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The Central-Pacific (CP) and Eastern-Pacific (EP) types of El Niño-Southern Oscillation (ENSO) and their ocean-atmosphere effect cause diverse responses in the hydroclimatological patterns of specific regions. Given the impact of ENSO diversity on the North Atlantic Oscillation (NAO), this study aimed to determine the relationship between the ENSO-NAO teleconnection and the ENSO-influenced precipitation patterns in Colombia during the December-February period. Precipitation data from 1981 to 2023, obtained from the Climate Hazards Group (CHIRPS), were analyzed using nine ENSO and NAO indices spanning from 1951 to 2023. Using Pearson's correlation and mutual information (MI) techniques, nine scenarios were devised, encompassing the CP and EP ENSO events, neutral years, and volcanic eruptions. The results suggest a shift in the direction of the ENSO-NAO relationship when distinguishing between the CP and EP events. Higher linear correlations were observed in the CP ENSO scenarios (r > 0.65) using the MEI and BEST indices, while lower correlations were observed when considering EP events along with the Niño 3 and Niño 1.2 indices. MI show difference in relationships based on the event type and the ENSO index used. Notably, an increase in the non-linear relationship was observed for the EP scenarios with respect to correlation. Both teleconnections followed a similar pattern, exhibiting a more substantial impact during CP ENSO events. This highlights the significance of investigating the impacts of ENSO on hydrometeorological variables in the context of adapting to climate change, while acknowledging the intricate diversity inherent to the ENSO phenomenon.

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Climate change has diversified negative implications on environmental sustainability and water availability. Assessing the impacts of climate change is crucial to enhance resilience and future preparedness particularly at a watershed scale. Therefore, the goal of this study is to evaluate the impact of climate change on the water balance components and extreme events in Piabanha watershed in the Brazilian Atlantic Forest. In this study, extreme climate change scenarios were developed using a wide array of global climate models acquired from the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Reports (AR6). Two extreme climate change scenarios, DryHot and WetCool, were integrated into the Soil and Water Assessment Tools (SWAT) hydrological model to evaluate their impacts on the hydrological dynamics in the watershed. The baseline SWAT model was first developed and evaluated using different model performance evaluation metrics such as coefficient of determination (R2), Nash-Sutcliffe (NSC), and Kling-Gupta efficiency coefficient (KGE). The model results illustrated an excellent model performance with metric values reaching 0.89 and 0.64 for monthly and daily time steps respectively in the calibration (2008 to 2017) and validation (2018 to 2023) periods. The findings of future climate change impacts assessment underscored an increase in temperature and shifts in precipitation patterns. In terms of streamflow, high-flow events may experience a 47.3 % increase, while low-flows could see an 76.6 % reduction. In the DryHot scenario, annual precipitation declines from 1657 to 1420 mm, with evapotranspiration reaching 54 % of precipitation, marking a 9 % rise compared to the baseline. Such changes could induce water stress in plants and lead to modifications on structural attributes of the ecosystem recognized as the Atlantic rainforest. This study established boundaries concerning the effects of climate change and highlighted the need for proactive adaptation strategies and mitigation measures to minimize the potential adverse impacts in the study watershed.

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Argentina has a relevant international role as a producer of agricultural commodities. Buenos Aires is the province with the largest cultivated area of cereals and oilseeds of the country. Rainfed crops depend exclusively on green water, meaning a comparative advantage for Buenos Aires province. The green virtual water content in the crops produced in Buenos Aires has implications for water allocation at international level. A great amount of countries depends on the Argentinean rainfed agriculture. Therefore, it is important to understand the effects of climate variations on Argentinean crop production at local level and the role of rainfed crops in regional and international trade. We analysed the temporal and territorial variations of crops green water demand in a climatic variability context and their influence on the water footprint. The green water footprint of the main crops of Buenos Aires was assessed, including soybeans, maize, sunflower, wheat and barley, in different climatic conditions: for the period 2008-2018, which include a dry year, a humid year and an ordinary year. A dataset about the green water footprint at municipality level was provided, and the results were presented on maps for each crop and for the different climatic conditions. The relevance of green water of main crops in the world water-dependent supply chains was shown. This comprehensive green water footprint assessment provides a useful database for researchers, companies and policy makers in Argentina and beyond.

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At the end of summer 2020, a moderate (~105 cells L-1) bloom of potential fish-killing Karenia spp. was detected in samples from a 24 h study focused on Dinophysis spp. in the outer reaches of the Pitipalena-Añihue Marine Protected Area. Previous Karenia events with devastating effects on caged salmon and the wild fauna of Chilean Patagonia had been restricted to offshore waters, eventually reaching the southern coasts of Chiloé Island through the channel connecting the Chiloé Inland Sea to the Pacific Ocean. This event occurred at the onset of the COVID-19 lockdown when monitoring activities were slackened. A few salmon mortalities were related to other fish-killing species (e.g., Margalefidinium polykrikoides). As in the major Karenia event in 1999, the austral summer of 2020 was characterised by negative anomalies in rainfall and river outflow and a severe drought in March. Karenia spp. appeared to have been advected in a warm (14-15 °C) surface layer of estuarine saline water (S > 21). A lack of daily vertical migration patterns and cells dispersed through the whole water column suggested a declining population. Satellite images confirmed the decline, but gave evidence of dynamic multifrontal patterns of temperature and chl a distribution. A conceptual circulation model is proposed to explain the hypothetical retention of the Karenia bloom by a coastally generated eddy coupled with the semidiurnal tides at the mouth of Pitipalena Fjord. Thermal fronts generated by (topographically induced) upwelling around the Tic Toc Seamount are proposed as hot spots for the accumulation of swimming dinoflagellates in summer in the southern Chiloé Inland Sea. The results here provide helpful information on the environmental conditions and water column structure favouring Karenia occurrence. Thermohaline properties in the surface layer in summer can be used to develop a risk index (positive if the EFW layer is thin or absent).

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A methodological framework is presented for the assessment of beach vulnerability to climate variability and change on small touristic islands. Based on the development of a coastal vulnerability index (CVI) fueled by open-source Earth Observations and social media information, it includes both physical and socio-economic characteristics of the shoreline. In a pilot study in the U.S. Virgin Islands (USVIs), most beaches were found to be vulnerable to erosion. The CVI was utilized to rank the most likely vulnerable beaches, which were then studied using historic geomorphologic data; these beaches were confirmed to be predominantly eroding. Significant erosion is projected as sea levels rise; for example, by 2050 under the RCP8.5 scenario, more than 50% of the 30 most vulnerable USVI beaches will erode by 50-100% of their current maximum width. The framework is designed to be used in vulnerable coastal settings that have limited financial and human resources.

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Climate change threatens agriculture and it remains a present global challenge to food security and Sustainable Development Goals. The potential impact on the supply of crops such as rice is seen as a major food security issue that requires intervention on several fronts. The literature on rice production, climate variations and climate change show several studies outlining various impacts on rice supply as a result of variations in temperature and rainfall. This study intends to further explore the impacts on rice production caused by temperature changes and rainfall variation by analyzing and modelling the production of rice by the top rice-producing countries globally. A time series of the national rice production and yield along with national average annual temperature and rainfall were sourced for 15 major rice-producing countries. The trends of the time series were then compared between the rice productivity variables and temperature and rainfall. A panel regression model was also developed to further assess the relationship between rice production and temperature and rainfall. The time series showed that rice production and yield are increasing for the majority of the countries analyzed. The panel regression model however showed that continued increase in temperature can result in decreased production of rice and that rainfall volume directly impacts rice output and therefore shows rice production is highly susceptible to flooding and drought events caused by climate variabilities.

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Comparing the thermal tolerance and performance of native and invasive species from varying climatic origins may explain why some native and invasive species can coexist. We compared the thermal niches of an invasive and native ant species. The Argentine ant (Linepithema humile) is an invasive species that has spread to Mediterranean climates worldwide, where it is associated with losses in native arthropod biodiversity. In northern California, long-term surveys of ant biodiversity have shown that the winter ant (Prenolepis imparis) is the native species best able to coexist with Argentine ants. Both species tend hemipteran scales for food, and previous research suggests that these species' coexistence may depend on seasonal partitioning: winter ants are active primarily in the colder winter months, while Argentine ants are active primarily in the warmer months in northern California. We investigated the physiological basis of seasonal partitioning in Argentine and winter ants by a) measuring critical thermal limits, and b) comparing how ant walking speed varies with temperature. While both species had similar CTmax values, we found differences between the two species' critical thermal minima that may allow winter ants to remain functional at ecologically relevant temperatures between 0 and 2.5 °C. We also found that winter ants' walking speeds are significantly less temperature-dependent than those of Argentine ants. Winter ants walk faster than Argentine ants at low temperatures, which may allow the winter ants to remain active and forage at lower winter temperatures. These results suggest that partitioning based on differences in temperature tolerance promotes the winter ant's continued occupation of areas invaded by the Argentine ant.

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Climate variability and change, associated with increasing water demands, can have significant implications for water availability. In the Brazilian semi-arid, eutrophication in reservoirs raises the risk of water scarcity. The reservoirs have also a high seasonal and annual variability of water level and volume, which can have important effects on chlorophyll-a concentration (Chla). Assessing the influence of climate and hydrological variability on phytoplankton growth can be important to find strategies to achieve water security in tropical regions with similar problems. This study explores the potential of machine learning models to predict Chla in reservoirs and to understand their relationship with hydrological and climate variables. The model is based mainly on satellite data, which makes the methodology useful for data-scarce regions. Tree-based ensemble methods had the best performances among six machine learning methods and one parametric model. This performance can be considered satisfactory as classical empirical relationships between Chla and phosphorus may not hold for tropical reservoirs. Water volume and the mix-layer depth are inversely related to Chla, while mean surface temperature, water level, and surface solar radiation have direct relationships with Chla. These findings provide insights on how seasonal climate prediction and reservoir operation might influence water quality in regions supplied by superficial reservoirs.

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The search for genetic materials resistant to adverse weather conditions has been a major focus in studies on species of economic interest. The objective of the present study was to assess the growth and photosynthesis of rubber seedlings clones under two conditions of atmospheric evaporative demand, characterized by fluctuations in temperature (TEMP) and vapor pressure deficit (VPD), associated to two water regimens. Hevea brasiliensis Muell. Arg (RRIM 600 and FX 3864) clones were assessed in two microclimates, at low (TEMP 21.2 ºC and VPD 0.29 Kpa) and high (TEMP 26.9 ºC and VPD 1.49 Kpa) atmospheric evaporative demand, under two water regimens: water deficit and well-watered. Water deficit 50% water availability was sufficient to reduce the net CO2 assimilation rate, leaf area and total chlorophyll of the clones studied that impacted growth in both microclimates. The effects of water deficit on growth and net carbon assimilation rate were intensified under high atmospheric evaporative demand. However, when comparing the two clones studied, RRIM 600 showed greater growth and photosynthesis without water restriction. The FX 3864 clone, despite the high CO2 assimilation values under high atmospheric demand and without water restriction, showed a reduced growth. The results of this study form an important basis for the selection of genotypes with the potential to develop in adverse climatic conditions. In this sense, the RRIM 600 genotype is recommended as a promising material that would best adapt under adverse climatic conditions.

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This essay is a conceptual framework for testing the causal mechanisms of system degradation by metals in the mangrove ecosystem. The Fundão Dam collapse caused massive damage to the marine environment on the Southern Atlantic and Brazilian coast, reaching various kilometers from its origin, becoming a source of contamination. Along this Brazilian coast are vast mangrove areas with high biodiversity, different geomorphology, and distinct ecological functioning. These mangroves support fisheries' productivity in the Tropical South Atlantic, in connection with Abrolhos Reef. Brazil does not have a protocol to monitor environmental damage in this ecosystem, and we proposed to develop a way to identify the impact and quantify it. Along the estuaries, to assess the damage, the plots were demarked in three regions: the upper, middle, and lower estuary, and in both types of forest: fridge and basin. Samples of sediment and leaves were collected bi-monthly to evaluate metal concentrations, especially iron and manganese, the most abundant metals in Fundão Dam. The monitoring also evaluated the forest structure, dynamics of the crabs' population, and flora productivity. First-year monitoring identifies a high concentration of iron or manganese in the sediment above the NOAAs' recommendation in all the estuaries. The concentration of Fe and Mn in sediment varies seasonally in magnitude, concentration, and types of metals between estuaries, sectors, and forests. The behavior of biological indicators in the presence of metals (type and concentration) differed between fauna and flora species. The monitoring recognized that the tailings mining from Fundão Dam impacted all estuaries by different magnitudes and persistence. These differences are due to geomorphology diversity, climate, and oceanographic influences.

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Dengue virus (DENV) is an endemic disease in the hot and humid low-lands of Colombia. We characterize the association of monthly series of dengue cases with indices of El Niño/Southern Oscillation (ENSO) at the tropical Pacific and local climatic variables in Colombia during the period 2007-2017 at different temporal and spatial scales. For estimation purposes, we use lagged cross-correlations (Pearson test), cross-wavelet analysis (wavelet cross spectrum, and wavelet coherence), as well as a novel nonlinear causality method, PCMCI, that allows identifying common causal drivers and links among high dimensional simultaneous and time-lagged variables. Our results evidence the strong association of DENV cases in Colombia with ENSO indices and with local temperature and rainfall. El Niño (La Niña) phenomenon is related to an increase (decrease) of dengue cases nationally and in most regions and departments, with maximum correlations occurring at shorter time lags in the Pacific and Andes regions, closer to the Pacific Ocean. This association is mainly explained by the ENSO-driven increase in temperature and decrease in rainfall, especially in the Andes and Pacific regions. The influence of ENSO is not stationary, given the reduction of DENV cases since 2005, and that local climate variables vary in space and time, which prevents to extrapolate results from one region to another. The association between DENV and ENSO varies at national and regional scales when data are disaggregated by seasons, being stronger in DJF and weaker in SON. Overall, the Pacific and Andes regions control the relationship between dengue dynamics and ENSO at national scale. Cross-wavelet analysis indicates that the ENSO-DENV relation in Colombia exhibits a strong coherence in the 12 to 16-months frequency band, which implies the frequency locking between the annual cycle and the interannual (ENSO) timescales. Results of nonlinear causality metrics reveal the complex concomitant effects of ENSO and local climate variables, while offering new insights to develop early warning systems for DENV in Colombia.

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The Brazil-nut tree (Bertholletia excelsa) is native to the Amazon rainforest, and its fruit production varies naturally with climatic conditions. Our aim was to evaluate the temporal variation in Brazil-nut production associated with climatic variables, including the strong El Niño of 2015/2016. The study was carried out in two 9-ha permanent plots in the northeastern Brazilian Amazon from 2007 to 2018: one in forest (12-year monitoring) and the other in savannah/forest transition (eight years). Overall, we monitored fruit production of 205 trees with diameter at breast height ≥ 50 cm. Annual fruit production was related to temporal series (2005-2018) of climatic data (the Oceanic Niño Index; and precipitation and air temperature from two local meteorological stations). Average fruit production per tree in 2017 was eight times lower than in 2015 and two times lower than the general average for both sites, and was significantly associated to the El Niño of 2015/2016, that increased average maximum monthly temperature and reduced the precipitation in the region, extending the dry season from three to six months. Years with higher and lower fruit production per tree coincided in both sites. Annual fruit production was significantly and negatively correlated with thermal anomalies that occurred in the third semester prior to harvest monitoring. Years with higher production were related with predominance of neutrality or the La Niña phenomenon at the global scale, and higher rainfall at the local scale. The relationship of fruit production with climate was independent of the local habitat.

A castanheira-da-amazônia (Bertholletia excelsa) é nativa da floresta amazônica e sua produção de frutos varia naturalmente com as condições climáticas. Nosso objetivo foi avaliar a variação temporal na produção de frutos da castanheira associada a variáveis ​​climáticas, incluindo o forte El Nino de 2015/2016. O estudo foi realizado em parcelas permanentes de 9 ha de 2007 a 2018, uma localizada em floresta (12 anos de monitoramento) e a outra em transição floresta/savana (oito anos). Em total, monitoramos 205 castanheiras com diâmetro à altura do peito ≥ 50 cm. A produção anual de frutos foi relacionada a séries temporais (2005-2018) de dados climáticos (o Índice Oceânico Niño; e a precipitação e temperatura do ar de duas estações meteorológicas locais). A produção média por castanheira em 2017 foi oito vezes menor que em 2015 e duas vezes menor que a média geral nos dois sítios, e foi significativamente associada ao El Niño de 2015/2016, que causou aumento na temperatura máxima mensal e redução na precipitação regional, prolongando a estação seca de três para seis meses. Os anos com maior e menor produção média por castanheira foram os mesmos nos dois ambientes. A produção anual de frutos foi significativa e negativamente correlacionada com as anomalias térmicas ocorridas no terceiro semestre antes da colheita. Anos de maior produção foram relacionados com predominância de neutralidade ou do fenômeno La Niña em escala global, e aumento da precipitação em nível local. A relação entre produção de frutos e clima foi independente do ambiente local.

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Amazonia experienced unusually devastating fires in August 2019, leading to huge regional and global environmental and economic losses. The increase in fires has been largely attributed to anthropogenic deforestation, but anomalous climate conditions could also have contributed. This study investigates the climate influence on Amazonia fires in August 2019 and underlying mechanisms, based on statistical correlation and multiple linear regression analyses of 2001-2019 satellite-based fire products and multiple observational or reanalyzed climate datasets. Positive fire anomalies in August 2019 were mainly located in southern Amazonia. These anomalies were mainly driven by low precipitation and relative humidity, which increased fuel dryness and contributed to 38.9 ± 9.5% of the 2019 anomaly in pyrogenic carbon emissions over the southern Amazonia. The dry conditions were associated with southerly wind anomalies over southern Amazonia that suppressed the climatological southward transport of water vapor originating from the Atlantic. The southerly wind anomalies were caused by the combination of a Gill-type cyclonic response to the warmer North Atlantic sea surface temperature (SST), and enhancement of the Walker and Hadley circulations over South America due to the colder SST in the eastern Pacific, and a mid-latitude wave train triggered by the warmer condition in the western Indian Ocean. Our study highlights, for the first time, the important role of Indian Ocean SST for fires in Amazonia. It also reveals how cold SST anomalies in the tropical eastern Pacific link the warm phase of the El Niño-Southern Oscillation (ENSO) in the preceding December-January to the dry-season fires in Amazonia. Our findings can develop theoretical basis of global tropical SST-based fire prediction, and have potential to improve prediction skill of extreme fires in Amazonia and thus to take steps to mitigate their impacts which is urgency given that dry conditions led to the extreme fires are becoming common in Amazonia.

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High-quality measured weather data (MWD) are essential for long-term and in-season crop model applications. When MWD is not available, one alternative for crop simulations is to employ gridded weather data (GWD), which needs to be evaluated a priori. Therefore, this study aimed to evaluate the impact of weather data from two GWD sources (NASA and XAVIER), in the way that they are available for end users, on simulating sugarcane crop performance within the APSIM-Sugar model at traditional sites where sugarcane is grown in Center-South Brazil, compared to simulations with MWD. Besides, this study also evaluated the impact of replacing GWD rainfall by the site-specific measured data on such simulations. A common sugarcane cropping system was repeatedly simulated between 1997 and 2015 for different combinations of climate input. Both NASA and XAVIER appear to be interesting for applications that only require temperature and solar radiation for predictions, such as crop phenology and potential yield. Nonetheless, GWD should be used with caution for crop model applications that rely on accurate estimation of crop water balance, canopy development, and biomass accumulation, at least with crop models that run at a daily time-step. The replacement of gridded rainfall with measured rainfall was pivotal for improving sugarcane simulations, as observed for cane yield, by increasing both agreement (NASA d index from 0.67 to 0.90; XAVIER d from 0.73 to 0.93) and R2 (NASA from 0.35 to 0.76; XAVIER from 0.43 to 0.79) and reducing root mean square errors (RMSE) from 32.8 to 16.3 t/ha when simulated with other variables of NASA data and from 27.9 to 12.7 t/ha when having XAVIER data as input. Therefore, while using both GWD sets without any correction, it is recommended to replace gridded rainfall by measured values, whenever possible, to improve sugarcane simulations in Center-South Brazil.

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Water reservoirs are essential for regional economic development, as populations depend on them for agriculture irrigation, flood control, hydroelectric power generation, water supply for human consumption, and subsistence fishing activities. However, the reservoir environmental quality can be disturbed by enhanced sediment input and trace metal contamination, affecting human health as a consequence of contaminated water and fish consumption. With the purpose to understand the trends and extent of sediment accumulation and trace element contamination in the Oviachic reservoir (OV, northwestern Mexico) since its construction, the temporal variations of sediment accumulation, and As, Cr, Cu, Hg, Ni, Pb, and Zn concentrations, enrichment, and fluxes, were evaluated through the study of two 210Pb-dated sediment cores. We assumed that siltation and trace element contamination were driven by the development of anthropogenic activities in the region within the past ~ 70 years. Elemental concentrations accounted from null to minor enrichment for most elements, but moderate to significant enrichment by Hg. Mercury, As, and Cu fluxes have notably increased since the past decade, most likely because of a combination of anthropogenic and natural processes, including catchment erosion, artisanal gold mining, and recent drought conditions in the region. Arsenic and Hg concentrations may pose deleterious risks to biota in the reservoir, and consequently to humans through fish consumption, for which further biological and toxicological tests are advisable. This study highlights the importance of using sediment dating to assess historical trends of metal contamination and identify possible sources, to support decision-making in programs addressed to reduce environmental and health risks in aquatic ecosystems.

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High Andean wetlands of the elevated plateaus of the Andes Mountains of Chile, Argentina, Perú and Bolivia are true oases that sustain life in this arid region. Despite their ecological value, they have been rarely studied and are vulnerable to climate change and human activities that require groundwater resources. One such activity that may be intensified in the near future is mining for nonmetallic minerals such as lithium, whose worldwide demand is expected to increase with the rise of electric vehicles that need batteries. To determine a baseline of the natural dynamics of these systems, which allows sustainable management, it is essential to understand the spatiotemporal dynamics of these wetlands. In this article, we studied the temporal and spatial dynamics of high Andean wetlands of Chile, with the aim of identifying the key processes that govern their dynamics. To do this, we used time series of Landsat data from 1984 to 2019 to study 10 high Andean wetlands. Furthermore, to characterize the climate variability in these systems, we studied the long-term relation between the changes in water and vegetation areas with rainfall and evaporation variability. It was found that the groundwater reservoir plays a key role in sustaining the high Andean wetlands. Wet years with a period of occurrence of 20-30 years are the years in which the groundwater reservoirs are actually recharged, and in between wet years, the groundwater reservoirs gradually release the water that sustains the aquatic ecosystems. Hence, groundwater exploitation should be carefully designed from a long-term perspective, as groundwater levels could take decades to recover.

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The Brazil-nut tree (Bertholletia excelsa) is native to the Amazon rainforest, and its fruit production varies naturally with climatic conditions. Our aim was to evaluate the temporal variation in Brazil-nut production associated with climatic variables, including the strong El Niño of 2015/2016. The study was carried out in two 9-ha permanent plots in the northeastern Brazilian Amazon from 2007 to 2018: one in forest (12-year monitoring) and the other in savannah/forest transition (eight years). Overall, we monitored fruit production of 205 trees with diameter at breast height ≥ 50 cm. Annual fruit production was related to temporal series (2005-2018) of climatic data (the Oceanic Niño Index; and precipitation and air temperature from two local meteorological stations). Average fruit production per tree in 2017 was eight times lower than in 2015 and two times lower than the general average for both sites, and was significantly associated to the El Niño of 2015/2016, that increased average maximum monthly temperature and reduced the precipitation in the region, extending the dry season from three to six months. Years with higher and lower fruit production per tree coincided in both sites. Annual fruit production was significantly and negatively correlated with thermal anomalies that occurred in the third semester prior to harvest monitoring. Years with higher production were related with predominance of neutrality or the La Niña phenomenon at the global scale, and higher rainfall at the local scale. The relationship of fruit production with climate was independent of the local habitat.(AU)

A castanheira-da-amazônia (Bertholletia excelsa) é nativa da floresta amazônica e sua produção de frutos varia naturalmente com as condições climáticas. Nosso objetivo foi avaliar a variação temporal na produção de frutos da castanheira associada a variáveis ​​climáticas, incluindo o forte El Nino de 2015/2016. O estudo foi realizado em parcelas permanentes de 9 ha de 2007 a 2018, uma localizada em floresta (12 anos de monitoramento) e a outra em transição floresta/savana (oito anos). Em total, monitoramos 205 castanheiras com diâmetro à altura do peito ≥ 50 cm. A produção anual de frutos foi relacionada a séries temporais (2005-2018) de dados climáticos (o Índice Oceânico Niño; e a precipitação e temperatura do ar de duas estações meteorológicas locais). A produção média por castanheira em 2017 foi oito vezes menor que em 2015 e duas vezes menor que a média geral nos dois sítios, e foi significativamente associada ao El Niño de 2015/2016, que causou aumento na temperatura máxima mensal e redução na precipitação regional, prolongando a estação seca de três para seis meses. Os anos com maior e menor produção média por castanheira foram os mesmos nos dois ambientes. A produção anual de frutos foi significativa e negativamente correlacionada com as anomalias térmicas ocorridas no terceiro semestre antes da colheita. Anos de maior produção foram relacionados com predominância de neutralidade ou do fenômeno La Niña em escala global, e aumento da precipitação em nível local. A relação entre produção de frutos e clima foi independente do ambiente local.(AU)

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Floods are one of the worst natural disasters in the world. Colombia is a country that has been greatly affected by this disaster. For example, in the years 2010 and 2011 there was a heavy rainy season, which caused floods that affected at least two million people and there were economic losses of 6.5 million dollars, which is equivalent to 5.7% of the country's Gross Domestic Product (GDP) at that time. The Magdalena River is the most important since 128 municipalities and 43 cities with a population of 6.3 million people, which is 13% of the total population of the country, are located in its basins. For this reason, the objective of the research is to design and implement a model that helps predict flooding over the Magdalena River by examining three techniques of artificial intelligence (Artificial Neuronal Networks, Adaptive Neuro Fuzzy Inference System, Support Vector Machine), and thus determining which of these techniques are the most effective according to the case study. The research was limited only to these three types, due to limitations of time, data, human and financial resources, and technological infrastructure. In the end, it is concluded that the Artificial Neural Networks technique is a suitable option to implement the predictive system as long as it is not very complex and does not require high processing machine. However, to establish a model based on rules to achieve a better interpretability of the floods, the ANFIS model can be used.

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OBJECTIVES: We aim to describe the relationships between climate variables and climate-sensitive diseases (CSDs) in semi-arid regions, highlighting the different main groups of CSDs and their climate patterns. METHODS: This systematic review considered Medline, Science Direct, Scopus and Web of Science. The data collection period was August and September 2019 and included studies published between 2008 and 2019. This study followed a protocol based on the PRISMA statement. Data analysis was done in a qualitative way. RESULTS: The most of works were from Africa, Asia and Iran (71%), where temperature was the main climatic variable. Although the studies provide climatic conditions that are more favorable for the incidence of vector-borne and respiratory diseases, the influence of seasonal patterns on the onset, development and end of CSDs is still poorly understood, especially for gastrointestinal disorders. Moreover, little is known about the impact of droughts on CSDs. CONCLUSIONS: This review summarized the state of art of the relationship between climate and CSDs in semi-arid regions. Moreover, a research agenda was provided, which is fundamental for health policy development, priority setting and public health management.

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Introducción: La variabilidad climática tiene efectos importantes sobre las diferentes actividades económicas que se desarrollan en zonas costeras y que emplean servicios ecosistémicos para su funcionamiento. Actualmente, no existen metodologías integrales que permitan realizar un proceso de valoración teniendo en cuenta todas las variables y las interacciones entre ellas. Objetivo: Proponer una aproximación metodológica que incluya de manera integral las diferentes etapas en el proceso de valoración económica de servicios ecosistémicos en zonas costeras, ante la variabilidad climática. Métodos: Se realizó una revisión bibliográfica, consulta a expertos y se empleó un ejemplo de aplicación usando la actividad turística de buceo con tiburones martillos en la Isla del Coco. Resultados: La aproximación metodológica propuesta inicia con la caracterización socioeconómica y ambiental de la actividad que emplea el recurso natural como insumo, posteriormente se realiza una identificación y caracterización de las variables ambientales que afectan el recurso natural y los efectos que la variación de este recurso tiene sobre la actividad económica. Conclusiones: Las variables que conforman el sistema climático, que tienen relación con los recursos naturales y las actividades económicas, al ser influenciadas por fenómenos externos, producen efectos que deben ser analizados por medio de aproximaciones metodológicas integrales, dentro de las cuales uno de los pasos es la metodología de valoración, que permitan generar recomendaciones de política que contribuyan a minimizar esos efectos.

Introduction: Climate variability has important effects on the different economic activities that take place in marine areas. Currently, there are no comprehensive methodologies to carry out an assessment process that consider all the variables and interactions between them. Objective: To propose a methodological approach that comprehensively includes the different stages in the process of economic valuation of ecosystem services in coastal areas, in the face of climate variability. Methods: A bibliographic review, expert consultations and an application of a methodological example using the impact over shark diving activities at Isla del Coco were conducted. Results: The proposed methodological approach begins with the socio-economic and environmental characterization of the activity that uses a natural resource as input, followed by the identification and characterization of the environmental variables that affect the natural resource and of the effects that the variation of this resource has on the economic activity. Conclusions: The variables that make up the climate system, which relate to natural resources and economic activities, being influenced by external phenomena, produce effects that must be analyzed by comprehensive methodological approximations, within which one of the steps is the valuation methodology, that will allow generating policy recommendations that help to minimize these effects.

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