Testing Above- and Below-Canopy Representations of Turbulent Fluxes in an Energy Balance Snowmelt Model

Turbulent fluxes of sensible and latent heat are important processes in the surface energy balance that drives snowmelt. Modeling these fluxes in a forested environment is complicated because of the canopy effects on the wind field. This paper presents and tests a turbulent flux model developed to represent these processes in an energy balance snowmelt model. The goal is to model these processes using the readily available inputs of canopy height and leaf area index in a way that minimizes the number of parameters, state variables, and assumptions about hard to quantify processes. Selected periods from 9 years of eddy-covariance (EC) measurements at Niwot Ridge, Colorado, were used to evaluate the effectiveness of this modeling approach. The model was able to reproduce the above-canopy sensible and latent heat fluxes reasonably with the correlation higher for sensible heat than latent heat. The modeled values of the below-canopy latent heat fluxes also matched the EC-measured values. The model captured the nighttime below-canopy sensible heat flux quite well, but there were discrepancies in daytime sensible heat flux possibly due to mountain slope circulation not quantifiable in this kind of model. Despite the uncertainties in the below-canopy sensible heat fluxes, the results are encouraging and suggest that reasonable predictions of turbulent flux energy exchanges and subsequent vapor losses from snow in forested environments can be obtained with a parsimonious single-layer representation of the canopy. The model contributes an improved physically based capability for predicting the snow accumulation and melt in a forested environment

Aircraft Regional-Scale Flux Measurements over Complex Landscapes of Mangroves, Desert, and Marine Ecosystems of Magdalena Bay, Mexico

Natural ecosystems are rarely structurally simple or functionally homogeneous. This is true for the complex coastal region of Magdalena Bay, Baja California Sur, Mexico, where the spatial variability in ecosystem fluxes from the Pacific coastal ocean, eutrophic lagoon, mangroves, and desert were studied. The Sky Arrow 650TCN environmental research aircraft proved to be an effective tool in characterizing land–atmosphere fluxes of energy, CO2, and water vapor across a heterogeneous landscape at the scale of 1 km. The aircraft was capable of discriminating fluxes from all ecosystem types, as well as between nearshore and coastal areas a few kilometers distant. Aircraft-derived average midday CO2 fluxes from the desert showed a slight uptake of −1.32 μmol CO2 m−2 s−1, the coastal ocean also showed an uptake of −3.48 μmol CO2 m−2 s−1, and the lagoon mangroves showed the highest uptake of −8.11 μmol CO2 m−2 s−1. Additional simultaneous measurements of the normalized difference vegetation index (NDVI) allowed simple linear modeling of CO2 flux as a function of NDVI for the mangroves of the Magdalena Bay region. Aircraft approaches can, therefore, be instrumental in determining regional CO2 fluxes and can be pivotal in calculating and verifying ecosystem carbon sequestration regionally when coupled with satellite-derived products and ecosystem models

Impact of different eddy covariance sensors, site set-up, and maintenance on the annual balance of CO2 and CH4 in the harsh Arctic environment

Improving year-round data coverage for CO2 and CH4 fluxes in the Arctic is critical for refining the global C budget but continuous measurements are very sparse due to the remote location limiting instrument maintenance, to low power availability, and to extreme weather conditions. The need for tailoring instrumentation, site set up, and maintenance at different sites can add uncertainty to estimates of annual C budgets from different ecosystems. In this study, we investigated the influence of different sensor combinations on fluxes of sensible heat, CO2, latent heat (LE), and CH4, and assessed the differences in annual CO2 and CH4 fluxes estimated with different instrumentation at the same sites. Using data from four sites across the North Slope of Alaska, we found that annual CO2 fluxes estimated with heated (7.5 ± 1.4 gC m−2 yr−1) and non-heated (7.9 ± 1.3 gC m−2 yr−1) anemometers were within uncertainty bounds. Similarly, despite elevated noise in 30-min flux data, we found that summer CO2 fluxes from open (−17.0 ± 1.1 gC m−2 yr−1) and close-path (−14.2 ± 1.7 gC m−2 yr−1) gas analyzers were not significantly different. Annual CH4 fluxes were also within uncertainty bounds when comparing both open (4.5 ± 0.31 gC m−2 yr−1) and closed-path (4.9 ± 0.27 gC m−2 yr−1) gas analyzers as well as heated (3.7 ± 0.26 gC m−2 yr−1) and non-heated (3.7 ± 0.28 gC m−2 yr−1) anemometers. A continuously heated anemometer increased data coverage (64%) relative to non-heated anemometers (47–52%). However, sensible heat fluxes were over-estimated by 12%, on average, with the heated anemometer, contributing to the overestimation of CO2, CH4, and LE fluxes (mean biases of −0.03 μmol m−2 s−1, −0.05 mgC m−2 h−1, and −3.77 W m−2, respectively). To circumvent this potential bias and reduce power consumption, we implemented an intermittent heating strategy whereby activation only occurred when ice or snow blockage of the transducers was detected. This resulted in comparable coverage (50%) during winter to the continuously heated anemometer (46%), while avoiding flux over-estimation. Closed and open-path analyzers showed good agreement, but data coverage was generally greater when using closed-path, especially during winter. Winter data coverage of 26–32% was obtained with closed-path devices, vs 10–14% for the open-path devices with unheated anemometers or up to 46% and 35% using closed and open-path analyzers, respectively with heated anemometers. Accurate estimation of LE remains difficult in the Arctic due to strong attenuation in closed-path systems, even when intake tubes are heated, and due to poor data coverage from open-path sensors in such a harsh environment

Neurocognitive Consequences of HIV Infection in Older Adults: An Evaluation of the “Cortical” Hypothesis

The incidence and prevalence of older adults living with HIV infection is increasing. Recent reports of increased neuropathologic and metabolic alterations in older HIV+ samples, including increased cortical beta-amyloid, have led some researchers to suggest that aging with HIV may produce a neuropsychological profile akin to that which is observed in “cortical” dementias (e.g., impairment in memory consolidation). To evaluate this possibility, we examined four groups classified by HIV serostatus and age (i.e., younger ≤40 years and older ≥50 years): (1) Younger HIV− (n = 24); (2) Younger HIV+ (n = 24); (3) Older HIV− (n = 20); and (4) Older HIV+ (n = 48). Main effects of aging were observed on episodic learning and memory, executive functions, and visuoconstruction, and main effects of HIV were observed on measures of verbal learning and memory. The interaction of age and HIV was observed on a measure of verbal recognition memory, which post hoc analyses showed to be exclusively attributed to the superior performance of the younger HIV seronegative group. Thus, in this sample of older HIV-infected individuals, the combined effects of HIV and aging do not appear to result in a “cortical” pattern of cognitive deficits

The USDA Barley Core Collection:Genetic Diversity, Population Structure, and Potential for Genome-Wide Association Studies

New sources of genetic diversity must be incorporated into plant breeding programs if they are to continue increasing grain yield and quality, and tolerance to abiotic and biotic stresses. Germplasm collections provide a source of genetic and phenotypic diversity, but characterization of these resources is required to increase their utility for breeding programs. We used a barley SNP iSelect platform with 7,842 SNPs to genotype 2,417 barley accessions sampled from the USDA National Small Grains Collection of 33,176 accessions. Most of the accessions in this core collection are categorized as landraces or cultivars/breeding lines and were obtained from more than 100 countries. Both STRUCTURE and principal component analysis identified five major subpopulations within the core collection, mainly differentiated by geographical origin and spike row number (an inflorescence architecture trait). Different patterns of linkage disequilibrium (LD) were found across the barley genome and many regions of high LD contained traits involved in domestication and breeding selection. The genotype data were used to define 'mini-core' sets of accessions capturing the majority of the allelic diversity present in the core collection. These 'mini-core' sets can be used for evaluating traits that are difficult or expensive to score. Genome-wide association studies (GWAS) of 'hull cover', 'spike row number', and 'heading date' demonstrate the utility of the core collection for locating genetic factors determining important phenotypes. The GWAS results were referenced to a new barley consensus map containing 5,665 SNPs. Our results demonstrate that GWAS and high-density SNP genotyping are effective tools for plant breeders interested in accessing genetic diversity in large germplasm collections

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions