Social-psychological determinants of farmer intention to adopt nutrient best management practices: Implications for resilient adaptation to climate change

Doran, Elizabeth M. B.; Zia, Asim; Hurley, Stephanie; Tsai, Yushiou; Koliba, Christopher; Adair, E. Carol; Schattman, Rachel E.; Rizzo, Donna M.; Méndez, V. Ernesto

doi:10.1016/j.jenvman.2020.111304

Cited by 38 publications

(23 citation statements)

References 59 publications

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“…These impacts are likely to become more frequent or intense in a changing climate (IPCC, 2014;Zhang et al, 2020), and thus it is increasingly important to understand the barriers and drivers to strengthen farmers' adaptive capacity-the available resources or assets to mitigate, prepare for, counter, and recover from impacts (Brooks and Adger, 2005;Gallopín, 2006;Wisner et al, 2012;Cinner et al, 2018;Barnes et al, 2020;Phillips et al, 2020). Since farmers are embedded within socialecological systems, it is important to recognize that adaptive capacity is comprised of various determinants that may extend beyond the individual to the institutional or systemic levels: political regulations, poverty, vulnerability to extreme events, and others (Reed et al, 2013;Shinbrot et al, 2019;Doran et al, 2020). Hence, when evaluating adaptive capacity, its determinants must be considered across scales (Adger, 2006;.…”

Section: Introductionmentioning

confidence: 99%

Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation Strategies After Hurricane Maria: A Mixed-Methods Approach to Understanding Adaptive Capacity

Rodríguez-Cruz

Moore

Niles

2021

Front. Sustain. Food Syst.

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Farmers across the globe are experiencing compounding shocks that make evident the need to better understand potential drivers and barriers to strengthen adaptive capacity. This is especially true in the context of a disaster, where a disruption in the natural and built environment hinders livelihood strategies and exposes the underlying dynamics that perpetuate vulnerability to natural hazards. As such, the interconnections of structural and individual attributes must be considered when evaluating adaptive capacity. This paper uses a convergent mixed-methods approach to assess Puerto Rican farmers' actual and intended adoption of adaptation practices, in light of the obstacles they faced toward recovery after 2017's category four Hurricane Maria, to contribute to better understanding adaptive capacity. This study uses data from 405 farmers across Puerto Rico (87% response rate), surveyed 8 months after Maria by agricultural agents of the Extension Service of the University of Puerto Rico at Mayagüez. Quantitative data was assessed through negative binomial regressions (actual adoption) and generalized linear models (intended adoption), while qualitative data (reported obstacles) were analyzed through thematic analysis. This study found that almost half of farmers adopted an adaptation practice after Maria, and that in many cases, broader structures, such as systems of governance, farmers' social networks, and infrastructure, affect adaptive capacity more than individual perceptions of capacity. Future adaptation strategies and interventions, especially in the context of disaster, should consider the extent to which structural factors hinder individuals' ability to prepare for, respond, and recover from the impacts of these shocks. Our results show that there might be opportunity to enact new systems in light of catastrophic events, but this does not solely depend on individual actions. The mixed-methods approach used can inform future studies in better assessing adaptive capacity from a standpoint that incorporates individual and structural components.

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Section: Introductionmentioning

confidence: 99%

Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation Strategies After Hurricane Maria: A Mixed-Methods Approach to Understanding Adaptive Capacity

Rodríguez-Cruz

Moore

Niles

2021

Front. Sustain. Food Syst.

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“…Already toxic blooms of blue-green algae in summer contaminate the shallow lake waters near the urban area of Burlington Vermont, impacting local health and tourism (Isles et al, 2015). In the broad context, the BREE project is developing an integrated assessment model for the Lake Champlain region (Zia et al, 2016) with an atmospheric model (Huang et al, 2019) driving a lake circulation model, coupled to a biogeochemistry model (e.g., Isles et al, 2017), and to land-use and governance issues (Bitterman and Koliba, 2020;Doran et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the FLake Model in ERA5 for Lake Champlain

Betts

Reid

Crossett

2020

Front. Environ. Sci.

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Global model reanalyses of temperature and radiation are used for many purposes because of their spatial and temporal homogeneity. However, they use sub-models for lakes that are smaller than the model grid. This paper compares the simplified small-lake model, known as FLake, used in the European Centre global reanalysis known as ERA5, with observations made in and near Lake Champlain in northern Vermont. Lake Champlain is a challenging test for the ERA5 FLake model. The lake, which extends over several grid cells, is the lowest region at 30 m above sea level within complex mountain topography. The smoothing of the adjacent mountain topography means that the ERA5 grid cells containing the lake have higher mean elevations then 30 m, and this contributes to a small cool bias in FLake mid-summer temperatures. The seasonal cycle of FLake temperatures has a sharper peak than the observed lake temperatures. In winter, lake temperatures are close to 3°C, while the 30 m deep FLake mixed layer (ML) is near freezing. In May and June, FLake maintains a deep ML, while lake profiles are generally strongly stratified with peak temperatures near the surface several degrees above the model ML. One possible contributing reason is that inflowing river temperatures that are not considered by FLake are as much as 5°C above the lake surface temperature from April to June. The lake does develop a ML structure as it cools from the temperature peak in August, but the FLake ML cools faster and grows deeper in fall. We conclude that the vertical mixing in the FLake ML is stronger than the vertical mixing in Lake Champlain.

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“…Framing outreach to build clear connections between climate adaptive practices and factors that farmers perceive to help them achieve success on their farm, such as their quality of life or community relationships, could be an opportunity to improve adoption (Jew et al 2020). Research as to how quality of life, community well-being, and sense of environmental stewardship may interact with farmers' perceived capacity to implement new practices, a strong influence on actual practice adoption (Niles et al 2016;Doran et al 2020), could provide valuable insights for professionals seeking to strengthen farmer outreach. We propose potential action steps to incorporate these social and human dimensions into agricultural climate change outreach and communication, presented in Table 4.…”

Section: Implications For Climate Change Outreachmentioning

confidence: 99%

Climate change in the context of whole-farming systems: opportunities for improved outreach

et al. 2021

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Climate change poses a challenge to farming systems worldwide. However, existing research suggests that farmers and those providing outreach may have different climate change perspectives, and there is little understanding of how farmers prioritize climate change compared with other aspects of their farming system. To compare how farmers and outreach professionals in northern New England consider climate change within the context of whole-farming systems, we conducted mental modeling interviews with 33 farmers and 16 outreach professionals. Despite being primed to consider climate during the interviews, only 24% of farmers and 25% of outreach professionals included climate in their mental models. Key differences arose in both group’s perceptions of weather: outreach professionals focused on connections between good weather and biophysical factors, while farmers drew additional connections to factors like quality of life and overall farm success. Social factors including community well-being, public education, and farm success were significantly more likely to be included (P < 0.05), and in some cases were more influential, in farmer models compared to outreach professional models. We conclude that farmer participants did not perceive climate to be a central factor of their farming systems, and valued human and social dimensions more highly than outreach professionals perceived. These factors may warrant special consideration in efforts to make outreach meaningful to local contexts, along with framing climate change within its broader relationship to other farming system aspects. Interdisciplinary teams may be helpful in developing outreach approaches that fully contextualize climate change within farmers’ complex whole-farm management perspectives.

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Social-psychological determinants of farmer intention to adopt nutrient best management practices: Implications for resilient adaptation to climate change

Cited by 38 publications

References 59 publications

Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation Strategies After Hurricane Maria: A Mixed-Methods Approach to Understanding Adaptive Capacity

Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation Strategies After Hurricane Maria: A Mixed-Methods Approach to Understanding Adaptive Capacity

Evaluation of the FLake Model in ERA5 for Lake Champlain

Climate change in the context of whole-farming systems: opportunities for improved outreach

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