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Item Assessing changes in spatial and temporal patterns of cropping sequences in northeast Montana(Montana State University - Bozeman, College of Agriculture, 2014) Long, John Allen; Chairperson, Graduate Committee: Rick L. Lawrence; Rick L. Lawrence, Perry R. Miller, Mark C. Greenwood and Lucy A. Marshall were co-authors of the article, 'Object-oriented crop classification using multitemporal ETM+ SLC-OFF imagery and random forest' in the journal 'GIScience and remote sensing ' which is contained within this thesis.; Rick L. Lawrence, Perry R. Miller, and Lucy A. Marshall were co-authors of the article, 'Changes in field-level cropping sequences: indicators of shifting agricultural practices' in the journal 'Agriculture, ecosystems & environment' which is contained within this thesis.; Rick L. Lawrence, Perry R. Miller, Mark C. Greenwood, and Lucy A. Marshall were co-authors of the article, 'Adoption of cropping sequences in northeast Montana: a spatio-temporal analysis' submitted to the journal 'Agriculture, ecosystems & environment' which is contained within this thesis.Initiatives to mitigate the effects of climate change have focused largely on the reduction of greenhouse gas production and on carbon capture and storage technologies. Changes in agricultural management practices have shown the ability to sequester carbon by increasing soil organic carbon and include reduced tillage intensity, decreased fallow, and changing from monoculture to rotational cropping. All have become more common in portions of the Northern Great Plains; but, despite the growth of these practices, it is unknown to what extent farmers have adopted particular cropping sequences or how they have spread temporally or spatially. My purpose here was to investigate the patterns of changing agricultural practices in northeast Montana during 2001-2012 by focusing on the increased adoption of cereal-pulse sequences and the adoption of block-managed cereal-based sequences in lieu of continuous strip-cropping. A method to identify crops via geospatial data and Landsat imagery was developed, and annual crop maps were created. Crop classifications were extracted from the maps for each field to create a 12-character string for the temporal sequence of crops, and specific 2- and 3-yr sequences were identified with a string-matching algorithm. Finally, I examined the observed spatial patterns of sequence adoption to determine if observed spatial patterns were random or were they consistent with the spread and adoption due to social interaction as described in innovation diffusion theory, adoption based on environmental factors, or neither. The major findings were: (1) cereal-fallow rotations, whether managed in blocks or by strip-cropping, no longer dominate the region; (2) there has been a substantial increase in the adoption of cereal-pulse sequences; (3) producers did not adhere strongly to specific sequences; (4) using 3-yr sequences added no additional information than 2-yr sequences; (5) the adoption of these practices was not randomly located but clustered; and (6) the adoption of these practice are not well-explained by innovation diffusion theory, although social interactions might have played a role in the early stages; the patterns are more consistent with suitability of the physical environment since available water was strongly associated with whether or not a field was managed with either practice.Item Understanding carbon sequestration in north central Montana dryland wheat systems(Montana State University - Bozeman, College of Agriculture, 2013) Feddema, Ryan Patrick; Co-chairs, Graduate Committee: Perry Miller and Richard E. EngelAgricultural management practices that reduce tillage and/or increase crop intensity have been shown to promote soil carbon sequestration in many regions of the Great Plains. Comparatively little information is available on the impact of these practices on soil organic carbon (SOC) in Montana's semi-arid climate. The objective of this research was to measure rates of change in SOC in cropland for north central Montana's Golden Triangle related to conversion of crop-fallow to annual cropping, conversion to no-till management, and the implementation of both simultaneously. A second objective was to measure differences in soil microbial biomass carbon (SMBC) as an "early indicator" for soil carbon accrual after six years of management. Field experiments were established at six farm sites in fall 2002. Soil organic C was not affected by the treatments at three of the six sites after six years (2002-2008). Three of the six sites had soil carbon accrual associated with annual cropping ranging from 0.19 to 0.53 Mg ha -1 yr -1. Only one site showed soil carbon accrual associated with no-till management, accruing 0.26 Mg ha -1 yr -1. It proved unreliable to make quantitative comparisons for samples from different collection times using SMBC because stored soil samples had diminished SMBC correlated with months in storage, making it impossible to compare accurately freshly obtained SMBC with earlier baseline values from stored soil samples. It was concluded that annual cropping is likely to increase SOC in many instances; however a longer study period may be required to understand SOC response to soil management in this region.Item Satellite monitoring of cropland-related carbon sequestration practices in North Central Montana(Montana State University - Bozeman, College of Agriculture, 2008) Watts, Jennifer Dawn; Chairperson, Graduate Committee: Rick L. Lawrence.This study used an object-oriented approach in conjunction with the Random Forest algorithm to classify agricultural practices set forth in carbon contract agreements associated with the Chicago Climate Exchange (CCX), including tillage (till or no-till (NT)), conservation reserve (CR), and crop intensity. The object-oriented approach allowed for per-field classifications and the incorporation of contextual elements in addition to spectral features. Random Forest is an advanced classification method that avoids data over-fitting and incorporates an internal classification accuracy assessment. Landsat satellite imagery was chosen for its continuous coverage, cost effectiveness, and image accessibility. Classification (2007) results included producer's accuracies of 91% for NT and 31% for tillage when applying Random Forest to image-objects generated from a May Landsat image. Low classification accuracies likely were attributed to the misclassification of conservation-based tillage practices as NT. Crop and CR lands resulted in producer's accuracies of 100% and 90%, respectively. Crop and fallow producer's accuracies were 95% and 82% in the 2007 classification; misclassification within the fallow class was attributed to pixel-mixing problems in areas of narrow (>100 m) strip management. A between-date normalized difference vegetation index approach was successfully used to detect areas "changed" in vegetation status between the 2007 and prior image dates; classified "changed" objects were then merged with "unchanged" objects to produce final classification maps of crop versus fallow. Resulting statistics showed that 22% of lands classified as CR had occurred outside of the Conservation Reserve Program (CRP). Field survey results were applied for tillage analysis because of low image classification rates and indicated that 56% of the evaluated region was under NT in 2007, with 44% practicing some form of tillage. Crop intensity estimates indicated that only 5% was under continuous cropping. These observations show the potential for the increased NT and continuous cropping. The application of carbon sequestration estimates to the land use data predict that approximately 59,497 t C yr⁻¹ might be sequestered through the universal adoption of NT and a 1.0 rotation (continuous cropping). Financial incentives through carbon credit programs might motivate land managers to make these management changes and to maintain CR lands.Item Nitrous oxide emissions from a Northern Great Plains soil as influenced by nitrogen fertilization and cropping systems(Montana State University - Bozeman, College of Agriculture, 2006) Dusenbury, Matthew Paul; Chairperson, Graduate Committee: Richard E. Engel.Agriculture has been identified by the Intergovernmental Panel on Climate Change (IPCC) as the major anthropogenic source of N₂O emissions. Field measurements of N₂O emissions are limited for cropping systems in the semi-arid Northern Great Plains (NGP). The study objectives were to determine temporal N₂O emission patterns for NGP cropping systems, and estimate fertilizer N induced emissions (FIE) and contrast with IPCC default methodology. No-till (NT) wheat (Triticum Aestivum L.)-fallow, wheat-wheat, and wheat-pea (Pisum sativum L.), and a conventional till (CT) wheat-fallow all with three N regimes (200 and 100 kg N ha-1 available N, unfertilized N control); plus a perennial grass system (CRP) were sampled over two years (15 Apr 2004 - 14 Apr 2006) using static chambers. Nitrous oxide emissions over two years were 209 to 1310 g N ha-1 for the cropping systems. Greatest N₂O emission activity occurred following urea-N fertilization (10-wk) and freeze-thaw cycles. The sum for these periods comprised 73-84% of total emissions. Emissions were positively correlated with urea-N fertilization rates and increased rapidly when water-filled pore was > 50%.Item Hyperspectral remote sensing as a monitoring tool for geologic carbon sequestration(Montana State University - Bozeman, College of Agriculture, 2011) Bellante, Gabriel John; Chairperson, Graduate Committee: Rick L. Lawrence; Scott Powell (co-chair)The contemporary global climate crisis demands mitigation technologies to curb atmospheric greenhouse gas emissions, principally carbon dioxide (CO 2). Geologic carbon sequestration (GCS) is a method by which point source CO 2 emissions are purified and deposited in subsurface geologic formations for long-term storage. Accompanying this technology is the inherent responsibility to monitor these large-scale subsurface reservoirs for CO 2 leaks to ensure safety to local environments and inhabitants, as well as to alleviate global warming. Elevated CO 2 levels in soil are known to cause anoxic conditions in plant roots, thereby interfering with plant respiration and inducing a stress response that could possibly be remotely sensed using aerial imagery. Airborne remote sensing technology has the potential to monitor large land areas at a relatively small cost compared to alternative methods. In 2010, an aerial campaign was conducted during the height of the growing season to obtain an image time series that could be used to identify and characterize CO 2 stress in vegetation from a simulated CO 2 leak. An unsupervised classification was performed to classify CO 2 stressed vegetation as a result of the subsurface injection. Furthermore, a spectral index was derived to amplify the CO 2 stress signal and chart vegetation health trajectories for pixels affected by the CO 2 release. A theoretical framework was developed for analysis strategies that could be implemented to detect a CO 2 leak using aerial hyperspectral imagery with minimal a priori knowledge. Although aerial detection of CO 2 stressed vegetation was possible while no other physiological plant stressors were present, the spectral distinction between vegetation stress agents would have important implications for the appropriate timing that GCS monitoring using remote sensing data could commence. A greenhouse experiment was devised to compare the spectral responses of alfalfa plants to CO 2 and water stress in order to reveal whether CO 2 leak detection is possible when soil water availability is highly variable or during periods of drought. Spectral discernment of a CO 2 leak appears to be possible when soil water is spatially variable and during moderate drought conditions with remote sensing instruments that are sensitive to reflectance in the short wave infrared, where water absorption features related to leaf water content occur.