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USGS2011

Looking beyond fertilizer: Assessing the contribution of nitrogen from hydrologic inputs and organic matter to plant growth in the cranberry agroecosystem

Even though nitrogen (N) is a key nutrient for successful cranberry production, N cycling in cranberry agroecosystems is not completely understood. Prior research has focused mainly on timing and uptake of ammonium fertilizer, but the objective of our study was to evaluate the potential for additional N contributions from hydrologic inputs (flooding, irrigation, groundwater, and precipitation) and organic matter (OM). Plant biomass, soil, surface and groundwater samples were collected from five cranberry beds (cranberry production fields) on four different farms, representing both upland and lowland systems. Estimated average annual plant uptake (63.3 ± 22.5 kg N ha −1 year −1 ) exceeded total average annual fertilizer inputs (39.5 ± 11.6 kg N ha −1 year −1 ). Irrigation, precipitation, and floodwater N summed to an average 23 ± 0.7 kg N ha −1 year −1 , which was about 60% of fertilizer N. Leaf and stem litterfall added 5.2 ± 1.2 and 24.1 ± 3.0 kg N ha −1 year −1 respectively. The estimated net N mineralization rate from the buried bag technique was 5 ± 0.2 kg N ha −1 year −1 , which was nearly 15% of fertilizer N. Dissolved organic nitrogen represented a significant portion of the total N pool in both surface water and soil samples. Mixed-ion exchange resin core incubations indicated that 80% of total inorganic N from fertilizer, irrigation, precipitation, and mineralization was nitrate, and approximately 70% of recovered inorganic N from groundwater was nitrate. There was a weak but significant negative relationship between extractable soil ammonium concentrations and ericoid mycorrhizal colonization (ERM) rates ( r = −0.22, P < 0.045). Growers may benefit from balancing the N inputs from hydrologic sources and OM relative to fertilizer N in order to maximize the benefits of ERM fungi in actively mediating N cycling in cranberry agroecosystems.

Nutrient Cycling in Agroecosystems↗

USGS2002

A prototype drought monitoring system integrating climate and satellite data

Droughts are natural hazards with varying patterns in space, time, and intensity. Their dynamic character challenges our ability in planning, predicting, monitoring, and providing relief to affected areas. Because of the spatial and temporal variability and multiple impacts of droughts, we need to improve the tools and data available for mapping and monitoring this phenomenon on all scales. A team of researchers from the US Geological Survey’s EROS Data Center, the National Drought Mitigation Center, and the High Plains Regional Climate Center are developing methods for regional-scale mapping and monitoring drought conditions for the conterminous U.S. Currently in its first year, the project is focusing on developing a prototype model for the central U.S. The ultimate goal of the project is to deliver timely geo-referenced information (in the form of maps and data) about areas where the vegetation is impacted by drought, using the Internet as the primary delivery mechanism. Data collected from the Advanced Very High Resolution Radiometer (AVHRR) sensor provide synoptic, near real time measurements of surface conditions. Previous studies have established significant relationships between climate variables and satellite-derived vegetation indices over non-irrigated croplands and grasslands. We are researching methods for integrating information provided by satellite-derived metrics on seasonal vegetation performance and climate-based drought indicators to produce a timely and spatially-detailed drought monitoring product. Eventually, this information, coupled with map products of key drought indicators, will be available to many end users for making critical and timely decisions, from farm to regional scale.

Conference Paper↗

USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗

USGS1984

Acute toxicity of diazinon is similar for eight stocks of bobwhite

Nine-week-old bobwhite ( Colinus virginianus ) from eight different game farms were tested for their sensitivity to an acute oral exposure of technical-grade diazinon (phosphorothioic acid O,O -diethyl- O -[6-methyl-2-(l-methylethyl) -4-pyrimidinyl]ester). Extraneous variables associated with interlaboratory differences in husbandry were eliminated by incubating eggs and rearing chicks to test age for all stocks simultaneously in the same facilities at the Patuxent Wildlife Research Center. Under this single set of conditions, the responses of the eight stocks of bobwhite to diazinon were statistically inseparable, with LD 50 values varying from 13 mg/kg (95% confidence interval, 8–21 mg/kg) to 17 mg/kg (95% confidence interval, 11–25 mg/kg). The pooled LD 50 for the eight stocks was 14.7 mg/kg (95% confidence interval, 13.1–16.5 mg/kg).

Environmental Toxicology and Chemistry↗

USGS2015

Paleoreconstruction of organic carbon inputs to an oxbow lake in the Mississippi River watershed: Effects of dam construction and land use change on regional inputs

We use a dated sediment core from Lake Whittington (USA) in the lower Mississippi River to reconstruct linkages in the carbon cycling and fluvial sediment dynamics over the past 80 years. Organic carbon (OC) sources were characterized using bulk (δ 13 C, ramped pyrolysis-oxidation (PyrOx) 14 C, δ 15 N, and TN:OC ratios) and compound-specific (lignin phenols and fatty acids, including δ 13 C and 14 C of the fatty acids) analyses. Damming of the Missouri River in the 1950s, other hydrological modifications to the river, and soil conservation measures resulted in reduced net OC export, in spite of increasing OC concentrations. Decreasing δ 13 C values coincided with increases in δ 15 N, TN:OC ratios, long-chain fatty acids, and lignin-phenol concentrations, suggesting increased inputs of soil-derived OC dominated by C 3 vegetation, mainly resulting from changes in farming practices and crop distribution. However, ramped PyrOx 14 C showed no discernible differences downcore in thermochemical stability, indicating a limited impact on soil OC turnover.

Mississippi↗

USGS2018

Raptor interactions with wind energy: Case studies from around the world

The global potential for wind power generation is vast, and the number of installations is increasing rapidly. We review case studies from around the world of the effects on raptors of wind-energy development. Collision mortality, displacement, and habitat loss have the potential to cause population-level effects, especially for species that are rare or endangered. The impact on raptors has much to do with their behavior, so careful siting of wind-energy developments to avoid areas suited to raptor breeding, foraging, or migration would reduce these effects. At established wind farms that already conflict with raptors, reduction of fatalities may be feasible by curtailment of turbines as raptors approach, and offset through mitigation of other human causes of mortality such as electrocution and poisoning, provided the relative effects can be quantified. Measurement of raptor mortality at wind farms is the subject of intense effort and study, especially where mitigation is required by law, with novel statistical approaches recently made available to improve the notoriously difficult-to-estimate mortality rates of rare and hard-to-detect species. Global standards for wind farm placement, monitoring, and effects mitigation would be a valuable contribution to raptor conservation worldwide.

Journal of Raptor Research↗

USGS2022

Iowa and Landsat

Iowa is famous for plenty of reasons—its State Fair butter sculptures, its first-in-the-Nation presidential caucuses, and the Iowa Hawkeyes football team, whose mascot doubles as the State nickname—but “corn” might be the first word to cross the mind of a non-Iowan. Iowa consistently leads the United States in corn production and in the production of hogs, which in turn consume a sizable share of the corn grown there. Corn also drives Iowa’s ethanol industry, which put nearly 4.5 billion gallons of fuel into the supply chain in 2020—more than any other State. Iowa owes its agricultural dominance largely to its fertile soils, making land management decisions critical to its future. Changes to land cover, more intensive land use, unusual precipitation patterns, and temperature changes, coupled with an influx of extreme weather events—some of which can be tied to or exacerbated by climate change—have placed pressure on the productive farm ground of Iowa’s 99 counties. Landsat Program satellites can be especially useful in the monitoring and management of croplands across the United States. Backed by a 50-year record of Earth surface change, Landsat satellites can detect the details of vegetation health by peering into the infrared and near-infrared parts of the electromagnetic spectrum. Iowa has long served as a proving ground for Landsat-based agricultural research, and its residents and leaders have benefited from that work. Here are a few examples of how the Landsat Program benefits Iowa.

Iowa↗

USGS2024

Controls on in-stream nitrogen loss in western Lake Erie tributaries

Management efforts to reduce cyanobacterial harmful algal blooms (cHABs) in the Great Lakes have focused on decreasing tributary inputs of phosphorus (P). Recent research has indicated that reduction of both P and nitrogen (N) can lessen cHABs severity. Microbially mediated N cycling in streambed sediment may reduce N riverine loads, yet little is known about in-stream N processing rates in the Maumee River Basin, a major source of nutrients to Lake Erie. During summer of 2019 and 2021, we sampled streambed sediment to measure potential nitrification and denitrification rates using the acetylene block method at 78 sites throughout the Maumee River network. We used structural equation models to identify indirect and direct drivers of denitrification. Precipitation was greater in 2019, resulting in a 67 % increase in mean discharge, 41 % of farm fields to be fallow, and a 50 % reduction in fertilizer use. During summer field surveys, median stream-water nitrate concentrations were not different between 2019 and 2021. Median denitrification rates were 13.3 mg N/m2/h and 31.2 mg N/m2/h, respectively, indicating high potential to remove N. Nitrate concentrations and nitrification rates were strong direct drivers of denitrification, especially in 2019 when coupled nitrification–denitrification sustained denitrification. Nitrate concentrations varied with land use. Notably, nitrate concentrations increased with the area of fallow land, which may indicate the presence of a legacy N source. These findings indicate that promoting streambed denitrification could reduce N loads to Lake Erie, but legacy N currently stored in the system may mask N reduction efforts.

Indiana, Michigan, Ohio↗

USGS2013

Scenarios of bioenergy development impacts on regional groundwater withdrawals

Irrigation increases agricultural productivity, but it also stresses water resources (Huffaker and Hamilton 2007). Drought and the potential for drier conditions resulting from climate change could strain water supplies in landscapes where human populations rely on finite groundwater resources for drinking, agriculture, energy, and industry (IPCC 2007). For instance, in the North American Great Plains, rowcrops are utilized for livestock feed, food, and bioenergy production (Cassman and Liska 2007), and a large portion is irrigated with groundwater from the High Plains aquifer system (McGuire 2011). Under projected future climatic conditions, greater crop water use requirements and diminished groundwater recharge rates could make rowcrop irrigation less feasible in some areas (Rosenberg et al. 1999; Sophocleous 2005). The Rainwater Basin region of south central Nebraska, United States, is an intensively farmed and irrigated Great Plains landscape dominated by corn (Zea mays L.) and soybean (Glycine max L.) production (Bishop and Vrtiska 2008). Ten starch-based ethanol plants currently service the region, producing ethanol from corn grain (figure 1). In this study, we explore the potential of switchgrass (Panicum virgatum L.), a drought-tolerant alternative bioenergy feedstock, to impact regional annual groundwater withdrawals for irrigation under warmer and drier future conditions. Although our research context is specific to the Rainwater Basin and surrounding North American Great Plains, we believe the broader research question is internationally pertinent and hope that this study simulates similar research in other areas.

Nebraska↗

USGS2017

Adding a nitrogen footprint to Colorado State University’s sustainability plan

As a large land grant university with more than 32,000 students, Colorado State University has both on-campus non-agricultural and agricultural sources of nitrogen (N) released to the environment. We used the Nitrogen Footprint Tool to estimate the amount of N released from different sectors of the university for the CSU 2014 academic year. The largest on campus sources were food production, utilities (heating, cooling, electricity), and research animals. The total on-campus N footprint in 2014 was 287 metric tons. This value was equivalent to the nitrogen footprint of agricultural experiment stations and other agricultural facilities, whose nitrogen footprint was 273 metric tons. CSU has opportunities to reduce its on-campus footprint through educational programs promoting low-meat diets and commuting by bicycle or bus. There is also an opportunity to advance ideas of agricultural best management practices, including precision farming and better livestock management. This article describes the planned and ongoing efforts to educate CSU about how societal activities release nitrogen to the environment, contributing to global change. It offers personal and institutional options for taking action, which would ultimately reduce CSU’s excess reactive nitrogen loss to the environment. The N-footprint for CSU, including scenarios of possible future nitrogen reductions, is also discussed.

Sustainability↗

USGS2010

External effects of irrigators' pumping decisions, high plains aquifer

The High Plains aquifer, which underlies about 174,000 square miles (1 square mile = 2.59 km 2 ) in the Great Plains, is the principal source of water in one of the nation's major agricultural areas. This paper examines relationships between the scale of management areas and physical factors, resulting from the lateral movement of groundwater, that limit the ability of irrigators in the High Plains to reduce their own future pumping lifts. At the scale of individual farms, irrigators have very limited ability to “bank” water in order to obtain reduced future pumping lifts. On the other hand, at the scales typical of regional management, reductions in pumpage will result primarily in reductions in water level declines within the management area.

Great Plains↗

USGS2007

Striving for collaborative science and communication through the Consortium for Research and Education on Emerging Contaminants (CREEC)

Current analytical capabilities are allowing scientists to identify possible contaminants in the environment that were previously unmonitored or were present at concentrations too low for detection. New scientific evidence about the exposure pathways and potential impacts of some of these compounds on human or environmental health is regularly being published (Woodling et al., 2006; Drewes et al., 2005; Kinney et al., 2006; Gibs et al., 2007; Veldhoen et al., 2006). Recent news headlines have declared potential human health and ecological concerns regarding the occurrence of personal care products and pharmaceuticals in our environment. These are products that we regularly use (or create) in our homes, businesses, farms and industry, including plasticizers, flame retardants, detergents, pesticides and herbicides, antibacterial agents, steroids, antibiotics, and disinfection byproducts. These ‘emerging contaminants’ (ECs) are compounds that have recently been shown to occur widely in one or more environmental media, have been identified as being a potential public health or ecological risk, and yet adequate data are lacking to determine their actual risk (Younos, 2005; Soin and Smagghe, 2007; Hutchinson, 2007).

Water Resources Impact↗

USGS2019

Evaluating the role of Farm Bill conservation program participation in conserving America’s grasslands

Grasslands are one of the most imperiled ecosystems in the world and the majority of the grassland ecosystem in the United States is privately owned and used for agriculture. Conversion of grasslands to row crops is expanding, fueled by commodity price increases, technological improvements, and agricultural policy. The U.S. government primarily uses voluntary incentive-based conservation programs to address the environmental impacts of agriculture and encourage conservation on private land. To investigate the utility of these programs to conserve grasslands, we surveyed private landowners in the Plains and Prairie Pothole Ecoregion (PPPE), one of America’s most at-risk grassland areas, about their land use, environmental attitudes and values, and reasons for or against participating in a Farm Bill conservation program. Agricultural landowners with large land holdings, who value hunting, and have positive environmental values, attitudes, and behaviors, were more likely to participate in a program. Financial considerations and a desire for autonomy limited participation. While program participants had less land in grass than nonparticipants and were more likely to convert planted grass to row crops and/or remove wetlands, they were also less likely to convert virgin sod to row crops. These findings signal the need for additional research and tools other than FBCPs to conserve the PPPE grasslands.

Land Use Policy↗

USGS1996

National Digital Orthophoto Program

A critical component of the National Spatial Data Infrastructure (NSDI) is Framework. Framework provides a base on which to collect, register, and integrate geospatial information accurately and consistently. The Federal Geographic Data Committee (FGDC) proposed that Framework include geodetic control, orthoimagery, elevation, transportation, hydrography, governmental units, and cadastral data. The Mapping Science Committee of the National Research Council recommends that geodetic control, orthoimagery, and elevation data become the critical foundation of the NSDI. The National Digital Orthophoto Program (NDOP) is a working model on how Federal, State, and local government, as well as private industry, can participate to develop the orthoimagery Framework for the Nation.

Report↗

USGS1993

Fish meal and alternate sources of protein in fish feeds: Update 1993

Close to 12% of the world's 6.5 million metric tons of fish meal is used for aquaculture feeds. If current trends continue, roughly 20% to 25% of total world fish meal production could be used for aquaculture by the year 2000. Fish stocks used in fish meal reduction, however, appear to be in worldwide decline. A growing fish farming industry and a stagnating, if not diminishing, supply of fish meal have sobering economic and technologic implications for fish culture. Unless suitable alternate protein sources are found or other animal feeds begin to rely less on fish meal, fish production costs can be expected to increase dramatically. A precedent was set by the poultry industry, the most economically successful and competitive of the animal agriculture industries. Twenty years ago, the poultry industry consumed up to 80% of fish meal supplies. Through deliberate and well-organized research into alternate protein sources, the industry now uses less than 40% of supplies, and the trend is toward complete independence from fish meal. A comparable research effort is needed for aquaculture. Considering the biotechnologies available, plant proteins, processed to remove enzyme inhibitors and other antinutritional factors and properly supplemented with essential amino acids and minerals where needed, could produce results at least equivalent to those obtained with fish meal.

Fisheries↗

USGS2024

Using an adaptive modeling framework to identify avian influenza spillover risk at the wild-domestic interface

The wild to domestic bird interface is an important nexus for emergence and transmission of highly pathogenic avian influenza (HPAI) viruses. Although the recent incursion of HPAI H5N1 Clade 2.3.4.4b into North America calls for emergency response and planning given the unprecedented scale, readily available data-driven models are lacking. Here, we provide high resolution spatial and temporal transmission risk models for the contiguous United States. Considering virus host ecology, we included weekly species-level wild waterfowl (Anatidae) abundance and endemic low pathogenic avian influenza virus prevalence metrics in combination with number of poultry farms per commodity type and relative biosecurity risks at two spatial scales: 3 km and county-level. Spillover risk varied across the annual cycle of waterfowl migration and some locations exhibited persistent risk throughout the year given higher poultry production. Validation using wild bird introduction events identified by phylogenetic analysis from 2022 to 2023 HPAI poultry outbreaks indicate strong model performance. The modular nature of our approach lends itself to building upon updated datasets under evolving conditions, testing hypothetical scenarios, or customizing results with proprietary data. This research demonstrates an adaptive approach for developing models to inform preparedness and response as novel outbreaks occur, viruses evolve, and additional data become available.

contiguous United States↗

USGS2024

Habitat amount and edge effects, not perch proximity, nest exposure, or vegetation diversity affect cowbird parasitism in agricultural landscapes

Context Prior research documented relationships between brown-headed cowbird ( Molothrus ater ) brood parasitism and edge effects, proximity of perches, and nest exposure. Those relationships have not been evaluated in agroecosystems containing extremes of fragmentation and vegetation diversity. Objectives We compared three existing hypotheses on how cowbirds locate host nests with two new hypotheses regarding habitat amount and vegetation diversity to determine how the configuration and location of agricultural conservation practices affect grassland bird nest parasitism rates and predicted rates for eight common conservation practices. Methods We assessed cowbird parasitism of grassland bird nests on corn and soybean farms in Iowa, USA, and measured perch proximity, nest exposure, edge effects, habitat amount, and vegetation diversity for each nest. We fit a global generalized linear mixed-effects model and compared importance of model parameters using odds ratios. We predicted parasitism likelihood for every subset model and averaged predictions to explore individual effects. Results The variables that most influenced parasitism rates included main effects for nest initiation day-of-season (OR = 0.71, CI 95 = 0.60–0.84) and the landscape variables of distance to nearest crop edge (0.63, 0.51–0.76) and proportion of grass land cover within 660 m (0.75, 0.57–1.00). We found little support that perch proximity, nest exposure, or native vegetation diversity affected parasitism. We also assessed parasitism likelihood by conservation practice and found no significant differences. Conclusions Our results provide evidence to support the edge effect and habitat amount hypotheses, but not the nest exposure, vegetation diversity, or perch proximity hypotheses.

Iowa↗

USGS2021

Oregon and Landsat

Oregon’s landscape is as complex and diverse as it is beautiful. Mountain peaks in the Cascade Range soar higher than 10,000 feet. Crater Lake sinks to a depth of 1,943 feet, making it the deepest lake in the United States. Oregon’s lands feature forests, farm fields, grasslands, ocean coastline, rivers, a semidesert, and mountain ranges that stretch across the State. A wide range of birds, animals, and fish—including 16 federally endangered species—share this space with more than 4 million people. With Oregon’s economy tied to these natural resources, industries like agriculture, timber, and fishing interlace with the well-being of wildlife and residents. Landsat data and imagery are one of many U.S. Geological Survey tools used by State resource managers and scientists to help achieve a natural balance and provide information about forests, habitats, and much more to Oregon decision makers. This will become even more important as research indicates climate change will make extreme weather more likely, leading to the likely increase in droughts, infestation, wildfires, and other natural hazards.

Oregon↗