Search for: All records

Abstract AimPollen assemblages are commonly used to reconstruct past climates yet have not yet been used to reconstruct past human activities, including deforestation. We aim to assess (i) how pollen assemblages vary across biogeographic and environmental gradients, (ii) the source area of pollen assemblages from lake sediment samples and (iii) which pollen taxa can best be used to quantify deforested landscapes. LocationAmazonia. TaxonPlantae. MethodsPollen assemblages (N = 65) from mud‐water interface samples (representing modern conditions) of lake sediment cores were compared with modern gradients of temperature, precipitation and elevation. Pollen assemblages were also compared with local‐scale estimates of forest cover at 1, 2, 5, 10, 20 and 40 km buffers around each lake. ResultsOver 250 pollen types were identified in the samples, and pollen assemblages were able to accurately differentiate biogeographic regions across the basin, corresponding with gradients in temperature and precipitation. Poaceae percentages were the best predictor of deforestation, and had a significant negative relationship with forest cover estimates. These relationships were strongest for the 1 km buffer area, weakening as buffer sizes increased. Main conclusionsThe diverse Amazonian pollen assemblages strongly reflect environmental gradients, and percentages of Poaceae best reflect local‐scale variability in forest cover. Our results of modern pollen‐landscape relationships can be used to provide a foundation for quantitative reconstructions of climate and deforestation in Amazonia. 

The Atlantic Deepwater Ecosystem Observatory Network (ADEON) along the US Mid- and South Atlantic Outer Continental Shelf (OCS) collected multiple years of measurements that describe the ecology and soundscape of the OCS. Ocean processes, marine life dynamics, and human use of the ocean are each three dimensional and time dependent, and occur at many spatial and temporal scales. Because no single measurement system (in situ or remote) is sufficient for describing dynamic ocean variables, the approach taken by ADEON was to integrate ocean measurements and models. Acoustic information was combined with contextual data from space-based remote sensing, hydrographic sensors, and mobile platforms in order to fully comprehend how human, biologic, and natural abiotic components create the OCS soundscape and influence its ecosystem dynamics. Standardized methodologies were developed for comparing soundscapes across regions and for generating predictive models of the soundscape and overall ecology of the OCS at 200–900 m water depths. These data provide a baseline for pattern and trend analyses of ambient sound and the ecosystem components of the OCS soundscapes. They contribute to understanding of regional processes over multi-year time­scales and support ecosystem-based management of marine resources in an acoustically under-sampled ocean region. 

Abstract. Atmospheric rivers (ARs) are synoptic-scale features that transport moisture poleward and may cause short-duration, high-volume melt events on the Greenland ice sheet (GrIS). In contrast with traditional climate modeling studies that rely on coarse (1 to 2°) grids, this project investigates the effectiveness of variable-resolution (VR) grids in modeling ARs and their subsequent precipitation using refined grid spacing (0.25 and 0.125°) around the GrIS and 1° grid spacing for the rest of the globe in a coupled land–atmosphere model simulation. VR simulations from the Community Earth System Model version 2.2 (CESM2.2) bridge the gap between the limitations of global and regional climate models while maximizing computational efficiency. ARs from CESM2.2 simulations using three grid types (VR, latitude–longitude, and quasi-uniform) with varying resolutions are compared to outputs from two observation-based reanalysis products, ERA5 and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), using a study period of 1 January 1979 to 31 December 1998. The VR grids produce ARs with smaller areal extents and lower area-integrated precipitation over the GrIS compared to latitude–longitude and quasi-uniform grids. We hypothesize that the smaller areal AR extents in VR grids are due to the refined topography resolved in these grids. In contrast, topographic smoothing in coarser-resolution latitude–longitude and quasi-uniform grids allows ARs to penetrate further inland on the GrIS. Precipitation rates are similar for the VR, latitude–longitude, and quasi-uniform grids; thus the reduced areal extent in VR grids produces lower area-integrated precipitation. The VR grids most closely match the AR overlap extent and precipitation in ERA5 and MERRA-2, suggesting the most realistic behavior among the three configurations. 

Recently, sensors deployed on unpiloted aerial systems (UAS) have provided snow depth estimates with high spatial resolution over watershed scales. While light detection and ranging (LiDAR) produces precise snow depth estimates for areas without vegetation cover, there has generally been poorer precision in forested areas. At a constant flight speed, the poorest precision within forests is observed beneath tree canopies that retain foliage into or through winter. The precision of lidar-derived elevation products is improved by increasing the sample size of ground returns but doing so reduces the spatial coverage of a mission due to limitations of battery power. We address the influence of flight speed on ground return density for baseline and snow-covered conditions and the subsequent effect on precision of snow depth estimates across a mixed landscape, while evaluating trade-offs between precision and bias. Prior to and following a snow event in December 2020, UAS flights were conducted at four different flight speeds over a region consisting of three contrasting land types: (1) open field, (2) deciduous forest, (3) conifer forest. For all cover types, we observed significant improvements in precision as flight speeds were reduced to 2 m s−1, as well as increases in the area over which a 2 cm snow depth precision was achieved. On the other hand, snow depth estimate differences were minimized at baseline flight speeds of 2 m s−1 and 4 m s−1 and snow-on flight speeds of 6 m s−1 over open fields and between 2 and 4 m s−1 over forest areas. Here, with consideration to precision and estimate bias within each cover type, we make recommendations for ideal flight speeds based on survey ground conditions and vegetation cover. 

Unoccupied aerial systems (UAS) are an established technique for collecting data on cold region phenomenon at high spatial and temporal resolutions. While many studies have focused on remote sensing applications for monitoring long term changes in cold regions, the role of UAS for detection, monitoring, and response to rapid changes and direct exposures resulting from abrupt hazards in cold regions is in its early days. This review discusses recent applications of UAS remote sensing platforms and sensors, with a focus on observation techniques rather than post-processing approaches, for abrupt, cold region hazards including permafrost collapse and event-based thaw, flooding, snow avalanches, winter storms, erosion, and ice jams. The pilot efforts highlighted in this review demonstrate the potential capacity for UAS remote sensing to complement existing data acquisition techniques for cold region hazards. In many cases, UASs were used alongside other remote sensing techniques (e.g., satellite, airborne, terrestrial) andin situsampling to supplement existing data or to collect additional types of data not included in existing datasets (e.g., thermal, meteorological). While the majority of UAS applications involved creation of digital elevation models or digital surface models using Structure-from-Motion (SfM) photogrammetry, this review describes other applications of UAS observations that help to assess risks, identify impacts, and enhance decision making. As the frequency and intensity of abrupt cold region hazards changes, it will become increasingly important to document and understand these changes to support scientific advances and hazard management. The decreasing cost and increasing accessibility of UAS technologies will create more opportunities to leverage these techniques to address current research gaps. Overcoming challenges related to implementation of new technologies, modifying operational restrictions, bridging gaps between data types and resolutions, and creating data tailored to risk communication and damage assessments will increase the potential for UAS applications to improve the understanding of risks and to reduce those risks associated with abrupt cold region hazards. In the future, cold region applications can benefit from the advances made by these early adopters who have identified exciting new avenues for advancing hazard research via innovative use of both emerging and existing sensors. 

Science is increasingly a collaborative pursuit. Although the modern scientific enterprise owes much to individuals working at the core of their field, humanity is increasingly confronted by highly complex problems that require the integration of a variety of disciplinary and methodological expertise. In 2016, the U.S. National Science Foundation launched an initiative prioritizing support for convergence research as a means of “solving vexing research problems, in particular, complex problems focusing on societal needs.” We discuss our understanding of the objectives of convergence research and describe in detail the conditions and processes likely to generate successful convergence research. We use our recent experience as participants in a convergence workshop series focused on resilience in the Arctic to highlight key points. The emergence of resilience science over the past 50 years is presented as a successful contemporary example of the emergence of convergence. We close by describing some of the challenges to the development of convergence research, such as timescales and discounting the future, appropriate metrics of success, allocation issues, and funding agency requirements.