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Biology subjects

Treml, E.

Publications and source records attributed to Treml, E..

2 recordsLinked to original sources

Leveraging the Red List of Ecosystems for national action on coral reefs through the Kunming-Montreal Global Biodiversity Framework

Countries have committed to conserving and restoring ecosystems after signing the Kunming-Montreal Global Biodiversity Framework (GBF). The IUCN Red List of Ecosystems (RLE) will serve as a headline indicator to track progress of countries towards achieving this goal, and to guide action across the GBFs targets. Using Kenyan coral reefs, we demonstrate how nations implementing the GBF, can use standardised estimates of ecosystem degradation from RLE assessments to support site-specific management decisions. We undertook a reef-by-reef analysis to evaluate the relative severity of decline of four key ecosystem components over the past 50-years: hard corals, macroalgae, parrotfish and groupers. Using the two benthic indicators, we also calculated standardised estimates of state to identify reef sites which maintain a better condition through time relative to adjacent sites. Over the past 50 years, Kenyas coral reefs have degraded across all four ecosystem components. At more than half the monitored sites both parrotfish and grouper abundance declined by more than 50%, while coral cover and macroalgae-coral ratio declined by at least 30%. This resulted in a Vulnerable threat status for coral reefs in Kenya based on degradation (under criterion D of the RLE). The temporal trends in coral cover revealed four sites which maintained an above average condition over their monitoring history (15-25 years). The results can guide management actions to contribute to at least nine of the 23 GBF targets. For example, we identified several sites with relatively healthy benthic and fish communities as candidate areas for protection measures under Target 3. We also found that Marine Protected Areas and Locally Managed Marine Areas, which restrict fishing and control gears, had lower declines in groupers compared to unmanaged areas, providing further evidence for their expansion. The RLE has a key role to play in monitoring and meeting the goals and targets of the Global Biodiversity Framework, and our work demonstrates how using the wealth of data within these assessments can inform local-scale ecosystem management and amplify the GBFs impact.

ecology↗

Predicting coral adaptation to global warming in the Indo-West-Pacific

The potential of reef-building corals to adapt to increasing sea surface temperatures is often speculated about but has rarely been comprehensively modeled on a region-wide scale. Here, we used individual-based simulations to model adaptation to warming in a coral metapopulation comprising 680 reefs and representing the whole of the Central Indo-West Pacific. We find that in the first century of warming (approximately from 50 years ago to 50 years in the future) corals adapt rapidly by redistributing pre-existing adaptive alleles among populations (\"genetic rescue\"). In this way, some coral populations - most notably, Vietnam, Japan, Taiwan, New Caledonia, and the southern half of the Great Barrier Reef - appear to be able to maintain their fitness even under the worst warming scenarios (at least in theory, assuming the rate of evolution is the only limitation to local coral recovery). Still, survival of the majority of reefs in the region critically depends on the warming rate, underscoring the urgent need to curb carbon emissions. Conveniently, corals adaptive potential was largely independent of poorly known genetic parameters and could be predicted based on a simple metric derived from the biophysical connectivity model: the proportion of recruits immigrating from warmer locations. We have confirmed that this metric correlates with actual coral cover changes throughout the region, based on published reef survey data from the 1970s to early 2000s. The new metric allows planning assisted gene flow interventions to facilitate adaptation of specific coral populations.

evolutionary biology↗