost hardiness was found. It is concluded that although the gain in productivity achieved by provenance transfer from Belarus was comparable to that achieved by using the progeny of plus trees of the local provenance, the use of trees of the Belarus provenance involved an increased risk of autumn frost damage because of later hardening.

Cash for carbon: A randomized trial of payments for ecosystem services to reduce deforestation.

PubMed

Jayachandran, Seema; de Laat, Joost; Lambin, Eric F; Stanton, Charlotte Y; Audy, Robin; Thomas, Nancy E

2017-07-21

We evaluated a program of payments for ecosystem services in Uganda that offered forest-owning households annual payments of 70,000 Ugandan shillings per hectare if they conserved their forest. The program was implemented as a randomized controlled trial in 121 villages, 60 of which received the program for 2 years. The primary outcome was the change in land area covered by trees, measured by classifying high-resolution satellite imagery. We found that tree cover declined by 4.2% during the study period in treatment villages, compared to 9.1% in control villages. We found no evidence that enrollees shifted their deforestation to nearby land. We valued the delayed carbon dioxide emissions and found that this program benefit is 2.4 times as large as the program costs. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition.

PubMed

Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi

2014-01-01

In this paper, some methods for ensemble learning of protein fold recognition based on a decision tree (DT) are compared and contrasted against each other over three datasets taken from the literature. According to previously reported studies, the features of the datasets are divided into some groups. Then, for each of these groups, three ensemble classifiers, namely, random forest, rotation forest and AdaBoost.M1 are employed. Also, some fusion methods are introduced for combining the ensemble classifiers obtained in the previous step. After this step, three classifiers are produced based on the combination of classifiers of types random forest, rotation forest and AdaBoost.M1. Finally, the three different classifiers achieved are combined to make an overall classifier. Experimental results show that the overall classifier obtained by the genetic algorithm (GA) weighting fusion method, is the best one in comparison to previously applied methods in terms of classification accuracy.

Rocket engine system reliability analyses using probabilistic and fuzzy logic techniques

NASA Technical Reports Server (NTRS)

Hardy, Terry L.; Rapp, Douglas C.

1994-01-01

The reliability of rocket engine systems was analyzed by using probabilistic and fuzzy logic techniques. Fault trees were developed for integrated modular engine (IME) and discrete engine systems, and then were used with the two techniques to quantify reliability. The IRRAS (Integrated Reliability and Risk Analysis System) computer code, developed for the U.S. Nuclear Regulatory Commission, was used for the probabilistic analyses, and FUZZYFTA (Fuzzy Fault Tree Analysis), a code developed at NASA Lewis Research Center, was used for the fuzzy logic analyses. Although both techniques provided estimates of the reliability of the IME and discrete systems, probabilistic techniques emphasized uncertainty resulting from randomness in the system whereas fuzzy logic techniques emphasized uncertainty resulting from vagueness in the system. Because uncertainty can have both random and vague components, both techniques were found to be useful tools in the analysis of rocket engine system reliability.

Noise enhances information transfer in hierarchical networks.

PubMed

Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

Noise enhances information transfer in hierarchical networks

PubMed Central

Czaplicka, Agnieszka; Holyst, Janusz A.; Sloot, Peter M. A.

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor. PMID:23390574

RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection.

PubMed

Wu, Ke; Zhang, Kun; Fan, Wei; Edwards, Andrea; Yu, Philip S

Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data. Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest. The piecewise constant density estimate of each RS-tree is defined on the tree node into which an instance falls. Each incoming instance in a data stream is scored by the density estimates averaged over all trees in the forest. Two strategies, statistical attribute range estimation of high probability guarantee and dual node profiles for rapid model update, are seamlessly integrated into RS-Forest to systematically address the ever-evolving nature of data streams. We derive the theoretical upper bound for the proposed algorithm and analyze its asymptotic properties via bias-variance decomposition. Empirical comparisons to the state-of-the-art methods on multiple benchmark datasets demonstrate that the proposed method features high detection rate, fast response, and insensitivity to most of the parameter settings. Algorithm implementations and datasets are available upon request.

Availability of nest cavity trees for wood ducks (Aix sponsa) at Sunkhaze Meadows National Wildlife Refuge, Maine

USGS Publications Warehouse

Clugston, D.A.

1999-01-01

The availability of natural cavities for cavitynesting waterfowl, especially wood ducks (Aix sponsa), was unknown ferating forest of Sunkhaze Meadows National Wildlife Refuge, ME. An assessment of cavity availability was needed to determine if the existing nesting box program should be increased. During November to March, 199697 and 199798, I sampled 56 onehalf ha random plots, stratified into 5 types (upland hardwood, upland conifer, upland mixwood, wetland conifer, and wetland hardwood) to assess availability of trees with cavities. The predominant tree species with cavities were red maple (Acer rubrum; 39%) and aspen (Populus sp.; 31%); 72% of all trees with cavities were alive. Density ees/plot averaged from 1.0 +0.4 (x +SE) in wetland softwoods to 1.9 +0.4 in upland hardwoods. This low density of potential cavity trees and the small mean dbh (39.4 +1.6 cm) indicate a young forest with few suitable cavities. Forested areas, especially hardwoods near canopy openings, need to be allowed to mature to increase the number and quality of future cavities. An expanded nest box program seems justified.

Agro-ecosystem and socio-economic role of homegarden agroforestry in Jabithenan District, North-Western Ethiopia: implication for climate change adaptation.

PubMed

Linger, Ewuketu

2014-01-01

Homegarden agroforestry is believed to be more diverse and provide multiple services for household than other monocropping system and this is due to the combination of crops, trees and livestock. The aim of this study was to assess socio-economic and agro-ecological role of homegardens in Jabithenan district, North-western Ethiopia. Two sites purposively and two villages randomly from each site were selected. Totally 96 households; in which 48 from homegarden agroforestry user and 48 from non-tree based garden user were selected for this study. Socio-economic data and potential economic and agro-ecosystem role of homegarden agroforestry over non-tree based garden were collected by using semi-structured and structured questionnaires to the households. Homegarden agroforestry significantly (P < 0.05) improved the farmers cash income than non-tree based garden. With insignificant garden size; homegarden agroforestry practice provides good socio-economical and agro-ecological service for farmers which have a higher implication for climate change adaptation than non-tree based garden.

RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection

PubMed Central

Wu, Ke; Zhang, Kun; Fan, Wei; Edwards, Andrea; Yu, Philip S.

2015-01-01

Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data. Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest. The piecewise constant density estimate of each RS-tree is defined on the tree node into which an instance falls. Each incoming instance in a data stream is scored by the density estimates averaged over all trees in the forest. Two strategies, statistical attribute range estimation of high probability guarantee and dual node profiles for rapid model update, are seamlessly integrated into RS-Forest to systematically address the ever-evolving nature of data streams. We derive the theoretical upper bound for the proposed algorithm and analyze its asymptotic properties via bias-variance decomposition. Empirical comparisons to the state-of-the-art methods on multiple benchmark datasets demonstrate that the proposed method features high detection rate, fast response, and insensitivity to most of the parameter settings. Algorithm implementations and datasets are available upon request. PMID:25685112

The effect of atomoxetine on random and directed exploration in humans.

PubMed

Warren, Christopher M; Wilson, Robert C; van der Wee, Nic J; Giltay, Eric J; van Noorden, Martijn S; Cohen, Jonathan D; Nieuwenhuis, Sander

2017-01-01

The adaptive regulation of the trade-off between pursuing a known reward (exploitation) and sampling lesser-known options in search of something better (exploration) is critical for optimal performance. Theory and recent empirical work suggest that humans use at least two strategies for solving this dilemma: a directed strategy in which choices are explicitly biased toward information seeking, and a random strategy in which decision noise leads to exploration by chance. Here we examined the hypothesis that random exploration is governed by the neuromodulatory locus coeruleus-norepinephrine system. We administered atomoxetine, a norepinephrine transporter blocker that increases extracellular levels of norepinephrine throughout the cortex, to 22 healthy human participants in a double-blind crossover design. We examined the effect of treatment on performance in a gambling task designed to produce distinct measures of directed exploration and random exploration. In line with our hypothesis we found an effect of atomoxetine on random, but not directed exploration. However, contrary to expectation, atomoxetine reduced rather than increased random exploration. We offer three potential explanations of our findings, involving the non-linear relationship between tonic NE and cognitive performance, the interaction of atomoxetine with other neuromodulators, and the possibility that atomoxetine affected phasic norepinephrine activity more so than tonic norepinephrine activity.

[The changes of forest canopy spectral reflectance with seasons in Xiaoxing'anling].

PubMed

Xu, Guang-Cai; Pang, Yong; Li, Zeng-Yuan; Zhao, Kai-Rui; Liu, Lu-Xia

2013-12-01

The ASD FieldSpec portable spectrometer was adopted to collect canopy reflectance spectrum data of the 9 main tree species in study area by a long-term observation to get the data of the four seasons Then the smoothed reflectance curve and the first derivation curve from 350 to 1400 nm and several commonly used vegetation spectral characteristic parameters were generated to analyse seasonal change characteristics and variation of the 9 tree species in visible and near-infrared band and to explore the best band characteristics and period for species identification. The results showed that different trees had different and rather unique spectral features during the four seasons. The spectral characteristics of the deciduous trees have regular changes with the cycle of the seasons, whereas those of the evergreen tree species have no significant changes in one year. As well changes in the spectral characteristics could effectively reflect forest phenology changes, and it is proposed that the optimal strategy for tree species classification may be the integration and analysis of multi-seasonal spectral data. Evergreen trees and deciduous trees in the winter have obvious differences in the canopy spectral characteristics and the best single-season remote sensing data for tree species recognition is in summer.

Modeling wind fields and fire propagation following bark beetle outbreaks in spatially-heterogeneous pinyon-juniper woodland fuel complexes

Treesearch

Rodman R. Linn; Carolyn H. Sieg; Chad M. Hoffman; Judith L. Winterkamp; Joel D. McMillin

2013-01-01

We used a physics-based model, HIGRAD/FIRETEC, to explore changes in within-stand wind behavior and fire propagation associated with three time periods in pinyon-juniper woodlands following a drought-induced bark beetle outbreak and subsequent tree mortality. Pinyon-juniper woodland fuel complexes are highly heterogeneous. Trees often are clumped, with sparse patches...

Comparing models for growth and management of forest tracts

Treesearch

J.J. Colbert; Michael Schuckers; Desta Fekedulegn

2003-01-01

The Stand Damage Model (SDM) is a PC-based model that is easily installed, calibrated and initialized for use in exploring the future growth and management of forest stands or small wood lots. We compare the basic individual tree growth model incorporated in this model with alternative models that predict the basal area growth of trees. The SDM is a gap-type simulator...

Over-expression of FT1 in plum (Prunus domestica) results in phenotypes compatible with spaceflight: a potential new candidate crop for bioregenerative life support systems

USDA-ARS?s Scientific Manuscript database

Tree fruits (e.g., apples, plums, cherries) are appealing constituents of a crew menu for long-duration exploration missions (i.e., Mars), both in terms of their nutritive and menu diversity contributions. Although appealing, tree fruit species have long been precluded as candidate crops for use in...

Exploring the optimal economic timing for crop tree release treatments in hardwoods: results from simulation

Treesearch

Chris B. LeDoux; Gary W. Miller

2008-01-01

In this study we used data from 16 Appalachian hardwood stands, a growth and yield computer simulation model, and stump-to-mill logging cost-estimating software to evaluate the optimal economic timing of crop tree release (CTR) treatments. The simulated CTR treatments consisted of one-time logging operations at stand age 11, 23, 31, or 36 years, with the residual...

Using Forest Inventory and Analysis data to model plant-climate relationships

Treesearch

Nicholas L. Crookston; Gerald E. Rehfeldt; Marcus V. Warwell

2007-01-01

Forest Inventory and Analysis (FIA) data from 11 Western conterminous States were used to (1) estimate and map the climatic profiles of tree species and (2) explore how to include climate variables in individual tree growth equations used in the Forest Vegetation Simulator (FVS). On the first front, we found the FIA data to be useful as training data in Breiman's...

Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

Treesearch

Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew Peters

2013-01-01

Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...

Sampling intensity and normalizations: Exploring cost-driving factors in nationwide mapping of tree canopy cover

Treesearch

John Tipton; Gretchen Moisen; Paul Patterson; Thomas A. Jackson; John Coulston

2012-01-01

There are many factors that will determine the final cost of modeling and mapping tree canopy cover nationwide. For example, applying a normalization process to Landsat data used in the models is important in standardizing reflectance values among scenes and eliminating visual seams in the final map product. However, normalization at the national scale is expensive and...

The NASA SCI Files: The Case of the Galactic Vacation. [Videotape].

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Hampton, VA. Langley Research Center.

The tree house detectives go galactic with their latest project by traveling to Mars and also seeing how the Moon affects the Earth. They visit the largest radio telescope in the world and help look for intelligent life in the universe. The tree house detectives prepare for an out-of-this-world vacation as they explore the future of space travel.…

Repeatability in photo-interpretation of tree canopy cover and its effect on predictive mapping

Treesearch

Thomas A. Jackson; Gretchen G. Moisen; Paul L. Patterson; John Tipton

2012-01-01

In this study, we explore repeatability in photo-interpreted imagery from the National Agriculture Imagery Program that was sampled as part of the National Land Cover Database 2011 Tree Canopy Cover pilot project. Data were collected in 5 diverse pilot areas in the US, including one each in Oregon, Utah, Kansas, Michigan and Georgia. Repeatability metrics. The intra-...

D Semantic Labeling of ALS Data Based on Domain Adaption by Transferring and Fusing Random Forest Models

NASA Astrophysics Data System (ADS)

Wu, J.; Yao, W.; Zhang, J.; Li, Y.

2018-04-01

Labeling 3D point cloud data with traditional supervised learning methods requires considerable labelled samples, the collection of which is cost and time expensive. This work focuses on adopting domain adaption concept to transfer existing trained random forest classifiers (based on source domain) to new data scenes (target domain), which aims at reducing the dependence of accurate 3D semantic labeling in point clouds on training samples from the new data scene. Firstly, two random forest classifiers were firstly trained with existing samples previously collected for other data. They were different from each other by using two different decision tree construction algorithms: C4.5 with information gain ratio and CART with Gini index. Secondly, four random forest classifiers adapted to the target domain are derived through transferring each tree in the source random forest models with two types of operations: structure expansion and reduction-SER and structure transfer-STRUT. Finally, points in target domain are labelled by fusing the four newly derived random forest classifiers using weights of evidence based fusion model. To validate our method, experimental analysis was conducted using 3 datasets: one is used as the source domain data (Vaihingen data for 3D Semantic Labelling); another two are used as the target domain data from two cities in China (Jinmen city and Dunhuang city). Overall accuracies of 85.5 % and 83.3 % for 3D labelling were achieved for Jinmen city and Dunhuang city data respectively, with only 1/3 newly labelled samples compared to the cases without domain adaption.

The ghosts of trees past: savanna trees create enduring legacies in plant species composition.

PubMed

Stahlheber, Karen A; Crispin, Kimberly L; Anton, Cassidy; D'Antonio, Carla M

2015-09-01

Isolated trees in savannas worldwide are known to modify their local environment and interact directly with neighboring plants. Less is known about how related tree species differ in their impacts on surrounding communities, how the effects of trees vary between years, and how composition might change following loss of the tree. To address these knowledge gaps, we explored the following questions: How do savanna trees influence the surrounding composition of herbaceous plants? Is the influence of trees consistent across different species and years? How does this change following the death of the tree? We surveyed herbaceous species composition and environmental attributes surrounding living and dead evergreen and deciduous Quercus trees in California (USA) savannas across several years that differed in their total precipitation. Oak trees of all species created distinct, homogenous understory communities dominated by exotic grasses across several sites. The composition of the low-diversity understory communities showed less interannual variation than open grassland, despite a two-fold difference in precipitation between the driest and wettest year. Vegetation composition was correlated with variation in soil properties, which were strongly affected by trees. Oaks also influenced the communities beyond the edge of the crown, but this depended on site and oak species. Low-diversity understory communities persisted up to 43 years following the death of the tree. A gradual decline in the effect of trees on the physical, environment following death did not result in vegetation becoming more similar to open grassland over time. The presence of long-lasting legacies of past tree crowns highlights the difficulty of assigning control of the current distribution of herbaceous species in grassland to their contemporary environment.

Simulation of land use change in the three gorges reservoir area based on CART-CA

NASA Astrophysics Data System (ADS)

Yuan, Min

2018-05-01

This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

Population Structure of the Primary Malaria Vector in South America, Anopheles darlingi, Using Isozyme, Random Amplified Polymorphic DNA, Internal Transcribed Spacer 2, and Morphologic Markers

DTIC Science & Technology

1999-01-01

distances and identities and Roger?’ genetic distances were clustered by the unweighted pair group method using arithmetic average ( UPGMA ) to produce...Seattle, WA) using the NEIGHBOR program with the UPGMA option and a phenogram was produced with DRAWGRAM, also in PHYLIP 3.X RAPDBOOT5’ was used to...generate 100 pseudoreplicate distance matrices, which were collapsed to form 100 trees with UPGMA . The bootstrap consensus tree was derived from the 100

Quiet planting in the locked constraints satisfaction problems

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

Zdeborova, Lenka; Krzakala, Florent

2009-01-01

We study the planted ensemble of locked constraint satisfaction problems. We describe the connection between the random and planted ensembles. The use of the cavity method is combined with arguments from reconstruction on trees and first and second moment considerations; in particular the connection with the reconstruction on trees appears to be crucial. Our main result is the location of the hard region in the planted ensemble, thus providing hard satisfiable benchmarks. In a part of that hard region instances have with high probability a single satisfying assignment.

A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

NASA Astrophysics Data System (ADS)

Ghosh, Aniruddha; Fassnacht, Fabian Ewald; Joshi, P. K.; Koch, Barbara

2014-02-01

Knowledge of tree species distribution is important worldwide for sustainable forest management and resource evaluation. The accuracy and information content of species maps produced using remote sensing images vary with scale, sensor (optical, microwave, LiDAR), classification algorithm, verification design and natural conditions like tree age, forest structure and density. Imaging spectroscopy reduces the inaccuracies making use of the detailed spectral response. However, the scale effect still has a strong influence and cannot be neglected. This study aims to bridge the knowledge gap in understanding the scale effect in imaging spectroscopy when moving from 4 to 30 m pixel size for tree species mapping, keeping in mind that most current and future hyperspectral satellite based sensors work with spatial resolution around 30 m or more. Two airborne (HyMAP) and one spaceborne (Hyperion) imaging spectroscopy dataset with pixel sizes of 4, 8 and 30 m, respectively were available to examine the effect of scale over a central European forest. The forest under examination is a typical managed forest with relatively homogenous stands featuring mostly two canopy layers. Normalized digital surface model (nDSM) derived from LiDAR data was used additionally to examine the effect of height information in tree species mapping. Six different sets of predictor variables (reflectance value of all bands, selected components of a Minimum Noise Fraction (MNF), Vegetation Indices (VI) and each of these sets combined with LiDAR derived height) were explored at each scale. Supervised kernel based (Support Vector Machines) and ensemble based (Random Forest) machine learning algorithms were applied on the dataset to investigate the effect of the classifier. Iterative bootstrap-validation with 100 iterations was performed for classification model building and testing for all the trials. For scale, analysis of overall classification accuracy and kappa values indicated that 8 m spatial resolution (reaching kappa values of over 0.83) slightly outperformed the results obtained from 4 m for the study area and five tree species under examination. The 30 m resolution Hyperion image produced sound results (kappa values of over 0.70), which in some areas of the test site were comparable with the higher spatial resolution imagery when qualitatively assessing the map outputs. Considering input predictor sets, MNF bands performed best at 4 and 8 m resolution. Optical bands were found to be best for 30 m spatial resolution. Classification with MNF as input predictors produced better visual appearance of tree species patches when compared with reference maps. Based on the analysis, it was concluded that there is no significant effect of height information on tree species classification accuracies for the present framework and study area. Furthermore, in the examined cases there was no single best choice among the two classifiers across scales and predictors. It can be concluded that tree species mapping from imaging spectroscopy for forest sites comparable to the one under investigation is possible with reliable accuracies not only from airborne but also from spaceborne imaging spectroscopy datasets.

Deviation from symmetrically self-similar branching in trees predicts altered hydraulics, mechanics, light interception and metabolic scaling.

PubMed

Smith, Duncan D; Sperry, John S; Enquist, Brian J; Savage, Van M; McCulloh, Katherine A; Bentley, Lisa P

2014-01-01

The West, Brown, Enquist (WBE) model derives symmetrically self-similar branching to predict metabolic scaling from hydraulic conductance, K, (a metabolism proxy) and tree mass (or volume, V). The original prediction was Kα V(0.75). We ask whether trees differ from WBE symmetry and if it matters for plant function and scaling. We measure tree branching and model how architecture influences K, V, mechanical stability, light interception and metabolic scaling. We quantified branching architecture by measuring the path fraction, Pf : mean/maximum trunk-to-twig pathlength. WBE symmetry produces the maximum, Pf = 1.0. We explored tree morphospace using a probability-based numerical model constrained only by biomechanical principles. Real tree Pf ranged from 0.930 (nearly symmetric) to 0.357 (very asymmetric). At each modeled tree size, a reduction in Pf led to: increased K; decreased V; increased mechanical stability; and decreased light absorption. When Pf was ontogenetically constant, strong asymmetry only slightly steepened metabolic scaling. The Pf ontogeny of real trees, however, was 'U' shaped, resulting in size-dependent metabolic scaling that exceeded 0.75 in small trees before falling below 0.65. Architectural diversity appears to matter considerably for whole-tree hydraulics, mechanics, photosynthesis and potentially metabolic scaling. Optimal architectures likely exist that maximize carbon gain per structural investment. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Test Input Generation for Red-Black Trees using Abstraction

NASA Technical Reports Server (NTRS)

Visser, Willem; Pasareanu, Corina S.; Pelanek, Radek

2005-01-01

We consider the problem of test input generation for code that manipulates complex data structures. Test inputs are sequences of method calls from the data structure interface. We describe test input generation techniques that rely on state matching to avoid generation of redundant tests. Exhaustive techniques use explicit state model checking to explore all the possible test sequences up to predefined input sizes. Lossy techniques rely on abstraction mappings to compute and store abstract versions of the concrete states; they explore under-approximations of all the possible test sequences. We have implemented the techniques on top of the Java PathFinder model checker and we evaluate them using a Java implementation of red-black trees.

Random walk on p-adics and hierarchical systems

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

Lukierska-Walasek, K.; Topolski, K.; Institute of Mathematics, Wroclaw University, pl. Grunwaldzki 2/4, 50-384 Wroclaw

2006-02-01

We show that p-adic analysis provides a quite natural basis for the description of relaxation in hierarchical systems. For our purposes, we specify the Markov stochastic process considered by Albeverio and Karwowski. As a result we have obtained a random walk on the p-adic integer numbers, which provides the generalization of Cayley tree proposed by Ogielski and Stein. The temperature-dependent power-law decay and the Kohlrausch law are derived.

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

PubMed Central

Argimón, Silvia; Abudahab, Khalil; Goater, Richard J. E.; Fedosejev, Artemij; Bhai, Jyothish; Glasner, Corinna; Feil, Edward J.; Holden, Matthew T. G.; Yeats, Corin A.; Grundmann, Hajo; Spratt, Brian G.

2016-01-01

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets. PMID:28348833

Seasonality on the rainfall partitioning of a fast-growing tree plantation under Mediterranean conditions

NASA Astrophysics Data System (ADS)

molina, antonio; llorens, pilar; biel, carme

2014-05-01

Studies on rainfall interception in fast-growing tree plantations are less numerous than those in natural forests. Trees in these plantations are regularly distributed, and the canopy cover is clumped but changes quickly, resulting on high variability in the volume and composition of water that reach the soil. In addition, irrigation supply is normally required in semiarid areas to get optimal wood production; consequently, knowing rainfall interception and its yearly evolution is crucial to manage the irrigation scheme properly. This work studies the rainfall partitioning seasonality in a cherry tree (Prunus avium) plantation orientated to timber production under Mediterranean conditions. The monitoring design started on March 2012 and consists of a set of 58 throughfall tipping buckets randomly distributed (based on a 1x1 m2 grid) in a plot of 128 m2 with 8 trees. Stemflow is measured in all the trees with 2 tipping buckets and 6 accumulative collectors. Canopy cover is regularly measured throughout the study period, in leaf and leafless periods, by mean of sky-orientated photographs taken 50 cm above the center of each tipping bucket. Others tree biometrics are also measured such as diameter and leaf area index. Meteorological conditions are measured at 2 m above the forest cover. This work presents the first analyses describing the rainfall partitioning and its dependency on canopy cover, distance to tree and meteorological conditions. The modified Gash' model for rainfall interception in dispersed vegetation is also preliminary evaluated.

Shade tree spatial structure and pod production explain frosty pod rot intensity in cacao agroforests, Costa Rica.

PubMed

Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo

2014-03-01

Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.

Influence of matrix type on tree community assemblages along tropical dry forest edges.

PubMed

Benítez-Malvido, Julieta; Gallardo-Vásquez, Julio César; Alvarez-Añorve, Mariana Y; Avila-Cabadilla, Luis Daniel

2014-05-01

• Anthropogenic habitat edges have strong negative consequences for the functioning of tropical ecosystems. However, edge effects on tropical dry forest tree communities have been barely documented.• In Chamela, Mexico, we investigated the phylogenetic composition and structure of tree assemblages (≥5 cm dbh) along edges abutting different matrices: (1) disturbed vegetation with cattle, (2) pastures with cattle and, (3) pastures without cattle. Additionally, we sampled preserved forest interiors.• All edge types exhibited similar tree density, basal area and diversity to interior forests, but differed in species composition. A nonmetric multidimensional scaling ordination showed that the presence of cattle influenced species composition more strongly than the vegetation structure of the matrix; tree assemblages abutting matrices with cattle had lower scores in the ordination. The phylogenetic composition of tree assemblages followed the same pattern. The principal plant families and genera were associated according to disturbance regimes as follows: pastures and disturbed vegetation (1) with cattle and (2) without cattle, and (3) pastures without cattle and interior forests. All habitats showed random phylogenetic structures, suggesting that tree communities are assembled mainly by stochastic processes. Long-lived species persisting after edge creation could have important implications in the phylogenetic structure of tree assemblages.• Edge creation exerts a stronger influence on TDF vegetation pathways than previously documented, leading to new ecological communities. Phylogenetic analysis may, however, be needed to detect such changes. © 2014 Botanical Society of America, Inc.

The algebra of the general Markov model on phylogenetic trees and networks.

PubMed

Sumner, J G; Holland, B R; Jarvis, P D

2012-04-01

It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the “splitting” operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications.

Age class, longevity and growth rate relationships: protracted growth increases in old trees in the eastern United States.

PubMed

Johnson, Sarah E; Abrams, Marc D

2009-11-01

This study uses data from the International Tree-Ring Data Bank website and tree cores collected in the field to explore growth rate (basal area increment, BAI) relationships across age classes (from young to old) for eight tree species in the eastern US. These species represent a variety of ecological traits and include those in the genera Populus, Quercus, Pinus, Tsuga and Nyssa. We found that most trees in all age classes and species exhibit an increasing BAI throughout their lives. This is particularly unusual for trees in the older age classes that we expected to have declining growth in the later years, as predicted by physiological growth models. There exists an inverse relationship between growth rate and increasing age class. The oldest trees within each species have consistently slow growth throughout their lives, implying an inverse relationship between growth rate and longevity. Younger trees (< 60 years of age) within each species are consistently growing faster than the older trees when they are of the same age resulting from a higher proportion of fast-growing trees in these young age classes. Slow, but increasing, BAI in the oldest trees in recent decades is a continuation of their growth pattern established in previous centuries. The fact that they have not shown a decreasing growth rate in their old age contradicts physiological growth models and may be related to the stimulatory effects of global change phenomenon (climate and land-use history).

Flowering phenology and its implications for management of big-leaf mahogany Swietenia macrophylla in Brazilian Amazonia.

PubMed

Grogan, James; Loveless, Marilyn D

2013-11-01

Flowering phenology is a crucial determinant of reproductive success and offspring genetic diversity in plants. We measure the flowering phenology of big-leaf mahogany (Swietenia macrophylla, Meliaceae), a widely distributed neotropical tree, and explore how disturbance from logging impacts its reproductive biology. We use a crown scoring system to estimate the timing and duration of population-level flowering at three forest sites in the Brazilian Amazon over a five-year period. We combine this information with data on population structure and spatial distribution to consider the implications of logging for population flowering patterns and reproductive success. Mahogany trees as small as 14 cm diam flowered, but only trees > 30 cm diam flowered annually or supra-annually. Mean observed flowering periods by focal trees ranged from 18-34 d, and trees flowered sequentially during 3-4 mo beginning in the dry season. Focal trees demonstrated significant interannual correlation in flowering order. Estimated population-level flowering schedules resembled that of the focal trees, with temporal isolation between early and late flowering trees. At the principal study site, conventional logging practices eliminated 87% of mahogany trees > 30 cm diam and an estimated 94% of annual pre-logging floral effort. Consistent interannual patterns of sequential flowering among trees create incompletely isolated subpopulations, constraining pollen flow. After harvests, surviving subcommercial trees will have fewer, more distant, and smaller potential partners, with probable consequences for post-logging regeneration. These results have important implications for the sustainability of harvesting systems for tropical timber species.

Enumeration of spanning trees in planar unclustered networks

NASA Astrophysics Data System (ADS)

Xiao, Yuzhi; Zhao, Haixing; Hu, Guona; Ma, Xiujuan

2014-07-01

Among a variety of subgraphs, spanning trees are one of the most important and fundamental categories. They are relevant to diverse aspects of networks, including reliability, transport, self-organized criticality, loop-erased random walks and so on. In this paper, we introduce a family of modular, self-similar planar networks with zero clustering. Relevant properties of this family are comparable to those networks associated with technological systems having low clustering, like power grids, some electronic circuits, the Internet and some biological systems. So, it is very significant to research on spanning trees of planar networks. However, for a large network, evaluating the relevant determinant is intractable. In this paper, we propose a fairly generic linear algorithm for counting the number of spanning trees of a planar network. Using the algorithm, we derive analytically the exact numbers of spanning trees in planar networks. Our result shows that the computational complexity is O(t) , which is better than that of the matrix tree theorem with O(m2t2) , where t is the number of steps and m is the girth of the planar network. We also obtain the entropy for the spanning trees of a given planar network. We find that the entropy of spanning trees in the studied network is small, which is in sharp contrast to the previous result for planar networks with the same average degree. We also determine an upper bound and a lower bound for the numbers of spanning trees in the family of planar networks by the algorithm. As another application of the algorithm, we give a formula for the number of spanning trees in an outerplanar network with small-world features.

Important LiDAR metrics for discriminating forest tree species in Central Europe

NASA Astrophysics Data System (ADS)

Shi, Yifang; Wang, Tiejun; Skidmore, Andrew K.; Heurich, Marco

2018-03-01

Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe.

Diversity Dynamics in Nymphalidae Butterflies: Effect of Phylogenetic Uncertainty on Diversification Rate Shift Estimates

PubMed Central

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution. PMID:25830910

Diversity dynamics in Nymphalidae butterflies: effect of phylogenetic uncertainty on diversification rate shift estimates.

PubMed

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution.

TSEMA: interactive prediction of protein pairings between interacting families

PubMed Central

Izarzugaza, José M. G.; Juan, David; Pons, Carles; Ranea, Juan A. G.; Valencia, Alfonso; Pazos, Florencio

2006-01-01

An entire family of methodologies for predicting protein interactions is based on the observed fact that families of interacting proteins tend to have similar phylogenetic trees due to co-evolution. One application of this concept is the prediction of the mapping between the members of two interacting protein families (which protein within one family interacts with which protein within the other). The idea is that the real mapping would be the one maximizing the similarity between the trees. Since the exhaustive exploration of all possible mappings is not feasible for large families, current approaches use heuristic techniques which do not ensure the best solution to be found. This is why it is important to check the results proposed by heuristic techniques and to manually explore other solutions. Here we present TSEMA, the server for efficient mapping assessment. This system calculates an initial mapping between two families of proteins based on a Monte Carlo approach and allows the user to interactively modify it based on performance figures and/or specific biological knowledge. All the explored mappings are graphically shown over a representation of the phylogenetic trees. The system is freely available at . Standalone versions of the software behind the interface are available upon request from the authors. PMID:16845017

[Single shot fast spin echo sequence MRI cholangiopancreatography].

PubMed

Lefèvre, F; Crouzet, P; Gaucher, H; Chapuis, F; Béot, S; Boccaccini, H; Bazin, C; Régent, D

1998-05-01

To assess the value of single shot fast spin echo MR sequence (SS-FSE) in the morphological analysis of the biliary tree and pancreatic ducts and to compare its accuracy with other imaging methods. 95 consecutive patients referred for clinical and/or biological suspicion of biliary obstruction were explored with MR cholangiopancreatography (MRCP). All patients were explored with a Signa 1.5 T GE MR unit, with High Gradient Field Strength and Torso Phased Array Coil. Biliary ducts were explored with SS-FSE sequence, coronal and oblique coronal 20 mm thick slices on a 256 x 256 matrix. Total acquisition time was 1 second. Native pictures were reviewed by two radiologists blinded to clinical information. In case of disagreement, a third radiologist's judgement was requested. In 88 cases, MRCP results were compared with direct biligraphy methods. In all cases, MRCP produced high quality images without MIP or other post-processing methods. For detection of biliary tree distensions, the concordance value of MRCP was over 91% (Kappa 0.82). For detection of biliary tree and/or pancreatic duct obstruction, MR sensitivity was 100% and specificity 91%. The overall diagnostic concordance value of MRCP was > or = 93%. Difficulties in MRCP were caused by functional diseases or benign stenosis. MRCP accurately diagnosed all lithiasic obstructions starting from a stone size of 3 mm. MRCP produces fastly high-quality images. As it is totally safe, it can be proposed as a first intention method in biliopancreatic duct explorations.

Universal scaling in the branching of the tree of life.

PubMed

Herrada, E Alejandro; Tessone, Claudio J; Klemm, Konstantin; Eguíluz, Víctor M; Hernández-García, Emilio; Duarte, Carlos M

2008-07-23

Understanding the patterns and processes of diversification of life in the planet is a key challenge of science. The Tree of Life represents such diversification processes through the evolutionary relationships among the different taxa, and can be extended down to intra-specific relationships. Here we examine the topological properties of a large set of interspecific and intraspecific phylogenies and show that the branching patterns follow allometric rules conserved across the different levels in the Tree of Life, all significantly departing from those expected from the standard null models. The finding of non-random universal patterns of phylogenetic differentiation suggests that similar evolutionary forces drive diversification across the broad range of scales, from macro-evolutionary to micro-evolutionary processes, shaping the diversity of life on the planet.

International Conference on Random Mappings, Partitions and Permutations Held in Los Angeles, California on 3-6 January 1992

DTIC Science & Technology

1992-08-01

cryptography to the simula- tion of epidemic processes and tests of the intrinsic randomness of quantum mechanics. Discussed in this paper are... theorem concerning the height of a random labelled rooted tree [4]; letting f( s ) = ½ + 82, G(t) = 1 - e-t if t > 0, G(t) = 0 otherwise, and A (0], p...o thi cOoection of infromaltion.% no|uaing• viggitIOns for riviucirg this curoon. to WasnaImllor "@as s n o w, i-i1it,"ersondO Daisr hqhvhwao. SWite

Scaling Limits and Generic Bounds for Exploration Processes

NASA Astrophysics Data System (ADS)

Bermolen, Paola; Jonckheere, Matthieu; Sanders, Jaron

2017-12-01

We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its neighboring nodes become blocked. Given an initial number of vertices N growing to infinity, we study statistical properties of the proportion of explored (active or blocked) nodes in time using scaling limits. We obtain exact limits for homogeneous graphs and prove an explicit central limit theorem for the final proportion of active nodes, known as the jamming constant, through a diffusion approximation for the exploration process which can be described as a unidimensional process. We then focus on bounding the trajectories of such exploration processes on random geometric graphs, i.e., random sequential adsorption. As opposed to exploration processes on homogeneous random graphs, these do not allow for such a dimensional reduction. Instead we derive a fundamental relationship between the number of explored nodes and the discovered volume in the spatial process, and we obtain generic bounds for the fluid limit and jamming constant: bounds that are independent of the dimension of space and the detailed shape of the volume associated to the discovered node. Lastly, using coupling techinques, we give trajectorial interpretations of the generic bounds.

The role of earlywood and latewood properties on dimensional stability of loblolly pine

Treesearch

David E. Kretschmann; Steven M. Cramer

2007-01-01

The role of tree ring location and height within tree has a very significant impact on the properties of earlywood and latewood. This paper explores the role of earlywood and latewood properties on the dimensional stability of loblolly pine. Test results from isolated 1 mm by 1 mm by 30 mm pieces of earlywood and latewood show the differences in earlywood and latewood...

Seasonal carbohydrate dynamics and growth in Douglas-fir trees experiencing chronic, fungal-mediated reduction in functional leaf area

Treesearch

B. J. Saffell; F. C. Meinzer; D. R. Woodruff; D. C. Shaw; S. L. Voelker; B. Lachenbruch; K. Falk

2014-01-01

Stored non-structural carbohydrates (NSCs) could play an important role in tree survival in the face of a changing climate and associated stress-related mortality. We explored the effects of the stomata-blocking and defoliating fungal disease called Swiss needle cast on Douglas-fir carbohydrate reserves and growth to evaluate the extent to which NSCs can be mobilized...

Problem Solving and Learning in a Natural Task Domain

DTIC Science & Technology

1988-09-01

algorithm is demonstrated in two further examples. For clarity, all examples present a single path through the causal model, rather than the tree ...Any implications are added to the list. EDSEL1 keeps recent chains of reasoning. The tree form of any explorations is retained for future reasoning...9) (CAUSE (CRANK CRANKSHAFT) (OVEVIENT CAMSHAFT ) 9) (CAUSE (CRANK CRANKSHAFT) (TUR:N DRIVESHAFT) 9) STARTER (CAUSE (SWITCH-ACTION SOLENOID ON

Exploring the Bilingualism of a Migrant Community through Language Dominance

ERIC Educational Resources Information Center

Santello, Marco

2014-01-01

This study outlines a linguistic profile of two subgroups of Italian English circumstantial bilinguals - one dominant in English and the other dominant in Italian--by exploring for the first time their linguistic repertoire through the Gradient Bilingual Dominance Scale (Dunn & Fox Tree, 2009). The scale takes into account language…

Shelterwood Teacher's Guide: Discovering the Forest.

ERIC Educational Resources Information Center

Markowsky, Judy Kellogg

This teacher's guide explores forest diversity, from learning about different kind of trees to understanding how the layers in a forest provide habitat for all kinds of animals and insects. Each chapter offers useful introductory material and clear objectives, followed by fun activities that encourage exploration while teaching important skills.…

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PubMed

Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien

2015-09-01

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Categorizing Ideas about Trees: A Tree of Trees

PubMed Central

Fisler, Marie; Lecointre, Guillaume

2013-01-01

The aim of this study is to explore whether matrices and MP trees used to produce systematic categories of organisms could be useful to produce categories of ideas in history of science. We study the history of the use of trees in systematics to represent the diversity of life from 1766 to 1991. We apply to those ideas a method inspired from coding homologous parts of organisms. We discretize conceptual parts of ideas, writings and drawings about trees contained in 41 main writings; we detect shared parts among authors and code them into a 91-characters matrix and use a tree representation to show who shares what with whom. In other words, we propose a hierarchical representation of the shared ideas about trees among authors: this produces a “tree of trees.” Then, we categorize schools of tree-representations. Classical schools like “cladists” and “pheneticists” are recovered but others are not: “gradists” are separated into two blocks, one of them being called here “grade theoreticians.” We propose new interesting categories like the “buffonian school,” the “metaphoricians,” and those using “strictly genealogical classifications.” We consider that networks are not useful to represent shared ideas at the present step of the study. A cladogram is made for showing who is sharing what with whom, but also heterobathmy and homoplasy of characters. The present cladogram is not modelling processes of transmission of ideas about trees, and here it is mostly used to test for proximity of ideas of the same age and for categorization. PMID:23950877

Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation.

PubMed

Serdukova, Larissa; Zheng, Yayun; Duan, Jinqiao; Kurths, Jürgen

2017-08-24

For the tipping elements in the Earth's climate system, the most important issue to address is how stable is the desirable state against random perturbations. Extreme biotic and climatic events pose severe hazards to tropical rainforests. Their local effects are extremely stochastic and difficult to measure. Moreover, the direction and intensity of the response of forest trees to such perturbations are unknown, especially given the lack of efficient dynamical vegetation models to evaluate forest tree cover changes over time. In this study, we consider randomness in the mathematical modelling of forest trees by incorporating uncertainty through a stochastic differential equation. According to field-based evidence, the interactions between fires and droughts are a more direct mechanism that may describe sudden forest degradation in the south-eastern Amazon. In modeling the Amazonian vegetation system, we include symmetric α-stable Lévy perturbations. We report results of stability analysis of the metastable fertile forest state. We conclude that even a very slight threat to the forest state stability represents L´evy noise with large jumps of low intensity, that can be interpreted as a fire occurring in a non-drought year. During years of severe drought, high-intensity fires significantly accelerate the transition between a forest and savanna state.

Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

NASA Astrophysics Data System (ADS)

Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

2018-02-01

A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

[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.

Time Series of Images to Improve Tree Species Classification

NASA Astrophysics Data System (ADS)

Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.

2017-10-01

Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.

3D Forest: An application for descriptions of three-dimensional forest structures using terrestrial LiDAR

PubMed Central

Krůček, Martin; Vrška, Tomáš; Král, Kamil

2017-01-01

Terrestrial laser scanning is a powerful technology for capturing the three-dimensional structure of forests with a high level of detail and accuracy. Over the last decade, many algorithms have been developed to extract various tree parameters from terrestrial laser scanning data. Here we present 3D Forest, an open-source non-platform-specific software application with an easy-to-use graphical user interface with the compilation of algorithms focused on the forest environment and extraction of tree parameters. The current version (0.42) extracts important parameters of forest structure from the terrestrial laser scanning data, such as stem positions (X, Y, Z), tree heights, diameters at breast height (DBH), as well as more advanced parameters such as tree planar projections, stem profiles or detailed crown parameters including convex and concave crown surface and volume. Moreover, 3D Forest provides quantitative measures of between-crown interactions and their real arrangement in 3D space. 3D Forest also includes an original algorithm of automatic tree segmentation and crown segmentation. Comparison with field data measurements showed no significant difference in measuring DBH or tree height using 3D Forest, although for DBH only the Randomized Hough Transform algorithm proved to be sufficiently resistant to noise and provided results comparable to traditional field measurements. PMID:28472167

Effects of Irrigation with Treated Wastewater on Root and Fruit Mineral Elements of Chemlali Olive Cultivar

PubMed Central

Bedbabis, Saida; Ben Rouina, Béchir; Boukhris, Makki

2014-01-01

Twenty-year-old “Chemlali” olive trees trained to vase and rainfed were investigated in either “on” (2004) or “off” (2003) year. A randomized block design with three blocks and three treatments was used and each experimental plot consisted of nine olive trees. Three treatments were applied: (1) rainfed conditions (RF, used as control treatment); (2) irrigation with well water (WW); and (3) irrigation with treated wastewater (TWW). Irrigation with TWW led to a significant increase of root N, P, Ca, Zn, Mn, Na, and Cl concentrations, in particular in the on-year. Data showed significant differences, between the two years, for the concentration of the mineral elements in the roots, with general lower values in the on-year, probably as a consequence of nutrients movement upward in the tree. Fruit N, P, K, Zn, Mn, and Cl contents were significantly higher in TWW irrigated trees with respect to both RF and WW trees, whereas similar values for Ca, Mg, Na, and Cl contents were measured for WW and TWW irrigated trees. The irrigation with TWW allowed to reuse problematic waters and to save nutrients inputs in the olive orchard thus moving towards a more sustainable management of olive orchards in countries where water is the major limiting factor for agriculture. PMID:25013873

Reproductive Ecology of Male and Female Strobili and Mating System in Two Different Populations of Pinus roxburghii

PubMed Central

Sharma, Chandra Mohan; Khanduri, Vinod Prasad; Ghildiyal, Sunil Kumar

2012-01-01

We studied several flowering traits, namely, male-female cone phenology, male-female cone production per tree, mating system, sex ratio, air-borne pollen grains and pollen migration, over four successive years in two different natural populations of P. roxburghii from Garhwal Himalaya, India. Assessment of each trait mentioned except pollen dispersion was done by selecting five representative trees randomly in each population. The pollen migration was studied on naturally isolated source trees. The pollen trapping was done in all directions up to 2.5 km. The average reproductive period in P. roxburghii was 36 days with 3–5 days protandry. There were significant year and population effects for male and female cone output and pollen grains production per tree. In mass production year (1999), an average production of pollen cone per tree was estimated as 42.44 ± 8.32 × 103 at lower altitude and 28.1 ± 0.89 × 103 at higher altitude. The controlled pollination results in high level of outcrossing with 90% seed setting. We conclude that the high male-female ratio and tremendous pollen production capacity in P. roxburghii indicate high male competition among trees within populations. The isolation strip of 600 m is considered minimal for the management of seed orchard. PMID:22654581

Exploiting machine learning algorithms for tree species classification in a semiarid woodland using RapidEye image

NASA Astrophysics Data System (ADS)

Adelabu, Samuel; Mutanga, Onisimo; Adam, Elhadi; Cho, Moses Azong

2013-01-01

Classification of different tree species in semiarid areas can be challenging as a result of the change in leaf structure and orientation due to soil moisture constraints. Tree species mapping is, however, a key parameter for forest management in semiarid environments. In this study, we examined the suitability of 5-band RapidEye satellite data for the classification of five tree species in mopane woodland of Botswana using machine leaning algorithms with limited training samples.We performed classification using random forest (RF) and support vector machines (SVM) based on EnMap box. The overall accuracies for classifying the five tree species was 88.75 and 85% for both SVM and RF, respectively. We also demonstrated that the new red-edge band in the RapidEye sensor has the potential for classifying tree species in semiarid environments when integrated with other standard bands. Similarly, we observed that where there are limited training samples, SVM is preferred over RF. Finally, we demonstrated that the two accuracy measures of quantity and allocation disagreement are simpler and more helpful for the vast majority of remote sensing classification process than the kappa coefficient. Overall, high species classification can be achieved using strategically located RapidEye bands integrated with advanced processing algorithms.

Reproductive ecology of male and female Strobili and mating system in two different populations of Pinus roxburghii.

PubMed

Sharma, Chandra Mohan; Khanduri, Vinod Prasad; Ghildiyal, Sunil Kumar

2012-01-01

We studied several flowering traits, namely, male-female cone phenology, male-female cone production per tree, mating system, sex ratio, air-borne pollen grains and pollen migration, over four successive years in two different natural populations of P. roxburghii from Garhwal Himalaya, India. Assessment of each trait mentioned except pollen dispersion was done by selecting five representative trees randomly in each population. The pollen migration was studied on naturally isolated source trees. The pollen trapping was done in all directions up to 2.5 km. The average reproductive period in P. roxburghii was 36 days with 3-5 days protandry. There were significant year and population effects for male and female cone output and pollen grains production per tree. In mass production year (1999), an average production of pollen cone per tree was estimated as 42.44 ± 8.32 × 10(3) at lower altitude and 28.1 ± 0.89 × 10(3) at higher altitude. The controlled pollination results in high level of outcrossing with 90% seed setting. We conclude that the high male-female ratio and tremendous pollen production capacity in P. roxburghii indicate high male competition among trees within populations. The isolation strip of 600 m is considered minimal for the management of seed orchard.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

Tree leaves extraction in natural images: comparative study of preprocessing tools and segmentation methods.

PubMed

Grand-Brochier, Manuel; Vacavant, Antoine; Cerutti, Guillaume; Kurtz, Camille; Weber, Jonathan; Tougne, Laure

2015-05-01

In this paper, we propose a comparative study of various segmentation methods applied to the extraction of tree leaves from natural images. This study follows the design of a mobile application, developed by Cerutti et al. (published in ReVeS Participation--Tree Species Classification Using Random Forests and Botanical Features. CLEF 2012), to highlight the impact of the choices made for segmentation aspects. All the tests are based on a database of 232 images of tree leaves depicted on natural background from smartphones acquisitions. We also propose to study the improvements, in terms of performance, using preprocessing tools, such as the interaction between the user and the application through an input stroke, as well as the use of color distance maps. The results presented in this paper shows that the method developed by Cerutti et al. (denoted Guided Active Contour), obtains the best score for almost all observation criteria. Finally, we detail our online benchmark composed of 14 unsupervised methods and 6 supervised ones.

Effectivity of Azotobacter chroococcum and arbuscular mycorrhiza fungi on physiological characteristics and growth of cocoa seedlings

NASA Astrophysics Data System (ADS)

Nasaruddin; Ridwan, I.

2018-05-01

This study aims to study the effectiveness of Azotobacter chroococcum bacteria and Arbuscula mycorrhiza on some physiological characteristics and growth of cocoa seedlings. The study was conducted from March to October 2015, designed in the form of a two factors experiment based on the Randomized Block Design in a screen house. Inoculation of A chroococcum as the first factor consisted of control, inoculation of 104 CFU ml-1 water and 106 CFU ml-1 water per tree given as much as 40 ml. Inoculation of arbuscula mycorrhiza as a second factor consisted of control, inoculation of 3.0 g, 6.0 g and 9.0 g per tree, respectively. The experimental results show that inoculation of Azotobacter chroococcum 106 CFU ml-1 water tree-1 and the arbuscular mycorrhizal fungi 6.0 g tree-1 resulted in higher chlorophyll a, b and total leaf chlorophyll content, increased light absorption rate, leaf stomatal conductance and better seedling growth.

Habitat characteristics of American woodcock nest sites on a managed area in Maine

USGS Publications Warehouse

McAuley, D.G.; Longcore, J.R.; Sepik, G.F.; Pendleton, G.W.

1996-01-01

We measured characteristics of habitat near 89 nests of American woodcock (Scolopax minor) and 100 randomly selected points on Moosehorn National Wildlife Refuge, Calais, Maine, an area managed for woodcock. At nest sites, basal area was lower (P 0.05) or between sites of successful nests and nests destroyed by predators, although the large variances of the variables reduced our power to detect differences. Habitat around sites of renests differed from sites of first nests. Sites around first nests had lower basal area of dead trees (P = 0.05) and higher stem densities of aspen (P = 0.03) and cherry saplings (P = 0.001), and viburnum (P = 0.05), while renest sites had taller trees (P = 0.02). The change from nest sites in areas dominated by alders and tree-size gray birch used in 1977-80 to sites dominated by sapling trees, especially aspen, used during 1987-90 suggests that woodcock in the expanding population at the refuge are selecting nest sites created by habitat management since 1979.

Microwave remote sensing and radar polarization signatures of natural fields

NASA Technical Reports Server (NTRS)

Mo, Tsan

1989-01-01

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Molecular performance of commercial MTG variety oil palm based on RAPD markers

NASA Astrophysics Data System (ADS)

Putri, L. A. P.; Setyo, I. E.; Basyuni, M.; Bayu, E. S.; Setiado, H.; Reynaldi, N. F.; Laia, H.; Puteri, S. A. K.; Arifiyanto, D.; Syahputra, I.

2018-02-01

The oil palm, an economically important tree in Indonesia, has been one of the world’s major sources of edible oil and a significant precursor of biodiesel fuel. This research is conducted by taking individual tree sample of commercial MTG variety germplasm oil palm one years old. The purpose of this research is to analyse molecular performance of some oil palm MTG variety based on RAPD markers. In this experiment, the DNA profile diversity was assessed using markers of oil palm’s random RAPD markers (OPD-20, SB-19, OPM-01 and OPO-11). A total of 15 trees commercial MTG oil palm variety were used for analysis. The results of the experiment indicated out of 4 RAPD markers (OPD-20, SB-19, OPM-01 and OPO-11) showed polymorphic of PCR product. These preliminary results demonstrated RAPD marker can be used to evaluate genetic relatedness among trees of commercial MTG variety oil palm and detecting either genetic variants or mislabelled.

Evaluation of Agrilus planipennis (Coleoptera: Buprestidae) control provided by emamectin benzoate and two neonicotinoid insecticides, one and two seasons after treatment.

PubMed

McCullough, Deborah G; Poland, Therese M; Anulewicz, Andrea C; Lewis, Phillip; Cappaert, David

2011-10-01

Effective methods are needed to protect ash trees (Fraxinus spp.) from emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), an invasive buprestid that has killed millions of North American ash (Fraxinus spp.) trees. We randomly assigned 175 ash trees (11.5-48.1 cm in diameter) in 25 blocks located in three study sites in Michigan to one of seven insecticide treatments in May 2007. Treatments included 1) trunk-injected emamectin benzoate; 2) trunk-injected imidacloprid; 3) basal trunk spray of dinotefuran with or 4) without Pentra-Bark, an agricultural surfactant; 5) basal trunk spray of imidacloprid with or 6) without Pentra-Bark; or (7) control. Foliar insecticide residues (enzyme-linked immunosorbent assay) and toxicity of leaves to adult A. planipennis (4-d bioassays) were quantified at 3-4-wk intervals posttreatment. Seven blocks of trees were felled and sampled in fall 2007 to quantify A. planipennis larval density. Half of the remaining blocks were retreated in spring 2008. Bioassays and residue analyses were repeated in summer 2008, and then all trees were sampled to assess larval density in winter. Foliage from emamectin benzoate-treated trees was highly toxic to adult A. planipennis, and larval density was < 1% of that in comparable control trees, even two seasons posttreatment. Larval densities in trees treated with trunk-injected imidacloprid in 2007 + 2008 were similar to control trees. Dinotefuran and imidacloprid were effectively translocated within trees treated with the noninvasive basal trunk sprays; the surfactant did not appreciably enhance A. planipennis control. In 2008, larval densities were 57-68% lower in trees treated with dinotefuran or imidacloprid trunk sprays in 2007 + 2008 than on controls, but densities in trees treated only in 2007 were similar to controls. Highly effective control provided by emamectin benzoate for > or = 2 yr may reduce costs or logistical issues associated with treatment.

Efficient random access high resolution region-of-interest (ROI) image retrieval using backward coding of wavelet trees (BCWT)

NASA Astrophysics Data System (ADS)

Corona, Enrique; Nutter, Brian; Mitra, Sunanda; Guo, Jiangling; Karp, Tanja

2008-03-01

Efficient retrieval of high quality Regions-Of-Interest (ROI) from high resolution medical images is essential for reliable interpretation and accurate diagnosis. Random access to high quality ROI from codestreams is becoming an essential feature in many still image compression applications, particularly in viewing diseased areas from large medical images. This feature is easier to implement in block based codecs because of the inherent spatial independency of the code blocks. This independency implies that the decoding order of the blocks is unimportant as long as the position for each is properly identified. In contrast, wavelet-tree based codecs naturally use some interdependency that exploits the decaying spectrum model of the wavelet coefficients. Thus one must keep track of the decoding order from level to level with such codecs. We have developed an innovative multi-rate image subband coding scheme using "Backward Coding of Wavelet Trees (BCWT)" which is fast, memory efficient, and resolution scalable. It offers far less complexity than many other existing codecs including both, wavelet-tree, and block based algorithms. The ROI feature in BCWT is implemented through a transcoder stage that generates a new BCWT codestream containing only the information associated with the user-defined ROI. This paper presents an efficient technique that locates a particular ROI within the BCWT coded domain, and decodes it back to the spatial domain. This technique allows better access and proper identification of pathologies in high resolution images since only a small fraction of the codestream is required to be transmitted and analyzed.

The Concept of Cosmic Tree in Armenian and Iranian Cosmologies

NASA Astrophysics Data System (ADS)

Farmanyan, S. V.; Mickaelian, A. M.

2016-09-01

Cosmic Tree or Tree of Life is a common motif in various world theologies, mythologies, and philosophies. In the present study we focus on Armenian and Iranian Cosmic Tree. In ancient Armenia, the Tree of Life (Կենաց Ծառ) is a religious symbol and is drawn on walls of fortresses and carved on the armour of warriors. According to ancient Armenians the center of the Universe is located at the crown of the tree or the column, which is the closest to the sky. We explore the idea of cosmic tree in the riddles, prayers, medieval rituals and miniatures. In the riddles, the tree mostly symbolizes the celestial phenomena (Sun, Stars, and Heavens), different units of time (years, months, weeks, days, and seasons), the people, Jerusalem, the apostles and Jesus Christ. The branches of the tree were equally divided on the right and left sides of the stem, with each branch having one leaf, and one leaf on the apex of the tree. Servants stood on each side of the tree with one of their hands up as if they are taking care of the tree. In pre-Islamic Persian mythology, the Gaokerena world tree is a large, sacred Haoma tree which bears all seeds. Ahriman created a frog to invade the tree and destroy it, aiming at preventing all trees from growing on the Earth. As a reaction, God (Ahura Mazda) created two kar fish staring at the frog to guard the tree. The concept of world tree in Persian Mythology is very closely related to the concept of the Tree of Life. Another related issue in ancient mythology of Iran is the myth of Mashya and Mashyane, two trees who were the ancestors of all living beings. This myth can be considered as a prototype for the creation myth where living beings are created by Gods (who have human forms). We come to the conclusion that in both cultures, no matter of the present different religions, the perception of Cosmic Tree is interconnected to the life on our planet and served as a metaphor for common descent in the evolutionary sense.

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

PubMed Central

dos Santos, Matheus; Ribeiro, Pedro Otávio; Núñez, Pedro; Botelho, Silvia

2017-01-01

The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS) are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper. PMID:28961163

Vertical stratification of the foliar fungal community in the world's tallest trees.

PubMed

Harrison, Joshua G; Forister, Matthew L; Parchman, Thomas L; Koch, George W

2016-12-01

The aboveground tissues of plants host numerous, ecologically important fungi, yet patterns in the spatial distribution of these fungi remain little known. Forest canopies in particular are vast reservoirs of fungal diversity, but intracrown variation in fungal communities has rarely been explored. Knowledge of how fungi are distributed throughout tree crowns will contribute to our understanding of interactions between fungi and their host trees and is a first step toward investigating drivers of community assembly for plant-associated fungi. Here we describe spatial patterns in fungal diversity within crowns of the world's tallest trees, coast redwoods (Sequoia sempervirens). We took a culture-independent approach, using the Illumina MiSeq platform, to characterize the fungal assemblage at multiple heights within the crown across the geographical range of the coast redwood. Within each tree surveyed, we uncovered evidence for vertical stratification in the fungal community; different portions of the tree crown harbored different assemblages of fungi. We also report between-tree variation in the fungal community within redwoods. Our results suggest the potential for vertical stratification of fungal communities in the crowns of other tall tree species and should prompt future study of the factors giving rise to this stratification. © 2016 Botanical Society of America.

The potential of high resolution airborne laser scanning for deriving geometric properties of single trees

NASA Astrophysics Data System (ADS)

Morsdorf, F.; Meier, E.; Koetz, B.; Nüesch, D.; Itten, K.; Allgöwer, B.

2003-04-01

The potential of airborne laserscanning for mapping forest stands has been intensively evaluated in the past few years. Algorithms deriving structural forest parameters in a stand-wise manner from laser data have been successfully implemented by a number of researchers. However, with very high point density laser (>20 points/m^2) data we pursue the approach of deriving these parameters on a single-tree basis. We explore the potential of delineating single trees from laser scanner raw data (x,y,z- triples) and validate this approach with a dataset of more than 2000 georeferenced trees, including tree height and crown diameter, gathered on a long term forest monitoring site by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The accuracy of the laser scanner is evaluated trough 6 reference targets, being 3x3 m^2 in size and horizontally plain, for validating both the horizontal and vertical accuracy of the laser scanner by matching of triangular irregular networks (TINs). Single trees are segmented by a clustering analysis in all three coordinate dimensions and their geometric properties can then be derived directly from the tree cluster.

Cordia dichotoma G. Forst. : Bioecology and population density

NASA Astrophysics Data System (ADS)

Rahayu, E. S.; Martin, P.; Dewi, N. K.; Kurniawan, F. H.

2017-04-01

Kendal tree is declared as an identity flora of Kendal Regency, Central Java, Indonesia. It is predicted as a rare species; most of the local people do not know the existence of this tree. The study aimed to describe some aspects of bioecology and a population density of Kendal tree. An explorative study was conducted from March to July 2016, through interview, observation, and literature review. The respondents were determined by purposive and snowball sampling methods. The data were analysed descriptively. Results showed that there were very limited numbers (only five trees) of Kendal tree throughout Kendal Regency. The species was identified as Cordia dichotoma G. Forst. The tree is 3-15 m in height. The leaves are simple and arranged spirally, inflorescence dichotomous, bisexual, with five gamosepalous and gamopetalous. Generative reproduction occurred at a low rate. The tree grew optimally in a dusty, sandy loam soil, pH 6.0-6.5 with a temperature ranged from 27-34 °C, a light intensity of 450-1580 lux, and an altitude of about 10 meters above sea level. In conclusion, C. dichotoma is a rare plant in Kendal Regency. This plant needs an alternative method of propagation, regeneration and conservation using in vitro technique.

The Case of the Great Space Exploration: An Educator Guide with Activities in Mathematics, Science, and Technology. The NASA SCI Files. EG-2004-09-12-LARC

ERIC Educational Resources Information Center

Ricles, Shannon; Jaramillo, Becky; Fargo, Michelle

2004-01-01

In this companion to the "NASA SCI Files" episode "The Case of the Great Space Exploration," the tree house detectives learn about NASA's new vision for exploring space. In four segments aimed at grades 3-5, students learn about a variety of aspects of space exploration. Each segment of the guide includes an overview, a set of objectives,…

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.

Relationships between tree size, crown shape, gender segregation and sex allocation in Pinus halepensis, a Mediterranean pine tree.

PubMed

Ne'eman, Gidi; Goubitz, Shirrinka; Werger, Marinus J A; Shmida, Avi

2011-07-01

Sex allocation has been studied mainly in small herbaceous plants but much less in monoecious wind-pollinated trees. The aim of this study was to explore changes in gender segregation and sex allocation by Pinus halepensis, a Mediterranean lowland pine tree, within tree crowns and between trees differing in their size or crown shape. The production of new male and female cones and sex allocation of biomass, nitrogen and phosphorus were studied. The relationship between branch location, its reproductive status and proxies of branch vigour was also studied. Small trees produced only female cones, but, as trees grew, they produced both male and female cones. Female cones were produced mainly in the upper part of the crown, and male cones in its middle and lower parts. Lateral branch density was correlated with the number of male but not female cones; lateral branches were more dense in large than in small trees and even denser in hemispherical trees. Apical branches grew faster, were thicker and their phosphorus concentration was higher than in lateral shoots. Nitrogen concentration was higher in cone-bearing apical branches than in apical vegetative branches and in lateral branches with or without cones. Allocation to male relative to female function increased with tree size as predicted by sex allocation theory. The adaptive values of sex allocation and gender segregation patterns in P. halepensis, in relation to its unique life history, are demonstrated and discussed. Small trees produce only female cones that have a higher probability of being pollinated than the probability of male cones pollinating; the female-first strategy enhances population spread. Hemispherical old trees are loaded with serotinous cones that supply enough seeds for post-fire germination; thus, allocation to males is more beneficial than to females.

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.

Sampling algorithms for validation of supervised learning models for Ising-like systems

NASA Astrophysics Data System (ADS)

Portman, Nataliya; Tamblyn, Isaac

2017-12-01

In this paper, we build and explore supervised learning models of ferromagnetic system behavior, using Monte-Carlo sampling of the spin configuration space generated by the 2D Ising model. Given the enormous size of the space of all possible Ising model realizations, the question arises as to how to choose a reasonable number of samples that will form physically meaningful and non-intersecting training and testing datasets. Here, we propose a sampling technique called ;ID-MH; that uses the Metropolis-Hastings algorithm creating Markov process across energy levels within the predefined configuration subspace. We show that application of this method retains phase transitions in both training and testing datasets and serves the purpose of validation of a machine learning algorithm. For larger lattice dimensions, ID-MH is not feasible as it requires knowledge of the complete configuration space. As such, we develop a new ;block-ID; sampling strategy: it decomposes the given structure into square blocks with lattice dimension N ≤ 5 and uses ID-MH sampling of candidate blocks. Further comparison of the performance of commonly used machine learning methods such as random forests, decision trees, k nearest neighbors and artificial neural networks shows that the PCA-based Decision Tree regressor is the most accurate predictor of magnetizations of the Ising model. For energies, however, the accuracy of prediction is not satisfactory, highlighting the need to consider more algorithmically complex methods (e.g., deep learning).