DnaDot - fixing ecology and evolution’s blind spot, population size

Abstract

To understand and manage any ecosystem, one of the most critical indicators is census population size (‘Nc’) for each component species. This is why the International Union for Conservation of Nature (IUCN) stipulates that it is ideal to know census size to an accuracy of ±10 % for each managed, endangered or exploited population. Knowledge of population size is also critical for: ecological studies in general; allowing biodiversity measures with low error margins; and assessing potential for evolutionary adaptation in long-term management. Unfortunately, despite their importance, all existing methods for estimating Nc have many difficulties, especially requiring independent knowledge or assumptions about demography, including: immigration, emigration, family size and its variance. As a result, even in the IUCN red list, many species are listed despite having unknown population size or trends. Therefore, we need an improved approach. This article introduces ‘DnaDot’, a strong new addition to our armory of census population size estimates, because it is an accurate estimate, with few assumptions. DnaDot is based on mark-release-recapture, but instead of marking, uses pre-existing polymorphisms to divide the population into separate groups. The method uses one sample, minimizing effort, uses no demographic assumptions or data, and does not require genotyping to be accurate enough to identify individuals and kin, which is problematic for other genetic methods especially when degraded field samples are used. DnaDot applies to any kind of variants, from tissue samples, or from noninvasive samples such as hair provided that the researcher can identify species-identity and variants within the species. DnaDot outperformed close competitors on minimal assumptions, and good detectability of marks. Also, in simulations of a wide range of scenarios, DnaDot had superior accuracy and precision, usually meeting the IUCN criterion of ±10 %, which competing methods rarely achieved. Finally, one other method is said to need smaller sample sizes than DnaDot, but only if that method is not required to meet the performance criteria of DnaDot.