Short-term response of macroalgal communities to ocean warming in the Southern Bay of Biscay
Climate change is causing significant shifts in biological communities worldwide, including the degradation of marine communities. Previous research has predicted that southern Bay of Biscay canopy-forming subtidal macroalgal communities will shift into turf-forming Mediterranean-like communities by...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/68133 |
| Acceso en línea: | http://hdl.handle.net/10810/68133 |
| Access Level: | acceso abierto |
| Palabra clave: | climate change temperature macroalgae community temperature index (CTI) canopy subtidal Iberian Peninsula monitoring |
| Sumario: | Climate change is causing significant shifts in biological communities worldwide, including the degradation of marine communities. Previous research has predicted that southern Bay of Biscay canopy-forming subtidal macroalgal communities will shift into turf-forming Mediterranean-like communities by the end of the century. These predictions were based on a community-environment relationship model that used macroalgal abundance data and IPCC environmental projections. We have tested the short-term accuracy of that model by resampling the same communities and locations four years later and found the short-term predictions to be consistent with the observed communities. Changes in sea surface temperature were positively correlated with changes in the Community Temperature Index, suggesting that macroalgal communities had responded quickly to global warming. The changes over four years were significant, but canopy-forming macroalgae were more resilient in local sites with favourable temperature conditions. Our study demonstrated that updating predictive models with new data has the potential to yield reliable predictions and inform effective conservation strategies. |
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