Research Outputs
Climate-induced habitat shifts of farmed mussel species
Marine mussels are one of the most important sources of cultivated shellfish worldwide, particularly among middle- and low-income countries where they are a key food source for coastal communities. Climate Change is bound to have a large impact on the distribution of suitable habitats for the mussel species cultivated throughout the world. To examine these impacts on mussel aquaculture and global food security, we evaluated the distribution of suitable current and future habitats for the six more widely cultivated mussel species under a Representative Concentration Pathway 8.5 emission scenario using ecological niche modelling. Occurrence records were obtained from online databases and the literature. The models had a good performance in predicting the current distribution of the six study species. In future scenarios, suitable mussel habitats were projected to shift poleward, with gains at higher latitudes and losses at lower latitudes. By 2050, significant impacts were projected along the Mediterranean coast for Mytilus galloprovincialis, an important mariculture species in Europe, and in Southeast Asia for the tropical green mussel Perna viridis. Overall, our predictions suggested that range shifts could create opportunities to expand mussel farming to higher latitudes, yet loss of suitable habitat in historically productive growing areas could disrupt current mussel aquaculture regions, highlighting the need for immediate action. Therefore, achieving a more nuanced understanding of the spatial changes in the geographic distribution of suitable habitats should be the first step in increasing the adaptive capacity of the mussel aquaculture sector, and ensuring the future supply of this key source of aquafood.
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.