The Impact of Oldfield Succession on Depression Storage

Quantifying the effect of vegetation cover change on runoff is essential for watershed management. Previous studies have noted the importance of vegetation in controlling soil infiltration because of the effect of vegetation on soil surface variables. Here, we hypothesize that ecologic succession from mowed grassland to oldfield to forest will impact depression storage by changing the microtopography of the surface. We test this idea by measuring depression storage and leaf litter water retention rates in twelve sites across a successional gradient under a variety of slope conditions. Sites of similar slope and soil type were also evaluated against one another to better isolate the effect of both vegetation diversity and management on depression storage. Results showed that average ideal depression storage was different for various eco-types with 5.8, 11.1, 14.3, 18.7 mm of storage for mowed grassland, old field, forest, and wetland respectively. This variation is attributed to changes in vegetation diversity and structure. Effective depression storage of unmanaged successional oldfield, shrubland, and forest was significantly higher than mowed grassland at all slopes, and mowed successional oldfield was not significantly different then mowed residential turf implying that management activities such as mowing retard the natural development of microtopography that occurs with natural vegetation succession. Results of leaf litter water retention varied significantly among land covers, but were much lower in most cases than depression storage from microtopography. Maximum leaf litter water retention rates were only 2 ml per gram of leaf litter after leaf fall, implying it contributes seasonally and to a lower extent for on-plot water storage. These results imply there are tight linkages between vegetation succession and runoff; and that land use modifications and grassland management strategies can dramatically effect run-off and water retention. Understanding these characteristics are very important for developing effective hydrologic models.