A Bayesian strategy for combining predictions from empirical and process-based models

We present a strategy for using an empirical forest growth model to reduce uncertainty in predictions made with a physiological process-based forest ecosystem model. The uncertainty reduction is carried out via Bayesian melding, in which information from prior knowledge and a deterministic computer model is conditioned on a likelihood function. We used predictions from an empirical forest growth model G-HAT in place of field observations of aboveground net primary productivity (ANPP) in a deciduous temperate forest ecosystem. Using Bayesian melding, priors for the inputs of the process-based forest ecosystem PnET-II were propagated through the model, and likelihoods for the PnET-II output ANPP were calculated using the G-HAT predictions. Posterior distributions for ANPP and many PnET-II inputs obtained using the G-HAT predictions largely matched posteriors obtained using field data. Since empirical growth models are often more readily available than extensive field data sets, the method represents a potential gain in efficiency for reducing the uncertainty of process-based model predictions when reliable empirical models are available but high-quality data are not.     

用Autospec-Ultima NT气相色谱-高分辨质谱分析二噁英及相关的持久性有机污染物

"二噁英"是指一类化学结构和生物特征均有某些相似之处的化合物.这些有毒化合物有几百种,可分为相关的三大类:氯代二苯并-对-二噁英(CDDs),氯代二苯并呋喃(CDFs)和某些多氯代联苯(PCBs).CDDs和CDFs并非与生具有,而是由于人类活动不注意而生成的.天然过程也会产生CDDs和CDFs.     

Quantifying biases in marine-protected-area placement relative to abatable threats

Marine protected areas (MPAs) are a critical defense against biodiversity loss in the world's oceans, but to realize near-term conservation benefits, they must be established where major threats to biodiversity occur and can be mitigated. We quantified the degree to which MPA establishment has targeted stoppable threats (i.e., threats that can be abated through effectively managed MPAs alone) by combining spatially explicit marine biodiversity threat data in 2008 and 2013 and information on the location and potential of MPAs to halt threats. We calculated an impact metric to determine whether countries are protecting proportionally more high- or low-threat ecoregions and compared observed values with random protected-area allocation. We found that protection covered <2% of ecoregions in national waters with high levels of abatable threat in 2013, which is ∼59% less protection in high-threat areas than if MPAs had been placed randomly. Relatively low-threat ecoregions had 6.3 times more strict protection (International Union for Conservation of Nature categories I–II) than high-threat ecoregions. Thirty-one ecoregions had high levels of stoppable threat but very low protection, which presents opportunities for MPAs to yield more significant near-term conservation benefits. The extent of the global MPA estate has increased, but the establishment of MPAs where they can reduce threats that are driving biodiversity loss is now urgently needed.     

Correction methods for organic carbon artifacts when using quartz-fiber filters in large particulate matter monitoring networks: the regression method and other options

Sampling and handling artifacts can bias filter-based measurements of particulate organic carbon (OC). Several measurement-based methods for OC artifact reduction and/or estimation are currently used in research-grade field studies. OC frequently is not artifact-corrected in large routine sampling networks (e.g., U.S. Environmental Protection Agency (EPA)'s Chemical Speciation Network). In some cases, the OC artifact has been corrected using a regression method (RM) for artifact estimation. In this method, the gamma-intercept of the regression of the OC concentration on the fine particle (PM2.5) mass concentration is taken to be an estimate of the average OC sampling artifact (net of positive and negative artifacts). This paper discusses options for artifact correction in large routine sampling networks. Specifically, the goals are to (1) articulate the assumptions and limitations inherent to the RM, (2) describe other artifact correction approaches, and (3) suggest a cost-effective method for artifact correction in large monitoring networks. The RM assumes a linear relationship between measured OC and PM mass: a constant slope (OC mass fraction) and a constant intercept (RM artifact estimate). These assumptions are not always valid. Additionally, outliers and other individual data points can have a large influence on the RM artifact estimates. The RM yields results within the range of measurement-based methods for some datasets and not for others. Given that the adsorption of organic gases increases with atmospheric concentrations of organics, subtraction of an average artifact from all samples (e.g., across multiple sites) will underestimate OC for lower-concentration samples (e.g., clean sites) and overestimate OC for higher-concentration samples (e.g., polluted sites). For relatively accurate, simple, and cost-effective artifact OC estimation in large networks, the authors suggest backup filter sampling on at least 10% of sampling days at all sites with artifact correction on a sample-by-sample basis as described herein.     

Characterization of PM(2.5) collected during broadcast and slash-pile prescribed burns of predominately ponderosa pine forests in northern Arizona

Prescribed burning, in combination with mechanical thinning, is a successful method for reducing heavy fuel loads from forest floors and thereby lowering the risk of catastrophic wildfire. However, an undesirable consequence of managed fire is the production of fine particulate matter or PM(2.5) (particles ≤2.5 μm in aerodynamic diameter). Wood-smoke particulate data from 21 prescribed burns are described, including results from broadcast and slash-pile burns. All PM(2.5) samples were collected in situ on day 1 (ignition) or day 2. Samples were analyzed for mass, polycyclic aromatic hydrocarbons (PAHs), inorganic elements, organic carbon (OC), and elemental carbon (EC). Results were characteristic of low intensity, smoldering fires. PM(2.5) concentrations varied from 523 to 8357 μg m(-3) and were higher on day 1. PAH weight percents (19 PAHs) were higher in slash-pile burns (0.21 ± 0.08% OC) than broadcast burns (0.07 ± 0.03% OC). The major elements were K, Cl, S, and Si. OC and EC values averaged 66 ± 7 and 2.8 ± 1.4% PM(2.5), respectively, for all burns studied, in good agreement with literature values for smoldering fires.     

Adverse outcome in pregnancy following amniotic fluid isolation of Ureaplasma urealyticum

Infections in pregnancy with Ureaplasma urealyticum have been associated with a wide range of adverse outcomes, such as early abortion, stillbirth, prematurity, and neonatal morbidity and mortality. Causality has been difficult to demonstrate secondary to the high prevalence of asymptomatic lower genital tract (LGT) colonization and culture data from inaccessible or potentially contaminated sites. Between 1985 and 1989, 2461 second-trimester genetic amniocenteses were evaluated at the cytogenetics section of the Children's Hospital Medical Center of Akron. All were cultured for the genital mycoplasmas: Mycoplasma hominis and Ureaplasma urealyticum. A total of nine patients were positive, all for Ureaplasma urealyticum, with one patient excluded because of subsequent therapeutic abortion. In addition, complete follow-up data, such as indication for amniocentesis, serum alpha-fetoprotein levels, gestational age at parturition, and out- come of pregnancy, were available on 86 Ureaplasma-negative (U –) patients during an approximate 2-year span within the time-frame of the study. This was in part due to physician response to a questionnaire sent after amniocentesis. Of the eight positive cultures, 100 per cent were associated with an adverse outcome, defined as fetal loss or premature delivery. This was significant compared with the U–group (p<0.001) with a more than eight times greater risk of adverse outcome. Six (75 per cent) resulted in spontaneous miscarriage within 4 weeks of amniocentesis and at less than 21 weeks' gestation. Two (25 per cent) delivered prematurely, with one (12.5 per cent) neonatal death at 24+ weeks. Histological examination of all eight placentae and the seven fetuses revealed a 100 per cent incidence of chorioamnionitis and pneumonia, respectively. In addition, in four of the five cases (80 per cent), cultures were positive for Ureaplasma urealyticum in pure culture from either placenta, fetal lung, or both tissues. The remaining case (20 per cent) was negative for aerobes, anaerobes, and mycoplasmas. The study demonstrates a significant association and supports a causal relationship between isolation of Ureaplasma from mid-trimester amniotic fluid with fetal wastage and premature birth.     

Degradation and mineralization of 2-chloro-, 3-chloro- and 4-chlorobiphenyl by a newly characterized natural bacterial strain isolated from an electrical transformer fluid-contaminated soil

A bacterium classified as Achromobacter xylosoxidans strain IR08 by phenotypic typing coupled with 16S rRNA gene analysis was isolated from a soil contaminated with electrical transformer ?uid for over sixty years using Aroclor 1221 as an enrichment substrate. The substrate utilization profiles revealed that IR08 could grow on all three monochlorobiphenyls (CBs), 2,4'- and 4,4'-dichlorobiphenyl as well as 2-chlorobenzoate (2-CBA), 3-CBA, 4-CBA, and 2,3-dichlorobenzoate. Unusually, growth was poorly sustaine...     

Geographic distribution and environmental characterization of livestock production systems in Eastern Africa

The central role played by livestock in the livelihoods of rural households in the developing world is seldom fully appreciated by policy makers, development agencies and donors. Knowledge gaps in the geographic distribution and environmental determinants of farming systems, especially if viewed through the livestock lens, compound this problem. We have produced a map of pastoral, agro-pastoral and mixed farming systems across Eastern Africa, by analysing datasets collected in the framework of livelihood analysis. Input data were gathered between 2000 and 2007 by various emergency and development agencies for Djibouti, Eritrea, Kenya, Somalia, Uganda and parts of Ethiopia and Sudan. A quantitative definition of the production systems is adopted, based on the ratio of livestock- to crop-derived income. The resulting livelihood-based map of livestock production systems was compared through correspondence analysis to an alternative livestock production systems map, produced independently from environmental data. Convergence between the two mapping approaches was evident. The geographic distribution of the livestock production systems was also modelled using multivariate analysis of remotely sensed and other geospatial datasets. Models show high statistical accuracy, and were thus used to fill the gaps in the observed distribution of livestock production systems. Finally, selected environmental factors underpinning the systems (agro-climatology, human and livestock populations and land cover) were analysed in detail, enabling the livestock production systems to be characterized in terms of them. The regional scope of the map, as well as its direct link with a vast amount of livelihood information, render it a valuable tool for a range of development and research applications, including those related to global change.