1/7/2024 0 Comments Songbird speciesThat is, these birds enjoy the omnivore’s advantage of waiting for just the right nights for flight. La Sorte’s research, using eBird data and weather radar images of massive flocks of birds, provided the first documented evidence that these insectivores-turned-omnivores migrate on the omnivore’s later schedule, with a migration window that extends into November. Insectivores-that-become-omnivores: Then there’s a third group of species-including Hermit Thrush, Eastern Phoebe, Yellow-rumped Warbler, and Red-eyed Vireo-that possess the physiological adaptation in their digestive systems to switch from a diet of insects to fruits and seeds in fall. For omnivorous birds, the fall migration window can stretch well into November. So they have the luxury of waiting for optimal travel conditions (fair skies and a favorable tailwind), which can make for a less dangerous migration than insectivorous birds often encounter. Omnivores: Birds that eat a balanced diet of insects, fruits, and seeds-such as sparrows-aren’t forced out of their northern breeding grounds because the food supply of bugs runs out. But when insect abundance fades in late summer, these insectivorous birds leave on migration-typically from late August to mid-September. After all, eating insects was an evolutionary reason their ancestors started flying long distances from the tropics to cash in on the protein pulse of the insect hatch in North America. And it makes sense that diet drives their population movements. Insectivores: Most species of warblers, vireos, and flycatchers primarily eat insects. Put simply, what some birds eat seems to determine when they fly south for the winter. New research published by Cornell Lab scientist Frank La Sorte delves into diet as a factor in migration timing. Studies have shown decreasing daylight to be a cue for many species. Scientists still don’t know all the drivers of fall migration. Others thought migratory birds flew all the way to the moon! In centuries past, people thought songbirds hitched a ride on the backs of storks. This variability was associated with vertical structure alone and shows how LiDAR can provide a source of complementary predictive data that can be incorporated in models of wildlife habitat associations across broad geographical extents.Fall bird migration has fascinated humans for ages. LiDAR forest structure metrics explained between 15 and 20% of the variability in richness within deciduous forest songbird communities. Forest interior specialists responded positively to a tall canopy, developed midstory, and a higher proportion of vegetation returns (R 2 = 0.195, p < 0.001). Richness of edge-preferring species was greater where there were fewer vegetation returns but higher density in the understory (R 2 = 0.153, p < 0.005). ![]() Species that forage on the ground responded to mean canopy height and the height of the lower canopy (R 2 = 0.149, p < 0.005) while aerial foragers had higher richness where the canopy was tall and dense and the midstory more sparse (R 2 = 0.216, p < 0.001). Richness of species that nest in the midstory was best explained by canopy height variables (R 2 = 0.197, p < 0.001). Songbird species richness was correlated most strongly with LiDAR variables related to canopy and midstory height and midstory density (R 2 = 0.204, p < 0.001). ![]() ![]() A suite of 35 LiDAR variables were used to model bird species richness using best-subsets regression and we used hierarchical partitioning analysis to quantify the explanatory power of each variable in the multivariate models. We conducted point counts to determine total forest songbird richness and the richness of foraging, nesting, and forest edge-related habitat guilds. In deciduous forests of southern Wisconsin, USA, we used discrete-return airborne LiDAR to derive forest structure metrics related to the height and density of vegetation returns, as well as composite variables that captured major forest structural elements. Our goal was to model the richness of forest songbirds using forest structure information obtained from LiDAR data. Airborne LiDAR, with its combination of relatively broad coverage and fine resolution provides existing new opportunities to map vegetation structure and hence avian habitat. Vegetation structure information is particularly important for avian habitat models and has largely been unavailable for large areas at the desired resolution. Conservation of biodiversity requires information at many spatial scales in order to detect and preserve habitat for many species, often simultaneously.
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