Improving the Understanding of Detections From iDNA Surveys in Malaysian Borneo With Multiscale Occupancy Models: A Case-Study Using Leech Blood Meals

Invertebrate-derived DNA (iDNA) has been successfully utilized for surveying mammalian biodiversity in several ecosystems. Yet, as with all sampling methods, this approach suffers from potential biases, including those introduced by the choice of invertebrate sampler, as well as the stochasticity of DNA amplification during PCR. Occupancy modeling is a statistical framework that can help account for imperfect detections in sampling and can be used to improve iDNA surveys. Using a case study based on the DNA screened from the blood meals of leeches, we demonstrate how multiscale occupancy models can be applied to the molecular detection of vertebrates to reveal the nuances in iDNA detections. Leeches were collected across a habitat degradation gradient in Sabah, Malaysian Borneo, in 2015 and 2016. We estimated three probabilities describing the occupancy, availability, and detection of three abundant mammals (bearded pig, muntjac and sambar deer) and compared how these values were impacted by environmental and technical covariates. For 2015, we found that null models without covariates revealed no clear differences in each of the three probabilities across taxa. However, in 2016, although the taxa have comparable occupancy, deviations occurred in the other two probabilities, with the sambar deer showing the lowest availability and muntjac with the lowest detection probability. Univariate models constructed for each taxon and year revealed differential impacts of the covariates; for example, a strong positive effect of DNA concentration on the detection of sambar deer and bearded pig was seen in 2016 only. Finally, our estimation of the minimum numbers of biological and technical replicates highlights the important trade-off between achieving high probabilities of availability and detection and realistic amounts of sampling. Our results showcase the use of occupancy models for leech-iDNA biodiversity surveys but highlight the potential effects of sample type, methodological design, and sample size.