Emergent productivity regimes of river networks

Abstract

The production of organic carbon by aquatic photosynthesis is a central ecosystem property that influences food webs and nutrient cycling rates. Although it is well known that several factors are related to variation in gross primary production in rivers, it is not known how these factors combine to determine primary productivity at the scale of river networks. Our simulation of river networks at a range of productivity regimes provides an initial approximation of river ecosystem productivity at broad scales, and shows that in some cases, small streams and certain time periods disproportionately influence river network productivity. AbstractHigh-resolution data are improving our ability to resolve temporal patterns and controls on river productivity, but we still know little about the emergent patterns of primary production at river-network scales. Here, we estimate daily and annual river-network gross primary production (GPP) by applying characteristic temporal patterns of GPP (i.e., regimes) representing distinct river functional types to simulated river networks. A defined envelope of possible productivity regimes emerges at the network-scale, but the amount and timing of network GPP can vary widely within this range depending on watershed size, productivity in larger rivers, and reachscale variation in light within headwater streams. Larger rivers become more influential on network-scale GPP as watershed size increases, but small streams with relatively low productivity disproportionately influence network GPP due to their large collective surface area. Our initial predictions of network-scale productivity provide mechanistic understanding of the factors that shape aquatic ecosystem function at broad scales.

Superlinear scaling of riverine biogeochemical function with watershed size

“…River network geomorphology is also characterized by fractal networks and exhibits allometric scaling relationships 21,22 . For example, power law scaling describes proportional removal of DOC and total gross primary production, driven by the interaction of biological activity, network structure, and river hydraulics [23][24][25] . However, it remains unclear why these patterns arise, and how they are influenced by temporal variation in river discharge 13,26 .…”

“…1B) as influenced by geomorphic attributes of the network (e.g. shape, number and length of streams in each river order) 23,24 . Scaling of length is due to geomorphic characteristics of the network alone, whereas surface area is also influenced by changes in wetted width as a function of mean discharge that accumulates with watershed area.…”

Generation and application of river network analogues for use in ecology and evolution

“…spreading of human [Bertuzzo et al, 2010;Gatto et al, 2013;Mari et al, 2019] and animal [Carraro et al, 2018] waterborne pathogens; ecosystem processes, such as carbon [Bertuzzo et al, 2017;Koenig et al, 2019] and nitrogen cycling [Helton et al, 2018]; migration fronts of human populations [Campos et al, 2006]; cross-ecosystem subsidies [Harvey et al, 2019]; riverine biodiversity patterns from a theoretical viewpoint [Muneepeerakul et al, 2019] or by means of mesocosm experiments [Carrara et al, 2012[Carrara et al, , 2014Harvey et al, 2018].…”

Generation and application of river network analogues for use in ecology and evolution

“…ecosystem processes, such as carbon (Bertuzzo, Helton, Hall, & Battin, 2017;Koenig et al, 2019) and nitrogen cycling (Helton et al, 2018); migration fronts of human populations (Campos, Fort, & Méndez, 2006); cross-ecosystem subsidies (Harvey, Gounand, Fronhofer, & Altermatt, 2020); sampling strategies for environmental DNA in rivers (Carraro, Stauffer, & Altermatt, 2020); riverine F I G U R E 1 Examples of river network analogues with increasing level of resemblance with real river networks. Line width increases toward the downstream direction.…”