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Climate change has profound impacts on marine biodiversity and biodiversity changes in turn might affect the community sensitivity to impacts of abiotic changes. We used mesocosm experiments and Next Generation Sequencing to study the response of the natural Baltic and Mediterranean unicellular eukaryotic plankton communities (control and +6°C heat shock) to subsequent salinity changes (-5 psu, +5 psu). The impact on Operational Taxonomic Unit (OTU) richness, taxonomic and functional composition and rRNA:rDNA ratios were examined. Our results showed that heat shock leads to lower OTU richness (21% fewer OTUs in the Baltic and 14% fewer in the Mediterranean) and a shift in composition toward pico- and nanophytoplankton and heterotrophic related OTUs. Heat shock also leads to increased rRNA:rDNA ratios for pico- and micrograzers. Less than 18% of shared OTUs were found among the different salinities indicating the crucial role of salinity in shaping communities. The response of rRNA:rDNA ratios varied highly after salinity changes. In both experiments the diversity decrease brought about by heat shock influenced the sensitivity to salinity changes. The heat shock either decreased or increased the sensitivity of the remaining community, depending on whether it removed the more salinity-sensitive or the salinity-tolerant taxa.

AbstractConventional analyses suggest that the metabolism of heterotrophs is thermally more sensitive than that of autotrophs, implying that warming leads to pronounced trophodynamic imbalances. However, these analyses inappropriately combine within- and across-taxa trends. Our new analysis separates these, revealing that 92% of the difference in the apparent thermal sensitivity between autotrophic and heterotrophic protists does indeed arise from within-taxa responses. Fitness differences among taxa adapted to different temperature regimes only partially compensate for the positive biochemical relationship between temperature and growth rate within taxa, supporting the hotter-is-partially-better hypothesis. Our work highlights the importance of separating within- and across-taxa responses when comparing temperature sensitivities between groups, which is relevant to how trophic imbalances and carbon fluxes respond to warming.

Paddy fields are major sources of global atmospheric greenhouse gases, including methane (CH4) and nitrous oxide (N2O). The different phases previous to emission (production, transport, diffusion, dissolution in pore water and ebullition) despite well-established have rarely been measured in field conditions. We examined them and their relationships with temperature, soil traits and plant biomass in a paddy field in Fujian, southeastern China. CH4 emission was positively correlated with CH4 production, plant-mediated transport, ebullition, diffusion, and concentration of dissolved CH4 in porewater and negatively correlated with sulfate concentration, suggesting the potential use of sulfate fertilizers to mitigate CH4 release. Air temperature and humidity, plant stem biomass, and concentrations of soil sulfate, available N, and DOC together accounted for 92% of the variance in CH4 emission, and Eh, pH, and the concentrations of available N and Fe3+, leaf biomass, and air temperature 95% of the N2O emission. Given the positive correlations between CH4 emission and DOC content and plant biomass, reduce the addition of a carbon substrate such as straw and the development of smaller but higher yielding rice genotypes could be viable options for reducing the release of greenhouse gases from paddy fields to the atmosphere.

AbstractOne of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth’s energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60–200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon.

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

Le paludisme est un fardeau majeur pour la santé publique sous les tropiques et pourrait augmenter considérablement en réponse au changement climatique. Les analyses des données du passé récent peuvent élucider comment les variations à court terme des facteurs météorologiques affectent la transmission du paludisme. Cette étude a exploré l'impact de la variabilité climatique sur la transmission du paludisme dans la zone de forêt tropicale humide du comté de Mengla, dans le sud-ouest de la Chine. L'analyse des séries chronologiques écologiques a été réalisée sur des données collectées entre 1971 et 1999. Des modèles de moyenne mobile intégrée autorégressive (ARIMA) ont été utilisés pour évaluer la relation entre les facteurs météorologiques et l'incidence du paludisme. À l'échelle de temps des mois, les prédicteurs de l'incidence du paludisme comprenaient : la température minimale, la température maximale et la fréquence des jours de brouillard. L'effet de la température minimale sur l'incidence du paludisme était plus important pendant les mois froids que pendant les mois chauds. La fréquence des jours de brouillard en octobre a eu un effet positif sur l'incidence du paludisme en mai de l'année suivante. À l'échelle des années, la fréquence annuelle des jours de brouillard était le seul prédicteur météorologique de l'incidence annuelle du paludisme. Pour la première fois, la fréquence des jours de brouillard s'est avérée être un prédicteur de l'incidence du paludisme dans une zone de forêt tropicale. L'effet retardé d'un an du brouillard sur la transmission du paludisme peut impliquer de fournir de l'eau et de maintenir des sites de reproduction aquatiques pour les moustiques dans les périodes vulnérables où il y a peu de précipitations pendant les saisons sèches de 6 mois. Ces résultats doivent être pris en compte dans la prédiction des tendances futures du paludisme pour des zones de forêt tropicale humide similaires dans le monde entier. La malaria es una importante carga de salud pública en los trópicos con el potencial de aumentar significativamente en respuesta al cambio climático. Los análisis de datos del pasado reciente pueden dilucidar cómo las variaciones a corto plazo en los factores climáticos afectan la transmisión de la malaria. Este estudio exploró el impacto de la variabilidad climática en la transmisión de la malaria en el área de la selva tropical del condado de Mengla, suroeste de China. El análisis de series de tiempo ecológico se realizó sobre los datos recopilados entre 1971 y 1999. Se utilizaron modelos de media móvil integrada autorregresiva (ARIMA) para evaluar la relación entre los factores climáticos y la incidencia de la malaria. En la escala de tiempo de meses, los predictores de la incidencia de la malaria incluyeron: temperatura mínima, temperatura máxima y frecuencia del día de niebla. El efecto de la temperatura mínima sobre la incidencia de malaria fue mayor en los meses fríos que en los meses calurosos. La frecuencia del día de niebla en octubre tuvo un efecto positivo en la incidencia de malaria en mayo del año siguiente. En la escala de tiempo de años, la frecuencia anual del día de niebla fue el único predictor meteorológico de la incidencia anual de malaria. Por primera vez, se descubrió que la frecuencia del día de niebla era un predictor de la incidencia de malaria en un área de selva tropical. El efecto retardado de un año de la niebla en la transmisión de la malaria puede implicar proporcionar entrada de agua y mantener sitios de reproducción acuáticos para mosquitos en momentos vulnerables cuando hay poca lluvia en las estaciones secas de 6 meses. Estos hallazgos deben considerarse en la predicción de patrones futuros de malaria para áreas de selva tropical similares en todo el mundo. Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China.Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence.At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria.Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide. تمثل الملاريا عبئًا كبيرًا على الصحة العامة في المناطق المدارية مع إمكانية حدوث زيادة كبيرة في الاستجابة لتغير المناخ. يمكن أن توضح تحليلات البيانات من الماضي القريب كيف تؤثر التغيرات قصيرة الأجل في عوامل الطقس على انتقال الملاريا. استكشفت هذه الدراسة تأثير تقلب المناخ على انتقال الملاريا في منطقة الغابات الاستوائية المطيرة في مقاطعة منغلا، جنوب غرب الصين. تم إجراء تحليل السلاسل الزمنية البيئية على البيانات التي تم جمعها بين عامي 1971 و 1999. تم استخدام نماذج المتوسط المتحرك المتكامل الانحداري التلقائي (ARIMA) لتقييم العلاقة بين عوامل الطقس وحدوث الملاريا. على المقياس الزمني للأشهر، تضمنت التنبؤات بحدوث الملاريا: الحد الأدنى لدرجة الحرارة والحد الأقصى لدرجة الحرارة وتكرار يوم الضباب. كان تأثير الحد الأدنى لدرجة الحرارة على الإصابة بالملاريا أكبر في الأشهر الباردة منه في الأشهر الحارة. كان لتكرار يوم الضباب في أكتوبر تأثير إيجابي على الإصابة بالملاريا في مايو من العام التالي. على المقياس الزمني للسنوات، كان تواتر يوم الضباب السنوي هو مؤشر الطقس الوحيد للإصابة السنوية بالملاريا. تم العثور على تواتر يوم الضباب لأول مرة كمؤشر للإصابة بالملاريا في منطقة الغابات المطيرة. قد يتضمن التأثير المتأخر لمدة عام للضباب على انتقال الملاريا توفير مدخلات المياه والحفاظ على مواقع التكاثر المائي للبعوض في الأوقات الهشة عندما يكون هناك هطول أمطار قليل في مواسم الجفاف لمدة 6 أشهر. وينبغي النظر في هذه النتائج عند التنبؤ بالأنماط المستقبلية للملاريا في مناطق الغابات الاستوائية المطيرة المماثلة في جميع أنحاء العالم.