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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. 

Land-use and land-cover (LULC) change is a primary driver of terrestrial carbon release, often through the conversion of forest into agriculture or expansion of urban areas. Classification schemes are a key component of landscape analyses. This study creates a novel LULC classification scheme by incorporating ecological data to redefine classes of an existing LULC classification based on variation in above-ground tree carbon. A tree inventory was conducted for 531 plots within a subbasin of the Tampa Bay Watershed, Florida, USA. Above-ground tree carbon was estimated using the i-Tree model. Plots were classified using the Florida Land Use Cover Classification System. Mean quantities of above-ground tree carbon, by class, were tested for statistical differences. A reclassification was conducted based on these differences. Sub-classes within a given “land cover” class were similar for six of the seven classes. Significant differences were found within the “Wetlands” class based on vegetation cover, forming two distinct groups: “Forested Wetlands” and “Non-forested and Mangrove Wetlands”. The urban “land use” class showed differences between “Residential” and “Non-residential” sub-classes, forming two new classes. LULC classifications can sometimes aggregate areas perceived as similar that are in fact distinct regarding ecological variables. These aggregations can obscure the true variation in a parameter at the landscape scale. Therefore, a study’s classification system should be designed to reflect landscape variation in the parameter(s) of interest. 

Abstract: Rain depth is collected using model 6011-A tipping bucket rain gauges manufactured by All Weather Inc. (formerly Qualimetrics). Two raingauges (RG1 and RG2) are installed at each of eight stations. Each rain gauge tip represents a depth of 0.01 inches of rainfall. Data are recorded by a data logger at the station and telemetered hourly to UMBC, where the data are stored in a data base. The rain gauges are not heated and therefore snow and ice storms are removed from the published record. The QA/QC procedure applied to the raw data includes removal of false tips and snow/ice events, accumulating tip data to a time series in inches/min, applying a laboratory-based calibration curve to the data, and converting corrected data to a one-minute time series in units of mm/min for publication.