Hilary A. Neckles Jessica L. Nagel Glenn R. Guntenspergen Erika Nicosia Rocks Donald R. Schoolmaster Jr. James B. Grace Dennis Skidds Sara Stevens 2017 The data are in eight .csv files Laurel, MD U.S. Geological Survey http://dx.doi.org/10.5066/F7ZP449D This dataset is comprised of eight files related to salt marsh monitoring data or measures of of human disturbance (i.e. human impacts in terms of physical, chemical, and land-use stressors) collected at 33 marsh study units (MSUs) in five National Parks within the NPS Northeast Coastal and Barrier Network (NCBN) along the northeastern coast of the US. Two files contain data related to the species and coverage of salt marsh vegetation observed in MSUs (1 data file, 1 definitions file). Two files contain data related to the species and abundance of nekton collected from creeks, pools and ditches in MSUs (1 data file, 1 definitions file). Two files contain data related to the height of key salt marsh vegetation species observed in MSUs (1 data file, 1 definitions file). Two files contain data related to metrics describing the degree of human disturbance in MSUs (1 data file, 1 definitions file). Salt marsh monitoring data were generally collected from 2008-2013; however, salt marsh monitoring data were collected irregularly between 1997 and 2007 as part of a pilot program in a small number of the MSUs. Human disturbance metrics were derived from existing aerial imagery and the 2006 National Land Cover Database. Marsh vegetation and nekton (i.e., fish and free-swimming crustaceans) monitoring data were collected as part of the network-wide vital signs monitoring program. Using these data, we derived a wide variety of vegetation and nekton response metrics for potential inclusion in the MMI. We then applied a multivariate, algorithmic approach for MMI development, which is an empirical method of MMI construction from a set of candidate metrics, in which the unique contribution of each metric toward explaining the variation in human disturbance is evaluated within the context of all candidates. The algorithm identified the optimal metric set, reducing a long list of potential candidate metrics to a vital few using an objective and transparent selection process. The MMIs produced can be applied to assess condition and detect change in northeastern national park marshes. 1997 2013 ground condition Complete Not planned -76.242370606022 -69.606628418787 42.556804415413 37.059211675507 Salt marsh monitoring data were collected from 33 marsh study units (MSUs) in five National Parks within the NPS Northeast Coastal and Barrier Network (NCBN) along the northeastern coast of the US. USGS thesaurus wetland ecosystems ecological monitoring vegetation nekton human impacts USGS Metadata Identifier USGS:586e4e2ce4b0f5ce109fcb6d Geographic Names Information System (GNIS) Assateague Island National Seashore, Worcester County, Maryland, USA Fire Island National Seashore, Suffolk County, New York, USA Sagamore Hill National Historic Site, Nassau County, New York, USA Gateway National Recreation Area, Monmouth County, New Jersey, USA Cape Cod National Seashore, Barnstable County, Massachusetts, USA none none Hilary A. Neckles USGS Patuxent Wildlife Research Center mailing and physical

196 Whitten Road

Augusta Maine 04330 USA (207) 626-6619 hneckles@usgs.gov This work was supported, in part, by funding from USGS National Park Monitoring Program and the USGS Climate and Land-Use Research and Development Program USGS Biocomplexity Thesaurus Crustaceans Fishes Plants Shrubs Trees Tiner, R. W. 2009 BOOK Unknown Univ. of Massachusetts Press. Unknown Chesapeake Bay Program. Unknown ONLINE_REFERENCE Unknown Chesapeake Bay Program. www.chesapeakebay.net/fieldguide Erika Nicosia Rocks National Park Service, Northeast Coastal and Barrier Network, Inventory and Monitoring Program mailing and physical

54 Elm Street

Woodstock VT 05091 USA (802)-457-3368 ext 233 erika_nicosia@nps.gov expert advice All vegetation and nekton samples were identified to the genus or species level. All vegetation and nekton samples were identified to the genus or species level. We used R Statistical Software to run the MMI assembly algorithm and to conduct a principal components analysis of disturbance metrics to generate a human disturbance index. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS https://www.r-project.org/ No formal attribute accuracy tests were conducted We conducted QA/QC prior to analysis. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted No formal positional accuracy tests were conducted We entered the monitoring data into Microsoft Excel worksheets and conducted QA/QC prior to analysis. We then classified vegetation and nekton species into key ecological and taxonomic categories. Each plant species was classified according to salt marsh zone (low marsh; high marsh; pannes, pools, and creeks; salt marsh border; brackish border; or upland), salinity tolerance (high, medium, or low), and native status (native or introduced) using information available from various sources. Similarly, nekton species were classified according to broad taxonomic group (e.g., fish, shrimp, crab, etc.), migrational status (resident or transient), and native status (native or introduced) using various sources. 20140115 Field The percent cover of marsh vegetation and other cover types (e.g., water, bare ground, wrack, and litter) was measured once during the peak of the growing season (early July through early September) per sampling year. From 2008 – 2013, cover was measured using the Braun-Blanquet method within ~50 randomized 1m x 1m quadrats along 10 randomized transects per MSU. Percent cover of each species was estimated visually within cover classes (absent; <1%; 1-5%; 6-25%; 26-50%; 51-75%; 76-100%) and was converted cover classes to class midpoints for analyses. Before 2008, cover was measured using either the Braun-Blanquet method or the point-intercept method, in which cover was recorded as the proportion of points intercepted by each species in a grid of 50 or 100 points per square-meter quadrat. In addition to percent cover of vegetation, the height of the introduced common reed, Phragmites australis, was recorded when it occurred within the quadrats. Nekton populations were monitored in shallow pools, creeks, and ditches within each MSU twice during the growing season: once in early summer (mid-June through July) and once in late summer-early fall (August through September). During each sampling event, between 5 and 20 stations were sampled per MSU, depending on the availability of pool, creek, or ditch habitat. Sampling stations were established randomly around the perimeter of pools or along the length of creeks and ditches. Shallow pools and creeks greater than 1 meter wide were sampled using throw traps, and ditches were sampled using ditch nets. Each individual captured was counted and identified to species and up to 15 individuals of each species were measured for total length (fish and shrimp) or carapace width (crabs) at each station. Species counts were converted to density (number m-2) by dividing by sampled area. Definitions tables included in data files. http://dx.doi.org/10.5066/F7ZP449D ScienceBase Team U.S. Geological Survey - ScienceBase mailing and physical

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Denver CO 80225 USA 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. 20200827 Hilary A. Neckles USGS Patuxent Wildlife Research Center Research Ecologist mailing and physical

196 Whitten Road

Augusta Maine 04330 USA (207) 626-6619 hneckles@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999