These data describe water chemistry and fish, macroinvertebrate and vegetation communities within recently restored, historically-restored, and unrestored wetland management units of the Shiawassee National Wildlife Refuge (SNWR; Michigan, USA). Data were collected in 2021 according to protocols and methods described in Conrad et al. 2022. These methods developed through previous years of fieldwork at SNWR and are similar to those implemented in the Great Lakes Coastal Wetlands Monitoring Program (CWMP) (Greenberg et al. 2021; Lugten et al. 2020; Uzarski et al. 2016). Water chemistry data include either field or lab-derived measurements including temperature, pH, turbidity, conductivity, dissolved oxygen, ammonia, chloride, sulfate, nitrite, nitrate, silicon dioxide, soluble reactive phosphorus, total phosphorus, total Kjeldahl nitrogen, suspended solids, and fluoride. Biological community data include taxa identifications and abundance estimates for macroinvertebrates, fish, and vegetation. Taxa are identified to the species level when practicable, with data derived from floral surveys, electrofishing, fyke net sets and macroinvertebrate dip net sampling. These data may serve as indicators of system quality or health, enabling users to conduct comparative analyses among different wetland areas and, in conjunction with cross referenced datasets, make comparisons across years.

Data represent physical (water quality) and biological (fish, macroinvertebrate, and vegetation community) collections as indicators for Pool 1A and the Maankiki Marsh North and South units at the Shiawassee National Wildlife Refuge in Saginaw, MI, USA. The Maankiki North and South units were recently reconnected to the Shiawassee River in 2018, whereas Pool 1A represents a historically reconnected wetland. All data were collected in 2020.

Data represent physical (water quality) and biological (fish, macroinvertebrate, and vegetation community) collections as indicators for Pool 1A and the Maankiki Marsh North and South units at the Shiawassee National Wildlife Refuge in Saginaw, MI, USA. The Maankiki North and South units were recently reconnected to the Shiawassee River in 2018, whereas Pool 1A represents a historically reconnected wetland. All data were collected in 2020.

Rivers and Streams data for the National Aquatic Resource Surveys. This dataset is associated with the following publication: Herlihy, A., J. Sifneos, R. Hughes, D. Peck, and R. Mitchell. The Relation of Lotic Fish and Benthic Macroinvertebrate Condition Indices to Environmental Factors Across the Conterminous USA. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 112: 105958, (2020).

Rivers and Streams data for the National Aquatic Resource Surveys. This dataset is associated with the following publication: Herlihy, A., J. Sifneos, R. Hughes, D. Peck, and R. Mitchell. The Relation of Lotic Fish and Benthic Macroinvertebrate Condition Indices to Environmental Factors Across the Conterminous USA. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 112: 105958, (2020).

Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains three datasets for adult White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. The primary purpose for this sampling was to capture White Sturgeon and implant acoustic telemetry tags for a tracking project. Therefore, the data are useful for determining when and where White Sturgeon were captured, but they should not be used to determine actual distribution or abundance. SJR_Adult_WST_Set contains data from a sampling program using various methods to catch adult White Sturgeon in the San Joaquin River. Sets were made at targeted locations primarily from March-May in 2012-2018 (other dates were occasionally sampled). SJR_Adult_WST_Catch contains data for individual fish caught via gillnets, trammel nets, setlines, or angling in the San Joaquin River. Species and fork length were recorded for all fish. For White Sturgeon, girth, maturation, tag, and surgery information are provided. SJR_Fish_Taxonomy contains data for fish codes used in the Catch datafile. For each species that was captured, the Species codes are listed with the corresponding Interagency Ecological Program code, common name, taxonomy (Phylum, Class, Order, Family, Genus, and Species), and whether or not the species is native to the region.

The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains three datasets for juvenile White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. After two years of this experimental sampling program, it was discontinued due to low catches of White Sturgeon. SJR_Juvenile_WST_Set Data This dataset contains data on an experimental sampling program using trammel nets and setlines to catch juvenile White Sturgeon in the San Joaquin River. Sets were made at targeted locations from November-January in 2016 and 2017. One White Sturgeon (1000 mm fork length) was captured in a trammel net in 2016. SJR_Juvenile_WST_Catch Data This dataset contains data for individual fish caught in trammel nets or setlines in the San Joaquin River. Species and fork length were recorded for all fish. For White Sturgeon, girth, maturation, and tag information are provided. SJR_Fish_Taxonomy Data This dataset contains data for fish codes used in the Catch datafile. For each species that was captured, the Species codes are listed with the corresponding Interagency Ecological Program code, common name, taxonomy (Phylum, Class, Order, Family, Genus, and Species), and whether or not the species is native to the region.

Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains two datasets for White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. The objective of this sampling to was determine if White Sturgeon were spawning in the San Joaquin River and to explore where and when spawning occurred, within areas where adult White Sturgeon were known to congregate during the suspected spawning season. SJR_Egg_WST_Set Data This dataset contains data on egg mat sets used to document White Sturgeon spawning in the San Joaquin River. Sets were made at non-random locations from February to May in 2011-2018. In 2017, additional “blitz” sets were used in areas where eggs were detected. Details about set location, timing, and environmental conditions are included, along with the total number eggs of White Sturgeon and other non-sturgeon eggs. SJR_Egg_WST_Catch Data This dataset contains data specific to eggs found in egg mat nets in the San Joaquin River. Across all years, the diameter of eggs (or groups of eggs) were recorded. In 2011 and 2012, efforts were made to describe the developmental stage of White Sturgeon eggs and estimates of spawning timing were sometimes calculated.

Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains three datasets for larval White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. SJR_Larval_WST_Set Data: This dataset contains data on an experimental sampling program using boat-mounted drift nets (D-frame nets), a large drift net attached to a stationary pontoon (pontoon net), and otter trawls to catch larval White Sturgeon in the San Joaquin River. Sets were made at targeted locations from March-July in 2013, 2015, 2016, and 2017. A total of ten White Sturgeon were captured in 2016 and 11 in 2017, all with D-frame driftnets. SJR_Larval_WST_Catch Data: This dataset contains data for individual fish caught in the San Joaquin River. Species and fork length were recorded for most individuals. SJR_Fish_Taxonomy Data: This dataset contains data for fish codes used in the Catch datafile. For each species that was captured, the Species codes are listed with the corresponding Interagency Ecological Program code, common name, taxonomy (Phylum, Class, Order, Family, Genus, and Species), and whether or not the species is native to the region.

Forest vegetation provides an integrated measure of terrestrial ecosystem health by expressing information about the collective suite of drivers and stressors which act upon it. These include climate, disturbance, browse, and invasive species. We developed a comprehensive forest monitoring protocol to detect change in the nine Great Lakes Network parks. Monitoring is conducted on a nine-year rotation, with each of the parks sampled over the course of one summer, once every nine years. Site locations were selected to ensure that they are random, but also spatially balanced throughout the parks. At each sampling site, we collect extensive data on trees (including saplings and seedlings), shrubs, herbs, coarse woody material, and browse. We also carry out assessments of tree health. Data are housed in a Microsoft Access database and published annually in an open-source, machine readable format. Quality control measures include both on site assessments of accuracy, as well as extensive data checking via automated parsing routines. Finally, reports from monitoring are produced on a regular basis and include internal National Park Service technical reports and externally reviewed manuscripts for publication in peer-reviewed journals. All data are publicly available.