Functional Importance of Plumage Badges as Intraspecific Signals in White-Crowned Sparrows (zonotrichia leucophrys oriantha)

Status badges, such as bird plumage colors, are important parts of animal communication; they mediate intra- as well as intersexual interactions. Reliability of avian plumage badges is thought to be maintained by selective pressures, including social punishment. Costs, benefits, and resultant fitness tradeoffs are thought to maintain reliable status badges as evolutionarily stable signals. We tested this hypothesis during two breeding seasons (summers 2008-2009) in a population of Mountain White-crowned Sparrows (Zonotrichia leucophrys oriantha; MWCS) in Colorado (USA). Both sexes of this species possess a black and white striped crown that mediates interactions between juvenile and adult birds. Crown whiteness, expressed as the percentage of the crown that consists of white feathers, varies widely across individual sparrows. To test whether the reliability (the consistent transfer of information relating signal design and content) of crown whiteness in males is maintained by social punishment, we examined cost and benefits associated with experimentally manipulated phenotypes. We predicted status badge related tradeoffs to sender condition and social interactions. We conducted a series of territory intrusions / call playbacks using male sparrow decoys with manipulated crowns to measure social punishment costs. Resident MWCS males received two simulated territorial intrusions by the same mounted decoy (once with a ‘white-enhanced’ and once with a ‘white-reduced’ crown treatment; these were presented in random order on different days). Males responded with significantly increased aggression when presented with white-enhanced decoys. In a parallel experiment we tested the prediction that crown whiteness is (1.) associated with sender condition and variation in levels of corticosterone and (2.) under sexual selection. That is, we predicted that males with whiter crowns would gain reproductive benefits (measured as number of fledglings). In these experiments we experimentally enlarged or reduced the proportion of whiteness in males’ crown feathers. Crown manipulations had no significant effect on baseline, nor on post-stress series corticosterone levels. While there was a trend for more offspring in males with white-enhanced crowns, this relationship was not ii significant due to small sample sizes of recovered nests. Our data provide support for the social punishment hypothesis, yet show no significant relationship between stress response and crown characteristics. Social costs are therefore at least partially responsible for maintaining the reliability of crown whiteness as a status badge in male MWCS.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/77948/1/ZL_Thesis_SNRE.pd

Associations between Toxoplasma gondii infection and steroid hormone levels in spotted hyenas

Toxoplasma gondii is a common parasite that infects warm-blooded animals and influences host physiology. T. gondii is known to target the host\u27s central nervous system, affecting circulating levels of steroid hormones, fear-related behaviors, and health, although these effects appear to vary among host taxa. Here, we investigated the relationship between T. gondii infection and levels of plasma testosterone and cortisol within a wild population of spotted hyenas (Crocuta crocuta, n = 109). In our analyses, we accounted for age and sex via stratified regression analyses. We detected a negative association between circulating plasma testosterone and T. gondii infection among female cubs and subadults as well as adult male hyenas. We found no associations between T. gondii infection and cortisol in any age class or sex group of hyenas. Our work adds to a growing body of literature by characterizing the relationship between T. gondii infection and physiology in a novel host in its natural habitat. In a broader context, our findings indicate that responses to infection vary with characteristics of the host and point to a clear need for additional studies and priorities for future work that include diverse taxa and ecological settings

Identification of woodland vernal pools with seasonal change PALSAR data for habitat conservation

Woodland vernal pools are important, small, cryptic, ephemeral wetland ecosystems that are vulnerable to a changing climate and anthropogenic influences. To conserve woodland vernal pools for the state of Michigan USA, vernal pool detection and mapping methods were sought that would be efficient, cost-effective, repeatable and accurate. Satellite-based L-band radar data from the high (10 m) resolution Japanese ALOS PALSAR sensor were evaluated for suitability in vernal pool detection beneath forest canopies. In a two phase study, potential vernal pool (PVP) detection was first assessed with unsupervised PALSAR (LHH) two season change detection (spring when flooded—summer when dry) and validated with 268, 1 ha field-sampled test cells. This resulted in low false negatives (14%–22%), overall map accuracy of 48% to 62% and high commission error (66%). These results make this blind two-season PALSAR approach for cryptic PVP detection of use for locating areas of high vernal pool likelihood. In a second phase of the research, PALSAR was integrated with 10 m USGS DEM derivatives in a machine learning classifier, which greatly improved overall PVP map accuracies (91% to 93%). This supervised approach with PALSAR was found to produce better mapping results than using LiDAR intensity or C-band SAR data in a fusion with the USGS DEM-derivatives

Mapping Kenyan grassland heights across large spatial scales with combined optical and radar satellite imagery

Grassland monitoring can be challenging because it is time-consuming and expensive to measure grass condition at large spatial scales. Remote sensing offers a time- and cost-effective method for mapping and monitoring grassland condition at both large spatial extents and fine temporal resolutions. Combinations of remotely sensed optical and radar imagery are particularly promising because together they can measure differences in moisture, structure, and reflectance among land cover types. We combined multi-date radar (PALSAR-2 and Sentinel-1) and optical (Sentinel-2) imagery with field data and visual interpretation of aerial imagery to classify land cover in the Masai Mara National Reserve, Kenya using machine learning (Random Forests). This study area comprises a diverse array of land cover types and changes over time due to seasonal changes in precipitation, seasonal movements of large herds of resident and migratory ungulates, fires, and livestock grazing. We classified twelve land cover types with user’s and producer’s accuracies ranging from 66%–100% and an overall accuracy of 86%. These methods were able to distinguish among short, medium, and tall grass cover at user’s accuracies of 83%, 82%, and 85%, respectively. By yielding a highly accurate, fine-resolution map that distinguishes among grasses of different heights, this work not only outlines a viable method for future grassland mapping efforts but also will help inform local management decisions and research in the Masai Mara National Reserve

Early life social and ecological determinants of global DNA methylation in wild spotted hyenas

Environmental factors early in life can have lasting influence on the development and phenotypes of animals, but the underlying molecular modifications remain poorly understood. We examined cross‐sectional associations among early life socioecological factors and global DNA methylation in 293 wild spotted hyenas (Crocuta crocuta) in the Masai Mara National Reserve, Kenya, grouped according to three age classes (cub, subadult and adult). Explanatory variables of interest included annual maternal rank based on outcomes of dyadic agonistic interactions, litter size, wild ungulate prey density and anthropogenic disturbance in the year each hyena was born based on counts of illegal livestock in the Reserve. The dependent variable of interest was global DNA methylation, assessed via the LUminometric Methylation Assay, which provides a percentage methylation value calculated at CCGG sites across the genome. Among cubs, we observed approximately 2.75% higher CCGG methylation in offspring born to high‐ than low‐ranking mothers. Among cubs and subadults, higher anthropogenic disturbance corresponded with greater %CCGG methylation. In both cubs and adults, we found an inverse association between prey density measured before a hyena was 3 months old and %CCGG methylation. Our results suggest that maternal rank, anthropogenic disturbance and prey availability early in life are associated with later life global DNA methylation. Future studies are required to understand the extent to which these DNA methylation patterns relate to adult phenotypes and fitness outcomes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151897/1/mec15174_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151897/2/mec15174.pd

Development of a bi-national Great Lakes coastal wetland and land use map using three-season PALSAR and landsat imagery

Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use) for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC) baseline data at moderate spatial resolution (20–30 m), but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha, Phragmites, Schoenoplectus) and differentiate peatlands (fens and bogs) from other wetland types. The overall accuracy for the coastal Great Lakes map of all five lake basins was 94%, with a range of 86% to 96% by individual lake basin (Huron, Ontario, Michigan, Erie and Superior)

Associations between Toxoplasma gondii infection and steroid hormone levels in spotted hyenas

Toxoplasma gondii is a common parasite that infects warm-blooded animals and influences host physiology. T. gondii is known to target the host's central nervous system, affecting circulating levels of steroid hormones, fear-related behaviors, and health, although these effects appear to vary among host taxa. Here, we investigated the relationship between T. gondii infection and levels of plasma testosterone and cortisol within a wild population of spotted hyenas (Crocuta crocuta, n = 109). In our analyses, we accounted for age and sex via stratified regression analyses. We detected a negative association between circulating plasma testosterone and T. gondii infection among female cubs and subadults as well as adult male hyenas. We found no associations between T. gondii infection and cortisol in any age class or sex group of hyenas. Our work adds to a growing body of literature by characterizing the relationship between T. gondii infection and physiology in a novel host in its natural habitat. In a broader context, our findings indicate that responses to infection vary with characteristics of the host and point to a clear need for additional studies and priorities for future work that include diverse taxa and ecological settings.publishe

p73α1, an Isoform of the p73 Tumor Suppressor, Modulates Lipid Metabolism and Cancer Cell Growth via Stearoyl-CoA Desaturase-1.

Altered lipid metabolism is a hallmark of cancer. p73, a p53 family member, regulates cellular processes and is expressed as multiple isoforms. However, the role of p73 in regulating lipid metabolism is not well-characterized. Previously, we found that loss of p73 exon 12 (E12) leads to an isoform switch from p73α to p73α1, the latter of which has strong tumor suppressive activity. In this study, comprehensive untargeted metabolomics was performed to determine whether p73α1 alters lipid metabolism in non-small cell lung carcinoma cells. RNA-seq and molecular biology approaches were combined to identify lipid metabolism genes altered upon loss of E12 and identify a direct target of p73α1. We found that loss of E12 leads to decreased levels of phosphatidylcholines, and this was due to decreased expression of genes involved in phosphatidylcholine synthesis. Additionally, we found that E12-knockout cells had increased levels of phosphatidylcholines containing saturated fatty acids (FAs) and decreased levels of phosphatidylcholines containing monounsaturated fatty acids (MUFAs). We then found that p73α1 inhibits cancer cell viability through direct transcriptional suppression of Stearoyl-CoA Desaturase-1 (SCD1), which converts saturated FAs to MUFAs. Finally, we showed that p73α1-mediated suppression of SCD1 leads to increased ratios of saturated FAs to MUFAs

Identification of Woodland Vernal Pools with Seasonal Change PALSAR Data for Habitat Conservation

Woodland vernal pools are important, small, cryptic, ephemeral wetland ecosystems that are vulnerable to a changing climate and anthropogenic influences. To conserve woodland vernal pools for the state of Michigan USA, vernal pool detection and mapping methods were sought that would be efficient, cost-effective, repeatable and accurate. Satellite-based L-band radar data from the high (10 m) resolution Japanese ALOS PALSAR sensor were evaluated for suitability in vernal pool detection beneath forest canopies. In a two phase study, potential vernal pool (PVP) detection was first assessed with unsupervised PALSAR (LHH) two season change detection (spring when flooded—summer when dry) and validated with 268, 1 ha field-sampled test cells. This resulted in low false negatives (14%–22%), overall map accuracy of 48% to 62% and high commission error (66%). These results make this blind two-season PALSAR approach for cryptic PVP detection of use for locating areas of high vernal pool likelihood. In a second phase of the research, PALSAR was integrated with 10 m USGS DEM derivatives in a machine learning classifier, which greatly improved overall PVP map accuracies (91% to 93%). This supervised approach with PALSAR was found to produce better mapping results than using LiDAR intensity or C-band SAR data in a fusion with the USGS DEM-derivatives