Long-term Average Temperature Research Articles

The temperature-precipitation duel and tropical greening during the Early Eocene Greenhouse episode

Under rising anthropogenic CO2, the future of the tropical climate states and the response of the biosphere, specifically the fate of the tropical rainforest (TRF), is uncertain. Therefore, deep-time climate proxy records and model simulations are being extensively utilized to understand the possible response of the TRF community during extreme climate states. However, comprehensive climate-TRF proxy data from the tropical/equatorial region for the paleo-global warming episodes, e.g., Late Paleocene – Early Eocene interval (~56 to 51 Ma, encompassing transient hyperthermal events like Paleocene-Eocene Thermal Maximum [PETM], Eocene Thermal Maximum2 [ETM2]/H1/ Eocene Layer of Mysterious Origin [ELMO], H2, I1, and I2), are very limited and create difficulties in the validation of simulated results. Here we present long-term land surface temperature and precipitation (δ2H and δ18O of pedogenic clay mineral-derived) and TRF diversity (palynology) data from a paleo-equatorial region, spanning the ~56 to 51 Ma interval. Present data suggest that the hydrological response to global warming was not temporally uniform in the paleo-equatorial land. While a significantly increased rainfall buffered the terrestrial temperature during the PETM, an insignificant increase in precipitation and negligible temperature lowering can be observed during the ETM2 hyperthermal event. However, the climate system's response during the other Early Eocene hyperthermals, i.e., H2, I1, and I2, was very similar to the PETM. Despite these small aberrations, the long-term average equatorial land surface temperature (27 ± 4 °C) during the Early Eocene greenhouse episode remained very similar to the modern equatorial temperature (28–30 °C). Rainfall proxy and plant diversity data suggest that the precipitation aided TRFs' resilience and proliferation, possibly through temperature buffering, during this paleo-greenhouse episode.

Long Term Historical Precipitation and Temperature Trend Analysis for Selected Stations in Bale and East Bale Zones of Southeastern Ethiopia

Trend analysis for the long-term average temperature and precipitation of Bale and East Bale Zones during 1901 to 2016 has been performed for selected 5 stations to understand the pattern of these important meteorological features under climate change. The precipitation characterizations viz. standardized Precipitation Index has been considered for Sinana, Goro, Ginnir, Dallo menna and Agarfa stations. This study was aimed to analysis ‘’long term historical climate analysis selected stations in Bale and East Bale zones’’. The study considered station nearby kebeles was selected purposively from highland, midland and lowland districts. Standardized Precipitation Index drought index method was used to classify drought condition of the area. The findings showed that, the average temperature of the district showed an increased in the past three decades whereas the annual precipitation of the districts showed a decreasing trend with some variation from the mean in the period 1901- 2016 which was validated with 1984 – 2016 observed data. In line with this, representative respondents were considered from lowland, highland and midland agro-ecologies. Long term annual mean temperature showed increase trends by 0.17°C per decade at Sinana, Goro, Ginnir and Agarfa stations. Additionally, it was revealed more increment by 0.19°C per decade at Dallo menna station. From long term climate data analysis, it was indicated that extremely wet recorded in 1903, 1914, 1917, 1926, 1977 and 2013, while extremely dry conditions were recorded in 1919, 1938 and 1943 annual precipitation recorded for the whole period has been calculated and interpreted.

ФАКТОРЫ ОКРУЖАЮЩЕЙ СРЕДЫ И ЗАРАЖЕННОСТЬ ЛОШАДЕЙ ЖЕЛУДОЧНО-КИШЕЧНЫМИ ГЕЛЬМИНТАМИ В ГОРНОМ АЛТАЕ

The aim of the study is to conduct a comparative assessment of the infestation of horses with intestinal helminths in various administrative districts and to characterize the patterns of the relationship between abiotic and anthropogenic environmental factors and the rates of infestation of horses with intestinal helminths in the Gorny Altai. Based on long-term (2019–2023) ovoscopic examinations of 1.2 thousand horses from 10 districts of the region, the infestation of animals with helminths of the gastrointestinal tract was characterized. Correlation analysis was used to characterize the relationship between the level of infestation of animals with helminths, the number of parasites with abiotic and anthropogenic environmental factors in the context of farms and districts of the Gorny Altai. Horses are mostly infected with helminths in the Chemalsky District, where the prevalence of infestation is 95.8 %, and the infection intensity is 458.3 eggs per gram of feces. The lowest prevalence of helminths in animals was recorded in the Ust-Kansky District – EI 56.3 %, with IIs – 186.7 specimens. g/f. The prevalence of infestation in animals is significantly lower in areas characterized by low temperatures and precipitation, and significantly higher in warmer and more humid areas of the region. The prevalence of infestation in horses is 84.6 %, with IIs – 337.5 specimens. g/f. The most significant factors influencing the infection of animals with intestinal helminths (EI, % and IIs) in farms are the long-term average annual precipitation (r = 0.42 and 0.52) and the degree of anthropogenic pressure (r = –0.55 and –0.63), in the context of regions, long-term average annual temperatures (r = 0.55 and 0.65) and long-term average precipitation (r = 0.69 and 0.65).

Effective methods of agricultural use of light colored gray soils distributed in Kuva hill

Fergana Valley is a tectonic depression surrounded by mountains, and its appearance is in the form of an ellipse. Its length from west to east is 300 km equal to 50 meters from south to north. 70 km The height of the valley reaches from sea level in the west to . in the 250 мeast 1000 м. The height of the surrounding high mountains of Central Ferghana is 2000 - 4000 m and more. Such a sharp geomorphological structure determines the specific characteristics of the valley’s climate. The western and central parts of the Fergana valley (up to the Margilan oasis) belong to the desert region, and the eastern part to the semi-desert region. The climatic conditions of the desert part are described by the meteorological stations “Ko’kan”, “Ultarma” and “Namangan”, and the semi-desert part by the data of the weather stations “Fergana”, “Nasriddinbek” and “Fedchenko”. In the western and northern regions of the valley, the long-term average air temperature is +13+13.5 0 C. The coldest month of the year is January, its average temperature is -2.1-2.40 C. The period with the highest temperature is July, and the average temperature is around +24.8+27.6 0 C. ( Tables 1-2 ). The minimum temperature is -27-29 0 C, the maximum temperature is +42+46 0 C. We present the detail of the morphology of the 1st soil cross-section, trying to reveal the specific characteristics of the pale gray gypsum soils in the Kuva hills. The soils formed in the Kuva hills, where we conducted research, are the result of the long-term development of the area. Kuva mountain range is located 500-600m above sea level. The pale gray soils distributed in these areas are composed of stony rocks formed on loess and loess sand. At the same time, it appeared on coarse, gravelly-soft rock formations and gravels, on top of which a thin skeleton of sand and silt is covered.

Effects of changing climate extremes and vegetation phenology on wildlife associated with grasslands in the southwestern United States

Assessments of the potential responses of animal species to climate change often rely on correlations between long-term average temperature or precipitation and species’ occurrence or abundance. Such assessments do not account for the potential predictive capacity of either climate extremes and variability or the indirect effects of climate as mediated by plant phenology. By contrast, we projected responses of wildlife in desert grasslands of the southwestern United States to future climate means, extremes, and variability and changes in the timing and magnitude of primary productivity. We used historical climate data and remotely sensed phenology metrics to develop predictive models of climate-phenology relations and to project phenology given anticipated future climate. We used wildlife survey data to develop models of wildlife-climate and wildlife-phenology relations. Then, on the basis of the modeled relations between climate and phenology variables, and expectations of future climate change, we projected the occurrence or density of four species of management interest associated with these grasslands: Gambel’s Quail (Callipepla gambelii), Scaled Quail (Callipepla squamat), Gunnison’s prairie dog (Cynomys gunnisoni), and American pronghorn (Antilocapra americana). Our results illustrated that climate extremes and plant phenology may contribute more to projecting wildlife responses to climate change than climate means. Monthly climate extremes and phenology variables were influential predictors of population measures of all four species. For three species, models that included climate extremes as predictors outperformed models that did not include extremes. The most important predictors, and months in which the predictors were most relevant to wildlife occurrence or density, varied among species. Our results highlighted that spatial and temporal variability in climate, phenology, and population measures may limit the utility of climate averages-based bioclimatic niche models for informing wildlife management actions, and may suggest priorities for sustained data collection and continued analysis.

Modelling spatiotemporal tendencies of climate types by Markov chain approach : A case study in Sanliurfa province in the south-eastern of Turkey

Identification of spatiotemporal tendencies of climate types may help water managers mitigate the negative impacts of droughts on water-demanding sectors. The primary objective of this study was to figure out the spatiotemporal tendencies of climatetypes in Sanliurfa province by using Erinc’s aridity index (EDI). To that end, long-term (1965-2018) annual precipitation and average annual maximum temperature series of meteorological stations were obtained and utilized to calculate the EDI series on a yearly basis. The EDI series of each station was divided into three periods, non-overlapping and successive, i.e., P1 (1965-1981), P2 (1982-1999) and P3 (2000-2018). Outliers were detected, andremoved from the EDI series; missing data were completed by regression analysis. The Markov transition probability matrix of the climate classes for the three periods was estimated for each station. Maps of the initial probability vectors and steady-state probabilities for the three periods of each climate class were generated by the inverse distance-weighted technique. Hypsometric curves for each climate class, as well as period, were developed and areal coverage of occurrence probabilities (OP) was determined. Results indicated that, as time progressed, the areal extent of severe-arid and arid climatic classes continued consistently to spread from the south to the north. Areas of semi-arid climate type showed a slight tendency towards the arid-climate type. Construction of large dams in the region could not prevent the shifts in the climate in favour of developing arid zones. The humid climate class is likely to vanish away in the future. Research led us to conclude that the expansion of the aridzone from south to northhas been alarming in terms of the adequacy of water resources. It is strongly recommended that spatiotemporal climate change studies should be periodically conducted in tandem with forest management practices for the region.

No Evidence of an Elevation Effect Caused by Temperature Differences on Soil Microbial Properties in a Walnut Fruit Forest in Kyrgyzstan

This study is to investigate the effect of differences in annual average temperature on soil microbial communities as caused by elevation in walnut-fruit forests in Kyrgyzstan with similar vegetation. Soil samples (n = 10 per site) were collected from top- and subsoil at three elevation levels (1000, 1300 and 1600 m above sea level) with an average temperature difference of 1.3 °C between sites and analysed for soil chemical and biological properties. All soil properties showed high variability within, but most revealed no differences between elevation levels. Microbial biomass, activity and community composition were largely similar at all sites with slightly higher fungal contribution based on internal transcribed spacer (ITS) sequence counts at high elevation, which, however was not reflected by ergosterol. Total soil organic carbon and nitrogen levels did not show elevation effects either. Mehlich-extractable elements revealed positive relationship with soil microbial properties, which was in particular pronounced for copper, manganese and zinc, highlighting the relevance of trace elements for soil microorganisms. The subsoil showed lower levels for all microbial properties even though they were on a comparably high level; it contained smaller sized bacteria and fungi, as revealed by MBC/dsDNA ratios, and fungal ITS counts/ergosterol ratios illustrating growth limitations for microorganisms in subsoils. Elevation with long-term average temperature differences did not yield pronounced differences in soil microbial properties, which were more potentially stronger affected by similar C input quantity and substrate quality from the similar vegetation. Consequently, climate change effects will more likely affect microbial properties indirectly via changes in vegetation.

Climate change-related warming reduces thermal sensitivity and modifies metabolic activity of coastal benthic bacterial communities

Besides long-term average temperature increases, climate change is projected to result in a higher frequency of marine heatwaves. Coastal zones are some of the most productive and vulnerable ecosystems, with many stretches already under anthropogenic pressure. Microorganisms in coastal areas are central to marine energy and nutrient cycling and therefore, it is important to understand how climate change will alter these ecosystems. Using a long-term heated bay (warmed for 50 years) in comparison with an unaffected adjacent control bay and an experimental short-term thermal (9 days at 6–35 °C) incubation experiment, this study provides new insights into how coastal benthic water and surface sediment bacterial communities respond to temperature change. Benthic bacterial communities in the two bays reacted differently to temperature increases with productivity in the heated bay having a broader thermal tolerance compared with that in the control bay. Furthermore, the transcriptional analysis showed that the heated bay benthic bacteria had higher transcript numbers related to energy metabolism and stress compared to the control bay, while short-term elevated temperatures in the control bay incubation experiment induced a transcript response resembling that observed in the heated bay field conditions. In contrast, a reciprocal response was not observed for the heated bay community RNA transcripts exposed to lower temperatures indicating a potential tipping point in community response may have been reached. In summary, long-term warming modulates the performance, productivity, and resilience of bacterial communities in response to warming.

Changes in the area of lakes in different natural regions of Mongolia and climate effect

There has not been much study done to explain how recent climate change affects the water surface area changes in lakes in different natural areas of Mongolia. Four lakes between 48° - 50° in Mongolia were chosen for this investigation because they have the same climatic and solar radiation patterns. The case studies of the Khoton Lake in the high mountain region, Terkhin Tsagaan in the forest-steppe region, Khukh Lake in the steppe region, and Namir (Khar Us) in the Govi region emphasized the relationship between lakes surface area and climate variables, which are temperature and precipitation. In the study, statistical analysis methods, the Mann-Kendall test (MK), the innovative trend analysis method (ITAM), the Sen's Slope Estimator Test (SET), and the normalized difference water index (NDWI) method were used. During the past 30 years, calculations based on satellite imagery of the lake area in different natural zones have shown a decreasing trend for the lake area. After 2000, all-natural regions saw a sharp rise in the long-term average air temperature. High mountain regions have seen an increase in precipitation since 2000, Forest-steppe regions have increased since 2010, and steppe and gobi regions have declined since 2000. Lake areas in the high mountain and forest-steppe regions showed a steady decreasing trend starting in 2000, while lakes in the steppe and Gobi regions showed a gradually creasing trend starting in 2010. The increase in the average annual air temperature (Z=1.17) in the high mountain region was more closely related to the changes in the lake region. On the other hand, the area in the forest-steppe zone was better correlated with the quantity of precipitation (Z=1.93). The effect of air temperature (Z=1.21) on the area of lakes in the steppe zone was more relevant, while the amount of precipitation was slightly related. Rainfall (Z=-1.80) was more related to the area of lakes in the Gobi region, while the air temperature was less related. The novelty of the research is that it has been clarified that the lake changes in the area in different natural regions are influenced differently by the climate.

Открытые источники данных для моделирования ареалов: информационные системы о биоразнообразии и наборы пространственных данных условий среды

Открытые источники данных для моделирования ареалов: информационные системы о биоразнообразии и наборы пространственных данных условий среды

Effects of long-term average temperature on cardiovascular disease hospitalizations in an American elderly population

BackgroundShort-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations. MethodsWe constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June–August) and winter (December–February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity. ResultsHigher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged <75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged <75 years and Black individuals, and individuals living in low relative humidity areas. ConclusionsLiving in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels.

Germination behaviour of

Context Avena sterilis subsp. ludoviciana (wild oats) is one of the major winter weeds of the Northern Grains Region of Australia. The abundance of this weed increased dramatically after the adoption of no-tillage conservation agriculture (NTCA). However, information is lacking on the germination characteristics of the two types of seed (i.e. primary and secondary) that it produces. Aims We aimed to determine the light and temperature requirements for germination and the time to germination of primary and secondary seeds of A. ludoviciana, in order to find ways to manage this weed effectively under NTCA systems. Methods Primary and secondary seeds and caryopses from two southern and two northern biotypes were exposed to a range of temperature and light regimes in the glasshouse, and germination was assessed. Key results All biotypes had ∼25% higher germination from primary than secondary seeds. Removing the hull increased caryopsis germination by ∼70%. The use of a light/dark photoperiod stimulated germination of both types of seed and caryopses compared with continuous darkness. Based on data for caryopses, 7°C and 9°C were found to be optimal germination temperatures for southern and northern biotypes, respectively. At optimum germination temperature, primary caryopses germinated 7–20 days earlier than secondary caryopses. In addition, a light/dark environment resulted in germination 2–6 days earlier than continuous darkness. Conclusions In the Northern Grains Region, seeds retained on or close to the soil surface (i.e. in NTCA systems) can undergo maximum germination during May–June (late autumn–winter), when long-term average temperatures match optimum germination temperatures. This coincides with winter crop plantings. Implications The seasonal timing of germination and the difference in germination timing between primary and secondary seeds, which help to stagger emergence of this weed, are major issues that need to be addressed in NTCA systems.

Effects of long-term average temperature and temperature variability on cardiovascular disease hospitalizations in the US Medicare population

BACKGROUND AND AIM: Numerous studies have shown short-term exposure to extreme temperature is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to warm or cold temperatures. Our aim was to evaluate associations of long-term temperature exposure and temperature variability with cardiovascular disease (CVD) hospitalizations. METHODS: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We used data from the 4km Gridded Surface Meteorological dataset to assess the annual (January-December), summer (June-August), and winter (December-February) average temperature and temperature variability (standard deviation) for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD, coronary heart disease (CHD) or cerebrovascular disease (CBV) hospitalization, after adjustment for potential confounders (including individual and area-level SES indicators). RESULTS:Higher annual average and summer average temperatures were associated with an increased risk of CVD, CHD and CBV hospitalization. Lower winter average temperatures were associated with an increased risk of CVD and CHD hospitalization, but a decreased risk of CBV hospitalization. For CVD hospitalization, we found a HR of 1.07 (95%CI: 1.06, 1.07) per IQR increase (8.1°C) for annual average temperature, a HR of 1.03 (95%CI: 1.03, 1.04) per IQR increase (5.2°C) for summer average temperature, and a HR of 0.97 (95%CI: 0.97, 0.98) per IQR increase (11.7°C) for winter average temperature. Higher annual and winter temperature variability and lower summer temperature variability were associated with an increased risk for all outcomes. Associations were modified by age, race, air pollution and greenness. CONCLUSIONS:Warmer annual and summer average temperatures and cooler winter average temperatures were associated with an increased risk of CVD hospitalizations. Higher annual and winter temperature variability and lower summer temperature variability were also associated with increased risk. KEYWORDS: temperature, temperature variability, Cardiovascular diseases

Büyük Menderes Havzasında Bazı Hidroklimatolojik Değişkenlerin Eğilim Analizi

İnsanlık tarihinden bu yana dünyanın değişen doğal dengesi, iklimleri de değiştirmektedir. Tüm canlı yaşamı ve çevresini tehdit eden küresel iklim değişikliğinin su kaynaklarımız üzerinde de önemli etkiler yaratması muhtemeldir. Dolayısıyla hidroklimatolojik değişkenlerin zaman içerisindeki değişimlerini incelemek önem arz etmektedir. Bu çalışmada Ege Bölgesinde yaklaşık 26.000 km2’lik bir alan ile en büyük havza niteliğinde olan Büyük Menderes Havzası ele alınmıştır. Havzada yer alan Aydın, Denizli ve Uşak illerine ait uzun yıllar aylık ortalama yağış, sıcaklık ve akım verileri Mann Kendall trend analizine tabii tutularak zaman içindeki değişim incelenmiştir. Buna göre sıcaklık bakımından en anlamlı artış eğilimi yedi ay ile Denizli’de olurken Uşak’ta da yaz aylarındaki artış istatistiksel olarak önemli bulunmuştur. Aydın ilinde ise sıcaklıklarda bir artış söz konusu olup bu artış istatistiki olarak önemli bulunmamıştır. Yağış ve akım eğilimleri incelendiğinde ise Denizli ve Uşak’ta yağışlarda görülen artış eğilimi anlam teşkil etmez iken havzada bulunan iki akım istasyonunda da önemli azalış eğilimi izlenmiştir.

Germination at Extreme Temperatures: Implications for Alpine Shrub Encroachment.

Worldwide, shrub cover is increasing across alpine and tundra landscapes in response to warming ambient temperatures and declines in snowpack. With a changing climate, shrub encroachment may rely on recruitment from seed occurring outside of the optimum temperature range. We used a temperature gradient plate in order to determine the germination niche of 14 alpine shrub species. We then related the range in laboratory germination temperatures of each species to long-term average temperature conditions at: (1) the location of the seed accession site and (2) across each species geographic distribution. Seven of the species failed to germinate sufficiently to be included in the analyses. For the other species, the germination niche was broad, spanning a range in temperatures of up to 17 °C, despite very low germination rates in some species. Temperatures associated with the highest germination percentages were all above the range of temperatures present at each specific seed accession site. Optimum germination temperatures were consistently within or higher than the range of maximum temperatures modelled across the species’ geographic distribution. Our results indicate that while some shrub species germinate well at high temperatures, others are apparently constrained by an inherent seed dormancy. Shrub encroachment in alpine areas will likely depend on conditions that affect seed germination at the microsite-scale, despite overall conditions becoming more suitable for shrubs at high elevations.

A hierarchical threshold modeling approach for understanding phenological responses to climate change: when did North American lilacs start to bloom earlier?

Prior to the recent upward climb, global average temperatures were relatively stable. This trend was described by Mann et al. [23] using a hockey-stick model consisting of two line segments (with the x-axis as time and temperature as the y-axis) meeting at a single changepoint. The line segment prior to the changepoint is flat (indicating a stable temperature), and the line after the changepoint has a positive slope (indicating increasing temperatures). Because the long-term average temperature change is a defining characteristic of climate change, researchers have shown that changes in many phenological variables over time can also be described by a hockey-stick model. For phenological variables, the changepoint and the slope of the line after the changepoint represent the timing of the onset and the effect of climate change. However, large annual variation often obscures the pattern when analyzed using data from a single location, whereas regional differences due to spatial variability of climate and weather patterns render pooling data from different locations impractical. We demonstrate that the Bayesian hierarchical modeling approach is effective in separating these two sources of variability by partially pooling data from multiple sites. Using the North American lilac first bloom dates, we show that the Bayesian approach can adequately separate the temporal and spatial variations, thereby quantify site-specific patterns of change as well as national/regional average trends. Our analysis, using the Bayesian hierarchical hockey-stick model, showed that the effects of climate change started as early as the 1970s and the lilacs in North America have been blooming on average one day earlier every three years since.

Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study

SummaryBackgroundVarious retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions.MethodsDTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985–2015) and future (2020–99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk.FindingsThe time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by −0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2–7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4–10·3% in 2090–99.InterpretationThis study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health.FundingKorea Ministry of Environment.

Trend analysis of long-term rainfall and temperature data for Ethiopia

ABSTRACT Trend analysis for the long-term average temperature and rainfall of Ethiopia during 1901 to 2015 has been performed to understand the pattern of these important meteorological features under climate change. The rainfall characterizations viz., precipitation concentration index (PCI), seasonality index (SI), rainfall anomaly index (RAI) and departure analysis of rainfall (DAR) have been calculated and interpreted. The annual rainfall recorded for the whole period was 816.3 ± 90.82 mm/year. During kiremt (long rainy) season, maximum seasonal rainfall of 453.2 mm were recorded while, its minimum value (39.6 mm) were received in bega (dry) season, respectively. The analysis of probability distribution for the time series data showed slightly positive skewness and kurtosis in monthly, seasonal and annual rainfall from the normal distribution. The results of Modified Mann–Kendall trend analysis for average temperature revealed a significant increasing trend from 1961 to 2015. Conversely, dry season (bega) rainfall, showed an increasing trend while kiremt season rainfall with decreasing trend for the period of 1901–2015. However, annual and other seasonal rainfall did not show any statistically significant trend. Study concludes that there is an increase in the average temperature in Ethiopia but, it constitutes a high degree of stability in rainfall rate and distribution.

Intestinal Helminths and the Influence of Environmental Factors on Cattle Infection in the Altai Mountains

The purpose of the research: comparative assessment of cattle infection with intestinal helminths in various provinces and characteristics of the relationship between abiotic and anthropogenic environmental factors with the level of infection and the number of helminths in the Altai Mountains. Materials and methods. According to the results of long-term (2010–2019) ovolarvoscopic examinations, more than 2.4 thousand heads of cattle from 7 regions of the Altai Republic characterized by extensity of infection (EI) and the number of helminth eggs in 1 g of feces (NHE/g) in animals. By correlation analysis, the association of animal EI with helminths, NHE/g and abiotic and anthropogenic environmental factors in the context of farms and regions of the Altai Mountains is shown. The following parameters are estimated: long-term average annual temperature, long-term average annual rainfall, longterm average summer temperature, long-term average summer rainfall, altitude above the sea level, population density of the host, the effect of parasiticidal treatments of animals on parasite infection. Results and discussion. It was found that animals are mostly infected with intestinal helminths in the Choy region, where the EI was 61.7% when detecting NHE/g 81.8 pcs. Minimal infection of cattle by helminths was recorded in the Kosh-Agach region – 38.8% with NHE/g of 22.9 pcs. In the whole country, EI of animals is 51.8% with an egg number of 44.1 individuals in 1 g of feces. Within the physical-geographical provinces, cattle are mostly infected in Central Altai (EI – 56.5%, NHE/g – 43.6 pcs.), to a lesser extent in Southeast Altai (EI – 38.8%, NHE/g – 22.9 pcs.). According to the results of ovoscopic examinations, it was found that the most significant factors affecting the infection of animals with intestinal helminths in farms are the long-term average annual precipitation (r = 0.60 and 0.34) and the degree of anthropogenic pressure (r = -0.52 and -0.59), in the context of districts, long-term average annual temperatures (r = 0.65 and 0.55), average annual summer rainfall (r = 0.74 and 0.65). According to larvoscopy, the most significant environmental factors affecting cattle infection are long-term average annual temperature (r = 0.62 and 0.72), long-term average annual rainfall (r = 0.76) and elevation (r = -0.71 and -0.73), in farms – the degree of anthropogenic press (r = -0.65 and -0.78).

A functional size-spectrum model of the global marine ecosystem that resolves zooplankton composition

Despite their critical role as the main energy pathway between phytoplankton and fish, the functional complexity of zooplankton is typically poorly resolved in marine ecosystem models. Trait-based approaches—where zooplankton are represented with functional traits such as body size—could help improve the resolution of zooplankton in marine ecosystem models and their role in trophic transfer and carbon sequestration. Here, we present the Zooplankton Model of Size Spectra version 2 (ZooMSSv2), a functional size-spectrum model that resolves nine major zooplankton functional groups (heterotrophic flagellates, heterotrophic ciliates, larvaceans, omnivorous copepods, carnivorous copepods, chaetognaths, euphausiids, salps and jellyfish). Each group is represented by the functional traits of body size, size-based feeding characteristics and carbon content. The model is run globally at 5° resolution to steady-state using long-term average temperature and chlorophyll a for each grid-cell. Zooplankton community composition emerges based on the relative fitness of the different groups. Emergent steady-state patterns of global zooplankton abundance, biomass and growth rates agree well with empirical data, and the model is robust to changes in the boundary conditions of the zooplankton. We use the model to consider the role of the zooplankton groups in supporting higher trophic levels, by exploring the sensitivity of steady-state fish biomass to the removal of individual zooplankton groups across the global ocean. Our model shows zooplankton play a key role in supporting fish biomass in the global ocean. For example, the removal of euphausiids or omnivorous copepods caused fish biomass to decrease by up to 80%. By contrast, the removal of carnivorous copepods caused fish biomass to increase by up to 75%. Our results suggest that including zooplankton complexity in ecosystem models could be key to better understanding the distribution of fish biomass and trophic efficiency across the global ocean.