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Baltimore forest patch point-sample overstory and understory vegetation, 2018-2020

Urban forest patches, including woodland interiors and bounding edge habitat, result from secondary succession and fragmentation of more extensive forested landscapes in the eastern USA. Management regimes, surrounding land use, and successional processes lead to distinct environments and contribute to local and regional heterogeneity. However, many woodlands are degraded due to frequent disturbance, aggressive exotic species, and heavy browsing, which stress canopies, reduce regeneration, and may reduce ecosystem services. Effective management requires rapid, repeatable assessment of forest composition, structure, and condition at the scale of local decision-making. We present and apply a protocol for characterizing urban woodlands that generates new insight into the status of urban woodlands and baseline data for change detection over time. Samples of overstory composition, ground cover, surface soil measurements, and the Schumacher Vine Encroachment Index were collected at 845 points across each of 47 patches across Baltimore, Maryland. Simple citywide summaries allowed characterization of Baltimore’s urban overstories as overwhelmingly native, though dominated by a range of successional conditions. By contrast, we found that ground layers were predominantly exotic, with abundant invasives or ruderal native species benefitting from disturbed conditions. Seven overstory types were distinguished, the majority under threat from aggressive vines. Most soils showed little evidence of compaction, but variable organic content. Distributed data allowed crosspatch comparison as well as within-patch analyses along edge-to-interior gradients. Species diversity, nativity, and overstory basal area all increased towards woodland interiors, whereas soil compaction and vine encroachment decreased. Structural and compositional shifts in both overstory and ground layer species revealed indicators of edge (15.2-18.7 m) and interior (> 41.5 m) conditions, as well as evidence of tran

ShareScore

52/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
12
Harmonization
16
Access
12
Reuse readiness
8
Engagement
4

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