National Ecological Observatory Network (NEON) is a large facility program operated by Battelle Memorial Institute and funded by the National Science Foundation. In full operation since 2019, NEON gathers and provides long-term, standardized data on ecological responses of the biosphere to changes in land use and climate, and on feedback with the geosphere, hydrosphere, and atmosphere. NEON is a continental-scale research platform for understanding how and why our ecosystems are changing.
Nitrogen is rapidly taken up by plants and microbes, but questions remain as to which forms are preferred. Using in situ stable isotope labelling (13C and 15N), we show that co-existing plant species of alpine heath mainly take up ammonium and nitrate, passing 15N from root to shoot over time, leading to accumulated nitrogen in the shoots (over 10-fold increase compared with roots), with more complex organic nitrogen forms such as amino acids taken up to a lesser extent. Conversely, soil microbes preferred amino acids, potentially as a side-effect of satisfying their carbon requirements to build cellular structures. We show that competition for nitrogen can be alleviated by differing growth rates in plants and varying microbial preference of nitrogen forms.
Methane fluxes in brackish tidal wetlands are challenging to predict because common controls interact with temporally varying salinity. We measured ecosystem-scale methane fluxes in a brackish marsh in Massachusetts during two hydrologically distinct years during which methane fluxes collapsed and then recovered. The wetland experienced exceptionally high salinity levels during a drought in 2022 and consistently moderate levels in the subsequent year. Soil salinity did not return to the initiicensal low values which was likely due to limited infiltration of fresh surface water in 2023. Methane fluxes averaged 0.120 $\mu$ mol $\mathrm{m}^{-2}$ $\mathrm{s}^{-1}$ before they were reduced to effectively zero when salinity increased rapidly. Fluxes recovered to 67% of original levels in August 2023. To understand the timescale and drivers of this ecosystem response as well as their interactions, we developed neural network models to predict methane fluxes for each year. We derived functional relationships by systematically varying each driver with the remaining drivers set constant. We found porewater specific conductivity, air temperature and to lesser degree gross primary production to be the dominant drivers of methane fluxes. Our modeling determined strong interactions between specific conductivity and temperature controlling methane fluxes. We identified a threshold of about 15 mS $\textrm{cm}^{-1}$ (8.7 psu) above which modeled methane fluxes decreased substantially, especially at higher temperatures. In 2023, the variation in measured specific conductivity was low and the neural network less predictive. At that time, our porewater measurements indicated variability of sulfate concentrations not captured by specific conductivity observations. Porewater methane concentrations were consistently detectable even during periods of flux suppression, indicating a role of methane oxidation in the prolonged flux suppression. Our findings demonstrate the value of applying machine learning approaches to flux analysis in dynamic wetland systems and suggest that drought-induced salinization can alter methane cycling in brackish tidal wetlands for prolonged periods of time.
Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. We focused our analysis on standard meteorological variables; fluxes of CO2, sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO2 and latent heat fluxes occurred at the annual scale, with implications especially for the forest carbon balance. The AmeriFlux tower measurements indicate a site that is close to carbon-neutral (-8 +/- 65 g C m-2 y-1, mean +/- 1 SD), whereas the NEON tower measurements indicate a forest that is a carbon sink (-137 +/- 10 g C m-2 y-1). Causes of this disagreement may include measurement height (26 m vs. 35 m), which resulted in different flux footprints being measured by the two towers, and differences in the flux measurement systems. Our results suggest the need for caution when attempting to merge long-term flux data from two different measurement platforms, and when using measurements from any one measurement platform to inform decision-making on issues related to carbon accounting or natural climate solutions.
Soil microbial communities regulate critical ecosystem functions including carbon cycling, nutrient transformation, and plant productivity. Despite their importance, comprehensive, standardized microbial datasets spanning continental scales remain rare. Here we present a synthesis of phospholipid fatty acid (PLFA) data from the National Ecological Observatory Network (NEON), encompassing 11,399 samples collected from 47 terrestrial sites across North America between 2017 and 2024. We developed neonPLFA , an open-source R workflow and Shiny application that harmonizes NEON's PLFA measurements, applies quality control procedures, accounts for known contaminant lipids, and calculates standardized microbial community metrics including total biomass, fungal:bacterial ratios, Gram-positive:Gram-negative ratios, and a cyclopropyl:precursor physiological stress index. The resulting dataset reveals strong latitudinal gradients in microbial community composition and provides unprecedented spatial and temporal resolution for investigating continental-scale patterns in soil microbial ecology. All data, code, and interactive visualization tools are publicly available, enabling reproducible research on soil microbial biogeography.
The 2024 ENSO event advanced the timing of spring phenological phases of native shrubs significantly more than non-native shrubs and native trees in a temperate deciduous woodland fragment in Wisconsin, USA. This suggests that, as spring temperatures warm, shrubs will likely play a pivotal role in forest dynamics including contributing to an earlier onset to the growing period and an early start to CO2 assimilation. The 2023/2024 El Niño Southern Oscillation (ENSO) event brought warmer than average temperatures to the Midwest USA. This presented a unique opportunity to examine how short-term warming might impact the phenology of temperate deciduous forest vegetation. To quantify the impact of an ENSO-driven warm spring on the phenology of temperate deciduous forest vegetation in order to assess how trees and shrubs respond to short-term temperature anomalies. Spring phenology was recorded twice weekly (2018–2024) on 5 dominant tree species and 5 native and 4 non-native shrub species, in a woodland fragment on the University of Wisconsin Milwaukee campus. In addition, phenological transition dates were extracted from daily Green Chromatic Coordinate (GCC) data from a PhenoCam installed at the site. In 2024, the average spring (March–May) temperature (8.7 ± 0.57 °C) was significantly warmer than the 2018–2023 average (6.7 ± 0.28 °C). Compared to the average of the previous 6 years, the timing of budburst in 2024 occurred significantly (p < 0.001) earlier on DOY 76, 82, and 98 for native shrubs, non-native shrubs, and trees, representing advances of 20, 17, and 18 days, respectively. The advance was greater in shrubs than trees suggesting that any future advance to the start of the growing-season in temperate deciduous forests resulting from warmer spring temperatures will likely be driven by early leafing species like shrubs. Notably, the rise in GCC in 2024 (DOY 116) occurred following budburst, indicating that PhenoCam imagery may not fully capture early vegetation phenology. Early leafing shrubs, and in particular native species, were more sensitive to warmer temperatures early in the season than non-native shrubs and native trees. Therefore, as temperatures warm in the future, the onset of growth in temperate deciduous forests is likely to be driven by the early spring phenophases of early leafing species.
