Filters: Tags: stress gradient (X)
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Ecological processes of low-productivity ecosystems have long been considered to be driven by abiotic controls with biotic interactions playing an insignificant role. However, existing studies present conflicting evidence concerning the roles of these factors, in part due to the short temporal extent of most data sets and inability to test indirect effects of environmental variables modulated by biotic interactions. Using structural equation modeling to analyze 65 years of perennial vegetation change in the Sonoran Desert, we found that precipitation had a stronger positive effect on recruitment beneath existing canopies than in open microsites due to reduced evaporation rates. Variation in perennial canopy cover...
Categories: Publication;
Types: Citation;
Tags: SEM,
Tumamoc Hill,
arid,
density dependence,
modeling,
These datasets provide: 1) field-collected geotechnical data, and 2) Real-Time-Kinematic GPS elevation data for coastal salt marsh in the Port Sulphur area, Louisiana from 2019.
Ecological processes of low-productivity ecosystems have long been considered to be driven by abiotic controls with biotic interactions playing an insignificant role. However, existing studies present conflicting evidence concerning the roles of these factors, in part due to the short temporal extent of most data sets and inability to test indirect effects of environmental variables modulated by biotic interactions. Using structural equation modeling to analyze 65 years of perennial vegetation change in the Sonoran Desert, we found that precipitation had a stronger positive effect on recruitment beneath existing canopies than in open microsites due to reduced evaporation rates. Variation in perennial canopy cover...
Categories: Publication;
Types: Citation,
Journal Citation;
Tags: Ecology,
SEM,
Tumamoc Hill,
arid,
density dependence,
These datasets provide: 1) field-collected biomass and structural attributes for coastal salt marsh in the Port Fourchon area, Louisiana; 2) simulated biomass and structural attributes along flooding gradients using mixed model regression outputs; and 3) resilience metrics calculated using multivariate hypervolumes along with potential environmental covariates of resilience metrics.
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