FIREBALL: Instrument pointing and aspect reconstruction

The Faint Intergalactic Redshifted Emission Balloon (FIREBALL) had its first scientific flight in June 2009. The instrument is a 1 meter class balloon-borne telescope equipped with a vacuum-ultraviolet integral field spectrograph intended to detect emission from the inter-galactic medium at redshifts 0.3 < z < 1.0. The scientific goals and the challenging environment place strict constraints on the pointing and tracking systems of the gondola. In this manuscript we briefly review our pointing requirements, discuss the methods and solutions used to meet those requirements, and present the aspect reconstruction results from the first successful scientific flight

FIREBALL: the Faint Intergalactic medium Redshifted Emission Balloon: overview and first science flight results

FIREBALL (the Faint Intergalactic Redshifted Emission Balloon) is a balloon-borne 1m telescope coupled to an ultraviolet fiber-fed spectrograph. FIREBALL is designed to study the faint and diffuse emission of the intergalactic medium, until now detected primarily in absorption. FIREBALL is a path finding mission to test new technology and make new constraints on the temperature and density of this gas. We report on the first successful science flight of FIREBALL, in June 2009, which proved every aspect of the complex instrument performance, and provided the strongest measurements and constraints on IGM emission available from any instrument

High-Q spectral peaks and nonstationarity in the deep ocean infragravity wave band: Tidal harmonics and solar normal modes

Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(3), (2019):2072-2087, doi:10.1029/2018JC014586.Infragravity waves have received the least study of any class of waves in the deep ocean. This paper analyzes a 389‐day‐long deep ocean pressure record from the Hawaii Ocean Mixing Experiment for the presence of narrowband (≲2 μHz) components and nonstationarity over 400–4,000 μHz using a combination of fitting a mixture noncentral/central χ2 model to spectral estimates, high‐resolution multitaper spectral estimation, and computation of the offset coherence between distinct frequencies for a given data segment. In the frequency band 400–1,000 μHz there is a noncentral fraction of 0.67 ± 0.07 that decreases with increasing frequency. Evidence is presented for the presence of tidal harmonics in the data over the 400‐ to 1,400‐μHz bands. Above ~2,000 μHz the noncentral fraction rises with frequency, comprising about one third of the spectral estimates over 3,000–4,000 μHz. The power spectrum exhibits frequent narrowband peaks at 6–11 standard deviations above the noise level. The widths of the peaks correspond to a Q of at least 1,000, vastly exceeding that of any oceanic or atmospheric process. The offset coherence shows that the spectral peaks have substantial (p = 0.99–0.9999) interfrequency correlation, both locally and between distinct peaks within a given analysis band. Many of the peak frequencies correspond to the known values for solar pressure modes that have previously been observed in solar wind and terrestrial data, while others are the result of nonstationarity that distributes power across frequency. Overall, this paper documents the existence of two previously unrecognized sources of infragravity wave variability in the deep ocean.This work was supported at WHOI by an Independent Research and Development award and the Walter A. and Hope Noyes Smith Chair for Excellence in Oceanography. At the University of Hawaii, Martin Guiles provided a number of consequential data analyses, and work was supported by NSF‐OCE1460022. D. J. T. acknowledges support from Queen's University and NSERC. The data used in this study are available from the supporting information.2019-08-2

Limited carbon and biodiversity co-benefits for tropical forest mammals and birds

The conservation of tropical forest carbon stocks offers the opportunity to curb climate change by reducing greenhouse gas emissions from deforestation and simultaneously conserve biodiversity. However, there has been considerable debate about the extent to which carbon stock conservation will provide benefits to biodiversity in part because whether forests that contain high carbon density in their aboveground biomass also contain high animal diversity is unknown. Here, we empirically examined medium to large bodied ground-dwelling mammal and bird (hereafter "wildlife") diversity and carbon stock levels within the tropics using camera trap and vegetation data from a pantropical network of sites. Specifically, we tested whether tropical forests that stored more carbon contained higher wildlife species richness, taxonomic diversity, and trait diversity. We found that carbon stocks were not a significant predictor for any of these three measures of diversity, which suggests that benefits for wildlife diversity will not be maximized unless wildlife diversity is explicitly taken into account; prioritizing carbon stocks alone will not necessarily meet biodiversity conservation goals. We recommend conservation planning that considers both objectives because there is the potential for more wildlife diversity and carbon stock conservation to be achieved for the same total budget if both objectives are pursued in tandem rather than independently. Tropical forests with low elevation variability and low tree density supported significantly higher wildlife diversity. These tropical forest characteristics may provide more affordable proxies of wildlife diversity for future multi-objective conservation planning when fine scale data on wildlife are lacking

A characterization of periodicity in the voltage time series of a riometer

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Space Physics 125(7), (2020): e2019JA027160, doi:10.1029/2019JA027160.This paper reveals unprecedented periodicity in the voltage series of relative ionospheric opacity meters (riometers) of the Canadian Riometer Array (CRA). In quiet times, the riometer voltage series is accurately modeled by a stochastic process whose components include both a six term expansion in harmonic functions and some amplitude modulated modes of lower signal to noise ratio (SNR). In units of cycles per sidereal day (cpsd), the frequencies of the six harmonic functions lie within 0.01 cpsd of an integer. Earth's rotation induces a splitting of the low SNR components, resulting in the appearance of nine multiplets in standardized power spectrum estimates of the considered CRA voltage series. A second feature of these spectrum estimates is a 6 min periodic element appearing in both the CRA voltage series and the proton mass density series of the Advanced Composition Explorer (ACE). Spectral peak frequencies have been detected, which lie near established solar mode frequency estimates. In addition, some of these peak frequency estimates are coincident with peak frequency estimates of the standardized power spectra for the time series of proton mass density and interplanetary magnetic field strength (IMF) at ACE.“Marshall_Francois_Supporting_Information_JGR_2019.pdf” contains a summary of the supporting information. The 1 hr sampled F10.7 series was obtained from DRAO (National Research Council, 2017). The three MAG time series of IMF strength were acquired from The ACE Science Center (2007), while the SWEPAM time series of proton mass density was acquired from Space Weather Prediction Center, National Oceanic and Atmospheric Administration (2018). The relevant data sets for the analysis of this paper are included in Marshall (2019). This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), Canadian Statistical Sciences Institute (CANSSI), Bonneyville Power Authority, and Queen's University. David J. Thomson, the official holder of the grants and contracts, provided research and conference funding to advance this project. Special thanks to Ken F. Tapping (DRAO of NRCan) for his guidance in finding the data sets relevant to solar radio emissions. Glen Takahara, of the Department of Mathematics and Statistics at Queen's University, suggested exploring different data sets to confirm the modal origin of spectral peaks observed in the Ottawa riometer of the CRA. Alessandra A. Pacini of the Arecibo Observatory recommended checking to see if some of the modes could have been driven by the harmonics of Earth's rotation. Frank Vernon of the Institute of Geophysics and Planetary Physics at Scripps Institution of Oceanography confirmed how seismic data could be expected to reveal coincident spectral peaks at the detected frequencies in the riometer standardized spectra.2020-10-2

A new hammer to crack an old nut : interspecific competitive resource capture by plants is regulated by nutrient supply, not climate

Peer reviewedPublisher PD

Ecological implications of a flower size/number trade-off in tropical forest trees

Peer reviewedPublisher PD

Does the disturbance hypothesis explain the biomass increase in basin-wide Amazon forest plot data?

Positive aboveground biomass trends have been reported from old-growth forests across the Amazon basin and hypothesized to reflect a large-scale response to exterior forcing. The result could, however, be an artefact due to a sampling bias induced by the nature of forest growth dynamics. Here, we characterize statistically the disturbance process in Amazon old-growth forests as recorded in 135 forest plots of the RAINFOR network up to 2006, and other independent research programmes, and explore the consequences of sampling artefacts using a data-based stochastic simulator. Over the observed range of annual aboveground biomass losses, standard statistical tests show that the distribution of biomass losses through mortality follow an exponential or near-identical Weibull probability distribution and not a power law as assumed by others. The simulator was parameterized using both an exponential disturbance probability distribution as well as a mixed exponential–power law distribution to account for potential large-scale blowdown events. In both cases, sampling biases turn out to be too small to explain the gains detected by the extended RAINFOR plot network. This result lends further support to the notion that currently observed biomass gains for intact forests across the Amazon are actually occurring over large scales at the current time, presumably as a response to climate change

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs