• Energy Research
• 2021-2025close

Data associated with the paper "Projected loss of brown macroalgae and seagrasses with global environmental change" by Federica Manca, Lisandro Benedetti-Cecchi, Corey J. A. Bradshaw, Mar Cabeza, Camilla Gustafsson, Alf M. Norkko, Tomas V. Roslin, David N. Thomas, Lydia White, Giovanni Strona

AbstractAlthough many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity remain relatively unexplored. In this work, we model global shifts in one of the most important marine functional groups—ecosystem-structuring macrophytes—and predict substantial end-of-century change. By modelling the future distribution of 207 brown macroalgae and seagrass species at high temporal and spatial resolution under different climate-change projections, we estimate that by 2100, local macrophyte diversity will decline by 3–4% on average, with 17 to 22% of localities losing at least 10% of their macrophyte species. The current range of macrophytes will be eroded by 5–6%, and highly suitable macrophyte habitat will be substantially reduced globally (78–96%). Global macrophyte habitat will shift among marine regions, with a high potential for expansion in polar regions.

Significance Species loss can weaken the trophic interactions that underpin ecosystem functioning. Coral reefs are the world’s most diverse marine ecosystem, harboring interaction networks of extraordinary complexity. We show that, despite this complexity, global coral reef food webs are governed by a suite of highly consistent energetic pathways, regardless of regional differences in biodiversity. All networks are characterized by species with narrow dietary preferences, arranged into distinct groups of predator–prey interactions. These characteristics suggest that coral reef food webs are robust to the loss of prey resources but vulnerable to local extinctions of consumer species.

AbstractEcosystems face both local hazards, such as over-exploitation, and global hazards, such as climate change. Since the impact of local hazards attenuates with distance from humans, local extinction risk should decrease with remoteness, making faraway areas safe havens for biodiversity. However, isolation and reduced anthropogenic disturbance may increase ecological specialization in remote communities, and hence their vulnerability to secondary effects of diversity loss propagating through networks of interacting species. We show this to be true for reef fish communities across the globe. An increase in fish-coral dependency with the distance of coral reefs from human settlements, paired with the far-reaching impacts of global hazards, increases the risk of fish species loss, counteracting the benefits of remoteness. Hotspots of fish risk from fish-coral dependency are distinct from those caused by direct human impacts, increasing the number of risk hotspots by ~30% globally. These findings might apply to other ecosystems on Earth and depict a world where no place, no matter how remote, is safe for biodiversity, calling for a reconsideration of global conservation priorities.

AbstractThe biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction‐risk studies only consider the direct effects of global change—such as predicting which species will breach their thermal limits under different warming scenarios—with predictions of trophic cascades and co‐extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real‐world communities. This gap partly reflects challenges in constructing trophic network models of real‐world food webs, highlighting the need to develop approaches for quantifying co‐extinction risk more accurately. We propose a framework for constructing ecological network models representing real‐world food webs in terrestrial ecosystems and subjecting these models to co‐extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co‐extinction (or those that might trigger co‐extinctions) will also guide conservation interventions aiming to reduce the probability of co‐extinction cascades and additional species losses.