Evaluating the effects of laboratory protocols on eDNA detection probability for an endangered freshwater fish

The effectiveness and accuracy of detection using environmental DNA (eDNA) is dependent on understanding the influence laboratory methods such as DNA extraction and PCR strategies have on detection probability. Ideally choice of sampling and extraction method will maximize eDNA yield and detection probability. Determining the survey effort required to reach a satisfactory detection probability (via increased PCR replicates or more sampling) could compensate for a lower eDNA yield if the sampling and extraction method has other advantages for a study, species or system. I analysed the effect of three different sampling and extraction methods on eDNA yield, detection probability and PCR replication for detecting the endangered freshwater fish Macquaria australasica from water samples. The impact of eDNA concentration, PCR strategy, target amplicon size and two marker regions: 12S (a mitochondrial gene) and 18S (a nuclear gene) was also assessed. The choice of sampling and extraction method and PCR strategy, rather than amplicon size and marker region, had the biggest effect on detection probability and PCR replication. The PCR replication effort required to achieve a detection probability of 0.95, ranged from 2 to 6 PCR replicates depending on the laboratory method used. As all methods yielded eDNA from which M. australasica was detected using the three target amplicons, differences in eDNA yield and detection probability between the three methods could be mitigated by determining the appropriate PCR replication effort. Evaluating the effect sampling and extraction methods will have on the detection probability and determining the laboratory protocols and PCR replication required to maximize detection and minimize false positives and negatives is a useful first step for eDNA occupancy studies.     

Site occupancy models with heterogeneous detection probabilities

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.     

A probabilistic model for designing and assessing the performance of eDNA sampling protocols

Environmental DNA (eDNA) sampling, the detection of species‐specific genetic material in water samples, is an emerging tool for monitoring aquatic invasive species. Optimizing eDNA sampling protocols can be challenging because there is imperfect understanding of how each step of the protocol influences its sensitivity. This paper develops a probabilistic model that characterizes each step of an eDNA sampling protocol to evaluate the protocol's overall detection sensitivity for one sample. The model is then applied to analyse how changes over time made to the eDNA sampling protocol to detect bighead (BH) and silver carp (SC) eDNA have influenced its sensitivity, and hence interpretation of the results. The model shows that changes to the protocol have caused the sensitivity of the protocol to fluctuate. A more efficient extraction method in 2013, new species‐specific markers with a qPCR assay in 2014, and a more efficient capture method in 2015 have improved the sensitivity, while switching to a larger elution volume in 2013 and a smaller sample volume in 2015 have reduced the sensitivity. Overall, the sensitivity of the current protocol is higher for BH eDNA detection and SC eDNA detection compared to the original protocol used from 2009 to 2012. The paper shows how this model of eDNA sampling can be used to evaluate the effect of proposed changes in an eDNA sampling and analysis protocol on the sensitivity of that protocol to help researchers optimize their design.     

The importance of incorporating imperfect detection in biodiversity assessments: a case study of small mammals in an Australian region

Aim Assessments of biodiversity are an essential requirement of conservation management planning. Species distributional modelling is a popular approach to quantifying biodiversity whereby occurrence data are related to environmental covariates. An important confounding factor that is often overlooked in the development of such models is uncertainty due to imperfect detection. Here, I demonstrate how an analytical approach that accounts for the bias due to imperfect detection can be applied retrospectively to an existing biodiversity survey data set to produce more realistic estimates of species distributions and unbiased covariate relationships. Location Pilbara biogeographic region, Australia. Methods As a component of the Pilbara survey, presence/absence (i.e. undetected) data on small ground‐dwelling mammals were collected. I applied a multiseason occupancy modelling approach to six of the most common species encountered during this survey. Detection and occupancy rates, as well as extinction and colonization probabilities, were determined, and the influence of covariates on these parameters was examined using the multi‐model inference approach. Results Detection probabilities for all six species were considerably lower than 1.0 and varied across time and species. Naïve estimates of occupancy underestimated occupancy rates corrected for species detectability by up to 45%. Seasonal variation in occupancy status was attributed to changes in detection for two of the focal species, while reproductive events explained variation in occupancy in three others. Covariates describing the substrate strongly influenced site occupancy for most of the species modelled. A comparison of the occupancy model with a generalized linear model, assuming perfect detection, showed that the effects of the covariates were underestimated in the latter model. Main conclusions The application of the multiseason occupancy modelling approach to the Pilbara mammal data set demonstrated a powerful framework for examining changes in site occupancy, as well as local colonization and extinction rates of species which are not confounded by variable species detection rates.     

Climate and the range dynamics of species with imperfect detection

Reliable predictions for species range changes require a mechanistic understanding of range dynamics in relation to environmental variation. One obstacle is that most current models are static and confound occurrence with the probability of detecting a species if it occurs at a site. Here we draw attention to recently developed occupancy models, which can be used to examine colonization and local extinction or changes in occupancy over time. These models further account for detection probabilities, which are likely to vary spatially and temporally in many datasets. Occupancy models require repeated presence/absence surveys, for example checklists used in bird atlas projects. As an example, we examine the recent range expansion of hadeda ibises (Bostrychia hagedash) in South African protected areas. Colonization exceeded local extinction in most biomes, and the probability of occurrence was related to local climate. Extensions of the basic occupancy models can estimate abundance or species richness. Occupancy models are an appealing additional tool for studying species' responses to global change.     

Taking eDNA underground: Factors affecting eDNA detection of subterranean fauna in groundwater

Stygofauna are aquatic fauna that have evolved to live underground. The impacts of anthropogenic climate change, extraction and pollution on groundwater pose major threats to groundwater health, prompting the need for efficient and reliable means to detect and monitor stygofaunal communities. Conventional survey techniques for these species rely on morphological identification and can be biased, labour-intensive and often indeterminate to lower taxonomic levels. By contrast, environmental DNA (eDNA)-based methods have the potential to dramatically improve on existing stygofaunal survey methods in a large range of habitats and for all life stages, reducing the need for the destructive manual collection of often critically endangered species or for specialized taxonomic expertise. We compared eDNA and haul-net samples collected in 2020 and 2021 from 19 groundwater bores and a cave on Barrow Island, northwest Western Australia, and assessed how sampling factors influenced the quality of eDNA detection of stygofauna. The two detection methods were complementary; eDNA metabarcoding was able to detect soft-bodied taxa and fish often missed by nets, but only detected seven of the nine stygofaunal crustacean orders identified from haul-net specimens. Our results also indicated that eDNA metabarcoding could detect 54%–100% of stygofauna from shallow-water samples and 82%–90% from sediment samples. However, there was significant variation in stygofaunal diversity between sample years and sampling types. The findings of this study demonstrate that haul-net sampling has a tendency to underestimate stygofaunal diversity and that eDNA metabarcoding of groundwater can substantially improve the efficiency of stygofaunal surveys.     

A framework for estimating the sensitivity of eDNA surveys

Imperfect sensitivity, or imperfect detection, is a feature of all survey methods that needs to be accounted for when interpreting survey results. Detection of environmental DNA (eDNA) is increasingly being used to infer species distributions, yet the sensitivity of the technique has not been fully evaluated. Sensitivity, or the probability of detecting target DNA given it is present at a site, will depend on both the survey method and the concentration and dispersion of target DNA molecules at a site. We present a model to estimate target DNA concentration and dispersion at survey sites and to estimate the sensitivity of an eDNA survey method. We fitted this model to data from a species‐specific eDNA survey for Oriental weatherloach, Misgurnus anguillicaudatus, at three sites sampled in both autumn and spring. The concentration of target DNA molecules was similar at all three sites in autumn but much higher at two sites in spring. Our analysis showed the survey method had ≥95% sensitivity at sites where target DNA concentrations were ≥11 molecules per litre. We show how these data can be used to compare sampling schemes that differ in the number of field samples collected per site and number of PCR replicates per sample to achieve ≥95% sensitivity at a given target DNA concentration. These models allow researchers to quantify the sensitivity of eDNA survey methods to optimize the probability of detecting target species, and to compare DNA concentrations spatially and temporarily.     

Optimizing occupancy surveys by maximizing detection probability: application to amphibian monitoring in the Mediterranean region

• Setting up effective conservation strategies requires the precise determination of the targeted species’ distribution area and, if possible, its local abundance. However, detection issues make these objectives complex for most vertebrates. The detection probability is usually <1 and is highly dependent on species phenology and other environmental variables. The aim of this study was to define an optimized survey protocol for the Mediterranean amphibian community, that is, to determine the most favorable periods and the most effective sampling techniques for detecting all species present on a site in a minimum number of field sessions and a minimum amount of prospecting effort. We visited 49 ponds located in the Languedoc region of southern France on four occasions between February and June 2011. Amphibians were detected using three methods: nighttime call count, nighttime visual encounter, and daytime netting. The detection nondetection data obtained was then modeled using site‐occupancy models. The detection probability of amphibians sharply differed between species, the survey method used and the date of the survey. These three covariates also interacted. Thus, a minimum of three visits spread over the breeding season, using a combination of all three survey methods, is needed to reach a 95% detection level for all species in the Mediterranean region. Synthesis and applications: detection nondetection surveys combined to site occupancy modeling approach are powerful methods that can be used to estimate the detection probability and to determine the prospecting effort necessary to assert that a species is absent from a site.

     

Taking the bait: The influence of attractants and microhabitat on detections of fauna by remote‐sensing cameras

Autonomously triggered cameras are a common wildlife survey technique. The use of attractants and surrounding microhabitats is likely to influence detection probabilities and survey outcomes; however, few studies consider these factors. We compared three attractants (peanut butter‐based, tuna‐based and a control) in a Latin square design through a coastal shrubland with high microhabitat variability at Cape Otway, Victoria, Australia (38º50?S, 143º30?E). Deployments involved 36 cameras for four days in each of five years. The percentage cover of each vegetation structural type (low [no or sparse cover], moderate [grass] or high [shrubs]) within 20 m of each camera was calculated and reduced to a single variable using PCA. Dynamic occupancy modelling, with lure type and vegetation structure as covariates of detection probability, found that peanut butter attracted the greatest diversity of species (24 of 35 species, 69%) and yielded the greatest number of detections (50% of 319) when compared with tuna oil (66% and 24%, respectively) and the control (43% and 26%, respectively). Peanut butter attracted more Macropodidae (wallabies) and Muridae (rats and mice); however, vegetation structural variables were the greatest influence on Corvidae/Artamidae (raven/currawong) detections with higher detectability in more open areas. Vegetation structure also influenced Muridae detections. This study reinforces the critical choice of appropriate attractants and camera placement when investigating vertebrate groups and highlights the role of microhabitat in the detection of small mammals and birds. We suggest future large‐scale camera surveys consider different bait types and microhabitats in their designs, to control for any biases and enable future advice on ‘optimal’ methods.     

Net overboard: Comparing marine eDNA sampling methodologies at sea to unravel marine biodiversity

Environmental DNA (eDNA) analyses are powerful for describing marine biodiversity but must be optimized for their effective use in routine monitoring. To maximize eDNA detection probabilities of sparsely distributed populations, water samples are usually concentrated from larger volumes and filtered using fine-pore membranes, often a significant cost–time bottleneck in the workflow. This study aimed to streamline eDNA sampling by investigating plankton net versus bucket sampling, direct versus sequential filtration including self-preserving filters. Biodiversity was assessed using metabarcoding of the small ribosomal subunit (18S rRNA) and mitochondrial cytochrome c oxidase I (COI) genes. Multispecies detection probabilities were estimated for each workflow using a probabilistic occupancy modelling approach. Significant workflow-related differences in biodiversity metrics were reported. Highest amplicon sequence variant (ASV) richness was attained by the bucket sampling combined with self-preserving filters, comprising a large portion of microplankton. Less diversity but more metazoan taxa were captured in the net samples combined with 5 μm pore size filters. Prefiltered 1.2 μm samples yielded few or no unique ASVs. The highest average (~32%) metazoan detection probabilities in the 5 μm pore size net samples confirmed the effectiveness of preconcentration plankton for biodiversity screening. These results contribute to streamlining eDNA sampling protocols for uptake and implementation in marine biodiversity research and surveillance.     

Modelling occupancy of an imperilled stream fish at multiple scales while accounting for imperfect detection: implications for conservation

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Effect of detection heterogeneity in occupancy‐detection models: an experimental test of time‐to‐first‐detection methods

Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time‐to‐first‐detection (TTD) occupancy models have been proposed as a cost–effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy‐detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala Phascolarctos cinereus populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness‐of‐fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy‐detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness‐of‐fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy‐detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.     

Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species

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Optimal sampling design and the accuracy of occupancy models

We present general theoretical limits on the possible accuracy (mean squared error or MSE) of occupancy estimates for a large range of occupancy study designs with imperfect detection and confirm our theoretical results via a simulation study. In particular, we show that for a given total survey effort, the best possible MSE is driven by two design-related factors: the fraction of visits made at occupied sites (regardless of whether that occupancy status is known or not) and the number of visits made to each site with unknown occupancy status (ie, sites with no detections). The limits reveal that there is very little room for improvement over optimal implementations of the three existing occupancy design paradigms: standard design (visit S sites K times each), removal design (visit S sites up to K times each, halting visits to each site following a positive detection), and conditional design (visit S sites once, then resurvey sites with a positive detection an additional $K-1$ times). For the small portion of the occupancy-detection parameter space where improvement can be achieved, we introduce a new hybrid survey design with accuracy closer to the theoretical limit, which we illustrate by reanalyzing an existing coyote (Canis latrans) camera trap dataset. Our results provide new clarity and intuition regarding key factors of occupancy study design.     

The distribution of coastal fish eDNA sequences in the Anthropocene

Aim

Coastal fishes have a fundamental role in marine ecosystem functioning and contributions to people, but face increasing threats due to climate change, habitat degradation and overexploitation. The extent to which human pressures are impacting coastal fish biodiversity in comparison with geographic and environmental factors at large spatial scale is still under scrutiny. Here, we took advantage of environmental DNA (eDNA) metabarcoding to investigate the relationship between fish biodiversity, including taxonomic and genetic components, and environmental but also socio-economic factors.

Location

Tropical, temperate and polar coastal areas.

Time period

Present day.

Major taxa studied

Marine fishes.

Methods

We analysed fish eDNA in 263 stations (samples) in 68 sites distributed across polar, temperate and tropical regions. We modelled the effect of environmental, geographic and socio-economic factors on α- and β-diversity. We then computed the partial effect of each factor on several fish biodiversity components using taxonomic molecular units (MOTU) and genetic sequences. We also investigated the relationship between fish genetic α- and β-diversity measured from our barcodes, and phylogenetic but also functional diversity.

Results

We show that fish eDNA MOTU and sequence α- and β-diversity have the strongest correlation with environmental factors on coastal ecosystems worldwide. However, our models also reveal a negative correlation between biodiversity and human dependence on marine ecosystems. In areas with high dependence, diversity of all fish, cryptobenthic fish and large fish MOTUs declined steeply. Finally, we show that a sequence diversity index, accounting for genetic distance between pairs of MOTUs, within and between communities, is a reliable proxy of phylogenetic and functional diversity.

Main conclusions

Together, our results demonstrate that short eDNA sequences can be used to assess climate and direct human impacts on marine biodiversity at large scale in the Anthropocene and can further be extended to investigate biodiversity in its phylogenetic and functional dimensions.     

Residual eDNA detection sensitivity assessed by quantitative real‐time PCR in a river ecosystem

Several studies have demonstrated that environmental DNA (eDNA) can be used to detect the presence of aquatic species, days to weeks after the target species has been removed. However, most studies used eDNA analysis in lentic systems (ponds or lakes), or in controlled laboratory experiments. While eDNA degrades rapidly in all aquatic systems, it also undergoes dilution effects and physical destruction in flowing systems, complicating detection in rivers. However, some eDNA (i.e. residual eDNA) can be retained in aquatic systems, even those subject to high flow regimes. Our goal was to determine residual eDNA detection sensitivity using quantitative real‐time polymerase chain reaction (qRT–PCR), in a flowing, uncontrolled river after the eDNA source was removed from the system; we repeated the experiment over 2 years. Residual eDNA had the strongest signal strength at the original source site and was detectable there up to 11.5 h after eDNA source removal. Residual eDNA signal strength decreased as sampling distance downstream from the eDNA source site increased, and was no longer detectable at the source site 48 h after the eDNA source water was exhausted in both experiments. This experiment shows that residual eDNA sampled in surface water can be mapped quantitatively using qRT–PCR, which allows a more accurate spatial identification of the target species location in lotic systems, and relative residual eDNA signal strength may allow the determination of the timing of the presence of target species.     

The hidden side of diversity: Effects of imperfect detection on multiple dimensions of biodiversity

1. Studies on ecological communities often address patterns of species distribution and abundance, but few consider uncertainty in counts of both species and individuals when computing diversity measures.
2. We evaluated the extent to which imperfect detection may influence patterns of taxonomic, functional, and phylogenetic diversity in ecological communities.
3. We estimated the true abundance of fruit‐feeding butterflies sampled in canopy and understory strata in a subtropical forest. We compared the diversity values calculated by observed and estimated abundance data through the hidden diversity framework. This framework evaluates the deviation of observed diversity when compared with diversities derived from estimated true abundances and whether such deviation represents a bias or a noise in the observed diversity pattern.
4. The hidden diversity values differed between strata for all diversity measures, except for functional richness. The taxonomic measure was the only one where we observed an inversion of the most diverse stratum when imperfect detection was included. Regarding phylogenetic and functional measures, the strata showed distinct responses to imperfect detection, despite the tendency to overestimate observed diversity. While the understory showed noise for the phylogenetic measure, since the observed pattern was maintained, the canopy had biased diversity for the functional metric. This bias occurred since no significant differences were found between strata for observed diversity, but rather for estimated diversity, with the canopy being more clustered.
5. We demonstrate that ignore imperfect detection may lead to unrealistic estimates of diversity and hence to erroneous interpretations of patterns and processes that structure biological communities. For fruit‐feeding butterflies, according to their phylogenetic position or functional traits, the undetected individuals triggered different responses in the relationship of the diversity measures to the environmental factor. This highlights the importance to evaluate and include the uncertainty in species detectability before calculating biodiversity measures to describe communities.

     

Testing the importance of auditory detections in avian point counts

ABSTRACT.   Recent advances in the methods used to estimate detection probability during point counts suggest that the detection process is shaped by the types of cues available to observers. For example, models of the detection process based on distance-sampling or time-of-detection methods may yield different results for auditory versus visual cues because of differences in the factors that affect the transmission of these cues from a bird to an observer or differences in an observer's ability to localize cues. Previous studies suggest that auditory detections predominate in forested habitats, but it is not clear how often observers hear birds prior to detecting them visually. We hypothesized that auditory cues might be even more important than previously reported, so we conducted an experiment in a forested habitat in North Carolina that allowed us to better separate auditory and visual detections. Three teams of three observers each performed simultaneous 3-min unlimited-radius point counts at 30 points in a mixed-hardwood forest. One team member could see, but not hear birds, one could hear, but not see, and the third was nonhandicapped. Of the total number of birds detected, 2.9% were detected by deafened observers, 75.1% by blinded observers, and 78.2% by nonhandicapped observers. Detections by blinded and nonhandicapped observers were the same only 54% of the time. Our results suggest that the detection of birds in forest habitats is almost entirely by auditory cues. Because many factors affect the probability that observers will detect auditory cues, the accuracy and precision of avian point count estimates are likely lower than assumed by most field ornithologists.