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| Foster, Scott D.; Vanhatalo, Jarno; Trenkel, Verena; Schulz, Torsti; Lawrence, Emma; Przeslawski, Rachel; Hosack, Geoffrey R.. |
| Data are currently being used, and reused, in ecological research at an unprecedented rate. To ensure appropriate reuse however, we need to ask the question: “Are aggregated databases currently providing the right information to enable effective and unbiased reuse?” We investigate this question, with a focus on designs that purposefully favour the selection of sampling locations (upweighting the probability of selection of some locations). These designs are common and examples are those designs that have uneven inclusion probabilities or are stratified. We perform a simulation experiment by creating datasets with progressively more uneven inclusion probabilities, and examine the resulting estimates of the average number of individuals per unit area... |
| Tipo: Text |
Palavras-chave: Bias; Survey Design; Database; Population Density Estimate; Model; Horvitz‐Thompson; FAIR; Reuse; Data; Inclusion Probability. |
| Ano: 2021 |
URL: https://archimer.ifremer.fr/doc/00691/80339/83422.pdf |
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| Hosack, Geoffrey R.; Trenkel, Verena. |
| The transitory and long-term elasticities of the Bay of Biscay ecosystem to densityindependent and density-dependent influences were estimated within a state space model that accounted for both process and observation uncertainties. A functional group based model for the Bay of Biscay fish ecosystem was fit to time series obtained from scientific survey and commercial catch and effort data. The observation model parameters correspond to the unknown catchabilities and observation error variances that vary across the commercial fisheries and fishery-independent scientific surveys. The process model used a Gompertz form of density dependence, which is commonly used for the analysis of multivariate ecological time series, with unknown time-varying fishing... |
| Tipo: Text |
Palavras-chave: Compensatory dynamics; Cumulative impacts; Elasticity; Fox model; Gompertz model; Predictive cross-validation. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00510/62119/66311.pdf |
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