Improved absolute abundance estimates from spatial count data with simulation and microfossil case studies Article Swipe
Chris Mays
,
Marcos Amores
,
Anthony Mays
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.10921
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.10921
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.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.10921
- https://arxiv.org/pdf/2406.10921
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399794665
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4399794665Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.10921Digital Object Identifier
- Title
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Improved absolute abundance estimates from spatial count data with simulation and microfossil case studiesWork title
- Type
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preprintOpenAlex work type
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-06-16Full publication date if available
- Authors
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Chris Mays, Marcos Amores, Anthony MaysList of authors in order
- Landing page
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https://arxiv.org/abs/2406.10921Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2406.10921Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2406.10921Direct OA link when available
- Concepts
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Abundance (ecology), Count data, Absolute (philosophy), Statistics, Environmental science, Mathematics, Ecology, Biology, Epistemology, Philosophy, Poisson distributionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.terrestrial | 163 |
| abstract_inverted_index.traditional | 192 |
| abstract_inverted_index.ecosystems). | 42 |
| abstract_inverted_index.microfossils | 165 |
| abstract_inverted_index.particularly | 45 |
| abstract_inverted_index.populations, | 63 |
| abstract_inverted_index.proportional | 24, 91 |
| abstract_inverted_index.simulations; | 153 |
| abstract_inverted_index.southeastern | 174 |
| abstract_inverted_index.standardised | 31 |
| abstract_inverted_index.subsampling, | 132 |
| abstract_inverted_index.Triassic-aged | 170 |
| abstract_inverted_index.concentration | 200 |
| abstract_inverted_index.extrapolated. | 140 |
| abstract_inverted_index.observational | 157 |
| abstract_inverted_index.percentages), | 27 |
| abstract_inverted_index.productivity, | 8 |
| abstract_inverted_index."field-of-view | 123 |
| abstract_inverted_index.(specimens/gram | 201 |
| abstract_inverted_index.target-to-marker | 245 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile |