Inferring host specificity and network formation through agent-based models: tick–mammal interactions in Borneo
- 640 Downloads
Patterns of host–parasite association are poorly understood in tropical forests. While we typically observe only snapshots of the diverse assemblages and interactions under variable conditions, there is a desire to make inferences about prevalence and host-specificity patterns. We studied the interaction of ticks with non-volant small mammals in forests of Borneo. We inferred the probability of species interactions from individual-level data in a multi-level Bayesian model that incorporated environmental covariates and advanced estimates for rarely observed species through model averaging. We estimated the likelihood of observing particular interaction frequencies under field conditions and a scenario of exhaustive sampling and examined the consequences for inferring host specificity. We recorded a total of 13 different tick species belonging to the five genera Amblyomma, Dermacentor, Haemaphysalis, Ixodes, and Rhipicephalus from a total of 37 different host species (Rodentia, Scandentia, Carnivora, Soricidae) on 237 out of 1,444 host individuals. Infestation probabilities revealed most variation across host species but less variation across tick species with three common rat and two tree shrew species being most heavily infested. Host species identity explained ca. 75 % of the variation in infestation probability and another 8–10 % was explained by local host abundance. Host traits and site-specific attributes had little explanatory power. Host specificity was estimated to be similarly low for all tick species, which were all likely to infest 34–37 host species if exhaustively sampled. By taking into consideration the hierarchical organization of individual interactions that may take place under variable conditions and that shape host–parasite networks, we can discern uncertainty and sampling bias from true interaction frequencies, whereas network attributes derived from observed values may lead to highly misleading results. Multi-level approaches may help to move this field towards inferential approaches for understanding mechanisms that shape the strength and dynamics in ecological networks.
KeywordsAcari Hierarchical model Biotic interaction Host specificity Multispecies model
We thank the Economic Planning Unit Malaysia for research permission and Sabah Parks and Yayasan Sabah for various kinds of support during field work. We are especially thankful to all staff and people at the different field sites for their warm hospitality. In particular, we thank Alim Biun, Fred Tuh Yit Yu, Jickson Sankin, Awang Matamin, Suati Selimon, Aloysius Mail and Jadda Suhaimi. We thank Brigitte Fiala and K. Eduard Linsenmair for academic and logistic support. We appreciate the mentoring and friendship of the late Elisabeth K. V. Kalko; she sadly passed away, to our disbelief, while this study was being performed. Field work was supported by the German Academic Exchange Service (DAAD).
- Anderson RM, May RM (1991) Infectious diseases of humans: dynamics and control. Oxford University Press, OxfordGoogle Scholar
- Geevarghese G, Mishra AC (2011) Haemaphysalis ticks of India. Elsevier, LondonGoogle Scholar
- Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New YorkGoogle Scholar
- Hoogstraal H (1964) Studies of Southeast Asian Haemaphysalis ticks (Ixodidea, Ixodidae). Redescription, hosts, and distribution of H. traguli Oudemans. The larva and nymph of H. vidua W. and N. Identity of H. papuana toxopei Warburton (new combination). J Parasitol 50:765–782PubMedCrossRefGoogle Scholar
- Kohls GM (1957) Malaysian parasites. XVIII. Ticks (Ixodoidea) of Borneo and Malaya. Stud Inst Med Res Malays 28:65–94Google Scholar
- Lande R, Engen S, Sæther B-E (2003) Stochastic population dynamics in ecology and conservation. Oxford University Press, OxfordGoogle Scholar
- Robinson WS (2009) Ecological correlations and the behavior of individuals. Int J Epidemiol 38:337–341 [reprinted from (1950) Am Sociol Rev 15(3):351–357]Google Scholar
- Vázquez DP, Melian CJ, Williams NM, Blüthgen N, Krasnov BR, Poulin R (2007) Species abundance and asymmetric interaction strength in ecological networks. Oikos 116:1120–1127Google Scholar
- Wilson DE, Reeder DM (eds) (2005) Mammal species of the world. A taxonomic and geographic reference, 3rd edn. Johns Hopkins University Press, BaltimoreGoogle Scholar