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The aesthetic, economic, and environmental benefits of urban trees are well recognized. Previous research has focused on understanding how a variety of social and environmental factors are related to urban vegetation. The aim is often to provide planners with information that will improve residential neighborhood design, or guide tree planting campaigns encouraging the cultivation of urban trees. In this paper we examine a broad range of factors we hypothesize are correlated to urban tree canopy heterogeneity in Salt Lake County, Utah. We use a multi-model inference approach to evaluate the relative contribution of these factors to observed heterogeneity in urban tree canopy cover, and discuss the implications of our analysis. An important contribution of this work is an explicit attempt to account for the confounding effect of neighborhood age in understanding the relationship between human and environmental factors, and urban tree canopy. We use regression analysis with interaction terms to assess the effects of 15 human and environmental variables on tree canopy abundance while holding neighborhood age constant. We demonstrate that neighborhood age is an influential covariate that affects how the human and environmental factors relate to the abundance of neighborhood tree canopy. For example, we demonstrate that in new neighborhoods a positive relationship exists between street density and residential tree canopy, but the relationship diminishes as the neighborhood ages. We conclude that to better understand the determinants of urban tree Urban Ecosyst (2012) 15:247-266 canopy in residential areas it is important to consider both human and environmental factors while accounting for neighborhood age.

ABSTRACT. Drylands cover 41% of the terrestrial surface and support > 36% of the world's population. However, the magnitude of dryland degradation is unknown at regional and global spatial scales and at 15-30-yr temporal scales. Historical archives of > 30 yr of Landsat satellite imagery exist and allow local to global monitoring and assessment of a landscape's natural resources in response to climatic events and human activities. Vegetation indices (VIs), i.e., proxies of vegetation characteristics such as phytomass, can be derived from the spectral properties of Landsat imagery. A dynamical systems analysis method called mean-variance analysis can be used to describe and quantify dynamic regimes of VI response to disturbance using characteristics of ecological resilience, particularly amplitude and malleability, from a change detection perspective. Amplitude is the magnitude of response of a VI to a disturbance; malleability is the degree of recovery of a resource after a disturbance. Spatially aggregate and spatially explicit (image) differencing are methods whereby a VI image or statistic from one time period is subtracted from a VI image or statistic from another time period. To illustrate this method, we used a time series of Landsat imagery from 1972 to 1987 to measure the response of vegetation communities that are managed by subsistence agropastoral communities to the severe 1982-1984 El Niño-induced drought on the Bolivian Altiplano. We found that the entire landscape had decreased vegetation cover, increased variance (diagnostic of a regime shift), and thus, increased susceptibility to soil erosion during the drought. The wet meadow vegetation cover class had the lowest amplitude and thus the most resilience relative to other vegetation cover classes. This response identified the wet meadow as a key resource, as well as a harbinger of climate change for agropastoral communities in areas where drought is an endemic stressor.

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The degree of rangeland degradation in the United States is unknown due to the failure of traditional field-based monitoring to capture the range of variability of ecological indicators and disturbances, including climatic effects and land use practices, at regional to national spatial scales, and temporal scales of decades. Here, a protocol is presented for retrospective monitoring and assessment of rangeland degradation using historical time series of remote sensing data and catastrophe theory as an ecological framework to account for both gradual and rapid changes of state. This protocol 1) justifies the use of time-series satellite imagery in terms of the spatial and temporal scale of data collection; 2) briefly explains how to acquire, process, and transform the data into ecological indicators; 3) discusses the use of time-series analysis as the appropriate procedure for detecting significant change; and 4) explains what reference conditions are appropriate. Landsat data have been collected and archived since 1972, and include complete coverage of US rangelands. Characteristics of land degradation can be retrospectively measured for a nearly 33-year trend using surrogate remote sensing-based indicators that correlate with changes in life-form composition (time series of thematic maps), declines in vegetation productivity (vegetation indices), accelerated soil erosion (soil indices), declines in soil quality (piospheric analysis), and changes in landscape configuration (time series of thematic maps). Aspects of 2 retrospective studies are presented as examples of application of the protocol to considerations of the land use impacts from military training and testing and ranching activities on rangelands. Resumen El grado de degradació n de los pastizales en los Estados Unidos de América es desconocido debido al fracaso del monitoreo tradicional de campo para capturar el rango de variabilidad de los indicadores ecoló gicos y disturbios, incluyendo los efectos climáticos y prácticas de uso de la tierra, a escalas espaciales de regional a nacional y escalas temporales de décadas. Consecuentemente, es presentado un protocolo para el monitoreo retrospectivo y la evaluació n de la degradació n de los pastizales usando series de tiempo histó ricas de sensores remotos y la teoría de catástrofe como un marco ecoló gico para cuantificar tanto los cambios graduales como los rápidos del estado del pastizal. Este protocolo: 1) justifica el uso de series de tiempo de imágenes de satélite en términos de escalas espacial y temporal de colecció n de datos; 2) explica brevemente como adquirir, procesar y transformar los datos en indicadores ecoló gicos; 3) discute el uso del análisis de series de tiempo como un procedimiento adecuado para detectar cambios significativos; y 4) explica que condiciones de referencia son apropiadas. Datos de Landsat han sido colectados y archivados desde 1972 e incluyen una cobertura completa de los pastizales de Estados Unidos de América. Las características de la degradació n de la tierra pueden...

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado. Overall rms. error was 24% for SWReGAP and 31% for FIA data. VCF bias was positive at low observed tree cover but systematically increased thereafter until at greater than 60% observed tree cover, VCF tree cover was 40% (SWReGAP) to 45% (FIA) too low. Errors are unlikely to be related to habitat fragmentation or variation in canopy height but may be influenced by scaling discontinuities between ground and satellite resolutions.