Pub Date : 2024-03-21DOI: 10.3389/fclim.2024.1306542
O. Zimmerman, Tanya Eison, Robert G. Carey, Phillip S. Levin
Anthropogenic impacts have altered and degraded global ecosystems. Integrated resource management offers an important solution to enhance collaboration, holistic thinking, and equity by considering diverse perspectives in decision making. In Washington State, Floodplains by Design (FbD) is a floodplain management and habitat restoration program that emphasizes bringing together diverse stakeholders and supporting conversations between local, state, and Tribal governments while enhancing environmental justice in the region. Marginalized communities continue to be disproportionately impacted by environmental disturbances. Our project interviewed Tribal natural resource managers to assess the degree to which they felt FbD was supporting their community’s needs. Our research asked three questions: (1) What Tribal needs and inequities associated with floodplains are identified by Tribal natural resource managers? (2) Are these needs and inequities being addressed by FbD? and (3) How can FbD better address these needs and inequities moving forward? We found that while the integrated approach of FbD was driving solutions in some realms, there are ways in which the program could better support needs and address inequities in Tribal communities. Specifically, we found that conventional responses to environmental challenges are rooted in modernist paradigm6s that have created persistent dualities, including that of human-nature and human-nonhuman. Such a paradigm is in conflict with wellbeing and self-determination of Tribal cultures that are deeply connected to Pacific salmon. In closing, we provide insights on these mechanisms and offer solutions moving forward.
{"title":"Addressing inequities and meeting needs of Indigenous communities in floodplain management","authors":"O. Zimmerman, Tanya Eison, Robert G. Carey, Phillip S. Levin","doi":"10.3389/fclim.2024.1306542","DOIUrl":"https://doi.org/10.3389/fclim.2024.1306542","url":null,"abstract":"Anthropogenic impacts have altered and degraded global ecosystems. Integrated resource management offers an important solution to enhance collaboration, holistic thinking, and equity by considering diverse perspectives in decision making. In Washington State, Floodplains by Design (FbD) is a floodplain management and habitat restoration program that emphasizes bringing together diverse stakeholders and supporting conversations between local, state, and Tribal governments while enhancing environmental justice in the region. Marginalized communities continue to be disproportionately impacted by environmental disturbances. Our project interviewed Tribal natural resource managers to assess the degree to which they felt FbD was supporting their community’s needs. Our research asked three questions: (1) What Tribal needs and inequities associated with floodplains are identified by Tribal natural resource managers? (2) Are these needs and inequities being addressed by FbD? and (3) How can FbD better address these needs and inequities moving forward? We found that while the integrated approach of FbD was driving solutions in some realms, there are ways in which the program could better support needs and address inequities in Tribal communities. Specifically, we found that conventional responses to environmental challenges are rooted in modernist paradigm6s that have created persistent dualities, including that of human-nature and human-nonhuman. Such a paradigm is in conflict with wellbeing and self-determination of Tribal cultures that are deeply connected to Pacific salmon. In closing, we provide insights on these mechanisms and offer solutions moving forward.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140221414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-21DOI: 10.3389/fclim.2024.1338259
B. Z. Birhanu, Gizaw Desta, O. Cofie, S. Tilahun, T. Mabhaudhi
Land degradation is a significant environmental challenge across sub-Saharan Africa. In recent decades, efforts have been undertaken, with varying successes, to rehabilitate degraded rural landscapes. However, there needs to be more evidence on the outcomes regarding enhanced productivity, environmental management, and socio-economic benefits.This study uses a case study approach, using contrasting sites from Ethiopia and Mali to appraise restoration innovations implemented through various programs. Two distinct sites were chosen from each of the study cases, and an extensive literature search was conducted to document the evidence, focusing on the sustainability gains derived from integrated landscape management (ILM). For this, the sustainable intensification assessment framework (SIAF) was used, encompassing five domains, namely productivity, economic, environmental, social, and human condition, and featuring scales from plot to landscape, all facilitated by simplified yet robust indicators such as yield, soil loss, net income, land access, and food availability.Results highlighted a higher productivity gain (35% to 55%) and an improved socio-economic benefit (>20%). The ILM in the Ethiopian highlands enabled a significant improvement in wheat and barley yield (p < 0.01). Introducing new crop varieties integrated with the in-situ and ex-situ practices enabled diversifying crops across the landscape and significantly reduced runoff and soil loss (p < 0.05). By increasing the cultivable land by 44%, household income was increased by selling potatoes and agroforestry products. In Mali, ILM practices reduced soil loss to 4.97t/ha from 12.1t/ha. In addition to the improvements in the yield of sorghum and maize (33% and 63%, respectively), rehabilitating the once marginal and abandoned landscape in Mali enabled landless and female-headed households to work together, improving the social cohesion among the groups. The introduction of irrigation facilities enabled widowed women to increase household vegetable consumption by 55% and increase their income by 24%.The study showed positive evidence from ILM practices in the two contrasting landscapes. However, there is a need to address challenges related to the absence of timely data monitoring and documentation of successful practices. For this, the generation of evidence-based data and the use of advanced geo-spatial tools such as Remote Sensing and GPS-installed drones are recommended.
{"title":"Restoring degraded landscapes and sustaining livelihoods: sustainability assessment (cum-review) of integrated landscape management in sub-Saharan Africa","authors":"B. Z. Birhanu, Gizaw Desta, O. Cofie, S. Tilahun, T. Mabhaudhi","doi":"10.3389/fclim.2024.1338259","DOIUrl":"https://doi.org/10.3389/fclim.2024.1338259","url":null,"abstract":"Land degradation is a significant environmental challenge across sub-Saharan Africa. In recent decades, efforts have been undertaken, with varying successes, to rehabilitate degraded rural landscapes. However, there needs to be more evidence on the outcomes regarding enhanced productivity, environmental management, and socio-economic benefits.This study uses a case study approach, using contrasting sites from Ethiopia and Mali to appraise restoration innovations implemented through various programs. Two distinct sites were chosen from each of the study cases, and an extensive literature search was conducted to document the evidence, focusing on the sustainability gains derived from integrated landscape management (ILM). For this, the sustainable intensification assessment framework (SIAF) was used, encompassing five domains, namely productivity, economic, environmental, social, and human condition, and featuring scales from plot to landscape, all facilitated by simplified yet robust indicators such as yield, soil loss, net income, land access, and food availability.Results highlighted a higher productivity gain (35% to 55%) and an improved socio-economic benefit (>20%). The ILM in the Ethiopian highlands enabled a significant improvement in wheat and barley yield (p < 0.01). Introducing new crop varieties integrated with the in-situ and ex-situ practices enabled diversifying crops across the landscape and significantly reduced runoff and soil loss (p < 0.05). By increasing the cultivable land by 44%, household income was increased by selling potatoes and agroforestry products. In Mali, ILM practices reduced soil loss to 4.97t/ha from 12.1t/ha. In addition to the improvements in the yield of sorghum and maize (33% and 63%, respectively), rehabilitating the once marginal and abandoned landscape in Mali enabled landless and female-headed households to work together, improving the social cohesion among the groups. The introduction of irrigation facilities enabled widowed women to increase household vegetable consumption by 55% and increase their income by 24%.The study showed positive evidence from ILM practices in the two contrasting landscapes. However, there is a need to address challenges related to the absence of timely data monitoring and documentation of successful practices. For this, the generation of evidence-based data and the use of advanced geo-spatial tools such as Remote Sensing and GPS-installed drones are recommended.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140223030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-19DOI: 10.3389/fclim.2024.1347519
Luca Sergio Italo Parodi, Markus Enenkel, Niccolò Lombardi, Joshua Ngaina
Anticipatory action is an approach that combines early warning information with flexible, pre-positioned funds to trigger actions that mitigate the impact of predictable shocks on the most vulnerable people. Historically, drought is the climatic hazard that led to the highest and most severe humanitarian impacts in the Sahel. This region, according to climate projections, will be one of the most deeply affected by climate change in future years, leading to considerable changes to societies, economies, as well as impacting rural communities. While this negative projection may lead to further increases in humanitarian consequences, recent experiences from integrating anticipatory action for drought into humanitarian practice hold positive prospects. This article will review current experiences on anticipatory action for drought in the Sahel and shed light on whether this approach has brought innovation in local disaster risk management. Through the review of recent initiatives in Burkina Faso, Chad and Niger, this paper highlights key advancements as well as gaps and challenges pertaining to key components of anticipatory action and disaster risk management, namely: (1) data, risk analysis and early warning; (2) funding; (3) preparedness and community engagement; (4) learning, coordination and partnership; (5) policies and institutional frameworks. Even in challenging environments like in the Sahel, anticipatory action for drought can become an integral component of standard disaster risk management and financing strategies. However, this process will require more robust evidence about which ingredients of anticipatory action approaches lead to the desired result.
{"title":"Anticipatory action for drought in the Sahel: an innovation for drought risk management or a buzzword?","authors":"Luca Sergio Italo Parodi, Markus Enenkel, Niccolò Lombardi, Joshua Ngaina","doi":"10.3389/fclim.2024.1347519","DOIUrl":"https://doi.org/10.3389/fclim.2024.1347519","url":null,"abstract":"Anticipatory action is an approach that combines early warning information with flexible, pre-positioned funds to trigger actions that mitigate the impact of predictable shocks on the most vulnerable people. Historically, drought is the climatic hazard that led to the highest and most severe humanitarian impacts in the Sahel. This region, according to climate projections, will be one of the most deeply affected by climate change in future years, leading to considerable changes to societies, economies, as well as impacting rural communities. While this negative projection may lead to further increases in humanitarian consequences, recent experiences from integrating anticipatory action for drought into humanitarian practice hold positive prospects. This article will review current experiences on anticipatory action for drought in the Sahel and shed light on whether this approach has brought innovation in local disaster risk management. Through the review of recent initiatives in Burkina Faso, Chad and Niger, this paper highlights key advancements as well as gaps and challenges pertaining to key components of anticipatory action and disaster risk management, namely: (1) data, risk analysis and early warning; (2) funding; (3) preparedness and community engagement; (4) learning, coordination and partnership; (5) policies and institutional frameworks. Even in challenging environments like in the Sahel, anticipatory action for drought can become an integral component of standard disaster risk management and financing strategies. However, this process will require more robust evidence about which ingredients of anticipatory action approaches lead to the desired result.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140229200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-15DOI: 10.3389/fclim.2024.1343072
Michael F. Wehner, Margaret L. Duffy, M. Risser, C. J. Paciorek, Dáithí A. Stone, P. Pall
Methods for calculating return values of extreme precipitation and their uncertainty are compared using daily precipitation rates over the Western U.S. and Southwestern Canada from a large ensemble of climate model simulations. The roles of return-value estimation procedures and sample size in uncertainty are evaluated for various return periods. We compare two different generalized extreme value (GEV) parameter estimation techniques, namely L-moments and maximum likelihood (MLE), as well as empirical techniques. Even for very large datasets, confidence intervals calculated using GEV techniques are narrower than those calculated using empirical methods. Furthermore, the more efficient L-moments parameter estimation techniques result in narrower confidence intervals than MLE parameter estimation techniques at small sample sizes, but similar best estimates. It should be noted that we do not claim that either parameter fitting technique is better calibrated than the other to estimate long period return values. While a non-stationary MLE methodology is readily available to estimate GEV parameters, it is not for the L-moments method. Comparison of uncertainty quantification methods are found to yield significantly different estimates for small sample sizes but converge to similar results as sample size increases. Finally, practical recommendations about the length and size of climate model ensemble simulations and the choice of statistical methods to robustly estimate long period return values of extreme daily precipitation statistics and quantify their uncertainty.
{"title":"On the uncertainty of long-period return values of extreme daily precipitation","authors":"Michael F. Wehner, Margaret L. Duffy, M. Risser, C. J. Paciorek, Dáithí A. Stone, P. Pall","doi":"10.3389/fclim.2024.1343072","DOIUrl":"https://doi.org/10.3389/fclim.2024.1343072","url":null,"abstract":"Methods for calculating return values of extreme precipitation and their uncertainty are compared using daily precipitation rates over the Western U.S. and Southwestern Canada from a large ensemble of climate model simulations. The roles of return-value estimation procedures and sample size in uncertainty are evaluated for various return periods. We compare two different generalized extreme value (GEV) parameter estimation techniques, namely L-moments and maximum likelihood (MLE), as well as empirical techniques. Even for very large datasets, confidence intervals calculated using GEV techniques are narrower than those calculated using empirical methods. Furthermore, the more efficient L-moments parameter estimation techniques result in narrower confidence intervals than MLE parameter estimation techniques at small sample sizes, but similar best estimates. It should be noted that we do not claim that either parameter fitting technique is better calibrated than the other to estimate long period return values. While a non-stationary MLE methodology is readily available to estimate GEV parameters, it is not for the L-moments method. Comparison of uncertainty quantification methods are found to yield significantly different estimates for small sample sizes but converge to similar results as sample size increases. Finally, practical recommendations about the length and size of climate model ensemble simulations and the choice of statistical methods to robustly estimate long period return values of extreme daily precipitation statistics and quantify their uncertainty.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.3389/fclim.2024.1287386
Tomohiro Kinoshita, Taira Ozaki
The objectives of this study are twofold. The first is to identify potential green infrastructure construction sites by building rooftops and sidewalks. The second is to analyze internal flooding for a wide range of drainage areas and to quantitatively evaluate the effectiveness of stormwater runoff control.The target area has approximately 600 ha with a runoff coefficient of 0.71. Using Arc GIS Desktop 10.8.1, this study has identified green roofs and bioswales that would be highly beneficial in capturing large amounts of rainfall. In addition, Info Works ICM was used for the inundation analysis, which can simultaneously calculate the flow in sewer pipelines and above-ground inundation flow. Runoff coefficients were calculated for each land use using the urban land use subdivision mesh data with 100 m unit. This study targeted a 10-year probability rainfall (total rainfall: 86.3 mm, maximum hourly rainfall: 52.3 mm/h, duration: 3 h) with a middle concentrated rainfall waveform obtained from past experiments in the d4PDF database of ensemble climate prediction contributing to global warming.The amount of land availability for green roofs and bioswales was about 1 and 0.1% of the drainage area, respectively. The runoff coefficients for green roofs only, bioswales only, with and without introduction of both green roofs and bioswales were 70.34, 70.87, 70.28, and 70.93%, respectively. The difference in runoff coefficients was about 0.65 percentage points even when both were constructed. As a result of inundation analysis, the reduction was 2.5% for the maximum waterlogged area, 1.5% for the flooded area, and 0.7% for the average depth of waterlogging divided by the maximum waterlogged area. The construction of green roofs and bioswales in the same area or downstream of the area shows little mitigation effect when flooding occurs in an area near the downstream end of the sewer network.Although this study has mainly discussed the stormwater runoff control aspect, the most important feature of green infrastructure is its multifunctionality. In terms of utilizing and promoting green infrastructure, it is important to visualize its multifaceted effects and share them with many stakeholders.
{"title":"Estimation of possible locations for green roofs and bioswales and analysis of the effect of their implementation on stormwater runoff control","authors":"Tomohiro Kinoshita, Taira Ozaki","doi":"10.3389/fclim.2024.1287386","DOIUrl":"https://doi.org/10.3389/fclim.2024.1287386","url":null,"abstract":"The objectives of this study are twofold. The first is to identify potential green infrastructure construction sites by building rooftops and sidewalks. The second is to analyze internal flooding for a wide range of drainage areas and to quantitatively evaluate the effectiveness of stormwater runoff control.The target area has approximately 600 ha with a runoff coefficient of 0.71. Using Arc GIS Desktop 10.8.1, this study has identified green roofs and bioswales that would be highly beneficial in capturing large amounts of rainfall. In addition, Info Works ICM was used for the inundation analysis, which can simultaneously calculate the flow in sewer pipelines and above-ground inundation flow. Runoff coefficients were calculated for each land use using the urban land use subdivision mesh data with 100 m unit. This study targeted a 10-year probability rainfall (total rainfall: 86.3 mm, maximum hourly rainfall: 52.3 mm/h, duration: 3 h) with a middle concentrated rainfall waveform obtained from past experiments in the d4PDF database of ensemble climate prediction contributing to global warming.The amount of land availability for green roofs and bioswales was about 1 and 0.1% of the drainage area, respectively. The runoff coefficients for green roofs only, bioswales only, with and without introduction of both green roofs and bioswales were 70.34, 70.87, 70.28, and 70.93%, respectively. The difference in runoff coefficients was about 0.65 percentage points even when both were constructed. As a result of inundation analysis, the reduction was 2.5% for the maximum waterlogged area, 1.5% for the flooded area, and 0.7% for the average depth of waterlogging divided by the maximum waterlogged area. The construction of green roofs and bioswales in the same area or downstream of the area shows little mitigation effect when flooding occurs in an area near the downstream end of the sewer network.Although this study has mainly discussed the stormwater runoff control aspect, the most important feature of green infrastructure is its multifunctionality. In terms of utilizing and promoting green infrastructure, it is important to visualize its multifaceted effects and share them with many stakeholders.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140244366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.3389/fclim.2024.1290999
H. Hilser, L. Hiraldo, C. Moreau, A. Draiby, E. Cox, M. G. Andrews, L. Winks, N. Walworth
Despite an increase in literature on public perceptions of carbon dioxide removal (CDR), there remains a paucity of evidence describing the social and developmental processes involved in the implementation of projects in-situ. This research illustrates a case study documenting a planned research project for coastal enhanced weathering—a form of ocean alkalinity enhancement—in a remote, rural area of the Northwestern Dominican Republic, a Small Island Developing State particularly at risk from climate change impacts. This paper is a collaboration between the company responsible for the project (Vesta) and researchers located in the Dominican Republic and the United Kingdom, We draw upon 2 years' worth of surveys, interviews, focus groups, group information sessions, and reflexive documentation by the Dominican Republic researchers, to present a first-hand account of local community responses to the planned research project and to coastal enhanced weathering and climate change more broadly. We discuss themes of climate vulnerability, justice, and adaptive capacity through the lens of the collaborative governance and social diffusion principles that the project was designed with. We also reflect on a program of outreach and participatory activities which was established to support community development in the areas surrounding the field trial site, as informed by exploration of community needs drawn from the research.
{"title":"Public engagement and collaboration for carbon dioxide removal: lessons from a project in the Dominican Republic","authors":"H. Hilser, L. Hiraldo, C. Moreau, A. Draiby, E. Cox, M. G. Andrews, L. Winks, N. Walworth","doi":"10.3389/fclim.2024.1290999","DOIUrl":"https://doi.org/10.3389/fclim.2024.1290999","url":null,"abstract":"Despite an increase in literature on public perceptions of carbon dioxide removal (CDR), there remains a paucity of evidence describing the social and developmental processes involved in the implementation of projects in-situ. This research illustrates a case study documenting a planned research project for coastal enhanced weathering—a form of ocean alkalinity enhancement—in a remote, rural area of the Northwestern Dominican Republic, a Small Island Developing State particularly at risk from climate change impacts. This paper is a collaboration between the company responsible for the project (Vesta) and researchers located in the Dominican Republic and the United Kingdom, We draw upon 2 years' worth of surveys, interviews, focus groups, group information sessions, and reflexive documentation by the Dominican Republic researchers, to present a first-hand account of local community responses to the planned research project and to coastal enhanced weathering and climate change more broadly. We discuss themes of climate vulnerability, justice, and adaptive capacity through the lens of the collaborative governance and social diffusion principles that the project was designed with. We also reflect on a program of outreach and participatory activities which was established to support community development in the areas surrounding the field trial site, as informed by exploration of community needs drawn from the research.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140392142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.3389/fclim.2024.1344899
Vanessa C. Ho, Anne H. Berman, Jackie Andrade, David J. Kavanagh, S. L. Branche, Jon May, Conner S. Philson, Daniel T. Blumstein
The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions—the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions—the emotions an individual actually experiences during decision-making—have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.
{"title":"Assessing immediate emotions in the theory of planned behavior can substantially contribute to increases in pro-environmental behavior","authors":"Vanessa C. Ho, Anne H. Berman, Jackie Andrade, David J. Kavanagh, S. L. Branche, Jon May, Conner S. Philson, Daniel T. Blumstein","doi":"10.3389/fclim.2024.1344899","DOIUrl":"https://doi.org/10.3389/fclim.2024.1344899","url":null,"abstract":"The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions—the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions—the emotions an individual actually experiences during decision-making—have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.3389/fclim.2024.1339587
Ruth R. Chinomona, O. Kupika, E. Gandiwa, N. Muboko
Climatic change related extreme events such as droughts negatively affect local communities in the semi-arid savanna ecosystems. This study mainly records and analyses local knowledge on the use of edible indigenous woody plant species by local communities during drought periods, as a coping strategy, in southeast lowveld of Zimbabwe. Secondary data on utilization of edible indigenous woody plants were gathered from literature sources focusing mainly on the southeast lowveld parts of Zimbabwe and covering the period 2000–2019. Quantitative ethnobotanical data analysis involved computing the frequency of citation (FC), relative frequency of citation (RFC) and family importance value (FIV) to determine the local significance of indigenous woody plant species. A total of 23 species from 12 families were recorded as being used during drought periods with key species including baobab (Adansonia digitata), bird plum (Tamarindus indica), corky-monkey orange (Strychnos cocculoides) and black monkey orange (Strychnos madagascariensis). Major use categories were food, medicine, and livestock feed. The study findings points to the need for embracing indigenous woody plants as a buffer against drought in semi-arid parts of the savanna. Future projects should focus on developing innovative strategies such as value addition and promoting sustainable use and restoration of non-wood forest products as part of livelihood diversification under drought situations.
{"title":"Contribution of edible indigenous woody plants as a coping strategy during drought periods in the southeast lowveld of Zimbabwe: a review","authors":"Ruth R. Chinomona, O. Kupika, E. Gandiwa, N. Muboko","doi":"10.3389/fclim.2024.1339587","DOIUrl":"https://doi.org/10.3389/fclim.2024.1339587","url":null,"abstract":"Climatic change related extreme events such as droughts negatively affect local communities in the semi-arid savanna ecosystems. This study mainly records and analyses local knowledge on the use of edible indigenous woody plant species by local communities during drought periods, as a coping strategy, in southeast lowveld of Zimbabwe. Secondary data on utilization of edible indigenous woody plants were gathered from literature sources focusing mainly on the southeast lowveld parts of Zimbabwe and covering the period 2000–2019. Quantitative ethnobotanical data analysis involved computing the frequency of citation (FC), relative frequency of citation (RFC) and family importance value (FIV) to determine the local significance of indigenous woody plant species. A total of 23 species from 12 families were recorded as being used during drought periods with key species including baobab (Adansonia digitata), bird plum (Tamarindus indica), corky-monkey orange (Strychnos cocculoides) and black monkey orange (Strychnos madagascariensis). Major use categories were food, medicine, and livestock feed. The study findings points to the need for embracing indigenous woody plants as a buffer against drought in semi-arid parts of the savanna. Future projects should focus on developing innovative strategies such as value addition and promoting sustainable use and restoration of non-wood forest products as part of livelihood diversification under drought situations.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.3389/fclim.2024.1289332
Jahangir Ali, Linyin Cheng
Accurate weather forecasts are critical for saving lives, emergency services, and future developments. Climate models such as numerical weather prediction models have made significant advancements in weather forecasts, but these models are computationally expensive and can be subject to inaccurate representations of complex natural interconnections. Alternatively, data-driven machine learning methods have provided new dimensions in assisting weather forecasts. In this study, we used convolutional neural networks (CNN) to assess how geopotential height at different levels of the troposphere may affect the predictability of extreme surface temperature (t2m) via two cases. Specifically, we analyzed temperature forecasts over the continental United States at lead times from 1 day to 30 days by incorporating z100, z200, z500, z700, and z925 hPa levels as inputs to the CNN. In the first case, we applied the framework to predict summer temperatures of 2012, which contributed to one of the extreme heatwave events in the U.S. history. The results show that z500 leads to t2m forecasts with relatively less root mean squared errors (RMSE) than other geopotential heights at most of the lead time under consideration, while the inclusion of more atmospheric pressure levels improves t2m forecasts to a limited extent. At the same lead time, we also predicted the z500 patterns with different levels of geopotential height and temperature as the inputs. We found that the combination of z500, t2m, and t850 (temperature at 850 hPa) is associated with less RMSE for the z500 forecasts compared to other inputs. In contrast to the 2012 summer, our second case examined the wintertime temperature of 2014 when the upper Midwest and Great Lakes regions experienced the coldest winter on record. We found that z200 contributes to better t2m predictions for up to 7-days lead times whereas z925 gives better results for z500 forecasts during this cold event. Collectively, the results suggest that for long-range temperature forecasts based on the CNN, including various levels of geopotential heights could be beneficial.
{"title":"Temperature forecasts for the continental United States: a deep learning approach using multidimensional features","authors":"Jahangir Ali, Linyin Cheng","doi":"10.3389/fclim.2024.1289332","DOIUrl":"https://doi.org/10.3389/fclim.2024.1289332","url":null,"abstract":"Accurate weather forecasts are critical for saving lives, emergency services, and future developments. Climate models such as numerical weather prediction models have made significant advancements in weather forecasts, but these models are computationally expensive and can be subject to inaccurate representations of complex natural interconnections. Alternatively, data-driven machine learning methods have provided new dimensions in assisting weather forecasts. In this study, we used convolutional neural networks (CNN) to assess how geopotential height at different levels of the troposphere may affect the predictability of extreme surface temperature (t2m) via two cases. Specifically, we analyzed temperature forecasts over the continental United States at lead times from 1 day to 30 days by incorporating z100, z200, z500, z700, and z925 hPa levels as inputs to the CNN. In the first case, we applied the framework to predict summer temperatures of 2012, which contributed to one of the extreme heatwave events in the U.S. history. The results show that z500 leads to t2m forecasts with relatively less root mean squared errors (RMSE) than other geopotential heights at most of the lead time under consideration, while the inclusion of more atmospheric pressure levels improves t2m forecasts to a limited extent. At the same lead time, we also predicted the z500 patterns with different levels of geopotential height and temperature as the inputs. We found that the combination of z500, t2m, and t850 (temperature at 850 hPa) is associated with less RMSE for the z500 forecasts compared to other inputs. In contrast to the 2012 summer, our second case examined the wintertime temperature of 2014 when the upper Midwest and Great Lakes regions experienced the coldest winter on record. We found that z200 contributes to better t2m predictions for up to 7-days lead times whereas z925 gives better results for z500 forecasts during this cold event. Collectively, the results suggest that for long-range temperature forecasts based on the CNN, including various levels of geopotential heights could be beneficial.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-13DOI: 10.3389/fclim.2024.1343993
Tobias Geiger, T. Röösli, D. Bresch, Bodo Erhardt, Andreas M. Fischer, Dominik Imgrüth, Stefan Kienberger, Laura Mainetti, Gudrun Mühlbacher, Raphael Spiekermann
Climate change will result in more intense and more frequent weather and climate events that will continue to cause fatalities, economic damages and other adverse societal impacts worldwide. To mitigate these consequences and to support better informed decisions and improved actions and responses, many National Meteorological and Hydrological Services (NMHSs) are discussing how to provide services on weather and climate impacts as part of their operational routines. The authors outline how a risk framework can support the development of these services by NMHSs. In addition to the hazard information, a risk perspective considers the propensity for a given hazard to inflict adverse consequences on society and environment, and attempts to quantify the uncertainties involved. The relevant strategic, methodological and technical steps are summarized and recommendations for the development of impact-related services are provided. Specifically, we propose that NMHSs adopt an integrated risk framework that incorporates a hazard-exposure-vulnerability model into operational services. Such a framework integrates all existing forecast and impact services, including the underlying impact models, and allows for flexible future extensions driven by the evolving collaboration with partners, stakeholders and users. Thereby, this paper attempts to unify existing work streams on impact-related services from different spatial and temporal scales (weather, climate) and disciplines (hydrology, meteorology, economics, social sciences) and to propose a harmonized approach that can create synergies within and across NMHSs to further develop and enhance risk-based services.
{"title":"How to provide actionable information on weather and climate impacts?–A summary of strategic, methodological, and technical perspectives","authors":"Tobias Geiger, T. Röösli, D. Bresch, Bodo Erhardt, Andreas M. Fischer, Dominik Imgrüth, Stefan Kienberger, Laura Mainetti, Gudrun Mühlbacher, Raphael Spiekermann","doi":"10.3389/fclim.2024.1343993","DOIUrl":"https://doi.org/10.3389/fclim.2024.1343993","url":null,"abstract":"Climate change will result in more intense and more frequent weather and climate events that will continue to cause fatalities, economic damages and other adverse societal impacts worldwide. To mitigate these consequences and to support better informed decisions and improved actions and responses, many National Meteorological and Hydrological Services (NMHSs) are discussing how to provide services on weather and climate impacts as part of their operational routines. The authors outline how a risk framework can support the development of these services by NMHSs. In addition to the hazard information, a risk perspective considers the propensity for a given hazard to inflict adverse consequences on society and environment, and attempts to quantify the uncertainties involved. The relevant strategic, methodological and technical steps are summarized and recommendations for the development of impact-related services are provided. Specifically, we propose that NMHSs adopt an integrated risk framework that incorporates a hazard-exposure-vulnerability model into operational services. Such a framework integrates all existing forecast and impact services, including the underlying impact models, and allows for flexible future extensions driven by the evolving collaboration with partners, stakeholders and users. Thereby, this paper attempts to unify existing work streams on impact-related services from different spatial and temporal scales (weather, climate) and disciplines (hydrology, meteorology, economics, social sciences) and to propose a harmonized approach that can create synergies within and across NMHSs to further develop and enhance risk-based services.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140245106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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