Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation.
We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability.
We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation.
The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient.
Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.
|Publication Subtype||Journal Article|
|Title||Using landscape metrics to characterize towns along an urban-rural gradient|
|Series title||Landscape Ecology|
|Contributing office(s)||Coop Res Unit Leetown|
|State||Connecticut. Maine, Massachusetts, New Hampshire, Rhode Island, Vermont|
|Google Analytic Metrics||Metrics page|