Research Outputs
Seasonal and inter-annual dynamics of a Macrocystis pyrifera forest in Concepcion Bay, Chile
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.
Spatio-temporal variability of turbidity derived from Sentinel-2 in Reloncaví sound, Northern Patagonia, Chile
Turbidity is associated with the loss of water transparency due to the presence of particles, sediments, suspended solids, and organic or inorganic compounds in the water, of natural or anthropogenic origin. Our study aimed to evaluate the spatio-temporal variability of turbidity from Sentinel-2 (S2) images in the Reloncaví sound and fjord, in Northern Patagonia, Chile, a coastal ecosystem that is intensively used by finfish and shellfish aqua culture. To this end, we downloaded 123 S2 images and assembled a five-year time series (2016–2020) covering five study sites (R1 to R5) located along the axis of the fjord and seaward into the sound. We used Acolite to perform the atmospheric correction and estimate turbidity with two algorithms proposed by Nechad et al. (2009, 2016 Nv09 and Nv16, respectively). When compared to match-up, and in situ measurements, both algorithms had the same performance (R2 = 0.40). The Nv09 algorithm, however, yielded smaller errors than Nv16 (RMSE = 0.66 FNU and RMSE = 0.84 FNU, respectively). Results from true-color imagery and two Nechad algorithms singled an image from the austral autumn of 2019 as the one with the highest turbidity. Similarly, three images from the 2020 austral autumn (May 20, 25, 30) also exhibited high turbidity values. The turbid plumes with the greatest extent occurred in the autumn of 2019 and 2020, coinciding with the most severe storms and runoff events of the year, and the highest turbidity values. Temporal trends in turbidity were not significant at any of the study sites. However, turbidity trends at sites R1 and R2 suggested an increasing trend, while the other sites showed the opposite trend. Site R1 recorded the highest turbidity values, and the lowest values were recorded at R5 in the center of the sound. The month of May was characterized by the highest turbidity values. The application of algorithms from high-resolution satellite images proved to be effective for the estimation and mapping of this water quality parameter in the study area. The use of S2 imagery unraveled a predictable spatial and temporal structure of turbidity patterns in this optically complex aquatic environment. Our results suggest that the availability of in situ data and the continued evaluation of the performance of the Nechad algorithms can yield significant insights into the dynamics and impacts of turbid waters in this important coastal ecosystem.
CDOM dynamics in two coastal zones influenced by contrasting land uses in northern Patagonia
Colored dissolved organic matter (CDOM) is an indicator and optical proxy of terrestrial processes such as land use with allochthonous material fluxes, biogeochemical cycles, and water quality in coastal zones influenced by rivers. However, the role of land use changes on the spatial and temporal availability of CDOM has been poorly explored in Chile. Here, we studied two watersheds with similar climates and contrasting land use patterns in northern Patagonia considering the sampling of CDOM in their estuarine and adjacent coastal ocean. An empirical algorithm with the coefficients adjusted to our study areas to estimate CDOM was applied to Landsat 7 and 8 images to examine temporal variability of CDOMest from 2001 to 2011 and 2013–2020. Our results showed an increasing trend of CDOMest in both areas. Different trends in land use patterns between the two watersheds showed a significant correlation with CDOMest and contrasting associations with environmental variables. Higher humification was found in Yaldad in comparison with Colu. In both areas, allochthonous materials predominated, especially during austral spring according to the low values of the Fluorescence Index (FI). Our results highlight the potential of CDOMest to parameterize biogeochemical cycling models and to further understand the dynamics of CDOM in coastal ecosystems.