SLR and wetlands in the SF Bay
Friday, February 14, 2014 at 1:19PM 
The resilience of four marshes examined in this paper.Schile, L.M., J.C. Callaway, J.T. Morris, D. Stralberg, V. T. Parker, and M. Kelly. 2014. Modeling tidal marsh distribution with sea-level rise: evaluating the role of vegetation and upland habitat in marsh resiliency. PLOS One 9(2): e88760
Tidal marshes maintain elevation relative to sea level through accumulation of mineral and organic matter, yet this dynamic accumulation feedback mechanism has not been modeled widely in the context of accelerated sea-level rise. Uncertainties exist about tidal marsh resiliency to accelerated sea-level rise, reduced sediment supply, reduced plant productivity under increased inundation, and limited upland habitat for marsh migration. We examined marsh resiliency under these uncertainties using the Marsh Equilibrium Model, a mechanistic, elevation-based soil cohort model, using a rich data set of plant productivity and physical properties from sites across the estuarine salinity gradient. Four tidal marshes were chosen along this gradient: two islands and two with adjacent uplands. Varying century sea-level rise (52, 100, 165, 180 cm) and suspended sediment concentrations (100%, 50%, and 25% of current concentrations), we simulated marsh accretion across vegetated elevations for 100 years, applying the results to high spatial resolution digital elevation models to quantify potential changes in marsh distributions.
gis, modeling, open access, wetlands Where will SF Bay wetlands be in 100 years?
Wednesday, November 16, 2011 at 7:43PM Stralberg, D., M. Brennan, J. C. Callaway, J. K. Wood, L. M. Schile, D. Jongsomjit, M. Kelly, V. T. Parker, and S. Crooks. 2011. Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay. PLoS ONE 6(11): e27388.
Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions.
Mapping changes in tidal wetland vegetation composition
Monday, December 27, 2010 at 9:43AM Tuxen, K, L Schile, D Stralberg, S Siegel, T Parker, M Vasey, J Callaway, and M Kelly. 2011. Mapping changes in tidal wetland vegetation composition and pattern across a salinity gradient using high spatial resolution imagery. Wetland Ecology and Management 19:141-157
Coon Island vegetation over two years. We mapped vegetation at six tidal marshes (two natural, four restored) in the San Francisco Estuary, CA, USA, between 2003 and 2004 using detailed vegetation field surveys and high spatial-resolution color-infrared aerial photography. Vegetation classes were determined by performing hierarchical agglomerative clustering on the field data collected from each tidal marsh.
metrics, pattern, remote sensing, wetlands Pattern metrics for wetland restoration management
Friday, November 12, 2010 at 7:54AM Kelly, M., K. Tuxen and D. Stralberg. 2011. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time. Ecological Indicators 11: 263-273. We sought to identify pattern metrics that are consistent across spatial scale and time – and thus robust measures of vegetation and habitat configuration – for a restored tidal marsh in the San Francisco Bay, CA, USA.
gis, metrics, pattern, remote sensing, wetlands Predicting bird abundance in tidal marshes
Wednesday, May 12, 2010 at 6:49AM 
Predicted mean abundance for common yellowthroat at Browns Is. and Sherman Lake
Stralberg, D., M. Herzog, N. Nur, K. Tuxen, S. Siegel and M. Kelly. 2010. Predicting avian abundance within and across tidal marshes using fine-scale vegetation and geomorphic metrics. Wetlands 30: 475-487
We used a blend of fine-scale remote sensing products and field-based survey data via spatial predictive models to aid in monitoring restoring tidal marshes for bird habitat. We developed a suite of 1-m pixel-level spatial metrics describing patterns in marsh vegetation and geomorphology for six sites across a large salinity gradient, and used these to predict avian abundance.