Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities

Abstract: Concerns about pollinator declines have grown in recent years, yet the ability to detect changes in abundance, taxonomic richness, and composition of pollinator communities is hampered severely by the lack of data over space and time. Citizen scientists may be able to extend the spatial and temporal extent of pollinator monitoring programs. We developed a citizen‐science monitoring protocol in which we trained 13 citizen scientists to observe and classify floral visitors at the resolution of orders or super families (e.g., bee, wasp, fly) and at finer resolution within bees (superfamily Apoidea) only. We evaluated the protocol by comparing data collected simultaneously at 17 sites by citizen scientists (observational data set) and by professionals (specimen‐based data set). The sites differed with respect to the presence and age of hedgerows planted to improve habitat quality for pollinators. We found significant, positive correlations among the two data sets for higher level taxonomic composition, honey bee (Apis mellifera) abundance, non‐Apis bee abundance, bee richness, and bee community similarity. Results for both data sets also showed similar trends (or lack thereof) in these metrics among sites differing in the presence and age of hedgerows. Nevertheless, citizen scientists did not observe approximately half of the bee groups collected by professional scientists at the same sites. Thus, the utility of citizen‐science observational data may be restricted to detection of community‐level changes in abundance, richness, or similarity over space and time, and citizen‐science observations may not reliably reflect the abundance or frequency of occurrence of specific pollinator species or groups.     

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10⁶ km² larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms.     

Uncertainty characterization for emergy values

While statistical estimation of uncertainty has not typically accompanied published emergy values, as with any other quantitative model, uncertainty is embedded in these values, and lack of uncertainty characterization makes their accuracy not only opaque, it also prevents the use of emergy values in statistical tests of hypotheses. This paper first attempts to describe sources of uncertainty in unit emergy values (UEVs) and presents a framework for estimating this uncertainty with analytical and stochastic models, with model choices dependent upon on how the UEV is calculated and what kind of uncertainties are quantified. The analytical model can incorporate a broader spectrum of uncertainty types than the stochastic model, including model and scenario uncertainty, which may be significant in emergy models, but is only appropriate for the most basic of emergy calculations. Although less comprehensive in its incorporation of uncertainty, the proposed stochastic method is suitable for all types of UEVs. The distributions of unit emergy values approximate the lognormal distribution with variations depending on the types of uncertainty quantified as well as the way the UEVs are calculated. While both methods of estimating uncertainty in UEVs have their limitations in their presented stage of development, this paper provides methods for incorporating uncertainty into emergy, and demonstrates how this can be depicted and propagated so that it can be used in future emergy analyses and permit emergy to be more readily incorporated into other methods of environmental assessment, such as LCA.     

Coupled reservoir-geomechanical analysis of CO2 injection and ground deformations at In Salah,Algeria

In Salah Gas Project in Algeria has been injecting 0.5–1 million tonnes CO₂ per year over the past 5 years into a water-filled strata at a depth of about 1800–1900 m. Unlike most CO₂ storage sites, the permeability of the storage formation is relatively low and comparatively thin with a thickness of about 20 m. To ensure adequate CO₂ flow-rates across the low-permeability sand-face, the In Salah Gas Project decided to use long-reach (about 1–1.5 km) horizontal injection wells. In an ongoing research project we use field data and coupled reservoir-geomechanical numerical modeling to assess the effectiveness of this approach and to investigate monitoring techniques to evaluate the performance of a CO₂ injection operation in relatively low-permeability formations. Among the field data used are ground surface deformations evaluated from recently acquired satellite-based inferrometry (InSAR). The InSAR data shows a surface uplift on the order of 5 mm per year above active CO₂ injection wells and the uplift pattern extends several km from the injection wells. In this paper we use the observed surface uplift to constrain our coupled reservoir-geomechanical model and conduct sensitivity studies to investigate potential causes and mechanisms of the observed uplift. The results of our analysis indicate that most of the observed uplift magnitude can be explained by pressure-induced, poro-elastic expansion of the 20-m-thick injection zone, but there could also be a significant contribution from pressure-induced deformations within a 100-m-thick zone of shaly sands immediately above the injection zone.     

Brain myelination in rats treated with ionizing radiation in utero

Abstract

Effects of ionizing radiation on brain myelination and some physical development parameters were studied in laboratory rats (Fisher F‐344 inbred strain). Rats were treated with three different doses of radiation (150 rad, 15 rad, and 6.8 rad) delivered on the 20th day of prenatal life. Exposure to 150 rad reduced body, brain, ovary, kidney, heart and spleen weights. Prenatal exposure to 150 rad of radiation reduced the cerebral cortex weight by 22 percent at 30 days of age, and 20 percent at 52 days of age which caused a reduction in cerebral cortex myelin content by 20 and 23 percent at the ages of 30 and 52 days respectively. This dose did not affect the myelin content of the cerebellum or the brain stem, or the myelin concentration (mg myelin/g brain tissue) of the cerebral cortex, cerebellum, and the brain stem. The cerebral cortex weight of the 15 rad treated rats was reduced at the age of 30 days. Exposure to 15 rad, and 6.8 rad did not affect either the myelin content or the myelin concentration of these brain areas.     

Photochemical Reactivities of Paraffinic Hydrocarbon-Nitrogen Oxide Mixtures Upon Addition of Propylene or Toluene

Effects associated with photochemical air pollution were measured during irradiation of n-butane-nitrogen oxide or n-butane-ethane-nitrogen oxide mixtures, with small amounts of propylene or toluene added. The effects measured including nitrogen dioxide and oxidant dosages, yields of formaldehyde and peroxy-acetyl nitrate, and eye irritation response. The results obtained clearly show that beneficial effects result from selective changes in hydrocarbon composition as well as from reduction of total hydrocarbon concenfration. Exclusion of olefins and alkylbenzenes was highly effective in reducing oxidant dosage, formaldehyde and peroxyacetyl nitrate concentrations, and eye irritation response. The only penalty was a modest increase in nitrogen dioxide dosage. A large reduction in nitrogen oxide concentration reduced nitrogen dioxide dosage and eye irritation response, but with the penalty of a large increase in oxidant dosage. The desirability of preferentially reducing olefins and alkylbenzenes rather than paraffinic hydrocarbons, acetylene, and benzene is strongly supported by this study. Research and development efforts should be directed toward preferential hydrocarbon control by mechanical or catalytic control     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

Sulfur Dioxide and Material Damage

Whereas most estimates of material damage are based on industrial surveys, the estimates produced in this study were derived from material damage experiments and ambient air quality data. Air quality data on SO₂ were obtained from 200 or more monitoring sites primarily located in heavily populated or polluted areas. Material threshold damage function data were then compared with SO₂ levels, and an estimate of losses, as reflected in increased maintenance and replacement costs, was determined. Estimates of the total stock of various materials in use were derived from census and industry data and allocated geographically according to population. A substantial decrease in the ambient SO₂ levels, particularly in larger urban areas, has occurred during the past five years. From 1968 to 1972, the estimated amount of material damage from SO₂ in the U. S. decreased from $900 million/yr to less than $100 million. During this period, the estimated percentage of man made materials exposed to SO₂ levels exceeding the proposed secondary annual average standard (60 μg/m³) and primary annual average standard (80 μg/m³) in the U. S. fell respectively, from 20% to less than 5% and from more than 10% to less than 1%. Most of the present loss is attributed to corrosion damage of metallic surfaces that are normally exposed to the ambient environment.