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79 records · Page 5Linked to original sources
USGS1956

Water levels in observation wells in Nebraska during 1955

The objective of the dbservation-well program in Nebraska is to provide an evaluation of the status of the ground-water supplies. Many uses for water-.level data are known but not all potential uses can be forseen. Among the important uses are the following: To indicate the status of ground water in storage or in transit and the availability of supplies. To show the trend of ground-water supplies and the outlook for the future. To estimate or forcast the base flow of streams. To indicate areas in which the water level is approaching too close to the land surface (water-logging) or is receding toward economic limits of lift or tow rd impairment by water of poor quality. To provide long-term vidence for evaluating the effectiveness of land-management and water...0 nservation programs in relation to water conservation actually of ected, and for use in basin or "watershed" studies. To provide longterm ontinuous records to serve as a framework to which short-term records collected during intensive investigation may be related. The water level in an observation well functions as a gage to indicate the position of the water table o The water table is defined as the upper surface of the zone of saturation except where that surface is formed by overlying impermeable materials. The water table is also the boundary between the zone of saturation and the zone of aeration. It is not a level surface but is a sloping surface that has many irregularities, and it often conforms in a general way to the land surface. The irregularities are caused by several factors. In places where the recharge to the ground-water reservoir is exceptionally large, the water-table may rise to form a mound from which the water slowly spreads. Depressions or troughs in the water table indicate places where the ground water is discharging, as along streams that are below the normal level of the water table, or indicate places where water is being withdrawn by wells or vegetation. The several factors that influence the water table vary in fact and amount from time to time because of changes in weather and the water requirements of vegetation and man; thus, the water table is nearly always rising or falling. The fluctuations of the water table are shown by the changes in water levels in wells. Thus, the rate and amount of the fluctuation of the water table can be ascertained by observing the water levels in wells, and the magnitude of the several factors effecting the position of the water table can be interpreted by analyzing the water—level data. Water-level measurements are given, in this report, in feet below the land surface at the well site. Water levels that are above land surface are preceded by a plus (+) sign, whereas those below land surface have no sign but are understood to be minus (-). The words "land-surface datum" are abbreviated "lsd" in tables of this report. The altitude above mean sea level (msl) of the land surface at many of the well sites has been determined and is included in the tables of this report. Lower case letters which appear in the table of water level measurements indicate the following: 6', nearby well pumped recently; f, dry; g, measured by outside agency; and j, frozen. Twenty-.six observation wells in Nebraska are equipped with recording gages. Each recording gage produces a continuous graph of water-level fluctuations in the well. Only the lowest water level on the last day of record in each month, as recorded by the gage, is given in this report; the complete record is on file in the office of the U. S. Geological Survey in Lincoln, Nebr.

Nebraska↗
USGS2014

Area- and depth- weighted averages of selected SSURGO variables for the conterminous United States and District of Columbia

This digital data release consists of seven data files of soil attributes for the United States and the District of Columbia. The files are derived from National Resources Conservations Service’s (NRCS) Soil Survey Geographic database (SSURGO). The data files can be linked to the raster datasets of soil mapping unit identifiers (MUKEY) available through the NRCS’s Gridded Soil Survey Geographic (gSSURGO) database ( http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628 ). The associated files, named DRAINAGECLASS, HYDRATING, HYDGRP, HYDRICCONDITION, LAYER, TEXT, and WTDEP are area- and depth-weighted average values for selected soil characteristics from the SSURGO database for the conterminous United States and the District of Columbia. The SSURGO tables were acquired from the NRCS on March 5, 2014. The soil characteristics in the DRAINAGE table are drainage class (DRNCLASS), which identifies the natural drainage conditions of the soil and refers to the frequency and duration of wet periods. The soil characteristics in the HYDRATING table are hydric rating (HYDRATE), a yes/no field that indicates whether or not a map unit component is classified as a "hydric soil". The soil characteristics in the HYDGRP table are the percentages for each hydrologic group per MUKEY. The soil characteristics in the HYDRICCONDITION table are hydric condition (HYDCON), which describes the natural condition of the soil component. The soil characteristics in the LAYER table are available water capacity (AVG_AWC), bulk density (AVG_BD), saturated hydraulic conductivity (AVG_KSAT), vertical saturated hydraulic conductivity (AVG_KV), soil erodibility factor (AVG_KFACT), porosity (AVG_POR), field capacity (AVG_FC), the soil fraction passing a number 4 sieve (AVG_NO4), the soil fraction passing a number 10 sieve (AVG_NO10), the soil fraction passing a number 200 sieve (AVG_NO200), and organic matter (AVG_OM). The soil characteristics in the TEXT table are percent sand, silt, and clay (AVG_SAND, AVG_SILT, and AVG_CLAY). The soil characteristics in the WTDEP table are the annual minimum water table depth (WTDEP_MIN), available water storage in the 0-25 cm soil horizon (AWS025), the minimum water table depth for the months April, May and June (WTDEPAMJ), the available water storage in the first 25 centimeters of the soil horizon (AWS25), the dominant drainage class (DRCLSD), the wettest drainage class (DRCLSWET), and the hydric classification (HYDCLASS), which is an indication of the proportion of the map unit, expressed as a class, that is "hydric", based on the hydric classification of a given MUKEY. (See Entity_Description for more detail). The tables were created with a set of arc macro language (aml) and awk (awk was created at Bell Labsin the 1970s and its name is derived from the first letters of the last names of its authors – Alfred Aho, Peter Weinberger, and Brian Kernighan) scripts. Send an email to mewieczo@usgs.gov to obtain copies of the computer code (See Process_Description.) The methods used are outlined in NRCS's "SSURGO Data Packaging and Use" (NRCS, 2011). The tables can be related or joined to the gSSURGO rasters of MUKEYs by the item 'MUKEY.' Joining or relating the tables to a MUKEY grid allows the creation of grids of area- and depth-weighted soil characteristics. A 90-meter raster of MUKEYs is provided which can be used to produce rasters of soil attributes. More detailed resolution rasters are available through NRCS via the link above.

Data Series↗
USGS2016

Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada

Changes in vegetation and snow cover may lead to feedbacks to climate through changes in surface albedo and energy fluxes between the land and atmosphere. In addition to these biogeophysical feedbacks, biogeochemical feedbacks associated with changes in carbon (C) storage in the vegetation and soils may also influence climate. Here, using a transient biogeographic model (ALFRESCO) and an ecosystem model (DOS-TEM), we quantified the biogeophysical feedbacks due to changes in vegetation and snow cover across continuous permafrost to non-permafrost ecosystems in Alaska and northwest Canada. We also computed the changes in carbon storage in this region to provide a general assessment of the direction of the biogeochemical feedback. We considered four ecoregions, or Landscape Conservations Cooperatives (LCCs; including the Arctic, North Pacific, Western Alaska, and Northwest Boreal). We examined the 90 year period from 2010 to 2099 using one future emission scenario (A1B), under outputs from two general circulation models (MPI-ECHAM5 and CCCMA-CGCM3.1). We found that changes in snow cover duration, including both the timing of snowmelt in the spring and snow return in the fall, provided the dominant positive biogeophysical feedback to climate across all LCCs, and was greater for the ECHAM (+3.1 W m −2 decade −1 regionally) compared to the CCCMA (+1.3 W m −2 decade −1 regionally) scenario due to an increase in loss of snow cover in the ECHAM scenario. The greatest overall negative feedback to climate from changes in vegetation cover was due to fire in spruce forests in the Northwest Boreal LCC and fire in shrub tundra in the Western LCC (−0.2 to −0.3 W m −2 decade −1 ). With the larger positive feedbacks associated with reductions in snow cover compared to the smaller negative feedbacks associated with shifts in vegetation, the feedback to climate warming was positive (total feedback of +2.7 W m −2 decade regionally in the ECHAM scenario compared to +0.76 W m −2 decade regionally in the CCCMA scenario). Overall, increases in C storage in the vegetation and soils across the study region would act as a negative feedback to climate. By exploring these feedbacks to climate, we can reach a more integrated understanding of the manner in which climate change may impact interactions between high-latitude ecosystems and the global climate system.

Environmental Research Letters↗
USGS2024

Multinational evaluation of genetic diversity indicators for the Kunming-Montreal Global Biodiversity Framework

Under the recently adopted Kunming-Montreal Global Biodiversity Framework, 196 Parties committed to reporting the status of genetic diversity for all species. To facilitate reporting, three genetic diversity indicators were developed, two of which focus on processes contributing to genetic diversity conservation: maintaining genetically distinct populations and ensuring populations are large enough to maintain genetic diversity. The major advantage of these indicators is that they can be estimated with or without DNA-based data. However, demonstrating their feasibility requires addressing the methodological challenges of using data gathered from diverse sources, across diverse taxonomic groups, and for countries of varying socio-economic status and biodiversity levels. Here, we assess the genetic indicators for 919 taxa, representing 5271 populations across nine countries, including megadiverse countries and developing economies. Eighty-three percent of the taxa assessed had data available to calculate at least one indicator. Our results show that although the majority of species maintain most populations, 58% of species have populations too small to maintain genetic diversity. Moreover, genetic indicator values suggest that IUCN Red List status and other initiatives fail to assess genetic status, highlighting the critical importance of genetic indicators.

Ecology Letters↗
USGS2021

Evaluating establishment of conservation practices in the Conservation Reserve Program across the central and western United States

The U.S. Department of Agriculture's Conservation Reserve Program (CRP) is one of the largest private lands conservation programs in the United States, establishing perennial vegetation on environmentally sensitive lands formerly in agricultural production. Over its 35 year existence, the CRP has evolved to include diverse conservation practices (CPs) while concomitantly meeting its core goals of reducing soil erosion, improving water quality, and providing wildlife habitat. Ongoing threats to grasslands and decreased CRP acreage highlighted the need for a national evaluation of the effectiveness in providing the program's intended benefits. To address this need, we conducted edge-of-field surveys of erosional features, vegetation, and soil cover on 1 786 fields across 10 CPs and 14 central and western states from 2016 to 2018. We grouped practices into three types (grassland, wetland, and wildlife) and states into six regions for analysis. Across practice types, ≥99% of fields had no evidence of rills, gullies, or pedestaling from erosion, and 91% of fields had <20% bare soil cover, with region being the strongest predictor of bare soil cover. Seventy-nine percent of fields had ≥50% grass cover, with cover differing by practice type and region. Native grass species were present on more fields in wildlife and wetland practices compared to grassland practices. Forb cover >50% and native forb presence occurred most frequently in wildlife practices, with region being the strongest driver of differences. Federally listed noxious grass and forb species occurred on 23% and 61% of fields, respectively, but tended to constitute a small portion of cover in the field. Estimates from edge-of-field surveys and in-field validation sampling were strongly correlated, demonstrating the utility of the edge-of-field surveys. Our results provide the first national-level assessment of CRP establishment in three decades, confirming that enrolled wildlife and wetland practices often have diverse perennial vegetation cover and very few erosional features.

Arizona, California, Colorado, Iowa, Idaho, Kansas↗
USGS2016

Shifting currents: Progress, setbacks, and shifts in policy and practice

The Wisconsin Academy’s initial Waters of Wisconsin project (WOW I) facilitated a statewide conversation between 2000 and 2003 around one main question: How can we ensure healthy aquatic ecosystems and clean, abundant water supplies for tomorrow’s Wisconsin? Robust participation in this conversation underscored the important role citizens have in the stewardship of our waters, and we found enthusiastic support for farsighted policies—based on sound science—to manage our water legacy. Overall, we found that Wisconsinites cherish water and see our waters as essential to our way of life in Wisconsin. Nationally, our state ranks 25th in land area but has the fourth-highest area covered by water. Wisconsin is 20th in population but is second only to Florida in the number of fishing licenses sold each year. Clean water supports billions of dollars’ worth of economic activity through tourism, agriculture, and industry. From the Northwoods cabin to the Port of Milwaukee to the Wisconsin Dells, water shapes our state’s identity. Our tradition of safeguarding Wisconsin’s waters is grounded in values such as responsibility to family and future generations, respect for land and wildlife, protecting public health and safety, and caring for water as a common good, as articulated in the state’s Public Trust Doctrine (see page 9). These deeply held values have also shaped a conservation ethic, and its legacy has served many generations who depend upon and enjoy the waters of the state. Through WOW I, we identified the need to overcome the institutional and disciplinary separation of science, policy, and management protocols through a more integrated approach to water management. WOW also affirmed that the Wisconsin Department of Natural Resources (DNR) and other public agencies play a critical role in sound scientific application, citizen participation, and the practical implementation of policy while balancing public and private interests toward the goal of a clean water future. More than a decade has passed since our first statewide WOW conversation and the report that captured recommendations from its participants: Waters of Wisconsin: The Future of Our Aquatic Ecosystems and Resources. Drawing from a diverse and growing set of stakeholders from across the state, the Wisconsin Academy initiated a new conversation in 2012 (known as WOW II) to assess progress in regard to our 2003 recommendations. We also sought to review the status of waters in Wisconsin today. The result of this renewed conversation is Shifting Currents: Progress, Setbacks, and Shifts in Policy and Practice. The new report assesses progress in brief, and explores in greater depth the continuing and emerging challenges to water quality, supply, and aquatic ecosystems in Wisconsin. In this report, we first review the context and frameworks for public decision-making about water and then examine some of the root causes—or “drivers”—and ecological stressors that underlie many of the symptoms we see in the form of pollution or ecosystem degradation in Wisconsin. This is followed by a summary of current water issues, many of which had been identified in the 2003 report and remain relevant today. We examine progress since 2003 but also setbacks, and discuss issues that we are likely to continue to face in the coming decades, including controlling agricultural runoff, mitigating climate change and grappling with its effects on the state’s waters, protecting groundwater from bacterial contamination and other pollutants, and preventing groundwater depletion. We also attempt to anticipate issues on the horizon. We offer a deeper look at some particular challenges, such as phosphorus pollution and groundwater contamination. We then consider the current decision-making framework and how it is shaping our capacity to respond to water challenges in Wisconsin. Finally, we offer recommendations and identify opportunities to safeguard Wisconsin’s waters in the decades ahead. From its inception, the Wisconsin Academy’s Waters of Wisconsin Initiative has brought together a diverse community of experts from across the state and from varied fields and areas of interest, to address challenges and seize opportunities related to our precious waters. We have done so as a matter of both principle and practical reality: the state of our waters reflects the ways we interact not only with them, but also with one another and our institutions. The WOW Initiative has aimed to provide guidance for Wisconsin citizens in sustaining the health of our aquatic ecosystems and the resilience of our water supplies over the long term.

Report↗
USGS2004

Demographic estimation methods for plants with dormancy

Demographic studies in plants appear simple because unlike animals, plants do not run away. Plant individuals can be marked with, e.g., plastic tags, but often the coordinates of an individual may be sufficient to identify it. Vascular plants in temperate latitudes have a pronounced seasonal life–cycle, so most plant demographers survey their study plots once a year often during or shortly after flowering. Life–states are pervasive in plants, hence the results of a demographic study for an individual can be summarized in a familiar encounter history, such as 0VFVVF000. A zero means that an individual was not seen in a year and a letter denotes its state for years when it was seen aboveground. V and F here stand for vegetative and flowering states, respectively. Probabilities of survival and state transitions can then be obtained by mere counting. Problems arise when there is an unobservable dormant state, i.e., when plants may stay belowground for one or more growing seasons. Encounter histories such as 0VF00F000 may then occur where the meaning of zeroes becomes ambiguous. A zero can either mean a dead or a dormant plant. Various ad hoc methods in wide use among plant ecologists have made strong assumptions about when a zero should be equated to a dormant individual. These methods have never been compared among each other. In our talk and in Kéry et al. (submitted), we show that these ad hoc estimators provide spurious estimates of survival and should not be used. In contrast, if detection probabilities for aboveground plants are known or can be estimated, capturerecapture (CR) models can be used to estimate probabilities of survival and state–transitions and the fraction of the population that is dormant. We have used this approach in two studies of terrestrial orchids, Cleistes bifaria (Kéry et al., submitted) and Cypripedium reginae (Kéry & Gregg, submitted) in West Virginia, U.S.A. For Cleistes, our data comprised one population with a total of 620 marked ramets over 10 years, and for Cypripedium , two populations with 98 and 258 marked ramets over 11 years. We chose the ramet (= single stem or shoot) as the demographic unit of our study since there was no way distinguishing among genets (genet = genetical individual, i.e., the “individual” that animal ecologists are mostly concerned with). This will introduce some non–independence into the data, which can nevertheless be dealt with easily by correcting variances for overdispersion. Using ramets instead of genets has the further advantage that individuals can be assigned to a state such as flowering or vegetative in an unambiguous manner. This is not possible when genets are the demographic units. In all three populations, auxiliary data was available to show that detection probability of aboveground plants was m 0.995 We fitted multistate models in program MARK by specifying three states (D, V, F), even though the dormant state D does not occur in the encounter histories. Detection probability is fixed at 1 for the vegetative (V) and the flowering state (F) and at zero for the dormant state (D). Rates of survival and of state transitions as well as slopes of covariate relationships can be estimated and LRT or the AIC machinery be used to select among models. To estimate the fraction of the population in the unobservable dormant state, the encounter histories are collapsed to 0 (plant not observed aboveground) and 1 (plant observed aboveground). The Cormack–Jolly–Seber model without constraints on detection probability is used to estimate detection probability, the complement of which is the estimated fraction of the population in the dormant state. Parameter identifiability is an important issue in multi state models. We used the Catchpole–Morgan–Freeman approach to determine which parameters are estimable in principle in our multi state models. Most of 15 tested models were indeed estimable with the notable exception of the most general model, which has fully interactive state- and time-dependent survival and state transition rates. This model would become identifiable if at least some plants would be excavated in years when they do not show up aboveground. Our analyses for three analyzed populations of Cleistes and Cypripedium yielded annual ramet survival rates ranging from 0.86–0.96. Estimates of the average fraction dormant ranged from 0.02–0.30, but with up to half a population in the dormant state in some years. Ultrastructural modeling enables interesting hypotheses to be tested about the relationships of demographic rates with climatic covariates for instance. Such covariate modeling makes the CR approach particularly interesting for evolutionary–ecological questions about, e.g., the adaptive significance of the dormant state.

Animal Biodiversity and Conservation↗