Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns

• Main Authors: Paul Holloway, Jennifer A. Miller
• Format: Article
• Language: English
• Published: MDPI AG 2015-05-01
• Series: ISPRS International Journal of Geo-Information
• Subjects: geographically weighted regression; scale; species richness; birds
• Online Access: http://www.mdpi.com/2220-9964/4/2/783

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.