An Account Analysis Of PCAOB Inspection Reports For Triennially-Inspected Audit Firms

Since 2005, the PCAOB (Public Company Accounting Oversight Board) has been issuing inspection reports for triennially-inspected audit firms as part of its overall mission to improve audit quality.  This study analyzes the findings in the PCAOB inspection reports by classifying the audit deficiencies cited in the reports by area of deficiency and type of audit failure.  CPA firms can utilize these findings in their efforts to reduce client engagement audit risk.  The results indicate that the overall number of cited deficiencies is declining each year, revenue and asset accounts are the most frequently cited accounts, business combinations and equity transactions are the most cited transactions, and insufficient testing or documentation is the primary type of audit failure.  We also document that most departures from GAAP occur in the accounting for business transactions or in liability accounts

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

GOES-R Algorithms: A Common Science and Engineering Design and Development Approach for Delivering Next Generation Environmental Data Products

GOES-R, the next generation of the National Oceanic and Atmospheric Administration’s (NOAA) Geostationary Operational Environmental Satellite (GOES) System, represents a new technological era in operational geostationary environmental satellite systems. GOES-R will provide advanced products that describe the state of the atmosphere, land, oceans, and solar/ space environments over the western hemisphere. The Harris GOES-R Ground Segment team will provide the software, based on government-supplied algorithms, and engineering infrastructures designed to produce and distribute these next-generation data products. The Harris GOES-R Team has adopted an integrated applied science and engineering approach that combines rigorous system engineering methods, with modern software design elements to facilitate the transition of algorithms for Level 1 and 2+ products to operational software. The Harris Team GOES-R GS algorithm framework, which includes a common data model interface, provides general design principles and standardized methods for developing general algorithm services, interfacing to external data, generating intermediate and L1b and L2 products and implementing common algorithm features such as metadata generation and error handling. This work presents the suite of GOES-R products, their properties and the process by which the related requirements are maintained during the complete design/development life-cycle. It also describes the algorithm architecture/engineering approach that will be used to deploy these algorithms, and provides a preliminary implementation road map for the development of the GOES-R GS software infrastructure, and a view into the integration of the framework and data model into the final design

Ecological research in the Large Scale Biosphere Atmosphere Experiment in Amazonia: A discussion of early results

The Large-scale Biosphere–Atmosphere Experiment in Amazonia (LBA) is a multinational, interdisciplinary research program led by Brazil. Ecological studies in LBA focus on how tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in the Amazon region. Early results from ecological studies within LBA emphasize the variability within the vast Amazon region and the profound effects that land-use and land-cover changes are having on that landscape. The predominant land cover of the Amazon region is evergreen forest; nonetheless, LBA studies have observed strong seasonal patterns in gross primary production, ecosystem respiration, and net ecosystem exchange, as well as phenology and tree growth. The seasonal patterns vary spatially and interannually and evidence suggests that these patterns are driven not only by variations in weather but also by innate biological rhythms of the forest species. Rapid rates of deforestation have marked the forests of the Amazon region over the past three decades. Evidence from ground-based surveys and remote sensing show that substantial areas of forest are being degraded by logging activities and through the collapse of forest edges. Because forest edges and logged forests are susceptible to fire, positive feedback cycles of forest degradation may be initiated by land-use-change events. LBA studies indicate that cleared lands in the Amazon, once released from cultivation or pasture usage, regenerate biomass rapidly. However, the pace of biomass accumulation is dependent upon past land use and the depletion of nutrients by unsustainable land-management practices. The challenge for ongoing research within LBA is to integrate the recognition of diverse patterns and processes into general models for prediction of regional ecosystem function

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone

Morality Stories: Dilemmas in Ethics, Crime & Justice

pt. 1. Stories and moral dilemmas : an introduction--pt. 2. Loyalty and personal relationships--Black and blue--Amnesia of the heart--Sarah Salvation--Rosy--A different justice--Stray dogs--A harmless little romance--The end is near--pt. 3. Duties to self and others--Rasheed\u27s ticket--Invisible boy--Short-cut--The big picture--Special of the week--It\u27s too bad about Tommy--Ballad of the Wafflehouse queen--Truth teller--pt. 4. Justice and redemption--The open door--Prison lullabies--Tin spoke parade--Thunder for Mally--Best intentions--The cracker jack gospel--The mercy seat--As is.https://dc.etsu.edu/etsu_books/1103/thumbnail.jp

Morality Stories: Dilemmas in Ethics, Crime & Justice

pt. 1. Stories and moral dilemmas : an introduction--pt. 2. Loyalty and personal relationships--1. Black and blue--2. Amnesia of the heart--3. Sarah Salvation--4. Rosy--5. A different justice--6. Stray dogs--pt. 3. Duties to self and others--7. Rasheed\u27s ticket--8. Invisible boy--9. The big picture--10. Special of the week--11. It\u27s too bad about Tommy--12. Truth teller--pt. 4. Justice and redemption--13. The open door--14. Prison lullabies--15. Tin spoke parade--16. Thunder for Mally--17. The mercy seat--18. As is.https://dc.etsu.edu/etsu_books/1102/thumbnail.jp

Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange

Tower-based eddy covariance measurements of forest-atmosphere carbon dioxide (CO2) exchange from many sites around the world indicate that there is considerable year-to-year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration,Reco, and gross photosynthesis, Pgross) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9-year data set from the Howland AmeriFlux site, a spruce-dominated forest in Maine, USA. Gap-filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m−2 yr−1, with a range from 130 to 270 g C m−2 yr−1. Our fitted model predicts somewhat more uptake (mean 270 g C m−2 yr−1), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both Reco and Pgross. Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual Pgross and Reco (r=−0.93,P≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either Pgross or Rec

The role of remote sensing in the study of terrestrial net primary production

Extension of field measurements to appropriate spatial scales is essential to addressing regional and global ecological patterns and environmental problems. The selective absorption and reflection of radiation by plant tissues provide the basis for obtaining relevant information using remote sensing platforms to sample large portions of the Earth\u27s surface. This chapter details the most commonly used remote sensing approaches for production estimation on land. Passive sensors are described in conjunction with light-use models and ecosystem process models for large-scale estimation of primary production. Active sensors, including radar and lidar, also are described

Use of digital webcam images to track spring green-up in a deciduous broadleaf forest

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO2 by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 × 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy (f APAR), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis (A max), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f APAR and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A max lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program