Statistical uncertainty of eddy flux–based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest-atmosphere CO2fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However, separation of tower-based net ecosystem exchange (NEE) into its components (respiration losses and photosynthetic uptake) requires at least one application of a model, which is usually a regression model fitted to nighttime data and extrapolated for all daytime intervals. In addition, the existence of a significant amount of missing data in eddy flux time series requires a model for daytime NEE as well. Statistical approaches for analytically specifying prediction intervals associated with a regression require, among other things, constant variance of the data, normally distributed residuals, and linearizable regression models. Because the NEE data do not conform to these criteria, we used a Monte Carlo approach (bootstrapping) to quantify the statistical uncertainty of GEE estimates and present this uncertainty in the form of 90% prediction limits. We explore two examples of regression models for modeling respiration and daytime NEE: (1) a simple, physiologically based model from the literature and (2) a nonlinear regression model based on an artificial neural network. We find that uncertainty at the half-hourly timescale is generally on the order of the observations themselves (i.e., ∼100%) but is much less at annual timescales (∼10%). On the other hand, this small absolute uncertainty is commensurate with the interannual variability in estimated GEE. The largest uncertainty is associated with choice of model type, which raises basic questions about the relative roles of models and data

Near-surface remote sensing of spatial and temporal variation in canopy phenology

There is a need to document how plant phenology is responding to global change factors, particularly warming trends. “Near-surface” remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras (“webcams”) can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for “regions of interest” within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface–atmosphere CO2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux

Nitrogen cycling, forest canopy reflectance, and emergent properties of ecosystems

In Ollinger et al. (1), we reported that mass-based concentrations of nitrogen in forest canopies (%N) are positively associated with whole-canopy photosynthetic capacity and canopy shortwave albedo in temperate and boreal forests, the latter result stemming from a positive correlation between %N and canopy near infrared (NIR) reflectance. This finding is intriguing because a functional link between %N and NIR reflectance could indicate an influence of nitrogen cycling on surface energy exchange, and could provide a means for estimating %N using broad-band satellite sensors

Evaluating the climate effects of mid-1800s deforestation in New England, USA, using a Weather, Research, and Forecasting (WRF) Model Multi-Physics Ensemble

The New England region of the northeastern United States has a land use history characterized by forest clearing for agriculture and other uses during European colonization and subsequent reforestation following widespread farm abandonment. Despite these broad changes, the potential influence on local and regional climate has received relatively little attention. This study investigated wintertime (December through March) climate impacts of reforestation in New England using a high-resolution (4 km) multiphysics ensemble of the Weather Research and Forecasting Model. In general, the conversion from mid-1800s cropland/grassland to forest led to warming, but results were sensitive to physics parameterizations. The 2-m maximum temperature (T2max) was most sensitive to choice of land surface model, 2-m minimum temperature (T2min) was sensitive to radiation scheme, and all ensemble members simulated precipitation poorly. Reforestation experiments suggest that conversion of mid-1800s cropland/grassland to present-day forest warmed T2max +0.5 to +3 K, with weaker warming during a warm, dry winter compared to a cold, snowy winter. Warmer T2max over forests was primarily the result of increased absorbed shortwave radiation and increased sensible heat flux compared to cropland/grassland. At night, T2min warmed +0.2 to +1.5 K where deciduous broadleaf forest replaced cropland/grassland, a result of decreased ground heat flux. By contrast, T2min of evergreen needleleaf forest cooled –0.5 to –2.1 K, primarily owing to increased ground heat flux and decreased sensible heat flux

Combining tower mixing ratio and community model data to estimate regional-scale net ecosystem carbon exchange by boundary layer inversion over 4 flux towers in the U.S.A.

We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling approach builds on a mixed-layer model to infer monthly average net CO2 fluxes using high-precision mixing ratio measurements taken on flux towers. We compared BL model net ecosystem exchange (NEE) with estimates from two independent approaches. First, we compared modeled NEE with tower eddy covariance measurements. The second approach (EC-MOD) was a data-driven method that upscaled EC fluxes from towers to regions using MODIS data streams. Comparisons between modeled CO2 and tower NEE fluxes showed that modeled regional CO2 fluxes displayed interannual and intra-annual variations similar to the tower NEE fluxes at the Rannells Prairie and Wind River Forest sites, but model predictions were frequently different from NEE observations at the Harvard Forest and Howland Forest sites. At the Howland Forest site, modeled CO2 fluxes showed a lag in the onset of growing season uptake by 2 months behind that of tower measurements. At the Harvard Forest site, modeled CO2 fluxes agreed with the timing of growing season uptake but underestimated the magnitude of observed NEE seasonal fluctuation. This modeling inconsistency among sites can be partially attributed to the likely misrepresentation of atmospheric transport and/or CO2gradients between ABL and the free troposphere in the idealized BL model. EC-MOD fluxes showed that spatial heterogeneity in land use and cover very likely explained the majority of the data-model inconsistency. We show a site-dependent atmospheric rectifier effect that appears to have had the largest impact on ABL CO2 inversion in the North American Great Plains. We conclude that a systematic BL modeling approach provided new insights when employed in multiyear, cross-site synthesis studies. These results can be used to develop diagnostic upscaling tools, improving our understanding of the seasonal and interannual variability of surface CO2 fluxes

Forest ecosystem changes from annual methane source to sink depending on late summer water balance

Forests dominate the global carbon cycle, but their role in methane (CH4) biogeochemistry remains uncertain. We analyzed whole-ecosystem CH4 fluxes from 2 years, obtained over a lowland evergreen forest in Maine, USA. Gross primary productivity provided the strongest correlation with the CH4 flux in both years, with an additional significant effect of soil moisture in the second, drier year. This forest was a neutral to net source of CH4 in 2011 and a small net sink in 2012. Interannual variability in the summer hydrologic cycle apparently shifts the ecosystem from being a net source to a sink for CH4. The small magnitude of the CH4 fluxes and observed control or CH4 fluxes by forest productivity and summer precipitation provide novel insight into the CH4 cycle in this globally important forest ecosystem.Organismic and Evolutionary Biolog

What do Professors do all Summer?

It’s a time to take a breath, re-energize, and re-center while also reconnecting with friends and family. Posting about the summer rhythm of life for five professors from In All Things - an online journal for critical reflection on faith, culture, art, and every ordinary-yet-graced square inch of God’s creation. https://inallthings.org/what-do-educators-do-all-summer

Lorrie Moore collection, 'A Little Ethnic Kink Is Always Good to See”: Jewish performance anxiety and anti-passing in the fiction of Lorrie Moore

This essay explores the ways in which the performance of Jewish identity (in the sense both of representing Jewish characters and of writing about those characters’ conscious and unconscious renditions of their Jewishness) is a particular concern (in both senses of the word) for Lorrie Moore. Tracing Moore's representations of Jewishness over the course of her career, from the early story “The Jewish Hunter” through to her most recent novel, A Gate at the Stairs, I argue that it is characterized by (borrowing a phrase from Moore herself) “performance anxiety,” an anxiety that manifests itself in awkward comedy and that can be read both in biographical terms and as an oblique commentary on, or reworking of, the passing narrative, which I call “anti-passing.” Just as passing narratives complicate conventional ethno-racial definitions so Moore's anti-passing narratives, by representing Jews who represent themselves as other to themselves, as well as to WASP America, destabilize the category of Jewishness and, by implication, deconstruct the very notion of ethnic categorization