Word cloud created from article titles from 180 NEON-related publications from 2017 to 2020.

Word cloud created from article titles from 180 NEON-related publications from 2017 to 2020.

Source publication
Article
Full-text available
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 operatio...

Contexts in source publication

Context 1
... of existing NEON data products and NEON Biorepository samples and specimens. As of October 2020, 267 publications have described, referenced, and used NEON data and network resources. While the range of topics varies greatly, drawing on the 181 open-access data products and 63 collections of physical samples, certain key themes have emerged (Fig. 1). The large emphasis on data suggests how valuable these products have been for the ecological community. Prominent topics include tracking phenology changes, forest structural dynamics and tree classification, soil organic matter (or carbon) dynamics, ecological forecasting, and small mammal biodiversity patterns. For example, early ...
Context 2
... for instructors include teaching and learning modules, and full courses available on the NEON Learning Hub (NEON 2021g), the Earth Data Science learning portal (earthdatascience.org; Earth Lab 2021), the QUBES portal (QUBES 2021b), and the Environmental DataDriven Inquiry and Exploration (EDDIE) website (EDDIE 2021). ...

Citations

... The use of real-world examples and real ecological data allows students to relate to a sense of place, making the module content much more relevant to students [45]. Our teaching module adds to the growing number of teaching resources which are using NEON data [46], though it is the first, to the best of our knowledge, to use NEON data for teaching forecasting to undergraduates. Moreover, our module can be taught using different modalities (hybrid, virtual, in-person), which provides a flexible approach for integrating NEON data into ecology curricula [47]. ...
Article
Full-text available
Ecological forecasting is an emerging approach to estimate the future state of an ecological system with uncertainty, allowing society to better manage ecosystem services. Ecological forecasting is a core mission of the U.S. National Ecological Observatory Network (NEON) and several federal agencies, yet, to date, forecasting training has focused on graduate students, representing a gap in undergraduate ecology curricula. In response, we developed a teaching module for the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration; MacrosystemsEDDIE.org) educational program to introduce ecological forecasting to undergraduate students through an interactive online tool built with R Shiny. To date, we have assessed this module, “Introduction to Ecological Forecasting,” at ten universities and two conference workshops with both undergraduate and graduate students (N = 136 total) and found that the module significantly increased undergraduate students’ ability to correctly define ecological forecasting terms and identify steps in the ecological forecasting cycle. Undergraduate and graduate students who completed the module showed increased familiarity with ecological forecasts and forecast uncertainty. These results suggest that integrating ecological forecasting into undergraduate ecology curricula will enhance students’ abilities to engage and understand complex ecological concepts.
... Methodological and epistemological challenges involved in using these data led the authors of this paper to recognize the necessity of having a team of collaborators to validate methods and test results before formally embedding them into a standard algorithmic process. While there is some research on the social and technical factors that allow for effective team science (Rhoten 2003, Oliver et al. 2018, there is room to consider how to best foster collaborations that can synthesize the wide variety of NEON data products to address interdisciplinary problems (e.g., Nagy et al. 2021). Interdisciplinary collaborations have been identified as avenues for fruitful and novel research in ecology and the environment as discussed above, but especially for understanding complex socioenvironmental issues (Palmer et al. 2016). ...
Article
Full-text available
Soil microbial communities play critical roles in various ecosystem processes, but studies at a large spatial and temporal scale have been challenging due to the difficulty in finding the relevant samples in available data sets as well as the lack of standardization in sample collection and processing. The National Ecological Observatory Network (NEON) has been collecting soil microbial community data multiple times per year for 47 terrestrial sites in 20 eco‐climatic domains, producing one of the most extensive standardized sampling efforts for soil microbial biodiversity to date. Here, we introduce the neonMicrobe R package—a suite of downloading, preprocessing, data set assembly, and sensitivity analysis tools for NEON’s newly published 16S and ITS amplicon sequencing data products which characterize soil bacterial and fungal communities, respectively. neonMicrobe is designed to make these data more accessible to ecologists without assuming prior experience with bioinformatic pipelines. We describe quality control steps used to remove quality‐flagged samples, report on sensitivity analyses used to determine appropriate quality filtering parameters for the DADA2 workflow, and demonstrate the immediate usability of the output data by conducting standard analyses of soil microbial diversity. The sequence abundance tables produced by neonMicrobe can be linked to NEON’s other data products (e.g., soil physical and chemical properties, plant community composition) and soil subsamples archived in the NEON Biorepository. We provide recommendations for incorporating neonMicrobe into reproducible scientific workflows, discuss technical considerations for large‐scale amplicon sequence analysis, and outline future directions for NEON‐enabled microbial ecology. In particular, we believe that NEON marker gene sequence data will allow researchers to answer outstanding questions about the spatial and temporal dynamics of soil microbial communities while explicitly accounting for scale dependence. We expect that the data produced by NEON and the neonMicrobe R package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.
Article
Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties. Continuous and discoverable observations of water potential could vastly improve understanding of biophysical processes throughout the soil–plant–atmosphere continuum and are achievable thanks to recent technological advances.