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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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