Ordinating tropical moth ensembles from an elevational gradient: a comparison of common methods

2004 ◽  
Vol 20 (2) ◽  
pp. 165-172 ◽  
Author(s):  
Gunnar Brehm ◽  
Konrad Fiedler
Keyword(s):  
Correspondence Analysis ◽  
Detrended Correspondence Analysis ◽  
Elevational Gradient ◽  
Habitat Diversity ◽  
Data Sets ◽  
Similar Data ◽  
Data Set ◽  
Montane Rain Forest ◽  
High Species Richness ◽  
Morisita's Index

The analysis of beta diversity (inter-habitat diversity) of very species-rich and incompletely sampled tropical arthropod communities requires the choice of appropriate statistical tools. The performance of the three commonly employed ordination methods, correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMDS), was compared on a large empirical data set of geometrid moths sampled along an altitudinal gradient in an Andean montane rain forest. Despite the high species richness and incompleteness of the ensembles, all methods depicted the same, readily interpretable patterns. Both CA and NMDS showed an arch-like structure, which hints at an underlying coenocline, whereas this arch was computationally eliminated in DCA. For this particular data set, CA and NMDS both provided convincing results while the detrending algorithm of DCA did not improve the interpretability of the data. Of the large number of similarity indices available to be used in combination with NMDS, the binary Sørensen and the abundance-based Normalized Expected Species Shared (NESS) index were tested. Performance of the indices was measured by comparing stress, a measure of poorness-of-fit in NMDS. NMDS ordinations with lowest values of stress were achieved by the NESS index with the parameter m set to its maximum (mmax). In contrast, ordinations based on NESS values with the parameter m set to 1 (identical with Morisita's index), had consistently higher stress values and performed worse than ordinations using Sørensen's index. Hence, if high values of m can be achieved in similar data sets, the NESS index with mmax is recommended for ordination purposes and Morisita's index should be avoided.

scholarly journals The vegetation types and management units of Goedverwacht farm in the mixed bushveld of the Northern Province, South Africa

Koedoe ◽  
1997 ◽  
Vol 40 (2) ◽  
Author(s):  
L. Breebaart ◽  
M. Deutschlander
Keyword(s):  
Plant Communities ◽  
Correspondence Analysis ◽  
Canonical Correspondence Analysis ◽  
Environmental Gradient ◽  
Detrended Correspondence Analysis ◽  
Northern Province ◽  
Computer Programme ◽  
Data Set ◽  
Management Units ◽  
Floristic Data

An analysis of the vegetation of Goedverwacht farm in the mixed bushveld of the Northern Province is presented. Releves were compiled in 33 stratified random sample plots. Eight distinct plant communities were identified by means ofBraun-Blanquet pro-cedures. Detrended correspondence analysis (DCA) was applied to the floristic data set using the computer programme DECORANA (Detrended Correspondence Analysis) to determine a probable environmental gradient and to facilitate in the identification of management units. The computer programme CANOCO (Canonical Correspondence Analysis) was used to apply canonical correspondence analysis (CCA) to the floristic data set. Two management units were determined by means of vegetation ordinations and soil data. A classification, description and ecological interpretation of the plant communities as well as a description of the management units are presented.

scholarly journals Multivariate analysis of the hunting tactics of Kalahari leopards

Koedoe ◽  
1997 ◽  
Vol 40 (1) ◽  
Author(s):  
J. Du P. Bothma ◽  
N. Van Rooyen ◽  
E.A.N. Le Riche
Keyword(s):  
Multivariate Analysis ◽  
Field Study ◽  
Correspondence Analysis ◽  
Detrended Correspondence Analysis ◽  
Prey Type ◽  
Data Sets ◽  
Male And Female ◽  
Sandy Substrate ◽  
Hunting Tactics

The hunting tactics of male and female leopards in the southern Kalahari were analysed for prey-specific patterns. The field study was based on tracking leopard spoor in the sandy substrate of the Kalahari. Visual profiles for each type of prey were compiled for various facets of hunting. Data sets were analysed further, using Correspondence Analysis and Detrended Correspondence Analysis. The results indicate that multivariate analysis can be used to demonstrate prey-specific hunting tactics in Kalahari leopards. In using a scarce prey base, Kalahari leopards seem to be number maximisers as they are unselective of prey type, age or sex. The presence of prey-specific hunting tactics may indicate a move along a continuum towards some degree of energy maximisation.

The prediction of understory vegetation by environmental factors for the purpose of site classification in forestry: an example from northern Ontario using residual ordination analysis

1985 ◽  
Vol 15 (6) ◽  
pp. 1099-1108 ◽  
Author(s):  
T. J. Carleton ◽  
R. K. Jones ◽  
G. Pierpoint
Keyword(s):  
Correspondence Analysis ◽  
Forest Ecosystem ◽  
Detrended Correspondence Analysis ◽  
Understory Vegetation ◽  
Soil Conditions ◽  
Site Classification ◽  
Data Set ◽  
Local Composition ◽  
Ecosystem Classification ◽  
Ordination Analysis

Problems arise in the use of understory vegetation as an indicator of site condition in that impermanent factors such as microclimate, succession, and chance may play significant roles in determining local composition. Residual ordination analysis is a method which facilitates quantification of the sources of variation in understory vegetation over a landscape. Here it is applied to survey data, representing 250 stands upon which the forest ecosystem classification programme for the Clay Belt portion of northeastern Ontario is based, to test the premise that vegetation types will differentiate soil conditions for forestry purposes. Ordination of the data by detrended correspondence analysis yielded a bivariate scatterplot which, through visual appraisal, seemed readily interpretable in terms of site-related nutrient and moisture gradients. Formal exploration, using canonical redundancy analysis, yielded the following predictive model: understory vegetation (detrended correspondence analysis axes 1 and 2) = soils (67%) + canopy (8%) + succession (1%) + error (24%). Extraction of residual ordinations confirmed this general model and demonstrated that although canopy and successional influences are minor in the data, they are significant. Because the nonsite-related, predictable components account for only 9% of the variation at most, the premise of the existing forest ecosystem classification system is judged to be sound insofar as the data upon which it is based adequately describe the range of commercial stand conditions normally encountered. The results are discussed in relation to vegetation survey design and the performance of residual ordination analysis on a large data set is assessed.

Synanthropic vegetation of the Eragrostion cilianensi-minoris alliance in the Czech Republic

Biologia ◽  
2011 ◽  
Vol 66 (6) ◽  
Author(s):  
Radomír Němec ◽  
Zdeňka Lososová ◽  
Pavel Dřevojan ◽  
Kristýna Žáková
Keyword(s):  
Czech Republic ◽  
Correspondence Analysis ◽  
Detrended Correspondence Analysis ◽  
Vegetation Types ◽  
Data Set ◽  
The Czech Republic ◽  
Synanthropic Vegetation ◽  
Arable Fields ◽  
Twinspan Classification ◽  
Southern Moravia

AbstractA synthesis of the alliance Eragrostion cilianensi-minoris in the Czech Republic is presented on the basis of 82 relevés including new unpublished data. A TWINSPAN classification and detrended correspondence analysis were used to identify the main vegetation types included in the alliance Eragrostion cilianensi-minoris. A syntaxonomic revision of the data set revealed five associations of the alliance: Digitario sanguinalis-Eragrostietum minoris, Portulacetum oleraceae, Eragrostio poaeoidis-Panicetum capillaris, Cynodontetum dactyli, and Hibisco trioni-Eragrostietum poaeoidis. The latter was recently found in several arable fields in Southern Moravia (Czech Republic) and was newly characterized.

scholarly journals Locality-Sensitive Hashing for Information Retrieval System on Multiple GPGPU Devices

2020 ◽  
Vol 10 (7) ◽  
pp. 2539 ◽  
Author(s):  
Toan Nguyen Mau ◽  
Yasushi Inoguchi
Keyword(s):  
Big Data ◽  
Information Retrieval ◽  
Retrieval System ◽  
Hash Table ◽  
Information Retrieval System ◽  
Main Memory ◽  
Locality Sensitive Hashing ◽  
Data Sets ◽  
Similar Data ◽  
Data Set

It is challenging to build a real-time information retrieval system, especially for systems with high-dimensional big data. To structure big data, many hashing algorithms that map similar data items to the same bucket to advance the search have been proposed. Locality-Sensitive Hashing (LSH) is a common approach for reducing the number of dimensions of a data set, by using a family of hash functions and a hash table. The LSH hash table is an additional component that supports the indexing of hash values (keys) for the corresponding data/items. We previously proposed the Dynamic Locality-Sensitive Hashing (DLSH) algorithm with a dynamically structured hash table, optimized for storage in the main memory and General-Purpose computation on Graphics Processing Units (GPGPU) memory. This supports the handling of constantly updated data sets, such as songs, images, or text databases. The DLSH algorithm works effectively with data sets that are updated with high frequency and is compatible with parallel processing. However, the use of a single GPGPU device for processing big data is inadequate, due to the small memory capacity of GPGPU devices. When using multiple GPGPU devices for searching, we need an effective search algorithm to balance the jobs. In this paper, we propose an extension of DLSH for big data sets using multiple GPGPUs, in order to increase the capacity and performance of the information retrieval system. Different search strategies on multiple DLSH clusters are also proposed to adapt our parallelized system. With significant results in terms of performance and accuracy, we show that DLSH can be applied to real-life dynamic database systems.

scholarly journals A Dataset for Comparing Mirrored and Non-Mirrored Male Bust Images for Facial Recognition

Data ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 26 ◽  
Author(s):  
Collin Gros ◽  
Jeremy Straub
Keyword(s):  
Data Collection ◽  
Facial Recognition ◽  
Data Sets ◽  
Similar Data ◽  
Data Set ◽  
Human Recognition ◽  
Related Research

Facial recognition, as well as other types of human recognition, have found uses in identification, security, and learning about behavior, among other uses. Because of the high cost of data collection for training purposes, logistical challenges and other impediments, mirroring images has frequently been used to increase the size of data sets. However, while these larger data sets have shown to be beneficial, their comparative level of benefit to the data collection of similar data has not been assessed. This paper presented a data set collected and prepared for this and related research purposes. The data set included both non-occluded and occluded data for mirroring assessment.

Functional Morphology at the Mall

2012 ◽  
Vol 74 (6) ◽  
pp. 401-408
Author(s):  
Scott P. Hippensteel
Keyword(s):  
Functional Morphology ◽  
Undergraduate Students ◽  
Sample Selection ◽  
The United States ◽  
Data Sets ◽  
Similar Data ◽  
Data Set ◽  
Fossil Resource ◽  
Upper Level ◽  
Fossil Data

The primary decorative flooring tile in the Southpark Mall in Charlotte, North Carolina, is fossiliferous limestone that contains Jurassic ammonoids and belemnoids. Visible in these tiles are more than 500 ammonoids, many of which have been cross sectioned equatorially perpendicular to the plane of coiling. Upper-level undergraduate students from UNC Charlotte used this data set to measure ammonoid coiling geometry and, thus, coiling strategy, and their findings were compared with earlier reported research presented in highly respected paleobiology journals. This example of urban paleobiology utilized a large, easily accessible, and readily available fossil data set to introduce functional morphology of coiled cephalopods. Similar data sets are available in public buildings around the United States, providing a valuable fossil resource at a time when shrinking academic budgets would prohibit purchasing such a collection (and many collections have not been updated in decades). As students compared their results with those previously published by professional paleontologists, they were exposed to the methods and limits of the scientific method in the historical sciences, as well as the dangers of poor sample selection.

scholarly journals A Feature Subset Selection Algorithm Automatic Recommendation Method

2013 ◽  
Vol 47 ◽  
pp. 1-34 ◽  
Author(s):  
G. Wang ◽  
Q. Song ◽  
H. Sun ◽  
X. Zhang ◽  
B. Xu ◽  
...  
Keyword(s):  
Feature Selection ◽  
Subset Selection ◽  
Feature Subset Selection ◽  
Data Sets ◽  
Feature Subset ◽  
Similar Data ◽  
K Nearest Neighbor ◽  
Real World Data ◽  
Feature Selection Problem ◽  
Data Set

Many feature subset selection (FSS) algorithms have been proposed, but not all of them are appropriate for a given feature selection problem. At the same time, so far there is rarely a good way to choose appropriate FSS algorithms for the problem at hand. Thus, FSS algorithm automatic recommendation is very important and practically useful. In this paper, a meta learning based FSS algorithm automatic recommendation method is presented. The proposed method first identifies the data sets that are most similar to the one at hand by the k-nearest neighbor classification algorithm, and the distances among these data sets are calculated based on the commonly-used data set characteristics. Then, it ranks all the candidate FSS algorithms according to their performance on these similar data sets, and chooses the algorithms with best performance as the appropriate ones. The performance of the candidate FSS algorithms is evaluated by a multi-criteria metric that takes into account not only the classification accuracy over the selected features, but also the runtime of feature selection and the number of selected features. The proposed recommendation method is extensively tested on 115 real world data sets with 22 well-known and frequently-used different FSS algorithms for five representative classifiers. The results show the effectiveness of our proposed FSS algorithm recommendation method.

scholarly journals NICMOS spectroscopy of HD 189733b

2010 ◽  
Vol 6 (S276) ◽  
pp. 148-153 ◽  
Author(s):  
Mark R. Swain ◽  
Pieter Deroo ◽  
Gautam Vasisht
Keyword(s):  
Reduction Process ◽  
Systematic Errors ◽  
Data Sets ◽  
Spectral Features ◽  
Similar Data ◽  
Data Set ◽  
Residual Structure ◽  
Flat Field ◽  
Consistent Method ◽  
Data Reduction Process

AbstractSpectral features corresponding to methane and water opacity were reported based on transmission spectroscopy of HD 189733b with Hubble/NICMOS. Recently, these data, and a similar data set for XO-1b, have been reexamined in Gibson et al. (2010), who claim they cannot reliably reproduce prior results. We examine the methods used by the Gibson team and identify two specific issues that could act to increase the formal uncertainties and to create instability in the minimization process. This would also be consistent with the GPA10 finding that they could not identify a way to select among the several instrument models they constructed. In the case of XO-1b, the Gibson team significantly changed the way in which the instrument model is defined (both with respect to the three approaches they used for HD 189733b, and the approach used by previous authors); this change, which omits the effect of the spectrum position on the detector, makes direct intercomparison of results difficult. In the experience of our group, the position of the spectrum on the detector is an important element of the instrument model because of the significant residual structure in the NICMOS spectral flat field. The approach of changing instrument models significantly complicates understanding the data reduction process and interpreting the results. Our team favors establishing a consistent method of handling NICMOS instrument systematic errors and applying it uniformly to data sets.

Influence of sample quantification and taxonomic resolution on the ordination of macroinvertebrate communities from running waters in Victoria, Australia

1995 ◽  
Vol 46 (2) ◽  
pp. 501 ◽  
Author(s):  
R Marchant ◽  
LA Barmuta ◽  
BC Chessman
Keyword(s):  
Binary Data ◽  
Environmental Gradients ◽  
Detrended Correspondence Analysis ◽  
Original Data ◽  
Taxonomic Resolution ◽  
Data Sets ◽  
Running Waters ◽  
Macroinvertebrate Communities ◽  
Data Set ◽  
Sample Quantification

The influence of sample quantification and taxonomic resolution on the ordination of macroinvertebrate communities from nine Victorian rivers was examined by progressively reducing the degree of detail in the original data (species level, quantitative). Five additional data sets were created that consisted of binary (presence or absence) data on species, quantitative or binary data on families, and quantitative data on PET (plecopteran, ephemeropteran and trichopteran) species or families. Ordinations were performed with detrended correspondence analysis (DCA) and semi-strong hybrid multi-dimensional scaling (SSH). With both ordination techniques, the ordinations of each data set (including the original) revealed the same three underlying gradients. An altitudinal gradient consistently achieved the highest correlations with the ordinations (r = 0.71-0.93), followed by a substratum gradient (r = 0.50-0.88) and a combined pH and conductivity gradient (r = 0.47-0.76). Each of the five less-complete data sets thus provides an adequate degree of detail for ordination analysis and subsequent interpretation of environmental gradients.

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