Using large, open datasets to understand spatial and temporal patterns in lotic ecosystems: NEON case studies DOI
Jennifer W. Edmonds, Katelyn King, Merrie Beth Neely

et al.

Ecosphere, Journal Year: 2022, Volume and Issue: 13(5)

Published: May 1, 2022

Abstract Leveraging big, open data is the next frontier in ecology. The National Ecological Observatory Network (NEON) a network of monitoring sites collecting ecological from across United States. Using case study approach, we provide examples how NEON can be applied to address few big questions aquatic First, examined spatial patterns stream water chemistry, determine whether tend cluster into regions based on geographic proximity. We found that this was not case, likely because hydrologic, geologic, and anthropogenic factors drive heterogeneity chemistry vary smaller scales. Second, temporal variability chemistry. determined majority catchments are relatively chemostatic (i.e., discharge varies by orders magnitude more than concentrations) differences between shift decades due changes conductivity. Third, tested predictions River Continuum Concept (RCC) along gradient second‐order seventh‐order river. longitudinal metabolism, carbon macroinvertebrate community composition generally follow predicted RCC. only its third year full operations, with planned 30‐year life. studies presented here show utility data, while using subset many products produces. massive amounts types generates, conjunction other national‐scale datasets, will allow research better understand ecosystems function respond drivers long‐term change.

Language: Английский

Recommendations for developing, documenting, and distributing data products derived from NEON data DOI Creative Commons
Jeff W. Atkins, Kelly S. Aho,

Xuan Chen

et al.

Ecosphere, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 1, 2025

Abstract The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States Puerto Rico. These include both field remote sensing collected using standardized protocols sampling schema, with centralized quality assurance control (QA/QC) provided by NEON staff. Such breadth of creates opportunities for research community to extend basic applied while also extending impact reach through creation derived products—higher level user data. Derived are curated, documented, reproducibly‐generated datasets created applying various processing steps one or more lower products—including interpolation, extrapolation, integration, statistical analysis, modeling, transformations. directly benefit increase broadening size diversity base, decreasing time effort needed working data, providing primary foci development via derivation process, helping users address multidisciplinary questions. Creating promotes personal career advancement those involved publications, citations, future grant proposals. However, is a nontrivial task. Here we provide an overview process creating outlining advantages, challenges, major considerations.

Language: Английский

Citations

0
Reservoir ecological health assessment Methods: A systematic review DOI Creative Commons

Esi Esuon Biney,

Charles Gyamfi, Anthony Yaw Karikari

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113130 - 113130

Published: Jan. 23, 2025

Language: Английский

Citations

0
Spanning scales: The airborne spatial and temporal sampling design of the National Ecological Observatory Network DOI Creative Commons
John Musinsky, Tristan Goulden, Gregory D. Wirth

et al.

Methods in Ecology and Evolution, Journal Year: 2022, Volume and Issue: 13(9), P. 1866 - 1884

Published: July 28, 2022

Abstract 1. Each year, the National Ecological Observatory Network's (NEON) Airborne Observation Platform (AOP) collects high‐resolution hyperspectral imagery, discrete and waveform lidar, digital photography at a subset of 81 terrestrial aquatic research sites throughout United States. These open remote sensing data, together with NEON in situ sensor measurements field observations, enable researchers to characterize ecological processes multiple spatial temporal scales. 2. Here we describe sampling design for AOP that aims meet diverse needs science community within operational constraints affecting airborne data collection. Our protocol captures instrumented systems, plots environmental gradients around each site while considering context airspace restrictions instrument capabilities. We use time series moderate resolution imaging spectroradiometer (MODIS) satellite PhenoCam near‐surface observations define windows based on vegetation peak foliar greenness. developed probabilistic model MODIS reflectance imagery Monte Carlo simulation estimate durations cloud‐free collection site. 3. Agreement estimated phenophase transition dates between Enhanced Vegetation Index Green Chromatic Coordinate varied by class. Results from both sensors show some classes have relatively consistent interannual greenness start‐ end‐dates, others experience high year‐to‐year variability green‐up senescence. In addition phenological among sites, certain forms demonstrate distinct, asynchronous responses climate, resulting non‐overlapping periods single flight campaigns showed cloud‐likelihood underestimated actual cloud conditions 13%–26%, depending probability used. 4. Where or intra‐site phenology is highly variable clouds are persistent problem, it becomes challenging schedule domain deployments so all flown their communities Despite limitations, application models results significant improvements quality. Although most applicable lidar instruments piloted aircraft, these methods may be valuable resource deployment Unmanned Aerial Vehicles research.

Language: Английский

Citations

14
A process approach to quality management doublesNEONsensor data quality DOI Creative Commons
Cove Sturtevant, Elizabeth DeRego, Stefan Metzger

et al.

Methods in Ecology and Evolution, Journal Year: 2022, Volume and Issue: 13(9), P. 1849 - 1865

Published: July 31, 2022

Abstract A quality management system is critical for ensuring that the data and services provided by an organization meet needs of its mission. With a mission to collect long‐term open‐access ecological better understand how US ecosystems are changing, National Ecological Observatory Network (NEON) highly standardized measurement network distributed across United States Puerto Rico collecting on biosphere interfaces with pedosphere, hydrosphere atmosphere. In order achieve high‐quality, comparable network, was developed applying seven ISO 9001:2015 principles management: customer focus , leadership, engagement people, process approach, improvement, evidence‐based decision making relationship . The resultant integrated throughout NEON's organizational structure approach connects people operational processes life cycle ( ). We describe respect sensor (automated measurements), demonstrating effectiveness through examples, lessons learned continuous history improvement towards goals, including doubling in meteorological soil datasets since 2015 substantial gains other datasets. Owing particularly interconnectedness human information systems, can serve as model networks variety structures sizes.

Language: Английский

Citations

11
The US National Ecological Observatory Network and the Global Biodiversity Framework: national research infrastructure with a global reach DOI Open Access
Katherine M. Thibault, Christine Laney, Kelsey M. Yule

et al.

Journal of Ecology and Environment, Journal Year: 2023, Volume and Issue: 47

Published: Dec. 14, 2023

Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure understand changing ecosystems for period of 30 years.NEON collects co-located measurements drivers environmental change biological responses, using standardized methods at 81 field sites systematically sample variability trends enable inferences regional continental scales.Alongside key atmospheric variables, NEON measures the biodiversity many taxa, including microbes, plants, animals, samples from these organisms long-term archiving research use.Here we review composition use resources date as whole specific an exemplar potential national contribute globally relevant outcomes.Since initiated full operations in 2019, has produced, on average, 1.4 M records over 32 TB data per year across more than 180 products, with 85 products that include taxonomic or other organismal information science.NEON also collected curated 503,000 specimens spanning all domains life, up 100,000 be added annually.Various metrics use, web portal visitation, download requests, scientific publications, reveal substantial interest global community NEON.More 47,000 unique IP addresses around world visit NEON's portals each month, requesting average 1.8 200 researchers have engaged requests Biorepository.Through its partnerships, particularly Global Biodiversity Information Facility, been used 900 publications date, samples.These outcomes demonstrate provided by NEON, situated broader network infrastructures, are critical scientists, conservation practitioners, policy makers.They effective approaches meeting targets, such those captured Kunming-Montreal Framework.

Language: Английский

Citations

6
Spatial Patterns in Fish Assemblages across the National Ecological Observation Network (NEON): The First Six Years DOI Creative Commons

Dylan Monahan,

Jeff S. Wesner, Stephanie M. Parker

et al.

Fishes, Journal Year: 2023, Volume and Issue: 8(11), P. 552 - 552

Published: Nov. 16, 2023

The National Ecological Observation Network (NEON) is a thirty-year, open-source, continental-scale ecological observation platform. objective of the NEON project to provide data facilitate understanding and forecasting impacts anthropogenic change at continental scale. Fish are sentinel taxa in freshwater systems, has been sampling collecting fish assemblage wadable stream sites for six years. One two located sixteen domains from Alaska Puerto Rico. goal site selection was that represent local conditions but with intention be analyzed observatory level. Site did not include criteria. Without using criteria, anomalies assemblages level may skew expected spatial patterns North American assemblages, thereby hindering detection subsequent However, if representative current distributions we could expect find most diverse Atlantic drainages depauperate Pacific drainages. Therefore, calculated alpha regional (beta) diversities highlight patterns. As expected, followed predictable diversity patterns, which future attribution changes environmental drivers, any.

Language: Английский

Citations

3
Using large, open datasets to understand spatial and temporal patterns in lotic ecosystems: NEON case studies DOI
Jennifer W. Edmonds, Katelyn King, Merrie Beth Neely

et al.

Ecosphere, Journal Year: 2022, Volume and Issue: 13(5)

Published: May 1, 2022

Abstract Leveraging big, open data is the next frontier in ecology. The National Ecological Observatory Network (NEON) a network of monitoring sites collecting ecological from across United States. Using case study approach, we provide examples how NEON can be applied to address few big questions aquatic First, examined spatial patterns stream water chemistry, determine whether tend cluster into regions based on geographic proximity. We found that this was not case, likely because hydrologic, geologic, and anthropogenic factors drive heterogeneity chemistry vary smaller scales. Second, temporal variability chemistry. determined majority catchments are relatively chemostatic (i.e., discharge varies by orders magnitude more than concentrations) differences between shift decades due changes conductivity. Third, tested predictions River Continuum Concept (RCC) along gradient second‐order seventh‐order river. longitudinal metabolism, carbon macroinvertebrate community composition generally follow predicted RCC. only its third year full operations, with planned 30‐year life. studies presented here show utility data, while using subset many products produces. massive amounts types generates, conjunction other national‐scale datasets, will allow research better understand ecosystems function respond drivers long‐term change.

Language: Английский

Citations

2