Spatial distribution characters of the purse-seine skipjack fishery in the western and central Pacific based on point-pattern analysis

AbstractResearchers have analyzed various properties of drumlins within individual drumlin fields in order to provide evidence to help in identifying the processes involved in drumlin formation. One property which has been examined is the spatial distribution of drumlins within a field. Traditionally, in such endeavours the individual drumlins have been represented as points and their distribution examined using techniques of point-pattern analysis. We suggest that not only is such a representation inappropriate at this scale, it also introduces statistical bias which makes the results of such analyses questionable. Consequently, we propose an alternative approach which involves representing individual drumlins as areal phenomena and considering their pattern as a two-phase mosaic. The advantages of such an approach are discussed and it is illustrated by applying it to two different drumlin fields.

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Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan

Journal of Biogeography ◽

10.1111/jbi.12534 ◽

2015 ◽

Vol 42 (7) ◽

pp. 1281-1292 ◽

Cited By ~ 13

Author(s):

Liesbeth I. Wilschut ◽

Anne Laudisoit ◽

Nelika K. Hughes ◽

Elisabeth A. Addink ◽

Steven M. de Jong ◽

...

Keyword(s):

Spatial Distribution ◽

Pattern Analysis ◽

Distribution Patterns ◽

Point Pattern Analysis ◽

Point Pattern ◽

Spatial Distribution Patterns

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Analyzing the Spatial Distribution of Drumlins: A Two-Phase Mosaic Approach

Journal of Glaciology ◽

10.1017/s0022143000006134 ◽

1984 ◽

Vol 30 (106) ◽

pp. 302-307 ◽

Cited By ~ 8

Author(s):

B. N. Boots ◽

R. K. Burns

Keyword(s):

Spatial Distribution ◽

Pattern Analysis ◽

Point Pattern Analysis ◽

Point Pattern ◽

Statistical Bias ◽

Two Phase ◽

Alternative Approach ◽

Mosaic Approach ◽

The Individual

AbstractResearchers have analyzed various properties of drumlins within individual drumlin fields in order to provide evidence to help in identifying the processes involved in drumlin formation. One property which has been examined is the spatial distribution of drumlins within a field. Traditionally, in such endeavours the individual drumlins have been represented as points and their distribution examined using techniques of point-pattern analysis. We suggest that not only is such a representation inappropriate at this scale, it also introduces statistical bias which makes the results of such analyses questionable. Consequently, we propose an alternative approach which involves representing individual drumlins as areal phenomena and considering their pattern as a two-phase mosaic. The advantages of such an approach are discussed and it is illustrated by applying it to two different drumlin fields.

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Spatial point pattern analysis of prehospital naloxone administrations

10.1101/100412 ◽

2017 ◽

Cited By ~ 1

Author(s):

Christopher Ryan

Keyword(s):

United States ◽

Monte Carlo Simulation ◽

Spatial Distribution ◽

Pattern Analysis ◽

Spatial Clustering ◽

The United States ◽

Point Pattern Analysis ◽

Point Pattern ◽

Opioid Overdose ◽

Spatial Point

AbstractObjectivesThe increasing problem in the United States with opioid dependence and overdose, often fatal, is well-recognized. As naloxone has only one clinical use—the treatment of opioid overdose—its administration by EMS personnel can serve as a surveillance indicator for opioid overdose. This study uses specific locations of EMS calls, and methods of point pattern analysis, to detect overall spatial clustering among EMS naloxone administrations compared to EMS calls in general.Study DesignA cross-sectional study of incident locations of EMS responses in a three-county EMS region in the United States.MethodsRepeated random samples from the spatial distribution of all EMS calls were used, in a Monte Carlo simulation, to represent the background inhomogeneity of the population. Observed F, G, and inhomogeneous K and L functions from the spatial distribution of naloxone-involved calls were compared to their null sampling distributions obtained from the Monte Carlo simulation.ResultsCases of naloxone administration demonstrated spatial clustering in the range of 0 to 5000 meters, and particularly around 2500 meters, beyond what could be attributable to the spatial heterogeneity of all EMS calls.ConclusionsEfforts to understand the fundamental nature of opioid overdose as a spatial point process could yield innovative public health interventions to control the epidemic.

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Application of the method of spatial point pattern analysis to the horizontal spatial distribution of preferential flow paths

The Forestry Chronicle ◽

10.5558/tfc2015-068 ◽

2015 ◽

Vol 91 (04) ◽

pp. 384-394

Author(s):

Wenxing Lu ◽

Jinhua Cheng ◽

Wei Wang ◽

Hongjiang Zhang ◽

Hongwen Zhou

Keyword(s):

Spatial Distribution ◽

Preferential Flow ◽

Pattern Analysis ◽

Point Pattern Analysis ◽

Plant Roots ◽

Water Volume ◽

Point Pattern ◽

Analysis Method ◽

Flow Paths ◽

Preferential Flow Paths

Preferential flow significantly influences hydrological processes in forests. The occurrence and development of this flow is directly affected by its spatial distribution. To determine whether or not point pattern analysis method can be used to examine the horizontal spatial distribution of preferential flow paths, experiments were conducted with dye tracer permeation to observe flow processes. Results indicated that an increase in penetration water volume exerted only a specific effect on preferential flow paths of large class in the topmost soil. Moreover, such paths showed distinct clumped patterns at the 25-cm scale under both high permeation water volume and low permeation water volume treatments. Nonetheless, the distribution pattern became uniform as scale range increased. The significance of the correlation between the spatial distribution of preferential flow paths and plant roots decreased from the top soil layer to the bottom. These findings suggest that soil depth and water permeation volume are important to the horizontal spatial distribution of preferential flow paths. Moreover, point pattern analysis method is suitable for investigating the horizontal spatial distribution of preferential flow paths and determining the correlation between the spatial distribution of preferential flow paths and plant roots.

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Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Ecological Processes ◽

10.1186/s13717-021-00314-4 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Mariem Ben-Said

Keyword(s):

Spatial Patterns ◽

Pattern Analysis ◽

Biotic Interactions ◽

Plant Ecology ◽

Point Pattern Analysis ◽

Point Pattern ◽

Summary Statistics ◽

Spatial Point Pattern ◽

Spatial Point ◽

Spatial Point Pattern Analysis

Abstract Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

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Space-Time Point Pattern Analysis of Flavescence Dorée Epidemic in a Grapevine Field: Disease Progression and Recovery

Frontiers in Plant Science ◽

10.3389/fpls.2016.01987 ◽

2017 ◽

Vol 7 ◽

Cited By ~ 11

Author(s):

Federico Maggi ◽

Domenico Bosco ◽

Luciana Galetto ◽

Sabrina Palmano ◽

Cristina Marzachì

Keyword(s):

Disease Progression ◽

Pattern Analysis ◽

Space Time ◽

Point Pattern Analysis ◽

Point Pattern ◽

Flavescence Dorée ◽

Time Point

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Potential contact statistics for measuring scale-dependent spatial pattern and association: an example of northern cod (Gadus morhua) and capelin (Mallotus villosus)

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f00-079 ◽

2000 ◽

Vol 57 (7) ◽

pp. 1355-1368 ◽

Cited By ~ 9

Author(s):

Richard L O'Driscoll ◽

David C Schneider ◽

George A Rose ◽

George R Lilly

Keyword(s):

Spatial Distribution ◽

Spatial Pattern ◽

Gadus Morhua ◽

Atlantic Cod ◽

Simulated Data ◽

Point Pattern Analysis ◽

Point Pattern ◽

Mallotus Villosus ◽

Capelin Mallotus Villosus ◽

Potential Contact

Analysis of simulated data showed that potential contact statistics could be used to describe spatial pattern in sample density data. Potential contact is a new method, analogous to Ripley's K function for mapped point pattern analysis. Potential contact can be used to describe spatial pattern and association over a range of scales without grouping data and is robust against the presence of zeros. The statistical output is ecologically interpretable, as a measure of the degree of contact between individuals. This new technique was applied to examine changes in the spatial distribution of Atlantic cod (Gadus morhua) off Newfoundland, Canada, from 1985 to 1994, a period that encompassed a collapse of the cod stock. Sample data from bottom-trawl surveys indicated that cod were aggregated in patches with dimensions of 100-250 km. During the period of cod decline in the 1990s, spatial structure changed in three ways: the number of patches decreased, patch size shrank, and contact with conspecifics at small (10-20 km) scales fell. Cod were broadly associated with capelin (Mallotus villosus), a major prey species. Spatial distribution of capelin changed over the same time period as changes in cod distribution, and there was no evidence that contact between cod and capelin decreased.

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