Model Assisted Survey Sampling Pdf 14l
Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.
Model Assisted Survey Sampling Pdf 14l
Next we sampled four regions without radiotelemetered snakes where constrictors have been sighted or captured in the past. Although experienced surveyors conducted the sample collection, no constrictor snakes were visually identified during the survey. We collected water samples at three locations in ENP with high Burmese python occupancy documented by multiple captures and previous radiotelemetric research. Within the region known to be occupied by Northern African pythons (Bird Drive Basin (BDB); Fig 1) on the western fringe of the city of Miami, water was collected near the locations of the three most recent captures of Northern African pythons. The Northern African python is considered to be established in this area, since over 25 snakes have been captured along with a small number of Burmese pythons (see Reed et al. [20]). Water samples from three locations were also collected in a forested hammock habitat at the Deering Estate (DE) in southern Miami, which is inhabited by a population of boa constrictors [19]. Live Burmese pythons have been captured less than five km from DE, but have not previously been documented there. Samples were collected from the nearest waterbody 500 m from a radiotelemetered boa constrictor that was in a dry upland burrow on our sampling date. Finally, Holey Land Wildlife Management Area (HLWM) bordered by Rotenberger and Everglades Wildlife Management Area, represents a northern extreme of the remaining Everglades sawgrass marsh and is managed by the State of Florida. Holey Land Wildlife Management Area was sampled at one location opportunistically one day after an eyewitness report of a large snake, putatively identified as an anaconda or Burmese python. Stormwater Treatment Area 5 (STA) was also opportunistically sampled at two locations one day after a Burmese python was sighted by an STA worker. These state lands contain canals and flooded wetlands suitable as habitat for giant constrictor snakes, although constrictors have not been sighted there previously.
The focus of our analysis was to estimate the parameters of this model for each of the regions surveyed in southern Florida. The parameters of interest included ψ (probability of occurrence of python eDNA among all surveyed locations), θi (conditional probability of occurrence of python eDNA in each sample of location i, given that python eDNA was present at that location), and p (conditional probability of detection of python eDNA in each qPCR replicate of an eDNA sample, given that python eDNA was present in the sample).
We were able to fit the multi-scale occupancy model to seven of the eight regions that were surveyed for python eDNA. The model could not be fitted to HLWM because eDNA samples were collected from only one location in that region. Estimates of detection probabilities of python eDNA suggested that qPCR was effective in detecting eDNA presence in a sample (Table 3, S2 Table). For example, estimated detection probabilities ranged from 0.59 to 0.87. In addition, estimates of the cumulative probability of detecting python eDNA (p*) ranged from 0.91 to 1.00, suggesting that three qPCR replicates per eDNA sample were sufficient to detect python eDNA when it was present in a sample.
The multi-scale (three-level) occupancy model described by Schmidt et al. [10] can be used to standardize the terminology used in eDNA-based surveys and to eliminate confusion between occurrence and detection. This model is consistent with the generic eDNA sampling design that we advocate wherein (1) multiple locations are selected to be representative of some region of interest, (2) multiple eDNA samples are collected at each location, and (3) each eDNA sample is subsampled to obtain quantitative PCR (qPCR) replicate observations of eDNA (that is, detections and/or nondetections). Using this design, detections of eDNA occur at the level of individual qPCR replicates. If eDNA is present in a sample, a conditional probability of detecting eDNA in each qPCR replicate is well defined and estimable using occupancy models. Similarly, if eDNA is present at a survey location, the conditional probability of eDNA occurring in a sample is well defined and estimable using occupancy models. Environmental DNA can be absent or present in samples collected from a location where the target species is present [14]. For example, in the analysis of Schmidt et al. [10], eDNA was present in only 45% of the samples collected from sites where eDNA of the target species was known to occur.