This dataset contains vegetation data collected at a variety of watershed restoration sites across southeastern Arizona over 5 years. The semiarid habitats in the Madrean Archipelago Ecoregion, which extends from southern Arizona into northern Mexico, are facing many challenges from climate change to land use change which threaten the ecological and cultural values of the region. Watershed restoration practitioners use a variety of techniques such as gabions, check dams, and cross vanes to reduce the effects of these threats and improve or maintain watershed function. Since vegetation dynamics in the area are driven by water availability, these restoration techniques appear to have secondary effects on the vegetation of a watershed. To evaluate and quantify these effects, vegetation data was collected at 5 restoration sites across southeastern Arizona. Three of these sites, Barboot (BB), Silver Creek (SC), and Vaughn Canyon (VC), were restored just before sampling occurred allowing for an "After-Control-Impact" design to assess the change in vegetation. Data was collected at SC and VC for 5 years while only 4 years of data was collected at BB due to a lack of continued change. At these sites treatment plots were established at structures within stream channels while control plots were established at locations in reaches without structures within the same drainages. At Deep Dirt (DD), the project drainage was fairly short and there was no area within it or in a similar drainage that did not have restoration structures. This prevented the installation of control plots, instead data was collected at two different types of structures for 5 years. At Cienega Ranch (CR), restoration structures had not been installed when data was collected. Plots were distributed in the project reaches and in a nearby control reach. One year of baseline data has been collected at CR which will allow for a “Before-After-Control-Impact” study design. At all project sites, each plot was stratified in zones based on hydrological position relative to the restoration structure and proximity to the structure. Nested quadrats were used to quantify abundance as well as basal and foliar cover. Subplots were used to quantify species composition. Data was collected for perennial species and non-native species during the summer monsoon season from August – September, sometimes extending into early October. This vegetation data is provided in 5 CSV files which form a relational database which is explained in further detail in "RelationalDatabase_VegetationResponseWatershedRestoration.xml". "Relationships.pdf" is an illustration of the relationships in the database. "StudySampleDesign.pdf" contains figures illustrating plot design and nested quadrat design to clarify the data collection process. "mtbl_Plants.csv" is the master plant list that includes taxonomic and other information for Arizona species; the development of this dataset is explained in further detail in "mtbl_Plants.xml". Every plot and nested quadrat was photodocumented; photos can be found in the "Photos_VegetationResponseWatershedRestoration" directory and process explained in the associated metadata file "Photos_VegetationResponseWatershedRestoration.xml". This data release can be downloaded with or without the photos. "VegetationResponseWatershedRestoration.zip" includes the photos; "VegetationResponseWatershedRestoration_noPhotos.zip" does not include the photos for faster download times.

This dataset is from a restoration field study conducted at seven sites distributed across the southern Colorado Plateau in northern Arizona as part of the RestoreNet dryland restoration field trial network. The data consist of post-experimental restoration treatment (2018-2019) plant density and height measurements along with site precipitation, temperature, and soils data. Plant data were collected through plot monitoring visits distributed throughout the first year following restoration treatments and seeding.

This dataset is from a restoration field study conducted at seven sites distributed across the southern Colorado Plateau in northern Arizona as part of the RestoreNet dryland restoration field trial network. The data consist of post-experimental restoration treatment (2018-2019) plant density and height measurements along with site precipitation, temperature, and soils data. Plant data were collected through plot monitoring visits distributed throughout the first year following restoration treatments and seeding.

We apply a research approach that can inform riparian restoration planning by developing products that show recent trends in vegetation conditions identifying areas potentially more at risk for degradation and the associated relationship between riparian vegetation dynamics and climate conditions. The vegetation is characterized using a series of remote sensing vegetation indices developing using satellite imagery, including the Normalized Difference Vegetation Index (NDVI) and Tasseled Cap (TC) Transformation metrics of brightness, greenness, and wetness. Each of these remote sensing vegetation indices provides a unique characterization of the vegetation properties. For example, NDVI provides a general overview of vegetation condition while the TC Transformation metrics are multi-dimensional and interrelated and can provide distinctive information on conditions within a vegetation ecosystem. The climate conditions are characterized by defining climate periods based on a timeseries of 1-year Standardized Precipitation Evapotranspiration Index (SPEI) values averaged across the Upper Gila River watershed and divided into climate periods (i.e., 1985 through 1993; 1993 through 2014; 2014 through 2021) using the breakpoints algorithm in R Software. Finally, the remote sensing products were developed based on a seasonal framework to obtain more information on the vegetation dynamics. The seasonal framework is defined by averaging multiple images across the following two-month periods: (i) spring (March/April), (ii) late-spring (May/June), (iii) summer (July/August), and (iv) fall (September/October). This Parent data release consists of five Child Items. The first Child Item includes the SPEI timeseries that was used to identify the climate periods applied in this analysis. The second Child Item consists of 16 rasters with 37 bands apiece, where each raster in this Child Item is identified by a combination of the index (i.e., NDVI, TC brightness, TC greenness, TC wetness) and the season (i.e., spring, late-spring, summer, fall), and each band represents a yearly mean value for all years from 1985 through 2021. The third Child Item also consists of 16 rasters, though with only 3 bands apiece. Similarly, for this Child Item, each raster is identified by a combination of the index (i.e., NDVI, TC brightness, TC greenness, TC wetness) and the season (i.e., spring, late-spring, summer, fall). However, each band represents the linear Sen's slope trend across a different climate period, where band 1 represents the Sen's slope trend across the 1st climate period (i.e., 1985 through 1993), band 2 represents the Sen's slope trend across the 2nd climate period (i.e., 1993 through 2014), and band 3 represents the Sen's slope trend across the 3rd climate period (i.e. 2014 through 2021). The fourth and fifth Child Items both include a series of monthly images, stacked into single rasters, for NDVI and TC greenness covering the length of the 3rd climate period (i.e., 2014 through 2021) that were produced to address a series of case studies more directly. Specifically, the fourth Child Item address a phenological analysis while the fifth Child Item addresses a fire-based case study. All raster products were developed using the Google Earth Engine (GEE) cloud computing software program.

This dataset contains data used in the associated publication in the International Journal of Remote Sensing.Wilson, Natalie R., and Laura M. Norman. 2018. “Analysis of Vegetation Recovery Surrounding a Restored Wetland Using the Normalized Difference Infrared Index (NDII) and Normalized Difference Vegetation Index (NDVI).” International Journal of Remote Sensing 39 (10): 3243–74. https://doi.org/10.1080/01431161.2018.1437297.The geodatabase contains four feature classes: AOI, MajorZone, MinorZone, and Green2007.Publication abstract: Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

These data were compiled to assess the status and trends of riparian plant communities along the Colorado River between Glen Canyon Dam and Lake Mead, AZ. Three metrics have been proposed to evaluate the "Riparian Vegetation" goal identified in the Glen Canyon Dam Adaptive Management Program's Long Term Experimental and Management Plan (U.S. Department of Interior, 2016). The three metrics are total living plant cover, the proportion of living cover composed of native species, and native species richness. Current policies for Glen Canyon Dam operations result in three longitudinal bands within the riparian area that are flooded at different frequencies. The band, or hydrologic zone, that is most frequently inundated is referred to here as the “active channel” or “AC.” This includes all areas inundated by releases up to 25,000 cubic feet per second (707 m3/s). The “active floodplain” or “AF” is inundated by high flow experiments and includes areas that are inundated by releases between 25,000 cubic feet per second and 45,000 cubic feet per second (1,274 m3/s). The “inactive floodplain” or “IF” is the area along the river that is inundated by releases over 45,000 cubic feet per second, which is not planned under current policies. The metrics are assessed for each of these hydrologic zones. Data from the Grand Canyon Monitoring and Research Center's riparian vegetation monitoring protocol (Palmquist and others, 2018) can be used to evaluate these metrics, which is what is provided here. In short, 80-100 sample sites are randomly selected each year. These sites include debris fans, eddy sandbars, and channel margins. At each randomly selected sample site, ocular cover estimates of each plant species occurring in 1-m2 quadrats spanning the hydrological zones are recorded, along with an estimate of total living plant cover and associated environmental variables. The first metric, total living plant cover, consists of two pieces of data; plant occurrence (a plant is present in the sample frame) and plant cover (proportion of the sample frame covered with living plants). Cover is represented by both an ordinal cover class (1, 2, 3, 4, 5, 6, etc.) and the midpoint of the cover class value (0.01%, 0.5%, 1%, 5%, 10%, 15%, etc). The proportion of native cover is the sum total of native plant cover divided by the sum total of plant cover (native plus nonnative cover) for a sample frame. Native plant richness is the total number of native species rooted inside a sample frame. The total living plant cover data are available for 2016 through 2023. The native cover and richness data are available for 2014 and 2016 through 2023.

The data release presents observations of riparian vegetation, topography, and sediment quality in five river reaches of the Lower Virgin River extending downstream 62 river kilometers (rkm), from near the town of Littlefield (Arizona) to approximately 15 rkm upstream from the confluence with the Muddy River (Nevada). Methods included field observations and analysis of the plant community before substantial biocontrol-induced dieback of invasive Tamarix spp. shrubs (surveys in 2010 and 2012) and after (surveys in 2015, 2017, and 2021). The first survey was conducted before a 40-year return period flood (December 2010, at the gaging station “Virgin River near Littlefield” (USGS gage #09415000)). The data release includes four .csv files related to field observations: UTM coordinates of field transect and vegetation plot locations; vegetation and topography; species codes; and sediment quality.

These data were compiled for a restoration experiment testing the regenerative and functional response of biocrust inoculum reintroduced to a field setting. Regenerative traits measured included measurements of biocrust cover, chlorophyll content, and the roughness of the soil surface. Functional traits measured included nutrient cycling and soil stability. Additionally, these data were compiled for an experiment testing how much soil is lost from different types of ground cover. The data collected was related to ground cover and the amount of soil lost from plots through time. These data were used to inform the conclusions drawn in the accompanying manuscript.