Pub Date : 2024-07-09DOI: 10.1088/1748-9326/ad5d0c
Josephine Borghi, Michael Kuhn
This perspective examines the relationship between climate change, health outcomes, and behavioural responses across the life course. It identifies three primary channels through which climate change impacts behaviours which in turn affect health: increased morbidity driving healthcare demand and accessibility, reduced productivity and income affecting health care investments, and combined health and economic risks shaping migration patterns, dietary choices and human capital investment across the life course and generations. Climate-induced changes in behaviours exacerbate existing health-related and socio-economic vulnerabilities. While climate-related shocks elevate demand for healthcare services, disruptions in infrastructure hinder access, especially for the poorest, widening health inequities. Loss of income and disrupted employment further compound health and economic risks, pushing vulnerable communities towards informal care options and impoverishment tied to health expenditures. Increased health and economic risks are associated with migration affecting healthcare access and health outcomes. They also influence dietary choices, with health consequences. Finally, deteriorating prospects of leading a long, prosperous and healthy life may induce individuals to reduce their time horizon and assign lower values to long-term survival, impacting human capital investments across the life course and generations. Again, these impacts are prone to exhibit a social gradient with vulnerable individuals being more likely to give up on striving for a healthier life. Effective policies must integrate climate, health, and socioeconomic factors, considering long-term behavioural responses and their health and socio-economic implications. Adapting health financing mechanisms to account for climate risks and incentivise resilience-building behaviours within health and social care systems is essential for protecting health across the life course, and avoiding widening inequities.
{"title":"A health economics perspective on behavioural responses to climate change across geographic, socio-economic and demographic strata","authors":"Josephine Borghi, Michael Kuhn","doi":"10.1088/1748-9326/ad5d0c","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5d0c","url":null,"abstract":"This perspective examines the relationship between climate change, health outcomes, and behavioural responses across the life course. It identifies three primary channels through which climate change impacts behaviours which in turn affect health: increased morbidity driving healthcare demand and accessibility, reduced productivity and income affecting health care investments, and combined health and economic risks shaping migration patterns, dietary choices and human capital investment across the life course and generations. Climate-induced changes in behaviours exacerbate existing health-related and socio-economic vulnerabilities. While climate-related shocks elevate demand for healthcare services, disruptions in infrastructure hinder access, especially for the poorest, widening health inequities. Loss of income and disrupted employment further compound health and economic risks, pushing vulnerable communities towards informal care options and impoverishment tied to health expenditures. Increased health and economic risks are associated with migration affecting healthcare access and health outcomes. They also influence dietary choices, with health consequences. Finally, deteriorating prospects of leading a long, prosperous and healthy life may induce individuals to reduce their time horizon and assign lower values to long-term survival, impacting human capital investments across the life course and generations. Again, these impacts are prone to exhibit a social gradient with vulnerable individuals being more likely to give up on striving for a healthier life. Effective policies must integrate climate, health, and socioeconomic factors, considering long-term behavioural responses and their health and socio-economic implications. Adapting health financing mechanisms to account for climate risks and incentivise resilience-building behaviours within health and social care systems is essential for protecting health across the life course, and avoiding widening inequities.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1088/1748-9326/ad59b6
Maximilian Wesemeyer, Daniel Müller, Tobia Lakes
Higher crop diversity can enhance biodiversity and ecosystem services; however, it remains unclear to what extent and where crop diversity can be increased. We use spatially explicit multiscale optimization to determine potential and attainable crop diversity with field-level land use data for case studies in Brandenburg, Germany. Our model maximizes crop diversity at the landscape scale while reassigning crop types over multiple years to existing arable fields. The model implements field-level crop sequence rules and maintains the crop composition of each farm and for each year. We found that a 10% higher crop diversity can be attained on average compared to currently observed diversity; minor changes in crop composition would close this gap. Improved crop allocation can contribute to closing the gap between observed and attainable crop diversity, which in turn can increase biodiversity, improve pollination services, and support pest control.
{"title":"Reallocating crops raises crop diversity without changes to field boundaries and farm-level crop composition","authors":"Maximilian Wesemeyer, Daniel Müller, Tobia Lakes","doi":"10.1088/1748-9326/ad59b6","DOIUrl":"https://doi.org/10.1088/1748-9326/ad59b6","url":null,"abstract":"Higher crop diversity can enhance biodiversity and ecosystem services; however, it remains unclear to what extent and where crop diversity can be increased. We use spatially explicit multiscale optimization to determine potential and attainable crop diversity with field-level land use data for case studies in Brandenburg, Germany. Our model maximizes crop diversity at the landscape scale while reassigning crop types over multiple years to existing arable fields. The model implements field-level crop sequence rules and maintains the crop composition of each farm and for each year. We found that a 10% higher crop diversity can be attained on average compared to currently observed diversity; minor changes in crop composition would close this gap. Improved crop allocation can contribute to closing the gap between observed and attainable crop diversity, which in turn can increase biodiversity, improve pollination services, and support pest control.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1088/1748-9326/ad5b77
Daniel Carrión, Johnathan Rush, Elena Colicino, Allan C Just
High ambient summertime temperatures are an increasing health concern with climate change. This is a particular concern for minoritized households in the United States, for which differential energy burden may compromise adaptive capacity to high temperatures. Our research question was: Do minoritized groups experience hotter summers than the area average, and do non-Hispanic white people experience cooler summers? Using a fine-scaled spatiotemporal air temperature model and U.S. census data, we examined local (within-county) differences in warm season cooling degree days (CDDs) by ethnoracial group as a proxy for local energy demand for space cooling across states of the northeast and mid-Atlantic U.S. in 2003–2019. Using state-specific regression models adjusted for year and county, we found that Black and Latino people consistently experienced more CDDs, non-Hispanic white people experienced fewer CDDs, and Asian populations showed mixed results. We also explored a concentration-based measure of residential segregation for each ethnoracial group as one possible pathway towards temperature disparities. We included the segregation measure as a smooth term in a regression model adjusted for county and year. The results were nonlinear, but higher concentrations of white people were associated with lower annual CDDs and higher concentrations of Latino people were associated with higher annual CDDs than the county average. Concentrations for Black and Asian people were nonmonotonic, sometimes with bowed associations. These findings suggest that present-day residential segregation, as modeled by spatially smoothed ethnoracial subgroup concentrations, may contribute to summertime air temperature disparities and influence adaptive capacity. We hope these findings can support place-based interventions, including targeting of energy insecurity relief programs.
{"title":"Residential segregation and summertime air temperature across 13 northeastern U.S. states: potential implications for energy burden","authors":"Daniel Carrión, Johnathan Rush, Elena Colicino, Allan C Just","doi":"10.1088/1748-9326/ad5b77","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5b77","url":null,"abstract":"High ambient summertime temperatures are an increasing health concern with climate change. This is a particular concern for minoritized households in the United States, for which differential energy burden may compromise adaptive capacity to high temperatures. Our research question was: Do minoritized groups experience hotter summers than the area average, and do non-Hispanic white people experience cooler summers? Using a fine-scaled spatiotemporal air temperature model and U.S. census data, we examined local (within-county) differences in warm season cooling degree days (CDDs) by ethnoracial group as a proxy for local energy demand for space cooling across states of the northeast and mid-Atlantic U.S. in 2003–2019. Using state-specific regression models adjusted for year and county, we found that Black and Latino people consistently experienced more CDDs, non-Hispanic white people experienced fewer CDDs, and Asian populations showed mixed results. We also explored a concentration-based measure of residential segregation for each ethnoracial group as one possible pathway towards temperature disparities. We included the segregation measure as a smooth term in a regression model adjusted for county and year. The results were nonlinear, but higher concentrations of white people were associated with lower annual CDDs and higher concentrations of Latino people were associated with higher annual CDDs than the county average. Concentrations for Black and Asian people were nonmonotonic, sometimes with bowed associations. These findings suggest that present-day residential segregation, as modeled by spatially smoothed ethnoracial subgroup concentrations, may contribute to summertime air temperature disparities and influence adaptive capacity. We hope these findings can support place-based interventions, including targeting of energy insecurity relief programs.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1088/1748-9326/ad5458
A Patrick Behrer, Sherrie Wang
Wildfires throughout western North America produce smoke plumes that can stretch across the agricultural regions of the American Midwest. Climate change may increase the number and size of these fires and subsequent smoke plumes. These smoke plumes change solar radiation, meteorological conditions, and surface pollutant concentrations during the crop growing season and consequently influence yields of both corn and soybeans. We use a twelve-year panel of county-level yields from all counties east of the 100th meridian combined with measures of exposure to smoke plumes of low and high-density during the growing season to show that low-density plumes enhance yields while high-density plumes decrease yields. These effects appear to be driven by different changes in solar radiation induced by each type of plume but we observe changes in surface pollutants and precipitation as well. Because there are more low-density plumes today, the net effect is a slight increase in yields on average. As climate change makes wildfires larger and more frequent, the overall impact of smoke on yields would be be substantially more negative.
{"title":"Current benefits of wildfire smoke for yields in the US Midwest may dissipate by 2050","authors":"A Patrick Behrer, Sherrie Wang","doi":"10.1088/1748-9326/ad5458","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5458","url":null,"abstract":"Wildfires throughout western North America produce smoke plumes that can stretch across the agricultural regions of the American Midwest. Climate change may increase the number and size of these fires and subsequent smoke plumes. These smoke plumes change solar radiation, meteorological conditions, and surface pollutant concentrations during the crop growing season and consequently influence yields of both corn and soybeans. We use a twelve-year panel of county-level yields from all counties east of the 100th meridian combined with measures of exposure to smoke plumes of low and high-density during the growing season to show that low-density plumes enhance yields while high-density plumes decrease yields. These effects appear to be driven by different changes in solar radiation induced by each type of plume but we observe changes in surface pollutants and precipitation as well. Because there are more low-density plumes today, the net effect is a slight increase in yields on average. As climate change makes wildfires larger and more frequent, the overall impact of smoke on yields would be be substantially more negative.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1088/1748-9326/ad5b76
Benjamin P Goldstein, Dimitrios Gounaridis, Joshua P Newell, Rylie Pelton, Jennifer Schmitt
Understanding how consumption patterns affect the environment and shape well-being hinges on the rationale that the data collected on what is consumed, who consumes it, and where it is consumed are indeed accurate. To identify these consumption patterns and recommend corresponding policies, researchers and policy makers often rely on national surveys. Studies have explored the accuracy of individual surveys and the level of agreement across surveys of the same type (e.g. household expenditures), but no studies have compared representative national surveys measuring consumption in different ways. This study compares household consumption measured as expenditures and as material consumption (i.e. physical units) to assess how well we currently measure what we consume. We use multiple rigorous, national surveys to estimate meat consumption, household energy use, and private automobile use in the United States, with consumption profiles parsed by affluence, race/ethnicity, and education. Our results indicate that commonly used surveys may not accurately track important aspects of household consumption. For meat consumption, which included 30 consumption profiles detailing the consumption patterns across different demographic characteristics and meat types (e.g. kilograms beef consumed/capita for Caucasians), there is considerable disagreement between data sources for 20 profiles. By contrast, national surveys accurately measure household energy and transport (disagreement for four profiles). Our findings indicate that national surveys more accurately measure consistently tracked, standardized consumables like electricity than irregularly tracked, variable goods such as food. These results cast doubt on studies that use national surveys to draw conclusions about the how the environmental impacts of food, and, potentially, other goods (e.g. manufactured goods) vary across demographic groups. Overcoming this challenge will necessitate new surveys, updating legacy databases, and harnessing breakthroughs in data science.
{"title":"Do we accurately measure what we consume?","authors":"Benjamin P Goldstein, Dimitrios Gounaridis, Joshua P Newell, Rylie Pelton, Jennifer Schmitt","doi":"10.1088/1748-9326/ad5b76","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5b76","url":null,"abstract":"Understanding how consumption patterns affect the environment and shape well-being hinges on the rationale that the data collected on what is consumed, who consumes it, and where it is consumed are indeed accurate. To identify these consumption patterns and recommend corresponding policies, researchers and policy makers often rely on national surveys. Studies have explored the accuracy of individual surveys and the level of agreement across surveys of the same type (e.g. household expenditures), but no studies have compared representative national surveys measuring consumption in different ways. This study compares household consumption measured as expenditures and as material consumption (i.e. physical units) to assess how well we currently measure what we consume. We use multiple rigorous, national surveys to estimate meat consumption, household energy use, and private automobile use in the United States, with consumption profiles parsed by affluence, race/ethnicity, and education. Our results indicate that commonly used surveys may not accurately track important aspects of household consumption. For meat consumption, which included 30 consumption profiles detailing the consumption patterns across different demographic characteristics and meat types (e.g. kilograms beef consumed/capita for Caucasians), there is considerable disagreement between data sources for 20 profiles. By contrast, national surveys accurately measure household energy and transport (disagreement for four profiles). Our findings indicate that national surveys more accurately measure consistently tracked, standardized consumables like electricity than irregularly tracked, variable goods such as food. These results cast doubt on studies that use national surveys to draw conclusions about the how the environmental impacts of food, and, potentially, other goods (e.g. manufactured goods) vary across demographic groups. Overcoming this challenge will necessitate new surveys, updating legacy databases, and harnessing breakthroughs in data science.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Interactions between landfalling tropical cyclones (TCs) and monsoons in South China significantly influence precipitation duration, leading to severe disasters. Previous studies have primarily been individual cases, lacking systematic large-scale statistical analysis of the monsoon and landfalling tropical cyclone persistent precipitation (LTCPP) relationship. This study quantitatively investigated the relationship between monsoonal wind intensity before TCs landfall and post-landfall persistent precipitation induced by TCs in South China, employing the ERA5 reanalysis data and the best track data of 147 TCs from 1979 to 2018. The LTCPP was characterized by the frequency of persistent precipitation events during 0–72 h after TC landfall within a 500 km radius from the TC center. TCs were subdivided into weak and strong LTCPP groups based on the category-specific median of Frequency of 24 h Landfalling Tropical Cyclone Persistent Precipitation (FLTCPP24): 2705 h for TS, 6007 h for STS, and 6419 h for TY. A South China Tropical Cyclone Precipitation Monsoon Index (SCTCPM) was proposed to quantify monsoonal wind intensity derived from zonal winds at 850 hPa over two regions located in the Indian Ocean and Northwestern Pacific Ocean, within 5 d before TC landfall. The results reveal that SCTCPM < 9 m s−1 yields a 72% probability of weak LTCPP occurrence, which increases to 77% when SCTCPM < 6 m s−1. Conversely, SCTCPM > 18 m s−1 corresponds to an 80% probability of strong LTCPP. SCTCPM is an effective indicator for monsoonal wind that impacts LTCPP. Enhanced monsoonal winds, quantified by higher SCTCPM, result in post-landfall changes in horizontal wind speed, moisture transport, convective activity and upward motion, ultimately increasing LTCPP. This study deepens our understanding of the monsoon-TC relationship, emphasizing the crucial role of monsoonal wind in LTCPP in South China and offering valuable insights for disaster preparedness and risk mitigation.
{"title":"The impact of monsoon on the landfalling tropical cyclone persistent precipitation in South China","authors":"Lunkai He, Qinglan Li, Liguang Wu, Xuyang Ge, Chunxia Liu, Guangxin Li, Jiali Zhang","doi":"10.1088/1748-9326/ad5c83","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5c83","url":null,"abstract":"Interactions between landfalling tropical cyclones (TCs) and monsoons in South China significantly influence precipitation duration, leading to severe disasters. Previous studies have primarily been individual cases, lacking systematic large-scale statistical analysis of the monsoon and landfalling tropical cyclone persistent precipitation (LTCPP) relationship. This study quantitatively investigated the relationship between monsoonal wind intensity before TCs landfall and post-landfall persistent precipitation induced by TCs in South China, employing the ERA5 reanalysis data and the best track data of 147 TCs from 1979 to 2018. The LTCPP was characterized by the frequency of persistent precipitation events during 0–72 h after TC landfall within a 500 km radius from the TC center. TCs were subdivided into weak and strong LTCPP groups based on the category-specific median of Frequency of 24 h Landfalling Tropical Cyclone Persistent Precipitation (FLTCPP24): 2705 h for TS, 6007 h for STS, and 6419 h for TY. A South China Tropical Cyclone Precipitation Monsoon Index (SCTCPM) was proposed to quantify monsoonal wind intensity derived from zonal winds at 850 hPa over two regions located in the Indian Ocean and Northwestern Pacific Ocean, within 5 d before TC landfall. The results reveal that SCTCPM < 9 m s<sup>−1</sup> yields a 72% probability of weak LTCPP occurrence, which increases to 77% when SCTCPM < 6 m s<sup>−1</sup>. Conversely, SCTCPM > 18 m s<sup>−1</sup> corresponds to an 80% probability of strong LTCPP. SCTCPM is an effective indicator for monsoonal wind that impacts LTCPP. Enhanced monsoonal winds, quantified by higher SCTCPM, result in post-landfall changes in horizontal wind speed, moisture transport, convective activity and upward motion, ultimately increasing LTCPP. This study deepens our understanding of the monsoon-TC relationship, emphasizing the crucial role of monsoonal wind in LTCPP in South China and offering valuable insights for disaster preparedness and risk mitigation.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.1088/1748-9326/ad5858
Wantong Li, Gregory Duveiller, Sebastian Wieneke, Matthias Forkel, Pierre Gentine, Markus Reichstein, Shuli Niu, Mirco Migliavacca, Rene Orth
Vegetation plays an essential role in regulating carbon and water cycles, e.g. by taking up atmospheric CO2 through photosynthesis and by transferring soil water to the atmosphere through transpiration. Vegetation function is shaped by its structure and physiology: vegetation structure is determined by the amount of materials for plants and how it is organised in space and time, while vegetation physiology controls the instantaneous response of vegetation function to environmental conditions. Recognizing and disentangling these aspects of vegetation is key to understanding and predicting the response of the terrestrial biosphere to global change. This is now possible, as comprehensive measurements from Earth observations, both from satellites and the ground, provide invaluable data and information. This review introduces and describes vegetation structure and physiology, and summarises, compares, and contextualises recent literature to illustrate the state of the art in monitoring vegetation dynamics, quantifying large-scale vegetation physiology, and investigating vegetation regulation on the changes of global carbon and water fluxes. This includes results from remote sensing, in-situ measurements, and model simulations, used either to study the response of vegetation structure and physiology to global change, or to study the feedback of vegetation to global carbon and water cycles. We find that observation-based work is underrepresented compared with model-based studies. We therefore advocate further work to make better use of remote sensing and in-situ measurements, as they promote the understanding of vegetation dynamics from a fundamental data-driven perspective. We highlight the usefulness of novel and increasing satellite remote sensing data to comprehensively investigate the structural and physiological dynamics of vegetation on the global scale, and to infer their influence on the land carbon sink and terrestrial evaporation. We argue that field campaigns can and should complement large-scale analyses together with fine spatio-temporal resolution satellite remote sensing to infer relevant ecosystem-scale processes.
{"title":"Regulation of the global carbon and water cycles through vegetation structural and physiological dynamics","authors":"Wantong Li, Gregory Duveiller, Sebastian Wieneke, Matthias Forkel, Pierre Gentine, Markus Reichstein, Shuli Niu, Mirco Migliavacca, Rene Orth","doi":"10.1088/1748-9326/ad5858","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5858","url":null,"abstract":"Vegetation plays an essential role in regulating carbon and water cycles, e.g. by taking up atmospheric CO<sub>2</sub> through photosynthesis and by transferring soil water to the atmosphere through transpiration. Vegetation function is shaped by its structure and physiology: vegetation structure is determined by the amount of materials for plants and how it is organised in space and time, while vegetation physiology controls the instantaneous response of vegetation function to environmental conditions. Recognizing and disentangling these aspects of vegetation is key to understanding and predicting the response of the terrestrial biosphere to global change. This is now possible, as comprehensive measurements from Earth observations, both from satellites and the ground, provide invaluable data and information. This review introduces and describes vegetation structure and physiology, and summarises, compares, and contextualises recent literature to illustrate the state of the art in monitoring vegetation dynamics, quantifying large-scale vegetation physiology, and investigating vegetation regulation on the changes of global carbon and water fluxes. This includes results from remote sensing, <italic toggle=\"yes\">in-situ</italic> measurements, and model simulations, used either to study the response of vegetation structure and physiology to global change, or to study the feedback of vegetation to global carbon and water cycles. We find that observation-based work is underrepresented compared with model-based studies. We therefore advocate further work to make better use of remote sensing and <italic toggle=\"yes\">in-situ</italic> measurements, as they promote the understanding of vegetation dynamics from a fundamental data-driven perspective. We highlight the usefulness of novel and increasing satellite remote sensing data to comprehensively investigate the structural and physiological dynamics of vegetation on the global scale, and to infer their influence on the land carbon sink and terrestrial evaporation. We argue that field campaigns can and should complement large-scale analyses together with fine spatio-temporal resolution satellite remote sensing to infer relevant ecosystem-scale processes.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.1088/1748-9326/ad5ab4
Rubén Vázquez, Iván M Parras-Berrocal, William Cabos, Dmitry Sein, Rafael Mañanes, Marina Bolado-Penagos, Alfredo Izquierdo
The Canary/Iberia region (CIR), part of the Canary Current Upwelling System, is well-known for its coastal productivity and crucial role in enriching the oligotrophic open ocean through the offshore transport of the upwelled coastal waters. Given its significant ecological and socio-economic importance, it is essential to assess the impact of climate change on this area. Therefore, the goal of this study is to analyze the climate change signal over the CIR using a high-resolution regional climate system model driven by the Earth system model MPI-ESM-LR under RCP8.5 scenario. This modelling system presents a regional atmosphere model coupled to a global ocean model with enough horizontal resolution at CIR to examine the role of the upwelling favourable winds and the ocean stratification as key factors in the future changes. CIR exhibits significant latitudinal and seasonal variability in response to climate change under RCP8.5 scenario, where ocean stratification and wind patterns will play both complementary and competitive roles. Ocean stratification will increase from the Strait of Gibraltar to Cape Juby by the end of the century, weakening the coastal upwelling all year long. This increase in stratification is associated with a freshening of the surface layers of the North Atlantic. However, modifications in the wind pattern will play a primary role in upwelling source water depth changes in the southernmost region of the CIR in winter and in the north of the Iberian Peninsula in summer. Wind pattern changes are related to the intensification of the Azores High in winter and to a deepening of the Iberian thermal low in summer months.
{"title":"Climate change in the Canary/Iberia upwelling region: the role of ocean stratification and wind","authors":"Rubén Vázquez, Iván M Parras-Berrocal, William Cabos, Dmitry Sein, Rafael Mañanes, Marina Bolado-Penagos, Alfredo Izquierdo","doi":"10.1088/1748-9326/ad5ab4","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5ab4","url":null,"abstract":"The Canary/Iberia region (CIR), part of the Canary Current Upwelling System, is well-known for its coastal productivity and crucial role in enriching the oligotrophic open ocean through the offshore transport of the upwelled coastal waters. Given its significant ecological and socio-economic importance, it is essential to assess the impact of climate change on this area. Therefore, the goal of this study is to analyze the climate change signal over the CIR using a high-resolution regional climate system model driven by the Earth system model MPI-ESM-LR under RCP8.5 scenario. This modelling system presents a regional atmosphere model coupled to a global ocean model with enough horizontal resolution at CIR to examine the role of the upwelling favourable winds and the ocean stratification as key factors in the future changes. CIR exhibits significant latitudinal and seasonal variability in response to climate change under RCP8.5 scenario, where ocean stratification and wind patterns will play both complementary and competitive roles. Ocean stratification will increase from the Strait of Gibraltar to Cape Juby by the end of the century, weakening the coastal upwelling all year long. This increase in stratification is associated with a freshening of the surface layers of the North Atlantic. However, modifications in the wind pattern will play a primary role in upwelling source water depth changes in the southernmost region of the CIR in winter and in the north of the Iberian Peninsula in summer. Wind pattern changes are related to the intensification of the Azores High in winter and to a deepening of the Iberian thermal low in summer months.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.1088/1748-9326/ad5bf3
Xun Su and Minpeng Chen
Crop migration as an adaptation to modulate climate change’s impact on crop yields presents both benefits and risks. We explored how maize migration in China modulates yield responses to climate change and quantified the potential economic benefits of maize migration as an adaptation strategy. We employed a panel data model to identify and measure the factors driving the relocation of maize area, linear regression to quantify the effects of maize migration on climate exposure and irrigated area, and an econometric model to estimate the effects of maize migration on yield. The results show that rise in temperature has a significant negative effect on maize area and that precipitation has a significant positive effect. The migration of maize area is driven by socio-economic factors including agricultural gross domestic product, power of farming machines, and fertilizer input. Moreover, expanded irrigation reduces the adverse effects of high temperatures on maize yield, thereby influencing adaptive crop migrations. The beneficial effects of maize migration are primarily achieved by reducing the adverse effects of extreme heat and strengthening the positive effects of irrigation. However, the extent of this adaptation is jointly affected by agricultural policies, irrigation infrastructure, and economic factors. Current market-oriented agricultural policies may be effective in guiding spatial shifts in maize distribution to align with climate-driven changes, potentially decreasing the vulnerability of China’s maize yield to the impact of climate change. China’s food security policies need to consider climate-driven spatial shifts in crop cultivation and enhance food subsidy policies to highlight the benefits of investment in climate change adaptation, such as adjusting cropping acreage and irrigation to farmers in North China.
{"title":"Maize migration mitigates the negative impact of climate change on China’s maize yield","authors":"Xun Su and Minpeng Chen","doi":"10.1088/1748-9326/ad5bf3","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5bf3","url":null,"abstract":"Crop migration as an adaptation to modulate climate change’s impact on crop yields presents both benefits and risks. We explored how maize migration in China modulates yield responses to climate change and quantified the potential economic benefits of maize migration as an adaptation strategy. We employed a panel data model to identify and measure the factors driving the relocation of maize area, linear regression to quantify the effects of maize migration on climate exposure and irrigated area, and an econometric model to estimate the effects of maize migration on yield. The results show that rise in temperature has a significant negative effect on maize area and that precipitation has a significant positive effect. The migration of maize area is driven by socio-economic factors including agricultural gross domestic product, power of farming machines, and fertilizer input. Moreover, expanded irrigation reduces the adverse effects of high temperatures on maize yield, thereby influencing adaptive crop migrations. The beneficial effects of maize migration are primarily achieved by reducing the adverse effects of extreme heat and strengthening the positive effects of irrigation. However, the extent of this adaptation is jointly affected by agricultural policies, irrigation infrastructure, and economic factors. Current market-oriented agricultural policies may be effective in guiding spatial shifts in maize distribution to align with climate-driven changes, potentially decreasing the vulnerability of China’s maize yield to the impact of climate change. China’s food security policies need to consider climate-driven spatial shifts in crop cultivation and enhance food subsidy policies to highlight the benefits of investment in climate change adaptation, such as adjusting cropping acreage and irrigation to farmers in North China.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.1088/1748-9326/ad5a27
Jörg Schwinger, Timothée Bourgeois and Wilfried Rickels
Ocean alkalinity enhancement (OAE) deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. The chemical efficiency of OAE (the amount of CO2 sequestered per unit of alkalinity added) depends, among other factors, on the background state of the surface ocean, which will significantly change until the end of this century and beyond. Here, we investigate the consequences of such changes for the long-term efficiency of OAE. We show, using idealized and scenario simulations with an Earth system model, that under doubling (quadrupling) of pre-industrial atmospheric CO2 concentrations, the simulated mean efficiency of OAE increases by about 18% (29%) from 0.76 to 0.90 (0.98). We find that only half of this effect can be explained by changes in the sensitivity of CO2 sequestration to alkalinity addition itself. The remainder is due to the larger portion of anthropogenic emissions taken up by a high-alkalinity ocean. Importantly, both effects are reversed if atmospheric CO2 concentrations were to decline due to large-scale deployment of land-based (or alternative ocean-based) carbon dioxide removal (CDR) methods. By considering an overshoot pathway that relies on large amounts of land-based CDR, we demonstrate that OAE efficiency indeed shows a strong decline after atmospheric CO2 concentrations have peaked. Our results suggest that the assumption of a constant, present-day chemical efficiency of OAE in integrated assessment modeling and carbon credit assignments could lead to economically inefficient OAE implementation pathways.
{"title":"On the emission-path dependency of the efficiency of ocean alkalinity enhancement","authors":"Jörg Schwinger, Timothée Bourgeois and Wilfried Rickels","doi":"10.1088/1748-9326/ad5a27","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5a27","url":null,"abstract":"Ocean alkalinity enhancement (OAE) deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. The chemical efficiency of OAE (the amount of CO2 sequestered per unit of alkalinity added) depends, among other factors, on the background state of the surface ocean, which will significantly change until the end of this century and beyond. Here, we investigate the consequences of such changes for the long-term efficiency of OAE. We show, using idealized and scenario simulations with an Earth system model, that under doubling (quadrupling) of pre-industrial atmospheric CO2 concentrations, the simulated mean efficiency of OAE increases by about 18% (29%) from 0.76 to 0.90 (0.98). We find that only half of this effect can be explained by changes in the sensitivity of CO2 sequestration to alkalinity addition itself. The remainder is due to the larger portion of anthropogenic emissions taken up by a high-alkalinity ocean. Importantly, both effects are reversed if atmospheric CO2 concentrations were to decline due to large-scale deployment of land-based (or alternative ocean-based) carbon dioxide removal (CDR) methods. By considering an overshoot pathway that relies on large amounts of land-based CDR, we demonstrate that OAE efficiency indeed shows a strong decline after atmospheric CO2 concentrations have peaked. Our results suggest that the assumption of a constant, present-day chemical efficiency of OAE in integrated assessment modeling and carbon credit assignments could lead to economically inefficient OAE implementation pathways.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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