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Dam removal is a river restoration technique that has complex landscape-level ecological impacts. Unmanned aerial vehicles (UAVs) are emerging as tools that enable relatively affordable, repeatable, and objective ecological assessment approaches that provide a holistic perspective of restoration impacts and can inform future restoration efforts. In this work, we use a consumer-grade UAV, structure-from-motion (SfM) photogrammetry, and machine learning (ML) to evaluate geomorphic and vegetation changes pre-/post-dam removal, and discuss how the technology enhanced our monitoring of the restoration project. We compared UAV evaluation methods to conventional boots-on-ground methods throughout the Bellamy River Reservoir (Dover, NH, USA) pre-/post-dam removal. We used a UAV-based vegetation classification approach that used a support vector machine algorithm and a featureset composed of SfM-derived elevation and visible vegetation index values to map other, herbaceous, shrub, and tree cover throughout the reservoir (overall accuracies from 83% to 100%), mapping vegetation succession as well as colonization of exposed sediments that occurred post-dam removal. We used SfM-derived topography and the vegetation classifications to map erosion and deposition throughout the reservoir, despite its heavily vegetated condition, and estimate volume changes post-removal. Despite some limitations, such as influences of refraction and vegetation on the SfM topography models, UAV provided information on post-dam removal changes that would have gone unacknowledged by the conventional ecological assessment approaches, demonstrating how UAV technology can provide perspective in restoration evaluation even in less-than-ideal site conditions for SfM. For example, the UAV provided perspective of the magnitude and extent of channel shape changes throughout the reservoir while the boots-on-ground topographic transects were not as reliable for detecting change due to difficulties in navigating the terrain. In addition, UAV provided information on vegetation changes throughout the reservoir that would have been missed by conventional vegetation plots due to their limited spatial coverage. Lastly, the COVID-19 pandemic prevented us from meeting to collect post-dam removal vegetation plot data. UAV enabled data collection that we would have foregone if we relied solely on conventional methods, demonstrating the importance of flexible and adaptive methods for successful restoration monitoring such as those enabled via UAV.

Accurate quantification of ecosystem services (ES) at regional scales is increasingly important for making informed decisions in the face of environmental change. We linked terrestrial and aquatic ecosystem process models to simulate the spatial and temporal distribution of hydrological and water quality characteristics related to ecosystem services. The linked model integrates two existing models (a forest ecosystem model and a river network model) to establish consistent responses to changing drivers across climate, terrestrial, and aquatic domains. The linked model is spatially distributed, accounts for terrestrial-aquatic and upstream-downstream linkages, and operates on a daily time-step, all characteristics needed to understand regional responses. The model was applied to the diverse landscapes of the Upper Merrimack River watershed, New Hampshire, USA. Potential changes in future environmental functions were evaluated using statistically downscaled global climate model simulations (both a high and low emission scenario) coupled with scenarios of changing land cover (centralized vs. dispersed land development) for the time period of 1980-2099. Projections of climate, land cover, and water quality were translated into a suite of environmental indicators that represent conditions relevant to important ecosystem services and were designed to be readily understood by the public. Model projections show that climate will have a greater influence on future aquatic ecosystem services (flooding, drinking water, fish habitat, and nitrogen export) than plausible changes in land cover. Minimal changes in aquatic environmental indicators are predicted through 2050, after which the high emissions scenarios show intensifying impacts. The spatially distributed modeling approach indicates that heavily populated portions of the watershed will show the strongest responses. Management of land cover could attenuate some of the changes associated with climate change and should be considered in future planning for the region.

GPCRs regulate all aspects of human physiology, and biophysical studies have deepened our understanding of GPCR conformational regulation by different ligands. Yet there is no experimental evidence for how sidechain dynamics control allosteric transitions between GPCR conformations. To address this deficit, we generated samples of a wild-type GPCR (A2AR) that are deuterated apart from 1H/13C NMR probes at isoleucine δ1 methyl groups, which facilitated 1H/13C methyl TROSY NMR measurements with opposing ligands. Our data indicate that low [Na+] is required to allow large agonist-induced structural changes in A2AR, and that patterns of sidechain dynamics substantially differ between agonist (NECA) and inverse agonist (ZM241385) bound receptors, with the inverse agonist suppressing fast ps-ns timescale motions at the G protein binding site. Our approach to GPCR NMR creates a framework for exploring how different regions of a receptor respond to different ligands or signaling proteins through modulation of fast ps-ns sidechain dynamics.