Joint Modeling of Distances and Times in Point-Count Surveys

Removal and distance modeling are two common methods to adjust counts for imperfect detection in point-count surveys. Several recent articles have formulated models to combine them into a distance-removal framework. We observe that these models fall into two groups building from different assumptions about the joint distribution of observed distances and first times to detection. One approach assumes the joint distribution results from a Poisson process (PP). The other assumes an independent joint (IJ) distribution with its joint density being the product of its marginal densities. We compose an IJ+PP model that more flexibly models the joint distribution and accommodates both existing approaches as special cases. The IJ+PP model matches the bias and coverage of the true model for data simulated from either PP or IJ models. In contrast, PP models underestimate abundance from IJ simulations, while IJ models overestimate abundance from PP simulations. We apply all three models to surveys of golden-crowned sparrows in Alaska. Only the IJ+PP model reasonably fits the joint distribution of observed distances and first times to detection. Model choice affects estimates of abundance and detection but has little impact on the magnitude of estimated covariate effects on availability and perceptibility.Supplementary materials accompanying this paper appear online.

Singing in the suburbs: point count surveys efficiently reveal habitat associations for nocturnal Orthoptera across an urban-to-rural gradient

As evidence for global insect population declines continues to amass, several studies have indicated that Orthoptera (grasshoppers, crickets, and katydids) are among the most threatened insect groups. Understanding Orthoptera populations across large spatial extents requires efficient survey protocols, however, many previously established methods are expensive and/or labor-intensive. One survey method widely employed in wildlife biology, the aural point count, may work well for crickets and katydids (suborder: Ensifera) because males produce conspicuous, species-specific mating calls. We conducted repeated point count surveys across an urban-to-rural gradient in central Pennsylvania. Occupancy analyses of ten focal species indicated that, although detection probability rates varied by species from 0.43 to 0.98, detection rates compounded over five visits such that all focal species achieved cumulative > 0.90. Factors associated with site occupancy varied among species with some positively associated with urbanization (e.g., Greater Anglewing, Microcentrum rhombifolium), some negatively associated with urbanization (e.g., Sword-bearing Conehead, Neoconocephalus ensiger), and others exhibiting constant occupancy across a habitat gradient (e.g., Common True Katydid, Pterophylla camellifolia). Our community-level analysis revealed that different species’ habitat associations interacted such that intermediate levels of urbanization (i.e., suburbs) hosted the highest number of species. Implications for insect conservation Ultimately, our analyses clearly support the concept that aural point counts paired with static occupancy modeling can serve as an important tool for monitoring night-singing Orthoptera populations. Applications of point count surveys by both researchers and citizen scientists may improve our understanding Ensifera populations and help in the global conservation of these threatened insects.

The density of the Atlantic marsh fiddler crab (Minuca pugnax, Smith, 1870) (Decapoda: Brachyura: Ocypodidae) in its expanded range in the Gulf of Maine, USA

The Atlantic marsh fiddler crab, Minuca pugnax (Smith, 1870), is a climate migrant that recently expanded its range northward into the Gulf of Maine. We tracked the M. pugnax population within the Great Marsh, in northeastern Massachusetts, USA, since it was first detected in 2014 using burrow counts. Because burrow counts can overestimate fiddler-crab density, we used camera traps to determine the relationship between burrow densities and fiddler-crab densities in 2019. The burrow count surveys show a six-fold increase in the density of M. pugnax in the Great Marsh from 2014 to 2019. Results indicates that the fiddler-crab population in the expanded range is established and growing. Based on burrow counts, however, the density of M. pugnax in the expanded range (6 burrows m–2) remains much lower than those found in the historical range (up to 300 burrows m–2). Based on the camera traps, we determined that burrow counts overestimated fiddler-crab densities by 47% in 2019. There was, on average, one crab detected for every two burrows observed. This result suggests that estimates of densities of M. pugnax based on burrow counts should be reduced by half. Minuca pugnax is an ecosystem engineer that can influence saltmarsh functioning and the magnitude of that influence is related to its density. Our results imply that the populations of M. pugnax in the expanded range are currently having minor impacts on marshes relative to larger populations in the historical range, but their impact will increase as the populations grow.

Seasonal and annual fluctuations of deer populations estimated by a Bayesian state–space model

Deer overabundance is a contributing factor in the degradation of plant communities and ecosystems worldwide. The management and conservation of the deer-affected ecosystems requires us to urgently grasp deer population trends and to identify the factors that affect them. In this study, we developed a Bayesian state–space model to estimate the population dynamics of sika deer (Cervus nippon) in a cool-temperate forest in Japan, where wolves (Canis lupus hodophilax) are extinct. The model was based on field data collected from block count surveys, road count surveys by vehicles, mortality surveys during the winter, and nuisance control for 12 years (2007–2018). We clarified the seasonal and annual fluctuation of the deer population. We found two peaks of deer abundance (2007 and 2010) over 12 years. In 2011 the estimated deer abundance decreased drastically and has remained at a low level then. The deer population increased from spring to autumn and decreased from autumn to winter in most years. The seasonal fluctuation we detected could reflect the seasonal migration pattern of deer and the population recruitment through fawn births in early summer. In our model, snowfall accumulation, which can be a lethal factor for deer, may have slightly affected their mortality during the winter. Although we could not detect a direct effect of snow on population dynamics, snowfall decrease due to global warming may decelerate the winter migration of deer; subsequently, deer staying on-site may intensively forage evergreen perennial plants during the winter season. The nuisance control affected population dynamics. Even in wildlife protection areas and national parks where hunting is regulated, nuisance control could be effective in buffering the effect of deer browsing on forest ecosystems.