| 1. |
- Asmala, Eero, et al.
(author)
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Role of Eelgrass in the Coastal Filter of Contrasting Baltic Sea Environments
- 2019
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In: Estuaries and Coasts. - : Springer Science and Business Media LLC. - 1559-2723 .- 1559-2731. ; 42:7, s. 1882-1895
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Journal article (peer-reviewed)abstract
- Coastal ecosystems act as filters of nutrients from land to the open sea. We investigated the role of eelgrass (Zostera marina) metabolism in the coastal filter transforming nitrogen, phosphorus, and organic carbon. Field campaigns following identical methodologies were carried out at two contrasting coastal locations: the mesohaline and nutrient-rich Roskilde Fjord, Denmark, and the mesotrophic brackish Tvarminne archipelago, Finland. Over the 24-h in situ benthic incubations, we measured oxygen concentrations continuously and assessed changes in DOM characteristics and net fluxes of carbon, nitrogen, and phosphorus. Ecosystem metabolism modeled on the basis of the O-2 data showed that the systems were either net heterotrophic (Roskilde Fjord; - 1.6 and - 2.4 g O-2 m(-2) day(-1) in eelgrass meadow and bare sand, respectively) or had balanced primary production and respiration (Tvarminne; 0.0 and 0.2 g O-2 m(-2) day(-1)). Overall, initial nutrient stoichiometry was a key factor determining benthic-pelagic fluxes of nutrients, which exacerbated the deviations from Redfield ratios of N and P, indicating an efficient use of the limiting nutrient. A net diel uptake of dissolved inorganic N was observed at both locations (- 2.3 mu mol l(-1) day(-1) in Roskilde Fjord and - 0.1 mu mol l(-1) day(-1) in Tvarminne). Despite minor changes in dissolved organic carbon concentrations during the incubations, a marked increase of fluorescent DOM was observed at both locations, suggesting rapid heterotrophic processing of the DOM pool. Our results underline that the biogeochemical role of eelgrass in the coastal filter is not inherent, but strongly dependent on the environmental conditions.
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| 2. |
- Schweinsberg, Martin, et al.
(author)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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In: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Journal article (peer-reviewed)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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