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It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100...
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The combination of continuing anthropogenic impact on ecosystems across the globe and the observation of catastrophic shifts in some systems has generated substantial interest in understanding and predicting ecological tipping points. The recent establishment and full operation of NEON has created an opportunity for researchers to access extensive datasets monitoring the composition and functioning of a wide range of ecosystems. These data may be uniquely effective for studying regime shifts and tipping points in ecological systems because of their long time horizon, spatial extent, and most importantly the coordinated monitoring of many biotic and abiotic components of focal ecosystems. The variety of these data...
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Post-fire shifts in vegetation composition will have broad ecological impacts. However, information characterizing post-fire recovery patterns and their drivers are lacking over large spatial extents. In this analysis we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of post-fire, dual season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally-specific drivers of post-fire rates of NDVI recovery. Rates of post-fire...
Tags: Arizona,
California,
Climatology,
Colorado,
Douglas fir, All tags...
Ecology,
Engelmann spruce,
Forestry,
Idaho,
Landsat,
Lodgepole pine,
Montana,
NDVI,
Nevada,
Oregon,
Pinyon pine,
Remote Sensing,
Rocky Mountains,
Sierra Nevada Mountains,
USGS Science Data Catalog (SDC),
Utah,
Washington,
Wyoming,
forest fire,
recovery,
resiliency,
succession,
wildfire, Fewer tags
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Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual‐season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field‐measured patterns of re‐vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI...
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Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further...
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