Influences of landscape characteristics on the nesting ecology of female wild turkeys and behavior of raccoons

Nest predation is the principle source of reproductive failure in many bird species. Understanding nest predation requires knowledge of interactions between landscape characteristics, and the ecology and behavior of birds and local nest predators. I studied nesting ecology and multi-scale habitat selection of female wild turkeys and the habitat selection and searching behaviors of raccoons, an important nest predator, in a bottomland hardwood forest in Louisiana. My objective was to evaluate the relationships between habitat, wild turkey nest site selection, and raccoon foraging behavior. I used first-passage time (FPT) analysis on nightly foraging tracks of raccoons during the turkey nesting period to test the applicability of the method to a terrestrial predator, determine whether raccoons engage in area-restricted searching (ARS), and to identify areas of concentrated searching activity. Mean turkey home ranges sizes varied from 673ha during pre-incubation to 363ha during brood-rearing. Mature upland forests were selected by turkeys year round. Wild turkeys nested in upland forests (n = 35) and openings (n = 6) offering understory cover, often close to forest edges. Wild turkey reproduction was characterized by low nesting rates (60%) and average nest success rates (39%), and nest predation was the leading cause of nest failure (34%). Mean raccoon home range sizes ranged from 177ha during breeding to 120ha during summer. Seasonal habitat selection varied, presumably as a response to spatio-temporal changes in food availability. Evidence of ARS was found in 55 of 58 paths analyzed and could be induced by supplemental feeding, validating the assumption that ARS represented foraging activity. ARS was associated with lower elevations and shallow standing water, whereas raccoons moved quickly through upland forest habitats with sparse understory vegetation. These results suggest that nest predation by raccoons is incidental rather than the result of targeted searching in habitats with similar structure to those selected by wild turkeys for nesting in this system. This represents the first time FPT has been applied to a terrestrial predator and researchers should consider FPT in future studies of habitat use and foraging ecology of terrestrial predators

Using object-based image analysis to detect laughing gull nests

Remote sensing has long been used to study wildlife; however, manual methods of detecting wildlife in aerial imagery are often time-consuming and prone to human error, and newer computer vision techniques have not yet been extensively applied to wildlife surveys. We used the object-based image analysis (OBIA) software eCognition to detect laughing gull (Leucophaeus atricilla) nests in Jamaica Bay as part of an ongoing monitoring effort at the John F. Kennedy International Airport. Our technique uses a combination of high resolution 4-band aerial imagery captured via manned aircraft with a multispectral UltraCam Falcon M2 camera, LiDAR point cloud data, and land cover data derived from a bathymetric LiDAR point cloud to classify and extract laughing gull nests. Our ruleset uses the site (topographic position of nest objects), tone (spectral characteristic of nest objects), shape, size, and association (nearby objects commonly found with the objects of interest that help identify them) elements of image interpretation, as well as NDVI and a sublevel object examination to classify and extract nests. The ruleset achieves a producer’s accuracy of 98% as well as a user’s accuracy of 65% and a kappa of 0.696, indicating that it extracts a majority of the nests in the imagery while reducing errors of commission to only 35% of the final results. The remaining errors of commission are difficult for the software to differentiate without also impacting the number of nests successfully extracted and are best addressed by a manual verification of output results as part of a semi-automated workflow in which the OBIA is used to complete the initial search of the imagery and the results are then systematically verified by the user to remove errors. This eliminates the need to manually search entire sets of imagery for nests, resulting in a much more efficient and less error prone methodology than previous unassisted image interpretation techniques. Because of the extensibility of OBIA software and the increasing availability of imagery due to small unmanned aircraft systems (sUAS), our methodology and its benefits have great potential for adaptation to other species surveyed using aerial imagery to enhance wildlife population monitoring

Developing fine-grained nationwide predictions of valuable forests using biodiversity indicator bird species

Publisher Copyright: © 2021 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.The use of indicator species in forest conservation and management planning can facilitate enhanced preservation of biodiversity from the negative effects of forestry and other uses of land. However, this requires detailed and spatially comprehensive knowledge of the habitat preferences and distributions of selected focal indicator species. Unfortunately, due to limited resources for field surveys, only a small proportion of the occurrences of focal species is usually known. This shortcoming can be circumvented by using modelling techniques to predict the spatial distribution of suitable sites for the target species. Airborne laser scanning (ALS) and other remote sensing (RS) techniques have the potential to provide useful environmental data covering systematically large areas for these purposes. Here, we focused on six bird of prey and woodpecker species known to be good indicators of boreal forest biodiversity values. We used known nest sites of the six indicator species based on nestling ringing records. Thus, the most suitable nesting sites of these species provide important information for biodiversity-friendly forest management and conservation planning. We developed fine-grained, i.e., 96 x 96 m grid cell resolution, predictive maps across the whole of Finland of the suitable nesting habitats based on ALS and other RS data and spatial information on the distribution of important forest stands for the six studied biodiversity indicator bird species based on nesting habitat suitability modelling, i.e., the MaxEnt model. Habitat preferences of the study species, as determined by MaxEnt, were in line with the previous knowledge of species-habitat relations. The proportion of suitable habitats of these species in protected areas was considerable, but our analysis also revealed many potentially high-quality forest stands outside protected areas. However, many of these sites are increasingly threatened by logging due to increased pressures for using forests for bioeconomy and forest industry based on National Forest Strategy. Predicting habitat suitability based on information on the nest sites of indicator species provides a new tool for systematic conservation planning over large areas in boreal forests in Europe, and corresponding approach would also be feasible and recommendable elsewhere where similar data are available.The use of indicator species in forest conservation and management planning can facilitate enhanced preservation of biodiversity from the negative effects of forestry and other uses of land. However, this requires detailed and spatially comprehensive knowledge of the habitat preferences and distributions of selected focal indicator species. Unfortunately, due to limited resources for field surveys, only a small proportion of the occurrences of focal species is usually known. This shortcoming can be circumvented by using modeling techniques to predict the spatial distribution of suitable sites for the target species. Airborne laser scanning (ALS) and other remote sensing (RS) techniques have the potential to provide useful environmental data covering systematically large areas for these purposes. Here, we focused on six bird of prey and woodpecker species known to be good indicators of boreal forest biodiversity values. We used known nest sites of the six indicator species based on nestling ringing records. Thus, the most suitable nesting sites of these species provide important information for biodiversity-friendly forest management and conservation planning. We developed fine-grained, that is, 96 x 96 m grid cell resolution, predictive maps across the whole of Finland of the suitable nesting habitats based on ALS and other RS data and spatial information on the distribution of important forest stands for the six studied biodiversity indicator bird species based on nesting-habitat suitability modeling, that is, the MaxEnt model. Habitat preferences of the study species, as determined by MaxEnt, were in line with the previous knowledge of species-habitat relations. The proportion of suitable habitats of these species in protected areas (PAs) was considerable, but our analysis also revealed many potentially high-quality forest stands outside PAs. However, many of these sites are increasingly threatened by logging because of increased pressures for using forests for bioeconomy and forest industry based on National Forest Strategy. Predicting habitat suitability based on information on the nest sites of indicator species provides a new tool for systematic conservation planning over large areas in boreal forests in Europe, and a corresponding approach would also be feasible and recommendable elsewhere where similar data are available.Peer reviewe

Applications Of An Unmanned Aircraft Vehicle And Remote Cameras For Studying A Sub-Arctic Ecosystem

The midcontinent population of lesser snow geese (Anser caerulescens caerulescens) has increased dramatically since the 1960’s due to changing agricultural practices in their southern wintering areas. The destructive foraging and continued population growth of lesser snow geese has resulted in cascading negative impacts on northern ecosystems. Studying remote sub-Arctic ecosystems is logistically challenging, but the advent of remote sensing technologies (such as drones and remote cameras) may assist ecologists in understanding snow goose ecology. Before these tools can be integrated into snow goose research programs, precursor “proof-of-concept” studies are required to validate tool use. The objectives of this study were to investigate the use of unmanned aircraft systems (hereafter “drones”) and remote cameras for studying various aspects of lesser snow goose ecology within the sub-Arctic ecosystem of the Cape Churchill Peninsula, Manitoba, Canada. We first evaluated impacts of drone surveys on wildlife by measuring drone-induced behavioural responses of nesting lesser snow geese using mini-surveillance cameras. We monitored 25 nests with cameras from 2015-2016, comparing behaviours of birds on days with drone surveys, and on days without surveys. Days with drone surveys resulted in decreased low-vigilance behaviours, and increased high-vigilance behaviours. Similarly, overhead vigilance behaviours increased from a baseline 0.03% of observation time to 0.56% when the drone was overhead, indicating birds were likely observing the drone as it flew overhead. Polar bears (Ursus maritimus) were also monitored via video recording during drone flights in 2016, and they responded in a similar fashion to previously published tourism activity impact estimates (mean vigilance bout lengths during drone surveys = 18.7 ± 2.6 seconds). We estimated goose habitat degradation using photointerpretation of drone imagery and compared estimates to those made with ground-based linear transects. We compared estimates between ground-based transects and those made from unsupervised classification of drone imagery collected at altitudes of 75, 100, and 120 m above ground level (ground sampling distances of 2.4, 3.2, and 3.8 cm respectively). We found large time savings during the data collection step of drone surveys, but these savings were ultimately lost during imagery processing. Based on photointerpretation, overall accuracy of drone imagery was generally high (88.8% to 92.0%) and Kappa coefficients were similar to previously published habitat assessments from drone imagery. Mixed model estimates indicated 75m drone imagery overestimated barren (F2,182 = 100.03, P \u3c 0.0001) and shrub classes (F2,182 = 160.16, P \u3c 0.0001) compared to ground estimates. Inconspicuous graminoid and forb species (non-shrubs) were difficult to detect from drone imagery and were underestimated compared to ground-based transects (F2,182 = 843.77, P \u3c 0.0001). Remote cameras were also used as a remote sensing tool to estimate impacts of Ursid predators on nesting lesser snow geese. From 2013-2018 we deployed 233 remote cameras on goose nests and reviewed images for occurrences of bears and associated avian predators. We recorded the amount of time that female geese spent on and of their nest on days with bears (bear-days), and the day before (control-days). Contrary to predictions, geese spent less total time off-nest on bear-days than control-days (β = -0.32 ± 0.13, P \u3c 0.05). Avian predators were observed more frequently on bear-days (13/18 days) than their paired control-days (2/18 days), and bear presence has a positive effect on avian predator occurrence (β = 3.035 ± 0.916, P \u3c 0.001). We suspect that geese spend more time on-nest in response to bears to defend nests from increased activity of avian predators, and we examined these behaviours using agent-based models. In mixed predator scenarios (bears and avian predators), birds that left their nest early would reduce the probability of nest loss by bears, but had increased risk by avian predators. This work demonstrates that the relationship between nesting geese and bear predators is more complex than commonly depicted, and provides a foundation for future examination of the continued impact of bears on nesting birds. This work demonstrates the value of remote sensing tools for understanding sub-Artic ecosystems and other regions where ecological research is logistically challenging

Long-Billed Curlew Nest Site Selection and Success in the Intermountain West

Grassland birds have experienced steeper population declines between 1966 and 2015 than any other bird group on the North American continent, and migratory grassland birds may face threats in all stages of their annual cycle. The grassland‐associated long‐billed curlew (Numenius americanus) is experiencing population declines in regional and local portions of their North American breeding range. The nesting period is an important portion of the annual cycle when curlews may face demographic rate limitations from a suite of threats including predators and anthropogenic disturbance. We compared nest sites to random sites within breeding territories to examine nest site selection, and modeled correlates of nesting success for 128 curlew nests at 5 Intermountain West sites. Nest sites were 6 times more likely than random sites to be situated adjacent to existing cowpies. Additionally, curlews selected nest sites with shorter vegetation, and less bare ground, grass, and shrub cover than at random sites within their territories. Nest success varied widely among sites and ranged from 12% to 40% in a season with a mean of 27% for all nests during the 2015 and 2016 seasons. Higher nest success probability was associated with higher curlew densities in the area, greater percent cover of conspicuous objects (cowpies, rocks) near the nest, and higher densities of black‐billed magpies (Pica hudsonia) and American crows (Corvus brachyrhynchos) at the site. We also found increased probability of nesting success with increased distance from a nest to the nearest potential perch in that territory. Given the central role of working lands to curlews in much of the Intermountain West, understanding limitations to nesting success in these diverse landscapes is necessary to guide adaptive management strategies in increasingly human‐modified habitats. We suggest some grazing and irrigation practices already provide suitable nesting conditions for curlews, and others may require only minor temporal shifts to improve compatibility