Researchers are making use of new gene-editing techniques in medicine, bioenergy, industrial biot... more Researchers are making use of new gene-editing techniques in medicine, bioenergy, industrial biotechnology, and beyond, and the field of crop breeding is no exception. These techniques, which differ from genetic modification techniques, spell difficult questions for regulatory oversight: will current rules-of-play apply, or do new techniques necessitate fundamental shifts in regulations? Thus far, little explicit attention has focused on the fundamental yet elusive questions of which technical specifics currently trigger regulation of gene-edited crops, and where different jurisdictions ‘draw’ this line. Here, we trace these regulatory lines across key jurisdictions. We argue that extant regulatory definitions are crumbling in the face of emerging technologies and assert that this breakdown poses a threat to responsible governance. Drawing upon insights from responsible research and innovation, we propose a shift away from technically based regulatory approaches and toward more risk-targeted oversight based on broader societal and ecological implications.
Abstract Commercial agriculture is central to problems of sustainability in food, water, energy a... more Abstract Commercial agriculture is central to problems of sustainability in food, water, energy and climate change. Appropriate solutions will depend on the effective promotion, monitoring and evaluation of changes in farming practice. Conservation agriculture (CA) is an important example of sustainable intensification and climate-smart agriculture, increasing the productivity and reliability of grain production while reducing agricultural inputs and future climate risks when adopted comprehensively. But to understand its implementation and benefits, researchers often rely on simplified measures of CA adoption (e.g., single proxies, binary measures, broad self-assessments, expert estimates). Here we use a national survey of South Africa’s commercial grain farmers (n = 441), contextualized by previous interviews, to investigate common measures of adoption and their implications for CA’s promotion, monitoring and evaluation. These farmers are unusually informative, because they are unsubsidized but have the capacity, incentive and willingness to adapt to climate change. We find that they are adopting CA autonomously, but that their implementation is highly variable and their interpretation of farming practice differs from that of local experts. Single proxies, binary adoption variables and broad farmer self-assessments suggest that between 40 and 80% of farmers have adopted CA. However, when evaluated across the three CA principles using UN-defined adoption thresholds, the comprehensive adoption rate is only 14%. Farmers’ definition of “conservation” differs substantially from that of the local experts most likely to be asked to contribute adoption estimates to global monitoring efforts, creating the potential for miscommunication. There is therefore substantial cause for concern in how CA is currently promoted, monitored and evaluated. Inaccurate adoption estimates jeopardize CA’s potential as a climate change adaptation strategy, creating illusory progress that may disincentivize further substantive efforts towards agricultural sustainability and climate resilience.
Ordinary least squares linear regression (LR) has long been a popular choice among researchers in... more Ordinary least squares linear regression (LR) has long been a popular choice among researchers interested in using historical data for estimating crop yield response to climate change. Today, the rapidly growing field of machine learning (ML) offers a wide range of advanced statistical tools that are increasingly being used for more accurate estimates of this relationship. This study compares LR to a popular ML technique called boosted regression trees (BRTs). We find that BRTs provide a significantly better prediction accuracy compared to various LR specifications, including those fitting quadratic and piece-wise linear functions. BRTs are also able to identify break points where the relationship between climate and yield undergoes significant shifts (for example, increasing yields with precipitation followed by a plateauing of the relationship beyond a certain point). Tests we performed with synthetically simulated climate and crop yield data showed that BRTs can automatically account for not only spatial variation in climate–yield relationships, but also interactions between different variables that affect crop yields. We then used both statistical techniques to estimate the influence of historical climate change on rice, wheat, and pearl millet in India. BRTs predicted a considerably smaller negative impact compared to LR. This may be an artifact of BRTs conflating time and climate variables, signaling a potential weakness of models with excessively flexible functional forms for inferring climate impacts on agriculture. Our findings thus suggest caution while interpreting the results from single-model analyses, especially in regions with highly varied climate and agricultural practices.
Climate services are intended to improve climate-sensitive decisions by making climate informatio... more Climate services are intended to improve climate-sensitive decisions by making climate information ‘useful, useable and used’. Here, we analyse 27 expert interviews to evaluate whether this user-driven model of climate science has been successfully implemented in the public sector. We show that, although climate services promise better decision-making, they mainly focus on delivering better data. The norms and institutions of climate science produce three key tensions in operationalizing climate services: a focus on products rather than processes, services based on broad assumptions about demand rather than being demand-driven, and the narrow economic valuation of products rather than evaluation of improvements in decision-making. These tensions help explain why climate services often generate nominal changes in climate science where transformations are promised. Transformational change requires that climate services account for diverse social structures, behaviours and contexts. Integrating social science is no panacea for demand-driven climate services, but it is certainly a prerequisite. Climate services aim to make climate data and information accessible for climate-sensitive decision-making. However, the grounding of climate services in the norms and institutions of climate science creates tensions that reduce the impact of climate services.
As human–wildlife conflicts escalate worldwide, concepts such as tolerance and acceptance of wild... more As human–wildlife conflicts escalate worldwide, concepts such as tolerance and acceptance of wildlife are becoming increasingly important. Yet, contemporary conservation studies indicate a limited understanding of positive human–wildlife interactions, leading to potentially inaccurate representations of human–animal encounters. Failure to address these limitations contributes to the design and implementation of poor wildlife and landscape management plans and the dismissal of Indigenous ecological knowledge. We examined Indigenous perspectives on human–wildlife coexistence in India by drawing ethnographic evidence from Kattunayakans, a forest‐dwelling Adivasi community living in the Wayanad Wildlife Sanctuary in Kerala. Through qualitative field study that involved interviews and transect walks inside the forests, we found that Kattunayakans displayed tolerance and acceptance of wild animals characterized as forms of deep coexistence that involves three central ideas: wild animals a...
Researchers are making use of new gene-editing techniques in medicine, bioenergy, industrial biot... more Researchers are making use of new gene-editing techniques in medicine, bioenergy, industrial biotechnology, and beyond, and the field of crop breeding is no exception. These techniques, which differ from genetic modification techniques, spell difficult questions for regulatory oversight: will current rules-of-play apply, or do new techniques necessitate fundamental shifts in regulations? Thus far, little explicit attention has focused on the fundamental yet elusive questions of which technical specifics currently trigger regulation of gene-edited crops, and where different jurisdictions ‘draw’ this line. Here, we trace these regulatory lines across key jurisdictions. We argue that extant regulatory definitions are crumbling in the face of emerging technologies and assert that this breakdown poses a threat to responsible governance. Drawing upon insights from responsible research and innovation, we propose a shift away from technically based regulatory approaches and toward more risk-targeted oversight based on broader societal and ecological implications.
Abstract Commercial agriculture is central to problems of sustainability in food, water, energy a... more Abstract Commercial agriculture is central to problems of sustainability in food, water, energy and climate change. Appropriate solutions will depend on the effective promotion, monitoring and evaluation of changes in farming practice. Conservation agriculture (CA) is an important example of sustainable intensification and climate-smart agriculture, increasing the productivity and reliability of grain production while reducing agricultural inputs and future climate risks when adopted comprehensively. But to understand its implementation and benefits, researchers often rely on simplified measures of CA adoption (e.g., single proxies, binary measures, broad self-assessments, expert estimates). Here we use a national survey of South Africa’s commercial grain farmers (n = 441), contextualized by previous interviews, to investigate common measures of adoption and their implications for CA’s promotion, monitoring and evaluation. These farmers are unusually informative, because they are unsubsidized but have the capacity, incentive and willingness to adapt to climate change. We find that they are adopting CA autonomously, but that their implementation is highly variable and their interpretation of farming practice differs from that of local experts. Single proxies, binary adoption variables and broad farmer self-assessments suggest that between 40 and 80% of farmers have adopted CA. However, when evaluated across the three CA principles using UN-defined adoption thresholds, the comprehensive adoption rate is only 14%. Farmers’ definition of “conservation” differs substantially from that of the local experts most likely to be asked to contribute adoption estimates to global monitoring efforts, creating the potential for miscommunication. There is therefore substantial cause for concern in how CA is currently promoted, monitored and evaluated. Inaccurate adoption estimates jeopardize CA’s potential as a climate change adaptation strategy, creating illusory progress that may disincentivize further substantive efforts towards agricultural sustainability and climate resilience.
Ordinary least squares linear regression (LR) has long been a popular choice among researchers in... more Ordinary least squares linear regression (LR) has long been a popular choice among researchers interested in using historical data for estimating crop yield response to climate change. Today, the rapidly growing field of machine learning (ML) offers a wide range of advanced statistical tools that are increasingly being used for more accurate estimates of this relationship. This study compares LR to a popular ML technique called boosted regression trees (BRTs). We find that BRTs provide a significantly better prediction accuracy compared to various LR specifications, including those fitting quadratic and piece-wise linear functions. BRTs are also able to identify break points where the relationship between climate and yield undergoes significant shifts (for example, increasing yields with precipitation followed by a plateauing of the relationship beyond a certain point). Tests we performed with synthetically simulated climate and crop yield data showed that BRTs can automatically account for not only spatial variation in climate–yield relationships, but also interactions between different variables that affect crop yields. We then used both statistical techniques to estimate the influence of historical climate change on rice, wheat, and pearl millet in India. BRTs predicted a considerably smaller negative impact compared to LR. This may be an artifact of BRTs conflating time and climate variables, signaling a potential weakness of models with excessively flexible functional forms for inferring climate impacts on agriculture. Our findings thus suggest caution while interpreting the results from single-model analyses, especially in regions with highly varied climate and agricultural practices.
Climate services are intended to improve climate-sensitive decisions by making climate informatio... more Climate services are intended to improve climate-sensitive decisions by making climate information ‘useful, useable and used’. Here, we analyse 27 expert interviews to evaluate whether this user-driven model of climate science has been successfully implemented in the public sector. We show that, although climate services promise better decision-making, they mainly focus on delivering better data. The norms and institutions of climate science produce three key tensions in operationalizing climate services: a focus on products rather than processes, services based on broad assumptions about demand rather than being demand-driven, and the narrow economic valuation of products rather than evaluation of improvements in decision-making. These tensions help explain why climate services often generate nominal changes in climate science where transformations are promised. Transformational change requires that climate services account for diverse social structures, behaviours and contexts. Integrating social science is no panacea for demand-driven climate services, but it is certainly a prerequisite. Climate services aim to make climate data and information accessible for climate-sensitive decision-making. However, the grounding of climate services in the norms and institutions of climate science creates tensions that reduce the impact of climate services.
As human–wildlife conflicts escalate worldwide, concepts such as tolerance and acceptance of wild... more As human–wildlife conflicts escalate worldwide, concepts such as tolerance and acceptance of wildlife are becoming increasingly important. Yet, contemporary conservation studies indicate a limited understanding of positive human–wildlife interactions, leading to potentially inaccurate representations of human–animal encounters. Failure to address these limitations contributes to the design and implementation of poor wildlife and landscape management plans and the dismissal of Indigenous ecological knowledge. We examined Indigenous perspectives on human–wildlife coexistence in India by drawing ethnographic evidence from Kattunayakans, a forest‐dwelling Adivasi community living in the Wayanad Wildlife Sanctuary in Kerala. Through qualitative field study that involved interviews and transect walks inside the forests, we found that Kattunayakans displayed tolerance and acceptance of wild animals characterized as forms of deep coexistence that involves three central ideas: wild animals a...
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