Worldwide climate-driven shifts in the distribution of species are 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. The Chapter 1 of this thesis 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.
In Chile, a leading kelp exporter, understanding the dynamics of kelp populations is crucial for sustainable management. The extensive and rugged coastline makes monitoring challenging, but remote sensing offers an effective solution for large-scale observation and management of these essential marine ecosystems. The Chapter 2 of this thesis aims to establish patterns of variation in the surface cover of a M. pyrifera forest off Central Chile by linking satellite observations of decadal and seasonal cover with field data and public repositories. Our 23-year time series of a M. pyrifera forest in Central Chile reveals typical year-to-year area fluctuations without discernible trends and no significant association with the El Niño-Southern Oscillation. Furthermore, the seasonal time series using Sentinel-2 data and the NDREB index demonstrated clear seasonal patterns with summer peaks and winter troughs, influenced by local environmental variables such as temperature, nitrate, silicate, and solar radiation. Understanding the seasonality and variables influencing these underwater forests is crucial for the future conservation of these ecosystems and underscores the potential of remote sensing for monitoring extensive and remote coastlines.
This thesis has helped to unveil how the interlinked contributions of environmental variability and climatic oscillations shape the spatio-temporal patterns in global/regional habitat suitability and local seasonal dynamics of M. pyrifera populations. By integrating scientific findings with proactive conservation measures, we can enhance resilience and ensure the future of this crucial habitat.