Abstract
Environmental DNA (eDNA) is an increasingly used non-invasive molecular tool for detecting species presence and monitoring populations. In this article, we review the current state of non-avian reptile eDNA work in aquatic systems, and present a field experiment on detecting the presence of painted turtle (Chrysemys picta) eDNA. Thus far, turtle and snake eDNA studies have shown mixed results in detecting the presence of these animals under field conditions. However, some instances of low detection rates and non-detection occur for these non-avian reptiles, especially for squamates. We explored non-avian reptile eDNA quantification by sampling four lentic ponds with different densities (0 kg/ha, 6 kg/ha, 9 kg/ha, and 13 kg/ha) of painted turtles over three months to detect differences in eDNA using a qPCR assay amplifying the COI gene of the mtDNA genome. Only one sample of the highest-density pond amplified eDNA for a positive detection. Yet, estimates of eDNA concentration from pond eDNA were rank-order correlated with turtle density. We present the “shedding hypothesis”—the possibility that animals with hard, keratinized integument do not shed as much DNA as mucus-covered organisms—as a potential challenge for eDNA studies. Despite challenges with eDNA inhibition and availability in water samples, we remain hopeful that eDNA can be used to detect freshwater turtles in the field. We provide key recommendations for biologists wishing to use eDNA methods for detecting non-avian reptiles.
Highlights
Monitoring changes in a target species, such as presence/absence in a given locality and abundance, is necessary to model future population trends [1]
This study found the warm season (May–September) yielded higher Environmental DNA (eDNA) detection rates for S. depressus, which likely corresponds to turtle activity [77]
Beyond solving eDNA technical difficulties, there is no stand-in for knowing the biology of the target organism
Summary
Monitoring changes in a target species, such as presence/absence in a given locality and abundance, is necessary to model future population trends [1]. Changes in population density and abundance have downstream demographic effects on range, metapopulation structure, and niche availability [2,3]. Stochastic environmental factors, anthropogenic pressures, or biotic interactions (e.g., disease, intrinsic growth and age class, fecundity, or predation) can change population density [4,5,6,7,8]. Changes in population density can inform researchers about fluctuations in environmental or biotic conditions. Increased resources allow for an increase of population size [11]. Monitoring current species presence and abundance may aid in predicting future densities if current population trajectories can be established
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