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Dryad

Supporting Data for Ocean acidification drives global reshuffling of ecological communities

Cite this dataset

Nagelkerken, Ivan; Connell, Sean (2022). Supporting Data for Ocean acidification drives global reshuffling of ecological communities [Dataset]. Dryad. https://doi.org/10.5061/dryad.98sf7m0mv

Abstract

The paradigm that climate change will alter global marine biodiversity is one of the most widely accepted. Yet, its predictions remain difficult to test because laboratory systems are inadequate at incorporating ecological complexity, and common biodiversity metrics have varying sensitivity to detect change. Here, we test for the prevalence of global responses in biodiversity and community-level change to future climate (acidification and warming) from studies at volcanic CO2 vents across four major global coastal ecosystems and studies in laboratory mesocosms. We detected globally replicable patterns of species replacements and community reshuffling under ocean acidification in major natural ecosystems, yet species diversity and other common biodiversity metrics were often insensitive to detect such community change, even under significant habitat loss. Where there was a lack of consistent patterns of biodiversity change, these were a function of similar numbers of studies observing negative vs positive species responses to climate stress. Laboratory studies showed weaker sensitivity to detect species replacements and community reshuffling in general. We conclude that common biodiversity metrics can be insensitive in revealing the anticipated effects of climate stress on biodiversity – even under significant biogenic habitat loss – and can mask widespread reshuffling of ecological communities in a future ocean. Whilst the influence of ocean acidification on community restructuring can be less evident than species loss, such changes can drive the dynamics of ecosystem stability or their functional change. Importantly, species identity matters, representing a substantial influence of future oceans.

Methods

Meta-analysis of published literature - see Materials and methods in main document.

Usage notes

Microsoft Excel

Funding

Australian Research Council, Award: FT120100183 / LP200201000