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37 results for “nest boxes”
FIG. 3 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge
FIG. 3. Bubble plot showing the results of two-dimensional local spatial autocorrelation analysis for all Eastern Box Turtles (n ¼ 165) sampled in northwestern Michigan. Circles represent individuals and the size of the circle is proportional to the P-values from permutation testing, with large circles representing individuals that are significantly more related to their five nearest neighbors than expected (P, 0.05) based on a random distribution of genotypes. Figure shows the distribution of five genetic ''hotspots'' in relation to known nesting sites (NS) across the study area. Some distantly sampled individuals are omitted for figure clarity.
FIG. 2 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge
FIG. 2. Spatial genetic autocorrelograms of genetic correlation coefficients (r) as a function of distance for Eastern Box Turtles in northwestern Michigan. Plots represent (A) all individuals (n ¼ 165), (B) females only (n ¼ 104), and (C) males only (n ¼ 51). Dashed lines are permuted 95% confidence intervals across all data, and error bars are bootstrapped 95% confidence intervals within each distance class. Tables below graphs represent data for each distance class including the number of pairwise comparisons (n), the correlation coefficients (r), and the P-values (p) associated with bootstrap tests of significance for positive spatial genetic autocorrelation.
FIG. 1 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge
FIG. 1. Scatterplot showing the matrix of pairwise genetic distances and matrix of pairwise geographic distances for box turtles sampled along the river corridor. Warmer colors within the kernel density indicate higher densities of points. The line (slope ¼ 1.074727e–05; R2 ¼ 0.002992) shows the correlation trend.
Nonideal nest box selection by tree swallows breeding in farmlands: evidence for an ecological trap?
<p>Animals are expected to select a breeding habitat using cues that should reflect, directly or not, the fitness outcome of the different habitat options. However, human-induced environmental changes can alter the relationships between habitat characteristics and their fitness consequences, leading to maladaptive habitat choices. The most severe case of such nonideal habitat selection is the ecological trap, which occurs when individuals prefer to settle in poor-quality habitats while better ones are available. Here we studied the adaptiveness of nest box selection in a tree swallow (<i>Tachycineta bicolor</i>) population breeding over a 10-year period in a network of 400 nest boxes distributed along a gradient of agricultural intensification in southern Québec, Canada. We first examined the effects of multiple environmental and social habitat characteristics on nest box preference to identify potential settlement cues. We then assessed the links between those cues and habitat quality as defined by the reproductive performance of individuals that settled early or late in nest boxes. We found that tree swallows preferred nesting in open habitats with high cover of perennial forage crops, high spring insect biomass, and high density of house sparrows (<i>Passer domesticus</i>), their main competitors for nest sites. They also preferred nesting where the density of breeders and their mean number of fledglings during the previous year were high. However, we detected mismatches between preference and habitat quality for several environmental variables. The density of competitors and conspecific social information showed severe mismatches, as their relationships to preference and breeding success went in opposite direction under certain circumstances. Spring food availability and agricultural landscape context, while related to preferences, were not related to breeding success. Overall, our study emphasizes the complexity of habitat selection behavior and provides evidence that multiple mechanisms may potentially lead to an ecological trap in farmlands. </p>
Nonideal nest box selection by tree swallows breeding in farmlands: evidence for an ecological trap?
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Data from: Reproductive effort and future parental competitive ability: a nest box removal experiment
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Data from: Nest-box temperature affects clutch size, incubation initiation, and nestling health in great tits
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Data from: Smart nest box: a tool and methodology for monitoring of cavity-dwelling animals
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Data from: Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia
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Enhancing ecosystem services in apple orchards: Nest boxes increase pest control by insectivorous birds
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Determinants of nest box local recruitment and natal dispersal in a declining bird population
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Data from: Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.
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Fig. 2 in Dipteran Assemblages In Red-Footed Falcon (Falco Vespertinus) Nest Boxes
Fig. 2. Phenology of emergence of Carnus hemapterus imagoes from three years old accumulated nest material (collected in 2009), grouped by the last breeding bird species (n =
Current nest box designs may not be optimal for the larger forest dormice; pre-hibernation increase in body mass might lead to sampling bias in ecological data
<p>Biologists commonly use nest boxes to study small arboreal mammals, including forest dormouse (Dryomys nitedula). Hibernating dormouse species often experience pronounced seasonal variations in body mass, which might lead to sampling biases if it is not taken into account when designing nest boxes. In our study of forest dormouse, we noticed that the entrance hole of nest boxes had been gnawed on. We hypothesized that this behavior was exhibited by individual dormice who had higher body mass and, therefore, were unable to pass through the entrance holes. To test our hypothesis, we categorized individual dormice present inside nest boxes based on their body mass; then compared the seasonal body mass dynamics with the timing of the gnawing behavior. We also compared nest box occupancy by forest dormouse before and after the gnawing behavior. Interestingly, we found that the gnawing behavior was displayed exclusively when part of the dormouse population increased considerably in body mass, which supports our hypothesis. Additionally, nest box occupancy decreased significantly from 20% before to 4.6% after the gnawing behavior. We suggest that researchers use nest boxes with entrance holes larger than 4 cm in future studies of forest dormouse to prevent the possible exclusion of the conspecifics that have higher body mass before hibernation. This type of sampling bias can probably happen in studies of other species, such as fat dormouse, that similarly show pronounced seasonal variations in body mass. We recommend that biologists consider the seasonal body mass dynamics of the target species when designing nest boxes to minimize bias in ecological data and improve management actions.</p>
Data from: Integrated population model reveals that Kestrels breeding in nest boxes operate as a source population
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Current nest box designs may not be optimal for the larger forest dormice; pre-hibernation increase in body mass might lead to sampling bias in ecological data
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Data from: Noise affects nest box choice of 2 competing songbird species, but not their reproduction
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.