Long-term carbon and nitrogen dynamics at SPRUCE revealed through stable isotopes in peat profiles

Peatlands encode information about past vegetation dynamics, climate, and microbial processes. Here, we used δ15N and δ13C patterns from 16 peat profiles to deduce how the biogeochemistry of the Marcell S1 forested bog in northern Minnesota responded to environmental and vegetation change over the past  ∼ 10000 years. In multiple regression analyses, δ15N and δ13C correlated strongly with depth, plot location, C∕N, %N, and each other. Correlations with %N, %C, C∕N, and the other isotope accounted for 80% of variance for δ15N and 38% of variance for δ13C, reflecting N and C losses. In contrast, correlations with depth and topography (hummock or hollow) reflected peatland successional history and climate. Higher δ15N in plots closer to uplands may reflect upland-derived DON inputs and accompanying shifts in N dynamics in the lagg drainage area surrounding the bog. The Suess effect (declining δ13CO2 since the Industrial Revolution) lowered δ13C in recent surficial samples. High δ15N from −35 to −55cm probably indicated the depth of ectomycorrhizal activity after tree colonization of the peatland over the last 400 years, as confirmed by the occasional presence of wood down to −35cm depth. High δ13C at  ∼ 4000 years BP (−65 to −105cm) could reflect a transition at that time to slower rates of peat accumulation, when 13C discrimination during peat decomposition may increase in importance. Low δ13C and high δ15N at −213 and −225cm ( ∼ 8500 years BP) corresponded to a warm period during a sedge-dominated rich fen stage. The above processes appear to be the primary drivers of the observed isotopic patterns, whereas there was no clear evidence for methane dynamics influencing δ13C patterns

National Geodetic Satellite Program, Part II: Smithsonian Astrophysical Observatory

A sequence of advances in the determination of geodetic parameters presented by the Smithsonian Astrophysical Observatory are described. A Baker-Nunn photographic system was used in addition to a ruby-laser ranging system to obtain data for refinement of geodetic parameters. A summary of the data employed to: (1) derive coordinates for the locations of various tracking stations; and (2) determine the gravitational potential of the earth, is presented

Using scenarios to explore UK upland futures

Uplands around the world are facing significant social, economic and environmental changes, and decision-makers need to better understand what the future may hold if they are to adapt and maintain upland goods and services. This paper draws together all major research comprising eight studies that have used scenarios to describe possible futures for UK uplands. The paper evaluates which scenarios are perceived by stakeholders to be most likely and desirable, and assesses the benefits and drawbacks of the scenario methods used in UK uplands to date. Stakeholders agreed that the most desirable and likely scenario would be a continuation of hill farming (albeit at reduced levels) based on cross-compliance with environmental measures. The least desirable scenario is a withdrawal of government financial support for hill farming. Although this was deemed by stakeholders to be the least likely scenario, the loss of government support warrants close attention due to its potential implications for the local economy. Stakeholders noted that the environmental implications of this scenario are much less clear-cut. As such, there is an urgent need to understand the full implications of this scenario, so that upland stakeholders can adequately prepare, and policy-makers can better evaluate the likely implications of different policy options. The paper concludes that in future, upland scenario research needs to: (1) better integrate in-depth and representative participation from stakeholders during both scenario development and evaluation; and (2) make more effective use of visualisation techniques and simulation models

A proximal sensing cart and custom cooling box for improved hyperspectral sensing in a desert environment

BackgroundAdvancements in field spectrometry have the potential to increase understanding of crop growth and development in response to hot and dry environments. However, as with any instrument used for scientific advancement, it is important to continue developing and optimizing data collection protocols to promote efficiency, safety, and data quality. The goal of this study was to develop a novel data collection method, involving a proximal sensing cart with onboard cooling equipment, to improve deployments of a field spectroradiometer in a hot and dry environment. Advantages and disadvantages of the new method were compared with the traditional backpack approach and other approaches reported in literature.ResultsThe novel method prevented the spectroradiometer from overheating and nearly eliminated the need to halt data collection for battery changes. It also enabled data collection from a significantly larger field area and from more field plots as compared to the traditional backpack method. Use of a custom cooling box to stabilize operating temperatures for the field spectroradiometer also improved stability of white panel data both within and among collections despite outside air temperatures in excess of 30°C.ConclusionsAs compared to traditional data collection approaches for measuring spectral reflectance of field crops in a hot and dry environment, use of a proximal sensing cart with a customized equipment cooling box improved spectroradiometer performance, increased practicality of equipment transport, and reduced operator safety concerns

The ALMaQUEST survey IX: The nature of the resolved star forming main sequence

We investigate the nature of the scaling relations between the surface density of star formation rate ($\Sigma _{\rm SFR}$), stellar mass ($\Sigma _*$), and molecular gas mass ($\Sigma _{\rm H_2}$), aiming at distinguishing between the relations that are primary, i.e. more fundamental, and those which are instead an indirect by-product of the other relations. We use the ALMaQUEST survey and analyse the data by using both partial correlations and Random Forest regression techniques. We unambiguously find that the strongest intrinsic correlation is between $\Sigma _{\rm SFR}$ and $\Sigma_{\rm H_2}$ (i.e. the resolved Schmidt-Kennicutt relation), followed by the correlation between $\Sigma _{\rm H_2}$ and $\Sigma _*$ (resolved Molecular Gas Main Sequence, rMGMS). Once these two correlations are taken into account, we find that there is no evidence for any intrinsic correlation between $\Sigma _{\rm SFR}$ and $\Sigma _*$, implying that SFR is entirely driven by the amount of molecular gas, while its dependence on stellar mass (i.e. the resolved Star Forming Main Sequence, rSFMS) simply emerges as a consequence of the relationship between molecular gas and stellar mass.Science and Technology Facilities Council (STFC). ERC Advanced Grant 695671 "QUENCH"

Characterizing the Cool KOIs. VI. H- and K-band Spectra of Kepler M Dwarf Planet-Candidate Hosts

We present H- and K-band spectra for late-type Kepler Objects of Interest (the "Cool KOIs"): low-mass stars with transiting-planet candidates discovered by NASA's Kepler Mission that are listed on the NASA Exoplanet Archive. We acquired spectra of 103 Cool KOIs and used the indices and calibrations of Rojas-Ayala et al. to determine their spectral types, stellar effective temperatures and metallicities, significantly augmenting previously published values. We interpolate our measured effective temperatures and metallicities onto evolutionary isochrones to determine stellar masses, radii, luminosities and distances, assuming the stars have settled onto the main-sequence. As a choice of isochrones, we use a new suite of Dartmouth predictions that reliably include mid-to-late M dwarf stars. We identify five M4V stars: KOI-961 (confirmed as Kepler 42), KOI-2704, KOI-2842, KOI-4290, and the secondary component to visual binary KOI-1725, which we call KOI-1725 B. We also identify a peculiar star, KOI-3497, which has a Na and Ca lines consistent with a dwarf star but CO lines consistent with a giant. Visible-wavelength adaptive optics imaging reveals two objects within a 1 arc second diameter; however, the objects' colors are peculiar. The spectra and properties presented in this paper serve as a resource for prioritizing follow-up observations and planet validation efforts for the Cool KOIs, and are all available for download online using the "data behind the figure" feature.Comment: Accepted for publication in the Astrophysical Journal Supplement Series (ApJS). Data and table are available in the sourc

Dynamic optimal taxation with human capital.

This paper revisits the dynamic optimal taxation results of Jones, Manuelli, and Rossi (1993, 1997). They use a growth model with human capital and find that optimal taxes on both capital income and labor income converge to zero in steady state. For one of the models under consideration, I show that the representative household's problem does not have an interior solution. This raises concerns since these corners are inconsistent with aggregate data. Interiority is restored if preferences are modified so that human capital augments the value of leisure time. With this change, the optimal tax problem is analyzed and, reassuringly, the Jones, Manuelli, and Rossi results are confirmed: neither capital income nor labor income should be taxed in steady state

Proximal hyperspectral sensing and data analysis approaches for field-based plant phenomics

Field-based plant phenomics requires robust crop sensing platforms and data analysis tools to successfully identify cultivars that exhibit phenotypes with high agronomic and economic importance. Such efforts will lead to genetic improvements that maintain high crop yield with concomitant tolerance to environmental stresses. The objectives of this study were to investigate proximal hyperspectral sensing with a field spectroradiometer and to compare data analysis approaches for estimating four cotton phenotypes: leaf water content (Cw), specific leaf mass (Cm), leaf chlorophyll a+b content (Cab), and leaf area index (LAI). Field studies tested 25 Pima cotton cultivars grown under well-watered and water-limited conditions in central Arizona from 2010 to 2012. Several vegetation indices, including the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the physiological (or photochemical) reflectance index (PRI) were compared with partial least squares regression (PLSR) approaches to estimate the four phenotypes. Additionally, inversion of the PROSAIL plant canopy reflectance model was investigated to estimate phenotypes based on 3.68 billion PROSAIL simulations on a supercomputer. Phenotypic estimates from each approach were compared with field measurements, and hierarchical linear mixed modeling was used to identify differences in the estimates among the cultivars and water levels. The PLSR approach performed best and estimated Cw,Cm,Cab, and LAI with root mean squared errors (RMSEs) between measured and modeled values of 6.8%, 10.9%, 13.1%, and 18.5%, respectively. Using linear regression with the vegetation indices, no index estimated Cw,Cm,Cab, and LAI with RMSEs better than 9.6%, 16.9%, 14.2%, and 28.8%, respectively. PROSAIL model inversion could estimate Cab and LAI with RMSEs of about 16% and 29%, depending on the objective function. However, the RMSEs for Cw and Cm from PROSAIL model inversion were greater than 30%. Compared to PLSR, advantages to the physically-based PROSAIL model include its ability to simulate the canopy's bidirectional reflectance distribution function (BRDF) and to estimate phenotypes from canopy spectral reflectance without a training data set. All proximal hyperspectral approaches were able to identify differences in phenotypic estimates among the cultivars and irrigation regimes tested during the field studies. Improvements to these proximal hyperspectral sensing approaches could be realized with a high-throughput phenotyping platform able to rapidly collect canopy spectral reflectance data from multiple view angles

The time resolution of the St. Petersburg paradox

A resolution of the St. Petersburg paradox is presented. In contrast to the standard resolution, utility is not required. Instead, the time-average performance of the lottery is computed. The final result can be phrased mathematically identically to Daniel Bernoulli's resolution, which uses logarithmic utility, but is derived using a conceptually different argument. The advantage of the time resolution is the elimination of arbitrary utility functions.Comment: 20 pages, 1 figur

Pregnancy intention and postpartum depression: secondary data analysis from a prospective cohort

To assess the relationship between unintended pregnancy and postpartum depression