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Spatial Variability in a Successional Plant Community: Patterns of Nitrogen Availability

Robertson, G. Philip, Hutson, Michael A., Evans, Francis C., Tiedje, James M.
Ecology 1988 v.69 no.5 pp. 1517-1524
acetylene, algorithms, ammonium nitrate, autocorrelation, community structure, denitrification, geostatistics, kriging, mineralization, nitrification, nitrogen, nitrous oxide, plant communities, population dynamics, soil, spatial distribution, topography, Michigan
We examined the spatial variability of N mineralization, nitrification, and denitrification at a resolution of 1 m over a 0.5—ha portion of an old field in southeast Michigan. Net mineralization and nitrification rates were estimated from changes in ammonium and nitrate during 45—d laboratory incubations of soil from >300 individual sample locations. Denitrification was estimated from nitrous oxide accumulation rates during 24—h incubations of intact cores (n = 252) under acetylene atmospheres at a pressure of 10 kPa. We used geostatistical procedures to characterize the spatial distributions of these and other soil variates. Semivariograms for all three N transformations showed a high degree of spatial dependence among points sampled within 1—40 m of one another. Nugget variances were 27—37% of structural variances, indicating that most of the variation within the sample populations for these rates could be attributed to spatial autocorrelation at a scale >1 m. Isopleths calculated using punctual kriging algorithms show a nonuniform distribution of these transformations across the field. High rates of all processes occurred in swales on the northern edge of the sample area, but also occurred elsewhere in the field on drier, more level sites. These results indicate that spatial characteristics of the measured nitrogen transformations in this old field are complex, and that only some of this complexity is associated with surface topography. Whether spatial complexity affects or mainly reflects plant community structure is not known, but this small—scale heterogeneity may influence existing plant and microbial population dynamics and should be considered by those attempting to understand community dynamics or to quantify ecosystem—level nutrient fluxes.