Pub Date : 2024-03-04DOI: 10.1371/journal.pclm.0000366
M. Pathak, Shaurya Patel, Shreya Some
{"title":"Climate change mitigation and Sustainable Development Goals: Evidence and research gaps","authors":"M. Pathak, Shaurya Patel, Shreya Some","doi":"10.1371/journal.pclm.0000366","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000366","url":null,"abstract":"","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140266924","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 : 2024-03-01DOI: 10.1371/journal.pclm.0000377
Max Troell, Catriona Hurd, Thierry Chopin, Barry A. Costa-Pierce, M. J. Costello
{"title":"Seaweeds for carbon dioxide removal (CDR)–Getting the science right","authors":"Max Troell, Catriona Hurd, Thierry Chopin, Barry A. Costa-Pierce, M. J. Costello","doi":"10.1371/journal.pclm.0000377","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000377","url":null,"abstract":"","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"108 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140088612","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 : 2024-02-01DOI: 10.1371/journal.pclm.0000359
Madeleine Lewis, Emily L. M. Broadwell
{"title":"Mental health in polar scientists: Navigating the emotional landscape of climate change","authors":"Madeleine Lewis, Emily L. M. Broadwell","doi":"10.1371/journal.pclm.0000359","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000359","url":null,"abstract":"","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"12 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139684289","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 : 2023-12-29DOI: 10.1371/journal.pclm.0000326
A. Lynch, Andrew DiSanto, J. Olden, Cindy Chu, C. Paukert, Daria Gundermann, Mitchel Lang, Ray Zhang, Trevor J. Krabbenhoft
Climate change remains a primary threat to inland fishes and fisheries. Using topic modeling to examine trends and relationships across 36 years of scientific literature on documented and projected climate impacts to inland fish, we identify ten representative topics within this body of literature: assemblages, climate scenarios, distribution, climate drivers, population growth, invasive species, populations, phenology, physiology, and reproduction. These topics are largely similar to the output from artificial intelligence application (i.e., ChatGPT) search prompts, but with some key differences. The field of climate impacts on fish has seen dramatic growth since the mid-2000s with increasing popularity of topics related to drivers, assemblages, and phenology. The topics were generally well-dispersed with little overlap of common words, apart from phenology and reproduction which were closely clustered. Pairwise comparisons between topics revealed potential gaps in the literature including between reproduction and distribution and between physiology and phenology. A better understanding of these relationships can help capitalize on existing literature to inform conservation and sustainable management of inland fishes with a changing climate.
{"title":"Climate impacts to inland fishes: Shifting research topics over time","authors":"A. Lynch, Andrew DiSanto, J. Olden, Cindy Chu, C. Paukert, Daria Gundermann, Mitchel Lang, Ray Zhang, Trevor J. Krabbenhoft","doi":"10.1371/journal.pclm.0000326","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000326","url":null,"abstract":"Climate change remains a primary threat to inland fishes and fisheries. Using topic modeling to examine trends and relationships across 36 years of scientific literature on documented and projected climate impacts to inland fish, we identify ten representative topics within this body of literature: assemblages, climate scenarios, distribution, climate drivers, population growth, invasive species, populations, phenology, physiology, and reproduction. These topics are largely similar to the output from artificial intelligence application (i.e., ChatGPT) search prompts, but with some key differences. The field of climate impacts on fish has seen dramatic growth since the mid-2000s with increasing popularity of topics related to drivers, assemblages, and phenology. The topics were generally well-dispersed with little overlap of common words, apart from phenology and reproduction which were closely clustered. Pairwise comparisons between topics revealed potential gaps in the literature including between reproduction and distribution and between physiology and phenology. A better understanding of these relationships can help capitalize on existing literature to inform conservation and sustainable management of inland fishes with a changing climate.","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"65 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139146753","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 : 2023-11-30DOI: 10.1371/journal.pclm.0000303
D. A. Herrera, B. I. Cook, John Fasullo, K. Anchukaitis, Marc Alessi, Carlos J. Martinez, Colin P. Evans, Xiaolu Li, Kelsey N. Ellis, Rafael Mendez, T. Ault, A. Centella, Tannecia S. Stephenson, Michael A. Taylor
Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation (P–E) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.
{"title":"Observed changes in hydroclimate attributed to human forcing","authors":"D. A. Herrera, B. I. Cook, John Fasullo, K. Anchukaitis, Marc Alessi, Carlos J. Martinez, Colin P. Evans, Xiaolu Li, Kelsey N. Ellis, Rafael Mendez, T. Ault, A. Centella, Tannecia S. Stephenson, Michael A. Taylor","doi":"10.1371/journal.pclm.0000303","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000303","url":null,"abstract":"Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation (P–E) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"211 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139204768","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 : 2023-11-28DOI: 10.1371/journal.pclm.0000304
J. Shumake-Guillemot, Rosa von Borries, D. Campbell-Lendrum, Juli Trtanj, Jonathan Abrahams, Peter Berry, S. C. Bhan, Juan Castillo, Yolanda Clewlow, Sally Edwards, David Gikungu, Kenza Khomsi, Qi Yong Liu, R. Mahon, A. Matzarakis, Marcella Ohira, Judy Omumbo, Kyu Rang Kim, R. Ruuhela, Ben Ryder, Craig Sinclair, Madeleine Thomson, Coleen Vogel
{"title":"Good practices: Co-producing integrated climate, environment and health services","authors":"J. Shumake-Guillemot, Rosa von Borries, D. Campbell-Lendrum, Juli Trtanj, Jonathan Abrahams, Peter Berry, S. C. Bhan, Juan Castillo, Yolanda Clewlow, Sally Edwards, David Gikungu, Kenza Khomsi, Qi Yong Liu, R. Mahon, A. Matzarakis, Marcella Ohira, Judy Omumbo, Kyu Rang Kim, R. Ruuhela, Ben Ryder, Craig Sinclair, Madeleine Thomson, Coleen Vogel","doi":"10.1371/journal.pclm.0000304","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000304","url":null,"abstract":"","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139223122","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 : 2023-11-22DOI: 10.1371/journal.pclm.0000298
H. Moki, Keigo Yanagita, Keiichi Kondo, Tomohiro Kuwae
The global area and distribution of shallow water ecosystems (SWEs), and their projected responses to climate change, are fundamental for evaluating future changes in their ecosystem functions, including biodiversity and climate change mitigation and adaptation. Although previous studies have focused on a few SWEs, we modelled the global distribution of all major SWEs (seagrass meadows, macroalgal beds, tidal marshes, mangroves, and coral habitats) from current conditions (1986–2005) to 2100 under the representative concentration pathway (RCP) 2.6 and 8.5 emission scenarios. Our projections show that global coral habitat shrank by as much as 75% by 2100 with warmer ocean temperatures, but macroalgal beds, tidal marshes, and mangroves remained about the same because photosynthetic active radiation (PAR) depth did not vary greatly (macroalgal beds) and the shrinkage caused by sea-level rise was offset by other areas of expansion (tidal marshes and mangroves). Seagrass meadows were projected to increase by up to 11% by 2100 because of the increased PAR depth. If the landward shift of tidal marshes and mangroves relative to sea-level rise was restricted by assuming coastal development and land use, the SWEs shrank by 91.9% (tidal marshes) and 74.3% (mangroves) by 2100. Countermeasures may be necessary for coastal defense in the future; these include considering the best mix of SWEs and coastal hard infrastructure because the significant shrinkage in coral habitat could not decrease wave energy. However, if appropriate coastal management is achieved, the other four SWEs, which have relatively high CO2 absorption rates, can help mitigate the climate change influences.
{"title":"Projections of changes in the global distribution of shallow water ecosystems through 2100 due to climate change","authors":"H. Moki, Keigo Yanagita, Keiichi Kondo, Tomohiro Kuwae","doi":"10.1371/journal.pclm.0000298","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000298","url":null,"abstract":"The global area and distribution of shallow water ecosystems (SWEs), and their projected responses to climate change, are fundamental for evaluating future changes in their ecosystem functions, including biodiversity and climate change mitigation and adaptation. Although previous studies have focused on a few SWEs, we modelled the global distribution of all major SWEs (seagrass meadows, macroalgal beds, tidal marshes, mangroves, and coral habitats) from current conditions (1986–2005) to 2100 under the representative concentration pathway (RCP) 2.6 and 8.5 emission scenarios. Our projections show that global coral habitat shrank by as much as 75% by 2100 with warmer ocean temperatures, but macroalgal beds, tidal marshes, and mangroves remained about the same because photosynthetic active radiation (PAR) depth did not vary greatly (macroalgal beds) and the shrinkage caused by sea-level rise was offset by other areas of expansion (tidal marshes and mangroves). Seagrass meadows were projected to increase by up to 11% by 2100 because of the increased PAR depth. If the landward shift of tidal marshes and mangroves relative to sea-level rise was restricted by assuming coastal development and land use, the SWEs shrank by 91.9% (tidal marshes) and 74.3% (mangroves) by 2100. Countermeasures may be necessary for coastal defense in the future; these include considering the best mix of SWEs and coastal hard infrastructure because the significant shrinkage in coral habitat could not decrease wave energy. However, if appropriate coastal management is achieved, the other four SWEs, which have relatively high CO2 absorption rates, can help mitigate the climate change influences.","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139250294","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 : 2023-11-17DOI: 10.1371/journal.pclm.0000254
Michael Gerhard, Emma Jones-Phillipson, Xoliswa Ndeleni
This study examines the practice of gender mainstreaming in the context of climate finance mobilisation. It reveals how financial institutions are adopting shifts to organisational strategy, policy, and practice that advance the integration of key aspects of social sciences. This article specifically examines the role played by the Green Climate Fund’s Gender Policy in promoting a shift in the organisational strategies developed by development finance institutions and commercial banks in southern Africa. It reveals how practitioners are grappling with the evolving role of financial intermediaries in promoting a shift towards low-emissions, climate-resilient, and just development. The analysis uncovers foundational components, highlights key lessons, and identifies strategic approaches to institutionalising gender mainstreaming practices. Critically, the research reveals that whilst gender mainstreaming involves multiple practicalities, the financial institutions that have most extensively institutionalised gender mainstreaming practices have done so by recognising its normative basis and have perpetuated changes to organisational values and culture alongside more pedestrian policy amendments. One of the critical aspects of this culture shift is the recognition that transformative social impacts in climate finance are predicated on the design and implementation of projects that account for existing gender-based vulnerabilities whilst also identifying and maximising opportunities for all genders. The study builds on and contributes new knowledge to existing frameworks for understanding gender mainstreaming in relation to multilateral climate finance.
{"title":"Strategies for gender mainstreaming in climate finance mobilisation in southern Africa","authors":"Michael Gerhard, Emma Jones-Phillipson, Xoliswa Ndeleni","doi":"10.1371/journal.pclm.0000254","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000254","url":null,"abstract":"This study examines the practice of gender mainstreaming in the context of climate finance mobilisation. It reveals how financial institutions are adopting shifts to organisational strategy, policy, and practice that advance the integration of key aspects of social sciences. This article specifically examines the role played by the Green Climate Fund’s Gender Policy in promoting a shift in the organisational strategies developed by development finance institutions and commercial banks in southern Africa. It reveals how practitioners are grappling with the evolving role of financial intermediaries in promoting a shift towards low-emissions, climate-resilient, and just development. The analysis uncovers foundational components, highlights key lessons, and identifies strategic approaches to institutionalising gender mainstreaming practices. Critically, the research reveals that whilst gender mainstreaming involves multiple practicalities, the financial institutions that have most extensively institutionalised gender mainstreaming practices have done so by recognising its normative basis and have perpetuated changes to organisational values and culture alongside more pedestrian policy amendments. One of the critical aspects of this culture shift is the recognition that transformative social impacts in climate finance are predicated on the design and implementation of projects that account for existing gender-based vulnerabilities whilst also identifying and maximising opportunities for all genders. The study builds on and contributes new knowledge to existing frameworks for understanding gender mainstreaming in relation to multilateral climate finance.","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139265733","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 : 2023-11-15DOI: 10.1371/journal.pclm.0000208
Quyen Nguyen, I. Diaz‐Rainey, Adam Kitto, Ben I. McNeil, Nicholas A. Pittman, Renzhu Zhang
Investors’ sophistication on climate risk is increasing and as part of this they require high-quality and comprehensive Scope 3 emissions data. Accordingly, we investigate Scope 3 emissions data divergence (across different providers), composition (which Scope 3 categories are reported) and whether machine-learning models can be used to predict Scope 3 emissions for non-reporting firms. We find considerable divergence in the aggregated Scope 3 emissions values from three of the largest data providers (Bloomberg, Refinitiv Eikon, and ISS). The divergence is largest for ISS, as it replaces reported Scope 3 emissions with estimates from its economic input-output and life cycle assessment modelling. With respect to the composition of Scope 3 emissions, firms generally report incomplete composition, yet they are reporting more categories over time. There is a persistent contrast between relevance and completeness in the composition of Scope 3 emissions across sectors, with low materiality categories such as travel emissions being reported more frequently than typically high materiality ones, such as the use of products and processing of sold products. Finally, machine learning algorithms can improve the prediction accuracy of the aggregated Scope 3 emissions by up to 6% and up to 25% when each category is estimated individually and aggregated into total Scope 3 emissions. However, absolute prediction performance is low even with the best models, with the accuracy of estimates primarily limited by low observations in specific Scope 3 categories. We conclude that investors should be cognizant of Scope 3 emissions data divergence, incomplete reporting of Scope 3 categories, and that predictions for non-reporting firms have high absolute errors even when using machine learning models. For both reported and estimated data, caveat emptor applies.
{"title":"Scope 3 emissions: Data quality and machine learning prediction accuracy","authors":"Quyen Nguyen, I. Diaz‐Rainey, Adam Kitto, Ben I. McNeil, Nicholas A. Pittman, Renzhu Zhang","doi":"10.1371/journal.pclm.0000208","DOIUrl":"https://doi.org/10.1371/journal.pclm.0000208","url":null,"abstract":"Investors’ sophistication on climate risk is increasing and as part of this they require high-quality and comprehensive Scope 3 emissions data. Accordingly, we investigate Scope 3 emissions data divergence (across different providers), composition (which Scope 3 categories are reported) and whether machine-learning models can be used to predict Scope 3 emissions for non-reporting firms. We find considerable divergence in the aggregated Scope 3 emissions values from three of the largest data providers (Bloomberg, Refinitiv Eikon, and ISS). The divergence is largest for ISS, as it replaces reported Scope 3 emissions with estimates from its economic input-output and life cycle assessment modelling. With respect to the composition of Scope 3 emissions, firms generally report incomplete composition, yet they are reporting more categories over time. There is a persistent contrast between relevance and completeness in the composition of Scope 3 emissions across sectors, with low materiality categories such as travel emissions being reported more frequently than typically high materiality ones, such as the use of products and processing of sold products. Finally, machine learning algorithms can improve the prediction accuracy of the aggregated Scope 3 emissions by up to 6% and up to 25% when each category is estimated individually and aggregated into total Scope 3 emissions. However, absolute prediction performance is low even with the best models, with the accuracy of estimates primarily limited by low observations in specific Scope 3 categories. We conclude that investors should be cognizant of Scope 3 emissions data divergence, incomplete reporting of Scope 3 categories, and that predictions for non-reporting firms have high absolute errors even when using machine learning models. For both reported and estimated data, caveat emptor applies.","PeriodicalId":510827,"journal":{"name":"PLOS Climate","volume":"44 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139274477","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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