Density-dependent role of an invasive marsh grass, <i>Phragmites australis</i>, on ecosystem service provision

<div><p>Invasive species can positively, neutrally, or negatively affect the provision of ecosystem services. The direction and magnitude of this effect can be a function of the invaders’ density and the service(s) of interest. We assessed the density-dependent effect of an invasive marsh grass, <i>Phragmites australis</i>, on three ecosystem services (plant diversity and community structure, shoreline stabilization, and carbon storage) in two oligohaline marshes within the North Carolina Coastal Reserve and National Estuarine Research Reserve System (NCNERR), USA. Plant species richness was equivalent among low, medium and high <i>Phragmites</i> density plots, and overall plant community composition did not vary significantly by <i>Phragmites</i> density. Shoreline change was most negative (landward retreat) where <i>Phragmites</i> density was highest (-0.40 ± 0.19 m yr^-1 vs. -0.31 ± 0.10 for low density <i>Phragmites</i>) in the high energy marsh of Kitty Hawk Woods Reserve and most positive (soundward advance) where <i>Phragmites</i> density was highest (0.19 ± 0.05 m yr^-1 vs. 0.12 ± 0.07 for low density <i>Phragmites</i>) in the lower energy marsh of Currituck Banks Reserve, although there was no significant effect of <i>Phragmites</i> density on shoreline change. In Currituck Banks, mean soil carbon content was approximately equivalent in cores extracted from low and high <i>Phragmites</i> density plots (23.23 ± 2.0 kg C m^-3 vs. 22.81 ± 3.8). In Kitty Hawk Woods, mean soil carbon content was greater in low <i>Phragmites</i> density plots (36.63 ± 10.22 kg C m^-3) than those with medium (13.99 ± 1.23 kg C m^-3) or high density (21.61 ± 4.53 kg C m^-3), but differences were not significant. These findings suggest an overall neutral density-dependent effect of <i>Phragmites</i> on three ecosystem services within two oligohaline marshes in different environmental settings within a protected reserve system. Moreover, the conceptual framework of this study can broadly inform an ecosystem services-based approach to invasive species management.</p></div

Sampling locations.

<p>A) Location of Currituck Banks and Kitty Hawk Woods Reserves (stars), components of the North Carolina Coastal Reserve and National Estuarine Research Reserve system, in Currituck Sound, North Carolina, USA. B) Location of sampled Low, Medium, and High <i>Phragmites</i> Density sites (stars) within Kitty Hawk Woods Reserve. C) Location of sampled Low and High <i>Phragmites</i> Density sites (stars) within Currituck Banks Reserve—note that no Medium <i>Phragmites</i> density sites were present within Currituck Banks Reserve. All satellite imagery was derived from United States Geological Survey, High Resolution Orthoimagery Dataset.</p

Mean (±SE) observed plant diversity parameters.

<p>A) Species Richness (<i>d</i>), B) Pielou’s Evenness (<i>J’</i>), C) Simpson’s Diversity (1-<b>D</b>), and D) Shannon Diversity (<i>H’</i>) for Low, Medium, and High <i>Phragmites</i> Density treatments in Currituck Banks Reserve (dark gray shading) and Kitty Hawk Woods Reserve (light gray shading). Note that the Medium <i>Phragmites</i> Density treatment was present only in Kitty Hawk Woods Reserve. See text for results of statistical analyses.</p

Results of Non-Metric Multidimensional Scaling (NMDS) and two-way crossed Analysis of Similarities (ANOSIM) used to evaluate effects of Reserve and <i>Phragmites</i> density on overall emergent vegetation community structure.

<p>2-dimensional stress values denote the degree of mismatch between the predicted values from the regression of the similarity matrix and the distances between samples as displayed by the two-dimensional nMDS plot.</p

Mean (±SE) shoreline change rate (m yr^-1) as determined in this study (gray shading) and from historical shoreline imagery (white shading).

<p>A) at Kitty Hawk Woods and Currituck Banks Reserves, B) between <i>Phragmites</i> Density treatments within Kitty Hawk Woods Reserve, and C) between <i>Phragmites</i> Density treatments within Currituck Banks Reserve. Note that the Medium <i>Phragmites</i> Density treatment was present only in Kitty Hawk Woods Reserve. Negative values indicate landward retreat and positive values indicate soundward advance. See text for results of statistical analyses.</p

Mean (±SE) normalized total below-ground carbon inventory (g C m^-3).

<p>Below-ground carbon inventory A) at Kitty Hawk Woods and Currituck Banks Reserves, B) between <i>Phragmites</i> Density treatments within Kitty Hawk Woods Reserve, and C) between <i>Phragmites</i> Density treatments within Currituck Banks Reserve. Note that the Medium <i>Phragmites</i> Density treatment was present only in Kitty Hawk Woods Reserve. See text for results of statistical analyses.</p

Mean (±SE) above-ground biomass (g dry plant material m^-2).

<p>Above-ground biomass A) at Kitty Hawk Woods and Currituck Banks Reserves, B) between <i>Phragmites</i> Density treatments within Kitty Hawk Woods Reserve, and C) between <i>Phragmites</i> Density treatments within Currituck Banks Reserve. Note that the Medium <i>Phragmites</i> Density treatment was present only in Kitty Hawk Woods Reserve. Letters indicate significant differences between levels of a factor. See text for results of statistical analyses.</p

Table1.docx

<p>Habitat suitability index (HSI) models are increasingly used to guide ecological restoration. Successful restoration is a byproduct of several factors, including physical and biological processes, as well as permitting and logistical considerations. Rarely are factors from all of these categories included in HSI models, despite their combined relevance to common restoration goals such as population persistence. We developed a Geographic Information System (GIS)-based HSI for restoring persistent high-relief subtidal oyster (Crassostrea virginica) reefs protected from harvest (i.e., sanctuaries) in Pamlico Sound, North Carolina, USA. Expert stakeholder input identified 17 factors to include in the HSI. Factors primarily represented physical (e.g., salinity) and biological (e.g., larval dispersal) processes relevant to oyster restoration, but also included several relevant permitting (e.g., presence of seagrasses) and logistical (e.g., distance to restoration material stockpile sites) considerations. We validated the model with multiple years of oyster density data from existing sanctuaries, and compared HSI output with distributions of oyster reefs from the late 1800's. Of the 17 factors included in the model, stakeholders identified four factors—salinity, larval export from existing oyster sanctuaries, larval import to existing sanctuaries, and dissolved oxygen—most critical to oyster sanctuary site selection. The HSI model provided a quantitative scale over which a vast water body (~6,000 km²) was narrowed down by 95% to a much smaller suite of optimal (top 1% HSI) and suitable (top 5% HSI) locations for oyster restoration. Optimal and suitable restoration locations were clustered in northeast and southwest Pamlico Sound. Oyster density in existing sanctuaries, normalized for time since reef restoration, was a positive exponential function of HSI, providing validation for the model. Only a small portion (10–20%) of historical reef locations overlapped with current, model-predicted optimal and suitable restoration habitat. We contend that stronger linkages between larval connectivity, landscape ecology, stakeholder engagement and spatial planning within HSI models can provide a more holistic, unified approach to restoration.</p