scholarly journals Characterizing the Relative Spatial Structure of Point Patterns

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Eric Marcon ◽  
Florence Puech ◽  
Stéphane Traissac
Keyword(s):  
Spatial Structure ◽  
Interspecific Competition ◽  
Null Hypothesis ◽  
Tropical Tree ◽  
Point Pattern ◽  
Data Set ◽  
New Approach ◽  
Point Patterns ◽  
Tree Data

We generalize Ripley’sKfunction to get a new function,M, to characterize the spatial structure of a point pattern relatively to another one. We show that this new approach is pertinent in ecology when space is not homogenous and the size of objects matters. We present how to use the function and test the data against the null hypothesis of independence between points. In a tropical tree data set we detect intraspecific aggregation and interspecific competition.

scholarly journals A Statistical Test for Ripley’s K Function Rejection of Poisson Null Hypothesis

ISRN Ecology ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Eric Marcon ◽  
Stéphane Traissac ◽  
Gabriel Lang
Keyword(s):  
Monte Carlo ◽  
Spatial Structure ◽  
Monte Carlo Simulations ◽  
Tropical Forest ◽  
Null Hypothesis ◽  
Statistical Test ◽  
Forest Plot ◽  
Complete Spatial Randomness ◽  
Point Patterns ◽  
K Function

Ripley’s K function is the classical tool to characterize the spatial structure of point patterns. It is widely used in vegetation studies. Testing its values against a null hypothesis usually relies on Monte-Carlo simulations since little is known about its distribution. We introduce a statistical test against complete spatial randomness (CSR). The test returns the P value to reject the null hypothesis of independence between point locations. It is more rigorous and faster than classical Monte-Carlo simulations. We show how to apply it to a tropical forest plot. The necessary R code is provided.

A New Approach for the Analysis of Mixture Toxicity Data

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2345-2348 ◽  
Author(s):  
C. N. Haas
Keyword(s):  
Quantitative Analysis ◽  
Mixture Toxicity ◽  
New Method ◽  
Metal Exposure ◽  
Positive Interactions ◽  
Toxicity Data ◽  
Data Set ◽  
New Approach ◽  
Negative Interactions

A new method for the quantitative analysis of multiple toxicity data is described and illustrated using a data set on metal exposure to copepods. Positive interactions are observed for Ni-Pb and Pb-Cr, with weak negative interactions observed for Ni-Cr.

scholarly journals Does fluvial channel-belt clustering predict net sand to gross rock volume? Architectural metrics and point-pattern analysis of a digital outcrop model

2019 ◽  
Vol 89 (11) ◽  
pp. 1109-1126
Author(s):  
Alexander R. Koch ◽  
Cari L. Johnson ◽  
Lisa Stright
Keyword(s):  
Large Scale ◽  
Small Scale ◽  
Point Pattern ◽  
Point Patterns ◽  
Spatial Point ◽  
Channel Belt ◽  
John Henry Member ◽  
Scale Point ◽  
Belt Width ◽  
Digital Outcrop

ABSTRACT Spatial point-pattern analyses (PPAs) are used to quantify clustering, randomness, and uniformity of the distribution of channel belts in fluvial strata. Point patterns may reflect end-member fluvial architecture, e.g., uniform compensational stacking and avulsion-generated clustering, which may change laterally, especially at greater scales. To investigate spatial and temporal changes in fluvial systems, we performed PPA and architectural analyses on extensive outcrops of the Cretaceous John Henry Member of the Straight Cliffs Formation in southern Utah, USA. Digital outcrop models (DOMs) produced using unmanned aircraft system-based stereophotogrammetry form the basis of detailed interpretations of a 250-m-thick fluvial succession over a total outcrop length of 4.5 km. The outcrops are oriented roughly perpendicular to fluvial transport direction. This transverse cross-sectional exposure of the fluvial system allows a study of the system's variation along depositional strike. We developed a workflow that examines spatial point patterns using the quadrat method, and architectural metrics such as net sand to gross rock volume (NTG), amalgamation index, and channel-belt width and thickness within moving windows. Quadrat cell sizes that are ∼ 50% of the average channel-belt width-to-thickness ratio (16:1 aspect ratio) provide an optimized scale to investigate laterally elongate distributions of fluvial-channel-belt centroids. Large-scale quadrat point patterns were recognized using an array of four quadrat cells, each with 237× greater area than the median channel belt. Large-scale point patterns and NTG correlate negatively, which is a result of using centroid-based PPA on a dataset with disparately sized channel belts. Small-scale quadrat point patterns were recognized using an array of 16 quadrat cells, each with 21× greater area than the median channel belt. Small-scale point patterns and NTG correlate positively, and match previously observed stratigraphic trends in the fluvial John Henry Member, suggesting that these are regional trends. There are deviations from these trends in architectural statistics over small distances (hundreds of meters) which are interpreted to reflect autogenic avulsion processes. Small-scale autogenic processes result in architecture that is difficult to correlate between 1D datasets, for example when characterizing a reservoir using well logs. We show that 1D NTG provides the most accurate prediction for surrounding 2D architecture.

scholarly journals Detecting Heterogeneity of Substitution Along DNA and Protein Sequences

Genetics ◽  
1996 ◽  
Vol 143 (1) ◽  
pp. 589-602 ◽  
Author(s):  
Peter J E Goss ◽  
R C Lewontin
Keyword(s):  
Null Hypothesis ◽  
Nonuniform Distribution ◽  
Critical Values ◽  
Third Order ◽  
Variance Test ◽  
Data Set ◽  
Significance Level ◽  
Uniformly Most Powerful Test ◽  
Interval Lengths ◽  
Uniformly Most Powerful

Abstract Regions of differing constraint, mutation rate or recombination along a sequence of DNA or amino acids lead to a nonuniform distribution of polymorphism within species or fixed differences between species. The power of five tests to reject the null hypothesis of a uniform distribution is studied for four classes of alternate hypothesis. The tests explored are the variance of interval lengths; a modified variance test, which includes covariance between neighboring intervals; the length of the longest interval; the length of the shortest third-order interval; and a composite test. Although there is no uniformly most powerful test over the range of alternate hypotheses tested, the variance and modified variance tests usually have the highest power. Therefore, we recommend that one of these two tests be used to test departure from uniformity in all circumstances. Tables of critical values for the variance and modified variance tests are given. The critical values depend both on the number of events and the number of positions in the sequence. A computer program is available on request that calculates both the critical values for a specified number of events and number of positions as well as the significance level of a given data set.

scholarly journals A short geostatistical study of the three-dimensional spatial structure of fumonisins in stored maize

2010 ◽  
Vol 3 (1) ◽  
pp. 95-103 ◽  
Author(s):  
M. Rivas Casado ◽  
D. Parsons ◽  
N. Magan ◽  
R. Weightman ◽  
P. Battilani ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Structure ◽  
Spatial Correlation ◽  
Three Dimensional ◽  
Sample Collection ◽  
Data Set ◽  
Research Areas ◽  
Geostatistical Approach ◽  
Sampling Protocols ◽  
Current Sample

The heterogeneous three-dimensional spatial distribution of mycotoxins has proven to be one of the main limitations for the design of effective sampling protocols. Current sample collection protocols for mycotoxins have been designed to estimate the mean concentration and fail to characterise the spatial distribution of the mycotoxin concentration due to the aggregation of the incremental samples. Geostatistical techniques have been successfully applied to overcome similar problems in many research areas. However, little work has been developed on the use of geostatistics for the design of sampling protocols for mycotoxins. This paper focuses on the analysis of the two and three-dimensional spatial structure of fumonisins B1 (FB1) and B2 (FB2) in maize in a bulk store using a geostatistical approach and on how results help determine the number and location of incremental samples to be collected. The spatial correlation between FB1 and FB2, as well as between the number of kernels infected and the level of contamination was investigated. For this purpose, a bed of maize was sampled at different depths to generate a unique three-dimensional data set of FB1 and FB2. The analysis found no clear evidence of spatial structure in either the two-dimensional or three-dimensional analyses. The number of Fusarium infected kernels was not a good indicator for the prediction of fumonisin concentration and there was no spatial correlation between the concentrations of the two fumonisins.

scholarly journals Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution

Geomatics ◽  
2021 ◽  
Vol 1 (4) ◽  
pp. 464-495
Author(s):  
Desi Suyamto ◽  
Lilik Prasetyo ◽  
Yudi Setiawan ◽  
Arief Wijaya ◽  
Kustiyo Kustiyo ◽  
...  
Keyword(s):  
Geometric Feature ◽  
Data Sets ◽  
Temporal Data ◽  
Spatial And Temporal Patterns ◽  
Data Set ◽  
Point Matching ◽  
Point Patterns ◽  
Visual Sensing ◽  
Point Data ◽  
Point To Point

This article demonstrated an easily applicable method for measuring the similarity between a pair of point patterns, which applies to spatial or temporal data sets. Such a measurement was performed using similarity-based pattern analysis as an alternative to conventional approaches, which typically utilize straightforward point-to-point matching. Using our approach, in each point data set, two geometric features (i.e., the distance and angle from the centroid) were calculated and represented as probability density functions (PDFs). The PDF similarity of each geometric feature was measured using nine metrics, with values ranging from zero (very contrasting) to one (exactly the same). The overall similarity was defined as the average of the distance and angle similarities. In terms of sensibility, the method was shown to be capable of measuring, at a human visual sensing level, two pairs of hypothetical patterns, presenting reasonable results. Meanwhile, in terms of the method′s sensitivity to both spatial and temporal displacements from the hypothetical origin, the method is also capable of consistently measuring the similarity of spatial and temporal patterns. The application of the method to assess both spatial and temporal pattern similarities between two deforestation data sets with different resolutions was also discussed.

scholarly journals Spatial analysis of phylogenetic community structure: New version of a classical method

2015 ◽  
Author(s):  
Carlo Ricotta ◽  
Eszter EA Ari ◽  
Giuliano Bonanomi ◽  
Francesco Giannino ◽  
Duncan Heathfield ◽  
...  
Keyword(s):  
Community Structure ◽  
Spatial Scales ◽  
Point Pattern ◽  
Maximum Deviation ◽  
Individual Plant ◽  
Phylogenetic Distance ◽  
Phylogenetic Structure ◽  
Phylogenetic Community Structure ◽  
Point Patterns ◽  
Wide Range

The increasing availability of phylogenetic information facilitates the use of evolutionary methods in community ecology to reveal the importance of evolution in the species assembly process. However, while several methods have been applied to a wide range of communities across different spatial scales with the purpose of detecting non-random phylogenetic patterns, the spatial aspects of phylogenetic community structure have received far less attention. Accordingly, the question for this study is: can point pattern analysis be used for revealing the phylogenetic structure of multi-species assemblages? We introduce a new individual-centered procedure for analyzing the scale-dependent phylogenetic structure of multi-species point patterns based on digitized field data. The method uses nested circular plots with increasing radii drawn around each individual plant and calculates the mean phylogenetic distance between the focal individual and all individuals located in the circular ring delimited by two successive radii. This scale-dependent value is then averaged over all individuals of the same species and the observed mean is compared to a null expectation with permutation procedures. The method detects particular radius values at which the point pattern of a single species exhibits maximum deviation from the expectation towards either phylogenetic aggregation or segregation. Its performance is illustrated using data from a grassland community in Hungary and simulated point patterns. The proposed method can be extended to virtually any distance function for species pairs, such as functional distances.

scholarly journals Multiscale Mask R-CNN–Based Lung Tumor Detection Using PET Imaging

2019 ◽  
Vol 18 ◽  
pp. 153601211986353 ◽  
Author(s):  
Rui Zhang ◽  
Chao Cheng ◽  
Xuehua Zhao ◽  
Xuechen Li
Keyword(s):  
Pet Imaging ◽  
Lung Tumor ◽  
Training Data ◽  
Fine Tuning ◽  
Weighted Voting ◽  
Data Set ◽  
New Approach ◽  
Positron Emission ◽  
Voting Strategy ◽  
Aided Diagnosis

Positron emission tomography (PET) imaging serves as one of the most competent methods for the diagnosis of various malignancies, such as lung tumor. However, with an elevation in the utilization of PET scan, radiologists are overburdened considerably. Consequently, a new approach of “computer-aided diagnosis” is being contemplated to curtail the heavy workloads. In this article, we propose a multiscale Mask Region–Based Convolutional Neural Network (Mask R-CNN)–based method that uses PET imaging for the detection of lung tumor. First, we produced 3 models of Mask R-CNN for lung tumor candidate detection. These 3 models were generated by fine-tuning the Mask R-CNN using certain training data that consisted of images from 3 different scales. Each of the training data set included 594 slices with lung tumor. These 3 models of Mask R-CNN models were then integrated using weighted voting strategy to diminish the false-positive outcomes. A total of 134 PET slices were employed as test set in this experiment. The precision, recall, and F score values of our proposed method were 0.90, 1, and 0.95, respectively. Experimental results exhibited strong conviction about the effectiveness of this method in detecting lung tumors, along with the capability of identifying a healthy chest pattern and reducing incorrect identification of tumors to a large extent.

scholarly journals The zone of latent solutions and its relevance to understanding ape cultures

2020 ◽  
Vol 35 (5) ◽  
Author(s):  
Claudio Tennie ◽  
Elisa Bandini ◽  
Carel P. van Schaik ◽  
Lydia M. Hopper
Keyword(s):  
Social Learning ◽  
Null Hypothesis ◽  
Experimental Methodology ◽  
Great Ape ◽  
Cultural Patterns ◽  
Learning Mechanisms ◽  
New Approach ◽  
Learning Hypothesis ◽  
Alternative Approach ◽  
Do So

Abstract The zone of latent solutions (ZLS) hypothesis provides an alternative approach to explaining cultural patterns in primates and many other animals. According to the ZLS hypothesis, non-human great ape (henceforth: ape) cultures consist largely or solely of latent solutions. The current competing (and predominant) hypothesis for ape culture argues instead that at least some of their behavioural or artefact forms are copied through specific social learning mechanisms (“copying social learning hypothesis”) and that their forms may depend on copying (copying-dependent forms). In contrast, the ape ZLS hypothesis does not require these forms to be copied. Instead, it suggests that several (non-form-copying) social learning mechanisms help determine the frequency (but typically not the form) of these behaviours and artefacts within connected individuals. The ZLS hypothesis thus suggests that increases and stabilisations of a particular behaviour’s or artefact’s frequency can derive from socially-mediated (cued) form reinnovations. Therefore, and while genes and ecology play important roles as well, according to the ape ZLS hypothesis, apes typically acquire the forms of their behaviours and artefacts individually, but are usually socially induced to do so (provided sufficient opportunity, necessity, motivation and timing). The ZLS approach is often criticized—perhaps also because it challenges the current null hypothesis, which instead assumes a requirement of form-copying social learning mechanisms to explain many ape behavioural (and/or artefact) forms. However, as the ZLS hypothesis is a new approach, with less accumulated literature compared to the current null hypothesis, some confusion is to be expected. Here, we clarify the ZLS approach—also in relation to other competing hypotheses—and address misconceptions and objections. We believe that these clarifications will provide researchers with a coherent theoretical approach and an experimental methodology to examine the necessity of form-copying variants of social learning in apes, humans and other species.

scholarly journals Method for Monitoring of Managing the Modernization of Regional Economy

2019 ◽  
Vol 71 ◽  
pp. 04004
Author(s):  
T. Krasnova ◽  
T. Plotnikova ◽  
A. Pozdnyakov ◽  
A. Vilgelm
Keyword(s):  
Spatial Distribution ◽  
Economic Activity ◽  
Urban Areas ◽  
Regional Economy ◽  
Regional Level ◽  
Market Potential ◽  
New Economic Geography ◽  
Local Market ◽  
Data Set ◽  
New Approach

This paper proposes a new approach for monitoring of managing the modernisation of regional economic. The model built on proposed methodology will make it possible to smooth out the influence of non-urban areas on the unevenness of economic activity in spatial development. This paper has two goals. The first is to provide a new compilation of data on spatial distribution of economic activity at the sub-regional level. This data set allows us to monitoring of different indicators within macroregions such as Siberia. The second goal is to construct an instrument that helps to overcome the endogeneity problem using new economic geography hypothesis about the mechanisms of distribution of economic activity. Section 2 describes the data and method that we have proposed, discusses the construction of the Theil indexes using these data at the sub-federal and the sub-regional level. Section 3 presents the correlations between spatial distribution of economic activity and local market potential, discusses the robustness of the results; and the last section concludes.

Sign in / Sign up

Export Citation Format

Share Document