Disturbance is complicated: Headward‐eroding saltmarsh creeks produce multiple responses and recovery trajectories

Disturbances are one of the most important processes affecting natural systems, but there is a gap between simple conceptual models of disturbance and complex empirical studies. We studied the perturbation caused by headward‐eroding creeks in southeastern USA salt marshes. We measured disturbance re...

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Veröffentlicht in:Limnology and oceanography 2022-02, Vol.67 (S1), p.S86-S100
Hauptverfasser: Wu, Fengrun, Pennings, Steven C., Ortals, Collin, Ruiz, Jennifer, Farrell, W. Reilly, McNichol, Samuel M., Angelini, Christine, Spivak, Amanda C., Alber, Merryl, Tong, Chunfu
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Sprache:eng
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Zusammenfassung:Disturbances are one of the most important processes affecting natural systems, but there is a gap between simple conceptual models of disturbance and complex empirical studies. We studied the perturbation caused by headward‐eroding creeks in southeastern USA salt marshes. We measured disturbance responses (magnitude and recovery trajectory) of 19 variables. Some variables (shoot density, root biomass, snail density, soil pH, soil strength, soil temperature, elevation) declined sharply, while other variables (crab burrow density, soil organic matter, soil redox) increased sharply, in response to the burrowed and grazed conditions at the creek head. These variables recovered over subsequent years or decades. Other variables (shoot height, aboveground biomass, rhizome biomass, light interception) declined sharply in the creek head, then overshot control values before recovering. Some variables (benthic algae, soil salinity) did not appear to be disturbed by the creek head. As hypothesized, plants recovered before soils and snails. Disturbance magnitude and time to recovery were often greater directly adjacent to the new creekbank than for the same variables in a parallel transect further away from the creekbank, and in some cases variables never converged with control values, indicating a persistent state change. Reducing the dimensionality of the data set into principal component axes obscured the diverse ways in which different aspects of the system responded to and recovered from the perturbation. Our study illustrates the challenges in moving from simple conceptual models of disturbance to empirical studies in which multiple variables are likely to be affected differently and follow different recovery trajectories.
ISSN:0024-3590
1939-5590
DOI:10.1002/lno.11867