Life Sciences Commons^™

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

Department of Biological Systems Engineering: Dissertations and Theses

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Characterization Of Physical And Biochemical Traits In Wheat And Corn Plants Using High Throughput Image Analysis, Kantilata Thapa

Department of Biological Systems Engineering: Dissertations and Theses

Plant phenotyping has been recognized as a rapidly growing field of research due to the labor-intensive, destructive, and time-consuming nature of traditional phenotyping methods. These phenotyping bottlenecks can be addressed by advancements in image-based phenotyping like RGB and hyperspectral imaging for the assessment of plant traits important for breeding purposes. This study aims (1) to characterize the physical and biochemical traits of wheat and corn plants using RGB and hyperspectral imaging in the greenhouse, and (2) to estimate leaf nitrogen (N), phosphorus (P), and potassium (K) content using hyperspectral imaging and an analytical spectral device (ASD spectrometer) and compare the …

Next-Generation Technologies Unlock New Possibilities To Track Rangeland Productivity And Quantify Multi-Scale Conservation Outcomes, Caleb P. Roberts, David E. Naugle, Brady W. Allred, Victoria M. Donovan, Dillon T. Fogarty, Matthew O. Jones, Jeremy D. Maestas, Andrew C. Olsen, Dirac L. Twidwell Jr

Department of Agronomy and Horticulture: Faculty Publications

Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing. In Oregon’s sagebrush …

Advances In Field-Based High-Throughput Photosynthetic Phenotyping, Peng Fu, Christopher M. Montes, Matthew H. Siebers, Nuria Gomez-Casanovas, Justin M. Mcgrath, Elizabeth A. Ainsworth, Carl J. Bernacchi

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing …

Regional Plant Community Differences In The Nebraska Sandhills, Travis Millikan

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

The Nebraska Sandhills is very valuable to the state of Nebraska, representing one of the most in-tact and largest grassland ecosystems in temperate regions in the world. Rangeland managers must understand plant community dynamics across the Sandhills to better inform management decisions. The first objective of this study was to evaluate plant community variability on upland Sands ecological sites across different precipitation zones in the Nebraska Sandhills. The second objective of our study was to utilize the Rangeland Analysis Platform (RAP) to examine spatial and temporal variability in biomass production and cover on pastures of ranches analyzed in the first …

Predicting Spatial-Temporal Patterns Of Diet Quality And Large Herbivore Performance Using Satellite Time Series, Sean P. Kearney, Lauren M. Porensky, David J. Augustine, Justin D. Derner, Feng Gao

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal …

Extreme Fire As A Management Tool To Combat Regime Shifts In The Range Of The Endangered American Burying Beetle, Alison K. Ludwig, Daniel R. Uden, Dirac Twidwell

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

This study is focused on the population of federally-endangered American burying beetles in south-central Nebraska. It is focused on changes in land cover over time and at several levels of spatial scale, and how management efforts are impacting both the beetle and a changing landscape. Our findings are applicable to a large portion of the Great Plains, which is undergoing the same shift from grassland to woodland, and to areas where the beetle is still found.

A Review Of Vegetation Phenological Metrics Extraction Using Time-Series, Multispectral Satellite Data, Linglin Zeng, Brian D. Wardlow, Daxiang Xiang, Shun Hu, Deren Li

School of Natural Resources: Faculty Publications

Vegetation dynamics and phenology play an important role in inter-annual vegetation changes in terrestrial ecosystems and are key indicators of climate-vegetation interactions, land use/land cover changes, and variation in year-to-year vegetation productivity. Satellite remote sensing data have been widely used for vegetation phenology monitoring over large geographic domains using various types of observations and methods over the past several decades. The goal of this paper is to present a detailed review of existing methods for phenology detection and emerging new techniques based on the analysis of time-series, multispectral remote sensing imagery. This paper summarizes the objective and applications of detecting …

Improving On Modis Mcd64a1 Burned Area Estimates In Grassland Systems: A Case Study In Kansas Flint Hills Tall Grass Prairie, Rheinhardt Scholtz, Jayson Prentice, Yao Tang, Dirac Twidwell

Department of Agronomy and Horticulture: Faculty Publications

Uncertainty in satellite-derived burned area estimates are especially high in grassland systems, which are some of the most frequently burned ecosystems in the world. In this study, we compare differences in predicted burned area estimates for a region with the highest fire activity in North America, the Flint Hills of Kansas, USA, using the moderate resolution imaging spectroradiometer (MODIS) MCD64A1 burned area product and a customization of the MODIS MCD64A1 product using a major ground-truthing effort by the Kansas Department of Health and Environment (KDHE-MODIS customization). Local-scale ground-truthing and the KDHE-MODIS product suggests MODIS burned area estimates under predicted fire …

Improving The Accessibility And Transferability Of Machine Learning Algorithms For Identification Of Animals In Camera Trap Images: Mlwic2, Michael A. Tabak, Mohammad S. Norouzzadeh, David W. Wolfson, Erica J. Newton, Raoul K. Boughton, Jacob S. Ivan, Eric Odell, Eric S. Newkirk, Reesa Y. Conrey, Jennifer Stenglein, Fabiola Iannarilli, John Erb, Ryan K. Brook, Amy J. Davis, Jesse Lewis, Daniel P. Walsh, James C. Beasley, Kurt C. Vercauteren, Jeff Clune, Ryan S. Miller

USDA Wildlife Services: Staff Publications

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera …

A Decade Of Unmanned Aerial Systems In Irrigated Agriculture In The Western U.S., Jose L. Chavez, Alfonso F. Torres-Rua, Wayne E. Woldt, Huihui Zhang, Christopher Robertson, Gary W. Marek, Dong Wang, Derek M. Heeren, Saleh Taghvaeian, Christopher M. U. Neale

Department of Biological Systems Engineering: Papers and Publications

Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible …

The Role Of Topography, Soil, And Remotely Sensed Vegetation Condition Towards Predicting Crop Yield, Trenton E. Franz, Sayli Pokal, Justin P. Gibson, Yuzhen Zhou, Hamed Gholizadeh, Fatima Amor Tenorio, Daran Rudnick, Derek M. Heeren, Matthew F. Mccabe, Matteo Ziliani, Zhenong Jin, Kaiyu Guan, Ming Pan, John Gates, Brian Wardlow

School of Natural Resources: Faculty Publications

Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Given the wide range of data costs (between USD $0−50/ha), it is important to understand where often limited financial resources should be directed to optimize field production. Two key questions arise. First, will these data actually aid in better fine-resolution yield prediction to help optimize crop management and farm economics? Second, what …

Use Of Uav Imagery And Nutrient Analyses For Estimation Of The Spatial And Temporal Contributions Of Cattle Dung To Nutrient Cycling In Grazed Ecosystems, Amanda Shine

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Nutrient inputs from cattle dung are crucial drivers of nutrient cycling processes in grazed ecosystems. These inputs are important both spatially and temporally and are affected by variables such as grazing strategy, water location, and the nutritional profile of forage being grazed. Past research has attempted to map dung deposition patterns in order to more accurately estimate nutrient input, but the large spatial extent of a typical pasture and the tedious nature of identifying and mapping individual dung pats has prohibited the development of a time- and cost-effective methodology. The first objective of this research was to develop and validate …

Variable Rate Irrigation Of Maize And Soybean In West-Central Nebraska Under Full And Deficit Irrigation, J Burdette Barker, Sandeep Bhatti, Derek M. Heeren, Christopher M.U. Neale, Daran Rudnick

Department of Biological Systems Engineering: Papers and Publications

Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model …

Unmanned Aerial System And Satellite-Based High Resolution Imagery For High-Throughput Phenotyping In Dry Bean, Sindhu Sankaran, Juan José Quirós, Phillip N. Miklas

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Dry bean breeding programs are crucial to improve the productivity and resistance to biotic and abiotic stress. Phenotyping is a key process in breeding that refers to crop trait evaluation. In recent years, high-throughput plant phenotyping methods are being developed to increase the accuracy and efficiency for crop trait evaluations. In this study, aerial imagery at different resolutions were evaluated to phenotype crop performance and phenological traits using genotypes from two breeding panels, Durango Diversity Panel (DDP) and Andean Diversity Panel (ADP). The unmanned aerial system (UAS) based multispectral and thermal data were collected for two seasons at multiple time …

Machine Learning To Classify Animal Species In Camera Trap Images: Applications In Ecology, Michael A. Tabak, Mohammad S. Norouzzadeh, David W. Wolfson, Steven J. Sweeney, Kurt C. Vercauteren, Nathan P. Snow, Joseph M. Halseth, Paul A. Di Salvo, Jesse S. Lewis, Michael D. White, Ben Teton, James C. Beasley, Peter E. Schlichting, Raoul K. Boughton, Bethany Wight, Eric S. Newkirk, Jacob S. Ivan, Eric A. Odell, Ryan K. Brook, Paul M. Lukacs, Anna K. Moeller, Elizabeth G. Mandeville, Jeff Clune, Ryan S. Miller

USDA Wildlife Services: Staff Publications

1. Motion-activated cameras (“camera traps”) are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses.

2. We trained machine learning models using convolutional neural networks with the ResNet-18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an …

Wheat Height Estimation Using Lidar In Comparison To Ultrasonic Sensor And Uas, Wenan Yuan, Jiating Li, Madhav Bhatta, Yeyin Shi, P. Stephen Baenziger, Yufeng Ge

Department of Agronomy and Horticulture: Faculty Publications

As one of the key crop traits, plant height is traditionally evaluated manually, which can be slow, laborious and prone to error. Rapid development of remote and proximal sensing technologies in recent years allows plant height to be estimated in more objective and efficient fashions, while research regarding direct comparisons between different height measurement methods seems to be lagging. In this study, a ground-based multi-sensor phenotyping system equipped with ultrasonic sensors and light detection and ranging (LiDAR) was developed. Canopy heights of 100 wheat plots were estimated five times during a season by the ground phenotyping system and an unmanned …

Developing The Framework For A Risk Map For Mite Vectored Viruses In Wheat Resulting From Pre-Harvest Hail Damage, Anthony L. Nguy-Robertson, Arthur Zygielbaum, Anthony J. Mcmechan, Gary L. Hein, Stephen N. Wegulo, Abby R. Stilwell, Travis M. Smith

Department of Plant Pathology: Faculty Publications

There is a strong economic incentive to reduce mite-vectored virus outbreaks. Most outbreaks in the central High Plains of the United States occur in the presence of volunteer wheat that emerges before harvest as a result of hail storms. This study provides a conceptual framework for developing a risk map for wheat diseases caused by mite-vectored viruses based on pre-harvest hail events. Traditional methods that use NDVI were found to be unsuitable due to low chlorophyll content in wheat at harvest. Site-level hyperspectral reflectance from mechanically hailed wheat showed increased canopy albedo. Therefore, any increase in NIR combined with large …

How Could Unmanned Aerial Systems (Uas) Be Used For Ecohydrological And Ecosystem Research? Experiences Of First Operations With Uas In River Flood Plains Of Northern Mongolia, Jürgen Hofmann, Martin Oczipka, Thomas Rutz, Hauke Dämpfling

Erforschung biologischer Ressourcen der Mongolei / Exploration into the Biological Resources of Mongolia, ISSN 0440-1298

This paper proposes the use of unmanned aerial systems (UAS) as a method for monitoring biotic resources and ecohydrological systems in river floodplains.

Small scale mapping based on LANDSAT and SRTM or ASTER data is of limited applicability since a spatial resolution of 30 to 90 m is not sufficient to meet the demands of habitat mapping and large scale 3D -modelling. Newer satellites like WorldView2 and SENTINEL (space mission from European Space Agency within the Copernicus Programme) could be an option to gain a 0.5 m resolution, but the availability of image data is limited.

UAS allow the collection …

Review Of Broad-Scale Drought Monitoring Of Forests: Toward An Integrated Data Mining Approach, Steven P. Norman, Frank H. Koch, William W. Hargrove

USDA Forest Service / UNL Faculty Publications

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can …

Quantitative Analysis Of Woodpecker Habitat Using High-Resolution Airborne Lidar Estimates Of Forest Structure And Composition, James E. Garabedian, Robert Mcgaughey, Stephen E. Reutebuch, Bernard R. Parresol, John C. Kilgo, Christopher E. Moorman, M. Nils Peterson

USDA Forest Service / UNL Faculty Publications

Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) …

Remote Estimation Of Nitrogen And Chlorophyll Contents In Maize At Leaf And Canopy Levels, Michael Schlemmer, Anatoly A. Gitelson, James S. Schepers, Richard B. Ferguson, Y. Peng, J. Shanahan, Donald Rundquist

Department of Agronomy and Horticulture: Faculty Publications

Leaf and canopy nitrogen (N) status relates strongly to leaf and canopy chlorophyll (Chl) content. Remote sensing is a tool that has the potential to assess N content at leaf, plant, field, regional and global scales. In this study, remote sensing techniques were applied to estimate N and Chl contents of irrigated maize (Zea mays L.) fertilized at five N rates. Leaf N and Chl contents were determined using the red-edge chlorophyll index with R2 of 0.74 and 0.94, respectively. Results showed that at the canopy level, Chl and N contents can be accurately retrieved using green and red-edge Chl …

Chlorophyll-Based Approach For Remote Estimation Of Crop Gross Primary Production: From In Situ Measurements To Satellite Imagery, Yi Peng

School of Natural Resources: Dissertations, Theses, and Student Research

The synoptic and accurate quantification of crop gross primary production (GPP) is essential for studying carbon budgets in croplands and monitoring crop status. The objective of this dissertation is to develop a quantitative technique to estimate crop GPP using remotely sensed data collected from close range to satellite altitudes. In this study, a model based on a recently developed paradigm, which relates crop GPP to a product of total crop chlorophyll content and incident radiation affecting vegetation photosynthesis, was justified for the remote estimation of GPP in crops. The model was tested with ground-observed incoming photosynthetically active radiation (PAR_{in …}

A Synoptic Review Of U.S. Rangelands A Technical Document Supporting The Forest Service 2010 Rpa Assessment, Matthew Clark Reeves, John E. Mitchell

USDA Forest Service / UNL Faculty Publications

The Renewable Resources Planning Act of 1974 requires the USDA Forest Service to conduct assessments of resource conditions. This report fulfills that need and focuses on quantifying extent, productivity, and health of U.S. rangelands. Since 1982, the area of U.S. rangelands has decreased at an average rate of 350,000 acres per year owed mostly to conversion to agricultural and residential land uses. Nationally, rangeland productivity has been steady over the last decade, but the Rocky Mountain Assessment Region appears to have moderately increased productivity since 2000. The forage situation is positive and, from a national perspective, U.S. rangelands can probably …

Evapotranspiration Information Reporting: I. Factors Governing Measurement Accuracy, Richard G. Allen, Luis S. Pereira, Terry A. Howell, Marvin E. Jensen

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

More and more evapotranspiration models, evapotranspiration crop coefficients and associated measurements of evapotranspiration (ET) are being reported in the literature and used to develop, calibrate and test important ET process models. ET data are derived from a range of measurement systems including lysimeters, eddy covariance, Bowen ratio, water balance (gravimetric, neutron meter, other soil water sensing), sap flow, scintillometry and even satellite-based remote sensing and direct modeling. All of these measurement techniques require substantial experimental care and are prone to substantial biases in reported results. Reporting of data containing measurement biases causes substantial confusion and impedance to the advancement of …

Improving In-Season Nitrogen Recommendations For Maize Using An Active Sensor, J. Schmidt, D. Beegle, Q. Q. Zhu, R. Sripada

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

An active crop canopy reflectance sensor could be used to increase N-use efficiency in maize (Zea mays L.), if temporal and spatial variability in soil N availability and plant demand are adequately accounted for with an in-season N application. Our objective was to evaluate the success of using an active canopy sensor for developing maize N recommendations. This study was conducted in 21 farmers’ fields from 2007 to 2009, representing the maize production regions of east central and southeastern Pennsylvania, USA. Four blocks at each site included seven sidedress N rates (0–280 kgNha⁻¹) and one at-planting N …

Remote Sensing To Detect The Movement Of Wheat Curl Mites Through The Spatial Spread Of Virus Symptoms, And Identification Of Thrips As Predators Of Wheat Curl Mites, Abby R. Stilwell

Department of Entomology: Dissertations, Theses, and Student Research

The wheat curl mite (WCM), Aceria tosichella Keifer, transmits three viruses to winter wheat: wheat streak mosaic virus, High Plains virus, and Triticum mosaic virus. This virus complex causes yellowing of the foliage and stunting of plants. WCMs disperse by wind, and an increased understanding of mite movement and subsequent virus spread is necessary in determining the risk of serious virus infections in winter wheat. These risk parameters will help growers make better decisions regarding WCM management. The objectives of this study were to evaluate the capabilities of remote sensing to identify virus infected plants and to establish the potential …

Detection And Measurement Of Water Stress In Vegetation Using Visible Spectrum Reflectance, Arthur Zygielbaum

Department of Geography: Dissertations, Theses, and Student Research

At any scale, from a single microbe to the planet that nurtures us, water defines our place in the universe. It provides the hydraulic forces needed to give plants structure, and the medium enabling photosynthesis, the basis for most life on Earth, to occur. Knowledge of plant water status is vital to understanding the state or condition of vegetation, information which is essential to disciplines as diverse as agriculture, geography, and climatology. Non-destructive and remote sensing of plant water status allows the gathering of such information across wide geographic extents and over long periods of time. Monitoring vegetation remotely requires …

Using Local Knowledge And Remote Sensing To Map Known And Potential Prairie-Chicken Distribution In Kansas, Michael E. Houts, Randy D. Rodgers, Roger D. Applegate, William H. Busby

The Prairie Naturalist

The greater prairie-chicken (Tympanuchus cupido) and lesser prairie-chicken (Tympanuchus pallidicinctus) have experienced considerable fluctuations in their range and distribution over time. Having current range maps would help wildlife managers and policy makers with decisions regarding prairie-chicken habitat. To create an updated and accurate map of the Kansas prairie-chicken range, a two-pronged approach was implemented. First, a map of potential habitat was created by using known habitat preferences and avoidance factors. Second, a preliminary map showing the distribution of greater and lesser prairie-chickens was created and mailed to regional experts for comments and edits. The returned edits …

Responsive In-Season Nitrogen Management For Cereals, J.F. Shanahan, N. R. Kitchen, W. R. Raun, James S. Schepers

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Current nitrogen (N) management strategies for worldwide cereal production systems are characterized by low N use efficiency (NUE), environmental contamination, and considerable ongoing debate regarding what can be done to improve N fertilizer management. Development of innovative strategies that improve NUE and minimize off-field losses is crucial to sustaining cereal-based farming. In this paper, we review the major managerial causes for low NUE, including (1) poor synchrony between fertilizer N and crop demand, (2) uniform field applications to spatially variable landscapes that commonly vary in crop N need, and (3) failure to account for temporally variable influences on crop N …