The effect of multiple stressors on salt marsh end-of-season biomass

Estuaries and Coasts
By: , and 



It is becoming more apparent that commonly used statistical methods (e.g. analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass.

Publication type Article
Publication Subtype Journal Article
Title The effect of multiple stressors on salt marsh end-of-season biomass
Series title Estuaries and Coasts
DOI 10.1007/BF02782001
Volume 29
Issue 2
Year Published 2006
Language English
Publisher Springer
Contributing office(s) Fort Collins Science Center
Description 12 p.
First page 331
Last page 342
Google Analytic Metrics Metrics page
Additional publication details