The role of floods in particulate organic matter dynamics of a southern Appalachian river–floodplain ecosystem

Abstract

We investigated the effect of a flood on particulate organic matter (POM) dynamics in the floodplain and active channel of the Little Tennessee River in western North Carolina. We measured litterfall, leaf breakdown, and floodplain litter (before and after the flood) at 12 sites. Annual litterfall (256-562 g m 2 y 1) was typical of a temperate deciduous forest but lower than lowland floodplain forests in the eastern US. Leaf breakdown rates of 4 tree species (Acer rubrum, Carpinus caroliniana, Juglans nigra, and Platanus occidentalis) ranged from 0.001 to 0.010/d. We separated the 12 sites into 2 groups (inundated and non-inundated) based on the degree of flooding after a flood on 8 January 1998 and determined POM exchange between the active channel and floodplain. Significant transport of leaves from the floodplain to the river occurred at inundated sites, but transport of herbaceous or woody material did not occur. The flood increased leaf breakdown rates of all 4 tree species. Our measurements of litterfall, leaf breakdown, and floodplain litter standing crop suggest that leaves entrained from the floodplain of Little Tennessee River during floods are a source of POM to the active channel. However, flood input of leaves to the river were a small source of POM compared to direct leaffall.

Longitudinal patterns of metabolism in a southern Appalachian river

“…Minshall et al (1983) observed longitudinal increases of similar magnitude in GPP, but these were measured across larger changes in stream size. Meyer and Edwards (1990) showed a remarkably similar increase from 4th-order Black Creek, Georgia, to 6th-order Ogeechee River, Georgia, sites with Neatrour (1999) at sites near river metabolism sites. Percent of total input is in parentheses below input values.…”

“…Direct litterfall input to the river decreased per unit area as the river got larger. Flood input of CPOM ranged from 16.2 g C m Ϫ2 y Ϫ1 at site 2 to 26.8 g C m Ϫ2 y Ϫ1 at site 1, but input varied dramatically because of differential inundation and entrainment (Neatrour 1999). Annual respiratory loss of C was highest at site 1 (522.7 g C m Ϫ2 y Ϫ1 ) and lowest at site 3 (384.5 g C m Ϫ2 y Ϫ1 ).…”

“…We performed all statistical analyses using SAS (version 8, SAS Institute, Cary, North Carolina). Neatrour (1999) quantified allochthonous input of coarse particulate organic matter (CPOM) to the LTR from direct litter fall and entrainment from the floodplain during floods. We used data from his sites closest to our metabolism sampling sites to estimate annual allochthonous C load of CPOM to these reaches of the LTR.…”

Planting grass filter strips: Does it influence the structure and function of riparian habitats of agricultural headwater streams?

“…Increased CPOM input, decreased herbaceous input, and increased leaf and woody input occurred as the composition of the riparian habitat shifted from herbaceous riparian habitat to a mixed herbaceous-shrub riparian habitat to forested riparian habitat along a prairie stream in Kansas [37] and along a fifth order stream in Idaho [4]. Neatrour et al [8] documented that reductions in riparian forest width as result of agriculture led to decreases in tree density and CPOM inputs within riparian habitats adjacent to a small river in North Carolina. Sites with < 5 m forested riparian widths had less tree density and less CPOM input than sites having forested riparian widths > 5 m [8].…”

Influence of episodic acidification on leaf breakdown in neighboring streams of the western Adirondacks, USA

“…We conducted all statistical analyses using Statistical Analysis System (version 9.1, SAS Institute, Cary, North Carolina). We used an analysis of covariance (ANCOVA) with a dummy variable to make comparisons in breakdown rates between species, between single-and mixed-species packs, and among streams (Neatrour et al 2004). To make pairwise comparisons in breakdown rates, we controlled the false discovery rate (i.e., the fraction of rejected null hypotheses) to reduce inflation of the Type 1 error rate resulting from multiple pairwise comparisons (Bejamini and Hochberg 1995).…”