Plant cover data were collected on 16, 1-ha experimental blocks in C3 and Marsh Creek units of Seney National Wildlife Refuge, 2006-2010. Within each unit, we selected 4 pairs of blocks representing sedge-shrub habitat, with one of the pair assigned to spring burning (C3, May 2008) or summer burning (Marsh Creek, 2007 and 2008). This before-after-control-impact design provided for data collection two growing seasons before the burn (2006, 16 blocks; 2007, 15 blocks) and two-three growing seasons (2008, 2009, and 2010; 13 blocks) after burning; the unburned plot of each pair served as the control, and the burned plot of each pair the treatment. This table provides calculated measures of species richness, Shannon Diversity Index (H), and scores for non-metric multidimensional scaling (3 axes), by treatment, site, and year. These metrics were not calculated for the 2 blocks in C3 dropped from data collection after 2007, or for the one Marsh Creek block burned in 2007 (hence just 13 blocks represented here). Raw data from which these metrics were described in Plant_Taxa_Metadata2.xml.

Plant data were collected on 16, 1-ha experimental blocks in C3 and Marsh Creek units of Seney National Wildlife Refuge, 2006-2010. The percent cover of each plant taxon, moss as a group, and open area was recorded sing a modified line-intercept method for each of 25 sampling points within a block. Sampling points were equidistantly spaced, with 5 points spaced 25 m apart along each of 5 transects also spaced 25 m apart within each sampling block. Within each unit, we selected 4 pairs of blocks representing sedge-shrub habitat, with one of the pair assigned to spring burning (C3, May 2008) or summer burning (Marsh Creek, 2007 and 2008). This before-after-control-impact design provided for data collection two growing seasons before the burn (2006, all 16 blocks; 2007, 15 blocks) and two-three growing seasons (2008, 2009, and 2010; 14 blocks) after burning; the unburned plot of each pair served as the control, and the burned plot of each pair the treatment. Taxa were identified to species where possible,but some taxa were identified only to genus, and some species were merged for analyses because of challenges separating similar species. These data were used in conjunction with environmental data within each block to examine the effects burning on the plant community.

In association with plant cover data, data on litter depth, water depth, and graminoid height were collected on 16, 1-ha experimental blocks in C3 and Marsh Creek units of Seney National Wildlife Refuge, 2006-2010. Within each unit, we selected 4 pairs of blocks representing sedge-shrub habitat, with one of the pair assigned to spring burning (C3, May 2008) or summer burning (Marsh Creek, 2007 and 2008). This before-after-control-impact design provided for data collection two growing seasons before the burn (2006, 16 blocks; 2007, 15 blocks) and two-three growing seasons (2008, 2009, and 2010; 14 blocks) after burning; the unburned plot of each pair served as the control, and the burned plot of each pair the treatment. Within each block, 25 points were established equidistant (25 m) from one another, 5 each along 5 transects. Data were collected at along a 2-m ruler set out at each points. The ruler was marked into 40 5-cm segments; these data were recorded only at the each fifth segment (5, 10, 15, 20, 25, 30, 35, and 40) as a single measure (not averaging accross the 5 segments). This table provides unsummarized data. Associated plant cover data are in Seney_ExpFireStudy_Plant_Taxa_Cover_data.csv.

Vegetation sampling and elevation data were collected to characterize the sedge-grass meadow of Arcadia Marsh, Arcadia, Michigan (USA), a drowned river mouth wetland near Lake Michigan. Wetland vegetation community data were collected by quadrat sampling in 1995, 2002, and 2010 and topographic data were collected via GPS and LIDAR positional data in 2010.

The U.S. Geological Survey (USGS), working in cooperation with the U.S. Fish and Wildlife Service, installed a groundwater and vegetation monitoring network in a proposed wetland area east of the Rio Grande near Bernardo, New Mexico on the NM Boys and Girls Ranch, at a site now known as the Blue Heron Wildlife Preserve (BHWP). In September of 2016, baseline vegetation data were collected across the BHWP to assess vegetation changes with time in the proposed wetland area as it is established and maintained. A second round of vegetation surveys were conducted in August of 2018 for comparative purposes. The collection of this data will support conservation and management decisions.

The U.S. Geological Survey (USGS), working in cooperation with the U.S. Fish and Wildlife Service, installed a groundwater and vegetation monitoring network in a proposed wetland area east of the Rio Grande near Bernardo, New Mexico on the NM Boys and Girls Ranch, at a site now known as the Blue Heron Wildlife Preserve (BHWP). In September of 2016, baseline vegetation data were collected across the BHWP to assess vegetation changes with time in the proposed wetland area as it is established and maintained. A second round of vegetation surveys were conducted in August of 2018 for comparative purposes. The collection of this data will support conservation and management decisions.

These datasets represent USGS-led coastal wetland vegetation survey and mapping efforts at Metzger Marsh, part of the Ottawa National Wildlife Refuge (Ohio, USA) along the coast of western Lake Erie between 1994 and 2022. Vegetation quadrat data provide percent cover estimates per sampling quadrat and overall mean percent cover (MPC) values per species by vegetation type from 1994, and 1996-2010. Vegetation mapping (a.k.a., "photointerpretation") geospatial datasets provide full site cover visualizations and feature class information by vegetation type from 1994,1996-2002, and 2022.

We identified nine study site locations, representing three mature vegetation communities [Atlantic White Cedar (desired community), tall pine pocosin (desired community), and red maple/black gum mixed (undesired community)] with typical water depth within each vegetation type. All measurements were replicated three times (3 vegetation types x 3 replicates = 9 sites total). We installed four flux chambers at each site to collect GHG fluxes from all nine sites. We measured CO2 and CH4 using a Los Gatos Research Ultra Portable Greenhouse Gas Analyzer and two-part 760 cm2 flux chambers (chamber base remained in situ; chamber top was placed on the bottom only when sampling). We checked the gas fluxes on a monthly time-table for 24 months (May 2015 through April 2017) measuring PPM CO2 and CH4 for ten minutes at each chamber. Monthly measurements were also taken for soil temperature and soil moisture. Soil temperature was recorded using a digital thermometer and soil moisture was recorded by measuring soil water content by mass using gravimetric soil moisture protocols at each site.

Species Inventory project as-delivered dataset, geodatabase

This dataset consists of three datafiles: 1) vegetation, 2) abiotic factors, and 3) groundwater levels. Vegetation data were collected twice per month between July and September of 2019 and 2020. Data was collected by establishing 1m x 1m subplots within 12 5m-radius sampling plots distributed across the management units of Bitter Lake National Wildlife Refuge. Subplots were established to represent plot-level vegetation structure and facilitate estimates of rare plant relative abundance. The abiotic factors dataset includes observations of surface soil moisture, salinity, groundwater quality data, and rare plant presence taken weekly between March – October 2019 and May – October 2020 at each established plot within management units of Bitter Lake National Wildlife Refuge. Surface soil conditions were measured using a handheld TEROS 12 soil moisture and salinity sensors (METER group Inc., Pullman, Washington). Groundwater quality data was measured using an YSI handheld multi-parameter (YSI Inc., Yellow Springs, Ohio). The groundwater level dataset includes groundwater depth data. Groundwater depth was monitored by installing an In-Situ Rugged TROLL 100 water level recorder (In-Situ Inc., Fort Collins, Colorado) in 4 wells within 4 different management units. Each recorder was programmed to conduct readings every 6 hours from March 2019 to October 2020. Groundwater level data was calibrated by installing one In-Situ Rugged BaroTROLL barometric pressure transducer at a midpoint. Groundwater data was downloaded to the Win Situ 5 software, where the data was gathered, calibrated, organized and exported as a .csv file. This dataset summarizes this information and was used for analysis.