The role of gastropod shell composition and microstructure in resisting dissolution caused by ocean acidification.

Organisms, such as molluscs, that produce their hard parts from calcium carbonate are expected to show increased difficulties growing and maintaining their skeletons under ocean acidification (OA). Any loss of shell integrity increases vulnerability, as shells provide protection against predation, desiccation, and disease. Not all species show the same responses to OA, which may be due to the composition and microstructural arrangement of their shells. We explore the role of shell composition and microstructure in resisting dissolution caused by decreases in seawater pH using a combination of microCT scans, XRD analysis, and SEM imaging. Two gastropods with different shell compositions and microstructure, Tegula funebralis and Nucella ostrina, were exposed to simulated ocean acidification conditions for six months. Both species showed signs of dissolution on the exterior of their shells, but changes in density were significantly more pronounced in T. funebralis. XRD analysis indicated that the exterior layer of both shell types was made of calcite. T. funebralis may be more prone to dissolution because their outer fibrous calcite layer has more crystal edges and faces exposed, potentially increasing the surface area on which dissolution can occur. These results support a previous study where T. funebralis showed significant decreases in both shell growth and strength, but N. ostrina only showed slight reductions in shell strength, and unaffected growth. We suggest that microstructural arrangement of shell layers in molluscs, more so than their composition alone, is critical for determining the vulnerability of mollusc shells to OA.

Ocean change within shoreline communities: from biomechanics to behaviour and beyond.

Humans are changing the physical properties of Earth. In marine systems, elevated carbon dioxide concentrations are driving notable shifts in temperature and seawater chemistry. Here, we consider consequences of such perturbations for organism biomechanics and linkages amongst species within communities. In particular, we examine case examples of altered morphologies and material properties, disrupted consumer-prey behaviours, and the potential for modulated positive (i.e. facilitative) interactions amongst taxa, as incurred through increasing ocean acidity and rising temperatures. We focus on intertidal rocky shores of temperate seas as model systems, acknowledging the longstanding role of these communities in deciphering ecological principles. Our survey illustrates the broad capacity for biomechanical and behavioural shifts in organisms to influence the ecology of a transforming world.

Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be.

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.