Progress 02/01/14 to 01/31/18
Outputs
Target Audience:Farmers/landowners, researchers, conservation managers at government agencies or non-government organizations. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Four graduate students were supported by this project: Gaurav Arora, PhD student in Economics, Iowa State University (graduated in 2017); Niaz M. Chowdhury (graduated in 2016) and Moses Luri (graduated in 2016), MS students in Economics, South Dakota State University; Benjamin Uecker (graduated in 2015), Natural Resource Management student, North Dakota State University. How have the results been disseminated to communities of interest?Project team members presented results at scientific meetings, wrote commentaries on research results, and wrote professional papers. For more details, please see publications and output in annual reports and this final report. In the first year of the project, we set up a website where project information is posted (https://www.card.iastate.edu/land-use/). We also set up a website showing constructed climate data (www.ndsu.edu/climate). For the project survey on land use decisions, we made a news release through South Dakota State University and the information can be found online. The project investigators all took a field trip guided by a local extension specialist in the first year. This lays a foundation to make practical connection with the local communities. Research results were also presented to land use professionals through two webinars. Additionally, the summary results of our farmers/landowners survey were mailed to all respondents who could then learn about our research findings first hand. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Overall impact: Understanding drivers of western expansion of the Corn Belt is imperative, especially in the face of climate change. We examined impacts of weather/climate in a framework that incorporates competition of all major crops in the region and the perspectives of landowners on land use decision factors. We found that weather was an important factor for historic crop yields and land use patterns, and that it is important to account for relative competitiveness of each crop when assessing land use impacts of climate changes. Our landowner surveys reveal weather/climate is not the most important factor in land use decisions. We suggest further investigation into this issue as the ranking of driving factors affects landowners' willingness to take up adaptation strategies in a changing climate environment. Obj-1) Climate data (1950-2014: min/max temperature [T], precipitation [P] and other data) were collected for each county in the Dakotas using ACIS query builder. County-wise growing degree-days were then used to make monthly and yearly graphs, which display time series including trend and annual fluctuations with unique regional characterizations. Standardized precipitation index (SPI) data were collected for each county spanning 119 years (1895-2014) using West Wide Drought Tracker (maintained by Oregon State) to show SPI change throughout time. County-wise season length data were obtained using ACIS 2 query builder (maintained by NOAA). All these data are available for public view. We used Intergovernmental Panel on Climate Change's (IPCC) A1B emission scenario (IPCC, 2012, p.4) to study implications of climate change. To draw a comparison between historical weather (1981-2010) and weather projections (2031-'60), we utilized median values from the output of seven climate models. Average T and total P is projected to increase for all months in the growing season of major crops. The highest increase in average T is projected in April (33%) and May (18%), and least increase in July (12%). August P will increase the most (15%). Monthly Z (a moisture index) will become more negative in future, primarily driven by higher future T. Obj-2) Cropland Data Layers (CDL) are 30-m raster products made available by USDA. However, CDL temporal depth is limited which precludes capture of longer-term trends in land use change. Hence, we implemented a phenology-based Landsat classification algorithm to create CDL-compatible data for eastern N&S Dakota that predates the initial CDL by 13 and 22 years. Five land covers (corn, soybeans, wheat, alfalfa and grass: including native grass, hay and pasture) are identified -with CDL-like accuracy-- using archived Landsat data. The long-term rate of grassland loss during 1985-2011 was found to be significantly lower (26,781 ha or 1.5% annually) relative to the near-term rate of grassland loss during 2006-'11 (84,545 ha or 5.2% ann.). We found similar discrepancy in regional corn expansion rates, which demonstrates the need for longer time series data for land cover change analyses -a limitation faced by studies that rely solely upon the current CDL archive. Our CDL-like algorithm and outputs are robust and can be used in concert with existing CDL archive to extend temporal depth and enhance identification of driving factors linked to changes over longer time frames. Obj-3) We designed a mail survey instrument "Farmland Use Decisions in the Dakotas" in 2015 to obtain data from agricultural landowners on their: (1) recent and projected agricultural land use patterns, (2) land use conversion (grass to crop, crop to grass), and (3) views on the main drivers of land use change and conversion. We asked the respondents to rank the relative importance of 10 different driving forces that affected their land use decisions in the past 10 years. Most of the drivers can be grouped into economic, technology change, policy and environmental factors. 1) Changing crop prices was salient to influencing land use decisions (single most important factor for 50% of respondents, especially conversion decisions). 2) Changing input prices (seed, fertilizer, chemicals etc.) and increased crop yields (reasons other than seed traits) were second and third most influential impact factors. These two factors were selected by 26% of all respondents. 3) Changing weather/climate ranked 4th as the most influential decision factor (6.9% selected this as their most important decision factor), which may reflect the extent to which some farmers encountered flood or drought issues. 4) More efficient crop equipment, pest management practices and crop insurance factors were the next items listed. Overall, the main results from this 2015 producer survey highlight the widespread extent of producer participation in both changing land use patterns and land conversion occurring in the PPR. Obj-4) Objective was to empirically disentangle the impacts of climate and other driving factors on the changes of Dakota's land use and production system. We tried to focus on the role of an integrated network of infrastructure by incorporating a variety of data: soil moisture, GDD and other weather data; historical crop/hay prices and yields; soil quality; government payment; roads, highways, and railroads; population density; ethanol plant locations, capacity and start-up dates; and locations of active grain elevator and other user agricultural infrastructure. By use of a spatially delineated dataset, Propensity Score Matching to construct pair comparisons and flexible Difference-in-Difference regression design, we estimated the impact of a corn-based ethanol plant on nearby corn-acres. By contrast with recent research for the United States as a whole, we could not discern a significant uniform impact on corn or tilled acres due to the presence of North Dakota ethanol plants. We also established a model that predicted how yields of major crops are related to weather and soil conditions. We contributed to scientific knowledge by analyzing major crops (corn, soybean, wheat, and grass) in our study region, not just an individual crop. We took into account non-linear impact of T and P on crop yields. This yield model was then linked to output and input prices to allow for the estimates of the economic competitiveness of each crop which would then lead to land use changes among the crops. By linking future climate projections to this yield modeling framework, we could analyze the impacts of alternative climate scenarios. Obj-5) Impact of alternative weather scenarios on land allocated to the region's major crops. We consider IPCC's A1B scenario (IPCC 2012) to construct weather changes between 1981-2010 and 2031-'60, whereby the region's growing-season T is likely to increase by ~2oC. We find that soybean yield losses were relatively modest (10%), followed by maize (35%), spring wheat (50%) and alfalfa (61%) for 2031-'60 relative to 1981-2010. Yield losses projected from the alternative yield-weather model specification with decomposed SDs, were higher for soybeans (22%) but lower for spring wheat (42%), and little changed for both maize (35%) and alfalfa (61%). To evaluate climate-driven land use impacts for the Dakotas we compare land use share estimates from projected and historical weather-induced crop returns, holding all else constant. We found that grass acreage in eastern South Dakota will increase by ~23%, replacing maize, soybeans and alfalfa. In North Dakota, grass acres will remain steady or decline while maize, soy and alfalfa acres will be displaced by spring wheat. High input costs for maize imply lower maize profits compared to wheat even when the projected impact of climate change on maize yields is likely to be relatively less severe. In the west, spring wheat and alfalfa acres are projected to decrease while maize/soy and grass acres are expected to increase, although these changes are projected to be modest.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Wang, T., M. Luri, L. Janssen, D.A. Hennessy, H. Feng, M.C. Wimberly, G. Arora. 2017. Determinants of motives for land use decisions at the margins of the Corn Belt. Ecological Economics. Volume 134, April, Pages 227237. http://dx.doi.org/10.1016/j.ecolecon.2016.12.006.
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Wimberly, M., L. Janssen, D. Hennessy, M. Luri, N. Chowdhury, H. Feng. 2017. Agricultural Land Use Change and Grassland Loss in the Eastern Dakotas: A Farm-Level Analysis. Land Use Policy. Volume 63, April, Pages 160-173. http://dx.doi.org/10.1016/j.landusepol.2017.01.026.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2018
Citation:
Arora, G., Wolter, P.T. (2018). Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: Observed trends and contributing factors. Journal of Land Use Science
- Type:
Journal Articles
Status:
Under Review
Year Published:
2018
Citation:
Gaurav Arora, Hongli Feng, Christopher Anderson, David A. Hennessy. Evidence of differential weather and climate change impacts on regional crop yields and land use change. Under Review. Climatic Change.
- Type:
Theses/Dissertations
Status:
Accepted
Year Published:
2017
Citation:
Gaurav Arora. 2017. Studies on factors affecting the evolution of agroecosystems in the Dakotas.
PhD Dissertation, Iowa State University.
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2017
Citation:
Doidge, M., D. Hennessy, and H. Feng. 2017. Farmers Motivations for Land Conversion in the Prairie Pothole Region of North and South Dakota. Proceedings of the 4th biennial Americas Grassland Conference, November 14-16, in Fort Worth, Texas.
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2017
Citation:
Du, Xiaodong, D.A. Hennessy, and H. Feng. Yield and Acreage Adaptation of US Crops to Climate Changes: Empirical Evidence in Recent Decades. Selected 20 min paper presentation at AAEA Annual Meeting, Chicago, IL, July 30-Aug. 1, 2017.
|
Progress 02/01/16 to 01/31/17
Outputs
Target Audience:Farmers/landowners, researchers, conservation managers at government agencies or non-government organizations. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?This project provided training opportunities for one graduate student during the reporting period: Gaurav Arora, PhD student in Economics, Iowa State University. Arora will have his thesis defense on 1/3/3017. How have the results been disseminated to communities of interest?Project team members presented results at scientific meetings, wrote commentaries on research results, and wrote professional papers. More details on journal papers, conference presentations, and the commentaries are provided in the products section. What do you plan to do during the next reporting period to accomplish the goals?The project team has preliminarily completed the tasks under all objectives. The plan for the next year (with a no-cost extension) is to refine our and modeling and analyses. Specifically, we plan to refine our land use modeling under future climate scenarios; we will improve our modeling of spatial and local spillover effects, we also plan to conduct more analyses of the farmers' survey data, esp., regarding farmers perception of land use changes and weather patterns.
Impacts
What was accomplished under these goals?
We developed an integrated framework to analyze the climate change impacts on regional agricultural productivity and private land use decisions. We demonstrated the agricultural impacts of climate change on recent land use transitions in the Northern Great Plains. We found evidence that weather-driven returns determine regional land use allocations. Additionally, we evaluated the medium-term climate change implications from the IPCC A1B emission scenario by 2031-60, relative to 1981-2010. We also found evidence on the existence of localized spillover effects. Our analyses show that people's perceptions of land use changes were affected by their land use decisions and in turn would affect land use changes. Findings of this project inform our understanding of climate change adaptation opportunities, and also inform policy alternatives to be considered. Obj. 1) Characterize spatial and temporal patterns in climate change relevant to agriculture across the Dakotas with a focus on grass-based agriculture, corn and soybeans, and small grain production. Using IPCC A1B emission scenario, to study the implications of climate change for this study. To draw a comparison between historical weather realizations (1981-2010) and the weather projections (2031-60), we utilize median values from the output of seven climate models. Briefly, average temperature and total precipitation is projected increase for all months in the growing season of the major crops. The highest increase in average temperature is projected in April (33%) and May (18%), and least increase in July (12%). August precipitation will increase the most (15%). Monthly Z (a moisture index) will become more negative in future, primarily driven by higher future temperatures. Obj. 2) Develop methodologies to discern shifts in the location of different agricultural production systems and land uses in the Dakotas. We have completed a draft of a manuscript to be submitted to a journal. We designed and implemented a robust satellite image processing algorithm to identify historical land uses in the South Dakota and North Dakota since 1984. We identified historical land allocations to five major land uses in the region: corn, soybeans, wheat, alfalfa, and grass. We contributed by extending the narrow time-window of publicly-available Dakotas' Cropland Data Layer (CDL) imagery that would facilitate a longer time-series to better document regional land use changes. We also summarized land use trends for this region and find that the restricted data availability due to CDL tends to substantially overestimate the rate of land use change across crop and non-crop categories. Obj. 3) Using information gleaned from Obj. 1 and 2, we will target surveys to land users in areas assessed as sensitive to agricultural production changes to solicit information on i) recent and long-range projected production patterns, ii) motives for recent and projected production choices, iii) personal views on the evolution of agricultural production in the locality, and iv) perspectives on adaptation strategies and policies. We have conducted several analyses based on the survey data which have led to one accepted journal paper, one paper invited for second round revision, and one paper in a draft form. We found that farmers' views are largely consistent with the economic margin viewpoint. The importance of crop output prices, crop input prices, innovations in cropping equipment and weather patterns on land use decisions grow as one moves north toward the economic margin. Land in more highly sloped areas is more sensitive to crop prices and crop insurance policies. Consistent with human capital theory, older operators are generally less responsive to factors that affect land use. Those renting more land, being more exposed to market forces, are more responsive. As farm size increases, respondents declared higher land use sensitivity to policy issues and technological innovations, suggesting that scale effects render land units more sensitive to land use change drivers. We found systematic biases in farmers' perceived land use changes and the biases are associated with decisions made in the past. Farmers who had converted grassland to cropland on average had over-perception in that they perceived larger cropland increases than there actually were; while farmers who had made the opposite conversion (i.e., from cropland to grassland) on average did not exhibit such biases. We also found evidence of the linkage between perception biases and intended future land conversions. Our findings suggest that any communication strategies that are intended to guide resource allocations through addressing perception biases have to recognize these linkages. We also found that people have very different perceptions regarding past and future weather patterns. Obj. 4) Set up a spatially explicit modeling framework to assess climate and other driving factors behind the adoption of 'new' production systems, focusing on the role of the factors as components of an integrated network of infrastructure. We evaluated the efficiency of past conservation easement allocations in protecting the grasslands of the Prairie Our spatio-temporal analysis suggests that the region's existing croplands and grasslands occur as large, contiguous tracts where permanent grass conversions occurred in proximity of the crop-intensive areas. We conjecture that localized spillovers exist in this region's land use decisions and present a game-theoretic framework of binary choices to evaluate easement allocations when strategic complementarities exist among private landowners. We find that that easement allocations are more cost-effective when acquired as contiguous tracts and on lands that provide weak cropping incentives, e.g. poor soils. We empirically validate our conjecture of localized spillovers by employing a duration modelling framework. We find that higher grass density inhibits the risk of conversion in its locality, and that easements are strategic complements to higher grass acres with regards to inhibiting conversion risks. The fact that past easements were acquired as relatively large tracts and on poorer quality soils is encouraging because our analytical findings would suggest that these easements were allocated in a cost-effective manner. Obj. 5) Apply inferences drawn from Objectives 1 through 4 above to project the evolution of production systems under alternative climate scenarios and to assess outcomes from alternative adaptation strategies. We found soybeans yield losses to be modest (11%) relative to the other crops, followed by corn (34%), spring wheat (51%) and alfalfa (65%) by 2031-'60, relative to the 1981-2010 levels, see figures 6-9. These individual crop yield losses translate into reductions in the weather-driven component of crop profits due to climate change. We feed these changes into our estimated system of land share equations and hold other variables constant at their means to evaluate regional implications of climate change on the land use allocations. As a result, in the eastern Dakotas' counties, we find that the average share of corn, soybeans and grass will increase by 59%, 20% and 158% respectively by 2031-'60 relative to 1996-2013. In addition, average spring wheat acreage share is projected to decline by 74% and alfalfa acreage will remain unaffected. On the other hand, in the western Dakotas counties where soybean shares are excluded, corn and grass acreage is expected to decline by 18% and 31% respectively, whereas spring wheat acreage is expected to go up by 179% by 2031-60 relative to 1996-2013. We expect the alfalfa acreage share to remain unaffected in the future for western counties as well. A regional consequence is that medium-term changes in climate will favor more wheat acres on the west and more corn and soybeans production on the east of the Missouri River.
Publications
- Type:
Journal Articles
Status:
Accepted
Year Published:
2017
Citation:
Wang, T., Luri, M., Janssen, L., Hennseey, D.A., Feng, H., Wimberly, M.C., In Review. Determinants of
motives for land use decisions at the marings of the Corn Belt. Ecological Economics. Accepted, 2016
- Type:
Journal Articles
Status:
Submitted
Year Published:
2017
Citation:
M. Wimberly, Larry Janssen, David Hennessy, Moses Luri, Niaz Chowdhury, Hongli Feng Agricultural Land Use Change and Grassland Loss in the Eastern Dakotas: A Farm-Level Analysis, Journal: Land Use Policy. Revise and resubmit invited, 2016
- Type:
Other
Status:
Published
Year Published:
2016
Citation:
Wang, T., M. Doidge, H. Feng, D.A. Hennessy. 2016. Rotational Grazing and Land Conversion in South Dakota. South Dakota State University Extension, iGrow article.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Crop Competitiveness and Future Climate Change in the Northern Great Plains. (with G. Arora*, D.A. Hennessy, A. Christopher J.) Agricultural & Applied Economics Association (AAEA) Annual Meeting, July 28-Aug 2, 2016, Boston, MA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Strategic Grasslands Conversions and Conservation Easement Acquisitions in the Dakotas: Analysis using Remotely Sensed Data. (with G. Arora, D.A. Hennessy, P. Wolter) Agricultural & Applied Economics Association (AAEA) Annual Meeting, July 28-Aug 2, 2016, Boston, MA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Grassland Easement Evaluation and Acquisition: an Integrated Framework. (with R. Miao*, D.A. Hennessy) Agricultural & Applied Economics Association (AAEA) Annual Meeting, July 28-Aug 2, 2016, Boston, MA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Perception Biases and Land Use Changes. (with D.A. Hennessy, T. Wang). Presented at the 9th Annual MSU/UM/WMU Energy & Environmental Economics Day, August 25, 2016. Also presented at Renmin University, China Agricultural University, and Center University of Finance and Economics in June, 2016.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Farmers Rankings of the Determinants of Land Use Decisions at the Margins of the Corn Belt. (with T. Wang*, M. Luri, L. Janssen, D. Hennessy, M. Wimberly, G. Arora.) Agricultural & Applied Economics Association (AAEA) Annual Meeting, July 28-Aug 2, 2016, Boston, MA.
- Type:
Journal Articles
Status:
Submitted
Year Published:
2016
Citation:
Arora, G., P.T. Wolter, H. Feng, and D.A. Hennessy (2016). Land Use Change and Policy in Iowas Loess Hills. Sustainable Agricultural Research (submitted)
|
Progress 02/01/15 to 01/31/16
Outputs
Target Audience:Farmers/landowners, researchers, conservation managers at government agencies or non-government organizations. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?This project provided training opportunities for four graduate students: Gaurav Arora, PhD student in Economics, Iowa State University; Moses Luri and Md. Niaz Chowdhury, MS students in Economics, South Dakota State University; Benjamin Uecker, Natural Resource Management; student, North Dakota State University. How have the results been disseminated to communities of interest?Project team members presented results at scientific meetings, wrote commentaries on research results, published datasets and maps on websites, and traveled to the study region to talk with land managers. More details on conference presentations and the commentaries are provided in the products section. What do you plan to do during the next reporting period to accomplish the goals?We plan to (1) refine the characterization of land use changes in the Dakotas and relate the changes to climate and market conditions; (2) refine the framework of landowners' decision making that incorporates their perceptions of neighborhood land use and infrastructure conditions; (3) improve our Cornbelt shift modeling framework and yield-profit-land use modeling framework; (4) identify future climate scenarios that will be used to predict the evolution of future production systems and design a strategy to apply these scenarios to our analytical framework; (5) discuss alternative adaptation strategies based on established framework.
Impacts
What was accomplished under these goals?
There is abundant evidence that significant land use changes have occurred in the western Corn Belt in recent decades. It is important that we understand the drivers behind these land use changes in the face of climate change. Our project provided an understanding of these drivers with data-driven research. In the past year, we identified landowners' rankings of different driving factors and in turn what determined their rankings. We also identified how weather and soil conditions have affected crop yields and land use shifts. We laid the foundation for further research in the coming year about the likely impacts of climate changes and the adaptation strategies that could be beneficial. Objective 1) In the past year all research components needed for the study have been collected and analyzed. Also a website showing the results has been constructed and finished (www.ndsu.edu/climate). Maps have been made usinggeographic information system (GIS) to show these climatic trends throughout the state. These maps are also portrayed on the website so the public can view them. We have dealt some methodological issues in characterizing climate changes and published the results in two journal papers and some conference proceedings. A list of literature review and a master student thesis will be added during the next reporting period. Objective 2) We utilized historical, 30-meter, satellite sensor data for 1984 and later, to better quantify the onset of land use change leading up to the first years of the cropland data layer (CDL) archive. Specifically, we designed and implemented a robust satellite image processing algorithm on the raw Landsat imagery acquired from the U.S. Geological Survey's online archive that dated back to 1984. We quantified corn, soybeans, wheat, alfalfa, and grass areas using multi-spectral visible and infrared reflectance information recorded by the Landsat Thematic Mapper (TM) sensor. Our algorithm utilized each crop's characteristic signature on the sensor's spectral bands based on its unique phenology that determines the best times of year for its identification. Visual cross-validations against the existing CDL products were used to specify the thresholds for respective characterization indices. We also evaluated the accuracy of our algorithm based on about 256 field data points that was recorded for South-East South Dakota on September 27, 2015. Our robust algorithm reveals a remarkable improvement over the CDL's accuracy of characterizing the grasses and alfalfa. We will use satellite data to examine the spatial pattern of land use changes and the underlying drivers. The work is accepted for presentation at the 2016 meeting of the Agricultural and Applied Economics of Association (AAEA). Objective 3) The Farmland Use Decision 2015 survey of producers and landowners in the Dakotas was developed to obtain data on their: (1) recent and projected agricultural land use patterns, (2) land use conversion (grass to crop/ crop to grass), and (3) views on the main drivers of land use change and conversion. The perspectives of agricultural producers are especially important if we wish to understand the dynamics of land use change and the major factors influencing these principal decision makers. We asked the respondents to rank the relative importance of 10 different driving forces that affected their land use decisions in the past 10 years. Most of the driving forces can be grouped into economic, technology change, policy and environmental factors. 1) Changing crop prices was the most important driving force influencing land use decisions. One-half of all respondents indicated increased crop prices was the single most important factor behind their land use decisions, especially conversion decisions. 2) Changing input prices (for seed, fertilizer, chemicals etc.) and increased crop yields (for reasons other than seed traits) were the second and third most influential impact factors. These two factors were selected by a total of 26% of all respondents. 3) Changing weather / climate ranked 4th in terms of percent of respondents selecting this item as their most influential decision factor. However, only 6.9% of respondents selected this item as their most important decision factor. Based on respondent comments, this factor may reflect the extent to which some farmers encountered flood or drought issues. 4) More efficient crop equipment, pest management practices and crop insurance factors were the next items listed. Overall, the main results from this 2015 producer survey highlight the widespread extent of producer participation in both changing land use patterns and land conversion occurring in the PPR. The other highlight is the importance of economic and technology factors on producer decisions concerning land use and land conversion. We also found that the importance of crop output prices, crop input prices, innovations in cropping equipment and weather patterns on land use decisions grow as one moves north toward the economic margin. Land in more highly sloped areas was found to be more sensitive to crop prices and crop insurance policies. Results on determinants of farmers' rankings on the factors and how the importance of the factors changes across regions are reported in a manuscript that is at the final stage of preparation for journal submission and has been accepted for presentation at the 2016 AAEA annual meeting. Objective 4) We analyzed "Cornbelt shift" by investigating the historical county-level changes of harvested acres of corn, spring and winter wheat from 1955 to 2014. We graphically illustrated the shift of corn belt. We also constructed county-level weather variables including, growing degree days (GDD), overheating degree days (OverDD), and precipitation and estimated how the shift of production centers were related to these weather variables. We empirically quantified the impact of various influencing factors on crop production shift including, e.g., time, weather, and time-weather interactions, using linear and quantile dynamic panel data models. By use of a spatially delineated dataset, Propensity Score Matching to construct pair comparisons and flexible Difference-in-Difference regression design, we estimated the impact of a corn-based ethanol plant on nearby corn-acres. By contrast with recent research for the United States as a whole, we could not discern a significant uniform impact on corn or tilled acres due to the presence of North Dakota ethanol plants. These results are reported in a 2016 working paper. We also established a model that predicted how yields of major crops are related to weather and soil conditions. We contributed to scientific knowledge by analyzing all four major crops (corn, soybean, wheat, and grass) in our study region, not just an individual crop. We took into account the non-linear impact of temperature and precipitation on crop yields. This yield model was then linked to output and input prices to allow for the estimates of the economic competitiveness of each crop which would then lead to land use changes among the crops. We are currently in the process of linking future climate projections to this yield modeling framework so that we could analyze the impacts of alternative climate scenarios. This work is also accepted for presentation at the 2016 AAEA meeting. Objective 5) This objective builds on the outcomes from objectives 1-4. In the past year, we laid the foundation to conduct work for this objective. Our Cornbelt shift modeling framework and our yield-profit-land use modeling framework will be used as a basis to analyze the impacts of alternative climate scenarios and adaptation strategies. The substantial work required for this objective will be conducted in the next year, as is planned in our grant proposal.
Publications
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2015
Citation:
Luri, Moses. 2015. Drivers of agricultural land use change and management decisions in the Dakotas: the influence of climate change and other factors. M.S. Thesis, Economics Dept., South Dakota State University, Brookings, SD.
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2016
Citation:
Chowdhury, Md. Niaz. 2016. Investigating Grassland and Cropland Conversion Decisions in the Dakotas, 2015 Producer Survey and Analysis. M.S. Thesis, Economics Dept. South Dakota State University, Brookings, SD.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Janssen, L; M. Luri, Md. Chowdhury, H. Feng and D. Hennessy. 2015. Farmland Use Decisions and Grassland Conversion in the Dakotas, 2015 Producer Survey and Analysis. IN: Proceedings Issue of Americas Grassland Conference: Partnerships for Grassland Conservation 3rd Biennial Conference, Ft. Collins, CO. Sept 29 2015. (proceeding issue is forthcoming, a powerpoint presentation was made at the conference).
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2015
Citation:
Janssen, L.; M. Luri, Md. Chowdhury, H. Feng, and D. Hennessy. 2015. Farmland Use Decisions and Grassland Conversion in the Dakotas: Report and Analysis of 2015 Survey. Plains and Prairie Potholes LLC Monthly Science Webinar Presentation, Dec. 2.
- Type:
Other
Status:
Published
Year Published:
2015
Citation:
Janssen, L; M. Luri, Md. Chowdhury, H. Feng & D. Hennessy.2015. Farmland Use Decisions in the Dakotas: Key Results from the 2015 Producer Survey. Economics Commentator No. 557. Economics Dept. South Dakota State University. November 20, 2015. (this manuscript was also sent to all 2015 survey respondents).
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Arora, G., P.T. Wolter, D.A. Hennessy, and H. Feng. Characterizing Dakotas Land Use Changes using Historical Satellite Sensor Data: 1984-2014. Proceedings for the conference: Americas Grasslands: Partnerships for Grassland Conservation, the Third Biennial Conference on the Conservation of Americas Grasslands, Ft. Collins, Colorado; September 29-October 1, 2015.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Arora, G., P.T. Wolter, D.A. Hennessy, and H. Feng. Role of Ethanol Plants in Dakotas Land Use Change: Analysis Using Remotely Sensed Data. Proceedings for the conference: Americas Grasslands: Partnerships for Grassland Conservation, The Third Biennial Conference on the Conservation of Americas Grasslands, Ft. Collins, Colorado; September 29-October 1, 2015
- Type:
Other
Status:
Published
Year Published:
2016
Citation:
Arora, G., P.T. Wolter, D.A. Hennessy, and H. Feng. Role of Ethanol Plants in Dakotas Land Use Change: Incorporating Flexible Trends in the Difference-in-Difference Framework with Remotely-Sensed Data. Working Paper 16-WP 564, March 2016, Center for Agricultural and Rural Development, Iowa State University.
- Type:
Other
Status:
Published
Year Published:
2015
Citation:
Bauman, P. and L. Janssen. 2015. New SDSU Survey on Land Use Decisions Highlights Role of Grasslands. IGROW, SDSU Extension, Dec. 9.
- Type:
Journal Articles
Status:
Published
Year Published:
2015
Citation:
Aky�z, F. A., J. K. Ransom. 2015: Growing Degree Day Calculation Method Comparison between Two Methods in the Northern Edge of the US Corn Belt Journal of Service Climatology. Volume 2015, No. 2, 18 Dec 2015.
- Type:
Journal Articles
Status:
Published
Year Published:
2015
Citation:
Ryberg, K. R., F. A. Akyuz, A. V. Vecchia, W. Lin. 2015: Changes in Seasonality and Timing of Peak Streamflow in Snow and Semi-Arid Climates of the North-Central United States, 1910-2012. Journal Hydrological Processes. Article first published online: 11 NOV 2015, DOI: 10.1002/hyp.10693.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Leelaruban, N, H. Simsek, M. S. Odabas, F. A. Aky�z, G. Padmanabhan. 2015: Effect of Drought on Corn (Zea Mays L.) Yield in North Dakota, USA. ASBE 2015 Annual International Meeting. Jul 26-29, 2015. New Orleans, LA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Uecker, B, and F. A. Akyuz. Climate Change Throughout the Dakotas. American Society of Agricultural and Biological Engineers Intersectional Meeting (ASABE-NC), Fargo, ND. April 10-11, 2015.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Ryberg, K. R., F. A. Akyuz, A. V. Vecchia, W. Lin. 2015: Changes in Seasonality and Timing of Peak Streamflow in the North-Central United States, 1910-2012. 2015 Western SD Hydrology Conference. Rapid City, SD.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Ryberg, K. R., A. V. Vecchia, F. A. Akyuz, W. Lin. 2015: Tree-Ring Based Estimates of Long-Term Seasonal Precipitation in the Souris River Region of Saskatchewan, North Dakota, and Manitoba. 68th National Conference of the Canadian Water Resources Association.
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Progress 02/01/14 to 01/31/15
Outputs
Target Audience: Farmers/Landowners; Researchers. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? Three graduate students were supported by this project: Gaurav Arora, PhD student in Economics, Iowa State University; Moses Luri, MS student in Economics, South Dakota State University; Benjamin Uecker, Natural Resource Management student, North Dakota State University. How have the results been disseminated to communities of interest? In this first year of the project, we have set up a website where project information is posted. For the project survey on land use decisions, we made a news release through South Dakota State University and the information can be found online. The project investigators have all taken a field trip guided by a local extension specialist. This lays a foundation to make practical connection with the local communities. What do you plan to do during the next reporting period to accomplish the goals? (1) Complete characterizing land use trends with raw Landsat surface reflectance data. (2) Now that the survey has mostly been returned. We will next analyze survey data to examine how farmers make land use changes and how their decisions are affected by climate changes in their locality. (3) As we understand more of our remote sensing land use data and other data regarding social-economic infrastructure, we will proceed to investigate how agricultural production systems have changed in response to different factors including climate conditions. (4) We will start scenario analysis as outlined in Objective 5.
Impacts
What was accomplished under these goals?
Land use at the fringe of the Corn Belt is changing, but why is unclear. Potential causes include policy, technology and climate change. This grant work is seeking to distinguish between these effects. During the first year we have generated and assembled data sources, including on land use, weather and markets. We have also sought direct input from 3,000 North and South Dakota land owners regarding their choices, motives and perceptions. Most of our work has not yet progressed to the point where we have findings to share. One tentative conclusion we have arrived at is that, when compared to land slightly further away, the local effect of an example infrastructure, an ethanol plant, on land use is difficult to identify. Objective 1: In the past year climate data consisting of temperature maximum, temperature minimum and precipitation and other data were collected for each county in North Dakota and South Dakota by Ben Uecker at North Dakota State University using ACIS query builder. Data were gathered using longitude and latitude coordinates and span 1950-2014. Using the temperature data accumulated Growing degree-days for each county were then calculated. All these data were used to make monthly and yearly graphs, which display time series including trend and annual fluctuations with unique regional characterizations. Standardized precipitation index (SPI) data were also collected for each county spanning 119 years (1895-2014). Data were found using West Wide Drought Tracker, maintained by Oregon State. Graphs were also made showing the changing SPI throughout time. Season length data were obtained for each county using ACIS 2 query builder. Both query builders are maintained by NOAA. All of these data, plus other data sets are available at a website for public view. Finally a presentation was given at an ASABE conference showing off some of the findings and also telling people about the website. Objective 2: We have tested and are now implementing a robust strategy to map and quantify corn/soybean tillage shifts beyond the historic western edge of the Corn Belt from neighboring Minnesota and Iowa into the Dakotas. Archived Landsat surface reflectance data (1984 to 2006) are being used on a near-annual time step to extend previous mapping and analysis efforts (by Wright & Wimberly) back approximately 22 additional years, which predates NASS Cropland Data Layer mapping effort in this region. Image processing work has been completed for two Landsat footprints (rows 29 & 30) within the eastern orbital path (P30), figure available upon request. Analysis of Landsat images in the western Landsat path (P31) are now underway. Based on preliminary Results from analyzing early remote sensing data, the biggest westward expansion of corn tillage area occurred in approximately 1993, with subsequent minor contractions and expansions leading up to 2005. Figures are available upon request. The Landsat-based corn and soybean area summaries for selected counties within Landsat Path 30 generally agree with those reported at the county level by USDA NASS for the same time periods, with a few notable exceptions. Tables are available upon request. Deviations between these fine grained (1 pixel = 0.09 ha) area estimates from perfect parity with coarse, county-level, NASS data were expected. However, some coarse disparities highlight areas where work is needed to refine discrimination criterion separating corn and soybean from other crops -- which is now underway. Our strategy of using available early September imagery holds seasonal difference to an absolute minimum. However, slight seasonal annual variation in corn and soybean crop senescence is likely to have produced the larger disparities from the NASS estimates. In these cases, adjustments to the threshold criterion are currently being applied. Once refined, these near-annual, pixel-wise summaries of corn tillage area will be used with spatial data from Objectives 1 & 4 to better understand driving mechanisms of observed Cornbelt expansion. Objective 3. During 2014, the mail survey instrument "Farmland Use Decisions in the Dakota's" was developed after many iterations. The ongoing data collection on the "Farmland Use decisions in the Dakotas" project by the Iowa State Survey Center is based on a questionnaire designed using collective inputs from all members of this grant project team. Larry Janssen and Moses Luri coordinated the questionnaire development process over several months beginning May 2014, after which project co-PIs and graduate students provided input. At this point, further questionnaire revision was primarily drafted by Jansen, Luri, Feng and Hennessy with substantial input from Carter Anderson of South Dakota Agricultural Statistics Service. Mr. Anderson explained some new requirements (as of 2014) by NASS on external surveys it conducts, including that all mail surveys be supplemented with a follow up phone survey and that surveys be shorter so as to be suitable for both mail and telephone surveying. A refined version of the survey draft was later submitted to NASS to commence work. However, NASS's charges significantly exceeded the amount originally posited and budgeted for it ($63,000 vs. $31,000). As a result, the Iowa State Survey Center (ISSC) was contracted in December 2014, as a lower cost alternative. In addition we found it necessary to seek, and we obtained, additional funding to support maintaining our desired survey size of 3,000. The first mailing was sent around February 20, 2015 and the second mailing was sent around March 15. As of April 17, the number of useable completed survey responses is close to the 1,050 completion goal, or 35% of the original sample size of 3,000 farm operators. Questions in the Farmland Use Decision survey instrument are focused on current farm operations as well as possible changes that may have occurred in the past 10 years (since 2004). The seven sections are titled: A: Farm Operator and Operation, B: Crop System, C: Land Use and Cropping Decisions, D: Market Outlets and Infrastructure, E: Local Changes in Agricultural Land Use Patterns, F: Weather Patterns / Adversity, and G: Farm Business or Operator Characteristics. The summer of 2015 will be devoted to analysis based on survey data, and development of Mr. Luri's Master's thesis. The remainder of 2015 will be devoted to publication development from this effort and working with other team members on using the survey results to more fully achieve other objectives of this NIFA grant. Objective 4: The main task of Objective 4 is to empirically disentangle the impacts of climate and other driving factors on the changes of land use and production system in Dakotas. We attempt to focus on the role of an integrated network of infrastructure. Soil moisture, GDD and other weather data are available, see objective 1 above. Gaurav Arora has established the availability of related economic and infrastructure datasets, including: (i) historical crop/hay prices and yields, (ii) soil quality, (iii) land value and rental rates, (iv) government payment, (v) roads, highways, railroads, (vi) population density, (vii) general commercial activities, (viii) ethanol plant locations, capacity and start-up dates, (ix) locations of active grain elevator and other user agricultural infrastructure. Problems have arisen in assembling the data. The main issues is that the data is available at different spatial aggregation levels and over different time periods, therefore constructing a consistent panel dataset has been a challenging task. But this may enable us to analyze the issue from multiple perspectives. Work has been initiated that seeks to use infrastructure data, specifically ethanol plant openings, to land use conversion as established under Objective 2. Objective 5: This objective is not scheduled to be addressed in the first year.
Publications
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2014
Citation:
Gaurav Arora, David A. Hennessy, Hongli Feng. Role of Ethanol Plants in Dakotas Land Use Change. Poster presentation at The 2014 Heartland Environmental and Resource Economics Workshop, University of Illinois, Urbana-Champaign.
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2015
Citation:
Benjamin Uecker. Climate Change throughout the Dakota's. Presented at 2015 ASABE North Central Intersectional Conference, Fargo, North Dakota.
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