Project Title: Adaptation of agroecosystems to climate ... · Project Title: Adaptation of agroecosystems to climate change at the edge of the U.S. Cornbelt ―assessing different

Project Title: Adaptation of agroecosystems to climate change at

the edge of the U.S. Cornbelt―assessing different drivers in a

network of infrastructure

David A. HennessyAgroclimatology Project Directors Meeting

San Francisco, Saturday December 17th 2016

IntroductionsMultidisciplinary, seeking to integrate land use data collection and analysis with climate data collection and analysis as well as production and environmental economics, and policy analysis

All of the above: Gaurav Arora

Many collaborators, incl. T. Wang, C. Anderson

Economists: H. Feng, L. Janssen, D. Hennessy, X. Du

Climatologists: A. Akyüz, B. Uecker

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Landscape ecologists: P. Wolter (PI), M. Wimberly

Backdrop• Most land privately owned. Markets, incl. gov’t

interventions, and technological innovation matter

• Marginal between grass, corn & soybean, and small grain systems

• Grass habitat for duck, songbirds, insects

• Non-irrigated, arid and cool except in mid-summer

• For 1981-2010 to 2031-’60 timeframe and Apr.-Aug., IPCC A1B emissions scenario projects

• 2.5o C average temp increase in S. Dakota

• 57.5 mm (24.3%) precipitation increase9/24/2017 3

Objectives1. Characterize spatial & temporal patterns in climate change of relevance to Dakotas agriculture

2. Develop methodologies to discern relocation of different Dakotas agricultural production systems

3. Target informational surveys to areas assessed as sensitive to land use change

4. Spatially explicit modeling framework to assess climate and other driving factors behind adoption of ‘new’ production systems with focus on integrated network of infrastructure

5. Apply inferences drawn from 1-4 to project evolution of production systems under alternative climate scenarios and assess outcomes from alternative adaptation strategies

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Historicalbaseline

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CORN

GRASS/PASTURE

SOYBEANS

17th-30th September Raw Landsat Imagery (Surface Reflectance)

B5/10 115-190

I(C/S)148-200

NDVI 145-162

NDVI >175IN

DEX

PRO

DU

CT

CORNGRASS/

PASTURESOY ALFALFA

CO

RR

ECTI

ON

S

Clip-Out: CORN. FINAL SOY.

Clip Out: CORN, FINAL WHEAT. FINAL GRASS.

Figure: Sept Algorithm to classify Corn, Soybeans, Wheat, Alfalfa & Grass. Overlay developed lands, forest, wetlands etc. from NLCD 2006 to obtain final product

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Historical Baseline & Analysis

Year Corn/Soy Wheat Alfalfa Grass1986 912 491 646 2,4341994 935 669 419 2,5872004 960 875 388 2,4382011 2,040 248 109 1,773

Table 6: Landsat derived land use areas (in ha) for eastern South Dakota swath (1984-’05). CDL-derived areas for 2011

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Ongoing work using baseline: a) Duration analysis of grasslands asking rate of conversion and causeb) Working with USFWS on grassland easements locations and spillover implications

Statistical Yield, Land Use & Climate Projection Models: All SD &ND

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Weather Station Data

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Yield Regression, 0 , , ,

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county-level average yield in year

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decadal trend rates.hea

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t stress degree days.low Palmer's Z to indicate drought stress.high Palmer's Z to indicate wetness stress.

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ms including soil-weather interactions9/24/2017 10

Crop Trends

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Climate Projections

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Preliminary Land Use Implications

• A regional consequence is that medium-term changes in climate will favor more wheat acres west and more corn and soybeans production east of Missouri River

• These projection in acreage shares are driven solely by weather, and we do not account for any potential technological/policy interventions or any national or global-level adaptations in production systems in the future

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Decadal Summary of Weather Variables, Corn, Average both states

Variable 1950-’60

1961-’70

1971-’80

1981-’90

1991-’00

2001-’10

Growing Degree Days

757 955 1004 1010 999 940

Heat Stress Degree Days

22.8 32.1 38.7 36.9 19.9 27.9

Palmer DRY 0.60 0.35 1.02 1.09 0.18 0.65Palmer WET 0.84 1.51 0.79 0.77 2.46 1.61

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Main point is that in short run climate change is overlaid by local wet-dry cycle that is not well understood

Also, frost-free days have increased. Together with tillageInnovations, this means a longer growing season for corn

Survey• Study area: Prairie Pothole region in Eastern

Dakotas. Surveyed 37 counties in Prairie Pothole region of South Dakota, 20 in North Dakota

• Evidence of extensive land use conversion activity 2005-2014. In each county, corn + soybean acres exceeded small grain acres. Sample at least 100 acres. Sample selection was proportional by county

• 3,000 farm operators sampled. Overall useable response rate was 36.7%, higher in SD

• Data collection period was March-May 2015

• Average total farm size 1,686 acres. Average operated cropland area 1,206 acres

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Land Use Survey Responses

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Dakota Soils

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Mean annual temperature (Degrees C)

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Mean annual precipitation (mm)

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0%

10%

20%

30%

40%

50%

60%

Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10

low crop profile Medium Crop profileHigh Crop Profile

Crop and Input Prices Technical Envir. Issues

Outputprices

Input prices

Insurance policies

Labor

Drought tolerance

PestMgt

Higher yield potentialBetter

machinery

Wildlife

Weather/Climate

How much impact has each of the following had on changes you made in way you use your agricultural land?

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10 year Land Use Change: Survey

Natural Grass to Crop Tame Grass to Crop CRP to Crop CRP to Pasture Conservation Enrollment

0-5

5-10

10-15

15-20

20-25

25-30

30-35

> 35

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National Issues, Corn Belt Shift 15% Threshold

1958-1977

1977-1996

1996-2014

No changeEntryExit

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Synopsis

• Corn, soybean and cropland expansion, wheat and alfalfa contraction in area may have occurred for many reasons

• policy and market prices• technology• perhaps to some extent weather favoring corn• positive infrastructure spillovers

• Unclear how climate change will affect area land use but technology and policy may matter more

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Outputs to date• Two manuscripts in late-stages of journal reviewing

process, both on survey

• Two manuscripts in preparation for submission

• Three published proceedings, on remote sensing, role of infrastructure on land use and on survey

• Multiple extension publications

• Dissertations, 1 PhD and 2-3 MS

• Formation of interdisciplinary team to work on nexus of climate, land use metrics, policy and environmental outputs in Northern Great Plains. Segue(?) into other grant support

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Questions?

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