Dr. Lara-Peña, Carlos

Coastal wetlands are highly threatened by human activities, leading to water quality degradation and biodiversity loss. This study assessed spatial variation in 27 water quality parameters, sediment organic matter, and macroinvertebrate assemblages across 12 sites in the estuarine Cruces River wetland (CRW Ramsar site, southern Chile) during summer 2019. Our analysis identified three areas of sampling stations in the wetland, categorized by trophic gradient and salinity: freshwater (n = 5), mixed (n = 3), and estuary (n = 4). Freshwater sites were characterized by low salinity, turbidity, and high nitrate concentrations. Estuarine sites were characterized by higher salinities and turbidity and low nitrates and total organic carbon (TOC) concentrations, and mixed sites had low salinities, high turbidities, high TOC, and low nitrates. Throughout the CRW, the richness and densities of different invertebrates were recorded. Freshwater stations had higher species richness, and estuary stations had higher abundance. Macroinvertebrates found in the lower reaches of the CRW included species characteristic of estuarine environments, whereas the upper stations were dominated by invertebrates inhabiting low-salinity environments. According to the ordination plot of distance-based redundancy analysis (dbRDA) and distance-based linear model (DistLM), our results indicate that macroinvertebrate assemblages differ significantly among areas of the CRW, primarily due to physicochemical variables (i.e., salinity, total carbon, and dissolved phosphorus). Total organic matter content in sediments was higher in freshwater sites and lower in estuarine sites. Our findings will be used to monitor the wetland and implement appropriate management measures for human activities, thereby protecting and conserving the estuarine Cruces River Ramsar wetland.

Kelp forest are foundation species that deliver key ecosystem services for coastal habitats. Chile is one of the largest exporters of kelp biomass, which relies on the harvesting of wild populations. The vast and rugged coastline of Chile hinders field-based studies of the seasonal and spatial dynamics of kelp biomass, yet remote sensing approaches can provide an effective tool to study temporal patterns of kelp distribution and biomass. Our study aimed to establish the basic patterns of variation in the surface area and biomass of a Macrocystis pyrifera forest off Concepcion Bay, Central Chile. Using archival data from the Landsat series we constructed a long-term series of annual kelp canopy cover and assessed patterns of interannual, and a seasonal variation with the more recent Sentinel 2 data using Google Earth Engine. We validated satellite observations of the kelp forest in the field by recording local temperature and nutrient concentrations and through a sample of blades and stipes, which we used to estimate whole-individual in situ biomass through allometric relationships. Finally, we related decadal to interannual changes in canopy cover to local and regional drivers using data from public repositories. Our 24-year annual time series revealed large year-to-year variability in kelp forest area that did not show a significant association with different El Niño-Southern Oscillation indices, but the deviance explained increased notably with a 1-year lag. The seasonal time series exhibited clear seasonal patterns with cover peaking during summer. We found a significant influence of local environmental variables such as temperature, wave height, nitrate concentration, and solar radiation on kelp forest area. Furthermore, blade counts appeared as the most reliable metric for estimating M. pyrifera biomass. Interestingly, we found no evidence of temperature or nutrient stress during the summer biomass peak, hence seasonal variation in M. pyrifera abundance appears to be primarily influenced by solar radiation and wave activity in our study population. Our results provide a basis to derive seasonal time series across Chile’s kelp forests and suggest that understanding local stressors is key to ensure harvesting practices that promote the sustainable management of these key habitats. As ongoing climate change and overexploitation threaten kelp forest habitats, remote sensing emerges as a promising tool for the monitoring and management of extensive and remote coastlines.

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.