Location: Invasive Species and Pollinator Health
Project Number: 2030-22000-029-009-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 28, 2015
End Date: Sep 30, 2019
Objective:
To assess ecology, growth and spread of invasive yellow flag iris (Iris psudacorus) with climate change and sea level rise. The objective is to evaluate climate and environmental characteristics of invaded sites; growth, fitness and phenotypic traits of the invasive plants; and assess invertebrate food webs at field sites in the Sacramento-San Joaquin Delta, San Francisco Bay Estuary (SFE), and in sensitive wetlands from a latitudinal gradient along the Pacific Coast. This study will contribute to an overall evaluation of the capacity of invasive aquatic plants/populations to maintain fitness and spread in response to climate change. Results will elucidate relationships among invasive iris abundance and growth, impacted habitat conditions, and infaunal invertebrate community/food web structure and the trophic implications of changing plant cover associated with plant invasion, weed management and ecological restoration.
Approach:
The ARS – CSULB team will identify study populations and conduct field research to evaluate species and population characteristics, environmental variables and food webs associated with invasive Iris pseudacorus (IRPS) a) at sites across an estuarine salinity and inundation gradient (Delta - SFE); and b) along a latitudinal/climate gradient from southern California ~33°N to northern Washington 48°N. At field sites, GPS coordinates and elevation data will be obtained and referenced to NOAA tide gage station data. We will use random quadrat sampling of vegetation at low tide (n=12+ per population) to quantify % cover of species, species richness, IRPS plant traits and biomass. Soil cores will be collected from invaded and uninvaded areas and evaluated for salinity and other properties, and for benthic invertebrates. Water quality will be measured using a multiparameter probe to record surface temperature, salinity, and pH at high slack tide. Climate and hydrologic data will be accessed from large USGS and NOAA databases. Plots will be revisited for seed collections. Plant traits from field populations will be compared using MANOVA. Principal component analysis (PCA) will be used to screen/reduce abiotic and leaf trait variables, analyzing the correlation matrix to extract independent PCA factors. PCA factors of the abiotic environment and PCA factors of plant traits will be evaluated with multiple linear regression models. Multivariate community analysis in Primer (ANOSIM, SIMPER) will be conducted on invertebrate communities to determine differences between invaded and uninvaded communities. Relationships between abiotic variables and plant traits will be examined with linear regressions.
