Search for: All records

Anthropogenic stressors to marine ecosystems from climate change and human activities increase extinction risk of species, disrupt ecosystem integrity, and threaten important ecosystem services. Addressing these stressors requires understanding where and to what extent they are impacting marine biological and functional diversity. We model cumulative risk of human impact upon 21,159 marine animal species by combining information on species-level vulnerability and spatial exposure to a range of anthropogenic stressors. We apply this species-level assessment of human impacts to examine patterns of species-stressor interactions within taxonomic groups. We then spatially map impacts across the global ocean, identifying locations where climate-driven impacts overlap with fishing, shipping, and land-based stressors to help inform conservation needs and opportunities. Comparing species-level modeled impacts to those based on marine habitats that represent important marine ecosystems, we find that even relatively untouched habitats may still be home to species at elevated risk, and that many species-rich coastal regions may be at greater risk than indicated from habitat-based methods alone. Finally, we incorporate a trait-based metric of functional diversity to identify where impacts to functionally unique species might pose greater risk to community structure and ecosystem integrity. These complementary lenses of species, function, and habitat provide a richer understanding of threats to marine biodiversity to help inform efforts to meet conservation targets and ensure sustainability of nature’s contributions to people. 

Geochemical proxies of sea surface temperature (SST) and seawater pH (pH_sw) in scleractinian coral skeletons are valuable tools for reconstructing tropical climate variability. However, most coral skeletal SST and pH_swproxies are univariate methods that are limited in their capacity to circumvent non-climate-related variability. Here we present a novel multivariate method for reconstructing SST and pH_swfrom the geochemistry of coral skeletons. Our Scleractinian Multivariate Isotope and Trace Element (SMITE) method optimizes reconstruction skill by leveraging the covariance across an array of coral elemental and isotopic data with SST and pH_sw. First, using a synthetic proxy experiment, we find that SMITE SST reconstruction statistics (correlation, accuracy, and precision) are insensitive to noise and variable calibration period lengths relative to Sr/Ca. While SMITE pH_swreconstruction statistics remain relative toδ¹¹B throughout the same synthetic experiment, the magnitude of the long-term trend in pH_swis progressively lost under conditions of moderate-to-high analytical uncertainty. Next, we apply the SMITE method to an array of seven coral-based geochemical variables (B/Ca,δ¹¹B, Li/Ca, Mg/Ca, Sr/Ca, U/Ca & Li/Mg) measured from two BermudanPorites astreoidescorals. Despite a <3.5 year calibration period, SMITE SST and pH_swestimates exhibit significantly better accuracy, precision, and correlation with their respective climate targets than the best single- and dual-proxy estimators. Furthermore, SMITE model parameters are highly reproducible between the two coral cores, indicating great potential for fossil applications (when preservation is high). The results shown here indicate that the SMITE method can outperform the most common coral-based SST and pH_swreconstructions methods to date, particularly in datasets with a large variety of geochemical variables. We therefore provide a list of recommendations and procedures for users to begin implementing the SMITE method as well as an open-source software package to facilitate dissemination of the SMITE method.