Ref ID : 6692
B.L. Simmons, R.K. Niles, and D.H. Wall; Distribution and abundance of alfalfa-field nematodes at various spatial scales. Applied Soil Ecology 38:211-222, 2008
Reprint
In File
Notes
Stem nematode disease of alfalfa (Medicago sativa) is an economically important issue facing agriculture in the western United States. A better understanding of the ecology of Ditylenchus dipsaci, the nematode that causes stem disease can help to improve survey techniques and management plans for this pathogen. Microhabitats (above- and below-ground), individual fields and regions (river basins) were investigated to determine the importance of scale dependency for D. dipsaci, Aphelenchoides ritzemabosi (an associated plant parasite), and other nematodes inhabiting fields of alfalfa in Colorado, United States. Nematode groups were assayed from microhabitats including aboveground plant, surface litter and soil substrates. At the regional scale of river basins, nematode communities were similar, and D. dispsaci and A. ritzemabosi were prominent members of a diverse community dominated by Panagrolaimus sp., a free-living nematode found mostly in the litter microhabitat in all three fields. At the field scale, a moisture gradient occurred in three of the four sites where the water content of the bulk soil increased with distance from the irrigation source. Certain nematode groups responded positively to this moisture gradient. This may indicate that nematodes are being relocated across the field in irrigation water or that conditions in the tail end of the field are more favorable for reproduction. At the scale of microhabitats, A. ritzemabosi functioned as a generalist by occupying more microhabitats than D. dipsaci, which functioned as a specialist in alfalfa crowns and crown soils. Bulk litter also supported both D. dipsaci and A. ritzemabosi, indicating that this microhabitat could serve as a refuge. Examining nematode distribution and abundance at various spatial scales verified that nematode ecology is scale-dependant, and this may have important implications for monitoring and management in agricultural systems.