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Ecological Niche models of plague in Uzbekistan : extracting biological information from multiple-species models vs. species specific models to understand hosts and vectors.

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  1. Ecological Niche models of plague in Uzbekistan:extracting biological information from multiple-species models vs. species specific models to understand hosts and vectors Jason K. Blackburn, PhD, Emerging Pathogens Institute & Department of Geography, University of Florida, Gainesville, FL USA ShaloRakimova, PhD, AminjanNematov, PhD Center for GIS, Center for Prophylaxis and Quarantine for Most Hazardous Infections, Tashkent, Uzbekistan Christopher Shane Foster Department of Geography, California State University, Fullerton, CA USA

  2. Acknowledgements • This Cooperative Biological Research project was funded by the United States Defense Threat Reduction Agency (DTRA) as part of the Biological Threat Reduction Program in Uzbekistan

  3. Status of Plague in Uzbekistan • Sporadic human cases of plague were documented in 1979 and 1999 in Uzbekistan and plague remains a threat to public health • CPQMHI maintains an active surveillance effort for natural presence of the disease in rodent and flea populations throughout the known regions of historical cases • Zoological surveillance remains a priority for plague, as both human and enzootic cases appear to be related to host/reservoir populations

  4. Ecological Niche Modeling • Ecological niche modeling (ENM) predicts the potential geographic distribution of species’ through the analysis of non-random relationships between environmental variables (e.g. – temperature, precipitation, elevation, etc) and laboratory positive sample locations • The idea is to model the distribution of the species in areas where surveillance may be lacking • This study employed plague locations and species-specific occurrence data from field studies and several environmental variables to model the ecological niche for Y. pestisin Uzbekistan

  5. Realized Niche Ecological Niche Theory (Grinnell 1917, Hutchinson 1957) ENVIRONMENTAL PARAMETER 2 (e.g. soil pH) Fundamental Niche ENVIRONMENTAL PARAMETER 1 (e.g. vegetation)

  6. GARP: Genetic Algorithm for Rule-Set Prediction Stockwelland Peters (1999) • This study employed the GARP modeling system to predict the niche for plague • GARP is an iterative modeling system that builds rules that relate points to ecological variables • Iterative modeling approach where rules define the distribution as PRESENT or ABSENT • Once the rules are developed, they are mapped onto the geography to map the potential distribution • GARP is stochastic (like many approaches) and multi-model development and agreement are used to determine accuracy/relevance

  7. MODEL VECTOR SPECIES OVERLAP MODEL HOST SPECIES MODEL HOSTS AND VECTORS AND IDENTIFY OVERLAP Peterson et al. 2002 (Chagas)

  8. MODEL HUMAN CASES OR MODEL ENTIRE HOST RANGE Peterson et al. 2004 (Ebola) Levine et al. 2007 (Monkey Pox) Williams et al. 2007 (Avian Influenza)

  9. MODEL HUMAN CASES OF PLAGUE: Explore “Niche Space” Neerinckx et al. (2008)

  10. SPECIES OCCURRENCE DATA: PLAGUE CASES FROM 2000 - 2007 2 1 Fleas Xenopsyllafleas Plague Rhombomysopimus (w or w/o plague) 4 3 Rodents (with or w/o plague) Meriones spp. (2 separate models)

  11. Environmental Coverages Mean LST Mean NDVI

  12. 2x2 Niche Space Predicted geography from niche models was plotted in 2x2 variable space to illustrate differences in realized niche space for each model developed in this study

  13. Predicted distributions of “plague”: Using all Y. pestispositives

  14. Predicted distributions of plague: Fleas

  15. Predicted distributions of plague: Plague vs Fleas

  16. Predicted distributions of plague: Rodents Model (all rodent species)

  17. Predicted distributions of plague: Rhombomysopimus

  18. Predicted distributions of plague: M. erythrourus(taxonomic review?)

  19. Predicted distributions of plague: M. meridianus

  20. Predicted distributions of plague: WHICH NICHE?

  21. Predicted distributions of plague: WHICH NICHE?

  22. What do the models mean? • Mixed mammal models are more reflective of the larger sample size • While successfully predicting test data, these models confound ecological signatures and are therefore not hugely informative • Flea models predicted the greatest geographic area, again confounding the ecological signature (niche definition) of any given host species • The “plague model” under predicted the R. opimusmodel, suggesting the “disease distribution” is a subset of host distributions • Overall, mixed species models are difficult to interpret and can either over or under predict any given component of the transmission cycle. While the geography may be captured, it may not be biologically meaningful when compared to specific models

  23. Summary • GARP can be interpreted as a “fundamental niche” modeling tool – but this relies on a Grinnellian definition of a single niche per species; modeling multi-species data sets conflates this definition and confuses the ecological space occupied by any given species of the enzootic transmission cycle of plague in Uzbekistan • Extrapolating potential geography to niche space (here 2x2 plots) illustrates the ecological space occupied by any individual species within the data set and compares each to the “plague” definition • Evaluating each species individually both adheres to the traditional ecological niche theory and provides an opportunity to evaluate possible differences in regional ecologies that comprise the “plague foci” of Uzbekistan

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