National University of Río Negro

Socio-environmental conflicts associated with large-scale economic projects in Indigenous territories are well documented, but conflicts in coastal areas remain largely unexplored, despite the crucial differences between inland and coastal ecosystems. While the empirical literature about socio-environmental conflicts in Indigenous territories in coastal areas is growing, the role of financial institutions and corporations in these conflicts is often overlooked. This study addresses this gap by examining the financial institutions and corporations associated with more than 400 reported socio-environmental conflicts affecting Indigenous Peoples in coastal areas worldwide. Our results show that most financial institutions supporting projects linked to conflicts are based in West Europe and North America, with North American financial institutions linked to multiple projects. The energy sector accounts for the highest number of socio-environmental conflicts, particularly those involving corporations operating across continents. Many European and North American corporations operate mostly in Africa, but also globally. Corporations with overseas operations are associated with a higher intensity of conflicts. These findings highlight the need to scrutinize financial investments and corporate practices driving socio-environmental conflicts in coastal Indigenous territories, where human rights are often at risk. The lack of due diligence and accountability in applying environmental and social safeguards weakens protections for both ecosystems and Indigenous communities. Strengthening the enforcement of national and international laws on environmental sustainability, human rights and Indigenous rights is therefore essential for coastal development projects.

We present an analysis of the electrokinetic coupling equations developed in a previous work by the same authors, where an extension to Pride’s theory encompassing partially saturated porous rocks was derived. One of the main hypotheses of the model establishes that the non-wetting fluid phase must be connected across the averaging volume, which may not be the case near full wetting phase saturation. This constraint is removed by developing new expressions for the model parameters, such as electric conductivity and electrokinetic coupling coefficient, accounting for the disconnection of the non-wetting fluid near full saturation. We study their sensitivity to the salinity of the electrolyte and to geometric parameters, such as porosity, tortuosity, and volume-to-surface ratio of the non-wetting fluid. Moreover, we consider different sets of values of the two different zeta potentials present in the model, one of which originates at the pore-wall/wetting-fluid interface and the other at the wetting/non-wetting fluid interface. Our model predicts that the electric conductivity, the electrokinetic coupling coefficient, and the streaming potential coefficient may show either a monotonic or a non-monotonic behaviour as a function of water saturation, depending on water salinity and geometrical parameters, and they tend to the corresponding saturated values predicted by Pride when water saturation tends to one. We show that the electric conductivity model predictions are in good agreement with data sets from the literature. Further, we numerically simulate the electrokinetic coupling phenomenon during drainage experiments over a rock column. The so-obtained ratio of the electric potential difference to the water pressure variation reproduces the main features of previously published data obtained in laboratory measurements for clean rocks.

The present study evaluates, for the first time, the concentration and distribution of metals (Cd, Cu, Cr, Fe, Hg, Mn, Ni, Pb, Zn) in the sediments of the seabed of El Rincón and adjacent shelf areas, in the South Atlantic coast. Over a three-year period, coastal sectors were differentiated from offshore platform areas. The results revealed spatial and temporal differences, with concentration ranges of < LOD—2.58 mg/kg for Hg, < LOD—0.655 mg/kg for Cd, 24—638 mg/kg for Mn, 2.46—26.89 mg/kg for Cr, 2.02—13.43 mg/kg for Ni, 1.41—6.47 mg/kg for Pb, 0.44 -13.90 mg/kg for Cu, 5.85—36.05 mg/kg for Zn and 8300—43900 mg/kg for Fe. The concentrations of Cd were high and reached values ​​close to, but without exceeding, the maximum level recommended by the Sediment Quality Guidelines for marine and estuarine sediments (0.7 mg/kg), while Hg concentrations exceeded the Sediment Quality Guidelines (0.13 mg/kg) and the Probable Effect Level values (0.70 mg/kg). For Hg, the geoaccumulation index and the enrichment factor revealed highly contaminated sediments across all sectors during 2016. For Cd and Mn, only a minor anthropogenic impact was suggested through the enrichment factor, while the geoaccumulation indicated an absence of contamination by these metals. Overall, being an integrated index, the PLI indicated no metal pollution for the study area even when individual metrics for Hg revealed severe contamination. Therefore, long-term monitoring of this metal is crucial to assess potential ecological risks and support the development of environmental management policies to prevent potential adverse effects.

This study evaluated the impact of the presence of diseases within the first 21 days in milk (DIM) in dairy cows on metabolic status after the voluntary waiting period (VWP), conception at first service, infectious disease seroconversion, and the association between metabolic status at first artificial insemination (AI) and conception at first service. Cows were classified as sick (n = 48) or healthy (n = 75) based on diseases within 21 DIM. Blood samples were obtained at first AI (D0), pregnancy diagnosis (D30), and pregnancy confirmation (D60) after the first AI. Samples were analyzed for glucose, cholesterol, aspartate aminotransferase, alanine aminotransferase, non-esterified fatty acids (NEFA), and insulin-like growth factor 1 (IGF-1) using a linear mixed model for repeated measures. An Energetic Metabolic Index (EMI) at AI was calculated, integrating cholesterol, NEFA, and glucose. Logistic regression models were used to predict EMI, conception at first service, and seroconversion to Leptospira spp. and Bovine Viral Diarrhea Virus (BVDV). The presence of diseases did not affect the metabolic status after the VWP (P > 0.05); however, changes in blood metabolites by day were observed (P < 0.001). EMI was not associated with the presence of diseases (P = 0.13). EMI, IGF-1 concentration, and the presence of diseases were significant predictors of conception at first service (P ≤ 0.05). Sick cows were 37 times more likely to seroconvert to BVDV at D60 (P = 0.001). EMI at AI may serve as a valuable biological marker for predicting fertility. Simple summary: This study identifies the association between the presence of diseases within the first 21 days in milk in dairy cows and metabolic status after the voluntary waiting period, conception at first service, and the effect of metabolic status at first artificial insemination on conception. Integrating multiple metabolites into an Energetic Metabolic Index (EMI) may improve the prediction of fertility outcomes by better capturing complex metabolic responses than relying on insufficient single metabolite analyses. EMI and the presence of diseases were significant predictors of conception at first service. The EMI may serve as a potential biological marker for predicting fertility.

Symbolic time series analyses are used in economics and other social sciences as a way of reducing the impact of noise on data and to exhibit more clearly the evolution of time series. We show that causality tests applied to symbolic series may fail to detect actual relations or generate statistical artifacts. Well-known causality detection methods, like transfer entropy, Granger's test, or Peter-Clark Momentary Conditional Independence (PCMCI), may miss some existing causal relationships or, more frequently, yield non-existent ones. The performance of these methods may differ, depending on the specific choices of lag structures and alphabet sizes, as well as on the characteristics of the underlying dynamic process.