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120 results for “Midwest”
Social-Ecological Dynamics of Recreational Fishery Landscapes: Recreational angler catch and satisfaction in the Midwest, 2018 to 2024
The goal of this dataset is to understand angler information gathering and sharing, technology use, expectation-setting, site choice, and the factors influencing angler satisfaction in rural and urban environments. These data were collected through on-site creel surveys and instantaneous counts of fishing effort and associated angler vehicles. Traditional creel surveys are completed only at the end of an angler's fishing trip. These dual-intercept creel survey data are novel because anglers were intercepted both before and after their fishing trip. This survey design allowed us to collect unbiased estimates of anglers' expected catch. These data can be used to understand the role of angler expectations in angler satisfaction and behavior. Data collection were conducted in two counties in Wisconsin, USA. Vilas County is a primarily rural, forested, and glaciated region with many relatively small lakes. Dane County has a larger urban center (Madison, WI) that is surrounded by agricultural areas. Most of the Dane County lakes surveyed were part of the Yahara chain of lakes: Lakes Mendota, Monona, Wingra, Waubesa, and Kegonsa. Dane county has fewer, larger lakes with greater connectivity to each other. Vilas County was sampled in the summer of 2018, the summer of 2019, and the summer and winter of 2022. Dane County was sampled in the winter and summer of 2022.
Upper Midwest Great Lakes Region Citizen Secchi Data 1938 - 2012
Upper MidwestorGreat Lakes Region Citiizen Secchi Data includes 239,741 citizen Secchi monitoring records (1938 – 2012) from Illinois Volunteer Lake Monitoring Program, Indiana Clean Lakes Program, Iowa Secchi Dip-In Project, Michigan Clean Water Corps, Lakes of Missouri Volunteer Program, Minnesota Citizen Lake Monitoring Program, Ohio Citizen Lake Awareness Program, and Wisconsin Citizen Lake Monitoring Records. Data were obtained from above monitoring groups and merged with the high resolution National Hydrography Dataset (www.nhd.usgs.gov) based on citizen proved latitudeorlongitude coordinates to verify the location of individual lakes and size of lake (hectare). Code used to estimate annual average Secchi depth (m) provided in metadata. These citizen-collected, publically available Secchi depth measurements were collected to answer two questions: (1) what are the long-term trends in lake water quality across a broad geographic region?; (2) how do trends differ as a function of spatial location, size of lake monitored, and when Secchi records were collected. Data collection and analysis were funded by the National Science Foundation (MSB- 1065786, EF-1065818, EF-1065649), NTL-LTER (DEB-0822700), STRIVE grant 2011-W-FS-7 from the Environmental Protection Agency. GLERL contribution number (1703).
LAGOS-NE Shallow Lakes: a dataset of lake variables and multi-scaled ecological context variables used to predict and compare trophic status and TP:CHLa relationships between shallow and non-shallow lakes in the Upper Midwest and Northeastern United States.
We conducted a macroscale study of 2,210 shallow lakes (mean depth ≤ 3m or a maximum depth ≤ 5m) in the Upper Midwestern and Northeastern U.S. We asked: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4,360 non-shallow lakes, and do results differ by hydrologic connectivity class? To answer this question, we assembled the LAGOS-NE Shallow Lakes dataset described herein, a dataset derived from existing LAGOS-NE, LAGOS-DEPTH, and LAGOS-CLIMATE datasets. Response data variables were the median of available summer (e.g., 15 June to 15 September) values of total phosphorus (TP) and chlorophyll a (CHLa). Predictor variables were assembled at two spatial scales for incorporation into hierarchical models. At the local or lake-specific scale (including the individual lake, its inter-lake watershed [iws] or corresponding HU12 watershed), variables included those representing land use/cover, hydrology, climate, morphometry, and acid deposition. At the regional scale (e.g., HU4 watershed), variables included a smaller set of predictor variables for hydrology and land use/cover. The dataset also includes the unique identifier assigned by LAGOS-NE(lagoslakeid); the latitude and longitude of the study lakes; their maximum and mean depths along with a depth classification of Shallow or non-Shallow; connectivity class (i.e., whether a lake was classified as connected (with inlets and outlets) or unconnected (lacking inlets); and the zone id for the HU4 to which each lake belongs. Along with the database, we provide the R scripts for the hierarchical models predicting TP or CHLa (TPorCHL_predictive_model.R), and the TP—CHLa relationship (TP_CHL_CSI_Model.R) for depth and connectivity subsets of the study lakes.
Red Oak Root and Soil Environmental Gradient Study, Midwest U.S., 2022-2023.
Fine root trait and soils data for Quercus rubra L. (northern red oak) sampled along a Midwestern latitudinal gradient. Fourteen sites spanning 5-14 degrees C were sampled. Each sample represents 2 6 cm deep x 5 cm wide soil cores obtained from near the base of a Q. rubra individuals, with 6 sampled plots per site. Plots were located approximately 40 m apart along a linear transect to be at a cluster of Q. rubra individuals. All 14 sites were visited twice in the growing season of 2022: between June 1st and June 21st, and between July 5th and July 21st. Root traits sampled include average diameter, root tissue density, specific root length, branching intensity, and specific respiration rate. A 1 mm diameter limit cut-off was used. These traits were measured in the field (respiration rates) or from output from RhizoVision Explorer image analysis. Traits are associated with the smaller fine root sample used for respiration measurement in the field (~2 g dry weight). Fine root biomass was also obtained by removing all remaining fine roots in the core, drying, and weighing, and then was multiplied by weight-normalized respiration rates to obtain estimates of fine root ecosystem respiration. This data package is complete, but will be associated with data from 4 sites revisited in 2023 to obtain repeat fine root trait measurements and fungal community community metrics.
EPA Eastern Lake Survey original data for the Upper Midwest Region 1984
Overton, W. S., P. Kanciruk, L. A. Hook, J. M. Eilers, D. H. Landers, D. F. BRAKKE, R. A. Linthurst, and M. D. DeHaan. 1986. Characteristics of lakes in the Eastern United States. Vol. 2. Lakes sampled and descriptive statistics for physical and chemical variables. US EPA 600/4-86/007B. 369 p. The Eastern Lake Survey-Phase I (ELS-I), conducted in the fall of 1984, was the first part of a long-term effort by the U.S. Environmental Protection Agency known as the National Surface Water Survey. It was designed to synoptically quantify the acid-base status of surface waters in the United States in areas expected to exhibit low buffering capacity. The effort was in support of the National Acid Precipitation Assessment Program (NAPAP). The survey involved a three-month field effort in which 1612 probability sample lakes and 186 special interest lakes in the northeast, southeast, and upper midwest regions of the United States were sampled. This dataset includes data on 592 lakes in Michigan, Minnesota and Wisconsin. Number of sites: 592
ReFAB 10,000 Year Statistical Estimate of Aboveground Woody Biomass, Midwest US, Level 2
How terrestrial biomass changed before the advent of industrial society is a major gap in our understanding of the Earth's carbon cycle. Here, we archive data used to reconstruct 10,000 years of aboveground woody biomass across the US Upper Midwest using statistical models based on historical forest surveys and fossil pollen assemblages. From our analyses we document a 5,000 year long carbon sink into vegetation, primarily caused by the range expansion of two late-successional species into the region during the late Holocene. The importance of such large slow-growing tree species in storing carbon during the pre-industrial past argues for protecting similar species in wild forests today. This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.
Integrated freshwater abundance and connectivity clusters at the Hydrologic Unit 8 scale for the Midwest and Northeast U.S.A. – freshwater metric variables and k-means cluster assignment
This dataset includes integrated freshwater abundance and connectivity cluster output, principal component scores, and lake, wetland, and stream abundance and connectivity metrics measured at the Hydrologic Unit 8 (HU8) scale for 17 U.S. states in the Midwest and Northeast regions (appr. 1,800,000 km2). The intent of the cluster analysis is to characterize the macroscale patterns of the integrated freshwater landscape that includes lakes, wetlands, and streams and their surface connectivity attributes. We define freshwater connectivity as the permanent surface hydrologic connections that link lakes, wetlands, and streams and measure connectivity as the landscape position of systems within stream networks. Geographic data used in the analysis are in LAGOS-NE-GEO database v. 1.03 (Lake multi-scaled geospatial and temporal database), an integrated, multi-thematic geographic database (Soranno et al. 2015). The integrated freshwater clusters were created through a multi-step process as follows: 1) we quantified multiple freshwater connectivity metrics for lakes, streams, and wetlands separately, 2) we performed principal components analysis (PCA) on the connectivity metric values for each freshwater type to reduce collinearity, and 3) we performed k-means cluster analysis to group spatial units with similar freshwater connectivity characteristics. The resulting freshwater clusters are representations of the macroscale patterns of freshwater abundance and connectivity in the landscape.
Freshwater connectivity clusters for lakes, wetlands, and streams at the Hydrologic Unit 12 scale in the Midwest and Northeast U.S.A. – freshwater metric variables and K-means cluster assignment
This dataset includes freshwater connectivity cluster output and principal component scores for lakes, wetlands, and streams measured at the Hydrologic Unit 12 (HU12) scale in 17 U.S. states in the Midwest and Northeast regions (appr. 1,800,000 km2). The intent of the cluster analysis is to characterize the macroscale patterns of freshwater connectivity attributes. We define freshwater connectivity as the permanent surface hydrologic connections that link lakes, wetlands, and streams and measure connectivity as the landscape position of systems within stream networks. Geographic data used in the analysis are in LAGOS-NE-GEO database v. 1.03 (Lake multi-scaled geospatial and temporal database), an integrated, multi-thematic geographic database (Soranno et al. 2015). Freshwater connectivity clusters were created separately for lakes, wetlands, and streams through a multi-step process as follows: 1) we quantified multiple freshwater connectivity metrics, 2) we performed principal components analysis (PCA) on the connectivity metric values for each freshwater type to reduce collinearity, and 3) we performed k-means cluster analysis to group spatial units with similar freshwater connectivity characteristics. The resulting freshwater clusters are representations of the macroscale patterns of lake, wetland, and stream connectivity in the landscape.
Lake chloride concentrations and model predictions for 49,432 lakes in the Midwest and Northeast United States.
Lakes in the Midwest and Northeast United States are at risk of anthropogenic chloride contamination, but we have little knowledge of the prevalence and spatial distribution of the problem. The majority of salt pollution in north temperate regions stems from road salt application but other chloride sources include water softeners, synthetic fertilizers, and livestock excretion. Although chloride contamination of lakes is well documented, it is unknown how many lakes are at risk of long-term salinization. We used a quantile regression forest to leverage information from 2,773 lakes to predict the chloride concentration of all 49,432 lakes greater than 4 ha in a 17-state area. The QRF used 22 predictor variables, which included lake morphometry characteristics, watershed land use, and distance to the nearest interstate and road. Model predictions had an r2 of 0.94 for all chloride observations, and 0.87 for predictions of the mean chloride concentration observed at each lake.
Midwest U.S. Fertilizer Data, 1985-2015
Sulfur, as an essential nutrient for plant growth, has increasingly been used in fertilizer applications for many crops. This increase is coincident with declines in atmospheric sulfur deposition in response to air quality improvements in the United States and Europe. Here, we provide data for sulfur fertilizer sales by mass, as a proxy for fertilizer application, and provide data to estimate total atmospheric sulfur deposition across the Midwestern United States, a 12-state region that includes: Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. In addition, we provide data on other major nutrient fertilizers, including nitrogen, phosphorus and potassium, to compare with sulfur. Fertilizer data are from the American Association for Plant Food Control Officials (AAPFCO) and are aggregated from the county-level to the 12-state Midwestern region for the period of 1985-2015.
Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest
Throughout most of the northern hemisphere, snow cover decreased in almost every winter month from 1967 to 2012. Because snow is an effective insulator, snow cover loss has likely enhanced soil freezing and the frequency of soil freeze–thaw cycles, which can disrupt soil nitrogen dynamics including the production of nitrous oxide (N2O). We used replicated automated gas flux chambers deployed in an annual cropping system in the upper Midwest US for three winters (December–March, 2011–2013) to examine the effects of snow removal and additions on N2O fluxes. Diminished snow cover resulted in increased N2O emissions each year; over the entire experiment, cumulative emissions in plots with snow removed were 69% higher than in ambient snow control plots and 95% higher than in plots that received additional snow (P < 0.001). Higher emissions coincided with a greater number of freeze–thaw cycles that broke up soil macroaggregates (250–8000 µm) and significantly increased soil inorganic nitrogen pools. We conclude that winters with less snow cover can be expected to accelerate N2O fluxes from agricultural soils subject to wintertime freezing.
Data from: Long-term nitrous oxide fluxes in annual and perennial agricultural and unmanaged ecosystems in the upper Midwest USA
Differences in soil nitrous oxide (N2O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N2O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn–soybean–wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N2O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N2O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30–80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop × management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N2O-N ha−1 yr−1 and were best predicted by IPCC Tier 1 and ΔEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil inline image pools (r2 = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N2O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes.
Figures 3–6. Adult male genitalia. 3 in A new species of Paranthrene Hübner (Lepidoptera: Sesiidae) from the northern midwest United States
Figures 3–6. Adult male genitalia. 3) Paranthrene sogaardi. new species 4) Paranthrene tabaniformis. 5) Paranthrene sogaardi new species aedeagus. 6) Paranthrene tabaniformis aedeagus.
Figures 7–10. Paranthrene sogaardi new species. 7 in A new species of Paranthrene Hübner (Lepidoptera: Sesiidae) from the northern midwest United States
Figures 7–10. Paranthrene sogaardi new species. 7) Dorsal view. 8) Lateral view. 9) Frons. 10) Michigan collection site of Paranthrene tabaniformis.
Figure 2 in Trichoderma: biological control efficiency and perspectives for the Brazilian Midwest states and Tocantins
Figure 2. Interaction mechanisms of Trichoderma spp. and phytopathogens. (A) Yellow, red, and blue correspond to the antagonistic actions of Trichoderma from contact with phytopathogens; (B) Contact of fungal hyphae (Trichoderma spp. in green and phytopathogens in orange). Elements in pink correspond to the process of competition for space (long base) and nutrients (rectangles). Blue circles correspond to the metabolites produced by Trichoderma. Yellow stars represent the enzymes produced by Trichoderma in the mycoparasitic process.
Figure7 in Habitat-Based Breeding Strategies of Female Hoplobatrachus occipitalis (Anura: Dicroglossidae) from Daloa Department, Midwest of Côte d'Ivoire
Figure7. Regression between female size (SVL) and absolute fecundity (Fa) in Hoplobatrachus occipitalis from Fatiga and Zaliohouan in Daloa Department
Figure2 in Habitat-Based Breeding Strategies of Female Hoplobatrachus occipitalis (Anura: Dicroglossidae) from Daloa Department, Midwest of Côte d'Ivoire
Figure2. Size (SVL) frequency distribution of female Hoplobatrachus occipitalis from Fatiga and Zaliohouan in Daloa Department
Figure6 in Habitat-Based Breeding Strategies of Female Hoplobatrachus occipitalis (Anura: Dicroglossidae) from Daloa Department, Midwest of Côte d'Ivoire
Figure6. Spatial variability in egg diameter of female Hoplobatrachus occipitalis from Fatiga and Zaliohouan in Daloa Department
Figure5 in Habitat-Based Breeding Strategies of Female Hoplobatrachus occipitalis (Anura: Dicroglossidae) from Daloa Department, Midwest of Côte d'Ivoire
Figure5. Egg diameter frequency distribution of female Hoplobatrachus occipitalis from Fatiga and Zaliohouan in Daloa Department.
Figure4 in Habitat-Based Breeding Strategies of Female Hoplobatrachus occipitalis (Anura: Dicroglossidae) from Daloa Department, Midwest of Côte d'Ivoire
Figure4. Spatial variability in gonado-somatic index of female Hoplobatrachus occipitalis from Fatiga and Zaliohouan in Daloa Department
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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