Exploring linkages between people and rural landscapes at broad ecological scales

TitleExploring linkages between people and rural landscapes at broad ecological scales
Publication TypeJournal Article
Year of Publication2010
AuthorsHe, Hong, Lewis Bernard J., Baer Adam D., and Nigh Timothy A.
JournalLandscape and Urban Planning
Volume97
Pagination49 - 57
Date Published07/2010
KeywordsCART analysis, Census of population and housing data, Ecological classification system, Ecological section and subsection, Prominent social variable, Social landscape
Abstract

Effective conservation and management of natural resources requires integrating knowledge of ecological systems with an understanding of the cultural, social and economic characteristics of people who live and work in ecological landscapes. This study explores how people with distinctive social attributes are situated spatially across the landscape at the level of ecological section and subsection in Missouri. We identify prominent (statistically significant) social variables that may have implications for policy making at these two levels. We also examine the composition and spatial distribution of social groups within each level. To do so, we link non-urban, statewide U.S. Census data with units of the Missouri Ecological Classification System. Results show that: (1) education trumps other social variables such as income and employment as the most prominent variable differentiating people by ecological section in Missouri; (2) housing and income also emerge as prominent partitioning variables for people across ecological sections; and (3) social groups tend to be more spatially fragmented in ecological subsections with low physiographic gradients. The findings suggest a variety of research questions for addressing regional policies relative to education and homestead tenure as well as the ecological effects of spatial distributions of people with different social attributes. The findings establish a broad socio-ecological context for natural resource studies at more magnified levels of ecological scale at which more specific hypotheses can be designed and tested. We discuss possible research questions and hypotheses underling each finding as well as management implications.