| Summary: | This doctoral thesis investigates the complex interplay between ecological diversity and research methods in the context of species interactions. By utilising two distinct ecological systems as case studies, I delve into the diverse approaches and techniques employed for analysing and collecting data on species interactions. The first system focuses on the dynamics between purinina/Tasmanian devils (Sarcophilus harrisii) and devil facial tumour disease (DFTD), exploring the utility of integral projection models (IPMs) in understanding interactions between host and pathogen. This study sheds light on the underlying demographic dynamics that have allowed purinina to coexist with DFTD and the broader ongoing implications for purinina populations. It additionally enhances our understanding of how research methods, specifically IPMs, can contribute to unravelling the complexities of species interactions in the face of disease outbreaks. The second system focuses on a wild small mammal community, investigating how different data collection techniques, namely count data and fine-scale RFID (Radio-Frequency Identification) logger data offer insights into different ecological questions. Comparing the outcomes of count data and RFID logger data analysis, the research highlights the strengths and limitations of each method, shedding light on their respective applications in ecological research. It demonstrates how the fine-scale data obtained from RFID loggers enable researchers to investigate intricate social interactions, movement patterns, and resource utilisation in the small mammal community, complementing traditional count data analyses. Overall, this research provides a comprehensive exploration of the interdependence between conservation efforts, research methods, and species interactions. It elucidates the value of population level statistical models in understanding host-pathogen dynamics, using the case of purinina and DFTD as an illustrative example. Additionally, it demonstrates the diverse insights that can be gained by employing different data collection methods. The thesis not only advances our ecological understanding but also offers practical guidance for researchers by providing novel technology and mathematical models to their toolkit. The work presented here is diverse, but ultimately when collated contributes to answering a single question – what is the best way to understand how species interact?
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