Authors

E Morgan¹;  ¹ Biological Sciences, Queen’s University of Belfast, UK

Discussion

Parasite transmission in multi-host systems involves many moving parts, and to gather comprehensive empirical understanding of its dynamics often faces insurmountable logistical challenges. Yet, guidance is needed on consequences for conservation and agriculture, especially under climate and landscape change. Computer models can help to fill this gap, but themselves require data inputs for parameterisation, calibration and validation. Given that generalist helminth species are the most relevant at the interface, it has been expedient to borrow heavily on knowledge from livestock systems to parameterise these models and to validate them, although this can generate bias and ignore key uncertainties. These issues are explored frankly through a series of case studies that set out to identify key points of nematode cross-transmission in complex ungulate systems, in which host movement - including vertical movements of mountain ungulates and horizontal antelope migrations - and variable weather generate highly discontinuous dynamics. New technologies are improving ability to collect more precise data in situ but there is still an ongoing need to determine response norms of key parasite vital rates in natural settings and populations, and to consider indirect as well as direct impacts of climate change on parasite ecology. Ultimately, predictive models are perhaps most useful in this context to generate testable hypotheses and should therefore be constructed with realistic data sources in mind. The skills and resources needed to combine models and data effectively and iteratively towards better predictions and applications will benefit from multi-disciplinary collaboration and an absence of hubris.