Monday, May 18, 2009 - 3:30 PM
62

Aquatic ecology of a mycobacterial disease: Environmental drivers of pathogen-invertebrate associations at multiple spatial scales

M. Eric Benbow1, Richard W. Merritt2, Ryan K. Kimbirauskas2, Mollie D. McIntosh2, Heather R. Williamson3, Pamela L.C. Small3, Daniel Boakye4, and Charles Quaye4. (1) Department of Biology, University of Dayton, 300 College Park, Dayton, OH 45469-2320, (2) Department of Entomology, Michigan State University, East Lansing, MI 48824, (3) Department of Microbiology, University of Tennessee, Knoxville, TN 37996, (4) Parasitology Department, Noguchi Memorial Institute of Medical Research, Legon, Ghana

Research evaluating multi-scale spatial variability of aquatic pathogens and related biological communities has largely been confined to temperate regions of the world and well studied disease systems. Few have considered neglected diseases of tropical ecosystems, which often demonstrate great morbidity and negative socio-economic consequences. We employed remotely sensed land use/cover data, rapid aquatic invertebrate bioassessment techniques and molecular detection (PCR-VNTR) of a human bacterial pathogen to evaluate scale-dependent (country, region, waterbody type, and flow) pathogen-invertebrate associations from 98 waterbodies of Ghana, Africa. From a total of 73,917 individuals, total invertebrate abundance and taxa richness ranged from 53-4499 and 15-70, respectively; and communities were dominated by gathering collectors (55%) and predators (19%). Shredders were <1%. Using classification tree and multiple regression analyses, we found invertebrates were best partitioned by waterbody flow (lentic vs lotic), and that landscape (e.g., % forest and agriculture) drivers of pathogen presence and invertebrate community structure were dependent on scale and flow type. Non-metric multidimensional scaling revealed that pathogen-invertebrate associations varied substantially at all spatial scales with no evidence of a significant mechanistic relationship; thus, suggesting non-vectorborne routes of transmission. Correlations of PCA loadings with regression residuals indicated significant associations of water quality, invertebrates and pathogen distribution.


Web Page: Disease ecology, Landscape, Microbial