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Abstract ContextLand use history of urban forests impacts present-day soil structure, vegetation, and ecosystem function, yet is rarely documented in a way accessible to planners and land managers. ObjectivesTo (1) summarize historical land cover of present-day forest patches in Baltimore, MD, USA across land ownership categories and (2) determine whether social-ecological characteristics vary by historical land cover trajectory. MethodsUsing land cover classification derived from 1927 and 1953 aerial imagery, we summarized present-day forest cover by three land cover sequence classes: (1) Persistent forest that has remained forested since 1927, (2) Successional forest previously cleared for non-forest vegetation (including agriculture) that has since reforested, or (3) Converted forest that has regrown on previously developed areas. We then assessed present-day ownership and average canopy height of forest patches by land cover sequence class. ResultsMore than half of Baltimore City’s forest has persisted since at least 1927, 72% since 1953. About 30% has succeeded from non-forest vegetation during the past century, while 15% has reverted from previous development. A large proportion of forest converted from previous development is currently privately owned, whereas persistent and successional forest are more likely municipally-owned. Successional forest occurred on larger average parcels with the fewest number of distinct property owners per patch. Average tree canopy height was significantly greater in patches of persistent forest (mean = 18.1 m) compared to canopy height in successional and converted forest patches (16.6 m and 16.9 m, respectively). ConclusionsHistorical context is often absent from urban landscape ecology but provides information that can inform management approaches and conservation priorities with limited resources for sustaining urban natural resources. Using historical landscape analysis, urban forest patches could be further prioritized for protection by their age class and associated ecosystem characteristics. 

Addressing the challenges of sustainable and equitable city management in the 21st century requires innovative solutions and integration from a range of dedicated actors. In order to form and fortify partnerships of multi-sectoral collaboration, expand effective governance, and build collective resiliency it is important to understand the network of existing stewardship organizations. The term ‘stewardship’ encompasses a spectrum of local agents dedicated to the evolving process of community care and restoration. Groups involved in stewardship across Baltimore are catalysts of change through a variety of conservation, management, monitoring, transformation, education, and advocacy activities for the local environment – many with common goals of joint resource management, distributive justice, and community power sharing. The “environment” here is intentionally broadly defined as land, air, water, energy and more. The Stewardship Mapping and Assessment Project (STEW-MAP) is a method of data collection and visualization that tracks the characteristics of organizations and their financial and informational flows across sectors and geographic boundaries. The survey includes questions about three facets of environmental stewardship groups: 1) organizational characteristics, 2) collaboration networks, and 3) stewardship “turfs” where each organization works. The data have been analyzed alongside landcover and demographic data and used in multi-city studies incorporating similar datasets across major urban areas of the U.S. Additional information about the growing network of cities conducting stewmap can be found here: https://www.nrs.fs.usda.gov/STEW-MAP/ Romolini, Michele; Grove, J. Morgan; Locke, Dexter H. 2013. Assessing and comparing relationships between urban environmental stewardship networks and land cover in Baltimore and Seattle. Landscape and Urban Planning. 120: 190-207. https://www.fs.usda.gov/research/treesearch/44985 Johnson, M., D. H. Locke, E. Svendsen, L. Campbell, L. M. Westphal, M. Romolini, and J. Grove. 2019. Context matters: influence of organizational, environmental, and social factors on civic environmental stewardship group intensity. Ecology and Society 24(4): 1. https://doi.org/10.5751/ES-10924-240401 Ponte, S. 2023. Social-ecological processes and dynamics of urban forests as green stormwater infrastructure in Maryland, USA. Doctoral dissertation, University of Maryland, College Park, MD. 

Landscape analyses are typically done using spatially explicit color aerial imagery. However, working with non-spatial black and white historical aerial photographs presents several challenges that require a combination of techniques and approaches. We analyzed 113 aerial images covering approx. 700 km2 (270 mi2) including all of Baltimore City, and a portion of Baltimore County surrounding the City. The images were taken between August 23rd 1952 and February 14th 1953. High-resolution scans were georeferenced and georectified against modern satellite imagery of the area and then combined to create a single raster mosaic. This process converted the images from a disparate set of photographs into a spatially explicit GIS data set that can be used to observe changes in land patches over time—and ultimately integrated with other long-term social, economic, and ecological data. 

Land-use and land cover classifications are typically created using automated methods to analyze modern, spatially explicit color aerial imagery. However, creating classifications from black and white historical aerial imagery presents a number of challenges that require a combination of more traditional, manual techniques and approaches. A georectified mosaic of 113 aerial images was digitized in ArcGIS to create a land-use/land cover classification. The analyzed area covered 700 km2 (270 mi2) including all of Baltimore City, and a portion of Baltimore County immediately surrounding the city. A combination of 8 land-use and land cover classes were used: Agriculture, Barren, Built (Other), Forest, Grass/Shrubland, Industrial, Residential, and Water. This geospatial data set captures an ecologically and socially important moment in the post-war history of the city. It can be used to examine relationships between property ownership and forest patch dynamics across time. These insights may help inform future environmental planning, conservation, management, and stewardship goals for Baltimore City forest patches, and other cities throughout the region. 

Urban grasslands cover large land areas in human-dominated landscapes, but little is known about how these landscapes cycle carbon (C). In this study, we examine turfgrass biomass and productivity at thirty-three urban grassland sites within the Gwynns Fall watershed (Baltimore, MD). These sites are characteristic of residential conditions in the region and were selected to provide contrasts in urban ecosystem structure (density of coarse vegetation and built structures) as well as historical (pre-development) land use. Aboveground net primary productivity (ANPP) was measured as the sum of clipping production plus stubble, thatch, and moss production. This work provides context for understanding the impact of urban expansion on regional ecosystem C dynamics and identifies specific needs related to standardized methods for measuring turfgrass ANPP in urban grassland systems. 

Landscape analyses are typically done using spatially explicit color aerial imagery. However, working with non-spatial black and white historical aerial photographs presents several challenges that require a combination of techniques and approaches. We analyzed 93 aerial images covering 544 km2 (210 mi2) including all of Baltimore City, and an area immediately adjacent to the city known at the time as the Metropolitan District of Baltimore County. The images were taken from a biplane between October 1926 and February 1927. High-resolution scans were georeferenced and georectified against modern satellite imagery of the area and then combined to create a single raster mosaic. This process converted the images from a disparate set of photographs into a spatially explicit GIS data set that can be used to observe changes in land patches over time—and ultimately integrated with other long-term social, economic, and ecological data. 

Land-use and land cover classifications are typically created using automated methods to analyze modern, spatially explicit color aerial imagery. However, creating classifications from black and white historical aerial imagery presents a number of challenges that require a combination of more traditional, manual techniques and approaches. A georectified mosaic of 93 aerial images was digitized in ArcGIS to create a land-use/land cover classification. The analyzed area covered 585 km2 (226 mi2) including all of Baltimore City, and an area immediately adjacent to the city known at the time as the Metropolitan District of Baltimore County. A combination of 8 land-use and land cover classes were used: Agriculture, Barren, Built (Other), Forest, Grass/Shrubland, Industrial, Residential, and Water. This geospatial data set captures a moment of dynamic expansion in the city, just prior to the Great Depression and can be used to examine relationships between property ownership and forest patch dynamics across time. These insights may help inform future environmental planning, conservation, management, and stewardship goals for Baltimore City forest patches, and other cities throughout the region. 

Foliar chemistry values were obtained from two important native tree species (white oak (Quercus alba L.) and red maple (Acer rubrum L.)) across urban and reference forest sites of three major cities in the eastern United States during summer 2015 (New York, NY (NYC); Philadelphia, PA; and Baltimore, MD). Trees were selected from secondary growth oak-hickory forests found in New York, NY; Philadelphia, PA; and Baltimore, MD, as well as at reference forest sites outside each metropolitan area. In all three metropolitan areas, urban forest patches and references forest sites were selected based on the presence of red maple and white oak canopy dominant trees in patches of at least 1.5 hectares with slopes less than 25%, and well-drained soils of similar soil series within each metropolitan area. Within each city, several forest patches were selected to capture the variation in forest patch site conditions across an individual city. All reference sites were located in protected areas outside of the city and within intermix wildland-urban interface landscapes, in order to target similar contexts of surrounding land use and population density (Martinuzzi et al. 2015). Several reference sites were selected for each city, located within the same protected area considered representative of rural forests of the region. White oaks were at least 38.1 cm diameter at breast height (DBH), red maples were at least 25.4 cm DBH, and all trees were dominant or co-dominant canopy trees. The trees had no major trunk cavities and had crown vigor scores of 1 or 2 (less than 25% overall canopy damage; Pontius & Hallett 2014). From early July to early August 2015, sun leaves were collected from the periphery of the crown of each tree with either a shotgun or slingshot for subsequent analysis to determine differences in foliar chemistry across cities and urban vs. reference forest site types. The data were used to invstigate whether differences in native tree physiology occur between urban and reference forest patches, and whether those differences are site- and species-specific. A complete analysis of these data can be found in: Sonti, NF. 2019. Ecophysiological and social functions of urban forest patches. Ph.D. dissertation. University of Maryland, College Park, MD. 166 p. References: Martinuzzi S, Stewart SI, Helmers DP, Mockrin MH, Hammer RB, Radeloff VC. 2015. The 2010 wildland-urban interface of the conterminous United States. Research Map NRS-8. US Department of Agriculture, Forest Service, Northern Research Station: Newtown Square, PA. Pontius J, Hallett R. 2014. Comprehensive methods for earlier detection and monitoring of forest decline. Forest Science 60(6): 1156-1163.