Landscape and Mechanistic Approaches to Describing Milkweed Habitat and Drought Tolerance and the Implications for Western Monarch Butterflies

It is vital that we understand the distribution and resilience of critical pollinator floral resources in the face of anthropogenic stressors. We utilized an unmanned aerial vehicle (UAV) remote sensing method along with the machine learning model you only look once (YOLO) to map floral habitat. We focused on detecting two milkweed species, narrowleaf milkweed (Asclepias fascicularis), and showy milkweed (Asclepias speciosa). These species are host plants for the declining monarch butterfly (Danaus plexippus). Utilizing our model, we quantified milkweed cover and isolated relationships between milkweed area and monarch presence. Additionally, we theorized that maternal effects could play an important role in milkweed's ability to adapt to drought stress. To test this, we grew narrowleaf milkweed from a lineage previously exposed to varying grandmaternal climatic conditions and maternal drought experimentation. We used statistical modeling to explore potential maternal and grandmaternal effects on our greenhouse generations physiological response to drought.

Level thesis:degree_level

Master's Degree

Year dc:date.issued

2025

Author dc:creator

• Zamboni, Gino Anthony

Advisor dc:contributor.advisor

• Pringle, Elizabeth G.

Committee members dc:contributor.committeemember

• Dilts, Thomas
• Weisberg, Peter
• Forister, Matthew

• Drones
• Milkweed
• Monarchs
• UAV

Language dc:language.iso

en_US, English

Repository record dc:identifier.uri

https://scholarwolf.unr.edu/handle/11714/11474

OAI identifier oai:identifier

oai:scholarwolf.unr.edu:11714/11474