Inferring host specificity and network formation through agent-based models: tick-mammal interactions in Borneo

Area of Science:

• Ecology
• Parasitology
• Tropical Biology

Background:

• Host-parasite associations in tropical forests remain poorly understood.
• Existing studies often provide only snapshots of complex interactions.
• There is a need to infer prevalence and host specificity patterns accurately.

Purpose of the Study:

• To investigate tick-small mammal interactions in Bornean forests.
• To develop a robust method for inferring interaction probabilities and host specificity.
• To account for sampling bias and environmental variability in ecological networks.

Main Methods:

• Utilized a multi-level Bayesian model with environmental covariates.
• Incorporated model averaging for estimating interactions of rare species.
• Analyzed individual-level data from 1,444 small mammals and 237 infested individuals.
• Recorded 13 tick species across five genera and 37 host species.

Main Results:

• Host species identity explained approximately 75% of infestation probability variation.
• Local host abundance explained an additional 8-10% of variation.
• Infestation probabilities varied more across host species than tick species.
• All tick species exhibited low host specificity, likely infesting 34-37 host species if sampled exhaustively.

Conclusions:

• Host traits and site attributes had minimal explanatory power for infestation.
• Observed network attributes can be misleading without accounting for sampling bias.
• Multi-level modeling approaches are crucial for understanding ecological network dynamics and mechanisms.