How to quantify factors degrading DNA in the environment and predict degradation for effective sampling design

Extra-organismal DNA (eoDNA) from material left behind by organisms
(non-invasive DNA: e.g., faeces, hair) or from environmental samples
(eDNA: e.g., water, soil) is a valuable source of genetic information.
However, the relatively low quality and quantity of eoDNA, which can be
further degraded by environmental factors, results in reduced
amplification and sequencing success. This is often compensated for
through cost- and time-intensive replications of genotyping/sequencing
procedures. Therefore, system- and site-specific quantifications of
environmental degradation are needed to maximize sampling efficiency
(e.g., fewer replicates, shorter sampling durations), and to improve
species detection and abundance estimates. Using ten environmentally
diverse bat roosts as a case study, we developed a robust modelling
pipeline to quantify the environmental factors degrading eoDNA, predict
eoDNA quality, and estimate sampling-site-specific ideal exposure
duration. Maximum humidity was the strongest eoDNA-degrading factor,
followed by exposure duration and then maximum temperature. We also found
a positive effect when hottest days occurred later. The strength of this
effect fell between the strength of the effects of exposure duration and
maximum temperature. With those predictors and information on sampling
period (before or after offspring were born), we reliably predicted mean
eoDNA quality per sampling visit at new sites with a mean squared error of
0.0349. Site-specific simulations revealed that reducing exposure duration
to 2-8 days could substantially improve eoDNA quality for future sampling.
Our pipeline identified high humidity and temperature as strong drivers of
eoDNA degradation even in the absence of rain and direct sunlight.
Furthermore, we outline the pipeline’s utility for other systems and study
goals, such as estimating sample age, improving eDNA-based species
detection, and increasing the accuracy of abundance estimates.