Landscape, vegetation characteristics, and group identity in an urban and suburban watershed: why the 60s matter

Boone, Christopher G.; Cadenasso, Mary L.; Grove, J. Morgan; Schwarz, Kirsten; Buckley, Geoffrey L.

doi:10.1007/s11252-009-0118-7

Cited by 175 publications

(112 citation statements)

References 31 publications

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“…Additional historical research on restrictive deed covenants and neighborhood improvement associations show that racial discrimination continued long after the redlining maps were in force (Boone 2013). Other environmental inequalities such as those associated with the uneven distribution of parks (Boone et al 2009), current distributions of urban heat islands (Huang et al 2011), tree canopy cover, and vacant lots (Grove et al 2015) are closely aligned with neighborhoods that were redlined during the 1930s. We hypothesize that these long-term patterns create persistent legacies that constrain current and future locational and land choices in several ways.…”

Section: The Urban Engineered Watershed: a Specific Model For Integramentioning

confidence: 99%

Dynamic heterogeneity: a framework to promote ecological integration and hypothesis generation in urban systems

et al. 2016

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Urban areas are understood to be extraordinarily spatially heterogeneous. Spatial heterogeneity, and its causes, consequences, and changes, are central to ecological science. The social sciences and urban design and planning professions also include spatial heterogeneity as a key concern. However, urban ecology, as a pursuit that integrates across these disciplines, lacks a theoretical framework that synthesizes the diverse and important aspects of heterogeneity. This paper presents the concept of dynamic heterogeneity as a tool to explore how social and ecological heterogeneities interact and how they together act as both an outcome of past interactions and a driver future heterogeneity and system functions. To accomplish this goal, we relate heterogeneity to the fundamental concept of the human ecosystem. The human ecosystem concept identifies key processes that require operationalized models of dynamic heterogeneity in three process realms: the flow of materials, the assembly of urban ecosystem biota, and the locational choices humans make concerning land. We exemplify a specific dynamic model of heterogeneity in each of these realms, and indicate a range of complementary statistical approaches to integrate the drivers and outcomes of dynamic heterogeneity across the three realms. We synthesize a hierarchical framework for a theory of dynamic urban heterogeneity, noting its complementarity to other major urban theories and general model approaches. We hypothesize that human actions and structures amplify the dynamics of heterogeneity in urban systems.

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Section: The Urban Engineered Watershed: a Specific Model For Integramentioning

confidence: 99%

Dynamic heterogeneity: a framework to promote ecological integration and hypothesis generation in urban systems

et al. 2016

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“…Directly testing this assertion would require longitudinal analysis. Nevertheless, others have noted the role of time lags and land legacy in both inherited versus contemporary observed landscape characteristics (Boone et al 2010).…”

Section: Morzillo Unpublished Data)mentioning

confidence: 99%

Resident perceptions of natural resources between cities and across scales in the Pacific Northwest

Morzillo¹,

Kreakie²,

Netusil³

et al. 2016

E&S

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ABSTRACT. As the global population becomes increasingly urban, research is needed to explore how local culture, land use, and policy will influence urban natural resource management. We used a broad-scale comparative approach and survey of residents within the Portland (Oregon)-Vancouver (Washington) metropolitan areas, USA, two states with similar geographical and ecological characteristics, but different approaches to land-use planning, to explore resident perceptions about natural resources at three scales of analysis: property level ("at or near my house"), neighborhood ("within a 20-minute walk from my house"), and metro level ("across the metro area"). At the metro-level scale, nonmetric multidimensional scaling revealed that the two cities were quite similar. However, affinity for particular landscape characteristics existed within each city with the greatest difference generally at the property-level scale. Portland respondents expressed affinity for large mature trees, tree-lined streets, public transportation, and proximity to stores and services. Vancouver respondents expressed affinity for plentiful accessible parking. We suggest three explanations that likely are not mutually exclusive. First, respondents are segmented based on preferences for particular amenities, such as convenience versus commuter needs. Second, historical land-use and tax policy legacies may influence individual decisions. Third, more environmentally attuned worldviews may influence an individual's desire to produce environmentally friendly outcomes. Our findings highlight the importance of acknowledging variations in residents' affinities for landscape characteristics across different scales and locations because these differences may influence future land-use policies about urban natural resources.

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“…Many other studies cite socio-economic factors as a dominant force driving urban green space changes (e.g., Iverson and Cook, 2000;Hope et al, 2003;Grove et al, 2006;Troy et al, 2007;Escobedo et al, 2006;Kirkpatrick et al, 2007;Conway and Hackworth, 2007;Zhang, 2010;Boone et al, 2010;Szantoi et al, 2012). More affluent places have a greater percentage of green space simply because more money can be invested in greening initiatives as opposed to basic needs, a phenomenon described as the "Luxury Effect" (Hope et al, 2003); this phenomenon, while not necessarily given this specific name, was also reported in other cases (Iverson and Cook, 2000;Escobedo et al, 2006;Luck et al, 2009;Troy et al, 2012;Cohen et al, 2012).…”

Section: Factors Affecting the Green Spaces Pattern Changes In Beijingmentioning

confidence: 99%

“…The more affluent residents might be able to provide more resources for their residential green space, and in turn, residential places with higher greening cover and plant diversity will attract more affluent buyers (Hope et al, 2003;Grove et al, 2006;Luck et al, 2009;Boone et al, 2010). House price varies by landscape type: attractive landscape types were shown to attract a premium of 5 ± 12% over less attractive environmental settings; a large tree in the front yard of the residence could increase the housing sales price by 0.88% (Anderson and Cordell, 1988).…”

Section: Factors Affecting the Green Spaces Pattern Changes In Beijingmentioning

confidence: 99%

Variations of urban greenness across urban structural units in Beijing, China

Wang

Qiu

Breuste

et al. 2013

Urban Forestry & Urban Greening

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a b s t r a c tUrban structural units (USUs) are work (or similar) units in urbanized areas. In this study, USUs based on urban land use and land cover were used to explain and compare urban ecological conditions within Beijing. This study focused on the spatial pattern of land use for different USUs in urban areas. The results showed that 453 USUs belong to 12 primary USUs and to 38 different secondary USUs. The percentage of built-up area was highest in those regions with hotels, and lowest in areas with cemeteries. The percentage of woodland area was highest in primary and middle schools, and the lowest in entertainment plazas. The percentage of grassland area was highest in farmland or orchards, and lowest in Siheyuan (courtyards). The percentage of green space is highest in lands dedicated to middle and primary schools, and lowest in areas with museums. There is no significant linear relationship between construction period and green space percentage in Colleges/Universities (R = 0.045, p = 0.806 > 0.05) and Parks (R = 0.13, p = 0.43 > 0.05). However, there was an inverted-U curve relationship with the relevant housing price in the residential area, a relationship that can be described by the equation: f = 17736.45 + 348.21x − 4.15 x 2 , p = 0.0022 < 0.05. This relationship implied that the socio-economic factors like housing prices may be a factor in determining the green space pattern of urban ecosystems in Beijing.

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Landscape, vegetation characteristics, and group identity in an urban and suburban watershed: why the 60s matter

Cited by 175 publications

References 31 publications

Dynamic heterogeneity: a framework to promote ecological integration and hypothesis generation in urban systems

Dynamic heterogeneity: a framework to promote ecological integration and hypothesis generation in urban systems

Resident perceptions of natural resources between cities and across scales in the Pacific Northwest

Variations of urban greenness across urban structural units in Beijing, China

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