The State of the Death Penalty

The death penalty is in decline in America and most death penalty states do not regularly impose death sentences. In 2016 and 2017, states reached modern lows in imposed death sentences, with just thirty-one defendants sentenced to death in 2016 and thirty-nine in 2017, as compared with over three hundred per year in the 1990s. In 2016, only thirteen states imposed death sentences, and in 2017, fourteen did so, although thirty-one states retain the death penalty. What explains this remarkable and quite unexpected trend? In this Article, we present new analysis of state-level legislative changes that might have been expected to impact death sentences. First, life without parole (LWOP) statutes, now enacted in nearly every state, might have been expected to reduce death sentences because they give jurors a non-capital option at trial. Second, legislatures have moved, albeit at varying paces, to comply with the Supreme Court’s holding in Ring v. Arizona, which requires that the final decision in capital sentencing be made not by a judge, but by a jury. Third, states at different times have created state-wide public defender offices to represent capital defendants at trial. In addition, the decline in homicides and homicide rates could be expected to contribute to the decline in state-level death sentencing. We find that contrary to the expectations of many observers, changes in the law such as adoption of LWOP and jury sentencing, did not consistently or significantly impact death sentencing. The decline in homicides and homicide rates is correlated with changes in death sentencing at the state level. However, this Article finds that state provision of capital trial representation is far more strongly and robustly correlated with reduced death sentencing than these other factors. The findings bolster the argument that adequacy of counsel has greater implications for the administration of the death penalty than other legal factors. These findings also have implications beyond the death penalty and they underscore the importance of a structural understanding of the Sixth Amendment right to counsel in our system of criminal justice

Carbon Flux Phenology from the Sky: Evaluation for Maize and Soybean

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. Presented here are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop-specific measurement tool

A rare case of Levofloxacin induced ventricular arrhythmia

Drug induced cardiac arrhythmias are seen commonly in clinical practice. Amongst drugs, antibiotics have a specific predisposition, and amongst them, macrolides and fluoroquinolones are specifically seen to have such a tendency. However, amongst fluoroquinolones, the rate of incidence of quinolone induced cardiac arrhythmia is reported as 5.4 cases per 10 million prescriptions. Here, we report a rare case of a probable Adverse Drug Reaction (ADR) i.e., Left Ventricular inferoposterior surface bigeminy recorded 24 hours after initiation of levofloxacin which disappeared after 24 hours of its discontinuation

The spatial scale dependence of water vapor variability inferred from observations from a very tall tower

Recent studies have established that atmospheric water vapor fields exhibit spatial spectra that take the form of power laws and hence can be compactly characterized by scaling exponents. The power law scaling exponents have been shown to exhibit substantial vertical variability. In this work, Taylor's frozen turbulence hypothesis is used to infer the first-order spatial structure function and generalized detrended fluctuation function scaling exponents for scales between 1 km and 100 km. Both methods are used to estimate the Hurst exponent (H) using 10 Hz time series of water vapor measured at 396 m altitude from an Ameriflux tower in Wisconsin. Due to the diurnal cycle in the boundary layer height at the 396 m observational level, H may be estimated for both the daytime convective mixed layer and the nocturnal residual layer. Values of H ≈ 1/3 are obtained for the convective mixed layer, while values of H > 1/2 apply in the nocturnal residual layer. The results are shown to be remarkably consistent with a similar analysis from satellite-based observations as reported in Pressel and Collins (2012)

Space‐Scale Resolved Surface Fluxes Across a Heterogeneous, Mid‐Latitude Forested Landscape

The Earth\u27s surface is heterogeneous at multiple scales owing to spatial variability in various properties. The atmospheric responses to these heterogeneities through fluxes of energy, water, carbon, and other scalars are scale-dependent and nonlinear. Although these exchanges can be measured using the eddy covariance technique, widely used tower-based measurement approaches suffer from spectral losses in lower frequencies when using typical averaging times. However, spatially resolved measurements such as airborne eddy covariance measurements can detect such larger scale (meso-β, meso-γ) transport. To evaluate the prevalence and magnitude of these flux contributions, we applied wavelet analysis to airborne flux measurements over a heterogeneous mid-latitude forested landscape, interspersed with open water bodies and wetlands. The measurements were made during the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors intensive field campaign. We ask, how do spatial scales of surface-atmosphere fluxes vary over heterogeneous surfaces across the day and across seasons? Measured fluxes were separated into smaller-scale turbulent and larger-scale mesoscale contributions. We found significant mesoscale contributions to sensible and latent heat fluxes through summer to autumn which would not be resolved in single-point tower measurements through traditional time-domain half-hourly Reynolds decomposition. We report scale-resolved flux transitions associated with seasonal and diurnal changes of the heterogeneous study domain. This study adds to our understanding of surface-atmospheric interactions over unstructured heterogeneities and can help inform multi-scale model-data integration of weather and climate models at a sub-grid scale

Persistent reduced ecosystem respiration after insect disturbance in high elevation forests

Amid a worldwide increase in tree mortality, mountain pine beetles (Dendroctonus ponderosae Hopkins) have led to the death of billions of trees from Mexico to Alaska since 2000. This is predicted to have important carbon, water and energy balance feedbacks on the Earth system. Counter to current projections, we show that on a decadal scale, tree mortality causes no increase in ecosystem respiration from scales of several square metres up to an 84 km2 valley. Rather, we found comparable declines in both gross primary productivity and respiration suggesting little change in net flux, with a transitory recovery of respiration 6–7 years after mortality associated with increased incorporation of leaf litter C into soil organic matter, followed by further decline in years 8–10. The mechanism of the impact of tree mortality caused by these biotic disturbances is consistent with reduced input rather than increased output of carbon

eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5

Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time

Novel approach to observing system simulation experiments improves information gain of surface-atmosphere field measurements

The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation-environmental response function (NS-ERF) approach to observing system simulation experiments that aids surface-atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS-ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS-ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS-ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases. © 2021 Stefan Metzger et al

Impact of forest plantation on methane emissions from tropical peatland

Tropical peatlands are a known source of methane (CH4) to the atmosphere, but their contribution to atmospheric CH4 is poorly constrained. Since the 1980s, extensive areas of the peatlands in Southeast Asia have experienced land‐cover change to smallholder agriculture and forest plantations. This land‐cover change generally involves lowering of groundwater level (GWL), as well as modification of vegetation type, both of which potentially influence CH4 emissions. We measured CH4 exchanges at the landscape scale using eddy covariance towers over two land‐cover types in tropical peatland in Sumatra, Indonesia: (a) a natural forest and (b) an Acacia crassicarpa plantation. Annual CH4 exchanges over the natural forest (9.1 ± 0.9 g CH4 m−2 year−1) were around twice as high as those of the Acacia plantation (4.7 ± 1.5 g CH4 m−2 year−1). Results highlight that tropical peatlands are significant CH4 sources, and probably have a greater impact on global atmospheric CH4 concentrations than previously thought. Observations showed a clear diurnal variation in CH4 exchange over the natural forest where the GWL was higher than 40 cm below the ground surface. The diurnal variation in CH4 exchanges was strongly correlated with associated changes in the canopy conductance to water vapor, photosynthetic photon flux density, vapor pressure deficit, and air temperature. The absence of a comparable diurnal pattern in CH4 exchange over the Acacia plantation may be the result of the GWL being consistently below the root zone. Our results, which are among the first eddy covariance CH4 exchange data reported for any tropical peatland, should help to reduce the uncertainty in the estimation of CH4 emissions from a globally important ecosystem, provide a more complete estimate of the impact of land‐cover change on tropical peat, and develop science‐based peatland management practices that help to minimize greenhouse gas emissions