Presence Absence Surveys Research Articles

Quantifying the conservation status and abundance trends of wildlife communities with detection-nondetection data.

Effective conservation requires understanding species' abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species' dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamic N-occupancy model to estimate unbiased, community-wide relative abundance and demographic rates. In this model, detection-nondetection data (e.g., repeated presence-absence surveys) are used to estimate species- and community-level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single-species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest-dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species' local population. The antelope community was fairly stable (although 17% of populations [species-park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species' life histories. The multispecies dynamic N-occupancy model requires only detection-nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.

Geographic Distribution and Habitat Characterization of the Threatened Delta Green Ground Beetle, Elaphrus viridis Horn, 1878 (Coleoptera: Carabidae), in the Jepson Prairie Region of Solano County, California, USA

Although it was described in 1878, Elaphrus viridis Horn (Carabidae) remained unknown for almost a century until its rediscovery during 1974 in the vernal pool-valley grassland region known as the Jepson Prairie in Solano County, California. Due to extensive loss and alteration of these seasonal wetlands and native grasslands throughout California's Central Valley, this beetle, commonly known as the Delta green ground beetle (DGGB), was recognized as a threatened species by the US Fish & Wildlife Service in 1980. However, despite its threatened species status, the beetle's geographic range, status, and habitat preferences have remained poorly known, factors that have hindered habitat management actions to benefit it. Presence-absence surveys were conducted throughout the entire approximately 200-km2 Jepson Prairie region to document the DGGB's geographic range and identify its habitat associations and microhabitat preferences. Habitat relationships were investigated using a suite of biotic and abiotic features and discriminant function analyses to explain the beetle's geographic distribution throughout the region, its habitat associations, and preferred habitat structure. Initially, 36 habitat variables were measured at 240 randomly selected locations, with 60 locations in each of four actual or potential DGGB habitat types to characterize these habitats. These same habitat variables were also measured at 60 DGGB-occupied locations and used to determine the beetle's microhabitat preferences. Results of these field surveys and habitat analyses indicate that life stages of the DGGB prefer the sparsely vegetated habitats with short-statured vegetation where sunlight penetrates to ground level, along the gently-sloped shorelines of vernal playas underlain by Pescadero clay soils.

Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Abstract Floral resources are a key driver of pollinator abundance and diversity, yet their quantification in the field and laboratory is laborious and requires specialist skills. Using a dataset of 25,000 labelled tags of fieldwork‐realistic quality, a convolutional neural network (Faster R‐CNN) was trained to detect the nectar‐producing floral units of 25 taxa in surveyors’ quadrat images of native, weed‐rich grassland in the United Kingdom. Floral unit detection on a test set of 50 model‐unseen images of comparable vegetation returned a precision of 90%, recall of 86% and F1 score (the harmonic mean of precision and recall) of 88%. Model performance was consistent across the range of floral abundance in this habitat. Comparison of the nectar sugar mass estimates made by the CNN and three human surveyors returned similar means and standard deviations. Over half of the nectar sugar mass estimates made by the model fell within the absolute range of those of the human surveyors. The optimal number of quadrat image samples was determined to be the same for the CNN as for the average human surveyor. For a standard quadrat sampling protocol of 10–15 replicates, this application of deep learning could cut pollinator‐plant survey time per stand of vegetation from hours to minutes. The CNN is restricted to a single view of a quadrat, with no scope for manual examination or specimen collection, though in contrast to human surveyors its object detection is deterministic and its floral unit definition is standardized. As agri‐environment schemes move from prescriptive to results‐based, this approach provides an independent barometer of grassland management which is usable by both landowner and scheme administrator. The model can be adapted to visual estimations of other ecological resources such as winter bird food, floral pollen volume, insect infestation and tree flowering/fruiting, and by adjustment of classification threshold may show acceptable taxonomic differentiation for presence–absence surveys.

Passive acoustic monitoring gives new insight into year-round duetting behaviour of a tropical songbird

Passive acoustic monitoring (PAM) allows for cost-effective, unattended and non-invasive acoustic sampling over an extended period of time and is now an invaluable tool for acoustic monitoring of vocally active species. Its application is rapidly growing in studies covering multiple aspects of avian ecology and behaviour, including presence-absence surveys, population density estimations, threatened species monitoring and anthropogenic impacts on populations. However, the potential for information on year-round variation in male and female vocalisations and the factors affecting duetting behaviour to be derived from PAM has never been exploited. In the present study we deployed automatic recording units (ARU) to investigate long-term sex-specific life strategies based on the vocal activity of the Yellow-breasted Boubou Laniarius atroflavus, an Afromontane, duetting songbird. Using automatic detection we showed strong seasonality in singing performance with males producing solo songs at a higher rate during the breeding than non-breeding season whereas female solos peaked at the end of the breeding season. Duets were produced at a relatively stable rate throughout the year except the time encompassing the turn of the rainy and dry seasons when overall vocal activity was at a low level. In general, year-round singing patterns coincided with the rainy and dry seasons at the study site with vocal activity peaking in the dry season and gradually declining with the onset of rainfall. In addition, we found that boubous were slightly more vocally active when morning temperature was higher, especially in the rainy season. Sex-dependent variation in vocal activity in relation to life cycle stage may suggest that differences between males and females are of functional significance. Most likely, the seasonality of male solo songs could be explained on the basis of sexual selection pressure and that male and female joint vocalizations act as a cooperative behaviour playing a role in territory defence against conspecifics. Our PAM-based results provide new and important insights into how male–female solo songs and duet interactions may be related to year-round territoriality. This may help us to better understand the evolutionary significance of duetting. Furthermore, our findings highlight the link between life cycle events of a tropical songbird and seasonal changes in weather conditions. By tracking the effect of weather on vocal activity, PAM might provide an important indication of how changes in climate may affect bird behaviour.

Presence-only and Presence-absence Data for Comparing Species Distribution Modeling Methods

Species distribution models (SDMs) are widely used to predict and study distributions of species. Many different modeling methods and associated algorithms are used and continue to emerge. It is important to understand how different approaches perform, particularly when applied to species occurrence records that were not gathered in struc­tured surveys (e.g. opportunistic records). This need motivated a large-scale, collaborative effort, published in 2006, that aimed to create objective comparisons of algorithm performance. As a benchmark, and to facilitate future comparisons of approaches, here we publish that dataset: point location records for 226 anonymized species from six regions of the world, with accompanying predictor variables in raster (grid) and point formats. A particularly interesting characteristic of this dataset is that independent presence-absence survey data are available for evaluation alongside the presence-only species occurrence data intended for modeling. The dataset is available on Open Science Framework and as an R package and can be used as a benchmark for modeling approaches and for testing new ways to evaluate the accuracy of SDMs.

Evaluation of Noninvasive Survey Methods for Detecting Endangered Shrews

ABSTRACTUsing traditional capture methods, shrews typically have low capture and high trap‐mortality rates. To reduce effects from live‐trapping and attempt to increase detection success, we investigated 3 potential noninvasive survey methods for shrews (Soricidae): track tubes, scat tubes, and camera traps. These 3 techniques were tested in areas of the San Joaquin Valley, California, USA, with high detection rates of shrews during previous live‐trapping surveys. We found that Reconyx camera traps specifically modified with a close focal distance resulted in the greatest number of positive detections and outperformed all other survey methods. Scat tubes also resulted in positive detections but were less reliable and required more expertise. Track tubes resulted in no positive detections. Use of camera traps is highly recommended for conducting presence–absence surveys for shrews. © 2020 The Wildlife Society.

The role of drought as a determinant of hemorrhagic disease in the eastern United States.

Bluetongue virus and epizootic hemorrhagic disease (HD) virus are globally distributed, vector-borne viruses that infect and cause disease in domestic and wild ruminant species. The forces driving increases in resulting HD may be linked to weather conditions and increasing severity has been noted in northerly latitudes. We evaluated the role of drought severity in both space and time on changes in HD reports across the eastern United States for a recent 15year period. The objectives of this study were to: (a) develop a spatiotemporal model to evaluate if drought severity explains changing patterns of HD presence; and (b) determine whether this potential risk factor varies in importance over the present range of HD in the eastern United States. Historic data (2000-2014) from an annual HD presence-absence survey conducted by the Southeastern Cooperative Wildlife Disease Study and from the United States Drought Monitor were used for this analysis. For every county in 23 states and for each of 15years, data were based on reported drought status for August, wetland cover, the physiographic region, and the status of HD in the previous year. We used a generalized linear mixed model to explain HD presence and evaluated spatiotemporal predictors across the region. We found that drought severity was a significant predictor of HD presence and the significance of this relationship was dependent on latitude. In more northerly latitudes, where immunological naivety is most likely, we demonstrated the increasing strength of drought severity as a determinant of reported HD and established the importance of variation in drought severity as a risk factor over the present range of HD in the eastern United States. Our research provides spatially explicit evidence for the link between climate forces and emerging disease patterns across latitude for a globally distributed disease.

River Otter Status, Management, and Distribution in the United States: Evidence of Large-Scale Population Increase and Range Expansion

Abstract River otter Lontra canadensis populations in the United States have expanded during the past 50 y as a result of improvements in habitat quality and effective management programs implemented by state and federal agencies and native tribes. Periodic assessments of river otter status, population trends, and geographic distribution are needed to detect changes in populations, assess management approaches, and to identify and prioritize conservation efforts. We surveyed state wildlife agency experts to assess the current population and regulatory status of river otters in their jurisdictions. River otters were legally harvested in 40 states as of 2016. Twenty-two states reported increasing populations while 25 reported stable populations. Most states used multiple methods to monitor river otter populations including harvest-based surveys, presence–absence surveys, and empirically derived population model predictions; harvest-based surveys were the most commonly used monitoring approach. As populations have expanded, river otter reintroduction efforts have become less frequent; two additional states had conducted reintroductions since 1998 and only one state had conducted a reintroduction since 2010. We estimated that river otter distribution increased by 10.2% in the continental United States and by 13.7% in the contiguous United States during an 18-y period. Although populations may continue to increase numerically, river otters may be approaching their potential maximum geographic distribution in the United States.

Cross-scale interactions and non-native cattails influence the distributions of a wetland-obligate species

Landscape configuration and composition can influence the spatial distribution of species. Cross-scale interactions may exist when multiscale effects interplay to shape species’ distribution patterns. We investigated how the spatial distribution of a semiaquatic mammal, muskrat (Ondatra zibethicus), is influenced by local-scale resource characteristics. We also assessed how fetch, the unobstructed distance wind can travel across water, influences fine-scale habitat use by muskrats. We used 2 years of presence-absence surveys (2015–2016) at 71 wetland sites to evaluate the spatial distribution of muskrats in a lacustrine system in Minnesota, USA. We expected site occupancy and colonization to be positively associated with the amount of Typha x glauca (a rapidly establishing invasive hybrid cattail species) at sites, and negatively associated with fetch impact, water depths, and open water areas. As expected, sites with greater coverage of T. x glauca, shallower water depths, and less open water had greater initial occupancy probabilities. Muskrats were more likely to colonize fetch-impacted sites if there were also greater coverages of T. x glauca present. The distribution and intensity of fetch, dictated by the watershed-scale configuration of upland landscapes, influenced site colonization by muskrats. Our results suggest that this landscape-scale effect is mediated by the amount of T. x glauca present at much finer scales. This cross-scale interaction may facilitate distribution expansions of wetland-obligate species into otherwise unsuitable habitats.

Land use and cover effects on an ecosystem engineer

Human induced land-use change in the form of urbanization and agriculture are rapidly transforming our planet’s terrestrial landscapes and causing the loss of species at unprecedented rates. Studies documenting the impacts of development are extensive; however, less is known about the scale at which species respond to development and specific features of altered landscapes that make them vulnerable. This shortcoming may be due to the difficulty of collecting data across large spatial extents, but filling these information gaps are critical, particularly for species that have a disproportionate influence on ecosystems, such as ecosystem engineers. One such species, the southeastern pocket gopher (Geomys pinetis), has been declining throughout its range (southeastern United States) and continued loss will likely have strong effects on the imperiled longleaf pine ecosystem in which it is closely associated. Using range-wide data from presence-absence surveys and publicly available presence-only data, we used recent advances in species distribution modeling to understand this ecosystem engineer’s associations with extensive land use and cover changes. Our study showed that pocket gophers inhabit a variety of land-use types, including regions with low levels of anthropogenic development, but are largely absent from intensely urbanized areas and closed-canopy forests. Conservation planning to reduce the spread of extensive development and forest management strategies to reduce closed-canopy systems will be instrumental in reducing the decline of the species and ultimately protection of the longleaf pine ecosystem. The approach used in this study will be increasingly beneficial for understanding species response to land-use change.

Implementation of an occupancy-based monitoring protocol for a widespread and cryptic species, the New England cottontail (Sylvilagus transitionalis)

Context Designing effective long-term monitoring strategies is essential for managing wildlife populations. Implementing a cost-effective, practical monitoring program is especially challenging for widespread but locally rare species. Early successional habitat preferred by the New England cottontail (NEC) has become increasingly rare and fragmented, resulting in substantial declines from their peak distribution in the mid-1900s. The introduction of a possible competitor species, the eastern cottontail (EC), may also have played a role. Uncertainty surrounding how these factors have contributed to NEC declines has complicated management and necessitated development of an appropriate monitoring framework to understand possible drivers of distribution and dynamics. Aims Because estimating species abundance is costly, we designed presence–absence surveys to estimate species distributions, test assumptions about competitive interactions, and improve understanding of demographic processes for eastern cottontails (EC) and New England cottontails (NEC). The survey protocol aimed to balance long-term management objectives with practical considerations associated with monitoring a widespread but uncommon species. Modelling data arising from these observations allow for estimation of covariate relationships between species status and environmental conditions including habitat and competition. The framework also allows inference about species status at unsurveyed locations. Methods We designed a monitoring protocol to collect data across six north-eastern USA states and, using data collected from the first year of monitoring, fit a suite of single-season occupancy models to assess how abiotic and biotic factors influence NEC occurrence, correcting for imperfect detectability. Key results Models did not provide substantial support for competitive interactions between EC and NEC. NEC occurrence patterns appear to be influenced by several remotely sensed habitat covariates (land-cover classes), a habitat-suitability index, and, to a lesser degree, plot-level habitat covariates (understorey density and canopy cover). Conclusions We recommend continuing presence–absence monitoring and the development of dynamic occupancy models to provide further evidence regarding hypotheses of competitive interactions and habitat influences on the underlying dynamics of NEC occupancy. Implications State and federal agencies responsible for conserving this and other threatened species can engage with researchers in thoughtful discussions, based on management objectives, regarding appropriate monitoring design to ensure that the allocation of monitoring efforts provides useful inference on population drivers to inform management intervention.

Occupancy modeling of Parnassius clodius butterfly populations in Grand Teton National Park, Wyoming

Estimating occupancy patterns and identifying vegetation characteristics that influence the presence of butterfly species are essential approaches needed for determining how habitat changes may affect butterfly populations in the future. The montane butterfly species, Parnassius clodius, was investigated to identify patterns of occupancy relating to habitat variables in Grand Teton National Park and Bridger-Teton National Forest, Wyoming, United States. A series of presence–absence surveys were conducted in 2013 in 41 mesic to xeric montane meadows that were considered suitable habitat for P. clodius during their flight season (June–July) to estimate occupancy (ψ) and detection probability (p). According to the null constant parameter model, P. clodius had high occupancy of ψ = 0.78 ± 0.07 SE and detection probability of p = 0.75 ± 0.04 SE. In models testing covariates, the most important habitat indicator for the occupancy of P. clodius was a strong negative association with big sagebrush (Artemisia tridentata; β = − 21.39 ± 21.10 SE) and lupine (Lupinus spp.; β = − 20.03 ± 21.24 SE). While P. clodius was found at a high proportion of meadows surveyed, the presence of A. tridentata may limit their distribution within montane meadows at a landscape scale because A. tridentata dominates a large percentage of the montane meadows in our study area. Future climate scenarios predicted for high elevations globally could cause habitat shifts and put populations of P. clodius and similar non-migratory butterfly populations at risk.

Large-scale citizen science improves assessment of risk posed by wind farms to bats in southern Scotland

In order to ensure that the placement of future wind energy developments does not conflict with important areas for bats, surveys and analyses are required to deliver a robust understanding of large-scale patterns in species’ distributions and abundance. We demonstrate that extensive presence-absence survey data can be collected for bats across a large (>20,000km2) region of southern Scotland using volunteers supplemented with additional fieldworker effort in remote areas. We advocate a survey design that allows data to be collected for all bat species, but provide more focused analyses on three species (Leisler's bat, noctule and Nathusius' pipistrelle) that are currently considered to be at highest risk from wind turbines. We estimate that between 16% and 24% of the regional populations of these three high risk species overlap existing and approved wind farms, with 50% of this overlap concentrated at just 10% of wind farms. This emphasises the importance of new wind farm placement to minimise impact on these species. We have stratified the region according to the potential impact on bats of future wind farm development, highlighting those areas in the top 1%, 5% and 10% of risk. We conclude that there is a need for higher quality data of this type in order to inform spatial models of bat distribution and activity. As a minimum standard, researchers working on bats should prioritise the collection and use of presence-absence data with consideration of the underlying survey design and representativeness of the data collected. This can be achieved most cost-effectively by working with the public to develop large-scale acoustic monitoring schemes.

Occupancy and Detection of Clinch Dace Using Two Gear Types

Abstract The Clinch Dace Chrosomus sp. cf. saylori, discovered in 1999, is an undescribed headwater fish species of global conservation concern with a limited distribution in two counties in southwest Virginia. Highly efficient sampling gears are key to monitoring headwater fish assemblages in Appalachia, including those containing Clinch Dace. Additional information is needed regarding the habitat requirements of the species to understand responses to future mining and logging activities in the region. An occupancy modeling framework is useful to account for incomplete detection, with multiple sampling gears in presence–absence surveys for cryptic or rare species. We detected Clinch Dace at 13 of 70 sites. Occupancy corrected for imperfect detection probability did not differ from naïve occupancy estimates and was 0.19. Clinch Dace occurred in streams with higher substrate embeddedness and catchment forest cover. Backpack electrofishing had a 55% higher probability of detecting Clinch Dace in a 50-m subreach than minnow traps. Appropriate management actions for this species may focus on preserving forested cover in occupied watersheds and monitoring the future impact of surface mining activities that increase total dissolved solids. Sampling protocols for the imperiled Clinch Dace can incorporate both gears and adjust sampling effort to maximize species detection in specific habitats and with specific research goals.

New Distributional Records of the Stygobitic CrayfishCambarus cryptodytes(Decapoda: Cambaridae) in the Floridan Aquifer System of Southwestern Georgia

Cambarus cryptodytes (Dougherty Plain Cave Crayfish) is an obligate inhabitant of groundwater habitats (i.e., a stygobiont) with troglomorphic adaptations in the Floridan aquifer system of southwestern Georgia and adjacent Florida panhandle, particularly in the Dougherty Plain and Marianna Lowlands. Documented occurrences of Dougherty Plain Cave Crayfish are spatially distributed as 2 primary clusters separated by a region where few caves and springs have been documented; however, the paucity of humanly accessible karst features in this intermediate region has inhibited investigation of the species' distribution. To work around this constraint, we employed bottle traps to sample for Dougherty Plain Cave Crayfish and other groundwater fauna in 18 groundwater-monitoring wells that access the Floridan aquifer system in 10 counties in southwestern Georgia. We captured 32 Dougherty Plain Cave Crayfish in 9 wells in 8 counties between September 2014 and August 2015. We detected crayfish at depths ranging from 17.9 m to 40.6 m, and established new county records for Early, Miller, Mitchell, and Seminole counties in Georgia, increasing the number of occurrences in Georgia from 8 to 17 sites. In addition, a new US Geological Survey (USGS) Hydrologic Unit Code 8 (HUC8) watershed record was established for the Spring Creek watershed. These new records fill in the distribution gap between the 2 previously known clusters in Georgia and Jackson County, FL. Furthermore, this study demonstrates that deployment of bottle traps in groundwater-monitoring wells can be an effective approach to presence—absence surveys of stygobionts, especially in areas where surface access to groundwater is limited.

A Presence-Absence Survey to Monitor Montezuma Quail in Western Texas

Developing an effective monitoring program for Montezuma quail (Cyrtonyx montezumae) is challenging because the technique must be practical for surveying vast, remote landscapes while accounting for the species’ low detectability. We used call-back surveys within a presence–absence framework to estimate occupancy and detection probability of Montezuma quail and used this information in conjunction with habitat data to develop an estimated probability of occurrence map for the species. We established survey points at 4 sites in western Texas (n = 20–30 points/site) and conducted 5 repeat surveys/season during June–August 2007 and 2008. We documented abiotic conditions (temperature, time of day, survey number, and year) during surveys and quantified microhabitat (% bare ground, food-plant density, vegetation height, and visual obstruction) and macrohabitat (vegetation type, elevation, aspect, and slope) at survey points. We then used an information-theoretic approach to evaluate the influence of micro- and macro-habitat on detection probability and occupancy at a local and regional scale, respectively. At a microhabitat scale, the most parsimonious model (ΔAICc R2 = 0.46) suggested detection probability was influenced primarily by year (βYear = 0.91, 95% CI = 0.24–1.57), with occupancy being influenced primarily (but minimally) by year (βYear = –59.7, 95% CI = –179.0–59.6) and vegetation-height (βVH = 67.7, 95% CI = –71.9–207.4). This model indicated that detection probability decreased from 2007 (0.40; 95% CI = 0.31–0.49) to 2008 (0.21; 95% CI = 0.14–0.32), as did occupancy (1.00 vs. 0.72, respectively), which corresponded to a transition from a relatively wet to dry year. At a macrohabitat scale, the most parsimonious model (ΔAICc R2 = 0.20) suggested occupancy was influenced by elevation (βElevation = 1.11 ± 0.56) and vegetation type (βVegetation type 2 = –3.17 ± 1.26; βVegetation type 3 = –1.20 ± 1.18), and we used these variables to construct a first-approximation, probability of occupancy map. Given our findings, presence–absence surveys may be a viable approach for monitoring Montezuma quail populations through time, and use of a probability of occupancy map can help with efficient allocation of survey points and effort. However, the viability of using a presence–absence approach to monitor Montezuma quail populations will depend on whether sampling effort can be increased sufficiently to obtain more precise estimates of occupancy. In addition, our probability of occupancy map should be regarded as a first approximation and further research should be conducted to refine the relationships.

Elliott traps found to be ineffective for the survey of swamp skink (Lissolepis coventryi): a cautionary tale of outdated survey guidelines

Context Cryptic (i.e. secretive, elusive or well camouflaged) species are often very challenging to accurately survey. Because many cryptic species are threatened, the development of robust and efficient survey methods to detect them is critically important for conservation management. The swamp skink (Lissolepis coventryi) is an example of an elusive and threatened species; it inhabits densely vegetated, wet environments throughout south-east Australia. The swamp skink occurs in peri-urban areas and faces many human-induced threats including habitat loss, introduced predators and environmental pollution. Effective and reliable survey methods are therefore essential for its conservation. Aims This study aimed to review the current swamp skink survey guidelines to compare the detection success of Elliott traps with two alternative methods: passive infrared cameras (camera traps) and artificial refuges. Methods Detection probabilities for the swamp skink were compared using Elliott traps, artificial refuges and camera traps at two known populations on the Mornington Peninsula, Victoria, Australia. Key results Artificial refuges and camera traps were significantly more successful than Elliott traps at detecting swamp skinks. Conclusions Elliott traps are currently regarded as the standard technique for surveying swamp skinks; however, these traps were the least successful of the three methods trialled. Therefore, the use of Elliott traps in future swamp skink presence–absence surveys is not recommended. Implications Many previous surveys utilising Elliott traps have failed to detect swamp skinks in habitats where they are likely to occur. Our findings suggest that at least some of these past surveys may have reported false absences of swamp skinks, potentially resulting in poor planning decisions. A reduction in the reliance on Elliott trapping is likely to increase future swamp skink detection success, broaden our understanding of this cryptic species and aid conservation efforts. Our results emphasise that it is essential to regularly review recommended survey methods to ensure they are accurate and effective for target species.

Detection limits of quantitative and digital PCR assays and their influence in presence–absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low-concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species' presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp (Ctenopharyngodon idella) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty-indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis and forensic and clinical diagnostics.

Designing occupancy studies when false‐positive detections occur

Summary Recently, estimators have been developed to estimate occupancy probabilities when false‐positive detections occur during presence–absence surveys. Some of these estimators combine different types of survey data to improve estimates of occupancy. With these estimators, there is a trade‐off between the number of sample units surveyed, and the number and type of surveys at each sample unit. Guidance on efficient design of studies when false positives occur is unavailable. For a range of scenarios, I identified survey designs that minimized the mean square error of the estimate of occupancy. I considered an approach that uses one survey method and two observation states and an approach that uses two survey methods. For each approach, I used numerical methods to identify optimal survey designs when model assumptions were met and parameter values were correctly anticipated, when parameter values were not correctly anticipated and when the assumption of no unmodelled detection heterogeneity was violated. Under the approach with two observation states, false‐positive detections increased the number of recommended surveys, relative to standard occupancy models. If parameter values could not be anticipated, pessimism about detection probabilities avoided poor designs. Detection heterogeneity could require more or fewer repeat surveys, depending on parameter values. If model assumptions were met, the approach with two survey methods was inefficient. However, with poor anticipation of parameter values, with detection heterogeneity or with removal sampling schemes, combining two survey methods could improve estimates of occupancy. Ignoring false positives can yield biased parameter estimates, yet false positives greatly complicate the design of occupancy studies. Specific guidance for major types of false‐positive occupancy models, and for two assumption violations common in field data, can conserve survey resources. This guidance can be used to design efficient monitoring programmes and studies of species occurrence, species distribution or habitat selection, when false positives occur during surveys.

Bird diversity in the savanna habitats of Akagera National Park, Rwanda, in the post-war recovery period

The biodiversity of Akagera National Park (ANP), Rwanda, has reportedly been declining since 1990 due to conflict and war in the country between 1990 and 1994. In this paper, we describe bird diversity in the post-war recovery period. We used systematic plots, point counts and presence–absence surveys to estimate bird species richness and diversity in acacia savanna habitats of the park between 2009 and 2011. We recorded a total number of 301 species, of which 75% were resident and 22% migrant, including a large number of Palearctic visitors and Afrotropical migrants. Particularly notable were four endemic species of the Lake Victoria region, four globally threatened and nine near-threatened species as well as species that had not previously been recorded in the park and those overlooked by past records. Estimated species richness and diversity at the landscape level were 346 and 0.98, respectively, mean estimates per plot were 42 and 0.86 for species richness and diversity, respectively. Our results highlight regional and international importance of ANP in protecting important bird diversity. We also emphasise that ANP is the only savanna habitat in Rwanda where typical savanna birds occur. Our findings provide new insights for further strengthening of efforts to conserve the park's biodiversity.