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How calorie-rich food could help marine calcifiers in a CO2-rich future.

ABSTRACT: Increasing carbon emissions not only enrich oceans with CO2 but also make them more acidic. This acidifying process has caused considerable concern because laboratory studies show that ocean acidification impairs calcification (or shell building) and survival of calcifiers by the end of this century. Whether this impairment in shell building also occurs in natural communities remains largely unexplored, but requires re-examination because of the recent counterintuitive finding that populations of calcifiers can be boosted by CO2 enrichment. Using natural CO2 vents, we found that ocean acidification resulted in the production of thicker, more crystalline and more mechanically resilient shells of a herbivorous gastropod, which was associated with the consumption of energy-enriched food (i.e. algae). This discovery suggests that boosted energy transfer may not only compensate for the energetic burden of ocean acidification but also enable calcifiers to build energetically costly shells that are robust to acidified conditions. We unlock a possible mechanism underlying the persistence of calcifiers in acidifying oceans.

SUBMITTER: Leung JYS

PROVIDER: S-EPMC6650713 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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How calorie-rich food could help marine calcifiers in a CO<sub>2</sub>-rich future.

Leung Jonathan Y S JYS Doubleday Zoë A ZA Nagelkerken Ivan I Chen Yujie Y Xie Zonghan Z Connell Sean D SD

Proceedings. Biological sciences 20190710 1906

Increasing carbon emissions not only enrich oceans with CO<sub>2</sub> but also make them more acidic. This acidifying process has caused considerable concern because laboratory studies show that ocean acidification impairs calcification (or shell building) and survival of calcifiers by the end of this century. Whether this impairment in shell building also occurs in natural communities remains largely unexplored, but requires re-examination because of the recent counterintuitive finding that po ...[more]

PMID: 31288703

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Project description:BACKGROUND:Software designed to accurately estimate food calories from still images could help users and health professionals identify dietary patterns and food choices associated with health and health risks more effectively. However, calorie estimation from images is difficult, and no publicly available software can do so accurately while minimizing the burden associated with data collection and analysis. OBJECTIVE:The aim of this study was to determine the accuracy of crowdsourced annotations of calorie content in food images and to identify and quantify sources of bias and noise as a function of respondent characteristics and food qualities (eg, energy density). METHODS:We invited adult social media users to provide calorie estimates for 20 food images (for which ground truth calorie data were known) using a custom-built webpage that administers an online quiz. The images were selected to provide a range of food types and energy density. Participants optionally provided age range, gender, and their height and weight. In addition, 5 nutrition experts provided annotations for the same data to form a basis of comparison. We examined estimated accuracy on the basis of expertise, demographic data, and food qualities using linear mixed-effects models with participant and image index as random variables. We also analyzed the advantage of aggregating nonexpert estimates. RESULTS:A total of 2028 respondents agreed to participate in the study (males: 770/2028, 37.97%, mean body mass index: 27.5 kg/m2). Average accuracy was 5 out of 20 correct guesses, where "correct" was defined as a number within 20% of the ground truth. Even a small crowd of 10 individuals achieved an accuracy of 7, exceeding the average individual and expert annotator's accuracy of 5. Women were more accurate than men (P<.001), and younger people were more accurate than older people (P<.001). The calorie content of energy-dense foods was overestimated (P=.02). Participants performed worse when images contained reference objects, such as credit cards, for scale (P=.01). CONCLUSIONS:Our findings provide new information about how calories are estimated from food images, which can inform the design of related software and analyses.

Dataset Information

How calorie-rich food could help marine calcifiers in a CO2-rich future.

Publications

How calorie-rich food could help marine calcifiers in a CO<sub>2</sub>-rich future.

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