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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]

En la presente investigación se detalló las barreras para la internacionalización de empresas de productos alimenticios orgánicos no tradicionales desde el cantón Machala hacia el mercado exterior. Se cumplió con el principal objetivo de la investigación que fue analizar las barreras para la internacionalización de las empresas de productos alimenticios orgánicos no tradicionales del cantón Machala mediante la revisión bibliográfica y una investigación de campo de tipo descriptiva y exploratoria con la aplicación de técnicas de investigación como la entrevista y la encuesta se obtuvo información directa de los gerentes de empresas exportadoras de productos alimenticios orgánicos no tradicionales y de los representantes de pymes dedicadas a la producción y comercialización de productos orgánicos en el cantón Machala. Los resultados de la investigación indican que existe un bajo nivel de exportación de productos alimenticios no tradicionales debido al desconocimiento de la demanda internacional y a las exigencias de los mercados internacionales.

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.)

Abstract: Surface and atmospheric water balances analysis for Amazon River basin at monthly time scale are performed with an emphasis on the linkages between the Andes and low‐lying Amazonia. Analyses are performed using observational and reanalysis data covering five different periods of analysis (depending on length of evapotranspiration data sets) for the entire basin, major subcatchments, and for the Andes and low‐lying Amazonia. Results for the entire basin show a state close to balance within tolerance, while the spatial disaggregation produced a less clear picture, presenting major discrepancies between observations and reanalysis data sets. The atmospheric budget exhibits no closure and positive residuals regardless of data set, with the magnitude of residuals for the entire Amazon basin highly dependent on evapotranspiration data source. The imbalance between the two water budgets (14%–16%) is driven by higher values of runoff and by an abrupt change in runoff when changing from dry to wet seasons in the Amazon. We unveil two shortcomings of the available data, namely poor quality in the representation of surface processes by reanalysis, and flaws and scarcity of information in the high Andes that induce uncertainties and errors in both water budgets. The results of the present study highlight the importance of the Andean region for the hydrological integrity of the entire Amazon River basin. Our results confirm the paramount importance of the joint analysis of atmospheric and surface water budgets at the basin level with respect to achieving a complete understanding of the whole hydrological cycle at the continental scale. [ABSTRACT FROM AUTHOR]

Malaria and dengue are vector-borne endemic diseases in the low-lying regions of Colombia. Outbreaks of both diseases appear during the occurrence of El Niño in the tropical Pacific. We present updated data confirming the relation, which are explained by the increase in temperature. Malaria shows an increasing trend, of which climate change cannot be disregarded. The migration of over 1?200?000 Venezuelans hiding away from the internal crisis has complicated the situation. Further research is needed to pinpoint the linkages between vector-borne diseases and climate variability, but also with current and future impacts of climate change, and alarming deforestation rates of Colombia. The public health system has been impacted by the COVID-19 pandemic, especially in the poorest and most vulnerable regions (Pacific coast, Amazon and Orinoco). This note constitutes a call to Colombia's public health system to maintain vector and water-borne diseases services, which cannot become neglected amid the COVID-19 pandemic., (© 2020 Elsevier B.V. All rights reserved.)

The dominant "convection" model of atmospheric circulation is based on the premise that hot air expands and rises, to be replaced by colder air, thereby creating horizontal surface winds. A recent theory put forward by Makarieva and Gorshkov (2007, 2013) maintains that the primary motive force of atmospheric circulation derives from the intense condensation and sharp pressure reduction that is associated with regions where a high rate of evapotranspiration from natural closed-canopy forests provides the "fuel" for cloud formation. The net result of the "biotic pump" theory is that moist air flows from ocean to land, drawn in by the pressure changes associated with a high rate of condensation. Discussion Paper | Discussion To test the physics underpinning the biotic pump theory, namely that condensation of water vapour, at a suficiently high rate, results in an uni-directional airflow, a 5m tall experimental apparatus was designed and built, in which a 20m³ body of atmospheric air is enclosed inside an annular 14m long space (a "square donut") around which it can circulate freely, allowing for rotary air flows. One vertical side of the apparatus contains some 17m of copper refrigeration coils, which cause condensation. The apparatus contains a series of sensors measuring temperature, humidity and barometric pressure every five seconds, and air flow every second. The laws of Newtonian physics are used in calculating the rate of condensation inside the apparatus. The results of more than one hundred experiments show a highly significant correlation, with r² > 0.9, of airflow and the rate of condensation. The rotary air flows created appear to be consistent both in direction and velocity with the biotic pump hypothesis, the critical factor being the rate change in the partial pressure of water vapour in the enclosed body of atmospheric air. Air density changes, in terms of kinetic energy, are found to be orders of magnitude smaller than the kinetic energy of partial pressure change. The consistency of the laboratory experiments, in confirming the physics of the biotic pump, has profound implications for current mathematical climate models, not just in terms of predicting the consequences of widespread deforestation, but also for better understanding the atmospheric processes which lead to air mass convection. [ABSTRACT FROM AUTHOR]

Clear-cut evidences of global environmental change in Colombia are discussed for diverse hydro-climatic records, and illustrated herein for increasing minimum temperature and decreasing annual maximum river flows records. As a consequence, eight tropical glaciers disappeared from the Colombian Andes during the 20th century, and the remaining six have experienced alarming retreat rates during the last decade. Here we report an updated estimation of retreat rates in the six remaining glacierized mountain ranges of Colombia for the period 1987-2007, using Landsat TM and TM+ imagery. Analyses are performed using detailed pre-processing, processing and post-processing satellite imagery techniques. Alarming retreat rates are confirmed in the studied glaciers, with an overall area shrinkage from 60 km² in 2002, to 55.4 km² in 2003, to less than 45 km² in 2007. Assuming such linear loss rate (~3 km² per year), for the near and medium term, the total collapse of the Colombian glaciers can be foreseen by 2022, but diverse physical mechanisms discussed herein would exacerbate the shrinkage processes, thus prompting us to forecast a much earlier deadline by the late 2010-2020 decade, long before the 100 years foreseen by the 2007 IPCC Fourth Assessment Report. This forecast demands detailed monitoring studies of mass and energy balances. Our updated estimations of Colombia's glacier retreat rates posse serious challenges for highly valuable ecosystem services, including water supply of several large cities and hundreds of rural settlements along the Colombian Andes, but also for cheap and renewable hydropower generation which provides 80% of Colombia's demand. Also, the identified changes threaten the survivability of unique and fragile ecosystems like paramos and cloud forests, in turn contributing to exacerbate social unrest and ongoing environmental problems in the tropical Andes which have been identified as the most critical hotspot for biodiversity on Earth. Colombia requires support from the global adaptation fund to develop research, and to design policies, strategies and tools to cope with these urgent social and environmental threats. [ABSTRACT FROM AUTHOR]

Debate and deliberation surrounding climate change has shifted from mitigation toward adaptation, with much of the adaptation focus centered on adaptive practices, and infrastructure development. However, there is little research assessing expected impacts, potential benefits, and design challenges that exist for reducing vulnerability to expected climate impacts. The uncertainty of design requirements and associated government policies, and social structures that reflect observed and projected changes in the intensity, duration, and frequency of water-related climate events leaves communities vulnerable to the negative impacts of potential flood and drought. The results of international research into how agricultural infrastructure features in current and planned adaptive capacity of rural communities in Argentina, Canada, and Colombia indicate that extreme hydroclimatic events, as well as climate variability and unpredictability are important for understanding and responding to community vulnerability. The research outcomes clearly identify the need to deliberately plan, coordinate, and implement infrastructures that support community resiliency.

Background: Pectinase enzymes catalyze the breakdown of pectin, a key component of the plant cell wall. At industrial level, pectinases are used in diverse applications, especially in food-processing industry. Currently, most of the industrial pectinases have optimal activity at mesophilic temperatures. On the contrary, very little is known about the pectinolytic activities from organisms from cold climates such as Antarctica. In this work, 27 filamentous fungi isolated from marine sponges collected in King George Island, Antarctica, were screened as new source of cold-active pectinases., Results: In semi-quantitative plate assays, 8 out 27 of these isolates showed pectinolytic activities at 15 °C and one of them, Geomyces sp. strain F09-T3-2, showed the highest production of pectinases in liquid medium containing pectin as sole carbon source. More interesting, Geomyces sp. F09-T3-2 showed optimal pectinolytic activity at 30 °C, 10 °C under the temperature of currently available commercial mesophilic pectinases., Conclusion: Filamentous fungi associated with Antarctic marine sponges are a promising source of pectinolytic activity. In particular, pectinases from Geomyces sp. F09-T3-2 may be potentially suitable for biotechnological applications needing cold-active pectinases. To the best of our knowledge, this is the first report describing the production of pectinolytic activity from filamentous fungi from any environment in Antarctica.

The present work uses a new approach to causal inference between complex systems called the Recurrence Measure of Conditional Dependence ( RMCD ) based on the recurrence plots theory, in order to study the role of the Amazon River basin (AM) as a land-atmosphere bridge between the Niño 3.0 region in the Pacific Ocean and the Tropical North Atlantic. Two anomalous droughts in the Amazon River basin were selected, one mainly attributed to the warming of the Tropical North Atlantic (2005) and the other to a warm phase of El Niño-Southern Oscillation (2010). The results of the RMCD analysis evidence the distinctive behavior in the causal information transferred between the two oceanic regions during the two extreme droughts, suggesting that the land-atmosphere bridge operating over the AM is an active hydroclimate mechanism at interannual timescales, and that the RMCD analysis may be an ancillary resort to complement early warning systems.

This paper studies a 3-D state space representation of Budyko's framework designed to capture the mutual interdependence among long-term mean actual evapotranspiration (E), potential evapotranspiration (Ep) and precipitatioψn (P). For this purpose we use three dimensionless and dependent quantities: DE=P , ΦDEp=P and ΩDE=Ep. This 3-D space and its 2-D projections provide an interesting setting to test the physical soundness of Budyko's hypothesis. We demonstrate analytically that Budyko-type equations are unable to capture the physical limit of the relation between Ω and Φ in humid environments, owing to the unfeasibility of Ep=P D0 when E=Ep→1. Using data from 146 sub-catchments in the Amazon River basin we overcome this inconsistency by proposing a physically consistent power law: Ψ =k #934; e, with k =0.66, and e=0.83 (R2 =0.93). This power law is compared with two other Budyko-type equations. Taking into account the goodness of fits and the ability to comply with the physical limits of the 3-D space, our results show that the power law is better suited to model the coupled water and energy balances within the Amazon River basin. Moreover, k is found to be related to the partitioning of energy via evapotranspiration in terms of Ω. This suggests that our power law implicitly incorporates the complementary relationship of evapotranspiration into the Budyko curve, which is a consequence of the dependent nature of the studied variables within our 3-D space. This scaling approach is also consistent with the asymmetrical nature of the complementary relationship of evapotranspiration. Looking for a physical explanation for the parameters k and e, the interannual variability of individual catchments is studied. Evidence of space-time symmetry in Amazonia emerges, since both between-catchment and between-year variability follow the same Budyko curves. Finally, signs of co-evolution of catchments are explored by linking spatial patterns of the power law parameters with fundamental characteristics of the Amazon River basin. In general, k and e are found to be related to vegetation, topography and water in soils. [ABSTRACT FROM AUTHOR]

This paper studies a 3-D generalization of Budyko's framework designed to capture the mutual interdependence among long-term mean actual evapotranspiration (E), potential evapotranspiration (Ep) and precipitation (P). For this purpose we use three dimensionless and dependent quantities: Ψ=E/P, Φ=Ep/P and Ω=E/Ep. This 3-D space and its 2-D projections provide an interesting setting to test the physical soundness of Budyko's hypothesis. We demonstrate analytically that Budyko-type equations are unable to capture the physical limit of the relation between ő and Φ in humid environments, owing to the unfeasibility of Ep/P →0 at E/Ep =1. Using data from 146 sub-catchments in the Amazon River basin we overcome this inconsistency by proposing a physically consistent power law:Ψ=kΦe, with k =0.66, and e=0.83 (R² =0.93). This power law is compared with two other Budyko-type equations. Taking into account the goodness of fits and the ability to comply with the physical limits of the 3-D space, our results show that the power law is better suited to model the coupled water and energy balances within the Amazon River basin. Moreover, k is found to be related to the partitioning of energy via evapotranspiration in terms of Ω. This suggests that our power law implicitly incorporates the complementary relationship of evapotranspiration into the Budyko curve, which is a consequence of the dependent nature of the studied variables within our 3-D space. This scaling approach is also consistent with the asym metrical nature of the complementary relationship of evapotranspiration. Looking for a physical explanation for the parameters k and e, the inter-annual variability of individual catchments is studied. Evidence of space-time symmetry in Amazonia emerges, since both between-catchment and between-year variability follow the same Budyko curves. Finally, signs of co-evolution of catchments are explored by linking spatial patterns of the power law parameters with fundamental characteristics of the Amazon River basin. In general, k and e are found to be related to vegetation, topography and water in soils. [ABSTRACT FROM AUTHOR]

Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Here we propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts.

Abstract: Societal needs for climate information on decadal timescales is confirmed in terms of its potential value and relevance as a driver in sector decision-making, but such information is currently lacking. Predictions and observationally based analyses for decadal climate variability and change are needed. In addition, the following issues have been identified as those that must be addressed in order to facilitate effective use of climate information on decadal timescales in the decision-making processes of different socio-economic sectors: building effective partnership systems linking stakeholders, users and decision-making sectors and climate information providers; more research and investment is to translate information of large-scale decadal variations into the regional and local scales required for decisions; maintaining and sustaining the Global Climate Observing System (GCOS), in particular, enhancement of the global ocean observing system; and, ways to assemble, check quality, reprocess and reanalyse datasets relevant to decadal prediction. Ways of securing climate observing systems particularly in least developed regions are urgently needed. [ABSTRACT FROM AUTHOR]

We study diverse scaling and information theory characteristics of Mesoscale Convective Systems (MCSs) as seen by the Tropical Rainfall Measuring Mission (TRMM) over continental and oceanic regions of tropical South America, and 2-D radar rainfall fields from Amazonia. The bi-dimensional Fourier spectra of MCSs exhibit inverse power laws with respect to the spatial scale, whose scaling exponents, β, capture the type of spatial correlation of rainfall among the study regions, including those over the Andes of Colombia as well as over oceanic and Amazonian regions. The moment-scaling analysis evidences that the structure function deviates from simple scaling at order q > 1.0, thus signaling the multi-scaling nature of rainfall fields within MCSs in tropical South America, with departures from simple scaling associated with the physical characteristics of MCSs over the different study regions. Entropy is estimated for a large set of radar rainfall fields during the distinctive atmospheric regimes (Easterly and Westerly events) in this part of Amazonia. Results evidence that there are significant differences in the dynamics of rainfall among regimes. No clear-cut relationship is found between entropy and the first two statistical moments, but power fits in space and time, S(γ) ∼ γ(-η) for skewness and, S(κ) ∼ κ(-ϵ) for kurtosis. The exponents η and ϵ are statistically different between Easterly and Westerly events, although the significance of fits is less when L-moments are used to estimate skewness and kurtosis. Interesting differences are identified between the time and space generalized q-entropy functions of Amazonian rainfall fields. In both cases, the functions are a continuous set of power laws (analogous to the structure function in turbulence), S(T, q) ∼ T(β), and, S(λ, q) ∼ λ(β), covering a broad range of temporal and spatial scales. Both time and space generalized q-entropy functions exhibit linear growth in the range -1.0 < q < -0.5, and saturation of the exponent β for q ≥ 1.0. In the case of the spatial analysis, the exponent saturates at 〈β〉∼1.0, whereas at 〈β〉=0.5 for the temporal case. Results are similar for time series extracted from the S-POL radar and time series of rainfall in tropical Andes. Additionally, differences in values of 〈β〉 for q ≥ 1.0 between Easterly and Westerly events are not statistically significant.

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]

One of the most promising fields for ambient intelligence is the implementation of intelligent emergency plans. Because the use of drills and living labs cannot reproduce social behaviors, such as panic attacks, that strongly affect these plans, the use of agent-based social simulation provides an approach to evaluate these plans more thoroughly. (1) The hypothesis presented in this paper is that there has been little interest in describing the key modules that these simulators must include, such as formally represented knowledge and a realistic simulated sensor model, and especially in providing researchers with tools to reuse, extend and interconnect modules from different works. This lack of interest hinders researchers from achieving a holistic framework for evaluating emergency plans and forces them to reconsider and to implement the same components from scratch over and over. In addition to supporting this hypothesis by considering over 150 simulators, this paper: (2) defines the main modules identified and proposes the use of semantic web technologies as a cornerstone for the aforementioned holistic framework; (3) provides a basic methodology to achieve the framework; (4) identifies the main challenges; and (5) presents an open and free software tool to hint at the potential of such a holistic view of emergency plan evaluation in indoor environments.

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]