How river network structure and habitat availability shape the spatial dynamics of larval sea lampreys

The spatial dynamics of many populations are highly contextual in that they depend on the structure of the environment at specific locations or scales. In this paper, we asked how the unique geomorphic structure of each river system might shape the spatial dynamics of larvae of sea lamprey (Petromyzon marinus), an anadromous fish species that is invasive and ecologically harmful in the Laurentian Great Lakes. We developed an individual-based model and conducted a series of simulations in which we varied geomorphic structure at two spatial scales (local habitat substrate composition and basin-wide river network shape). We observed three main results: (1) Larval distribution depended on both river network structure and the distribution of larval habitat, but the relative importance of these two factors depended on the basin-wide abundance of larval habitat. (2) Larvae in the model became spatially aggregated over time, and the degree and rate of this aggregation depended on river network structure and the amount and distribution of larval habitat. Larvae aggregated most quickly, and eventually into the smallest number of reaches, in elongated river networks with abundant larval habitat. (3) Total larval population size in a watershed varied with factors that control larval aggregation, i.e. river network structure and amount and distribution of larval habitat, but relationships were strongly nonlinear. In summary, we found that the population dynamics of anadromous lampreys in Great Lakes tributary rivers constitute an interesting and complex ecological system in which some perennial themes of landscape ecology emerge: connectivity, historical process, and the importance of spatial arrangement. Our results overall suggest that the spatial dynamics of larval lampreys might be highly varied from river system to river system across the Great Lakes basin. We discuss how the unique geomorphic structure of each river might inform adaptive management strategies at specific locations and scales. (c) 2011 Elsevier B.V. All rights reserved.