Plants have evolved to represent a diversity of species, characterized by functional traits that dictate their performance in response to changing environments. One such leaf functional trait that relates to plant ecological strategy and is strongly correlated with photosynthetic rates, is minor leaf vein density (LVD). Our study will assess how ecological strategies within plant communities shifted in response to Earth’s most recent major global warming event, the Middle Miocene Climatic Optimum (MMCO) from 17-14 Ma, where rises in both global temperature and atmospheric CO₂ levels occurred. We hypothesize that global warming led to longer growing seasons and ecological strategies that prioritized persistence over productivity became dominant, and more favorable climates increased the diversity of ecological strategies present within the community. We will be traveling to various museums to photograph fossils that have all their minor veins preserved, collected from sites representing before, during, and after the MMCO in the Pacific Northwest region. Our goal will be to include several species per site, and photograph their fossil leaves under a stereo microscope. From there we will measure LVD using the program ImageJ using standard protocols. Once we have that data, we will calculate measures of the community-level distribution of this trait (mean, variance, kurtosis), and then compare those values between sites, and thus across the MMCO. In support of our hypothesis, we predict to see a lower mean and kurtosis, and higher variance of LVD values in MMCO plant communities, relative to those existing before or after the warming event. Overall this research is important to not only understanding how plant communities responded in ancient times to rising temperature but how plant communities could potentially respond to the rising temperatures in the future.

Steller's Jays (Cyanocitta stelleri) emit multiple call types. Variation within and between call types could indicate a sophisticated method of vocal communication. Variation could also indicate different selective geographic pressures or learned regional dialects. It is currently unknown whether Steller's Jays have geographic variation in their calls. In this study, I investigated whether the 'wah call' of Steller's Jays varies between and within geographic regions. I analyzed recordings of 'wah calls' from two geographic regions spanning from Canada to Mexico. I quantified the number of syllables, the syllable duration, the call duration, and the average silence between syllables. 'Wah calls' are highly variable, with durations from 0.41 to 10.00 seconds, one to eleven syllables with durations from 0.26 to 0.71 seconds, and gap (silence between syllable) durations from <.01 seconds to 0.67 seconds. Preliminary analysis shows no significant differences in these acoustic variables between Steller's Jays in the Marine West Coast Forest and Mediterranean California regions. I am currently increasing my sample size, beginning analysis of additional Steller's Jay call types, and expanding data analysis to five geographic regions. The presence of regional variation could indicate that Steller's Jays learn their different vocalizations. Learning vocalizations could be a sign of complex communication within Steller's Jays. 

Disease is a major threat to tropical coral reefs which can be made worse by local stressors like overfishing and nutrient pollution and global stressors such as climate change. However, not all coral species suffer disease at equal rates. It has been hypothesized that these differences may be due to differences in coral innate immune strategies, biogeography, or the symbiotic associations between corals and protective microorganisms (the ‘coral probiotic hypothesis’). This project seeks to test if there are properties of coral microbiomes that correlate with differences in disease susceptibility. We’ve tested this using 1272 coral 16S rRNA gene amplicon libraries and three long-term coral disease datasets. Establishing a general picture of coral disease susceptibility requires integrating data from multiple regional disease monitoring projects. This is challenging because these projects use different methodologies, monitor different species and occasionally use different terminology for the same diseases. I’ve merged three long-term coral disease datasets: the Florida Reef Resilience Project, the Hawai’i Coral Disease database, and an extensive unpublished dataset from Dr. Joleah Lamb. This combined dataset consists of 141 different coral taxa and 31 unique categories of diseases and stressors. This combined disease resource allows for both investigation of the evolutionary history of coral disease susceptibility and comparison against our microbiome data. Our results so far identify coral groups especially susceptible to certain diseases (e.g., Acropora and Skeletal Eroding Band). So far, phylomorphospace analysis indicates an intriguing potential association between microbiome complexity and disease susceptibility. Preliminary results also indicate a strong correlation between microbiome richness and skeletal eroding band disease over more than 450 million years of coral evolution. This new evidence, if confirmed would support the coral probiotic hypothesis.

Songbirds can learn different song dialects depending on their geographical location. Taxonomically, the American Crow (Corvus brachyrhynchos) is a songbird, but lacks a traditional ‘song’. Despite this, research suggests that crows do possess brain regions necessary for song learning and production. Unlike their songbird relatives, it is not understood whether American Crow populations learn regional call dialects. Using recorded crow calls from the online database, Xeno-Canto, I analyzed the acoustic properties of over 150 audio files across nine ecoregions of North America. Using the bioacoustics program Raven Pro 1.6, I am currently quantifying the lowest frequency, syllable number, syllable duration, and call duration for each call. Geographical differences in call structure, if detected, may indicate that crows learn regional dialects, or the differences may be the result of different selection pressures in each region.

As scientists collect ever larger volumes of data, methods to deal with these data have evolved as well. One of the fields that has thus emerged is the field of network science. Network science has many applications in biological fields as it allows scientists to connect variables of any type in a quantitative way. This versatility makes network science ideal for studies on comorbidity, or the consistent cooccurrence of various diseases in individuals. By analyzing comorbidities, we gain greater insight into interactions between diseases and systems of the body. This helps us understand how potential risk factors such as age, sex, and genotype affect various disease risks as well as the risk of comorbidity. We applied these methods to data on age of diagnosis for over 300 diseases collected from more than 28,000 owner reported surveys through the Dog Aging Project. We constructed comorbidity networks from these data and analyzed these networks using quantitative network statistics which allowed us to compare nodes both in and between networks. We first constructed undirected networks with the nodes representing various diseases to establish and identify pairs of diseases with significantly higher rates of cooccurrence than expected by chance. Using this network, we assigned directions to edges based on temporal data on the relative ages of diagnoses, which allowed us to identify which diseases are precursors to others. We observed how these networks changed through stratifications based on age, sex, and size to identify disease progression through age. In doing so, we hope that we can identify how age affects comorbidity in dogs, which can help researchers identify and develop therapies for lengthening dog lifespans. This knowledge will also provide insight into the mechanisms behind certain disease connections that were previously unknown.

Plants face an enormous number of environmental stressors, including agriculturally important pests and pathogens. To defend against these biotic stressors, plants rely on pattern recognition receptors (PRRs), which are cell surface proteins that recognize conserved, non-self molecules indicative of attack or infection and initiate pattern triggered immunity (PTI) signaling pathways to mount defense responses. Recently, the first PRR involved in immunity against herbivorous pests was discovered in legumes. INR, a leucine-rich repeat receptor-like protein, mediates defense responses to inceptin, a peptide found in the oral secretions of caterpillars. To better understand the structural aspects of INR that are necessary for its ability to bind to inceptin and associate with downstream signaling components, I am developing a reporter system to screen INR variants to identify mutations that affect its function as a PRR. I have generated several different reporter constructs driving luciferase expression with promoter regions of genes found to be upregulated by inceptin when INR is transgenically expressed in the model organism Nicotiana benthamiana. These constructs vary in strength of expression but only one promoter region shows inducibility by inceptin. However, several constructs also show responses to a different immune elicitor, a peptide fragment of bacterial flagellin, which suggests that these constructs could be used as markers of PTI in plants more broadly. Robust reporters of PTI would not only be useful in understanding the structure and function of INR but may also enable further studies that will inform engineering practices to improve crop resistance to pests and pathogens.