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A (mis)alignment of farmer experience and perceptions of climate change in the U.S. inland Pacific Northwest

Abstract

Climate change is expected to have heterogeneous effects on agriculture across the USA, where temperature and precipitation regimes are already changing. While the overall effect of climate change on agriculture is uncertain, farmers’ perceptions of current and future climate and weather conditions will be a key factor in how they adapt. This paper analyzes data from paired surveys (N = 817) and natural variation from baseline weather across the inland Pacific Northwest (iPNW), to determine if long-term, gradual changes in precipitation, and temperature distributions affect farmers’ weather perceptions and intentions to adapt. We note that some areas in the iPNW have experienced significant changes in weather, while others have remained relatively constant. However, we find no relationship between changes in temperature and precipitation distributions and individuals’ perceptions and intentions to adapt. Our findings provide evidence that gradual, long-term changes in weather are temporally incongruous with human perception, which can impede support for climate action policy and adaptation strategies.

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Notes

  1. Harmful growing degree days are periods where maximum temperatures exceed a crop’s ability to transpire (around 30 °C), damaging the plant and reducing yields for the farmer (Schlenker and Roberts 2009).

  2. Studies suggest that belief in anthropogenic climate change has implications for an individual’s subsequent support of mitigation and adaption actions (Arbuckle et al. 2013b; Hyland et al. 2015; Chatrchyan et al. 2017), although climate change attitudes provide weak evidence in support of actually implemented climate-related changes in agricultural production (Schattman et al. 2018a).

  3. Results from survey 1 were not weighted since the calculated base weights were very close to one (ranging between 0.957 and 1.09). This confirmed that NASS was successful in identifying a representative sample.

  4. Other analysis from the REACCH (Roesch-McNally 2018) project uses the entire sample, since it was not necessary to geolocate farms in much of this work. Moreover, we have statistically compared results from farms with and without locations and found no significant difference in their responses to the relevant survey questions (p = .42).

  5. Using kurtosis as a metric may also be relevant given the importance of tails in weather distributions, but statistical methods for these moments are less developed.

  6. Note that the results using the average daily temperature (used by Egan and Mullin 2012) are nearly identical to those using maximum temperature.

  7. Year is a countable number from 0 (1981) to 35 (2015).

  8. This is a combined model but provides equivalent point estimates as 12 individual models for each month.

  9. This transformation was necessary to fulfill the normality assumption.

  10. Four permutations of these variables are presented in the “Results” section, but results were qualitatively similar in coefficient sign and significance across most specifications.

  11. A formal (Ramsey) test was used to evaluate omitted variables and did not find evidence of omitted variables.

  12. Psychological distance is the cognitive separation between the self and other entities (persons, places, times, etc.) Construal level theory outlines four key dimensions of such psychological distance: geographical distance; temporal distance; distance between the perceiver and a social target; and uncertainty (Spence et al. 2011). Climate change is distant on all of these dimensions.

References

  • Abatzoglou JT, Rupp DE, Mote PW (2014) Seasonal climate variability and change in the Pacific Northwest of the United States. J Clim 27(5):2125–2142. https://doi.org/10.1175/JCLI-D-13-00218.1

  • Ajzen I, Fishbein M (1977) Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychol Bull 84(5):888. https://doi.org/10.1037/0033-2909.84.5.888

  • Ajzen I, Fishbein M (2005) The Influence of Attitudes on Behavior. In Albarracín D, Johnson BT, Zanna MP (Eds.), The handbook of attitudes (p. 173–221). Lawrence Erlbaum Associates Publishers

  • Anhalt-Depies CM, Knoot TG, Rissman AR, Sharp AK, Martin KJ (2016) Understanding climate adaptation on public lands in the Upper Midwest: implications for monitoring and tracking progress. Environ Manag 57(5):987–997. https://doi.org/10.1007/s00267-016-0673-7

  • Arbuckle JG, Morton LW, Hobbs J (2013) Farmer beliefs and concerns about climate change and attitudes toward adaptation and mitigation: Evidence from Iowa. Clim Chang 118(3–4):551–563. https://doi.org/10.1007/s10584-013-0700-0

  • Arbuckle JG, Prokopy LS, Haigh T, Hobbs J, Knoot T, Knutson C, Loy A, Mase AS, McGuire J, Morton LW (2013) Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States. Clim Chang 117(4):943–950. https://doi.org/10.1007/s10584-013-0707-6

  • Asseng S, Ewert F, Martre P, Rötter R, Lobell D, Cammarano D, Kimball B, Ottman M, Wall G, Reynolds M (2015) Rising temperatures reduce global wheat production. Nat Clim Chang 5(2):143. https://doi.org/10.1038/nclimate2470

  • Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburn PJ, Rötter RP, Cammarano D (2013) Uncertainty in simulating wheat yields under climate change. Nat Clim Chang 5:143–147. https://doi.org/10.1038/nclimate1916

  • Berg W, Chase R (1992) Determination of mean rainfall from the special sensor microwave/imager (SSM/I) using a mixed lognormal distribution. J Atmos Ocean Technol 9(2):129–141. https://doi.org/10.1175/1520-0426(1992)009<0129:DOMRFT>2.0.CO;2

  • Cameron AC, Trivedi PK (2005) Microeconometrics: methods and applications. Cambridge University Press, Cambridge

  • Carlton JS, Mase AS, Knutson CL, Lemos MC, Haigh T, Todey DP, Prokopy LS (2016) The effects of extreme drought on climate change beliefs, risk perceptions, and adaptation attitudes. Clim Chang 135(2):211–226. https://doi.org/10.1007/s10584-015-1561-5

  • Chatrchyan AM, Erlebacher RC, Chaopricha NT, Chan J, Tobin D, Allred SB (2017) United States agricultural stakeholder views and decisions on climate change. Wiley Interdiscip Rev Clim Chang 8:e469. https://doi.org/10.1002/wcc.469

  • Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int J Climatol 28(15):2031–2064. https://doi.org/10.1002/joc.1688

  • Deschênes O, Greenstone M (2012) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather: reply. Am Econ Rev 102(7):3761–3773. https://doi.org/10.1257/aer.102.7.3761

  • Dillman D, Smyth JD, Christian LM (2014) Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Wiley & Sons, New York

  • Egan PJ, Mullin M (2012) Turning personal experience into political attitudes: The effect of local weather on Americans’ perceptions about global warming. J Polit 74(3):796–809. https://doi.org/10.1017/S0022381612000448

  • Feng H, Bin-Tzong C, Tai-Hsin H (2017) Residential Water Demand and Water Waste in Taiwan. Environ Econ Policy Stud 19(2):249–268. https://doi.org/10.1007/s10018-016-0154-5

  • Fisher AC, Hanemann WM, Roberts MJ, Schlenker W (2012) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather: comment. Am Econ Rev 102(7):3749–3760. https://doi.org/10.1257/aer.102.7.3749

  • Grothmann T, Patt A (2005) Adaptive capacity and human cognition: the process of individual adaptation to climate change. Glob Environ Chang 15(3):199–213. https://doi.org/10.1016/j.gloenvcha.2005.01.002

  • Haden VR, Niles M, Lubell M, Perlman J, Jackson LE (2012) Global and local concerns: what attitudes and beliefs motivate farmers to mitigate and adapt to climate change? PLoS One 7(12):e52882. https://doi.org/10.1371/journal.pone.0052882

  • Hamilton LC, Stampone MD (2013) Blowin’in the wind: Short-term weather and belief in anthropogenic climate change. Weather, Climate, and Society 5(2):112–119. https://doi.org/10.1175/WCAS-D-12-00048.1

  • Hausman DM (2018) Philosophy of Economics, The Stanford Encyclopedia of Philosophy. The Metaphysics Research Lab. Center for the Study of Language and Information. https://plato.stanford.edu/entries/economics/

  • Hyland JJ, Jones DL, Parkhill KA, Barnes AP, Williams AP (2015) Farmers’ perceptions of climate change: identifying types. Agric Hum Values 33(2):323–339. https://doi.org/10.1007/s10460-015-9608-9

  • Kahan DM, Peters E, Wittlin M, Slovic P, Ouellette LL, Braman D, Mandel G (2012) The polarizing impact of science literacy and numeracy on perceived climate change risks. Nat Clim Chang 2(10):732–735. https://doi.org/10.1038/nclimate1547

  • Karimi T, Stöckle C, Higgins S, Nelson R, Huggins D (2017) Projected Dryland Cropping System Shifts in the Pacific Northwest in Response to Climate Change. Front Ecol Evol 5(20). https://doi.org/10.3389/fevo.2017.00020

  • Leakey ADB, Ainsworth EA, Bernacchi CJ, Rogers A, Long SP, Ort DR (2009) Elevated CO2 effects on plant carbon, nitrogen, and water relations: six important lessons from FACE. J Exp Bot 60(10):2859–2876. https://doi.org/10.1093/jxb/erp096

  • Lobell DB, Burke MB (2008) Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation. Environ Res Lett 3(3):34007. https://doi.org/10.1088/1748-9326/3/3/034007

  • Lobell DB, Burke MB, Tebaldi C, Mastrandrea MD, Falcon WP, Naylor RL (2008) Prioritizing climate change adaptation needs for food security in 2030. Science 319(5863):607–610. https://doi.org/10.1126/science.1152339

  • Lobell DB, Field CB, Cahill KN, Bonfils C (2006) Impacts of future climate change on California perennial crop yields: Model projections with climate and crop uncertainties. Agric For Meteorol 141(2–4):208–218. https://doi.org/10.1016/j.agrformet.2006.10.006

  • Maas A, Dozier A, Manning DT, Goemans C (2016) Water storage in a changing environment: The impact of allocation institutions on value. Water Resources Research https://doi.org/10.1002/2016WR019239

  • Maaz TM, Schillinger W, Machado S, Brooks E, Johnson-Maynard J, Young L, Young F, Leslie I, Glover A, Madsen I, Esser A, Collins H, Pan W (2017) Impact of climate change adaptation strategies on winter wheat and cropping system performance across precipitation gradients in the inland Pacific Northwest, USA. Front Environ Sci (5):23. https://doi.org/10.3389/fenvs.2017.00023

  • Manning DT, Goemans C, Maas A (2017) Producer responses to surface water availability and implications for climate change adaptation. Land Econ 93(4). https://doi.org/10.3368/le.93.4.63

  • McCright AM, Marquart-Pyatt S, Shwom R, Brechin S, Allen S (2016) Ideology, capitalism, and climate: Explaining public views about climate change in the United States. Energy Res Soc Sci 21:180–189. https://doi.org/10.1016/j.erss.2016.08.003

    Article  Google Scholar 

  • McFadden J, Smith DJ, Wallander S (2018) Adoption of Drought-Tolerant Corn in the US: A Field-Level Analysis of Adoption Patterns and Emerging Trends. Selected Paper from 2018 Agricultural & Applied Economics Association Annual Meeting, Washington, DC

  • McGrath JM, Lobell DB (2013) Regional disparities in the CO2 fertilization effect and implications for crop yields. Environ Res Lett 8(1):14054. https://doi.org/10.1088/1748-9326/8/1/014054

    Article  Google Scholar 

  • Mendelsohn R, Nordhaus WD, Shaw D (1994) The impact of global warming on agriculture: a Ricardian analysis. The American economic review 753–771. www.jstor.org/stable/2118029

  • Mertz O, Mbow C, Reenberg A, Diouf A (2009) Farmers’ perceptions of climate change and agricultural adaptation strategies in rural Sahel. Environ Manag 43(5):804–816. https://doi.org/10.1007/s00267-008-9197-0

    Article  Google Scholar 

  • Morton TA, Rabinovich A, Marshall D, Bretschneider P (2011) The future that may (or may not) come: How framing changes responses to uncertainty in climate change communications. Glob Environ Chang 21(1):103–109. https://doi.org/10.1073/pnas.1007887107

    Article  Google Scholar 

  • Moser SC, Ekstrom JA (2010) A framework to diagnose barriers to climate change adaptation. Proc Natl Acad Sci 107(51):22026 LP–22022031

    Article  Google Scholar 

  • Mote PW, Salathe EP (2010) Future climate in the Pacific Northwest. Clim Chang 102(1–2):29–50. https://doi.org/10.1007/s10584-010-9848-z

    Article  Google Scholar 

  • Nelson GC, Valin H, Sands RD, Havlík P, Ahammad H, Deryng D, Elliott J, Fujimori S, Hasegawa T, Heyhoe E, Kyle P, Von Lampe M, Lotze-Campen H, Mason d’Croz D, van Meijl H, van der Mensbrugghe D, Müller C, Popp A, Robertson R, Robinson S, Schmid E, Schmitz C, Tabeau A, Willenbockel D (2014) Climate change effects on agriculture: Economic responses to biophysical shocks. Proc Natl Acad Sci 111(9):3274–3279. https://doi.org/10.1073/pnas.1222465110

  • Niles MT, Lubell M, Brown M (2015) How limiting factors drive agricultural adaptation to climate change. Agric Ecosyst Environ 200:178–185. https://doi.org/10.1016/j.agee.2014.11.010

  • Niles MT, Mueller ND (2016) Farmer perceptions of climate change: Associations with observed temperature and precipitation trends, irrigation, and climate beliefs. Glob Environ Chang 39:133–142. https://doi.org/10.1016/j.gloenvcha.2016.05.002

  • Parker LE, Abatzoglou JT (2018) Shifts in the thermal niche of almond under climate change. Clim Chang 147(1–2):211–224. https://doi.org/10.1007/s10584-017-2118-6

    Article  Google Scholar 

  • Reidmiller DR, Avery CW, Easterling DR, Kunkel KE, Lewis KLM, Maycock TK, Stewart BC, Wuebbles DJ, Fahey DW, Hibbard KA (2018) Impacts, risks, and adaptation in the United States: fourth national climate assessment, vol 2. U.S. Global Change Research Program, Washington. https://doi.org/10.7930/NCA4.2018

  • Roesch-McNally G (2018) US Inland Pacific Northwest Wheat Farmers’ Perceived Risks: Motivating Intentions to Adapt to Climate Change? Environments 5(4):49. https://doi.org/10.3390/environments5040049

    Article  Google Scholar 

  • Roesch-McNally GE, Arbuckle JG, Tyndall JC (2017) What would farmers do? Adaptation intentions under a Corn Belt climate change scenario. Agric Hum Values 34(2):333–346. https://doi.org/10.1007/s10460-016-9719-y

    Article  Google Scholar 

  • Rosenzweig C, Elliott J, Deryng D, Ruane AC, Müller C, Arneth A, Boote KJ, Folberth C, Glotter M, Khabarov N, Neumann K (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci 111(9):3268–3273. https://doi.org/10.1073/pnas.1222463110

    Article  Google Scholar 

  • Running K, Burke J, Shipley K (2017) Perceptions of environmental change and climate concern among Idaho’s farmers. Soc Nat Resour 30(6):659–673. https://doi.org/10.1080/08941920.2016.1239151

    Article  Google Scholar 

  • Rupp DE, Abatzoglou JT, Mote PW (2017) Projections of 21st century climate of the Columbia River Basin. Clim Dyn 49(5–6):1783–1799. https://doi.org/10.1007/s00382-016-3418-7

    Article  Google Scholar 

  • Schattman RE, Méndez VE, Merrill SC, Zia A (2018) Mixed methods approach to understanding farmer and agricultural advisor perceptions of climate change and adaptation in Vermont, United States. Agroecol Sustain Food Syst 42(2):121–148. https://doi.org/10.1080/21683565.2017.1357667

    Article  Google Scholar 

  • Schattman RE, Roesch-McNally G, Wiener S, Niles MT, Hollinger DY (2018) Farm service agency employee intentions to use weather and climate data in professional services. Renewable Agric Food Syst 33(3):212–221. https://doi.org/10.1017/S1742170517000783

    Article  Google Scholar 

  • Schillinger WF (2017) Winter Pea: Promising New Crop for Washington’s Dryland Wheat-Fallow Region. Front Ecol Evol 5(43). https://doi.org/10.3389/fevo.2017.00043

  • Schillinger WF, Papendick RI, Guy SO, Rasmussen PE, Van Kessel C (2015) Dryland cropping in the western United States. In: Peterson GA, Unger PW, Payne WA (eds) Dryland agriculture, pp 365–393. https://doi.org/10.2134/agronmonogr23.2ed.c11

    Chapter  Google Scholar 

  • Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc Natl Acad Sci 106(37):15594–15598. https://doi.org/10.1073/pnas.0906865106

    Article  Google Scholar 

  • Seamon E, Roesch-McNally G, McNamee L, Roth I, Wulfhorst JD, Eigenbrode S, Daley Laursen S (2016) Producer perceptions on climate change and agriculture: A statistical atlas. University of Idaho Agricultural Economic Extension Series: 17-18. https://www.reacchpna.org/sites/default/files/REACCHStatAtlasWEB.pdf

  • Semenza JC, Hall DE, Wilson DJ, Bontempo BD, Sailor DJ, George LA (2008) Public perception of climate change: voluntary mitigation and barriers to behavior change. Am J Prev Med 35(5):479–487. https://doi.org/10.1016/j.amepre.2008.08.020

    Article  Google Scholar 

  • Spence A, Poortinga W, Butler C, Pidgeon NF (2011) Perceptions of climate change and willingness to save energy related to flood experience. Nat Clim Chang 1(1):46. https://doi.org/10.1038/nclimate1059

    Article  Google Scholar 

  • Spence A, Poortinga W, Pidgeon N (2012) The psychological distance of climate change. Risk Analysis: An International Journal 32(6):957–972. https://doi.org/10.1111/j.1539-6924.2011.01695.x

    Article  Google Scholar 

  • Stein BA, Staudt A, Cross MS, Dubois NS, Enquist C, Griffis R, Hansen LJ, Hellmann JJ, Lawler JJ, Nelson EJ (2013) Preparing for and managing change: climate adaptation for biodiversity and ecosystems. Front Ecol Environ 11(9):502–510. https://doi.org/10.1890/120277

    Article  Google Scholar 

  • Stöckle CO, Higgins S, Nelson R, Abatzoglou J, Huggins D, Pan W, Karimi T, Antle J, Eigenbrode SD, Brooks E (2018) Evaluating opportunities for an increased role of winter crops as adaptation to climate change in dryland cropping systems of the US Inland Pacific Northwest. Clim Chang 146(1–2):247–261. https://doi.org/10.1007/s10584-017-1950-z

    Article  Google Scholar 

  • Takahashi B, Burnham M, Terracina-Hartman C, Sopchak AR, Selfa T (2016) Climate change perceptions of NY state farmers: the role of risk perceptions and adaptive capacity. Environ Manag 58(6):946–957. https://doi.org/10.1007/s00267-016-0742-y

    Article  Google Scholar 

  • Taylor A, de Bruin WB, Dessai S (2014) Climate change beliefs and perceptions of weather‐related changes in the United Kingdom. Risk Anal 34(11):1995–2004. https://doi.org/10.1111/risa.12234

    Article  Google Scholar 

  • Thomas DSG, Twyman C, Osbahr H, Hewitson B (2007) Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Clim Chang 83(3):301–322. Available at. https://doi.org/10.1007/s10584-006-9205-4

    Article  Google Scholar 

  • Usman MT, Reason CJC (2004) Dry spell frequencies and their variability over southern Africa. Clim Res 26(3):199–211. https://doi.org/10.3354/cr026199

    Article  Google Scholar 

  • Weber EU (2010) What shapes perceptions of climate change? Wiley Interdiscip Rev Clim Chang 1(3):332–342. https://doi.org/10.1002/wcc.41

    Article  Google Scholar 

  • Weber EU, Sonka S (1994) Production and pricing decisions in cash-crop farming: effects of decision traits and climate change expectations. In: Jacobsen BH, Pedersen DE, Christensen J, Rasmussen S (eds) Farmers’ Decision Making: A Descriptive Approach. Institute for Agricultural Economics, Copenhagen

    Google Scholar 

  • Whitmarsh L (2008) Are flood victims more concerned about climate change than other people? The role of direct experience in risk perception and behavioural response. J Risk Res 11(3):351–374

    Article  Google Scholar 

  • Whitmarsh L, O’Neill S (2010) Green identity, green living? The role of pro-environmental self-identity in determining consistency across diverse pro-environmental behaviours. J Environ Psychol 30(3):305–314. https://doi.org/10.1016/j.jenvp.2010.01.003

    Article  Google Scholar 

  • Woods BA, Nielsen HØ, Pedersen AB, Kristofersson D (2017) Farmers’ perceptions of climate change and their likely responses in Danish agriculture. Land Use Policy 65:109–120. https://doi.org/10.1016/j.landusepol.2017.04.007

    Article  Google Scholar 

  • Yorgey GG, Hall SA, Allen ER, Whitefield EM, Embertson NM, Jones VP, Saari BR, Rajagopalan K, Roesch-McNally GE, Van Horne B, Abatzoglou JT, Collins HP, Houston LL, Ewing TW, Kruger CE (2017) Northwest U.S. Agriculture in a Changing Climate: Collaboratively Defined Research and Extension Priorities. Front Environ Sci 5:52. https://doi.org/10.3389/fenvs.2017.00052

    Article  Google Scholar 

  • Yue S, Hashino M (2007) Probability distribution of annual, seasonal and monthly precipitation in Japan. Hydrol Sci J 52(5):863–877. https://doi.org/10.1623/hysj.52.5.863

    Article  Google Scholar 

  • Zanocco C, Boudet H, Nilson R, Satein H, Whitley H, Flora J (2018) Place, proximity, and perceived harm: extreme weather events and views about climate change. Clim Chang 149(3-4):349–365. https://doi.org/10.1007/s10584-018-2251-x

    Article  Google Scholar 

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Maas, A., Wardropper, C., Roesch-McNally, G. et al. A (mis)alignment of farmer experience and perceptions of climate change in the U.S. inland Pacific Northwest. Climatic Change 162, 1011–1029 (2020). https://doi.org/10.1007/s10584-020-02713-6

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Keywords

  • Climate change
  • Perceptions
  • Experience
  • Agricultural adaptation
  • Wheat
  • Weather