Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture

Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Baqir Lalani [verfasserIn] Steven Gray [verfasserIn] Tora Mitra-Ganguli [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA)

Übergeordnetes Werk:	In: Frontiers in Integrative Neuroscience - Frontiers Media S.A., 2008, 17(2023)
Übergeordnetes Werk:	volume:17 ; year:2023

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fnint.2023.1145744

Katalog-ID:	DOAJ089821963

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allfields	10.3389/fnint.2023.1145744 doi (DE-627)DOAJ089821963 (DE-599)DOAJ80da753dde6f456cb648d66082aa9b6b DE-627 ger DE-627 rakwb eng RC321-571 RC346-429 Baqir Lalani verfasserin aut Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space. Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA) Neurosciences. Biological psychiatry. Neuropsychiatry Neurology. Diseases of the nervous system Steven Gray verfasserin aut Tora Mitra-Ganguli verfasserin aut In Frontiers in Integrative Neuroscience Frontiers Media S.A., 2008 17(2023) (DE-627)579826406 (DE-600)2452962-X 16625145 nnns volume:17 year:2023 https://doi.org/10.3389/fnint.2023.1145744 kostenfrei https://doaj.org/article/80da753dde6f456cb648d66082aa9b6b kostenfrei https://www.frontiersin.org/articles/10.3389/fnint.2023.1145744/full kostenfrei https://doaj.org/toc/1662-5145 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2023
spelling	10.3389/fnint.2023.1145744 doi (DE-627)DOAJ089821963 (DE-599)DOAJ80da753dde6f456cb648d66082aa9b6b DE-627 ger DE-627 rakwb eng RC321-571 RC346-429 Baqir Lalani verfasserin aut Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space. Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA) Neurosciences. Biological psychiatry. Neuropsychiatry Neurology. Diseases of the nervous system Steven Gray verfasserin aut Tora Mitra-Ganguli verfasserin aut In Frontiers in Integrative Neuroscience Frontiers Media S.A., 2008 17(2023) (DE-627)579826406 (DE-600)2452962-X 16625145 nnns volume:17 year:2023 https://doi.org/10.3389/fnint.2023.1145744 kostenfrei https://doaj.org/article/80da753dde6f456cb648d66082aa9b6b kostenfrei https://www.frontiersin.org/articles/10.3389/fnint.2023.1145744/full kostenfrei https://doaj.org/toc/1662-5145 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2023
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allfieldsGer	10.3389/fnint.2023.1145744 doi (DE-627)DOAJ089821963 (DE-599)DOAJ80da753dde6f456cb648d66082aa9b6b DE-627 ger DE-627 rakwb eng RC321-571 RC346-429 Baqir Lalani verfasserin aut Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space. Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA) Neurosciences. Biological psychiatry. Neuropsychiatry Neurology. Diseases of the nervous system Steven Gray verfasserin aut Tora Mitra-Ganguli verfasserin aut In Frontiers in Integrative Neuroscience Frontiers Media S.A., 2008 17(2023) (DE-627)579826406 (DE-600)2452962-X 16625145 nnns volume:17 year:2023 https://doi.org/10.3389/fnint.2023.1145744 kostenfrei https://doaj.org/article/80da753dde6f456cb648d66082aa9b6b kostenfrei https://www.frontiersin.org/articles/10.3389/fnint.2023.1145744/full kostenfrei https://doaj.org/toc/1662-5145 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2023
allfieldsSound	10.3389/fnint.2023.1145744 doi (DE-627)DOAJ089821963 (DE-599)DOAJ80da753dde6f456cb648d66082aa9b6b DE-627 ger DE-627 rakwb eng RC321-571 RC346-429 Baqir Lalani verfasserin aut Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space. Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA) Neurosciences. Biological psychiatry. Neuropsychiatry Neurology. Diseases of the nervous system Steven Gray verfasserin aut Tora Mitra-Ganguli verfasserin aut In Frontiers in Integrative Neuroscience Frontiers Media S.A., 2008 17(2023) (DE-627)579826406 (DE-600)2452962-X 16625145 nnns volume:17 year:2023 https://doi.org/10.3389/fnint.2023.1145744 kostenfrei https://doaj.org/article/80da753dde6f456cb648d66082aa9b6b kostenfrei https://www.frontiersin.org/articles/10.3389/fnint.2023.1145744/full kostenfrei https://doaj.org/toc/1662-5145 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2023
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spellingShingle	Baqir Lalani misc RC321-571 misc RC346-429 misc Global South misc Systems Thinking (ST) misc climate change misc mobile data collection misc Climate Smart Agriculture (CSA) misc Neurosciences. Biological psychiatry. Neuropsychiatry misc Neurology. Diseases of the nervous system Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture
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topic_title	RC321-571 RC346-429 Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture Global South Systems Thinking (ST) climate change mobile data collection Climate Smart Agriculture (CSA)
topic	misc RC321-571 misc RC346-429 misc Global South misc Systems Thinking (ST) misc climate change misc mobile data collection misc Climate Smart Agriculture (CSA) misc Neurosciences. Biological psychiatry. Neuropsychiatry misc Neurology. Diseases of the nervous system
topic_unstemmed	misc RC321-571 misc RC346-429 misc Global South misc Systems Thinking (ST) misc climate change misc mobile data collection misc Climate Smart Agriculture (CSA) misc Neurosciences. Biological psychiatry. Neuropsychiatry misc Neurology. Diseases of the nervous system
topic_browse	misc RC321-571 misc RC346-429 misc Global South misc Systems Thinking (ST) misc climate change misc mobile data collection misc Climate Smart Agriculture (CSA) misc Neurosciences. Biological psychiatry. Neuropsychiatry misc Neurology. Diseases of the nervous system
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title	Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture
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title_full	Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture
author_sort	Baqir Lalani
journal	Frontiers in Integrative Neuroscience
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author_browse	Baqir Lalani Steven Gray Tora Mitra-Ganguli
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title_sort	systems thinking in an era of climate change: does cognitive neuroscience hold the key to improving environmental decision making? a perspective on climate-smart agriculture
callnumber	RC321-571
title_auth	Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture
abstract	Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space.
abstractGer	Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space.
abstract_unstemmed	Systems Thinking (ST) can be defined as a mental construct that recognises patterns and connections in a particular complex system to make the “best decision” possible. In the field of sustainable agriculture and climate change, higher degrees of ST are assumed to be associated with more successful adaptation strategies under changing conditions, and “better” environmental decision making in a number of environmental and cultural settings. Future climate change scenarios highlight the negative effects on agricultural productivity worldwide, particularly in low-income countries (LICs) situated in the Global South. Alongside this, current measures of ST are limited by their reliance on recall, and are prone to possible measurement errors. Using Climate-Smart Agriculture (CSA), as an example case study, in this article we explore: (i) ST from a social science perspective; (ii) cognitive neuroscience tools that could be used to explore ST abilities in the context of LICs; (iii) an exploration of the possible correlates of systems thinking: observational learning, prospective thinking/memory and the theory of planned behaviour and (iv) a proposed theory of change highlighting the integration of social science frameworks and a cognitive neuroscience perspective. We find, recent advancements in the field of cognitive neuroscience such as Near-Infrared Spectroscopy (NIRS) provide exciting potential to explore previously hidden forms of cognition, especially in a low-income country/field setting; improving our understanding of environmental decision-making and the ability to more accurately test more complex hypotheses where access to laboratory studies is severely limited. We highlight that ST may correlate with other key aspects involved in environmental decision-making and posit motivating farmers via specific brain networks would: (a) enhance understanding of CSA practices (e.g., via the frontoparietal network extending from the dorsolateral prefrontal cortex (DLPFC) to the parietal cortex (PC) a control hub involved in ST and observational learning) such as tailoring training towards developing improved ST abilities among farmers and involving observational learning more explicitly and (b) motivate farmers to use such practices [e.g., via the network between the DLPFC and nucleus accumbens (NAc)] which mediates reward processing and motivation by focussing on a reward/emotion to engage farmers. Finally, our proposed interdisciplinary theory of change can be used as a starting point to encourage discussion and guide future research in this space.
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title_short	Systems Thinking in an era of climate change: Does cognitive neuroscience hold the key to improving environmental decision making? A perspective on Climate-Smart Agriculture
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