Matthew E. Baker

Urban forest patches, including woodland interiors and bounding edge habitat, result from secondary succession and fragmentation of more extensive forested landscapes in the eastern United States. 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 benefiting 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 cross‐patch comparison as well as within‐patch analyses along edge‐to‐interior gradients. Species diversity, nativity, and overstory basal area all increased toward 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 transitional zones with distinct patterns of biodiversity. Despite high levels of fragmentation and disturbance that challenge municipal land managers operating with limited resources, rapid, low‐cost sampling enabled comparison across multiple scales, encouraging repeated sampling and adaptive response to changing forest conditions. Qualitative and quantitative analysis as well as specific examples illustrated the generic utility of the protocol for a range of applications and its ability to produce new insight enabling management action and informed conservation planning.

Forest patches in urban landscapes make outsized contributions to biodiversity, ecosystem function, and human health and well‐being. However, urbanization can alter environmental conditions that underpin forest health. Most studies of forest health in urban landscapes have focused on few forest patches across a single metropolitan region, and synthesis is needed to understand broader patterns. We assessed variation among measures of forest health across land cover gradients and ecoregions by determining (1) whether the degree of urban, agricultural, and forested land surrounding a forest patch was reflected in differences in tree community composition, diversity, and structure and (2) whether these differences were consistent across ecoregions. We synthesized data from 17 observational studies (3334 plots) and remotely sensed land cover (1‐km buffer) across four metropolitan regions (Baltimore–Washington DC, Chicago, New York City, and Philadelphia) spanning five ecoregions of the eastern deciduous forest of North America. Land cover surrounding forest patches differed among ecoregions, and forests were surrounded by heterogeneous land cover even in the most urbanized areas. Patterns of tree species composition and forest structure reflected landscape context. Forest patches surrounded by high canopy cover had greater or equal tree species diversity, density, basal area, and diversity of tree sizes relative to patches surrounded by highly agricultural or highly impervious landscapes. In contrast, there was little difference in structure and diversity between forests in highly agricultural and impervious settings. Tree species composition varied among ecoregions, yet tree community assemblages of forests in intensively urbanized areas were consistently distinct from those of forests in other contexts. Forest patches in the most urban and most agricultural landscapes shared predominantly native species communities and were characterized by low tree species diversity, basal area, and size class diversity, as well as high non‐native tree abundance, highlighting commonalities among these intensive anthropogenic landscapes. These results point to both common challenges to forest health and common opportunities for forest stewardship in urban and agricultural landscapes.

Plant traits are often measured in the field or laboratory to characterize stress responses. However, direct measurements are not always cost effective for broader sampling efforts, whereas indirect approaches such as reflectance spectroscopy could offer efficient and scalable alternatives. Here, we used field spectroscopy to assess whether (1) existing vegetation indices could predict leaf trait responses to heat stress, or if (2) partial least squares regression (PLSR) spectral models could quantify these trait responses. On several warm, sunny days, we measured leaf trait responses indicative of photosynthetic mechanisms, plant water status, and morphology, including electron transport rate (ETR), photochemical quenching (qP), leaf water potential (Ψ_leaf), and specific leaf area (SLA) in 51 urban trees from nine species. Concurrent measures of hyperspectral leaf reflectance from the same individuals were used to calculate vegetation indices for correlation with trait responses. We found that vegetation indices predicted only SLA robustly (R² = 0.55), while PLSR predicted all leaf trait responses of interest with modest success (R² = 0.36 to 0.58). Using spectral band subsets corresponding to commercially available drone-mounted hyperspectral cameras, as well as those selected for use in common multispectral satellite missions, we were able to estimate ETR, qP, and SLA with reasonable accuracy, highlighting the potential for large-scale prediction of these parameters. Overall, reflectance spectroscopy and PLSR can identify wavelengths and wavelength ranges that are important for remote sensing-based modeling of important functional trait responses of trees to heat stress over broad ranges.

This archive contains research data collected and/or funded by Forest Service Research and Development (FS R&D), U.S. Department of Agriculture. It is a resource for accessing both short and long-term FS R&D research data, which includes Experimental Forest and Range data. It is a way to both preserve and share the quality science of our researchers.

Context: Previous studies developed distance-weighted regression to describe how land use effects on aquatic systems attenuate with arrangement of source areas within catchments. Objectives: We clarify and extend the conceptual foundations of this approach, enhance the spatial and statistical methods, and provide new tools to interpret the results. Methods: We derive the framework from first principles to resolve conceptual issues with how weighting is applied to source area versus total area, and we formalize the requirements for an ideal weighting function. We quantify the spatial distributions of land areas in a way that integrates with model fitting. We adapt non-linear optimization to simultaneously fit regression and weighting parameters. We quantify the spatial distribution of source effects with arrangement and document how different weighting functions alter that distribution. Results: To verify their utility, we applied these methods to a published analysis relating polychlorinated biphenyls in fish to developed land use in catchments. We identified a stronger distance-weighted model and more completely characterized the effects of weighting on where aquatic impacts originate. Conclusions: Our methods enable more comprehensive analyses of the effects of spatial arrangement to better inform a wide range of scientific investigations and applications. Our methods can relate almost any spatially distributed source or driver to an integrated response at a point or along a boundary; and alternate hypotheses about the effects of pattern or proximity on processes can be tested with alternative weighting functions. New applications will generate additional weighting functions that enhance the general approach.

Intensive agricultural landscapes pose a challenge to wildlife managers, policymakers, and landowners hoping to increase the diversity of desired wildlife species, such as grassland birds, which require urgent conservation action. In intensive agricultural landscapes, like those of the Midwestern United States, most land area is privately owned and operated and managed primarily for production. Thus, conducting ecological research in intensive agricultural landscapes requires collaborative approaches aimed at farm owners and operators. Recent advances in acoustic data collection and high‐resolution habitat mapping, including low‐cost acoustic recorders and satellite remote sensing, may be well positioned to address this challenge by enabling expanded assessments and monitoring of wildlife populations and habitats across regions. This study examined fine‐grained habitat characteristics and their relationship with avian biodiversity in intensive agricultural landscapes at 44 agricultural sites across the state of Iowa. Passive acoustic monitoring and manual identification of bird species allowed for measurement of vocalizing bird richness. High‐resolution mapping of noncrop vegetation provided detailed information on small noncrop vegetation habitat complexes within row‐crop agriculture. Measures of image texture provided characterizations of compositional heterogeneity within noncrop vegetation. General linear Poisson modeling demonstrated robust associations between noncrop vegetation and vocalizing bird richness, yet variation in grassland bird richness was not well predicted by noncrop vegetation. Noncrop vegetation texture demonstrated potential as a predictor of vocalizing bird richness, though not better than or when combined with noncrop vegetated area, indicating it may not be an independent measure of habitat quality. Passive acoustic monitoring resulted in useful data at 44 out of 60 originally selected sites, with some lost to failed recorders and/or collaboration issues. Challenges remain in detecting habitat characteristics that promote grassland birds in row crop landscapes. Working toward probabilistic research design across privately owned working landscapes and incorporating more detailed management practice information would improve the transferability of this approach to farmland management and policy.

Understanding patterns of species coexistence is a fundamental challenge in ecology. The physical environment is believed to play an important role, influencing patterns of dispersal and biotic interactions across space and time. Floodplain forest species are presumed to interact strongly with their environment, as evidenced by pronounced spatial variation in forest composition associated with flood‐driven abiotic constraints. Questions of how, and to what degree, fine‐scale heterogeneity interacts with broad‐scale hydrogeomorphology to influence patterns of functional composition remain unresolved. We examined how functional diversity (i.e. richness and range of functional traits) and ecological strategies (i.e. functional trait combinations) of floodplain forest communities varied across regional and local gradients of flooding in a northern temperate region of the United States of America. We found functional diversity of woody overstory species varied across hydrogeomorphic settings and that different settings altered associations between functional diversity and both the relative elevation above and proximity to rivers. Ecological strategies shifted over local gradients of relative elevation and distance to channel with different magnitudes and directions depending on the broader hydrogeomorphic context. We found evidence that interactions among flood regimes and landform position impose different levels of functional constraint. These results indicate patterns of community assembly are not easily discerned from landform type or position alone, but rather from filtering that operates and interacts with biota over multiple spatial scales. Our results imply that it is important to characterize flood dynamics in ways that can be clearly linked to ecological processes and that treatment of floodplain landforms as transferable units across river‐valley segments is problematic, even within a single basin.

Under‐representations of headwater channels in digital stream networks can result in uncertainty in the magnitude of headwater habitat loss, stream burial, and watershed function. Increased availability of high‐resolution (<2 m) elevation data makes the delineation of headwater channels more attainable. In this study, elevation data derived from light detection and ranging was used to predict ephemeral stream networks across a forested and urban watershed in the Maryland Piedmont USA. A method was developed using topographic openness (TO) and wetness index to remotely predict the extent of stream networks. Predicted networks were compared against a comprehensive field survey of the ephemeral network in each watershed to evaluate performance. Comparisons were also made to the U.S. Geological Survey National Hydrography Dataset (NHD) and a flow accumulation approach where a single drainage area threshold defined channel initiation. Although the NHD and flow accumulation methods resulted in low commission errors, omission errors were highest in these networks. The TO‐based networks detected a larger number of ephemeral channels, but with higher commission error. Small ephemeral channels with less defined banks or originating at groundwater seeps were difficult to detect in all methods. Comparisons between forested and urban watersheds also highlight the difficulty of identifying headwater channels using topographic attributes in human‐modified landscapes.

Tree cover is generally associated with cooler air temperatures in urban environments but the roles of canopy configuration, spatial context, and time of day are not well understood. The ability to examine spatiotemporal relationships between trees and urban climate has been hindered by lack of appropriate air temperature data and, perhaps, by overreliance on a single ‘tree canopy’ class, obscuring the mechanisms by which canopy cools. Here, we use >70 000 air temperature measurements collected by car throughout Washington, DC, USA in predawn (pd), afternoon (aft), and evening (eve) campaigns on a hot summer day. We subdivided tree canopy into ‘soft’ (over unpaved surfaces) and ‘hard’ (over paved surfaces) canopy classes and further partitioned soft canopy into distributed (narrow edges) and clumped patches (edges with interior cores). At each level of subdivision, we predicted air temperature anomalies using generalized additive models for each time of day. We found that the all-inclusive ‘tree canopy’ class cooled linearly at every time (pd = 0.5 °C ± 0.3 °C, aft = 1.8 °C ± 0.6 °C, eve = 1.7 °C ± 0.4 °C), but could be explained in the afternoon by aggregate effects of predominant hard and soft canopy cooling at low and high canopy cover, respectively. Soft canopy cooled nonlinearly in the afternoon with minimal effect until ∼40% cover but strongly (and linearly) across all cover fractions in the evening (pd = 0.7 °C ± 1.1 °C, aft = 2.0 °C ± 0.7 °C, eve = 2.9 °C ± 0.6 °C). Patches cooled at all times of day despite uneven allocation throughout the city, whereas more distributed canopy cooled in predawn and evening due to increased shading. This later finding is important for urban heat island mitigation planning since it is easier to find planting spaces for distributed trees rather than forest patches.

Measuring, monitoring, and managing biodiversity across agricultural regions depends on methods that can combine high-resolution mapping of landscape patterns with local biodiversity observations. This study explores the potential to monitor biodiversity in agricultural landscapes by linking high-resolution remote sensing with passive acoustic monitoring. Land cover maps produced using a small unmanned aerial system (UAS) and PlanetScope (PS) satellite imagery were used to investigate relationships between landscape patterns and an acoustically derived biodiversity index (vocalizing bird species richness) across 12 agricultural sample locations equipped with acoustic recorders in Iowa, USA during the 2018 growing season. Statistical assessment revealed a significant direct association between vocalizing bird richness and percent noncrop vegetation cover. High spatial resolution (1 m) UAS mapping produced stronger statistical associations than PS-based maps (3 m) for landscape composition metrics. Landscape configuration metrics (Shannon’s diversity index, contagion, perimeter-area-ratio, and circumscribing circle index) were either cross-correlated with composition metrics or unusable owing to complete landscape homogeneity in some agricultural landscape samples. This study shows that high resolution mapping of noncrop vegetation cover can be linked with acoustic monitoring of unique bird vocalizations to provide a useful indicator of biodiversity in agricultural landscapes.