Profiles of ethnic-racial socialization from family,school, neighborhood,and the Internet: Relations to adolescent outcomes

Given that ecological models of development highlight the interacting influences of multiple environments, further research is needed that explores ethnic-racial socialization from multiple contexts. The current study explores how families, schools, neighborhoods, and the Internet jointly impact academic outcomes, critical consciousness, and psychological well-being in adolescents, both through socialization messages and experiences with racial discrimination. The research questions were: (a) What profiles of multiple contexts of socialization exist? and (b) How are the different profiles associated with academic outcomes, critical consciousness, and psychological well-being? The sample consisted of 1,084 U.S. adolescents aged 13–17 (M = 14.99, SD = 1.37; 49% girls) from four ethnic-racial groups: 25.6% Asian American, 26.3% Black/African American, 25.3% Latinx, and 22.9% White. The participants completed online surveys of socialization and discrimination from four contexts and three types of outcomes: academic outcomes, critical consciousness, and well-being. A latent profile analysis revealed three profiles: Average, High Discrimination, and Positive School. The Positive School class had the most positive academic outcomes and well-being. The High Discrimination class reported the highest critical consciousness. Their academic outcomes and well-being were similar to the Average group. The findings support complexity in perceptions of socialization from different contexts and the associations of socialization with youth outcomes.     

Variations in Athlete Heat-Loss Potential Between Hot-Dry and Warm-Humid Environments at Equivalent Wet-Bulb Globe Temperature Thresholds

ContextMany organizations associated with sports medicine recommend using wet-bulb globe temperature (WBGT)-based activity-modification guidelines that are uniform across the country. However, no consideration has been given to whether the WBGT thresholds are appropriate for different weather conditions, such as warm-humid (WH) relative to hot-dry (HD), based on known differences in physiological responses to these environments.ObjectiveTo identify if personnel in regions with drier conditions and greater evaporative cooling potential should consider using WBGT-based activity-modification thresholds that differ from those in more humid weather.DesignObservational study.SettingWeather stations across the contiguous United States.Main Outcome Measure(s)A 15-year hourly WBGT dataset from 217 weather stations across the contiguous United States was used to identify particular combinations of globe temperature, wet-bulb temperature, and air temperature that produce WBGTs of 27.9°C, 30.1°C, and 32.3°C. A total of 71 302 observations were clustered into HD and WH environmental conditions. From these clusters, maximum heat-loss potential and heat-flux values were modeled at equivalent WBGT thresholds with various activity levels, clothing, and equipment configurations.ResultsWe identified strong geographic patterns, with HD conditions predominant in the western half and WH conditions predominant in the eastern half of the country. Heat loss was systematically greater in HD than in WH conditions, indicating an overall less stressful environment, even at equivalent WBGT values. At a WBGT of 32.3°C, this difference was 11 W·m⁻² at an activity velocity of 0.3 m·s⁻¹, which doubled for an activity velocity of 0.7 m·s⁻¹. The HD and WH difference increased with the WBGT value, demonstrating that evaporative cooling differences between HD and WH conditions were even greater at a higher, rather than lower, WBGT.ConclusionsPotential heat loss was consistently greater in HD than in WH environments despite equal WBGTs. These findings support the need for further clinical studies to determine the appropriate WBGT thresholds based on environmental and physiological limits to maximize safety while avoiding unnecessary limitations.     

Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change.The gradual rise in greenhouse gas concentrations is projected to drive a mostly smooth increase in global temperature (1). However, the Earth system is suspected to have a range of “tipping elements” with the characteristic that their gradual change will be punctuated by critical transitions on regional scales (2, 3). That is, for relatively small changes in atmospheric concentrations of greenhouse gases, parts of the Earth system exhibit major changes. The recent fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) presents a catalog of possible abrupt or irreversible changes (table 12.4 in ref. 4). This catalog builds on a previous literature review (2) of components believed to have the potential for an acceleration of change as fossil fuel burning changes atmospheric composition and thus radiative forcing.The expert elicitation (2) motivated discussion of a multitude of environmental threats to the planet in which it was critically argued that atmospheric carbon dioxide concentration should not cross 350 ppm (5), trying to determine what constitutes safe levels of global warming. This threshold was suggested in ref. 5 to minimize the risk due to massive sea ice change, sea level rise, or major changes to terrestrial ecosystems and crops. An alternative purely temperature-based threshold is that from the Copenhagen accord, setting an upper limit of 2° (6). However, major uncertainty exists in knowledge of climate sensitivity (7), which makes it difficult to relate this warming level to a precise CO₂ concentration. However, despite this and the growing interest in the societal effects of such transitions, there has been no systematic study of the potential for abrupt shifts in state-of-the-art Earth System Models.To explore what may be deduced from the current generation of climate models in this context, we analyze the simulations produced by Coupled Model Intercomparison Project 5 (CMIP5) (8) that were used to inform the IPCC. CMIP5 provides a compilation of coordinated climate model experiments. Each of 37 analyzed models includes representations of the oceans, atmosphere, land surface, and cryosphere. The climate models have been forced with future changes in atmospheric gas concentrations, depicted in four Representative Concentration Pathways (RCPs) (9), starting in year 2006. Of these, we analyze RCP2.6, RCP4.5, and RCP8.5 to explore a range of changes in radiative forcing, reaching levels of 2.6 W⋅m⁻², 4.5 W⋅m⁻², and 8.5 W⋅m⁻², respectively, by year 2100 (including all available simulations that go beyond 2100). We also analyze historical simulations, capturing changes from preindustrial conditions in year 1850 to the present, and preindustrial control simulations.To assess future risks of abrupt, potentially irreversible, changes in important climate phenomena, we first need to define what we mean by “abrupt.” This term clearly refers to time scale and is usually defined as when changes observed are faster than the time scale of the external forcing. Here we choose a methodology consisting of three stages. Firstly, we systematically screen the CMIP5 multimodel ensemble of simulations for evidence of abrupt changes using search criteria (Methods) to make a first filtering of regions of potentially relevant abrupt events from this dataset (stage 1). These criteria are motivated by the definition of the assessment report, AR5 (4): “A large-scale change in the climate system that takes place over a few decades or less, persists (or is anticipated to persist) for at least a few decades, and causes substantial disruptions in human and natural systems.” Other definitions have emphasized the timescales of the change, e.g., 30 y (10), and rapidity in comparison with the forcing (11), which also meet our search criteria. Global maps of quantities with potential to change abruptly are expressed as (i) the mean difference between end and beginning of a simulation, (ii) the SD of the detrended time series, and (iii) the maximum absolute change within 10 y. These maps are made for all scenario runs and compared with values for the preindustrial control runs. When at least two indicators suggest locations of major change, we construct time series for area averages of at least 0.5 × 10⁶ km² (roughly 10 by 10 degrees) and visually inspect these for abrupt shifts standing out from the internal variability (stage 2). Subsequently, we check whether the selected cases can indeed be considered examples of abrupt change applying formal classification criteria (Methods) such as the criterion that the change should be larger than 4 times the SD of the preindustrial simulation, in combination with additional statistical tests (stage 3).We find a broad range of transitions passing our classification criteria (Fig. 1, SI Appendix, Table S1), which can be grouped into four categories (Fig. 2). They include abrupt shifts in sea ice and ocean circulation patterns as well as abrupt shifts in vegetation and the terrestrial cryosphere. Fig. 2 shows a selected example for each category. All other time series are displayed in Fig. 3. Information on the regions where the shifts occur and the results of the statistical tests used for classification are displayed in SI Appendix, Tables S2 and S3, respectively. A list of the climate models and their acronyms is provided in SI Appendix, Table S1.Open in a separate windowFig. 1.Geographical location of the abrupt climate change occurrences. All 30 model cases listed in

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.Amazonia consists of 815 million ha of rainforest, transitional forest, and tropical savannahs; stores approximately half of tropical forest carbon (1); and plays a vital role in global water, energy, and carbon cycling (2). Although uncertainties in climate predictions for the region remain large (3), recent analyses imply that significant portions of the basin will experience both longer and more intense dry seasons by the end of the 21st century (3–6). There is particular concern about southern Amazonian forests that experience longer dry seasons than forests in central and western Amazonia (3) and where a trend of increasing dry season length (DSL) and intensity has already been observed (7). Despite the importance of this region for regional and global climate, the climate sensitivity of the Amazon forests remains uncertain: model predictions range from a large-scale die-back of the Amazon (8, 9) to predictions that the biome will remain largely intact, and may even increase in biomass (10–12). Although some of these differences can be attributed to differences in the predicted future climate forcing of the region (13, 14), accurate predictions of how changes in climate will affect Amazonian forests also rely on an accurate characterization of how the ecosystem is affected by a given change in climate forcing. In this study, we examine the climate sensitivity of the Amazon ecosystem, focusing on the mechanisms underpinning changes in forest dynamics and their implications for the timing and nature of basin-wide shifts in biomass in response to a drying climate.Variation in forest biomass across the Amazon basin (15–17) has been shown to correlate with DSL (16–18) (Fig. 1), soil texture (16), shifts in stem turnover rate (19), and forest composition (20). In general, high-biomass moist tropical forests occur where DSL, defined here as the number of months in which precipitation is <100 mm (6, 9), is short, and low-biomass, savannah-like ecosystems are primarily found when DSLs are long (Fig. 1A). In addition, a significant relationship is observed between regional-scale spatial heterogeneity in above-ground biomass (AGB > 2 kg of carbon per square meter) and DSL, with drier places having greater spatial heterogeneity: This pattern is seen both at the scale of 1° (Fig. 1C; r² = 0.88, P < 0.01 for remote sensing-based AGB estimates) and at smaller spatial scales (SI Appendix, section S1). In other words, in moist areas, where DSL is short, forests have relatively homogeneous levels of AGB, whereas in drier areas, forests are increasingly heterogeneous. As we show below, this observed heterogeneity in response to increasing DSL has important implications for how the structure, composition, and dynamics of Amazon forests will be affected by changes in climate.Open in a separate windowFig. 1.(A) Change in AGB with DSL for remote sensing-based estimates (black and gray circles), ground-based plot measurements (blue triangles), ED2 model output (green circles), and ED2-BL model output (purple circles). (B) Distribution of AGB in the observations and the two models. (C) Change in the percentage of biomass variability, with the coefficient of variation (CV) defined as 1σ/mean. Results are for undisturbed primary vegetation forests. Data are from Baccini et al. (1), Saatchi et al. (48), and Baker et al. (20, 49).The Ecosystem Demography Biosphere (ED2) model, a process-based terrestrial biosphere model that represents individual plant-level dynamics, including competition for light and water (21, 22), was used to investigate the impact of ecosystem heterogeneity on the Amazon forest’s ecological resilience to climate perturbations (SI Appendix, section S3). Here, the term “ecological resilience” is used to describe the ability of a forest to maintain fundamental characteristics, such as carbon pools, composition, and structure, despite changes in climate (23). ED2 model simulations for the Amazon region, forced with a regional climate dataset derived from in situ measurements and remote-sensing observations, correctly reproduce the observed pattern of AGB variability as a function of DSL and soil texture (Fig. 1 and SI Appendix, section S4). In addition, ED2 model simulations for sites with detailed ground-based soil texture, forest structure, turnover, and composition measurements are also consistent with the observed patterns of variation in these quantities (SI Appendix, section S4).An ensemble of model simulations with varying soil texture was used to investigate the mechanisms that underpin the observed variable response to increasing DSL (SI Appendix, section S3). In the model, individual plant productivity is modified by a measure of plant water stress (γ_WS) that integrates soil texture, precipitation, and plant transpiration demand such that, as γ_WS increases, the plants close their stomata to reduce water loss. In the ED2 ensemble simulations, plot biomass is highly correlated with the average γ_WS for the forested sites (defined here as AGB > 3 kg of carbon per square meter) (Fig. 2C; r² = 0.96–0.99, P < 0.01; SI Appendix, section S5). Associated with changes in AGB that occur as water stress increases are correlated changes in the productivity and composition of the plant canopy (SI Appendix, section S6).Open in a separate windowFig. 2.Impact of changes in soil clay fraction (A and B) and plant water stress (C and D) on AGB in the ED2 (A and C) and ED2-BL (B and D) model simulations. Four climatological conditions are shown, a 2-month dry season, a 4-month dry season, a 6-month dry season, and an 8-month dry season.The important role that water stress operating at the scale of individual plants plays in generating these responses is illustrated by comparing the native ED2 model predictions with output from a horizontally and vertically averaged version of the model (ED2-BL), analogous to a conventional “big leaf” terrestrial biosphere model that represents the canopy in an aggregated manner (SI Appendix, section S3). In the ED2-BL simulations, there is no significant relationship between the spatial heterogeneity of forested sites and DSL (Fig. 1 A and C; r² = 0.24, P = 0.32). The absence of individual-level plant dynamics in the ED2-BL model results in a markedly different response to variations in soil texture and DSL than the native model formulation: Biomass initially declines as a function of increasing water stress, but a tipping point is then reached, beyond which the high-biomass forest is no longer stable and is replaced by a low-biomass savannah (Fig. 2). The result is a bimodal distribution of AGB across the basin in the ED2-BL model simulations, in contrast to the continuous distribution seen in the native model formulation and the observations (Fig. 1B). This response mirrors the response seen in other big-leaf-type ecosystem models (9). In native ED2 simulations, when water stress is prevented from influencing plant productivity, DSL and soil texture no longer have an impact on AGB (SI Appendix, section S5 and Fig. S5). Taken together, these simulations indicate that the driving mechanism behind the observed heterogeneous response to changes in DSL is the differential performance of individuals within the canopy to declining water availability, and how this response is modulated by soils with different hydrological properties. Specifically, the size and age structure of the ED2 plant canopy results in individuals’ differential access to both light and soil water, influencing the dynamics of individual plant growth and mortality (SI Appendix, section S6). Due to the nonlinear nature of functions governing plant growth, mortality, and recruitment, this heterogeneity results in a more continuous, graded response to changes in water stress than the big leaf (ED2-BL) formulation (Fig. 2). The consequence of this heterogeneity in plant-level responses to changes in soil moisture is that soil texture is likely to become increasingly important for controlling AGB as DSL increases. Soil fertility gradients also influence Amazonian AGB (16–18); however, as we show in SI Appendix, section S2, they do not account for the observed regional-scale pattern of increasing biomass heterogeneity with increasing DSL.The ED2 biosphere model was used to investigate the expected patterns and time scales of Amazonian ecosystem response to a 1- to 4-month change in DSL over the 21st century (6). Earlier analyses have suggested that by accurately representing the dynamics of individual trees, models such as ED2 that incorporate plant-level dynamics are likely to provide more realistic estimates of forest successional change (21). Forests with a 4-month dry season (24% of the Amazon basin) are projected to lose ∼20% of their biomass with a 2-month increase in DSL (range of 11–58% loss of AGB dependent on clay content), whereas drier forests (6-month DSL) respond more rapidly to changes in climate, losing ∼29% (20–37% loss dependent on clay content) of their biomass with a 1-mo increase in DSL (Fig. 3A and SI Appendix, section S7). As the forests adjust to the new climate regime, the spatial heterogeneity of forest structure, composition, and biomass across the range of soil textures gradually increase. As seen in Fig. 3B, the model predicts that forests in soils with low clay content will be relatively unaffected by the change in climate regime; however, in soils with high clay content, the increase in levels of water stress caused by the onset of a longer dry season will result in marked changes in forest AGB and composition, beginning approximately 3 years after the perturbation (Fig. 3C). The time scale of the predicted initial ecosystem response is consistent with the results from two field-based through-fall exclusion experiments, which showed declining biomass 3–4 years after a drought was introduced (24, 25). Underlying these predicted changes in AGB and canopy composition are reductions in plant growth and increases in mortality rates (SI Appendix, Figs. S14 and S15). Whereas the majority of the change in AGB occurs in the first 100 y, the composition and structure of the forest continue to reorganize for more than 200 years after the perturbation (Fig. 3C). Specifically, the simulations predict a substantial decline in the abundance of late-successional trees in soils with high clay content. This prediction arises as a consequence of the slower rate of growth of late-successional trees that makes them more vulnerable to water stress-induced increases in mortality rates and less competitive against mid-successional species that are favored by drought-induced increases in understory light levels. This prediction of increased vulnerability of late-successional trees to increases in water stress is as yet untested; however, more generally, our analysis highlights how shifts in climate forcing are likely to drive significant shifts in tropical forest composition and structure over decadal and centennial time scales.Open in a separate windowFig. 3.Predicted response of forest AGB and composition to an increase in DSL. (A) Change in AGB after 100 y as a result of increasing DSL for forests with historic DSLs of 2, 4, and 6 months for the range of soil textures simulated in the ensemble model simulations (n = 30). The magnitude of the change in AGB is influenced by soil clay fraction: The mean (solid line), 1σ deviation (shaded region), and minimum and maximum values (dashed lines) are shown. (B and C) Bar plots illustrating the impact of a 2-month increase in dry season (from 4 to 6 months) on a forest situated on a low clay content soil and a forest situated on a high clay content soil. The color of the bars indicates the contribution of mid- and late-successional trees, illustrating the shift in composition caused by the increase in DSL.Recent work has hypothesized that two stable ecosystem states may exist along the boundaries of tropical forests and that a tipping point may occur once a climatological moisture threshold is passed (26, 27). Instead, by combining field observations, remote-sensing estimates, and a terrestrial biosphere model, we find no evidence that an irreversible rapid transition or dieback of Amazon forests will occur in response to a drying climate (8, 9) or that forests will be unresponsive (11, 12). Rather, our results suggest that, at least in the case of Amazonian forests, the ecosystem will exhibit an immediate but heterogeneous response to changes in its climate forcing and that a continuum of transitional forest ecosystem states exists. These conclusions are consistent with experimental observations across Amazonia of short-term drought impacts (28). Furthermore, we find that future climate-induced shifts between a moist tropical forest and a dry forest will be a more graded transition accompanied by increasing spatial heterogeneity in forest AGB, composition, and dynamics across gradients in soil texture. The ability of Amazonian forests to undergo reorganization of their structure and composition in response to climate-induced changes in levels of plant water stress acts as an important buffer against more drastic threshold changes in vegetation state that would otherwise occur; however, it also means that the forests are more sensitive to smaller magnitude changes in their climate forcing than previous studies have suggested.The analysis conducted here intentionally focused on the direct impacts of changes in climate forcing on vegetation, and did not incorporate the effects of soil nutrients, climate-driven changes in fire frequency, the effects of increasing atmospheric CO₂ concentrations, the impacts of land transformation, and biosphere/atmosphere feedbacks. With regard to soil nutrients, at the basin scale, analyses indicate that forest composition, structure, biomass, and dynamics also vary across a gradient in soil fertility (16, 17), with the younger, more fertile soils of western Amazonia supporting forests with lower AGB and higher rates of biomass productivity and stem turnover relative to the forests of the central Amazon and Guianan Shield, which are located on older, more nutrient-poor soils. Meanwhile, landscape-scale studies in central (29) and northwestern (30) Amazonia have found that more fertile clay soils have higher AGB than nutrient-poor sandy soils. Further discussion of the impact of soil nutrients can be found in SI Appendix, section S2).Plant water availability is affected by both the hydraulic properties of soils and plant hydraulic architecture. Our findings of the importance of individual plant water stress on forest response to changes in climate highlight the need for additional studies into these two important, but relatively understudied, properties of tropical forests. With regard to soil hydraulic properties, recent studies suggest that the relationship between a soil’s texture and its hydraulic properties may differ significantly between tropical and temperate soils (31, 32). However, the impact of these differences on plant water availability remains uncertain. With regard to plant hydraulic architecture, although some measurements exist on rooting properties and vascular architecture of tropical trees (33–36), the above- and below-ground hydraulic attributes of tropical trees remain poorly characterized, especially compared with the hydraulic attributes of their temperate counterparts.In some areas, particularly those areas with long dry seasons, increasing water stress is likely to be accompanied by increases in fire frequency, which may act to generate more rapid transitions from a higher biomass forested state to a more savannah-like biome (26, 27). Because these two mechanisms have distinct impacts on forest composition, structure, and function, both must be considered when predicting future responses to changes in climate. The potential impacts of fire on patterns of ecosystem change are discussed in SI Appendix, section S1. Recent modeling studies indicate that CO₂ fertilization may mitigate the impact of increasing water stress (37); however, experimental studies are needed to quantify the impact of elevated CO₂ concentrations better on the physiological functioning of Amazon trees.Although regional patterns of Amazonian AGB are complex, reflecting the impact of multiple factors, our results suggest that plant-level responses to soil texture heterogeneity and changes in DSL are important in explaining the observed basin-wide pattern of variation in Amazonian AGB, providing a mechanistic explanation for the observed correlations between DSL, AGB, and changes in stand structure and composition (16, 17). These conclusions may also apply to African and Asian tropical forests; however, important differences exist in the future climate predictions for these regions (38) and their soil edaphic and nutrient characteristics and historical fire regimes (39–41).The response of forests to changes in their climate forcing is an emergent ecosystem-level response that is ultimately driven by individual trees responding to changes in their local environments. Nonlinearities in the performance of individual plants, such as their rates of photosynthetic assimilation and mortality, as environmental conditions change imply that terrestrial biosphere models need to represent these differential responses of individuals to capture emergent ecosystem properties accurately (42). This analysis demonstrates that the conventional approach of modeling average plants in average environments within climatological grid cells underestimates the direct, near-term response of tropical forests to climatological change but overestimates the direct impacts of larger scale changes in forcing. Consequently, accurate predictions for the timing and nature of forest responses to changes in climate require consideration of how climate and soils affect the performance of individuals within plant canopies. As we have shown here, models that incorporate plant-level dynamics are able to characterize observed extant patterns of variation in the structure, composition, and dynamics of Amazonian ecosystems more accurately, and accounting for these patterns has important implications for the sensitivity and ecological resilience of Amazon forests to different levels of climatological perturbation.     

Exposure to ambient black carbon derived from a unique inventory and high-resolution model

Black carbon (BC) is increasingly recognized as a significant air pollutant with harmful effects on human health, either in its own right or as a carrier of other chemicals. The adverse impact is of particular concern in those developing regions with high emissions and a growing population density. The results of recent studies indicate that BC emissions could be underestimated by a factor of 2–3 and this is particularly true for the hot-spot Asian region. Here we present a unique inventory at 10-km resolution based on a recently published global fuel consumption data product and updated emission factor measurements. The unique inventory is coupled to an Asia-nested (∼50 km) atmospheric model and used to calculate the global population exposure to BC with fully quantified uncertainty. Evaluating the modeled surface BC concentrations against observations reveals great improvement. The bias is reduced from −88% to −35% in Asia when the unique inventory and higher-resolution model replace a previous inventory combined with a coarse-resolution model. The bias can be further reduced to −12% by downscaling to 10 km using emission as a proxy. Our estimated global population-weighted BC exposure concentration constrained by observations is 2.14 μg⋅m⁻³; 130% higher than that obtained using less detailed inventories and low-resolution models.Black carbon (BC), or soot, emitted from incomplete combustion of carbonaceous fuels is an air pollutant which also plays an important role in climate change (1). BC is an indicator of air particulate pollution and BC in ambient air has an impact on human health (2). In a recent study in China, it was found that the effects of BC on morbidity appear to be more robust than the effects of fine particles in general (3, 4).However, global atmospheric aerosol models often underestimate the concentration of BC at the surface, particularly over Asia, by a factor that typically ranges from 2 to 10 (5–7). In one study, the observed BC surface concentration for China could only be reproduced by doubling the emissions prescribed to a transport model (8). It is often argued that the underestimation is due to a low bias in BC emission inventories, suggesting a need to revisit these previous inventories (9).In a bottom-up approach, BC emission is estimated based on the amount of fuel consumed and an emission factor (EF_BC, defined as the amount of BC emitted per unit mass of fuel consumed) for each of various combustion sources. For previous inventories, the lack of EF_BC measurements in developing countries led to high uncertainty in estimating the total emissions (10). In addition, the use of fuel data at the national level is likely to distort the geographical distribution of emissions within large countries such as China and India (11). Recently, a 0.1° × 0.1° fuel database with 64 types of combustion has been developed based on local or national fuel consumption statistics. This database improves the resolution of the spatial distribution of emissions for large countries (12). To fill the data gap in developing countries, a set of EF_BC values has been compiled for various residential solid fuel combustion devices and vehicles (13–20). In addition to the problems with the emission inventories, the coarse resolution of existing global aerosol models also hinders our ability to capture detailed spatial variation, leading to poor agreement between model prediction and observations (7).In this study we develop and evaluate a unique global BC emission inventory using a zoomed aerosol model, and estimate the global population’s exposure to BC with a focus on Asia. The influence of model resolution and the use of an updated emission inventory on the calculated BC concentration are evaluated against field observations.     

Increasing aridity reduces soil microbial diversity and abundance in global drylands

Soil bacteria and fungi play key roles in the functioning of terrestrial ecosystems, yet our understanding of their responses to climate change lags significantly behind that of other organisms. This gap in our understanding is particularly true for drylands, which occupy ∼41% of Earth´s surface, because no global, systematic assessments of the joint diversity of soil bacteria and fungi have been conducted in these environments to date. Here we present results from a study conducted across 80 dryland sites from all continents, except Antarctica, to assess how changes in aridity affect the composition, abundance, and diversity of soil bacteria and fungi. The diversity and abundance of soil bacteria and fungi was reduced as aridity increased. These results were largely driven by the negative impacts of aridity on soil organic carbon content, which positively affected the abundance and diversity of both bacteria and fungi. Aridity promoted shifts in the composition of soil bacteria, with increases in the relative abundance of Chloroflexi and α-Proteobacteria and decreases in Acidobacteria and Verrucomicrobia. Contrary to what has been reported by previous continental and global-scale studies, soil pH was not a major driver of bacterial diversity, and fungal communities were dominated by Ascomycota. Our results fill a critical gap in our understanding of soil microbial communities in terrestrial ecosystems. They suggest that changes in aridity, such as those predicted by climate-change models, may reduce microbial abundance and diversity, a response that will likely impact the provision of key ecosystem services by global drylands.Climate change is a major driver of biodiversity loss from local to global scales, in both terrestrial and aquatic ecosystems (1, 2). Given the dependence of crucial ecosystem processes and services on biodiversity (3–5), climate-change-driven biodiversity losses will dramatically alter the functioning of natural ecosystems (4, 6). Key ecosystem processes—such as nutrient cycling, carbon (C) sequestration, and organic matter decomposition—depend on soil bacteria and fungi (7–9). However, we have limited knowledge of the role of climatic factors as drivers of their abundance and diversity at regional and global scales (10–12). This gap in our understanding is particularly true for drylands, areas with an aridity index (precipitation/potential evapotranspiration ratio) below 0.65 (13), which are among the most sensitive ecosystems to climate change (14). Drylands are expected to expand in global area by 11–23% by 2100 (15), experiencing increased aridity and reduced soil moisture (16). Land degradation and desertification already affect ∼250 million people in the developing world (17). Altered climate and the growth of human populations will almost inevitably exacerbate these problems in drylands (14, 17). Because the provisioning of ecosystem services essential for human development (e.g., soil fertility, food, and biomass production) heavily relies on the abundance, composition, and diversity of soil fungi and bacteria (18, 19), it is crucial to understand how changes in aridity affect soil microbial communities. Drylands, however, are poorly represented in global soil bacteria and fungi databases (10–12, 20), and no field study has simultaneously examined how the abundance, composition, and diversity of these organisms vary along aridity gradients in drylands worldwide.Here, we present a global field study conducted across 80 dryland sites from all continents, except Antarctica (Fig. S1), to assess how changes in aridity, as defined by the aridity index, affect the total abundance and diversity of soil bacteria and fungi and the relative abundance of major bacterial and fungal taxa. The studied ecosystems encompass a wide variety of the climatic, edaphic, and vegetation conditions found in drylands worldwide (Materials and Methods). We predict that increases in aridity should reduce the abundance and diversity of soil bacteria and fungi due to the negative relationships typically found between aridity and the availability of resources such as water and C (21), which largely drive soil microbial abundance and activity in drylands (22–24). To test this hypothesis, we characterized bacterial and fungal communities in the soil surface (top 7.5 cm) along natural aridity gradients by using Illumina Miseq profiling of ribosomal genes and internal transcribed spacer (ITS) markers, quantified bacterial and fungal abundances with quantitative PCR (qPCR), and gathered information on multiple biotic and abiotic factors known to influence soil microbes (Fig. S2).Open in a separate windowFig. S1.Location of the 80 sites used in this study. Some of them overlap and are thus indistinguishable. Exact locations and additional site characteristics are provided in figshare (DOI 10.6084/m9.figshare.1487693).Open in a separate windowFig. S2.A priori SEM used in this study. Spatial is a composite variable formed by latitude and longitude. MDR, mean diurnal temperature range (mean of monthly differences between maximum and minimum temperature). The numbers in the arrows denote example references used to support our predictions, which can be found in the reference list.     

Assessment of Climate-sensitive Infectious Diseases in the Federated States of Micronesia

Background: The health impacts of climate change are an issue of growing concern in the Pacific region. Prior to 2010, no formal, structured, evidence-based approach had been used to identify the most significant health risks posed by climate change in Pacific island countries. During 2010 and 2011, the World Health Organization supported the Federated States of Micronesia (FSM) in performing a climate change and health vulnerability and adaptation assessment. This paper summarizes the priority climate-sensitive health risks in FSM, with a focus on diarrheal disease, its link with climatic variables and the implications of climate change. Methods: The vulnerability and adaptation assessment process included a review of the literature, extensive stakeholder consultations, ranking of climate-sensitive health risks, and analysis of the available long-term data on climate and climate-sensitive infectious diseases in FSM, which involved examination of health information data from the four state hospitals in FSM between 2000 and 2010; along with each state’s rainfall, temperature and El Niño-Southern Oscillation data. Generalized linear Poisson regression models were used to demonstrate associations between monthly climate variables and cases of climate-sensitive diseases at differing temporal lags. Results: Infectious diseases were among the highest priority climate-sensitive health risks identified in FSM, particularly diarrheal diseases, vector-borne diseases and leptospirosis. Correlation with climate data demonstrated significant associations between monthly maximum temperature and monthly outpatient cases of diarrheal disease in Pohnpei and Kosrae at a lag of one month and 0 to 3 months, respectively; no such associations were observed in Chuuk or Yap. Significant correlations between disease incidence and El Niño-Southern Oscillation cycles were demonstrated in Kosrae state. Conclusions: Analysis of the available data demonstrated significant associations between climate variables and climate-sensitive infectious diseases. This information should prove useful in implementing health system and community adaptation strategies to avoid the most serious impacts of climate change on health in FSM.     

疾病预防控制档案的长期趋势及影响因素分析

目的通过对绵阳疾控中心有史以来的全部归档文件从数量上的动态变动趋势及其影响因素的分析,预测今后一段时期疾控档案数量可能达到的规模,为疾控档案管理提供措施。方法应用动态数列理论对档案资料作动态变动趋势描述并作出预测;查阅相关历史文献、大众媒体公开资料探讨影响疾控档案动态走势因素。结果疾控档案在数量上随着时间的延续整体呈波浪上升态势,其定基发展速度为18.99倍,平均发展速度为1.25倍,平均增长速度是0.25倍,预计未来一段时间的2012-2014年归档文件数量平均每年将达到765.66件、2015-2017年将达956.96件;影响疾控档案归档文件数量动态变动趋势的因素有历史原因和档案本身原因。结论疾控档案资料的动态走势与疾控工作的工作量、档案工作的工作量呈正比,工作量越大存档文件越多;适时清理过期档案文件、档案资料在整理时准确归类是缓解储存空间压力的必要手段。     

国境口岸加强对裂谷热早期预警的措施探讨

目的 裂谷热是由蚊子传播的,以急性、高热为特征的病毒性人畜共患病,OIE将其列为A类传染病.目前我国尚未有感染裂谷热的报道,但是该病的全球扩散形势依然严峻.方法 对建立安全高效的动物卫生监测体系和裂谷热气候模型两种预警措施进行简单的综述.结果 裂谷热在动物发病情况优先于人体发病,因此建立动物卫生监测系统早期预警机制效果显著,同时利用裂谷热媒介生物条件特异性可以通过卫星遥感技术建立气候模型进行早期预警.结论 国境口岸加强对裂谷热的早期预警能够及时地监测疫病的发展趋势,对有关部门采取相应措施来防止疫病的入侵具有十分重要的意义.     

Relationship between climate conditions and nosocomial infection rates

Background

Nosocomial infections constitute a global health problem.

Objectives

To explore the relationship between nosocomial infection rates (NIRs) and climatic factors including temperature and relative humidity in Guangzhou area of China.

Methods

30892 patients in our hospital in 2009 were investigated for nosocomial infection status, and the contemporaneous temperature and relative humidity were analyzed statistically. NIRs increased with relative humidity and temperature in central ICU and geriatric department.

Results

No statistical differences were found between each quarter of 2009 in the distribution of nosocomial infection sites. There were no statistical differences in the pathogenic species of nosocomial infections between high-temperature and low-temperature months in different departments. NIRs had a correlation with temperature and relative humidity in geriatric department and central ICU.

Conclusions

To decrease NIRs and improve health care quality, it is necessary to strengthen the control of temperature and humidity especially for geriatric department and central ICU.