Aichi Target 11 committed governments to protect ≥17% of their terrestrial environments by 2020, yet it was rarely achieved, raising questions about the post-2020 Global Biodiversity Framework goal to protect 30% by 2030. Asia is a challenging continent for such targets, combining high biodiversity with dense human populations. Here, we evaluated achievements in Asia against Aichi Target 11. We found that Asia was the most underperforming continent globally, with just 13.2% of terrestrial protected area (PA) coverage, averaging 14.1 ± SE 1.8% per country in 2020. 73.1% of terrestrial ecoregions had <17% representation and only 7% of PAs even had an assessment of management effectiveness. We found that a higher agricultural land in 2015 was associated with lower PA coverage today. Asian countries also showed a remarkably slow average annual pace of 0.4 ± SE 0.1% increase of PA extent. These combined lines of evidence suggest that the ambitious 2030 targets are unlikely to be achieved in Asia unless the PA coverage to increase 2.4-5.9 times faster. We provided three recommendations to support Asian countries to meet their post-2020 biodiversity targets: complete reporting and the wider adoption "other effective area-based conservation measures"; restoring disturbed landscapes; and bolstering transboundary PAs.
One mechanism proposed to explain high species diversity in tropical systems is strong negative conspecific density dependence (CDD), which reduces recruitment of juveniles in proximity to conspecific adult plants. Although evidence shows that plant-specific soil pathogens can drive negative CDD, trees also form key mutualisms with mycorrhizal fungi, which may counteract these effects. Across 43 large-scale forest plots worldwide, we tested whether ectomycorrhizal tree species exhibit weaker negative CDD than arbuscular mycorrhizal tree species. We further tested for conmycorrhizal density dependence (CMDD) to test for benefit from shared mutualists. We found that the strength of CDD varies systematically with mycorrhizal type, with ectomycorrhizal tree species exhibiting higher sapling densities with increasing adult densities than arbuscular mycorrhizal tree species. Moreover, we found evidence of positive CMDD for tree species of both mycorrhizal types. Collectively, these findings indicate that mycorrhizal interactions likely play a foundational role in global forest diversity patterns and structure.
Coral reefs in the Central Indo-Pacific region comprise some of the most diverse and yet threatened marine habitats. While reef monitoring has grown throughout the region in recent years, studies of coral reef benthic cover remain limited in spatial and temporal scales. Here, we analysed 24,365 reef surveys performed over 37 years at 1972 sites throughout East Asia by the Global Coral Reef Monitoring Network using Bayesian approaches. Our results show that overall coral cover at surveyed reefs has not declined as suggested in previous studies and compared to reef regions like the Caribbean. Concurrently, macroalgal cover has not increased, with no indications of phase shifts from coral to macroalgal dominance on reefs. Yet, models incorporating socio-economic and environmental variables reveal negative associations of coral cover with coastal urbanisation and sea surface temperature. The diversity of reef assemblages may have mitigated cover declines thus far, but climate change could threaten reef resilience. We recommend prioritisation of regionally coordinated, locally collaborative long-term studies for better contextualisation of monitoring data and analyses, which are essential for achieving reef conservation goals.
Deep-learning (DL) methods like DeepMind's AlphaFold2 (AF2) have led to substantial improvements in protein structure prediction. We analyse confident AF2 models from 21 model organisms using a new classification protocol (CATH-Assign) which exploits novel DL methods for structural comparison and classification. Of ~370,000 confident models, 92% can be assigned to 3253 superfamilies in our CATH domain superfamily classification. The remaining cluster into 2367 putative novel superfamilies. Detailed manual analysis on 618 of these, having at least one human relative, reveal extremely remote homologies and further unusual features. Only 25 novel superfamilies could be confirmed. Although most models map to existing superfamilies, AF2 domains expand CATH by 67% and increases the number of unique 'global' folds by 36% and will provide valuable insights on structure function relationships. CATH-Assign will harness the huge expansion in structural data provided by DeepMind to rationalise evolutionary changes driving functional divergence.