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- 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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- Ferraguti, Martina, et al.
(author)
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Ecological determinants of avian malaria infections : An integrative analysis at landscape, mosquito and vertebrate community levels
- 2018
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In: Journal of Animal Ecology. - : Wiley. - 0021-8790. ; 87:3, s. 727-740
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Journal article (peer-reviewed)abstract
- Vector and host communities, as well as habitat characteristics, may have important but different impacts on the prevalence, richness and evenness of vector-borne parasites. We investigated the relative importance of (1) the mosquito community composition, (2) the vertebrate community composition and (3) landscape characteristics on the prevalence, richness and evenness of avian Plasmodium. We hypothesized that parasite prevalence will be more affected by vector-related parameters, while host parameters should be also important to explain Plasmodium richness and evenness. We sampled 2,588 wild house sparrows (Passer domesticus) and 340,829 mosquitoes, and we performed vertebrate censuses at 45 localities in the Southwest of Spain. These localities included urban, rural and natural landscapes that were characterized by several habitat variables. Twelve Plasmodium lineages were identified in house sparrows corresponding to three major clades. Variation partitioning showed that landscape characteristics explained the highest fraction of variation in all response variables (21.0%-44.8%). Plasmodium prevalence was in addition explained by vector-related variables (5.4%) and its interaction with landscape (10.2%). Parasite richness and evenness were mostly explained by vertebrate community-related variables. The structuring role of landscape characteristics in vector and host communities was a key factor in determining parasite prevalence, richness and evenness, although the role of each factor differed according to the parasite parameters studied. These results show that the biotic and abiotic contexts are important to explain the transmission dynamics of mosquito-borne pathogens in the wild.
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- Guzman, Laura Melissa, et al.
(author)
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Accounting for temporal change in multiple biodiversity patterns improves the inference of metacommunity processes
- 2022
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In: Ecology. - : John Wiley & Sons. - 0012-9658 .- 1939-9170. ; 103:6
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Journal article (peer-reviewed)abstract
- In metacommunity ecology, a major focus has been on combining observational and analytical approaches to identify the role of critical assembly processes, such as dispersal limitation and environmental filtering, but this work has largely ignored temporal community dynamics. Here, we develop a "virtual ecologist" approach to evaluate assembly processes by simulating metacommunities varying in three main processes: density-independent responses to abiotic conditions, density-dependent biotic interactions, and dispersal. We then calculate a number of commonly used summary statistics of community structure in space and time and use random forests to evaluate their utility for inferring the strength of these three processes. We find that (i) both spatial and temporal data are necessary to disentangle metacommunity processes based on the summary statistics we test, and including statistics that are measured through time increases the explanatory power of random forests by up to 59% compared to cases where only spatial variation is considered; (ii) the three studied processes can be distinguished with different descriptors; and (iii) each summary statistic is differently sensitive to temporal and spatial sampling effort. Including repeated observations of metacommunities over time was essential for inferring the metacommunity processes, particularly dispersal. Some of the most useful statistics include the coefficient of variation of species abundances through time and metrics that incorporate variation in the relative abundances (evenness) of species. We conclude that a combination of methods and summary statistics is probably necessary to understand the processes that underlie metacommunity assembly through space and time, but we recognize that these results will be modified when other processes or summary statistics are used.
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