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Forest and water‐resources management in floodplains requires an understanding of the nature of drought specific to ecosystems there. The complex relationships among floodplain vegetation, topography and hydrology affect water availability. This paper investigated whether hydrological assumptions within meteorological drought indicators and ecophysiological assumptions within remote‐sensing drought indicators reflect drought deficits as they occur in floodplain forests. We compared the performance of widely used meteorological and remote‐sensing drought indicators in floodplain forests to tree‐ring validation using five species at three floodplains in eastern Texas, USA. We found that the water balance in the Standardized Precipitation Evapotranspiration Index and the water loss estimated by the Evaporative Stress Index were useful models of water deficits in floodplain forests at the site and sub‐site scales, respectively. Hydrological and stand conditions varied among sites enough to affect the specific patterns of tree‐species responded to drought. However, of the species we examined, tree rings in green ash were the most consistently affected by drought across floodplains and were the most closely correlated with both meteorological and remotely sensed drought indicators. Finally, drought effects varied by species and among and within floodplains, but generally, growth of trees in topographically drier sites was more closely correlated with drought indicators. [ABSTRACT FROM AUTHOR]

Vegetation canopy height mapping is vital for forest monitoring. However, the high cost and inefficiency of manual tree measurements, coupled with the irregular and limited local-scale acquisition of airborne LiDAR data, continue to impede its widespread application. The increasing availability of high spatial resolution imagery is creating opportunities to characterize forest attributes at finer resolutions over large regions. In this study, we investigate the synergy of airborne lidar and high spatial resolution USDA-NAIP imagery for detailed canopy height mapping using an image-to-image deep learning approach. Our main inputs were 1 m NAIP image patches which served as predictor layers and corresponding 1 m canopy height models derived from airborne lidar data, which served as output layers. We adapted a U-Net model architecture for canopy height regression, training and validating the models with 10,000 256-by-256 pixel image patches. We evaluated three settings for the U-Net encoder depth and used both 1 m and 2 m datasets to assess their impact on model performance. Canopy height predictions from the fitted models were highly correlated (R2 = 0.70 to 0.89), precise (MAE = 1.37–2.21 m), and virtually unbiased (Bias = −0.20–0.07 m) with respect to validation data. The trained models also performed adequately well on the independent test data (R2 = 0.62–0.78, MAE = 3.06–4.1 m). Models with higher encoder depths (3,4) and trained with 2 m data provide better predictions than models with encoder depth 2 and trained on 1 m data. Inter-comparisons with existing canopy height products also showed our canopy height map provided better agreement with reference airborne lidar canopy height estimates. This study shows the potential of developing regional canopy height products using airborne lidar and NAIP imagery to support forest productivity and carbon modeling at spatially detailed scales. The 30 m canopy height map generated over Texas holds promise in advancing economic and sustainable forest management goals and enhancing decision-making in natural resource management across the state. [ABSTRACT FROM AUTHOR]

Despite his marked intellectual indebtedness to Coulter and his mentor's massive 588-page tome, Bray's scholarship dovetailed with that of his classmate and later University of Chicago ecologist Henry Chandler Cowles; the latter's pathbreaking research on habitat succession in the Indiana Dunes near Chicago sparked concerted efforts to protect this imperiled plant community.11 As Bray noted about his own work, it too focused on "the study of plants in their natural environments", that is, in their ecological relationships.12 The organizational structure of Bray's dissertation reflected its innovative methodology. 48 Bray, " I The Timber of the Edwards Plateau i , 25; making extensive use of Bray's foundational report is Lisa O'Donnell, I Historical Ecology of the Texas Hill Country i (Austin: City of Austin, Wildland Conservation Division, 2019), < http://www.austintexas.gov/edims/document.cfm?id=321715 > [Accessed Feb. 9, 2021]. 61 Bray, "The Timber of the Edwards Plateau", 29. 62 Rodgers, I Bernhard Eduard Fernow i , 482-485; Frank N. Edgerton, I A Centennial History of Ecological Society of America i (Boca Raton, Fla.: CRC Press/Taylor & Francis Group, 2015), 1-28. 63 Faust, "William L. Bray"; Anders S. Saustrup, "Bray, William L." I The Handbook of Texas Online i , < https://www.tshaonline.org/handbook/entries/bray-william-l > [Accessed Dec. 22, 2020]. Graph: Ecologist William L. Bray (1865-1953) was an expert on the vegetation of western Texas and one of the state's first conservationists; he taught at the University of Texas and Syracuse University. [Extracted from the article]