Forecasting parasite sharing under climate change.

Area of Science:

• Ecology
• Climate Change Biology
• Parasitology

Background:

• Species distributions are shifting due to climate change, leading to new species interactions.
• These novel co-occurrences can facilitate the exchange of parasites between previously isolated hosts.
• Predicting new host-parasite interactions is crucial for forecasting disease emergence and guiding surveillance.

Purpose of the Study:

• To develop and validate a generalized framework for predicting novel host-parasite interactions.
• To assess the potential for cross-species parasite transmission under future climate scenarios.
• To identify regions and species at higher risk of emergent infectious diseases.

Main Methods:

• Combined niche modeling of future host distributions with parasite sharing models.
• Utilized North American ungulates as a case study for proof of concept.
• Employed cross-validation techniques to assess model accuracy.

Main Results:

• The proposed framework demonstrated high cross-validation accuracy for over 85% of modelled parasites.
• Over 34% of forecasted host-parasite associations were found to be already documented in scientific literature.
• Identified specific regions and taxa susceptible to emergent pathogens due to climate-driven host shifts.

Conclusions:

• Forecasting parasite sharing in response to climate-driven host distribution shifts is a viable approach.
• This method aids in identifying areas and species most vulnerable to novel pathogens.
• The findings support proactive disease surveillance and management strategies in a changing climate.