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Social-ecological analysis of timely rice planting in Eastern India

Timely crop planting is a foundation for climate-resilient rice-wheat systems of the Eastern Gangetic Plains—a global food insecurity and poverty hotspot. We hypothesize that the capacity of individual farmers to plant on time varies considerably, shaped by multifaceted enabling factors and constrai...

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Autores principales: Urfels, Anton, McDonald, Andrew J., van Halsema, Gerardo, Struik, Paul C., Kumar, Pankaj, Malik, Ram K., Poonia, S. P., Balwinder-Singh, Singh, Deepak K., Singh, Madhulika, Krupnik, Timothy J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Paris 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892698/
https://www.ncbi.nlm.nih.gov/pubmed/33680098
http://dx.doi.org/10.1007/s13593-021-00668-1
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author Urfels, Anton
McDonald, Andrew J.
van Halsema, Gerardo
Struik, Paul C.
Kumar, Pankaj
Malik, Ram K.
Poonia, S. P.
Balwinder-Singh
Singh, Deepak K.
Singh, Madhulika
Krupnik, Timothy J.
author_facet Urfels, Anton
McDonald, Andrew J.
van Halsema, Gerardo
Struik, Paul C.
Kumar, Pankaj
Malik, Ram K.
Poonia, S. P.
Balwinder-Singh
Singh, Deepak K.
Singh, Madhulika
Krupnik, Timothy J.
author_sort Urfels, Anton
collection PubMed
description Timely crop planting is a foundation for climate-resilient rice-wheat systems of the Eastern Gangetic Plains—a global food insecurity and poverty hotspot. We hypothesize that the capacity of individual farmers to plant on time varies considerably, shaped by multifaceted enabling factors and constraints that are poorly understood. To address this knowledge gap, two complementary datasets were used to characterize drivers and decision processes that govern the timing of rice planting in this region. The first dataset was a large agricultural management survey (rice-wheat: n = 15,245; of which rice: n = 7597) from a broad geographic region that was analyzed by machine learning methods. The second dataset was a discussion-based survey (n = 112) from a more limited geography that we analyzed with graph theory tools to elicit nuanced information on planting decisions. By combining insights from these methods, we show for the first time that differences in rice planting times are primarily shaped by ecosystem and climate factors while social factors play a prominent secondary role. Monsoon onset, surface and groundwater availability, and land type determine village-scale mean planting times whereas, for resource-constrained farmers who tend to plant later ceteris paribus, planting is further influenced by access to farm machinery, seed, fertilizer, and labor. Also, a critical threshold for economically efficient pumping appears at a groundwater depth of around 4.5 m; below this depth, farmers do not irrigate and delay planting. Without collective action to spread risk through synchronous timely planting, ecosystem factors such as threats posed by pests and wild animals may further deter early planting by individual farmers. Accordingly, we propose a three-pronged strategy that combines targeted strengthening of agricultural input chains, agroadvisory development, and coordinated rice planting and wildlife conservation to support climate-resilient agricultural development in the Eastern Gangetic Plains.
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spelling pubmed-78926982021-03-03 Social-ecological analysis of timely rice planting in Eastern India Urfels, Anton McDonald, Andrew J. van Halsema, Gerardo Struik, Paul C. Kumar, Pankaj Malik, Ram K. Poonia, S. P. Balwinder-Singh Singh, Deepak K. Singh, Madhulika Krupnik, Timothy J. Agron Sustain Dev Research Article Timely crop planting is a foundation for climate-resilient rice-wheat systems of the Eastern Gangetic Plains—a global food insecurity and poverty hotspot. We hypothesize that the capacity of individual farmers to plant on time varies considerably, shaped by multifaceted enabling factors and constraints that are poorly understood. To address this knowledge gap, two complementary datasets were used to characterize drivers and decision processes that govern the timing of rice planting in this region. The first dataset was a large agricultural management survey (rice-wheat: n = 15,245; of which rice: n = 7597) from a broad geographic region that was analyzed by machine learning methods. The second dataset was a discussion-based survey (n = 112) from a more limited geography that we analyzed with graph theory tools to elicit nuanced information on planting decisions. By combining insights from these methods, we show for the first time that differences in rice planting times are primarily shaped by ecosystem and climate factors while social factors play a prominent secondary role. Monsoon onset, surface and groundwater availability, and land type determine village-scale mean planting times whereas, for resource-constrained farmers who tend to plant later ceteris paribus, planting is further influenced by access to farm machinery, seed, fertilizer, and labor. Also, a critical threshold for economically efficient pumping appears at a groundwater depth of around 4.5 m; below this depth, farmers do not irrigate and delay planting. Without collective action to spread risk through synchronous timely planting, ecosystem factors such as threats posed by pests and wild animals may further deter early planting by individual farmers. Accordingly, we propose a three-pronged strategy that combines targeted strengthening of agricultural input chains, agroadvisory development, and coordinated rice planting and wildlife conservation to support climate-resilient agricultural development in the Eastern Gangetic Plains. Springer Paris 2021-02-18 2021 /pmc/articles/PMC7892698/ /pubmed/33680098 http://dx.doi.org/10.1007/s13593-021-00668-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Urfels, Anton
McDonald, Andrew J.
van Halsema, Gerardo
Struik, Paul C.
Kumar, Pankaj
Malik, Ram K.
Poonia, S. P.
Balwinder-Singh
Singh, Deepak K.
Singh, Madhulika
Krupnik, Timothy J.
Social-ecological analysis of timely rice planting in Eastern India
title Social-ecological analysis of timely rice planting in Eastern India
title_full Social-ecological analysis of timely rice planting in Eastern India
title_fullStr Social-ecological analysis of timely rice planting in Eastern India
title_full_unstemmed Social-ecological analysis of timely rice planting in Eastern India
title_short Social-ecological analysis of timely rice planting in Eastern India
title_sort social-ecological analysis of timely rice planting in eastern india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892698/
https://www.ncbi.nlm.nih.gov/pubmed/33680098
http://dx.doi.org/10.1007/s13593-021-00668-1
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