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The objective was to evaluate vaginal temperature as a thermoregulatory response of Nellore heifers under different microclimatic conditions. The study was conducted during one year in an experimental area located at 54°37′W, 20°27′S, and 530 m of altitude in Brazil. Twenty-four Nellore females were reared in integrated crop-livestock-forestry systems with different shading patterns. The randomized complete block experimental design was utilized with a sub subdivided plots scheme, with plot corresponding to the production systems, the subplot to the season of the year, and the sub subplot, the hours of the day. To characterize the microclimate, data regarding air and black globe temperatures, and air relative humidity were collected and from them, temperature-humidity index was calculated. Vaginal temperature was obtained by using a bottom-type temperature logger (i-button) attached to an adapted intravaginal device. The black-globe temperature explained the variation on vaginal temperature. Increases on vaginal temperature were only observed, on average, two hours after the increase of black-globe temperature. The microclimatic conditions found in the systems, resulting from the various tree densities, modify the vaginal temperature in different degrees, demonstrating that the shading effect is not always accompanied by improvements in thermal comfort. The system with intermediate density showed a better microclimatic condition and, consequently, a lower increase in vaginal temperature. The interaction between air temperature, humidity and solar radiation resulted in adverse environmental conditions, however, Nellore heifers showed good adaptation to the environment. In conclusion, vaginal temperature is a good indicator to evaluate the thermoregulatory response in Nellore heifers. [ABSTRACT FROM AUTHOR]

Background: Changes in climate and environmental conditions could be the driving factors for the transmission of hantavirus. Thus, a thorough collection and analysis of data related to the epidemic status of hemorrhagic fever with renal syndrome (HFRS) and the association between HFRS incidence and meteorological factors, such as air temperature, is necessary for the disease control and prevention. Methods: Journal articles and theses in both English and Chinese from Jan 2014 to Feb 2019 were identified from PubMed, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data and VIP Info. All identified studies were subject to the six criteria established to ensure the consistency with research objectives, (i) they provided the data of the incidence of HFRS in mainland China; (ii) they provided the type of air temperature indexes; (iii) they indicated the underlying geographical scale information, temporal data aggregation unit, and the data sources; (iv) they provided the statistical analysis method that had been used; (v) from peer-reviewed journals or dissertation; (vi) the time range for the inclusion of data exceeded two consecutive calendar years. Results: A total of 27 publications were included in the systematic review, among them, the correlation between HFRS activity and air temperature was explored in 12 provinces and autonomous regions and also at national level. The study period ranged from 3 years to 54 years with a median of 10 years, 62.3% of the studies were based on the monthly HFRS incidence data, 21 studies considered the lagged effect of air temperature factors on the HFRS activity and the longest lag period considered in the included studies was 34 weeks. The correlation between HFRS activity and air temperature varied widely, and the effect of temperature on the HFRS epidemic was seasonal. Conclusions: The present systematic review described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and the incidence of HFRS in mainland China during the period from January 2014 to February 2019. The appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period should be considered when exploring the relationship between HFRS incidence and meteorological factors such as air temperature. Further investigation is warranted to detect the thresholds of meteorological factors for the HFRS early warning purposes, to measure the duration of lagged effects and determine the timing of maximum effects for reducing the effects of meteorological factors on HFRS via continuous interventions and to identify the vulnerable populations for target protection. [ABSTRACT FROM AUTHOR]

Climate change is negatively affecting many species. The increase in mean air temperature is often associated with shifts in distribution, changes in phenology, and local extinctions. Other factors that only partially correlate with air temperature, like water shortage, may also contribute to the negative consequences of climate change. Although the effect of temperature on lizards’ ecophysiology is highly studied, many lizards are also at risks of increased water loss and dehydration, which are predicted to increase under climate change. Here we aimed for the first time to explore if lacertid lizards exposed to dehydration thermoregulate less precisely than hydrated lizards and if dehydrated lizards are less active, change the daily pattern of thermoregulation and balance water balance against thermoregulation. We exposed four lizard species with differences in the thermal preference to thermal gradients with or without a source of water. We measured preferred body temperatures, daily pattern of thermoregulation, and the use of space. Dehydration negatively affected thermoregulation in all investigated species. Dehydrated lizards reduced their preferred body temperature and showed a species-specific pattern of hourly change in thermal preference. Furthermore, they more frequently used the colder parts of the gradients and spent more time hidden. Lizards experiencing dehydration may suffer a reduction in survival and fitness because of poor thermoregulation. Similarly, they may spend more time hidden, waiting for more favourable weather conditions. Such inactivity may carry ecological costs especially in those regions that undergo either short or prolonged periods of droughts. [ABSTRACT FROM AUTHOR]

Understanding how increases in water temperature may affect winter dormancy period duration and overwinter survival are important for the effective conservation and management of estuarine species in the face of a warming climate. In this study, we determined the length of the overwintering period and the probability of overwinter survival of blue crab (Callinectes sapidus), an ecologically and economically important estuarine crustacean. Overwintering period length and probability of overwinter survival were determined using projected water temperatures up to the year 2100, derived from a harmonic model that utilized air temperatures from multi-model ensemble of regional-scale climate projections. Our estimates of warming water temperatures by 2100 in Chesapeake Bay indicate that winters will be up to 50% shorter and overwinter survival will increase by at least 20% compared to current conditions. The warmer conditions will lead to faster and prolonged seasonal growth, which, when combined with lower winter mortality, will lead to increased population productivity. The level of expression of this increased productivity will depend on the response of other elements of the Chesapeake Bay food web, as well as possible changes to fishery management policies over the same time period. [ABSTRACT FROM AUTHOR]

Air temperature data retrieved from global atmospheric models may show a systematic bias with respect to measurements from weather stations. This is a common concern in local climate studies. The current study presents two methods based upon copulas and Conditional Probability (CP) to predict bias-corrected mean air temperature in a data-scarce environment: CP-I offers a single conditional probability as a predictor, CP-II is a pixel-wise version of CP-I and offers spatially varying predictors. The methods were applied on daily air temperature in the Qazvin Plain, Iran that were collected at 24 weather stations and 150 ECMWF ERA-interim grid cells from a single month (June) over 11 years. We compared the methods with the commonly applied conditional expectation and conditional median methods. Leave-k-out cross-validation and correlation scores show that the new methods reduced the bias with 44–68% for the full data set and with 34–74% on a homogeneous subarea. We conclude that the two methods are able to locally improve ECMWF air temperatures in a data-scarce area. [ABSTRACT FROM AUTHOR]

Surface incoming shortwave (solar) radiation data are an important component of many scientific analyses, but direct measurements are not commonly available. Estimates can be obtained from gridded meteorological analysis or reanalysis systems, such as the Global Data Assimilation Systems (GDAS) and Modern Era Retrospective Reanalysis System (MERRA-2), or calculated using empirical models dependent on meteorological variables such as air temperature. The purpose of this analysis was to compare multiple methods for estimating daily shortwave radiation in a tropical highland environment in Ethiopia. Direct solar radiation outputs of GDAS and MERRA-2, topographically corrected outputs of the two analysis systems, and empirically estimated solar radiation values calculated with the systems’ air temperature data were compared to see which produced the most reliable radiation values. GDAS appeared to underestimate the seasonal variability, resulting in low correlation (R2) with in situ data and large mean bias error (MBE). In comparison, MERRA-2 did not underestimate variability, but produced larger bias than the empirical model estimates. There was an improvement in correlation and reduction in MBE when using the GDAS air temperature predictions in the empirical model, but the opposite was true for MERRA-2. The empirical model using station air temperature data (stationT) produced the highest correlation across all four stations, with best performance at the lower elevation sites. The direct shortwave radiation outputs of MERRA-2 produced comparable correlation values, with larger R2 at stations at higher elevation. Topography possibly influenced these results, as MERRA-2 performed comparably to stationT at the stations in moderate terrain, but not in steeper terrain. This work can serve as a starting point for analyses in other tropical highland regions, where continuous in situ solar radiation data are rarely available. [ABSTRACT FROM AUTHOR]

Climatological changes in the environments of key meteorological parameters that affect Significant Tornado Days (SigTorDs) have been determined for two active tornado regions defined as Box a and Box ß, centered, respectively, over Oklahoma and Alabama and their respective environs. The North American Regional Reanalysis data was selected for 1980-2013, providing two successive 17-year periods corresponding to the last 34 years of previous research findings that focused on the aforementioned regions. This data record also corresponds to an increasing surface air temperature trend for the continental United States. Period I (1980-1996) and Period II (1997-2013) defined the years of changing environments for the two regions studied. Environmental parameters investigated and compared to SigTorDs were surface-based convective available potential energy (CAPE), storm relative helicity (0-3 km), bulk wind difference (1,000 mb to 500 mb), and lifted condensation level (LCL). Environments have changed to fewer SigTorDs (130 to 74) in Box a from Period I to Period II, dominated by decreasing frequency of storm relative helicity and slightly increasing CAPE. Box ß is characterized by more SigTorDs (94 to 119) in Period II with an environment dominated by increasing frequency of storm relative helicity and minimal change in CAPE. These results support the importance of the changes in storm relative helicity (as opposed to CAPE) in explaining the eastward shift in U.S. tornado activity. [ABSTRACT FROM AUTHOR]

In this study, experiments are conducted to gauge the relative importance of model, initial condition, and driving climate uncertainty for simulations of malaria transmission at a highland plantation in Kericho, Kenya. A genetic algorithm calibrates each of these three factors within their assessed prior uncertainty in turn to see which allows the best fit to a timeseries of confirmed cases. It is shown that for high altitude locations close to the threshold for transmission, the spatial representativeness uncertainty for climate, in particular temperature, dominates the uncertainty due to model parameter settings. Initial condition uncertainty plays little role after the first two years, and is thus important in the early warning system context, but negligible for decadal and climate change investigations. Thus, while reducing uncertainty in the model parameters would improve the quality of the simulations, the uncertainty in the temperature driving data is critical. It is emphasized that this result is a function of the mean climate of the location itself, and it is shown that model uncertainty would be relatively more important at warmer, lower altitude locations. [ABSTRACT FROM AUTHOR]

Climate change has caused shifts in the phenology and distributions of many species but comparing responses across species is challenged by inconsistencies in the methodology and taxonomic and temporal scope of individual studies. Natural history collections offer a rich source of data for examining phenological shifts for a large number of species. We paired specimen records from Pacific Northwest insect collections to climate data to analyze the responses of 215 moth species to interannual climate variation over a period of 119 years (1895–2013) during which average annual temperatures have increased in the region. We quantified the effects of late winter/early spring temperatures, averaged annually across the region, on dates of occurrence of adults, taking into account the effects of elevation, latitude, and longitude. We assessed whether species-specific phenological responses varied with adult flight season and larval diet breadth. Collection dates were significantly earlier in warmer years for 36.3% of moth species, and later for 3.7%. Species exhibited an average phenological advance of 1.9 days/°C, but species-specific shifts ranged from an advance of 10.3 days/°C to a delay of 10.6 days/°C. More spring-flying species shifted their phenology than summer- or fall-flying species. These responses did not vary among groups defined by larval diet breadth. The highly variable phenological responses to climate change in Pacific Northwest moths agree with other studies on Lepidoptera and suggest that it will remain difficult to accurately forecast which species and ecological interactions are most likely to be affected by climate change. Our results also underscore the value of natural history collections as windows into long-term ecological trends. [ABSTRACT FROM AUTHOR]

Climate change projections show that temperature and precipitation increases can alter the exchange of greenhouse gases between the atmosphere and high latitude landscapes, including their freshwaters. Dissolved organic carbon (DOC) plays an important role in greenhouse gas emissions, but the impact of catchment productivity on DOC release to subarctic waters remains poorly known, especially at regional scales. We test the hypothesis that increased terrestrial productivity, as indicated by the normalized difference vegetation index (NDVI), generates higher stream DOC concentrations in the Stordalen catchment in subarctic Sweden. Furthermore, we aimed to determine the degree to which other generic catchment properties (elevation, slope) explain DOC concentration, and whether or not land cover variables representing the local vegetation type (e.g., mire, forest) need to be included to obtain adequate predictive models for DOC delivered into rivers. We show that the land cover type, especially the proportion of mire, played a dominant role in the catchment’s release of DOC, while NDVI, slope, and elevation were supporting predictor variables. The NDVI as a single predictor showed weak and inconsistent relationships to DOC concentrations in recipient waters, yet NDVI was a significant positive regulator of DOC in multiple regression models that included land cover variables. Our study illustrates that vegetation type exerts primary control in DOC regulation in Stordalen, while productivity (NDVI) is of secondary importance. Thus, predictive multiple linear regression models for DOC can be utilized combining these different types of explanatory variables. [ABSTRACT FROM AUTHOR]

Bangladesh is one of the world’s most vulnerable countries for climate change. This observational study examined the association of temperature, humidity and rainfall with six common climate-sensitive infectious diseases in adults (malaria, diarrheal disease, enteric fever, encephalitis, pneumonia and bacterial meningitis) in northeastern Bangladesh. Subjects admitted to the adult medicine ward of a tertiary referral hospital in Sylhet, Bangladesh from 2008 to 2012 with a diagnosis of one of the six chosen climate-sensitive infectious diseases were enrolled in the study. Climate-related data were collected from the Bangladesh Meteorological Institute. Disease incidence was then analyzed against mean temperature, humidity and average rainfall for the Sylhet region. Statistical significance was determined using Mann-Whitney test, Chi-square test and ANOVA testing. 5033 patients were enrolled (58% male, 42% female, ratio 1.3:1). All six diseases showed highly significant (p = 0.01) rises in incidence between the study years 2008 (540 cases) and 2012 (1330 cases), compared with no significant rise in overall all-cause hospital admissions in the same period (p = 0.19). The highest number of malaria (135), diarrhea (266) and pneumonia (371) cases occurred during the rainy season. On the other hand, the maximum number of enteric fever (408), encephalitis (183) and meningitis (151) cases occurred during autumn, which follows the rainy season. A positive (P = 0.01) correlation was observed between increased temperature and the incidence of malaria, enteric fever and diarrhea, and a negative correlation with encephalitis, meningitis and pneumonia. Higher humidity correlated (P = 0.01) with a higher number of cases of malaria and diarrhea, but inversely correlated with meningitis and encephalitis. Higher incidences of encephalitis and meningitis occurred while there was low rainfall. Incidences of diarrhea, malaria and enteric fever, increased with rainfall, and then gradually decreased. The findings support a relationship between weather patterns and disease incidence, and provide essential baseline data for future large prospective studies. [ABSTRACT FROM AUTHOR]

Understanding how climate change affects host-parasite systems and predicting the consequences for ecosystems, economies, and human health has emerged as an important task for science and society. Some basic insight into this complex problem can be gained by comparing the thermal physiology of interacting host and parasite species. In this study, we compared upper thermal tolerance among three component species in a natural host-parasitoid-hyperparasitoid system from Virginia, USA. To assess the ecological relevance of our results, we also examined a record of maximum daily air temperatures collected near the study site in the last 124 years. We found that the caterpillar host Manduca sexta had a critical thermal maximum (CTmax) about 4°C higher than the parasitic wasp, Cotesia congregata, and the hyperparasitic wasp, Conura sp., had a CTmax about 6°C higher than its host, C. congregata. We also found significant differences in CTmax among instars and between parasitized and non-parasitized M. sexta. The highest maximum daily air temperature recorded near the study in the last 124 years was 42°C, which equals the average CTmax of one species (C. congregata) but is several degrees lower than the average CTmax of the other two species (M. sexta, Conura sp.) in this study. Our results combined with other studies suggest that significant differences in thermal performance within and among interacting host and parasite species are common in nature and that climate change may be largely disruptive to these systems with responses that are highly variable and complex. [ABSTRACT FROM AUTHOR]

Understanding the spatial and temporal dynamics of species assemblages is a main challenge in ecology. The mechanisms that shape species assemblages and their temporal fluctuations along tropical elevational gradients are particularly poorly understood. Here, we examined the spatio-temporal dynamics of bird assemblages along an elevational gradient in Ecuador. We conducted bird point counts at three elevations (1000, 2000 and 3000 m) on 18 1-ha plots and repeated the sampling eight times over two years (216 hours in total). For each plot, we obtained data of monthly temperatures and precipitation and recorded the overall resource availability (i.e., the sum of flower, fruit, and invertebrate resources). As expected, bird richness decreased from low to high elevations. Moreover, we found a significant decrease in bird abundance and richness and an increase in evenness between the most and least humid season at each of the three elevations. Climatic factors were more closely related to these temporal fluctuations than local resource availability. While temperature had significant positive effects on the abundance of birds at mid and high elevations, precipitation negatively affected bird abundance at low and mid elevations. Our study highlights that bird assemblages along tropical elevational gradients can show pronounced seasonal fluctuations. In particular, low temperatures and high precipitation seem to impose important constraints on birds. We conclude that potential changes in climate, due to global warming, are likely to affect the spatio-temporal dynamics of bird assemblages along tropical elevational gradients. [ABSTRACT FROM AUTHOR]

Mitigating extreme heat in urban areas is beneficial and sometimes critical to human health. Thriving plant communities in community parks play an important role in mitigating extreme heat through providing cooling effect, while inevitably affecting how people perceive the benefits of using community parks for recreation. Thus, the impacts of plant communities on the thermal environment should be quantified to determine the optimal structure of the plant community. The goal would be to harmonize the functions of improving the thermal environment with the preferences people have related to the recreational benefits of plant communities with various levels of vegetation density. In this paper, the correlations between the structural characteristics of plant communities and their function in mitigating the thermal environment were investigated on calm summer days in Xincheng Central Park, Minhang District, Shanghai, China. In addition to analyzing the plant communities present and their effects on the park microclimate, a questionnaire was employed to determine the plant community preferences of recreational park users. The results showed that plant communities could reduce the air temperature by 1.23–2.42 °C and increase the relative humidity by 2.4–4.2% during the daytime. The microclimate conditions in plant communities with varying vegetation densities were significantly different. The canopy density and leaf area index primarily controlled the temperature reduction, while the canopy density and total canopy cover ratio primarily controlled the increase in humidity; meanwhile, these correlations varied at different times of the day. Moreover, most of the park users preferred a moderately dense plant community which met their environmental perceptions for recreation in parks. Age or education level variables of park users would also predict preferences for different plant community densities. Ultimately, one plant community pattern with appropriate canopy density (60%), leaf area index (≥3) and canopy cover ratio (total 0.80–1.20, with 0.6–0.75 for trees and 0.20–0.45 for shrubs/woodland area) was recommended, which would harmonize the functions of the mitigation of the thermal environment with most people’s perception of a desirable vegetation density. [ABSTRACT FROM AUTHOR]

The Earth′s climate is warming, especially in the mid- and high latitudes of the Northern Hemisphere. The northern elephant seal (Mirounga angustirostris) breeds and haul-outs on islands and the mainland of Baja California, Mexico, and California, U.S.A. At the beginning of the 21st century, numbers of elephant seals in California are increasing, but the status of Baja California populations is unknown, and some data suggest they may be decreasing. We hypothesize that the elephant seal population of Baja California is experiencing a decline because the animals are not migrating as far south due to warming sea and air temperatures. Here we assessed population trends of the Baja California population, and climate change in the region. The numbers of northern elephant seals in Baja California colonies have been decreasing since the 1990s, and both the surface waters off Baja California and the local air temperatures have warmed during the last three decades. We propose that declining population sizes may be attributable to decreased migration towards the southern portions of the range in response to the observed temperature increases. Further research is needed to confirm our hypothesis; however, if true, it would imply that elephant seal colonies of Baja California and California are not demographically isolated which would pose challenges to environmental and management policies between Mexico and the United States. [ABSTRACT FROM AUTHOR]

Although estimates of the annual methane (CH4) flux from agriculturally managed peatlands exist, knowledge of controls over the variation of CH4 at different time-scales is limited due to the lack of high temporal-resolution data. Here we present CH4 fluxes measured from May 2014 to April 2016 using the eddy covariance technique at an abandoned peatland pasture in western Newfoundland, Canada. The goals of the study were to identify the controls on the seasonal variations in CH4 flux and to quantify the annual CH4 flux. The seasonal variation in daily CH4 flux was not strong in the two study years, however a few periods of pronounced emissions occurred in the late growing season. The daily average CH4 flux was small relative to other studies, ranging from -4.1 to 9.9 nmol m-2 s-1 in 2014–15 and from -7.1 to 12.1 nmol m-2 s-1 in 2015–16. Stepwise multiple regression was used to investigate controls on CH4 flux and this analysis found shifting controls on CH4 flux at different periods of the growing season. During the early growing season CH4 flux was closely related to carbon dioxide fixation rates, suggesting substrate availability was the main control. The peak growing season CH4 flux was principally controlled by the CH4 oxidation in 2014, where the CH4 flux decreased and increased with soil temperature at 50 cm and soil water content at 10 cm, but a contrasting temperature-CH4 relation was found in 2015. The late growing season CH4 flux was found to be regulated by the variation in water table level and air temperature in 2014. The annual CH4 emission was near zero in both study years (0.36 ± 0.30 g CH4 m-2 yr-1 in 2014–15 and 0.13 ± 0.38 g CH4 m-2 yr-1 in 2015–16), but fell within the range of CH4 emissions reported for agriculturally managed peatlands elsewhere. [ABSTRACT FROM AUTHOR]

Climate change may affect the chemical composition of riparian leaf litter and, aquatic organisms and, consequently, leaf breakdown. We evaluated the effects of different scenarios combining increased temperature and carbon dioxide (CO2) on leaf detritus of Hevea spruceana (Benth) Müll. and decomposers (insect shredders and microorganisms). We hypothesized that simulated climate change (warming and elevated CO2) would: i) decrease leaf-litter quality, ii) decrease survival and leaf breakdown by shredders, and iii) increase microbial leaf breakdown and fungal biomass. We performed the experiment in four microcosm chambers that simulated air temperature and CO2 changes in relation to a real-time control tracking current conditions in Manaus, Amazonas, Brazil. The experiment lasted seven days. During the experiment mean air temperature and CO2 concentration ranged from 26.96 ± 0.98ºC and 537.86 ± 18.36 ppmv in the control to 31.75 ± 0.50ºC and 1636.96 ± 17.99 ppmv in the extreme chamber, respectively. However, phosphorus concentration in the leaf litter decreased with warming and elevated CO2. Leaf quality (percentage of carbon, nitrogen, phosphorus, cellulose and lignin) was not influenced by soil flooding. Fungal biomass and microbial leaf breakdown were positively influenced by temperature and CO2 increase and reached their highest values in the intermediate condition. Both total and shredder leaf breakdown, and shredder survival rate were similar among all climatic conditions. Thus, low leaf-litter quality due to climate change and higher leaf breakdown under intermediate conditions may indicate an increase of riparian metabolism due to temperature and CO2 increase, highlighting the risk (e.g., decreased productivity) of global warming for tropical streams. [ABSTRACT FROM AUTHOR]

Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise. [ABSTRACT FROM AUTHOR]

The persistence of atmospheric circulation anomalies over East Asia shows a winter to winter recurrence (WTWR) phenomenon. Seasonal variations in sea level pressure anomalies and surface wind anomalies display significantly different characteristics between WTWR and non-WTWR years. The WTWR years are characterized by the recurrence of both a strong (weak) anomalous Siberian High and an East Asian winter monsoon over two successive winters without persistence through the intervening summer. However, anomalies during the non-WTWR years have the opposite sign between the current and ensuing winters. The WTWR of circulation anomalies contributes to that of surface air temperature anomalies (SATAs), which is useful information for improving seasonal and interannual climate predictions over East Asia and China. In the positive (negative) WTWR years, SATAs are cooler (warmer) over East Asia in two successive winters, but the signs of the SATAs are opposite in the preceding and subsequent winters during the non-WTWR years. [ABSTRACT FROM AUTHOR]

Several studies on global change over the next century predict increases in mean air temperatures of between 1°C to 5°C that would affect not only water temperature but also river flow. Climate is the predominant environmental driver of thermal and flow regimes of freshwater ecosystems, determining survival, growth, metabolism, phenology and behaviour as well as biotic interactions of aquatic fauna. Thus, these changes would also have consequences for species phenology, their distribution range, and the composition and dynamics of communities. These effects are expected to be especially severe in the Mediterranean basin due its particular climate conditions, seriously threatening Southern European ecosystems. In addition, species with restricted distributions and narrow ecological requirements, such as those living in the headwaters of rivers, will be severely affected. The study area corresponds to the Spanish Mediterranean and Balearic Islands, delimited by the Köppen climate boundary. With the application of the MEDPACS (MEDiterranean Prediction And Classification System) predictive approach, the macroinvertebrate community was predicted for current conditions and compared with three posible scenarios of watertemperature increase and its associated water flow reductions. The results indicate that the aquatic macroinvertebrate communities will undergo a drastic impact, with reductions in taxa richness for each scenario in relation to simulated current conditions, accompanied by changes in the taxa distribution pattern. Accordingly, the distribution area of most of the taxa (65.96%) inhabiting the mid-high elevations would contract and rise in altitude. Thus, families containing a great number of generalist species will move upstream to colonize new zones with lower water temperatures. By contrast, more vulnerable taxa will undergo reductions in their distribution area. [ABSTRACT FROM AUTHOR]

Understanding the warming trends at local level is critical; and, the development of relevant adaptation and mitigation policies at those levels are quite challenging. Here, our overall goal was to generate local warming trend map at 1 km spatial resolution by using: (i) Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composite surface temperature data; (ii) weather station-based yearly average air temperature data; and (iii) air temperature normal (i.e., 30 year average) data over the Canadian province of Alberta during the period 1961–2010. Thus, we analysed the station-based air temperature data in generating relationships between air temperature normal and yearly average air temperature in order to facilitate the selection of year-specific MODIS-based surface temperature data. These MODIS data in conjunction with weather station-based air temperature normal data were then used to model local warming trends. We observed that almost 88% areas of the province experienced warming trends (i.e., up to 1.5°C). The study concluded that remote sensing technology could be useful for delineating generic trends associated with local warming. [ABSTRACT FROM AUTHOR]

Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations)–despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region- to region- variation in responses (i.e. from as many as 73% to as few as 32% of species shifting upward). To understand the factors that might be controlling region-specific distributional shifts of plant species, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction that distribution limits shifted was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species were more likely to shift upward at their upper elevational limit when minimum temperatures increased and snowfall was unchanging or declined at slower rates (<0.5 mm/year). This suggests that both low temperature and water availability limit upward shifts at upper elevation limits. By contrast, species were more likely to shift upwards at their lower elevation limit when maximum temperatures increased, but also shifted upwards under conditions of cooling temperatures when precipitation decreased. This suggests increased water stress may drive upward shifts at lower elevation limits. Our results suggest that species’ elevational distribution shifts are not predictable by climate warming alone but depend on the interaction between seasonal temperature and precipitation change. [ABSTRACT FROM AUTHOR]

Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scal land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we examine the effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is simulated over low latitude deforested areas. Mid latitude SAT response is mixed. In all simulations deforested areas tend to become drier and have lower SAT, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation cause an increase in soil carbon large enough to produce a net decrease of atmospheric CO2. Our results reveal the complex interactions between soil carbon dynamics and other climate subsystems in the energy partition responses to land cover change. [ABSTRACT FROM AUTHOR]

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. [ABSTRACT FROM AUTHOR]

Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i) an emotive simulated example, ii) application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife. [ABSTRACT FROM AUTHOR]

There has been evidence of warming rate varying largely over space and between seasons. However, little has been done to evaluate the spatial and temporal variability of air temperature in the Tarim Basin, northwest China. In this study, we collected daily air temperature from 19 meteorological stations for the period of 1960–2012, and analyzed annual mean temperature (AMT), the annual minimum (Tmin) and maximum temperature (Tmax), and mean temperatures of all twelve months and four seasons and their anomalies. Trend analyses, standard deviation of the detrended anomaly (SDDA) and correlations were carried out to characterize the spatial and temporal variability of various mean air temperatures. Our data showed that increasing trend was much greater in the Tmin (0.55°C/10a) than in the AMT (0.25°C/10a) and Tmax (0.12°C/10a), and the fluctuation followed the same order. There were large spatial variations in the increasing trends of both AMT (from −0.09 to 0.43 °C/10a) and Tmin (from 0.15 to 1.12°C/10a). Correlation analyses indicated that AMT had a significantly linear relationship with Tmin and the mean temperatures of four seasons. There were also pronounced changes in the monthly air temperature from November to March at decadal time scale. The seasonality (i.e., summer and winter difference) of air temperature was stronger during the period of 1960–1979 than over the recent three decades. Our preliminary analyses indicated that local environmental conditions (such as elevation) might be partly responsible for the spatial variability, and large scale climate phenomena might have influences on the temporal variability of air temperature in the Tarim Basin. In particular, there was a significant correlation between index of El Niño-Southern Oscillation (ENSO) and air temperature of May (P = 0.004), and between the index of Pacific Decadal Oscillation (PDO) and air temperature of July (P = 0.026) over the interannual to decadal time scales. [ABSTRACT FROM AUTHOR]

The effects of land cover on urban-rural and intra-urban temperature differences have been extensively documented. However, few studies have quantitatively related air temperature to land cover composition at a local scale which may be useful to guide landscape planning and design. In this study, the quantitative relationships between air temperature and land cover composition at a neighborhood scale in Beijing were investigated through a field measurement campaign and statistical analysis. The results showed that the air temperature had a significant positive correlation with the coverage of man-made surfaces, but the degree of correlation varied among different times and seasons. The different land cover types had different effects on air temperature, and also had very different spatial extent dependence: with increasing buffer zone size (from 20 to 300 m in radius), the correlation coefficient of different land cover types varied differently, and their relative impacts also varied among different times and seasons. At noon in summer, ∼37% of the variations in temperature were explained by the percentage tree cover, while ∼87% of the variations in temperature were explained by the percentage of building area and the percentage tree cover on summer night. The results emphasize the key role of tree cover in attenuating urban air temperature during daytime and nighttime in summer, further highlighting that increasing vegetation cover could be one effective way to ameliorate the urban thermal environment. [ABSTRACT FROM AUTHOR]

Understanding environmental and climatic drivers of natural mortality of marine mammals is critical for managing populations effectively and for predicting responses to climate change. Here we use a 17-year dataset to demonstrate a clear relationship between environmental forcing and natural mortality of inshore marine mammals across a subtropical-tropical coastline spanning a latitudinal gradient of 13° (>2000 km of coastline). Peak mortality of inshore dolphins and dugongs followed sustained periods of elevated freshwater discharge (9 months) and low air temperature (3 months). At a regional scale, these results translated into a strong relationship between annual mortality and an index of El Niño-Southern Oscillation. The number of cyclones crossing the coastline had a comparatively weak effect on inshore marine mammal mortality, and only in the tropics. Natural mortality of offshore/migratory cetaceans was not predicted by freshwater discharge, but was related to lagged air temperature. These results represent the first quantitative link between environmental forcing and marine mammal mortality in the tropics, and form the basis of a predictive tool for managers to prepare responses to periods of elevated marine mammal mortality. [ABSTRACT FROM AUTHOR]

Recent increases in tree mortality rates across the western USA are correlated with increasing temperatures, but mechanisms remain unresolved. Specifically, increasing mortality could predominantly be a consequence of temperature-induced increases in either (1) drought stress, or (2) the effectiveness of tree-killing insects and pathogens. Using long-term data from California’s Sierra Nevada mountain range, we found that in water-limited (low-elevation) forests mortality was unambiguously best modeled by climatic water deficit, consistent with the first mechanism. In energy-limited (high-elevation) forests deficit models were only equivocally better than temperature models, suggesting that the second mechanism is increasingly important in these forests. We could not distinguish between models predicting mortality using absolute versus relative changes in water deficit, and these two model types led to different forecasts of mortality vulnerability under future climate scenarios. Our results provide evidence for differing climatic controls of tree mortality in water- and energy-limited forests, while highlighting the need for an improved understanding of tree mortality processes. [ABSTRACT FROM AUTHOR]

The Arctic is rapidly warming and host-parasite relationships may be modified by such environmental changes. Here, I showed that the average winter temperature in Svalbard, Arctic Norway, explained almost 90% of the average prevalence of ticks in an Arctic seabird, the Brünnich’s guillemot Uria lomvia. An increase of 1°C in the average winter temperature at the nesting colony site was associated with a 5% increase in the number of birds infected by these ectoparasites in the subsequent breeding season. Guillemots were generally infested by only a few ticks (≤5) and I found no direct effect of tick presence on their body condition and breeding success. However, the strong effect of average winter temperature described here clearly indicates that tick-seabird relationships in the Arctic may be strongly affected by ongoing climate warming. [ABSTRACT FROM AUTHOR]

In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10−6 to 2.4×10−5 S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security. [ABSTRACT FROM AUTHOR]

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961–2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of −6°C and −4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961–2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991–2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions. [ABSTRACT FROM AUTHOR]

A total of 290 tree-ring samples, collected from six sites in the West Qinling Mountains of China, were used to develop six new standard tree-ring chronologies. In addition, 73 proxy records were assembled in collaboration with Chinese and international scholars, from 27 publically available proxy records and 40 tree-ring chronologies that are not available in public datasets. These records were used to reconstruct annual mean temperature variability in the West Qinling Mountains over the past 500 years (AD 1500–1995), using a modified point-by-point regression (hybrid PPR) method. The results demonstrate that the hybrid PPR method successfully integrates the temperature signals from different types of proxies, and that the method preserves a high degree of low-frequency variability. The reconstruction shows greater temperature variability in the West Qinling Mountains than has been found in previous studies. Our temperature reconstruction for this region shows: 1) five distinct cold periods, at approximately AD 1520–1535, AD 1560–1575, AD 1610–1620, AD 1850–1875 and AD 1965–1985, and four warm periods, at approximately AD 1645–1660, AD 1705–1725, AD 1785–1795 and AD 1920–1945; 2) that in this region, the 20th century was not the warmest period of the past 500 years; and 3) that a dominant and persistent oscillation of ca. 64 years is significantly identified in the 1640–1790 period. [ABSTRACT FROM AUTHOR]

Here, first we study the effectiveness of multilayer perceptron networks (MLPs) for prediction of the maximum and the minimum temperatures based on past observations on various atmospheric parameters. To capture the seasonality of atmospheric data, with a view to improving the prediction accuracy, we then propose a novel neural architecture that combines a self-organizing feature map (SOFM) and MLPs to realize a hybrid network named SOFM-MLP with better performance. We also demonstrate that the use of appropriate features such as temperature gradient can not only reduce the number of features drastically, but also can improve the prediction accuracy. These observations inspired us to use a feature selection MLP (FSMLP) instead of MLP, which can select good features online while learning the prediction task. FSMLP is used as a preprocessor to select good features. The combined use of FSMLP and SOFM-MLP results in a network system that uses only very few inputs but can produce good prediction. [ABSTRACT FROM AUTHOR]