Improved absolute abundance estimates from spatial count data with simulation and microfossil case studies
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866915829177647104 |
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| author | Mays, Chris Amores, Marcos Mays, Anthony |
| author_facet | Mays, Chris Amores, Marcos Mays, Anthony |
| contents | Many fundamental parameters of biological systems -- eg. productivity, population sizes and biomass -- are most effectively expressed in absolute terms. In contrast to proportional data (eg. percentages), absolute values provide standardised metrics on the functioning of biological entities (eg. organisism, species, ecosystems). These are particularly valuable when comparing assemblages across time and space. Since it is almost always impractical to count entire populations, estimates of population abundances require a sampling method that is both accurate and precise. Such absolute abundance estimates typically entail more "sampling effort" (data collection time) than proportional data. Here we refined a method of absolute abundance estimates -- the "exotic marker technique" -- by producing a variant that is more efficient without losing accuracy. This new method, the "field-of-view subsampling method" (FOVS method) is based on area subsampling, from which large samples can be quickly extrapolated.
Two case studies of the exotic marker technique were employed: 1, computer simulations; and 2, an observational "real world" data set of terrestrial organic microfossils from the Permian- and Triassic-aged rock strata of southeastern Australia, spiked with marker grains of known quantity and variance. We compared the FOVS method against the traditional "linear method" method using three metrics: 1, concentration (specimens/gram of sediment); 2, precision and 3, data collection effort. In almost all cases, the FOVS method delivers higher precision than the linear method, with equivalent effort, and our computer simulations suggest that the FOVS method more accurately estimates the true error for large target-to-marker ratios. Since we predict that these conditions are typically common, we recommend the new FOVS method in almost every "real world" case. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_10921 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Improved absolute abundance estimates from spatial count data with simulation and microfossil case studies Mays, Chris Amores, Marcos Mays, Anthony Quantitative Methods 92-08 Many fundamental parameters of biological systems -- eg. productivity, population sizes and biomass -- are most effectively expressed in absolute terms. In contrast to proportional data (eg. percentages), absolute values provide standardised metrics on the functioning of biological entities (eg. organisism, species, ecosystems). These are particularly valuable when comparing assemblages across time and space. Since it is almost always impractical to count entire populations, estimates of population abundances require a sampling method that is both accurate and precise. Such absolute abundance estimates typically entail more "sampling effort" (data collection time) than proportional data. Here we refined a method of absolute abundance estimates -- the "exotic marker technique" -- by producing a variant that is more efficient without losing accuracy. This new method, the "field-of-view subsampling method" (FOVS method) is based on area subsampling, from which large samples can be quickly extrapolated. Two case studies of the exotic marker technique were employed: 1, computer simulations; and 2, an observational "real world" data set of terrestrial organic microfossils from the Permian- and Triassic-aged rock strata of southeastern Australia, spiked with marker grains of known quantity and variance. We compared the FOVS method against the traditional "linear method" method using three metrics: 1, concentration (specimens/gram of sediment); 2, precision and 3, data collection effort. In almost all cases, the FOVS method delivers higher precision than the linear method, with equivalent effort, and our computer simulations suggest that the FOVS method more accurately estimates the true error for large target-to-marker ratios. Since we predict that these conditions are typically common, we recommend the new FOVS method in almost every "real world" case. |
| title | Improved absolute abundance estimates from spatial count data with simulation and microfossil case studies |
| topic | Quantitative Methods 92-08 |
| url | https://arxiv.org/abs/2406.10921 |