Abstract

Efforts to conserve, restore, or otherwise manage large rivers and the services they provide are hindered by limited understanding of the functional dynamics of these systems. This shortcoming is especially evident with regard to trophic structure and energy flow. We used natural abundances of carbon and nitrogen isotopes to examine patterns of material flow in ten large-river food webs characterized by different landscape-scale hydrologic characteristics (low-gradient river, high-gradient river, river stretches downstream of reservoirs, and reservoirs), and tested predictions from three ecosystem concepts commonly applied to large-rivers: The River Continuum Concept, The Flood Pulse Concept and the Riverine Productivity Model. Carbon derived from aquatic C3 plants and phytoplankton were the dominant energy sources supporting secondary consumers across the ten large-river food webs examined, but relative contributions differed significantly among landscape types. For low-gradient river food webs, aquatic C3 plants were the principal carbon source, contributing as much as 80% of carbon assimilated by top consumers, with phytoplankton secondarily important. The estimated relative importance of phytoplankton was greatest for food webs of reservoirs and river stretches downriver from impoundments, although aquatic C3 plants contributed similar amounts in both landscape types. Highest 99th percentile source contribution estimates for C4 plants and filamentous algae (both approximately 40%) were observed for high-gradient river food webs. Our results for low-gradient rivers supported predictions of the Flood Pulse Concept, whereas results for the three other landscape types supported the Riverine Productivity Model to varying degrees. Incorporation of landscape-scale hydrologic or geomorphic characteristics, such as river slope or floodplain width, may promote integration of fluvial ecosystem concepts. Expanding these models to include hydrologically impacted landscapes should lead to a more holistic understanding of ecosystem processes in large-river systems.

Highlights

  • Freshwater ecosystems, especially large rivers, are some of the most threatened on the planet (Allan and Flecker 1993; Jackson and others 2001)

  • Despite the relative paucity of food web studies conducted in large rivers, three general concepts of ecosystem functioning are widely cited, each stressing the importance of a different principal energy source driving large-river food webs: the River Continuum Concept (RCC—Vannote and others 1980), the Flood Pulse Concept (FPC—Junk and others 1989) and the Riverine Productivity Model (RPM—Thorp and Delong 1994, 2002)

  • Given that sampling occurred during the late dry season, the oligotrophic nature of the waterbodies and large watershed size, the comparatively enriched d13C values observed for algae may result from relative limitation of dissolved CO2

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Summary

Introduction

Freshwater ecosystems, especially large rivers, are some of the most threatened on the planet (Allan and Flecker 1993; Jackson and others 2001). Few large rivers remain in relatively natural states (Gore and Shields 1995; Rosenberg and others 2000; Nilsson and others 2005). The vast majority of temperate-zone rivers are heavily regulated (Dynesius and Nilsson 1994), and construction of large dams for the production of hydroelectric power and flood control is widespread and continuing in tropical latitudes (Dudgeon 2000; Pringle and others 2000). Restore or otherwise manage large rivers are hindered by limited understanding of the functional dynamics of natural and modified systems, especially with regard to energy flow (Johnson and others 1995; Delong and Thorp 2006). Despite the relative paucity of food web studies conducted in large rivers, three general concepts of ecosystem functioning are widely cited, each stressing the importance of a different principal energy source driving large-river food webs: the River Continuum Concept (RCC—Vannote and others 1980), the Flood Pulse Concept (FPC—Junk and others 1989) and the Riverine Productivity Model (RPM—Thorp and Delong 1994, 2002)

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