Existing evidence on the effects of climate variability and climate change on ungulates in North America: a systematic map.

BACKGROUND: Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America's ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. METHODS: We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. REVIEW FINDINGS: We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou (Rangifer tarandus), elk (Cervus canadensis), and white-tailed deer (Odocoileus virginianus) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. CONCLUSIONS: The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn (Antilocapra americana) and mountain goats (Oreamnos americanus), and on ungulates in the eastern U.S. and Mexico.

Climate change impacts on dengue transmission areas in Espírito Santo state, Brazil.

Espírito Santo state, in Brazil, is a dengue-endemic region predicted to suffer from an increase in temperature and drought due to climate change, which could affect the areas with active dengue virus transmission. The study objective was modeling climatic factors and climate change effects in zones suitable for dengue virus transmission in Espírito Santo state, Brazil. Data on dengue reports from 2022 were used to determine climatic variables related to spatial distribution. The climate change projections were generated for the 2030s, 2050s, 2070s, and 2090s for three distinct Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5 and SSP5-8.5. A maximum entropy algorithm was used to construct the three models and projections, and the results were used to calculate the ensemble mean. Isothermality, the maximum temperature of the warmest month, precipitation of the wettest month, precipitation of the warmest quarter, and annual precipitation impacted the model. Projections indicated a change in areas suitable for dengue virus transmission, varying from -30.44% in the 2070s (SSP1-2.6) to +13.07% in the 2070s (SSP5-8.5) compared to 2022. The coastal regions were consistently suitable in all scenarios. Urbanized and highly populated areas were predicted to persist with active dengue transmission in Espírito Santo state, posing challenges for public health response.

Unveiling the diversity, composition, and dynamics of phyllosphere microbial communities in Alhagi sparsifolia across desert basins and seasons in Xinjiang, China.

Phyllosphere microbes residing on plant leaf surfaces for maintaining plant health have gained increasing recognition. However, in desert ecosystems, knowledge about the variety, composition, and coexistence patterns of microbial communities in the phyllosphere remains limited. This study, conducted across three basins (Turpan-TLF, Tarim-CL, and Dzungaria-MSW) and three seasons (spring, summer, and autumn) in Xinjiang, China, aimed to explore the diversity and composition of microbial communities in the phyllosphere, encompassing both bacteria and fungi in Alhagi sparsifolia. We also investigated the co-occurrence patterns, influencing factors, and underlying mechanisms driving these dynamics. Results indicate that phyllosphere bacteria exhibited lower diversity indices (ACE, Shannon, Simpson, Fisher phylogenetic diversity, and Richness) in spring compared to summer and autumn, while the Goods Coverage Index (GCI) was higher in spring. Conversely, diversity indices and GCI of phyllosphere fungi showed an opposite trend. Interestingly, the lowest level of multi-functionality and niche width in phyllosphere bacteria occurred in spring, while the highest level was observed in phyllosphere fungi. Furthermore, the study revealed that no significant differences in multi-functionality were found among the regions (CL, MSW, and TLF). Network analysis highlighted that during spring, phyllosphere bacteria exhibited the lowest number of nodes, edges, and average degree, while phyllosphere fungi had the highest. Surprisingly, the multi-functionality of both phyllosphere bacteria and fungi showed no significant correlation with climatic and environmental factors but displayed a significant association with the morphological characteristics and physicochemical properties of leaves. Structural Equation Model indicated that the morphological characteristics of leaves significantly influenced the multi-functionality of phyllosphere bacteria and fungi. However, the indirect and total effects of climate on multi-functionality were greater than the effects of physicochemical properties and morphological characteristics of leaves. These findings offer new insights into leaf phyllosphere microbial community structure, laying a theoretical foundation for vegetation restoration and rational plant resource utilization in desert ecosystems.

Differential sensitivity of climate conditions on birth weight genetic values in mice divergently selected for birth weight residual variance.

After 32 generations of a divergent selection experiment for residual variance of birth weight in mice, two divergent lines were thus obtained: the heterogeneous line (H-line) and the homogeneous line (L-line). Throughout the generations, differences were observed between the two lines in traits such as litter size, survival at weaning, and birth weight variability caused by unidentified environmental conditions. The L-line exhibited advantages in terms of higher survival rates, larger litter sizes, and less sensitivity to changes in food intake. The study is an examination of the effects of climate as an environmental factor on the performance of these animals. Climate factors including maximum, minimum, and mean temperature (T), humidity (H), and TH index; at three stages (the fecundation, a week before the parturition and the parturition), were linked to a birth weight dataset consisting of 22,614 records distributed as follows: 8,853 corresponding to the H-line, 12,649 to the L-line, and 1,112 to the initial population. Out of the 27 analyzed climatic variables, the maximum temperature 1 wk before parturition (MXTW) was identified as the most influential when comparing heteroscedastic models with the deviance information criterion. The order of Legendre polynomial to apply in the following random regression model was tested by a cross-validation using homoscedastic models. Finally, MXTW was compared on how it affected the two divergent lines by analyzing predicted breeding values (PBV) obtained from a random regression heteroscedastic model. The mean PBV of the H-line in the first generation showed a range of 0.070 g with a negative slope, which was 35 times higher than the range obtained for the L-line, which varied within 0.002 g. In the last generation of selection, the H-line exhibited greater instability of PBV across temperatures, with a difference of 0.101 g between the maximum and minimum mean PBV, compared to 0.017 g for the L-line. The standard deviations of the slopes in the H-line were more dispersed than in the L-line. Unlike the H-line, the L-line had slopes that were not significantly different from 0 throughout the generations of selection, indicating greater stability in response to MXTW variations. The H-line exhibited a higher sensitivity to changes in MXTW, particularly in birth weight, with the L-line being more stable. The selection for uniformity of birth weight could lead to less sensitive animals under environmental changes.

Two mice lines obtained by divergent selection for birth weight residual variance were used to determine whether environmental factors could differently affect the homogeneous and heterogeneous lines. The maximum temperature 1 wk before parturition (MXTW) had the higher impact on the birth weight of the animals. A random regression model showed the individual trajectory of birth weight throughout the changes in MXTW. It was evident that the homogeneous line is less susceptible to changes in climate. This result, therefore, supports the hypothesis that the selection for homogeneity in production animals is more advantageous. More robust animals are obtained that can better cope with changes in climate without compromising their productive traits.

Quantifying the effects of cold waves on carbon monoxide poisoning: A time-stratified case-crossover study in Jinan, China.

Background: Previous studies have shown that carbon monoxide (CO) poisoning occurs mostly in winter and is associated with severe cold weather (e.g., ice storms, temperature drops). However, according to previous studies, the impact of low temperature on health has a delayed effect, and the existing research cannot fully reveal the delayed effect of cold waves on CO poisoning. Objectives: The purpose of this study is to analyze the temporal distribution of CO poisoning in Jinan and to explore the acute effect of cold waves on CO poisoning. Methods: We collected emergency call data for CO poisoning in Jinan from 2013 to 2020 and used a time-stratified case-crossover design combined with a conditional logistic regression model to evaluate the impact of the cold wave day and lag 0-8 days on CO poisoning. In addition, 10 definitions of a cold wave were considered to evaluate the impact of different temperature thresholds and durations. Results: During the study period, a total of 1,387 cases of CO poisoning in Jinan used the emergency call system, and more than 85% occurred in cold months. Our findings suggest that cold waves are associated with an increased risk of CO poisoning in Jinan. When P01, P05, and P10 (P01, P05, and P10 refer to the 1st, 5th, and 10th percentiles of the lowest temperature, respectively) were used as temperature thresholds for cold waves, the most significant effects (the maximum OR value, which refers to the risk of CO poisoning on cold wave days compared to other days) were 2.53 (95% CI:1.54, 4.16), 2.06 (95% CI:1.57, 2.7), and 1.49 (95% CI:1.27, 1.74), respectively. Conclusion: Cold waves are associated with an increased risk of CO poisoning, and the risk increases with lower temperature thresholds and longer cold wave durations. Cold wave warnings should be issued and corresponding protective policies should be formulated to reduce the potential risk of CO poisoning.

A systems-level model of direct and indirect links between environmental health, socioeconomic factors, and human mortality.

Major efforts are being made to better understand how human health and ecosystem health are influenced by climate and other environmental factors. However, studies that simultaneously address human and ecosystem health within a systems-level framework that accounts for both direct and indirect effects are rare. Using path analysis and a large database of environmental and socioeconomic variables, we create a systems-level model of direct and indirect effects on human and ecosystem health in counties throughout the conterminous United States. As indicators of human and ecosystem health, we use age-adjusted mortality rate and an index of biological integrity in streams and rivers, respectively. We show that: (i) geology and climate set boundary conditions for all other variables in the model; (ii) hydrology and land cover have predictable but distinct effects on human and ecosystem health; and (iii) forest cover is a key link between the environment and the socioeconomic variables that directly influence human health.

Mitigating climate disruption in time: A self-consistent approach for avoiding both near-term and long-term global warming.

The ongoing and projected impacts from human-induced climate change highlight the need for mitigation approaches to limit warming in both the near term (<2050) and the long term (>2050). We clarify the role of non-CO2 greenhouse gases and aerosols in the context of near-term and long-term climate mitigation, as well as the net effect of decarbonization strategies targeting fossil fuel (FF) phaseout by 2050. Relying on Intergovernmental Panel on Climate Change radiative forcing, we show that the net historical (2019 to 1750) radiative forcing effect of CO2 and non-CO2 climate forcers emitted by FF sources plus the CO2 emitted by land-use changes is comparable to the net from non-CO2 climate forcers emitted by non-FF sources. We find that mitigation measures that target only decarbonization are essential for strong long-term cooling but can result in weak near-term warming (due to unmasking the cooling effect of coemitted aerosols) and lead to temperatures exceeding 2 °C before 2050. In contrast, pairing decarbonization with additional mitigation measures targeting short-lived climate pollutants and N2O, slows the rate of warming a decade or two earlier than decarbonization alone and avoids the 2 °C threshold altogether. These non-CO2 targeted measures when combined with decarbonization can provide net cooling by 2030 and reduce the rate of warming from 2030 to 2050 by about 50%, roughly half of which comes from methane, significantly larger than decarbonization alone over this time frame. Our analysis demonstrates the need for a comprehensive CO2 and targeted non-CO2 mitigation approach to address both the near-term and long-term impacts of climate disruption.

An integrated assessment on the warming effects of urbanization and agriculture in highly developed urban agglomerations of China.

Urbanization and agriculture, the two major and concurrent land use activities, can dramatically alter land surface temperature (LST) through multiple biophysical processes. However, previous studies mainly focused on the warming effects of urbanization in large cities and/or urban core areas that may greatly underestimate the land use impacts on regional climate. Using natural forest as a reference, we assessed the LST changes of both urbanization and agriculture in the three most developed urban agglomerations of China (Jing-Jin-Ji, JJJ; Yangtze River Delta, YRD; Pearl River Delta, PRD) according to satellite observations. Results show that the urban-dominated lands warm the daytime LST substantially, especially in the south subtropical PRD (with an annual mean intensity of 5.5 °C), and the highest do not occur in the core cities. The crop-dominated lands also warm the daytime LST dramatically, especially in the temperate semi-humid JJJ (with an annual mean intensity of 3.9 °C). The daytime warming effects increase significantly from 2003 to 2018 mainly due to urban expansion in crop-dominated and mixed lands. The two land uses continue to warm the LST at night though in a lower magnitude in the PRD. However, the urban-dominated lands warm the LST slightly and the crop-dominated lands cool the LST substantially at night in the JJJ and YRD. Overall, the crop-dominated and/or mixed lands dominate the regional LST changes owing to their large areas. We further show that the daytime warming effects of the two land uses are likely caused by the changes of evapotranspiration, whereas the nighttime cooling effects might be mainly due to the changes in surface albedo and roughness. Our results highlight the importance of considering the urbanization in small-medium sized satellite cities and the more widespread agricultural activities in rural areas when assessing the regional climate change and formulating the mitigation strategies.

Stock collapse and its effect on species interactions: Cod and herring in the Norwegian-Barents Seas system as an example.

Both the Norwegian Spring Spawning herring (Clupea harengus) and the Northeast Arctic (NEA) cod (Gadus morhua) are examples of strong stock reduction and decline of the associated fisheries due to overfishing followed by a recovery. Cod and herring are both part of the Barents Sea ecosystem, which has experienced major warming events in the early (1920-1940) and late 20th century. While the collapse or near collapse of these stocks seems to be linked to an instability created by overfishing and climate, the difference of population dynamics before and after is not fully understood. In particular, it is unclear how the changes in population dynamics before and after the collapses are associated with biotic interactions. The combination of the availability of unique long-term time series for herring and cod makes it a well-suited study system to investigate the effects of collapse. We examine how species interactions may differently affect the herring and cod population dynamic before and after a collapse. Particularly we explore, using a GAM modeling approach, how herring could affect cod and vice versa. We found that the effect of cod biomass on herring that was generally positive (i.e., covariation) but the effect became negative after the collapse (i.e., predation or competition). Likewise a change occurred for the cod, the juvenile herring biomass that had no effect before the collapse had a negative effect after. Our results indicate that the population collapses may alter the inter-specific interactions and response to abiotic environmental changes. While the stocks are at similar abundance levels before and after the collapses, the system is potentially different in its functioning and may require different management action.

Dry Climate Aggravates Riverine Nitrogen Pollution in Australia by Water Volume Reduction.

Freshwater is a scarce resource, and maintaining water quality is of great importance in dryland Australia. How water quality is affected by the dry climate and socio-economic influences in Australia remains widely unknown. Here, we find that agriculture activity dominates reactive nitrogen (Nr) emissions to water bodies. Such emissions not only contribute to deteriorating water quality in Southeastern Australia but also harm marine ecosystems, including the Great Barrier Reef, a World Natural Heritage site. A dry and warm climate reduces the share of Nr emitted directly to water bodies; however, it increases the Nr concentration in surface water due to reduced water volume, leading to a 3-fold higher water Nr concentration compared to major rivers globally, e.g., in the US or China. Business-as-usual socioeconomic development would increase the total Nr emitted to surface water by at least 43% by 2050, while effective mitigation measures could reduce N runoff by about 27%. Advanced agricultural management strategies should be considered to reduce future environmental pressures due to N runoff in Australia.

Quantifying the Effects of Climate Factors on Carbon Monoxide Poisoning: A Retrospective Study in Taiwan.

Background: Carbon monoxide (CO) poisoning is the leading cause of poisoning death worldwide, but associations between CO poisoning and weather remain unclear. Objective: To quantify the influence of climate parameters (e.g., temperature, relative humidity, and wind speed) on the incidence risk of acute CO poisoning in Taiwan. Methods: We used negative binomial mixed models (NBMMs) to evaluate the influence of weather parameters on the incidence risk of acute CO poisoning. Subgroup analyses were conducted, based on the seasonality and the intentionality of acute CO poisoning cases. Results: We identified a total of 622 patients (mean age: 32.9 years old; female: 51%) with acute CO poisoning in the study hospital. Carbon monoxide poisoning was associated with temperature (beta: -0.0973, rate ratio (RR): 0.9073, p < 0.0001) but not with relative humidity (beta: 0.1290, RR: 1.1377, p = 0.0513) or wind speed (beta: -0.4195, RR: 0.6574, p = 0.0806). In the subgroup analyses, temperature was associated with the incidence of intentional CO poisoning (beta: 0.1076, RR: 1.1136, p = 0.0333) in spring and unintentional CO poisoning (beta: -0.1865, RR: 0.8299, p = 0.0184) in winter. Conclusion: Changes in temperature affect the incidence risk for acute CO poisoning, but the impact varies with different seasons and intentionality in Taiwan. Our findings quantify the effects of climate factors and provide fundamental evidence for healthcare providers to develop preventative strategies to reduce acute CO poisoning events.

Investigation of black carbon climate effects in the Arctic in winter and spring.

Black carbon (BC) exerts a potential influence on climate, especially in the Arctic, where the environment is very sensitive to climate change. Therefore, the study of climate effects of BC in this region is particularly important. In this study, numerical simulations were performed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in the Arctic in winter and spring for two years to investigate the atmospheric BC causing changes in surface radiation, meteorology, and atmospheric stability. Generally, WRF-Chem well reproduced the temporal variations of meteorological variables and BC concentration. Numerical simulations showed that BC concentrations in the Arctic in winter were mostly higher than those in spring, and the BC-induced near-surface temperature changes were also stronger. The effects of BC on near-surface water vapor mixing ratio were consistent with the spatial pattern of near-surface temperature changes. That was probably the result of the regional circulation anomaly due to the temperature changes. Additionally, the distributions of near-surface temperature changes and horizontal wind changes also reflected in the distribution of planetary boundary layer height. Ultimately, this study revealed that the downward longwave radiation related to cloudiness changes played an important role for driving near-surface temperature in the Arctic in winter. While in spring, the relatively less changes in near-surface temperature may be the result of the mutual compensation between the surface longwave and shortwave radiation effects.

Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses.

Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.

Warming weather changes the chemical composition of oat hulls.

The current threats of climate change are driving attention away from the petrochemical industry towards more sustainable and bio-based production processes for fuels and speciality chemicals. These processes require suitable low-cost starting material. One potential material assessed here is the oat hull. Its overall chemical composition has so far not been fully characterized. Furthermore, it is not known how it is affected by extreme weather events. Oat hulls (Kerstin and Galant varieties) grown during 'normal' weather years (2016 and 2017) are compared to the harvest of the warmer and drier year (2018). Standard methods for determination of plant chemical composition, with focus on carbohydrate composition, are utilized. Oat hulls grown in 'normal' weather conditions (2017) are rich in lignocellulose (84%), consisting of 35% hemicellulose, 25% lignin and 23% cellulose. Arabinoxylan was found to be the major biopolymer (32%). However, this composition is greatly influenced by weather variations during the oat growth phase. A lignocellulose reduction of 25% was recorded in the warmer and drier 2018 harvest. Additionally, a 6.6-fold increase in starch content, a four-fold increase in protein content and a 60% decrease in phenolic content was noted. Due to its high lignocellulose composition, with an exceptionally large hemicellulose fraction, the chemical composition of oat hulls is unique among agricultural by-products. However, this characteristic is significantly reduced when grown in warmer and drier weather, which could compromise its suitability for use in a successful biorefinery.

Differentiation of key biomarkers in tea infusions using a target/nontarget gas chromatography/mass spectrometry workflow.

Climatic conditions affect the chemical composition of edible crops, which can impact flavor, nutrition and overall consumer preferences. To understand these effects new data analysis software capable of tracking hundreds of compounds across years of samples under various environmental conditions is needed. Our recently developed mass spectral (MS) subtraction algorithms have been used with spectral deconvolution to efficiently analyze complex samples by 2-dimensional gas chromatography/mass spectrometry (GC-GC/MS). In this paper, we address the accuracy of identifying target and nontarget compounds by GC/MS. Findings indicate that Yunnan tea contains higher concentrations of floral compounds. In contrast, Fujian tea contains higher concentrations of compounds that exhibit fruity characteristics, but contains much less monoterpenes. Principal components analysis shows that seasonal changes in climate impact tea plants similarly despite location differences. For example, spring teas contained more of the sweet, floral and fruity compounds compared to summer teas, which had higher concentrations of green, woody, herbal compounds.

[Climate-sensitive diseases in Brazil and the world: systematic reviewEnfermedades sensibles al clima en Brasil y el mundo: revisión sistemática]. / Doenças sensíveis ao clima no Brasil e no mundo: revisão sistemática.

OBJECTIVE: To survey the literature regarding climate-sensitive diseases (CSD) and the impacts of climate changes on health. METHOD: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The Lilacs, SciELO, Scopus, and PubMed databases were searched in July 2017 without temporal restrictions for articles published in in Portuguese, English and Spanish. The following search strategy was used in all databases: (climate) AND (disease) AND (sensitive). RESULTS: The systematic review included 106 articles, most of which focused on dengue, malaria, and respiratory and cardiovascular diseases. The most commonly studied climate variables were temperature and precipitation. The studies revealed a relationship between the incidence of certain diseases, especially cardiovascular and respiratory diseases, dengue, malaria, and arboviral diseases, and climate conditions in different regions of the world. This relationship was analyzed considering both past data on the incidence of diseases and climate variables and projections regarding the future incidence of diseases according to expected climate variations. A greater number of studies was performed by authors originating from developed countries. The world regions most often studied were China, the United States, Australia, and Brazil. CONCLUSIONS: Despite the increase in the number of published articles on this theme, a greater number of climate and environmental variables must be studied, with expansion of studies to additional regions in the world.

OBJETIVOS: Hacer un examen de las publicaciones sobre las enfermedades sensibles al clima y los efectos de las alteraciones climáticas sobre la salud. MÉTODO: La revisión sistemática se efectuó de conformidad con el método basado en elementos de notificación preferidos para revisiones sistemáticas y metanálisis (PRISMA, por su sigla en inglés). Las búsquedas se realizaron en las bases LILACS, PubMed, Scopus y SciELO en julio del 2017, sin limitaciones de tiempo. En todas las bases se utilizó la siguiente estrategia de búsqueda: (climate) AND (disease) AND (sensitive). Las búsquedas se realizaron en inglés, español y portugués. RESULTADOS: Se seleccionaron 106 publicaciones. Las enfermedades más estudiadas fueron el dengue, la malaria y las enfermedades cardiovasculares y respiratorias. Las variables climáticas más estudiadas fueron la temperatura y las precipitaciones. Los estudios mostraron una relación entre la incidencia de determinadas de enfermedades, principalmente de las enfermedades cardiovasculares y respiratorias, el dengue, la malaria y las enfermedades arbovirales, y las condiciones climáticas en diferentes regiones del mundo. Esa relación se analizó tanto con datos pasados de incidencia de enfermedades y variables climáticas como con una proyección de la incidencia futura de enfermedades, de acuerdo con las variaciones previstas del clima. Se encontró un mayor número de estudios realizados por autores oriundos de países desarrollados. Los lugares estudiados con mayor frecuencia fueron Australia, Brasil, China y Estados Unidos. CONCLUSIONES: A pesar del aumento del número de artículos publicados sobre el tema, es preciso enfocarse en un mayor número de variables climáticas y ambientales, y ampliar los estudios a otras regiones del mundo.

Doenças sensíveis ao clima no Brasil e no mundo: revisão sistemática / Climate-sensitive diseases in Brazil and the world: systematic review / Enfermedades sensibles al clima en Brasil y el mundo: revisión sistemática

RESUMO Objetivos. Fazer um levantamento da literatura existente acerca das doenças sensíveis ao clima (DSC) e dos impactos das alterações climáticas sobre a saúde. Método. A revisão sistemática foi conduzida conforme a metodologia PRISMA. As buscas foram realizadas nas bases LILACS, PubMed, Scopus e SciELO em julho de 2017, sem restrição temporal. Em todas as bases utilizou-se a seguinte estratégia de busca: (climate) AND (disease) AND (sensitive). As buscas foram realizadas em inglês, espanhol e português. Resultados. Foram selecionadas 106 publicações. As doenças mais estudadas foram dengue, malária e doenças respiratórias e cardiovasculares. As variáveis climáticas mais estudadas foram temperatura e precipitação. Os estudos mostraram uma relação entre a incidência de determinadas de doenças, principalmente doenças cardiovasculares e respiratórias, dengue, malária e arboviroses, e as condições climáticas em diferentes regiões do mundo. Essa relação foi analisada considerando tanto dados pretéritos de incidência de doenças e variáveis climáticas como pela projeção futura de incidência de doenças de acordo com variações previstas do clima. Identificou-se um número maior de estudos realizados por autores oriundos de países desenvolvidos. Os locais estudados com maior frequência foram China, Estados Unidos, Austrália e Brasil. Conclusões. Apesar do aumento no número de artigos publicados sobre o tema, é preciso enfocar um número maior de variáveis climáticas e ambientais e expandir os estudos para outras regiões do globo.

ABSTRACT Objective. To survey the literature regarding climate-sensitive diseases (CSD) and the impacts of climate changes on health. Method. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The Lilacs, SciELO, Scopus, and PubMed databases were searched in July 2017 without temporal restrictions for articles published in in Portuguese, English and Spanish. The following search strategy was used in all databases: (climate) AND (disease) AND (sensitive). Results. The systematic review included 106 articles, most of which focused on dengue, malaria, and respiratory and cardiovascular diseases. The most commonly studied climate variables were temperature and precipitation. The studies revealed a relationship between the incidence of certain diseases, especially cardiovascular and respiratory diseases, dengue, malaria, and arboviral diseases, and climate conditions in different regions of the world. This relationship was analyzed considering both past data on the incidence of diseases and climate variables and projections regarding the future incidence of diseases according to expected climate variations. A greater number of studies was performed by authors originating from developed countries. The world regions most often studied were China, the United States, Australia, and Brazil. Conclusions. Despite the increase in the number of published articles on this theme, a greater number of climate and environmental variables must be studied, with expansion of studies to additional regions in the world.

RESUMEN Objetivos. Hacer un examen de las publicaciones sobre las enfermedades sensibles al clima y los efectos de las alteraciones climáticas sobre la salud Método. La revisión sistemática se efectuó de conformidad con el método basado en elementos de notificación preferidos para revisiones sistemáticas y metanálisis (PRISMA, por su sigla en inglés). Las búsquedas se realizaron en las bases LILACS, PubMed, Scopus y SciELO en julio del 2017, sin limitaciones de tiempo. En todas las bases se utilizó la siguiente estrategia de búsqueda: (climate) AND (disease) AND (sensitive). Las búsquedas se realizaron en inglés, español y portugués. Resultados. Se seleccionaron 106 publicaciones. Las enfermedades más estudiadas fueron el dengue, la malaria y las enfermedades cardiovasculares y respiratorias. Las variables climáticas más estudiadas fueron la temperatura y las precipitaciones. Los estudios mostraron una relación entre la incidencia de determinadas de enfermedades, principalmente de las enfermedades cardiovasculares y respiratorias, el dengue, la malaria y las enfermedades arbovirales, y las condiciones climáticas en diferentes regiones del mundo. Esa relación se analizó tanto con datos pasados de incidencia de enfermedades y variables climáticas como con una proyección de la incidencia futura de enfermedades, de acuerdo con las variaciones previstas del clima. Se encontró un mayor número de estudios realizados por autores oriundos de países desarrollados. Los lugares estudiados con mayor frecuencia fueron Australia, Brasil, China y Estados Unidos. Conclusiones. A pesar del aumento del número de artículos publicados sobre el tema, es preciso enfocarse en un mayor número de variables climáticas y ambientales, y ampliar los estudios a otras regiones del mundo.

Tendencia espacial y temporal de eventos climáticos extremos en el valle geográfico del río cauca / Spatial and temporal trends of extreme climate events in geographical valley of cauca river

Los eventos climáticos extremos pueden incrementar la ocurrencia del dengue y de enfermedades diarreicas agudas, en áreas altamente sensibles, con poco nivel de adaptación a condiciones cambiantes, bajo el escenario del cambio climático. El objetivo de este estudio fue describir la tendencia espacial y temporal de los eventos extremos de temperatura y de precipitación en el valle geográfico del río Cauca. Se controló la calidad y la homogenización de los datos climáticos. Se desarrolló un análisis robusto no paramétrico de tendencia de eventos climáticos extremos para precipitación y temperatura. Se analizaron 24 estaciones climatológicas en el Valle geográfico del río Cauca. El análisis regional para precipitación y temperatura mostró una tendencia al incremento de los índices de eventos extremos y el análisis local identificó una distribución no homogénea, en el área de estudio. Los resultados se discutieron en virtud de los posibles impactos en salud, específicamente, para dengue y enfermedad diarreica aguda. El aumento de los días lluviosos y de la cantidad de precipitación podrían generar un aumento en la densidad vectorial y la longevidad larval de Aedes aegypti, además causar el desbordamiento de ríos y canales, con combinación de aguas servidas y resuspensión de sólidos, produciendo el aumento de microorganismos patógenos en el agua de consumo. Adicionalmente, la tendencia al incremento de la temperatura podría acortar el ciclo de vida del Aedes y la replicación interna del virus con mayor probabilidad de transmisión del dengue, al mismo tiempo, que aumentaría la sobrevida de bacterias y de protozoos en aguas negras, superficiales y suelo, aumentando la ocurrencia de las EDA.

Extreme climate events can impact the occurrence of dengue and diarrheal diseases. The objective of this paper was to describe the spatial and temporal trend of extreme temperature and precipitation events in the geographical Valley of Cauca River. Quality and homogenization of climate data was monitored. Robust nonparametric trend analysis of extreme weather events for precipitation and temperature was developed. 24 weather stations were analyzed in the geographical Valle del Cauca River. The regional trend analysis showed a trend of increasing rates of extreme events for precipitation and temperature. Meanwhile, local analysis identified that this trend is not homogeneous in the study area. The rise in volume of precipitation and in the number of rainy days can increase Aedes aegypti, density and larval longevity and also cause overflowing of rivers and canals, with combination of sewage and resuspension of solids and pathogenic microorganisms in water. In addition, the rise in temperature shortens Aedes life cycle and viral replication in mosquitoes with higher probability of dengue transmission and meanwhile increases the survival of bacteria and protozoa in surface sewage and soil causing more occurrence of EDA.

Effect of a fish stock's demographic structure on offspring survival and sensitivity to climate.

Commercial fishing generally removes large and old individuals from fish stocks, reducing mean age and age diversity among spawners. It is feared that these demographic changes lead to lower and more variable recruitment to the stocks. A key proposed pathway is that juvenation and reduced size distribution causes reduced ranges in spawning period, spawning location, and egg buoyancy; this is proposed to lead to reduced spatial distribution of fish eggs and larvae, more homogeneous ambient environmental conditions within each year-class, and reduced buffering against negative environmental influences. However, few, if any, studies have confirmed a causal link from spawning stock demographic structure through egg and larval distribution to year class strength at recruitment. We here show that high mean age and size in the spawning stock of Barents Sea cod (Gadus morhua) is positively associated with high abundance and wide spatiotemporal distribution of cod eggs. We find, however, no support for the hypothesis that a wide egg distribution leads to higher recruitment or a weaker recruitment-temperature correlation. These results are based on statistical analyses of a spatially resolved data set on cod eggs covering a period (1959-1993) with large changes in biomass and demographic structure of spawners. The analyses also account for significant effects of spawning stock biomass and a liver condition index on egg abundance and distribution. Our results suggest that the buffering effect of a geographically wide distribution of eggs and larvae on fish recruitment may be insignificant compared with other impacts.

When three traits make a line: evolution of phenotypic plasticity and genetic assimilation through linear reaction norms in stochastic environments.

Genetic assimilation emerges from selection on phenotypic plasticity. Yet, commonly used quantitative genetics models of linear reaction norms considering intercept and slope as traits do not mimic the full process of genetic assimilation. We argue that intercept-slope reaction norm models are insufficient representations of genetic effects on linear reaction norms and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead, we suggest a model with three traits representing genetic effects that, respectively, (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually becomes equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs of maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population.