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<title>Biological Sciences</title>
<link>https://aurora.auburn.edu/handle/11200/44208</link>
<description/>
<pubDate>Mon, 06 Apr 2026 08:26:43 GMT</pubDate>
<dc:date>2026-04-06T08:26:43Z</dc:date>
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<title>Dataset: Captivity negatively affects production of red carotenoid pigments in Cardinalis cardinalis (Northern Cardinals)</title>
<link>https://aurora.auburn.edu/handle/11200/50762</link>
<description>Dataset: Captivity negatively affects production of red carotenoid pigments in Cardinalis cardinalis (Northern Cardinals)
Carotenoid-based coloration is a well-documented example of a condition-dependent trait, but much of the evidence supporting condition dependence of red carotenoid coloration comes from species that color their feathers primarily with 3-hydroxyechinenone, a red carotenoid produced from yellow dietary carotenoids via an unknown pathway. The condition dependence of red plumage in species that use the more common CYP2J19 and BDH1L enzymes to modify dietary yellow carotenoids into red ketocarotenoids is less well studied. We tested the hypothesis that captivity would negatively affect production of red pigments by male Cardinalis cardinalis (Northern Cardinals), a songbird with extensive red coloration produced via the CYP2J19/BDH1L pathway.  We confined a group of wild-caught male cardinals in cages during molt, using captivity as a physiological challenge, and compared them to free-living cardinals. We provided captive birds with abundant zeaxanthin and lutein, the dietary yellow pigments that cardinals enzymatically convert into the red ketocarotenoids astaxanthin and alpha-doradexanthin, to ensure that insufficient carotenoid access would not limit production of red pigments. During molt, we measured concentrations of carotenoid pigments in the plasma and growing feather follicles of both captive and free-living cardinals. Compared to free-living cardinals, captive birds had significantly lower relative concentrations of red carotenoids in both follicles and plasma. The observation that, compared to free-living cardinals, captive male cardinals showed reduced production of red carotenoids with lower quantities in feather follicles supports the hypothesis that red coloration produced via the CYP2J19/BDH1L pathway is a condition-dependent trait.
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<title>Neural correlates of suppressed spatial learning in zebra finches exposed to methylmercury DATA</title>
<link>https://aurora.auburn.edu/handle/11200/50753</link>
<description>Neural correlates of suppressed spatial learning in zebra finches exposed to methylmercury DATA
This dataset includes the neural total population, density, thresholding percentages (area covered) for neural data for birds that went through spatial memory trials. Bird information is also included.
</description>
<guid isPermaLink="false">https://aurora.auburn.edu/handle/11200/50753</guid>
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<title>Data: Egg incubation temperature affects habitat use of adult lizards in a heterogeneous environment</title>
<link>https://aurora.auburn.edu/handle/11200/50752</link>
<description>Data: Egg incubation temperature affects habitat use of adult lizards in a heterogeneous environment
Do environmental conditions during embryonic development influence the ways in which an animal selects among alternative habitat types later in life? We studied an Australian lizard (Amphibolurus muricatus) to test the hypothesis that developmental temperatures affect adult habitat choice, and to explore links between habitat use and fitness. To address these aims, we incubated eggs under a range of ecologically relevant temperatures and quantified the effects of incubation regimes on habitat choice by adult lizards (~2 years after hatching) within field enclosures that contained low- and high-quality habitat patches. During the reproductive season, we quantified each lizard’s habitat choice, movements, and perch heights, as well as two fitness correlates (growth rate, reproductive success). Cool incubation temperatures resulted in adults that moved more frequently and perched lower than did those from warmer incubation. Moreover, individuals that had developed at an intermediate incubation temperature used high-quality habitat more frequently than did those from either cool or warm incubation treatments. Lizard behavior also shifted seasonally, with the animals increasingly using high-quality habitats and perching higher but moving less as the reproductive season progressed. Despite these long-term effects of developmental temperature on adult behavior, the only variable strongly associated with growth and reproductive success was body size rather than behavior. These results highlight the ability of embryonic environments to influence adult behaviors in ways that modify the distribution of organisms across heterogeneous landscapes.
</description>
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<title>High-resolution fluorescence images of Drosophila ovaries</title>
<link>https://aurora.auburn.edu/handle/11200/50750</link>
<description>High-resolution fluorescence images of Drosophila ovaries
To compare the differences of caloric density on oogenesis and DNA degradation, adult females were collected at three time points: 0, 2, and 5 days post-eclosion. A total of 81 flies were dissected in the morning to ensure consistency, with no more than 20 minutes between the start of dissection and fixation to prevent tissue degradation. Ovaries were processed following Meehan et al. (2015), staining nuclei with DAPI (Vectashield with DAPI) and detecting DNA degradation with Fluorescein-12-dUTP via the DeadEnd™ Fluorometric TUNEL System (Promega). High-resolution fluorescence images were captured using a BZ-X microscope. Sample sizes of successfully stained ovaries used in the analysis per genetic background, age, and diet can be found in Supplementary Table 2. Oocyte developmental stages were classified according to Jia et al (2016), into five groups: germarium, stages 270 1 – 7, stages 8 – 10, stage 11, and stages 12-14. Images were standardized for size and brightness, converted to black and white using scikit-image v0.22.0 (Walt et al. 2014) and Napari (Chiu et al. 2022) in Jupyter (Kluyver et al. 2016), and annotated via a trained AI model in APEER (Dang et al. 2021). Model training included manual annotation of at least 50 objects per class (developmental stages and background) in a randomly selected images, with iterative updates until accuracy exceeded 95%. The processed image files and the APEER model have been provided in this data repository.
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