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Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
by
Miller, Jennifer
, Holloway, Paul
in
Autocorrelation
/ Birds
/ Climate
/ Clusters
/ Environmental factors
/ geographically weighted regression
/ New York
/ Productivity
/ Regression
/ scale
/ Species richness
/ Statistics
2015
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Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
by
Miller, Jennifer
, Holloway, Paul
in
Autocorrelation
/ Birds
/ Climate
/ Clusters
/ Environmental factors
/ geographically weighted regression
/ New York
/ Productivity
/ Regression
/ scale
/ Species richness
/ Statistics
2015
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Do you wish to request the book?
Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
by
Miller, Jennifer
, Holloway, Paul
in
Autocorrelation
/ Birds
/ Climate
/ Clusters
/ Environmental factors
/ geographically weighted regression
/ New York
/ Productivity
/ Regression
/ scale
/ Species richness
/ Statistics
2015
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Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
Journal Article
Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
2015
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Overview
In this paper we explore relationships between bird species richness and environmental factors in New York State, focusing particularly on how spatial scale, autocorrelation and nonstationarity affect these relationships. We used spatial statistics, Getis-Ord Gi*(d), to investigate how spatial scale affects the measurement of richness “hot-spots” and “cold-spots” (clusters of high and low species richness, respectively) and geographically weighted regression (GWR) to explore scale dependencies and nonstationarity in the relationships between richness and environmental variables such as climate and plant productivity. Finally, we introduce a geovisualization approach to show how these relationships are affected by spatial scale in order to understand the complex spatial patterns of species richness.
Publisher
MDPI AG
Subject
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