ArticlePloS one2025
Field-of-view subsampling: A novel 'exotic marker' method for absolute abundances, validated by simulation and microfossil case studies.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Key parameters of biological systems-e.g., productivity, population sizes, biomass-are best expressed as absolute values. Exotic markers (e.g., Lycopodium spores introduced into microfossil populations) have long been used to estimate population sizes from representative samples. However, the traditional approach-the 'linear method' herein-can be extremely time consuming and impractical for routine use. Here, we present a new variant of this technique: the 'field-of-view subsampling method' (FOVS method). This new method requires a few simple, easily obtainable statistical parameters, beyond the standard inputs for the traditional linear method. The FOVS method adds error from sample heterogeneity, but enables the collection of very large sample sizes with low additional effort. We compared the FOVS and linear methods with two case studies: 1, Monte Carlo simulations to validate the methods with idealised datasets; and 2, terrestrial organic microfossils from Permian-Triassic rock strata in southeastern Australia as 'real-world' empirical datasets. Three output parameters were measured: 1, absolute abundance; 2, precision (=error rate); and 3, data collection effort (typically, this translates to data collection time). The linear method showed superior efficiency only for assemblages with very low specimen densities and/or near-equivalent target-to-marker ratios, conditions we predict are rare under real-world conditions. In contrast, the FOVS method provided greater precision and/or reduced effort under almost all conditions, without sacrificing accuracy. Although originally developed for microfossils, the new method may apply to any spatial data collection where markers of known quantity can be introduced to a population. Given its demonstrable increased speed and precision, we recommend the FOVS method as the new standard for such absolute abundance estimates. Guidelines and a user-friendly digital interface for implementing both of these count methods are provided, in addition to simulation codes aimed to assist readers in designing their own experiments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.