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The Colombian Andes (CA) are located over the northwestern corner of tropical South America (NW‐TropSA), where land and atmosphere interchange moisture and energy in a complex way owing to the orographic influence on the recycling of moisture over land. We aim to understand where and when water vapor evaporated from land turns into rainfall through moisture recycling, using the Water Accounting Model‐2layers (WAM‐2), an offline model to track atmospheric moisture forced with data from ERA‐5 at its native 0.25° resolution during 1980–2020. We define the spatiotemporal distribution of sources (high evaporation recycle ratios, ϵC) and receptors (high precipitation recycle ratios, ρC) of continental moisture at diverse timescales, including monthly, seasonal, annual and interannual (ENSO). Referring to the regional runs of WAM‐2 over NW‐TropSA (4°S–12°N/80°W–66°W), at elevations above 1,000 m.a.s.l., the CA has a mean annual ρC of 11% (ranging 6%–16%) and a mean annual ϵC of 35% (ranging 27%–40%). Moisture recycling in the CA exhibits a strong annual cycle over the region. The seasonal dynamic of moisture recycling shows two clear‐cut sources of moisture: the eastern foothills of the Eastern and Central ranges of the CA. Both foothills are also regions of high rainfall, although moisture recycling mechanisms differ. Sources of continental moisture grow spatially during September‐October‐November and March‐April‐May. The seasonal availability of moisture recycled coincides with regions where orography interacts with low level jets sourcing humidity. At interannual timescales, sources and receptors of continental moisture in the CA are modulated by the extreme phases of ENSO. Key Points: The orography of the Colombian Andes emerged as a critical factor shaping the interaction between land and atmospheric moisture fluxesFoothills and valleys of the Colombian Andes play a pivotal role in continental moisture recycling, in terms of convergence and divergenceENSO modulates both sources and receptors of continental moisture at interannual timescales [ABSTRACT FROM AUTHOR]

We employ the approach of Roderick and Farquhar (2011) to assess the sensitivity of runoff (R) given changes in precipitation (P), potential evapotranspiration (E p ), and other properties that change the partitioning of P (n) by estimating coefficients that predict the weight of each variable in the relative change of R. We use this framework using different data sources and products for P, actual evapotranspiration (E), and E p within the Amazon River basin to quantify the uncertainty of the hydrologic response at the subcatchment scale. We show that when estimating results from the different combinations of datasets for the entire river basin (at Óbidos), a 10% increase in P would increase R on average 16%, while a 10% increase in E p would decrease R about 6%. In addition, a 10% change in the parameter n would affect the hydrological response of the entire basin around 5%. However, results change from catchment to catchment and are dependent on the combination of datasets. Finally, results suggest that enhanced estimates of E and E p are needed to improve our understanding of the future scenarios of hydrological sensitivity with implications for the quantification of climate change impacts at the regional (subcatchment and subbasin) scale in Amazonia., (© 2020 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences.)

The juvenile dispersal of raptors is a crucial stage that stretches from parental independence to the establishment of the first breeding area. Between 2012 and 2020, 44 juvenile red kites Milvus milvus from the Spanish breeding population were tagged using GPS telemetry to study their dispersal. Juveniles left the parental breeding area at the end of their first summer and performed wandering movements throughout the Iberian Peninsula, returning to the parental breeding area the following year, repeating the same pattern until they settled in their first breeding area. We analyzed the mean distance from the nest, the maximum reached distances, and the traveled distances (daily and hourly) during the first 2 years of dispersal and compared them. Despite the high individual variability, variables describing the dispersal movements of juveniles showed a decreasing trend during the second dispersal year: 80% of individuals reached a shorter maximum distance in the second year, 70% decreased their mean distance to the nest, 65% decreased their hourly traveled distances, and 50% decreased their daily traveled distances. On the other hand, the red kites usually combined wandering movements with the establishment of temporary settlement areas (TSA). The average duration of settlement in the TSAs was 75 ± 40 days (up to 182 days) and was located at 182 ± 168 km from the nest. In those areas, juveniles used 781.0 ± 1895.0 km 2 (KDE 95%). Some of the TSAs were used by several individuals, which suggests that these areas might be good targets for conservation in future management plans., (© The Author(s) 2022. Published by Oxford University Press on behalf of Editorial Office, Current Zoology.)

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., (Copyright © 2021. Published by Elsevier B.V.)

The far Eastern Tropical Pacific (EPAC) and Western Colombia are one of the rainiest places on Earth, and the Choco low-level jet (ChocoJet) is one of the processes that influence the formation of copious precipitation and convection organization in this region. This study investigates the projected changes in precipitation in this region using historical and future simulations based on model output from two models contributing to the Coupled Model Intercomparison Project phase 6 (CMIP6). In close agreement with observations, models simulate that ChocoJet intensity is directly proportional to precipitation in the region. This relationship is also found far inland in Central America, the northwestern part of South America Pacific Coast, and the intermountain valleys of the Colombian Andes. Late 21st century simulations show a southward migration in mean and regional daily precipitation consistent with a decreased ChocoJet intensity. The weaker ChocoJet is related to a projected increase in EPAC tropical sea surface temperatures (SSTs) and an increased frequency and intensity of the warm phase of the Niño 1+2 SST interannual variability. [ABSTRACT FROM AUTHOR]

This paper provides a survey of the literature on the application of Multi-agent Systems (MAS) technology for Smartgrids. Smartgrids represent the next generation electric network, as communities are developing self-sufficient and environmentally friendly energy production. As a cyber-physical system, the development of the vision of Smartgrids requires the resolution of major technical problems; this has fed over a decade of research. Due to the stochastic, intermittent nature of renewable energy resources and the heterogeneity of the agents involved in a Smartgrid, demand and supply management, energy trade and control of grid elements constitute great challenges for stable operation. In addition, in order to offer resilience against faults and attacks, Smartgrids should also have restoration, self-recovery and security capabilities. Multi-agent systems (MAS) technology has been a popular approach to deal with these challenges in Smartgrids, due to their ability to support reasoning in a distributed context. This survey reviews the literature concerning the use of MAS models in each of the relevant research areas related to Smartgrids. The survey explores how researchers have utilized agent-based tools and methods to solve the main problems of Smartgrids. The survey also discusses the challenges in the advancement of Smartgrid technology and identifies the open problems for research from the view of multi-agent systems. [ABSTRACT FROM AUTHOR]

The Gran Chaco ecoregion is South America's largest remaining continuous stretch of dry forest. It has experienced intensive deforestation, mainly in the western part known as the Dry Chaco, resulting in the highest rate of dry-forest loss globally between 2000 and 2012. The replacement of natural vegetation with other land uses modifies the surface's biophysical properties, affecting heat and water fluxes and modifying the regional climate. This study examines land use and land cover changes (LULCCs) in the Dry Chaco from 2001 to 2015 and their effects on local and non-local climate and explores the potential impacts of future agricultural expansion in the region. To this end, Weather Research and Forecasting (WRF) model simulations are performed for two scenarios: the first one evaluates the observed land cover changes between 2001 and 2015 that covered 8 % of the total area of the Dry Chaco; the second scenario assumes an intensive agricultural expansion within the Dry Chaco. In both scenarios, deforestation processes lead to decreases in leaf area index (LAI), reductions in stomatal resistance, and increases in albedo, thus reducing the net surface radiation and, correspondingly, decreasing the turbulent fluxes, suggesting a decline in available energy in the boundary layer. The result is an overall weakening of the water cycle in the Dry Chaco and, most prominently, implying a reduction in precipitation. A feedback loop develops since dry soil absorbs significantly less solar radiation than moist soil. Finally, the simulations suggest that the Dry Chaco will intensify its aridity, extending drier and hotter conditions into the Humid Chaco. [ABSTRACT FROM AUTHOR]

In 2023, most parts of the world experienced exceptional heat. In particular, anomalous warm temperatures and heatwave events were evidenced across South America during the second half of the year. The situation was particularly critical in the Amazon region in terms of not only hydrometeorological drought but also ecological and socioeconomic impacts. In this study, remote-sensing data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to observe the changes in temperature and vegetation across Amazonia during the exceptional drought of 2023. This analysis was based on anomalies in the land surface temperature (LST) and vegetation indices: the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI). The amplitude of the LST (AMP-LST), an indicator of the energy partitioning between the latent and sensible heat flux, and fire counts were also considered. The results show widespread and extreme warming across Amazonia during the austral spring in 2023, accompanied by a decline in vegetation greenness, water stress conditions across northern Amazonia, and an enhanced fire occurrence across central and northern Amazonia. [ABSTRACT FROM AUTHOR]

Andean glaciers are losing mass rapidly but a centennial‐scale context to those rates is lacking. Here we show the extent of >5,500 glaciers during the Little Ice Age chronozone (LIA; c. 1,400 to c. 1,850) and compute an overall area change of −25% from then to year 2000 at an average rate of −36.5 km2 yr−1 or −0.11% yr−1. Glaciers in the Tropical Andes (Peru, Bolivia) have depleted the most; median −56% of LIA area, and the fastest; median −0.16% yr−1. Up to 10 × acceleration in glacier area loss has occurred in Tropical mountain sub‐regions comparing LIA to 2,000 rates to post‐2000 rates. Regional climate controls inter‐regional variability, whereas local factors affect intra‐region glacier response time. Analyzing glacier area change by river basins and by protected areas leads us to suggest that conservation and environmental management strategies should be re‐visited as proglacial areas expand. Plain Language Summary: Andean glaciers are melting fast but how that rate compares in a longer‐term context is unknown. In this study we mapped the extent of >5,500 glaciers during the Little Ice Age, which was the last major glacial advance culminating about c. 150 years ago. We analyzed the change in glacier size and computed overall area change of −25% from the LIA to year 2000 at a rate of −36.5 km2 per year or −0.11% per year. Glaciers within Peru and Bolivia have shrunk the most by median −56% of LIA area, and the fastest by median −0.16% per year. We discuss that these glaciers are depleting and retreating due to climate change but that response is compounded by glacier size, shape and terminus environment effects. As glaciers melt they reveal proglacial landscapes that tend to be highly unstable, impacting water resources, natural hazards and terrestrial and aquatic ecology. Key Points: Little Ice Age (LIA) chronozone extent of >5,500 glaciers mapped from geomorphological evidenceOverall glacier area change of −25% to year 2000 at a rate of −36.5 km2 yr−1 or −0.11% yr−1Up to 10 × acceleration in glacier area loss for Tropical sub‐regions comparing LIA to 2,000 with post‐2000 rates [ABSTRACT FROM AUTHOR]

The comprehensive understanding of propagation patterns of extreme precipitation events (EPEs) is essential for early warning of associated hazards such as floods and landslides. In this study, we utilize climate networks based on an event synchronization measure to investigate the propagation patterns of EPEs over the global land masses, and identify 16 major propagation pathways. We explain them in association with regional weather systems, topographic effects, and travelling Rossby wave patterns. We also demonstrate that the revealed propagation pathways carry substantial EPE predictability in certain areas, such as in the Appalachian, the Andes mountains. Our results help to improve the understanding of key propagation patterns of EPEs, where the global diversity of the propagated patterns of EPEs and corresponding potential predictability provide prior knowledge for predicting EPEs, and demonstrate the power of climate network approaches to study the spatiotemporal connectivity of extreme events in the climate system. [ABSTRACT FROM AUTHOR]

Currently there are several precipitation reconstructions for northern Mexico; however, there is a lack of temperature reconstructions to understand past climate change, the impact on ecosystems and societies, etc. The central region of Chihuahua is located in a transition zone between the Sierra Madre Occidental and the Great Northern Plain, characterized by extreme temperatures and marked seasonal variability. The objectives of this study were (1) to generate a climatic association between variables from reanalysis models and the earlywood series for the center of Chihuahua, (2) to generate a reconstruction of mean temperature, (3) to determine extreme events, and (4) to identify the influence of ocean–atmosphere phenomena. Chronologies were downloaded from the International Tree-Ring Data Bank and climate information from the NLDAS-2 and ClimateNA reanalysis models. The response function was performed using climate models and regional dendrochronological series. A reconstruction of mean temperature was generated, and extreme periods were identified. The representativeness of the reconstruction was evaluated through spatial correlation, and low-frequency events were determined through multitaper spectral analysis and wavelet analysis. The influence of ocean–atmosphere phenomena on temperature reconstruction was analyzed using Pearson correlation, and the influence of ENSO was examined through wavelet coherence analysis. Highly significant correlations were found for maximum, minimum, and mean temperature, as well as for precipitation and relative humidity, before and after the growth year. However, the seasonal period with the highest correlation was found from May to June for mean temperature, which was used to generate the reconstruction from 1775 to 2022. The most extreme periods were 1775, 1801, 1805, 1860, 1892–1894, 1951, 1953–1954, and 2011–2012. Spectral analysis showed significant frequencies of 56.53 and 2.09 years, and wavelet analysis from 0 to 2 years from 1970 to 1980, from 8 to 11 years from 1890 to 1910, and from 30 to 70 years from 1860 to 2022. A significant association was found with the Multivariate ENSO Index phenomenon (r = 0.40; p = 0.009) and Pacific Decadal Oscillation (r = −0.38; p = 0.000). Regarding the ENSO phenomenon, an antiphase association of r = −0.34; p = 0.000 was found, with significant periods of 1 to 4 years from 1770 to 1800, 1845 to 1850, and 1860 to 1900, with periods of 6 to 10 years from 1875 to 1920, and from 6 to 8 years from 1990 to 2000. This study allowed a reconstruction of mean temperature through reanalysis data, as well as a historical characterization of temperature for central Chihuahua beyond the observed records. [ABSTRACT FROM AUTHOR]

This study aims to investigate the hydrodynamic-morphological interactions on a microtidal intermediate-dissipative beach under low to moderate wave energy conditions using field measurements during two climatic seasons. The separate contributions of currents, sea-swell waves, and infragravity waves to high- and low-frequency sediment fluxes were analyzed. The infragravity wave energy was more relevant near the swash zone than in other areas. Although the currents are the primary suspended sediment transport mechanism, the results suggest that the waves are an important driver of sediment suspension from the seabed. The results indicate that Sea-Swell (SS) waves and cross-shore currents are the prevailing hydrodynamic factors in nearshore sediment transport, and the cross-shore suspended sediment transport rates are higher than those in alongshore transport. The submerged bar intensified during the wet season (1–4 November 2018) when the wave height intensities were lower, contrary to the dry season (24–25 March 2018). Significant accretion nearshore was identified (in the subaerial beach) during the wet season when the suspended sediments were greater, the SS-wave heights nearshore were lower, and sediment flux was directed onshore. A notorious erosion was distinguished during the dry season. The most representative volume changes occurred during the dry season (with high erosion), which is attributed to the high SS-wave energy. [ABSTRACT FROM AUTHOR]

The influence of El Niño–Southern Oscillation (ENSO) on productivity at upwelling systems has been extensively studied. However, in recent decades, ENSO diversity has been documented; there are more frequent events with anomalies in the central Pacific (CP) causing ecological impacts that are different from the canonical events centered in the eastern Pacific (EP). We hypothesize that ENSO effects on upwelling intensity and its biological response are highly dependent on ENSO diversity. Wavelet coherence was computed for monthly standardized anomalies of Ekman transport and sea surface Chlorophyll-a (Chl-a) concentration from eight upwelling centers located along the west coast of the Baja California peninsula (1993–2022). Ekman transport (ET) showed a non-linear association with ENSO at interannual periodicities between 1.2 and 7 years, as well as semiannual scale variability. Coherence between ENSO and ET showed a reduction in upwelling intensity during CP ENSO events and an increased upwelling intensity after EP El Niño events with regional differences. Our results reveal an influence of northern Pacific circulation that subsequently influences ENSO events during its development and its peak. We detected an influence of SST and wind anomalies on the ENSO–Ekman transport connection associated with the northern Pacific Meridional Mode pattern. The CP shows an important role in sea surface Chl-a concentration anomalies (1998–2022). We highlight the conceptual relevance of distinguishing ENSO diversity, with influential ecological effects associated with CP ENSO events. [ABSTRACT FROM AUTHOR]

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data "on the same page" in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual. [ABSTRACT FROM AUTHOR]

Global change is altering hydrologic regimes worldwide, including large basins that play a central role in the sustainability of human societies and ecosystems. The basin water budget is a fundamental framework for understanding these basins' sensitivity and future dynamics under changing forcings. In this budget, studies often treat atmospheric processes as external to the basin and assume that atmosphere-related water storage changes are negligible in the long term. These assumptions are potentially misleading in large basins with strong land–atmosphere feedbacks, including terrestrial moisture recycling, which is critical for global water distribution. Here, we introduce the land–atmosphere reservoir (LAR) concept, which includes atmospheric processes as a critical component of the basin water budget and use it to study long-term changes in the water storage of some of the world's largest basins. Our results show significant LAR water storage trends over the last 4 decades, with a marked latitudinal contrast: while low-latitude basins have accumulated water, high-latitude basins have been drying. If they continue, these trends will disrupt the discharge regime and compromise the sustainability of these basins, resulting in widespread impacts. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Global climate models that incorporate carbon sources and sinks usually consider that forest uptake of carbon is in a state of equilibrium. Both historical and paleoecological records suggest that this is commonly not the case for Amazonia. Here, the impacts of colonial practices on Amazonian Indigenous peoples and forests are reviewed. Human activities affect forests' successional stages, trajectories, and species composition. By increasing the spatial coverage of paleoecological records that focus on pre‐ and post‐Columbian periods, the long‐term interactions between humans and Amazonian forests and their role in affecting Earth's climate may be better understood. Summary: Legacy effects left by the activities of Indigenous people in Amazonia are well known. Although severe, widespread, and recently occurring, the impacts left post‐1492 CE have been less investigated. We review the impact of colonial practices on Indigenous peoples and Amazonian forests. We suggest that forests comprise the sum of their past events, in a mosaic of different cumulative successional trajectories depending on the type, frequency, intensity, and timing of human influence. In regions with a history of minimal human influence, old‐growth species sensitive to fire would be the dominant landscape. In regions with high pre‐Columbian and low colonial influence, old‐growth forests carrying pre‐Columbian ecological legacies would be prevalent. Regions occupied by Indigenous groups post‐1492 CE would also carry similar ecological legacies. In regions influenced by the Jesuits, mid‐successional forests are expected to be enriched with cacao trees. In regions of latex extraction during the rubber boom, mid‐growth forests would present high abundances of early and mid‐successional species and depletion of some species. In deforested areas, we expect early successional forests with influence of exotic useful species. This patchwork of history probably plays a large role in shaping today's forests, and the biodiversity and carbon dynamics documented within them. Paleoecological work focusing on the last millennium, although scarce, has the potential to detect these mosaics of past human influence, and they should be considered when estimating forest ages and successional stages across the basin. [ABSTRACT FROM AUTHOR]

Oñate, V.; Orejarena-Rondón, A.F., and Restrepo, J.C., 2024. A simple approach to the risk assessment of strategic infrastructure on the Colombian Caribbean coast. Journal of Coastal Research, 40(4), 749–767. Charlotte (North Carolina), ISSN 0749-0208. Strategic infrastructure at risk was identified on the Colombian Caribbean coast. The risk approach consisted of an estimation of the main coastal hazards (coastal erosion, mean sea-level rise, and changes in wave energy flux) and the exposure level, as one of the most significant components of vulnerability, through multicriteria analysis and GISs. It identified 88 strategic coastal infrastructures that are at risk, located less than 250 m from the coastline, and belong to the energy, health, education, and transportation sectors. Of these, 34.1% are at a medium-high risk level, and 20.5% are classified as high-risk critical infrastructure. The analysis also revealed that anthropogenic interventions, such as sand mining, poorly designed hard coastal protection structures (groins, seawalls, and breakwaters), or damage to marine ecosystems, might have a relevant weight on the risk degree of critical infrastructure, highlighting the relevance of appropriate coastal protection measures for strategic infrastructure. This simplified approach aimed to contribute to the risk management of such essential elements and guarantee compliance with the predisaster stage of disaster risk management. [ABSTRACT FROM AUTHOR]

Healthcare professionals constantly face situations that reflect ecosystems' degradation. These can negatively affect their mental health. Research suggests that hope and resilience can play an important role in this scenario, since they are related to/predict mental health in highly heterogeneous samples (considering geography, age, profession, health, etc.). In this context, the aims of the present study are the following: to characterize and explore the relationship between hope, resilient coping and mental health in Portuguese healthcare professionals. Using Google Forms, 276 healthcare professionals answered the GHQ-28, the (adult) Trait Hope Scale, and the Brief Resilient Coping Scale (retrospective, analytical observational, cross-sectional, descriptive and correlational research design). The minimum and maximum possible scores were reached, with the exception of the maximum score of GHQ-28-Total. Regarding Hope, 19.6% scored below the midpoint (M = 43.46, SD = 11.97); 29.3% revealed low resilience (M = 14.93, SD = 4.05); and the average of four of the five Mental Health scores (exception: Severe depression) indicates the probability of a psychiatric case. Hope correlated with Social dysfunction and GHQ-28-Total; resilient coping proved to be a (weak) predictor of four of the five GHQ-28 indicators (exception: Severe depression). The results support the need to promote the sample's mental health, hope and resilient coping. They also suggest that stimulating resilient coping may contribute to improving healthcare professionals' mental health. Prior research (e.g., on therapies to enhance hope, resilience and, thus, mental health), to which the current study contributes, supports optimism towards the necessary internal sustainability transition. [ABSTRACT FROM AUTHOR]

Most studies in the field of land use and land cover (LULC) classification in remote sensing rely on supervised classification, which requires a substantial amount of accurate label data. However, reliable data are often not immediately available, and are obtained through time-consuming manual labor. One potential solution to this problem is the use of already available classification maps, which may not be the true ground truth and may contain noise from multiple possible sources. This is also true for the classification maps of the MapBiomas project, which provides land use and land cover (LULC) maps on a yearly basis, classifying the Amazon basin into more than 24 classes based on the Landsat data. In this study, we utilize the Sentinel-2 data with a higher spatial resolution in conjunction with the MapBiomas maps to evaluate a proposed noise removal method and to improve classification results. We introduce a novel noise detection method that relies on identifying anchor points in feature space through clustering with self-organizing maps (SOM). The pixel label is relabeled using nearest neighbor rules, or can be removed if it is unknown. A challenge in this approach is the quantification of noise in such a real-world dataset. To overcome this problem, highly reliable validation sets were manually created for quantitative performance assessment. The results demonstrate a significant increase in overall accuracy compared to MapBiomas labels, from 79.85% to 89.65%. Additionally, we trained the L2HNet using both MapBiomas labels and the filtered labels from our approach. The overall accuracy for this model reached 93.75% with the filtered labels, compared to the baseline of 74.31%. This highlights the significance of noise detection and filtering in remote sensing, and emphasizes the need for further research in this area. [ABSTRACT FROM AUTHOR]

The shock index (SI) has been associated with predicting transfusion needs in trauma patients. However, its utility in penetrating thoracic trauma (PTTrauma) for predicting the Critical Administration Threshold (CAT) has not been well-studied. This study aimed to evaluate the prognostic value of SI in predicting CAT in PTTrauma patients and compare its performance with the Assessment of Blood Consumption (ABC) and Revised Assessment of Bleeding and Transfusion (RABT) scores. We conducted a prognostic type 2, single-center retrospective observational cohort study on patients with PTTrauma and an Injury Severity Score (ISS) > 9. The primary exposure was SI at admission, and the primary outcome was CAT. Logistic regression and decision curve analysis were used to assess the predictive performance of SI and the PTTrauma score, a novel model incorporating clinical variables. Of the 620 participants, 53 (8.5%) had more than one CAT. An SI > 0.9 was associated with CAT (adjusted OR 4.89, 95% CI 1.64–14.60). The PTTrauma score outperformed SI, ABC, and RABT scores in predicting CAT (AUC 0.867, 95% CI 0.826–0.908). SI is a valuable predictor of CAT in PTTrauma patients. The novel PTTrauma score demonstrates superior performance compared to existing scores, highlighting the importance of developing targeted predictive models for specific injury patterns. These findings can guide clinical decision-making and resource allocation in the management of PTTrauma. [ABSTRACT FROM AUTHOR]

Satellite-based monitoring provides insights on synergies and trade-offs between energy production and land use and land cover (LULC) changes (LULCC) around hydropower dams. Using Landsat data, we mapped LULCC related to hydropower expansion to understand change dynamics of cash crop production in the Magdalena River basin (Colombian Andes). We leveraged secondary map products and an active learning routine to produce thematically detailed LULC maps, for 2009, 2015, and 2020, including key cash crops (rice and oil palm). Our area-adjusted accuracy assessment revealed high overall and class-specific user's and producer's accuracies, exceeding 80% for oil palm, rice, non-agricultural vegetation, wetlands, and grasslands, and accuracies of ~60% for other temporary and permanent crops. We identified substantial losses of rice (10,6%) and grasslands (25,9%) in El Quimbo due to reservoir flooding. For Hidrosogamoso, there was a loss of wetlands downstream. Our products provide the basis for balancing social, economic, and environmental trade-offs related to conflicting land uses. [ABSTRACT FROM AUTHOR]

Ozone in the troposphere is a greenhouse gas and a pollutant; hence, additional understanding of the drivers of tropospheric ozone evolution is essential. The El Niño–Southern Oscillation (ENSO) is a main climate mode and may contribute to the variations of tropospheric ozone. Nevertheless, there is uncertainty regarding the causal influences of ENSO on tropospheric ozone under a warming environment. Here, we investigated the links between ENSO and tropospheric ozone using Coupled Modeling Intercomparison Project Phase 6 (CMIP6) data over the period 1850–2014. Our results show that ENSO impacts on tropospheric ozone are primarily found over oceans, while the signature of ENSO over continents is largely nonsignificant. Springtime surface ozone is more sensitive to ENSO compared to other seasons. The response of ozone to ENSO may vary depending on specific air pressure levels in the troposphere. These responses are weak in the middle troposphere and are stronger in the upper and lower troposphere. There is high consistency across CMIP6 models in simulating the signature of ENSO on ozone over the lower, middle, and upper troposphere. While the response of tropical tropospheric ozone to ENSO is in agreement with previous works, our results suggest that ENSO impacts on tropospheric ozone over the northern North Pacific, American continent, and the midlatitude regions of the southern Pacific, Atlantic, and Indian oceans might be more significant than previously understood. [ABSTRACT FROM AUTHOR]

The Brazilian Legal Amazon, crucial for ecosystem services such as biodiversity, carbon sequestration, and climate regulation, has declined over time in its capacity to absorb carbon dioxide. In response, global policies are being developed to mitigate climate change, which has emerged as a central issue in the planetary health approach. The objective of this study was to investigate how elementary school students in a rural school in the Southern Amazonas state perceive climate change and understand its implications for the health of the planet. Understanding the phenomenon's complexity, we conducted research with students from riverside communities in the Southern Amazon region. The data were analyzed using relative, absolute and percentage frequency tables, with a Fisher's test applied at a 5% significance level. A significant finding was the predominant difficulty students had in accurately conceptualizing climate change, highlighting notable gaps in their understanding of these wide-ranging issues. In the context of the global climate crisis we are experiencing, the integration of concepts related to climate change in basic education becomes indispensable. This study emphasizes not only the existing knowledge gap but also the urgency of educational approaches that prepare children and young people for the challenges of mitigation, adaptation, and understanding the complexities of climate change and its planetary implications. [ABSTRACT FROM AUTHOR]

We evaluated the coupled dynamics of vegetation dynamics (NDVI) and soil moisture (SMOS) at monthly resolution over different regions of tropical South America and the effects of the Eastern Pacific (EP) and the Central Pacific (CP) El Niño–Southern Oscillation (ENSO) events. We used linear Pearson cross-correlation, wavelet and cross wavelet analysis (CWA) and three nonlinear causality methods: ParrCorr, GPDC and PCMCIplus. Results showed that NDVI peaks when SMOS is transitioning from maximum to minimum monthly values, which confirms the role of SMOS in the hydrological dynamics of the Amazonian greening up during the dry season. Linear correlations showed significant positive values when SMOS leads NDVI by 1–3 months. Wavelet analysis evidenced strong 12- and 64-month frequency bands throughout the entire record length, in particular for SMOS, whereas the CWA analyses indicated that both variables exhibit a strong coherency at a wide range of frequency bands from 2 to 32 months. Linear and nonlinear causality measures also showed that ENSO effects are greater on SMOS. Lagged cross-correlations displayed that western (eastern) regions are more associated with the CP (EP), and that the effects of ENSO manifest as a travelling wave over time, from northwest (earlier) to southeast (later) over tropical South America and the Amazon River basin. The ParrCorr and PCMCIplus methods produced the most coherent results, and allowed us to conclude that: (1) the nonlinear temporal persistence (memory) of soil moisture is stronger than that of NDVI; (2) the existence of two-way nonlinear causalities between NDVI and SMOS; (3) diverse causal links between both variables and the ENSO indices: CP (7/12 with ParrCorr; 6/12 with PCMCIplus), and less with EP (5/12 with ParrCorr; 3/12 with PCMCIplus). [ABSTRACT FROM AUTHOR]

The high complexity of the parameter–simulation problem in land surface models over semiarid areas makes it difficult to reasonably estimate the surface simulation conditions that are important for both weather and climate in different regions. In this study, using the dense site datasets of a typical semiarid region over Tibet and the Noah land surface model with the constrained land parameters of multiple sites, an enhanced Kling–Gupta efficiency criterion comprising multiple objectives, including variable and layer dimensions, was obtained, which was then applied to calibration schemes based on two global search algorithms (particle swarm optimization and shuffled complex evaluation) to investigate the site-scale spatial complexities in soil temperature simulations. The calibrations were then compared and further validated. The results show that the Noah land surface model obtained reasonable simulations of soil moisture against the observations with fine consistency, but the negative fit and huge spatial errors compared with the observations indicated its weak ability to simulate the soil temperature over regional semiarid land. Both calibration schemes significantly improved the soil moisture and temperature simulations, but particle swarm optimization generally converged to a better objective than shuffled complex evaluation, although with more parameter uncertainties and less heterogeneity. Moreover, simulations initialized with the optimal parameter tables for the calibrations obtained similarly sustainable improvements for soil moisture and temperature, as well as good consistency with the existing soil reanalysis. In particular, the soil temperature simulation errors for particle swarm optimization were unbiased, while those for the other method were found to be biased around −3 K. Overall, particle swarm optimization was preferable when conducting soil temperature simulations, and it may help mitigate the efforts in surface forecast improvement over semiarid regions. [ABSTRACT FROM AUTHOR]

Zika, a viral disease transmitted to humans by Aedes mosquitoes, emerged in the Americas in 2015, causing large-scale epidemics. Colombia alone reported over 72,000 Zika cases between 2015 and 2016. Using national surveillance data from 1121 municipalities over 70 weeks, we identified sociodemographic and environmental factors associated with Zika's emergence, re-emergence, persistence, and transmission intensity in Colombia. We fitted a zero-state Markov-switching model under the Bayesian framework, assuming Zika switched between periods of presence and absence according to spatially and temporally varying probabilities of emergence/re-emergence (from absence to presence) and persistence (from presence to presence). These probabilities were assumed to follow a series of mixed multiple logistic regressions. When Zika was present, assuming that the cases follow a negative binomial distribution, we estimated the transmission intensity rate. Our results indicate that Zika emerged/re-emerged sooner and that transmission was intensified in municipalities that were more densely populated, at lower altitudes and/or with less vegetation cover. Warmer temperatures and less weekly-accumulated rain were also associated with Zika emergence. Zika cases persisted for longer in more densely populated areas with more cases reported in the previous week. Overall, population density, elevation, and temperature were identified as the main contributors to the first Zika epidemic in Colombia. We also estimated the probability of Zika presence by municipality and week, and the results suggest that the disease circulated undetected by the surveillance system on many occasions. Our results offer insights into priority areas for public health interventions against emerging and re-emerging Aedes-borne diseases. [ABSTRACT FROM AUTHOR]

The spatial distribution of vegetation in a basin has a far-reaching influence on the potential for sediment separation and transport capacity. However, many landslides induced by strong earthquakes have greatly changed the existing pattern, which further increases the probability of debris flow in a basin during heavy rainfall and has a significant impact on the stability of the basin. Thus, this study selected the debris flow basin in the Qipan catchment of the Wenchuan earthquake area as the research object. Multisource and high-precision remote sensing images were used to analyze the land use changes in the basin, and the index of connectivity (IC) was introduced to analyze the evolution of sediment transport capacity. An ecosystem stability assessment method suitable for post-earthquake debris flow basins was proposed. Through quantitative assessment of the ecosystem stability of the basin after the Wenchuan earthquake in 2008 and the two debris flow events after the earthquake, the dynamic relationship between the debris-flow-prone area and the ecosystem stability of the basin was revealed. The results showed that the stability of the ecosystem in the Qipan catchment increased annually, indicating a stable and substable state. The spatial distribution characteristics were lower in the north and south and greater in the middle. By comparing the evaluation results with the actual terrain change trend, the accuracy and feasibility of the evaluation method are verified. The results of this study provide a scientific basis for the formulation of regional disaster prevention strategies and help to accelerate the improvement of regional stability in debris-flow-prone areas. [ABSTRACT FROM AUTHOR]

Hydrological predictions at subseasonal-to-seasonal (S2S) time scales can support improved decision-making in climate-dependent sectors like agriculture and hydropower. Here, we present an S2S hydrological forecasting system (S2S-HFS) for western tropical South America (WTSA). The system uses the global NASA Goddard Earth Observing System S2S meteorological forecast system (GEOS-S2S) in combination with the generalized analog regression downscaling algorithm and the NASA Land Information System (LIS). In this implementation study, we evaluate system performance for 3-month hydrological forecasts for the austral autumn season (March–May) using ensemble hindcasts for 2002–17. Results indicate that the S2S-HFS generally offers skill in predictions of monthly precipitation up to 1-month lead, evapotranspiration up to 2 months lead, and soil moisture content up to 3 months lead. Ecoregions with better hindcast performance are located either in the coastal lowlands or in the Amazon lowland forest. We perform dedicated analysis to understand how two important teleconnections affecting the region are represented in the S2S-HFS: El Niño–Southern Oscillation (ENSO) and the Antarctic Oscillation (AAO). We find that forecast skill for all variables at 1-month lead is enhanced during the positive phase of ENSO and the negative phase of AAO. Overall, this study indicates that there is meaningful skill in the S2S-HFS for many ecoregions in WTSA, particularly for long memory variables such as soil moisture. The skill of the precipitation forecast, however, decays rapidly after forecast initialization, a phenomenon that is consistent with S2S meteorological forecasts over much of the world. [ABSTRACT FROM AUTHOR]

The linkage between the salt wedge, tidal patterns, and the Magdalena River discharge is established by assessing the ensuing parameters: stratification (ϵ), buoyancy frequency (β), potential energy anomaly (φ), Richardson number by layers (RL), and bottom turbulent energy production (P). The salinity, temperature, density, and water velocity data utilized were derived from MOHID 3D, a previously tailored and validated model for the Magdalena River estuary. To grasp the dynamics of the river, a flow regime analysis was conducted during both the wet and dry climatic seasons of the Colombian Caribbean. The utilization of this model aimed to delineate the estuary's spatial reach, considering flow rates spanning from 2000 to 6500 m3/s across two tidal cycles. This approach facilitates the prediction of the position, stability, and stratification degree of the salt front. Among the conclusions drawn, it is highlighted that: 1. The river flow serves as the principal conditioning agent for the system, inducing a strong estuary response to weather stations; 2. The extent of wedge intrusion and the river discharge exhibit a non-linear, inversely correlation; 3. Tidal waves cause differences of up to 1000 m in the horizontal extent of the wedge; 4. Widespread channel erosion occurs during the rainy season when the salt intrusion does not exceed 2 km; 5. Flocculation processes intensify during the transition between the dry and wet seasons; 6. The stability of the salt layering and the consolidation of the FSI–TMZ are contingent upon the geometric attributes of the channel. [ABSTRACT FROM AUTHOR]

Maternally‐inherited sex ratio distorting microbes (SRDMs) are common among arthropod species. Typically, these microbes cause female‐biased sex ratios in host broods, either by; killing male offspring, feminising male offspring, or inducing parthenogenesis. As a result, infected populations can experience drastic ecological and evolutionary change. The mechanism by which SRDMs operate is likely to alter their impact on host evolutionary ecology; despite this, the current literature is heavily biased towards a single mechanism of sex ratio distortion, male‐killing. Furthermore, amidst the growing concerns surrounding the loss of arthropod diversity, research into the impact of SRDMs on the viability of arthropod populations is generally lacking. In this study, using a theoretical approach, we model the epidemiology of an understudied mechanism of microbially‐induced sex ratio distortion—feminisation—to ask an understudied question—how do SRDMs impact extinction risk in a changing environment? We constructed an individual‐based model and measured host population extinction risk under various environmental and epidemiological scenarios. We also used our model to identify the precise mechanism modulating extinction. We find that the presence of feminisers increases host population extinction risk, an effect that is exacerbated in highly variable environments. We also identified transmission rate as the dominant epidemiological trait responsible for driving extinction. Finally, our model shows that sex ratio skew is the mechanism driving extinction. We highlight feminisers and, more broadly, SRDMs as important determinants of the resilience of arthropod populations to environmental change. [ABSTRACT FROM AUTHOR]

Platinum (Pt)‐based chemotherapy is the main treatment for ovarian cancer (OC); however, most patients develop Pt resistance (Pt‐R). This work shows that Pt‐R OC cells increase intracellular cholesterol through uptake via the HDL receptor, scavenger receptor type B‐1 (SR‐B1). SR‐B1 blockade using synthetic cholesterol‐poor HDL‐like nanoparticles (HDL NPs) diminished cholesterol uptake leading to cell death and inhibition of tumor growth. Reduced cholesterol accumulation in cancer cells induces lipid oxidative stress through the reduction of glutathione peroxidase 4 (GPx4) leading to ferroptosis. In turn, GPx4 depletion induces decreased cholesterol uptake through SR‐B1 and re‐sensitizes OC cells to Pt. Mechanistically, GPx4 knockdown causes lower expression of the histone acetyltransferase EP300, leading to reduced deposition of histone H3 lysine 27 acetylation (H3K27Ac) on the sterol regulatory element binding transcription factor 2 (SREBF2) promoter and suppressing expression of this key transcription factor involved in the regulation of cholesterol metabolism. SREBF2 downregulation leads to decreased SR‐B1 expression and diminished cholesterol uptake. Thus, chemoresistance and cancer cell survival under high ROS burden obligates high GPx4 and SR‐B1 expression through SREBF2. Targeting SR‐B1 to modulate cholesterol uptake inhibits this axis and causes ferroptosis in vitro and in vivo in Pt‐R OC. [ABSTRACT FROM AUTHOR]

This study explores user perceptions, engagement, and the credibility of climate change information shared on Facebook. This research seeks to uncover the impact of this influential social media platform on climate change awareness in a specific regional context. Researcher Research validity and reliability depend on sample size. This technique involves assessing confidence level, margin of error, effect magnitude based on study objectives, and statistical test selection. The researcher must also account for attrition and non-response rates to maintain sample size during data collection. The ability to recruit and survey within resources and timetables is essential. The sample size estimate was used for an unlimited population, and 384 responded. Complex situations may require a statistician or statistical software to calculate sample size. The findings offer insights into the dynamics of climate change communication in Lahore through Facebook and provide a foundation for informed policy decisions and awareness campaigns. It is evident that social media platforms, when harnessed effectively, can contribute significantly to advancing climate change awareness and fostering collective efforts toward climate action in the context of Lahore, Pakistan, and beyond. [ABSTRACT FROM AUTHOR]

Mountains are climate change hotspots and their ecosystems are key components in the supply of ecosystem goods and services to local communities. Low-income communities that directly depend on mountain resources are highly vulnerable to the harsh impacts of climate change. Using rainfall and temperature trends, and data collected from a household questionnaire survey, the objective of this study is to assess the impact of climate change on low-income households living in the Maluti-a-Phofung Municipality part of the Drakensberg Mountains. Climatic data were obtained from Climate Explorer while the household data were collected from a sample of 383 households in the villages of Qwaqwa. The results show that temperature and rainfall changes have significantly increased over a period of 120 years. About 51 percent of the respondents experienced extreme weather events which has the greatest impact on their households followed by drought (25.5%). Employment status was found to be significantly associated with the perception that hazards negatively impact natural resource availability, with 54% of those who had this perception being unemployed. In addition, income was found to have a significant relationship with extreme weather impacts on households and 60% of those households had a low monthly income of ZAR 2000 or less. Based on these findings, mountain households along the Drakensberg Mountains in Qwaqwa villages are already experiencing the negative impacts of climate change and their socio-economic characteristics indicate very low levels of adaptation capacity. [ABSTRACT FROM AUTHOR]

Quantifying the atmospheric water balance is critical for the study of hydrological processes in significant regions. This study quantified atmospheric water balance closure at 205 stations in mainland China on a monthly timescale from 2009 to 2018 using datasets from ground- and satellite-based observations and reanalysis data. The closure performances were firstly quantified using the mean and root mean square (RMS) of the residuals, and the possible influencing factors were explored, as well as the influence of different water balance components (WBCs) using different datasets. In the closure experiment using ERA5, the mean and residuals were 6.26 and 12.39 mm/month, respectively, on average, which indicated a closure uncertainty of 12.8%. Using ERA5 analysis as a reference, the closure experiment using different combinations revealed average mean residuals of 8.73, 11.50, and 15.89 mm/month, indicating a precipitation closure uncertainty of 22.0, 23.7, and 24.4% for the ground- and satellite-based observations and reanalysis data, respectively. Two possible influencing factors, station latitude and the climatic zone in which the station is located, were shown to be related to closure performance. Finally, the analysis of the impact from different WBCs showed that precipitation tended to have the most significant impact, which may have been due to larger observation uncertainties. Generally, the atmospheric water balance in mainland China can be closed using datasets from different observational techniques. [ABSTRACT FROM AUTHOR]

The extratropical west coast of South America has one of the largest frequencies of landfalling atmospheric rivers (ARs), with dozens of events per season that account for ~50% of the annual precipitation and can produce extreme rainfall events in south-central Chile. Most ARs form an acute angle with the Andes, but, in some cases, the moist stream impinges nearly perpendicular to the mountains, referred to as zonal atmospheric rivers (ZARs). Enhanced surface-based and upper-air measurements in Concepcion (36.8° S), as well as numerical simulations, were used to characterize a ZAR and a meridionally oriented AR in July 2022. They represent extremes of the broad distribution of winter storms in this region and exhibit key features that were found in a composite analysis based on larger samples of ZARs and tilted ARs. The latter is associated with an upper-level trough, broad-scale ascent, extratropical cyclone, and cold front reaching southern Chile. Instead, ZARs are associated with tropospheric-deep, strong zonal flow and a stationary front across the South Pacific, with ascent restricted upstream of the Andes. Consequently, ZARs have minimum precipitation offshore but a marked orographic precipitation enhancement and exhibit relatively warm temperatures, thus resulting in an augmented risk of hydrometeorological extreme events. [ABSTRACT FROM AUTHOR]

Microorganisms known as psychrophiles/psychrotrophs, which survive in cold climates, constitute majority of the biosphere on Earth. Their capability to produce cold‐active enzymes along with other distinguishing characteristics allows them to survive in the cold environments. Due to the relative ease of large‐scale production compared to enzymes from plants and animals, commercial uses of microbial enzyme are alluring. The ocean depths, polar, and alpine regions, which make up over 85% of the planet, are inhabited to cold ecosystems. Microbes living in these regions are important for their metabolic contribution to the ecosphere as well as for their enzymes, which may have potential industrial applications. Cold‐adapted microorganisms are a possible source of cold‐active enzymes that have high catalytic efficacy at low and moderate temperatures at which homologous mesophilic enzymes are not active. Cold‐active enzymes can be used in a variety of biotechnological processes, including food processing, additives in the detergent and food industries, textile industry, waste‐water treatment, biopulping, environmental bioremediation in cold climates, biotransformation, and molecular biology applications with great potential for energy savings. Genetically manipulated strains that are suitable for producing a particular cold‐active enzyme would be crucial in a variety of industrial and biotechnological applications. The potential advantage of cold‐adapted enzymes will probably lead to a greater annual market than for thermo‐stable enzymes in the near future. This review includes latest updates on various microbial source of cold‐active enzymes and their biotechnological applications. [ABSTRACT FROM AUTHOR]

Cruzeiro do Sul, a municipality in Northwestern Brazil is recurrently impacted by floods, particularly along the Juruá River. This study presents a comprehensive flood risk analysis by integrating geoprocessing, remote sensing, and hydraulic modeling techniques. Our objectives are to simulate flood extents, identify high-risk areas, and guide sustainable territorial management. Our findings illustrate that the flood impacts are distributed across urban (27%), agricultural (55%), and forest/grassland (17%) landscapes. Historical records and literature reviews also underscore a recurring pattern of extreme floods in the municipality, notably during February's La Niña events. Some vulnerable urban neighborhoods were identified: Vila Cruzeirinho, Centro, Miritizal, and Da Várzea. These areas are especially susceptible due to their proximity to the river and increased surface runoff during high flood events. By amalgamating various data sources and methods, this research aids decision making for flood mitigation and urban development, fostering resilience against recurrent flooding events in Cruzeiro do Sul. [ABSTRACT FROM AUTHOR]

The distribution range of the jumbo squid (Dosidicus gigas) has increased over the past few decades; it is now found in the entire Eastern Pacific Ocean and is considered an important species in the small and large fisheries of Chile, Perú, Ecuador, Costa Rica and Mexico but not in the Pacific region of Colombia. Three night-fishing campaigns were conducted over a year in the coastal Baudó-San Juan environmental unit, adjacent to the Bajo Baudó Encanto de Manglares Regional Integrated Management District in Chocó, at three locations 20 km, 35 km, and 45 km from the coastline to establish the availability and viability of jumbo squid as an alternative to the target species of artisanal fisheries in the Colombian Pacific. Night fishing sets were conducted at 60 m and 200 m depth at each sampling station to assess some of the biological parameters of the jumbo squid population (mantle length-ML, weight, growth and size at sexual maturity). Most catches were obtained in February and March. Growth was isometric, the average catch size was 24.3 cm ML, size at sexual maturity (L50) was 23.25 cm ML, estimated maximum size (L∞) was 39.9 cm ML, the growth constant (K) was 0.83, and mortality due to experimental fishing was 26 cm ML. According to our results, the jumbo squid fishery in the Colombian Pacific artisanal fishery would be viable during the first months of the year. [ABSTRACT FROM AUTHOR]

Enhanced anthropogenic climatic variability challenges small farmers. In the Sumapaz páramo (Colombia), higher irregularity in precipitation and temperature reduces the quality of pasture and cattle health. Data from surveys, semi-structured interviews, and focus groups were analyzed to understand livestock farmers' responses to the impacts of climatic variability. To estimate the communities' resilience in the páramo, we used the capitals framework, the Baseline Resilience Indicator for Communities (BRIC), and cluster analysis. The responses of most households aim to reduce the impacts of climatic variability on the production system, chiefly intensifying practices such as the rotation of paddocks, livelihood diversification, purchase of grass, and buying and selling livestock. Interestingly, farmers did not recognize the value of the types of capital for responding to climatic variability. Results showed that the use of available physical, social, and economic capitals render the farming system resilient. Our probit model estimated that economic and human capitals are the largest and most significant contributors to communities' capacity to respond to climatic variability. However, pre-existing non-climatic vulnerabilities are also important. For example, poverty hinders farmers from using their income in response to climatic variability. The place-based measurements used in this research are easily understood and applicable by local policy makers to address increasing climate variability. [ABSTRACT FROM AUTHOR]

Simple Summary: The El Niño presents itself as a serious problem in the pastures of the northern region of Brazil, as it compromises the availability and quality of forage and water. Therefore, the objective of this study was to characterize the thermographic profile of three production systems in the Eastern Amazon, Brazil. The results show significant differences between areas with and without chestnut tree shade. Between August and November, the highest temperatures were recorded in full sun pastures, contrasting with lower temperatures in shaded areas. The interaction between the systems revealed significant thermal variations, highlighting the positive impact of native trees on thermal regulation and indicating possible strategies to mitigate the adverse effects of El Niño. The El Niño represents a substantial threat to pastures, affecting the availability of water, forage and compromising the sustainability of grazing areas, especially in the northern region of Brazil. Therefore, the objective of this study was to characterize the thermographic profile of three production systems in the Eastern Amazon, Brazil. The study was conducted on a rural cattle farm in Mojuí dos Campos, Pará, Brazil, between August and November 2023. The experiment involved livestock production systems, including traditional, silvopastoral and integrated, with different conditions of shade and access to the bathing area. An infrared thermographic (IRT) camera was used, recording temperatures in different zones, such as areas with trees, pastures with forage and exposed pastures. The highest mean temperatures (p = 0.02) were observed in pastures with full sun from August to November. On the other hand, the lowest average temperatures were recorded in areas shaded by chestnut trees (Bertholletia excelsa). The highest temperature ranges were found in sunny areas and the lowest were recorded in shaded areas. The highest temperatures were observed in the pasture in full sun, while the lowest were recorded in areas shaded by chestnut trees (p < 0.0001). The interaction between the systems and treatments revealed significant temperature differences (p < 0.0001), with the native trees showing an average temperature of 35.9 °C, lower than the grasses and soil, which reached 61.2 °C. This research concludes that, under El Niño in the Eastern Amazon, areas shaded by Brazil nut trees had lower temperatures, demonstrating the effectiveness of shade. Native trees, compared to grasses and soil, showed the ability to create cooler environments, highlighting the positive influence on different species such as sheep, goats and cattle. [ABSTRACT FROM AUTHOR]

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions. [ABSTRACT FROM AUTHOR]

DNA barcoding, based on mitochondrial markers, is widely applied in species identification and biodiversity studies. The aim of this study was to establish a barcoding reference database of fishes inhabiting the Cube River from Western Ecuador in the Chocó-Darien Global Ecoregion (CGE), a threatened ecoregion with high diversity and endemism, and evaluate the applicability of using barcoding for the identification of fish species. Barcode sequences were obtained from seven orders, 17 families, 23 genera and 26 species, which were validated through phylogenetic analysis, morphological measurements, and literature review. Our results showed that 43% of fish species in this region are endemic, confirmed the presence of known species in the area, and included the addition of three new records of native (Hoplias microlepis, Rhamdia guatemalensis and Sicydium salvini) and an introduced species (Xiphophorus maculatus) to Ecuador. In addition, eight species were barcoded for the first time. Species identification based on barcoding and morphology showed discrepancy with species lists from previous studies in the CGE, suggesting that the current baseline of western fishes of Ecuador is still incomplete. Because this study analyzed fishes from a relatively small basin (165 km2), more molecular-based studies focusing on fish are needed to achieve a robust sequence reference library of species inhabiting Western Ecuador. The new sequences of this study will be useful for future comparisons and biodiversity monitoring, supporting the application of barcoding tools for studying fish diversity in genetically unexplored regions and to develop well-informed conservation programs. [ABSTRACT FROM AUTHOR]

Paleoclimatological field reconstructions are valuable for understanding hydroclimatic variability. While being similarly impactful on societies as temperature variability, hydroclimatic variability has still remained less in focus. However, reconstructing globally complete fields of climate variables lacks adequate proxy data from tropical regions like South America, limiting our understanding of past hydroclimatic changes in these areas. This study addresses this gap using low resolution climate archives, including speleothems, previously omitted from reconstructions. Speleothems record climate variations on decadal to centennial time scales and provide a rich dataset for the otherwise proxy data scarce region of tropical South America. By employing a multi-time scale Paleoclimate Data Assimilation approach, we synthesize climate proxy records and climate model simulations, capable of simulating water isotopologues in the atmosphere, to reconstruct 2000 years of South American climate. This includes surface air temperature, precipitation amount, drought index, isotopic composition of precipitation amount, and the intensity of the South American Summer Monsoon. The reconstruction reveals anomalous climate periods: a wetter and colder phase during the Little Ice Age (1500–1850 CE) and a drier, warmer period corresponding to the early Medieval Climate Anomaly (600–900 CE). However, these patterns are not uniform across the continent, with exceptions in northeastern Brazil and the Southern Cone, indicating regional variability. The anomalies are more pronounced than in previous reconstructions, but align with local proxy record studies, thus highlighting the importance of including speleothem proxies. The multi-timescale approach is essential for reconstructing multi-decadal and centennial climate variability. Despite methodological uncertainties regarding climate model biases and proxy record interpretations, this study marks a crucial first step in incorporating speleothems into climate field reconstructions, potentially enhancing insights into past hydroclimatic variability and hydroclimate projections. [ABSTRACT FROM AUTHOR]

The expansion of copper mining on the hyper-arid pacific slope of Southern Peru has precipitated growing concern for scarce water resources in the region. Located in the headwaters of the Torata river, in the department of Moquegua, the Cuajone mine, owned by Southern Copper, provides a unique opportunity in a little-studied region to examine the relative impact of the landscape-scale mining on water resources in the region. Principal component and cluster analyses of the water chemistry data from 16 sites, collected over three seasons during 2017 and 2018, show distinct statistical groupings indicating that, above the settlement of Torata, water geochemistry is a function of chemical weathering processes acting upon underlying geological units, and confirming that the Cuajone mine does not significantly affect water quality in the Torata river. Impact mitigation strategies that firstly divert channel flow around the mine and secondly divert mine waste to the Toquepala river and tailings dam at Quebrada Honda remove the direct effects on the water quality in the Torata river for the foreseeable future. In the study area, our results further suggest that water quality has been more significantly impacted by urban effluents and agricultural runoff than the Cuajone mine. The increase in total dissolved solids in the waters of the lower catchment reflects the cumulative addition of dissolved ions through chemical weathering of the underlying geological units, supplemented by rapid recharge of surface waters contaminated by residues associated with agricultural and urban runoff through the porous alluvial aquifer. Concentrations in some of the major ions exceeded internationally recommended maxima for agricultural use, especially in the coastal region. Occasionally, arsenic and manganese contamination also reached unsafe levels for domestic consumption. In the lower catchment, below the Cuajone mine, data and multivariate analyses point to urban effluents and agricultural runoff rather than weathering of exposed rock units, natural or otherwise, as the main cause of contamination. [ABSTRACT FROM AUTHOR]

Climatic seasonality has lacked research attention in terms of global tropical forests, where it impacts vegetation productivity, biodiversity, and hydrological cycles. This study employs two methods—climatological anomalous accumulation (CAA) and potential evapotranspiration (PET) threshold—to detect the climatic seasonality of global tropical forests, including the onset and duration of wet seasons. Spatial clustering based on the length of the wet season is used to delineate smaller regions within the tropical forest areas to observe their precipitation patterns. The results show that these methods effectively reveal more homogeneous regions and their respective rainfall patterns. In particular, we found that the wet season in Amazon forests detected by the CAA method is more uniform in space than the PET threshold, but the global tropical forest regions divided by the CAA method on average contain more complex climates than the PET threshold. Moreover, the year-round abundant precipitation in Southeast Asia, which is strongly influenced by monsoons, presents challenges for wet season detection. Overall, this work provides an objective perspective for understanding the climatic seasonality changes in tropical forests and lays a scientific foundation for future forest management and the development of adaptation strategies to global climate change. [ABSTRACT FROM AUTHOR]

Extreme rainfall events frequently cause hazardous floods in many parts of the world. With growing human exposure to floods, studying conditions that trigger floods is imperative. Flash floods, in particular, require well-defined models for the timely warning of the population at risk. Intensity–duration–frequency (IDF) curves are a common way to characterize rainfall and flood events. Here, the copula method is employed to model the dependence between the intensity and duration of rainfall events flexibly and separately from their respective marginal distribution. Information about the localization of 93 flash floods in Jamaica was gathered and linked to remote-sensing rainfall data, and additional data on location-specific yearly maximum rainfall events were constructed. The estimated normal copula has Weibull and generalized extreme value (GEV) marginals for duration and intensity, respectively. Due to the two samples, it is possible to pin down above which line in the intensity duration space a rainfall event likely triggers a flash flood. The parametric IDF curve with an associated return period of 216 years is determined as the optimal threshold for flash flood event classification. This methodology delivers a flexible approach to generating rainfall IDF curves that can directly be used to assess flash flood risk. [ABSTRACT FROM AUTHOR]

The anthropogenic impacts on the environment, including deforestation and the escalating emissions of greenhouse gases, have significantly contributed to global climate change that can lead to alterations in ecosystems. In this context, protected areas (PAs) are pillars for biodiversity conservation by being able, for example, to maintain the viability of populations of endangered species. On the other hand, the species range shifts do not follow the limits of PAs, jeopardizing the conservation of these species. Furthermore, the effectiveness of PAs is consistently undermined by impacts stemming from land use, hunting activities, and illegal exploitation, both within the designated areas and in their adjacent zones. The objectives of this study are to quantify the impacts of climate change on the distribution of threatened and endemic birds of the Amazon biome, evaluate the effectiveness of PAs in protecting the richness of threatened birds, and analyze the representativeness of species within PAs. We found with our results that climate suitability loss is above 80 for 65% of taxa in the optimistic scenario and above 93% in the pessimistic scenario. The results show that PAs are not effective in protecting the richness of Amazonian birds, just as they are ineffective in protecting most of the taxa studied when analyzed individually Although some taxa are presented as "Protected," in future scenarios these taxa may suffer major shrinkages in their distributions and consequently present population unviability. The loss of climatically suitable areas and the effectiveness of PAs can directly influence the loss of ecosystem services, fundamental to maintaining the balance of biodiversity. Therefore, our study paves the way for conservation actions aimed at these taxa so that they can mitigate current and future extinctions due to climate change. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is a crucial parameter for characterizing vegetation canopy structure and energy absorption capacity. The Moderate Resolution Imaging Spectroradiometer (MODIS) LAI has played a significant role in landmark studies due to its clear theoretical basis, extensive historical time series, extensive validation results, and open accessibility. However, MODIS LAI retrievals are calculated independently for each pixel and a specific day, resulting in high noise levels in the time series and limiting its applications in the regions of optical remote sensing. Reprocessing MODIS LAI predominantly relies on temporal information to achieve smoother LAI profiles with little use of spatial information and may easily ignore genuine LAI anomalies. To address these problems, we designed the spatiotemporal information compositing algorithm (STICA) for the reprocessing of MODIS LAI products. This method integrates information from multiple dimensions, including pixel quality information, spatiotemporal correlation, and the original retrieval, thereby enabling both "reprocessing" and "value-added data" with respect to the existing MODIS LAI products, leading to the development of the high-quality LAI (HiQ-LAI) dataset. Compared with ground measurements, HiQ-LAI shows better performance than the original MODIS product with a root-mean-square error (RMSE) or bias decrease from 0.87 or -0.17 to 0.78 or -0.06 , respectively. This is due to the improvement of HiQ-LAI with respect to capturing the seasonality in vegetation phenology and reducing abnormal time-series fluctuations. The time-series stability (TSS) index, which represents temporal stability, indicated that the area with smooth LAI time series expanded from 31.8 % (MODIS) to 78.8 % (HiQ) globally, and this improvement is more obvious in equatorial regions where optical remote sensing cannot usually achieve good performance. We found that HiQ-LAI demonstrates superior continuity and consistency compared with raw MODIS LAI from both spatial and temporal perspectives. We anticipate that the global HiQ-LAI time series, generated using the STICA procedure on the Google Earth Engine (GEE) platform, will substantially enhance support for diverse global LAI time-series applications. The 5 km 8 d HiQ-LAI datasets from 2000 to 2022 are available at 10.5281/zenodo.8296768 (Yan et al., 2023). [ABSTRACT FROM AUTHOR]

Concurrent meteorological extremes (CMEs) represent a class of pernicious climatic events characterized by the coexistence of two extreme weather phenomena. Specifically, the juxtaposition of Urban Extreme Rainfall (UER) and Urban Extreme Heat (UEH) can precipitate disproportionately deleterious impacts on both ecological systems and human well-being. In this investigation, we embarked on a meticulous risk appraisal of CMEs within China's Greater Bay Area (GBA), harnessing the predictive capabilities of three shared socioeconomic pathways (SSPs) namely, SSP1-2.6, SSP3-7.0, and SSP5-8.5, in conjunction with the EC-Earth3-Veg-LR model from the CMIP6 suite. The findings evidence a pronounced augmentation in CME occurrences, most notably under the SSP1-2.6 trajectory. Intriguingly, the SSP5-8.5 pathway, typified by elevated levels of greenhouse gas effluents, prognosticated the most intense CMEs, albeit with a temperate surge upon occurrence. Additionally, an ascendant trend in the ratio of CMEs to the aggregate of UER and UEH portends an escalating susceptibility to these combined events in ensuing decades. A sensitivity analysis accentuated the pivotal interplay between UER and UEH as a catalyst for the proliferation of CMEs, modulated by alterations in their respective marginal distributions. Such revelations accentuate the imperative of assimilating intricate interdependencies among climatic anomalies into evaluative paradigms for devising efficacious climate change countermeasures. The risk assessment paradigm proffered herein furnishes a formidable instrument for gauging the calamitous potential of CMEs in a dynamically shifting climate, thereby refining the precision of prospective risk estimations. [ABSTRACT FROM AUTHOR]