Dr. Lara-Peña, Carlos

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.

Worldwide climate‐driven shifts in the distribution of species is of special concern when it involves habitat‐forming species. In the coastal environment, large Laminarian algae—kelps—form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat‐forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of −17.08° S of latitude for 2090–2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to −27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio‐ecological systems of the Southeast Pacific.

Spatial synchrony occurs when geographically separated time series exhibit correlated temporal variability. Studies of synchrony between different environmental variables within marine ecosystems worldwide have highlighted the extent of system responses to exogenous large-scale forcing. However, these spatial connections remain largely unstudied in marine systems, particularly complex coastlines, where a paucity of field observations precludes the analysis of time series. Here, we used time-frequency analyses based on wavelet and wavelet coherence (WC) analysis to quantify the synchrony (co-variations) between environmental time series derived from MODIS (moderate resolution imaging spectroradiometer) in the topographically complex inner sea of Chiloé (ISC, 41–44°S) for the 2003–2022 period. We find that the strength of the synchrony between chlorophyll a (𝐶ℎ𝑙𝑎) and turbid river plumes (for which we use remote sensing reflectance at 645 nm, 𝑅𝑟𝑠645) varies between the northern and southern areas of the ISC; higher synchrony, measured as the WC between these variables, is observed along the northern basin where water and particle exchanges with the Pacific Ocean are reduced. The WC analysis showed higher synchrony between these variables, with dominant periodicities of 0.5 and 1 year resulting from the hydrological regime of the freshwater input in the area that persisted throughout the 2004–2018 period. Our results suggest that the strong and significant spatial synchrony at the regional scale is likely related to the phases of large-scale climatic oscillations, as inferred through the partial wavelet coherence analysis. Potential mechanisms driving spatial synchrony are discussed in the context of climate and oceanographic regimes in the area.