Search

Urbanization has altered many landscapes around the world and created novel contexts and interactions, such as the rural–urban interface. We sought to address how a forest patch’s location in the rural–urban interface influences which avian species choose to occur within the patch. We predicted a negative relationship between forest bird richness and urbanization surrounding the patch, but that it would be ameliorated by the area of tree cover in the patch and matrix, and that total tree-cover area would be more influential on forest bird species richness than area of tree cover in the focal patch alone. We conducted bird surveys in 44 forest patches over 2 years in Southeast Michigan and evaluated bird presence and richness relative to patch and matrix tree cover and development density. We observed 43 species, comprised of 21 Neotropical migrants, 19 residents, and three short-distance migrants. Focal-patch tree-cover area and the matrix tree-cover area were the predominant contributors to a site’s overall forest-bird species richness at the rural–urban interface, but the addition of percent of over-story vegetation and percentage of deciduous tree cover influenced the ability of the patches to support forest species, especially Neotropical migrants. Development intensity in the matrix was unrelated to species richness and only had an effect in four species models. Although small forest patches remain an important conservation strategy in developed environments, the influence of matrix tree cover suggests that landscape design decisions in surrounding matrix can contribute conservation value at the rural–urban interface.

Although wetland condition assessment procedures have been developed, validated, and calibrated in the continental United States, they have not yet been fully developed or field-tested for wetlands in Hawai‘i. In order to address the need for comprehensive assessment methods for Hawaiian coastal wetlands, our research compared three indicators of landscape condition (landscape development intensity, road density, and forest cover) with wetland condition as measured by rapid assessment methods (RAM) and detailed field data collected on soil and water quality. We predicted that wetlands located in the least developed landscapes would have more nutrient rich soils, yet lower nutrient levels in the surface water, and would receive the highest rapid assessment scores. The hypotheses of our study were generally supported. However, while the correlations between landscape variables and δ15N isotopes and CRAM scores were relatively strong, the correlations between the landscape indicators and the other Level II and III field indicators were not very strong. These results suggest that further calibration and refinement of metrics is needed in order to more accurately assess the condition of Hawaiian coastal wetlands. A more detailed land use map, in addition to more comprehensive assessments of wetland water quality and biotic integrity would likely improve the relationships between indicators of landscape condition and wetland condition. Nonetheless, our research demonstrated that landscape analysis at larger scales (1,000 m buffers and watersheds) could provide managers with valuable information on how regional stressors may be affecting wetland water quality (measured as δ15N in plant tissue) as well as overall wetland condition (RAM scores).

Housing growth is a primary form of landscape change that is occurring throughout the world. Because of the ecological impacts of housing growth, understanding the patterns of growth over time is imperative in order to better inform land use planning, natural resource management, and conservation. Our primary goal was to quantify hotspots of housing growth in the North Central United States over a 60-year time frame (1940–2000) using a spatial statistical approach. Specifically, our objectives were to: (1) determine where housing growth hotspots exist; (2) determine if hotspots are changing in space and over time; and, (3) investigate if hotspots differ based upon the type of measurement and scale of analysis. Our approach was based on a spatial statistical framework (Getis-Ord G* statistic) that compared local housing growth patterns with regional growth rates. Over the 60-year period the number and mean area of hotspots, measured both as absolute and percent growth, remained largely constant. However, total area of all hotspots increased significantly over time as measured by absolute growth. Spatially, the hotspots shifted over time and exhibited different patterns based upon the measurement. Absolute growth hotspots exhibited patterns of expanding sets of rings around urban centers, whereas percent growth hotspots exhibited both expanding rings and shifting locations throughout rural locations. When increasing the neighborhood size used to discern hotspots from 5 to 50 km, the number of hotspots decreased while their size increased. Regardless of neighborhood size, ∼95 and ∼88% of the landscape, as measured by absolute and percent growth, respectively, never contained a hotspot. Overall our results indicate that housing growth is occurring at distinct locations on the landscape, which change in space and time, and are influenced by the scale of analysis and type of measure. In general these results provide useful information for the natural resource, planning, and policy communities.