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  1. Savanna plant communities are highly diverse, characterized by an open-canopy structure with rich herbaceous diversity, and maintained by frequent low-intensity fire and grazing. Due to habitat loss and fragmentation, savannas are globally threatened, with less than 1% of former oak savanna land cover found in the Midwestern United States remaining. In remnant oak savannas, loss of fire and grazing has led to woody encroachment and canopy closure over the past century with cascading consequences for the taxonomic composition. Whether these taxonomic changes can be broadly predicted using species functional traits (morpho-physio-phenological characteristics that impact the fitness of a species) is a key question. We ask whether the impacts of woody encroachment on herbaceous species can be predicted from species’ abilities to persist (avoid extinction) and disperse (colonize new areas). Specifically, we pair persistence traits (e.g., clonality, belowground storage) and dispersal traits (e.g., seed mass, dispersal mode, flowering height) with a rare 60-year dataset from oak savannas in Wisconsin, USA to understand how the representation of these traits has changed in the herbaceous community over time. Over 60 years, change in species composition was explained both by dispersal abilities and persistence traits; small-seeded species reliant on unassisted dispersal and moderately clonal species experienced the greatest losses. These changes in functional composition are likely due to increased woody encroachment, which may impede propagule production and movement. Restoration efforts need to prioritize species that are dispersal limited and those that create fine fuels, which aid the persistence of fire-maintained open habitat savannas. 
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  2. Abstract

    Advances in remote sensing technologies offer new means to monitor habitats of importance on large scales. Florida rosemary scrub is one such threatened habitat, found in patches across the landscape in relatively elevated areas, and is often characterized by shrub‐less areas (gaps) among the dominant shrubs, which provide favorable microhabitats for many endemic and endangered plants and animals. However, gaps are difficult and time‐consuming to characterize, especially across large areas, using traditional ground‐based field methods. We developed and tested a method for rapidly classifying gaps using an unmanned aerial vehicle (UAV or drone). Aerial data were collected by a UAV‐mounted camera in April 2018, and stratified, random ground surveys to verify UAV data were conducted March through April 2018 at Archbold Biological Station in south‐central Florida, USA. We used mosaicked and georeferenced digital surface and terrain models to calculate vegetation height across 33 rosemary scrub sites (~230,000 m2at 0.064 m2pixel resolution). Gaps were defined as >1 m2areas where vegetation height was <10 cm. We found that gap areas from UAV models and field surveys were significantly correlated across varying gap sizes, times‐since‐fire, and relative elevations. We also observed a significant decrease in mean gap area and percent gap space with increasing time‐since‐fire, a pattern consistent with smaller‐scale, ground‐based sampling, and a marginally significant increase in gap area with relative elevation. This remote sensing method lends itself to better exploration of how gap areas, their spatiotemporal patterns, and associated fire history, elevation, soil, and other geographic data affect structural vegetation dynamics across the landscape. This study illustrates the success of UAV modeling of gap space in Florida rosemary scrub, a result of regional consequence for the southeastern United States, but more broadly, it encourages the use of UAV technology as a tool to enhance traditional field‐based methods in systems globally. As habitat fragmentation and loss become increasingly problematic for the conservation of threatened habitats, understanding these complex spatial dynamics is crucial to the conservation and management of vegetation communities and their biodiversity.

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