Dr. Lara-Peña, Carlos

Surface oceanic fronts are regions characterized by high biological activity. Here, Sea Surface Temperature (SST) fronts are analyzed for the period 2003–2019 using the Multi-scale Ultra-high Resolution (MUR) SST product in northern Patagonia, a coastal region with high environmental variability through river discharges and coastal upwelling events. SST gradient magnitudes were maximum off Chiloé Island in summer and fall, coherent with the highest frontal probability in the coastal oceanic area, which would correspond to the formation of a coastal upwelling front in the meridional direction. Increased gradient magnitudes in the Inner Sea of Chiloé (ISC) were found primarily in spring and summer. The frontal probability analysis revealed the highest occurrences were confined to the northern area (north of Desertores Islands) and around the southern border of Boca del Guafo. An Empirical Orthogonal Function analysis was performed to clarify the dominant modes of variability in SST gradient magnitudes. The meridional coastal fronts explained the dominant mode (78% of the variance) off Chiloé Island, which dominates in summer, whereas the SST fronts inside the ISC (second mode; 15.8%) were found to dominate in spring and early summer (October–January). Future efforts are suggested focusing on high frontal probability areas to study the vertical structure and variability of the coastal fronts in the ISC and its adjacent coastal ocean.

This study assessed natural variation in the macroinvertebrate assemblages (MIB) and water quality in one of the main basins with the largest agricultural activities in Chile (Aconcagua River Basin). We sampled throughout the annual cycle; nine sampling sites were established along the basin, classifying according to agricultural area coverage as least-disturbed, intermediate, and most-disturbed. We collected 56 macroinvertebrate taxa throughout the entire study area. Multivariate analysis shows significant differences among the three disturbance categories in different seasons, both water quality variables and the MIB structure. Distance-based linear model (DistLM) analysis for all seasons explained more than 95.9% of the macroinvertebrate assemblages, being significantly explained by chemical oxygen demand, pH, total coliforms, nitrites, elevation, and water temperature. ANOVA test revealed significant differences in the proportion of noninsect individuals, macroinvertebrates density, and the number of taxa among the three disturbance categories (p < 0.05). In general, water temperature, conductivity, chemical oxygen demand, ammonium, nitrites, and nitrates increased their values downstream in the basin. Our results indicate that the elevation gradient and increment in agricultural land use in the basin had a strong influence on water quality and MIB. A better understanding of these ecosystems could help conservation and integrated watershed management.

The coastal region off Chilean Patagonia has been poorly studied due to the lack of available observations. Here we analyzed, by the very first time, biogeochemical (BGC) data to elucidate the role that biological and physical processes play on nitrate, oxygen, pH and hydrographic variables, along a salinity gradient off central Patagonia. Argo float profiles covering the upper ocean from December 2015 to July 2019 reveal that offshore waters are characterized by low temperatures and high salinities related to high oxygen and medium-high values of pH and nitrate. As the Argo float drifted onshore, freshwater influences the upper 50–100 m with low salinity and high temperature. Waters under the influence of the continental runoff were characterized by medium-to-high oxygen and pH levels, and the lowest nitrate concentrations. Interestingly, oxygen-deficient waters located beneath the freshwater-modified layer showed the lowest pH and highest nitrate. A comprehensive analysis of the temporal and vertical variability of the oxygen:nitrate ratio, in conjunction with biological-related and physical parameters, indicates that the BGC variability seems to be the result of a synergistic interaction between physical and biological processes, where the stratification sets up the environment and promotes the biological response that, in turn, is auto-regulated by modifying the chemical composition in the freshwater-influenced zone. The arrival of future floats with additional sensors (Chlorophyll/Fluorescence, Photosynthetically Active Radiation, Backscatter, etc.) will add new BGC properties that improve our understanding of the coastal marine response to the increasing freshwater input off western Patagonia in the context of climate change.

Using 19 years of remotely sensed Enhanced Vegetation Index (EVI), we examined the effects of climatic variability on terrestrial vegetation of six protected areas along southwestern South America, from the semiarid edge of the Atacama desert to southern Patagonia (30∘S–51∘S). The relationship between satellite phenology and climate indices, namely MEI (Multivariate ENSO Index), PDO (Pacific Decadal Oscillation) and SAM (Southern Annular Mode) were established using statistical analyses for non-stationary patterns. The annual mode of phenological activity fluctuated in strength through time from the semiarid region to the border of southern Patagonia. Concomitantly, enhanced synchrony between EVI and climatic oscillations appeared over interannual cycles. Cross correlations revealed that variability in MEI was the lead predictor of EVI fluctuations over scales shorter than 4 months at lower latitudes and for the most poleward study site. The PDO was correlated with EVI over lags longer than 4 months at low latitude sites, while the SAM showed relationships with EVI only for sites located around 40∘S. Our results indicate that the long-term phenological variability of the vegetation within protected areas along southwestern South America is controlled by processes linked to climate indices and that their influence varies latitudinally. Further studies over longer time scales will be needed to improve our understanding the impacts of climate change on vegetation condition and its effect over phenological variability.