Simon Kamwele Awala, Kudakwashe Hove, Johanna Shekupe Valombola, Helena Nalitende Nafuka, Evans Kamwi Simasiku, Barthlomew Chataika, Lydia Ndinelao Horn, Simon Angombe, Levi S. M. Akundabweni, Osmund D. Mwandemele
In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies.
{"title":"Co-Cultivation and Matching of Early- and Late-Maturing Pearl Millet Varieties to Sowing Windows Can Enhance Climate-Change Adaptation in Semi-Arid Sub-Saharan Agroecosystems","authors":"Simon Kamwele Awala, Kudakwashe Hove, Johanna Shekupe Valombola, Helena Nalitende Nafuka, Evans Kamwi Simasiku, Barthlomew Chataika, Lydia Ndinelao Horn, Simon Angombe, Levi S. M. Akundabweni, Osmund D. Mwandemele","doi":"10.3390/cli11110227","DOIUrl":"https://doi.org/10.3390/cli11110227","url":null,"abstract":"In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"118 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135138223","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}
This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.
{"title":"A GIS-Based Assessment of Flood Hazard through Track Records over the 1886–2022 Period in Greece","authors":"Niki Evelpidou, Constantinos Cartalis, Anna Karkani, Giannis Saitis, Kostas Philippopoulos, Evangelos Spyrou","doi":"10.3390/cli11110226","DOIUrl":"https://doi.org/10.3390/cli11110226","url":null,"abstract":"This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"7 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135392023","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}
This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water.
{"title":"Examining the Spatiotemporal Changes in the Annual, Seasonal, and Daily Rainfall Climatology of Puerto Rico","authors":"José Javier Hernández Ayala, Rafael Méndez Tejeda","doi":"10.3390/cli11110225","DOIUrl":"https://doi.org/10.3390/cli11110225","url":null,"abstract":"This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"8 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589674","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}
Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed.
{"title":"Time Series Homogenization with ACMANT: Comparative Testing of Two Recent Versions in Large-Size Synthetic Temperature Datasets","authors":"Peter Domonkos","doi":"10.3390/cli11110224","DOIUrl":"https://doi.org/10.3390/cli11110224","url":null,"abstract":"Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"83 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135635392","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}
Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities.
{"title":"Regional to Mesoscale Influences of Climate Indices on Tornado Variability","authors":"Cooper P. Corey, Jason C. Senkbeil","doi":"10.3390/cli11110223","DOIUrl":"https://doi.org/10.3390/cli11110223","url":null,"abstract":"Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"1 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774621","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}
Han Ling, Guangyu Wang, Wanli Wu, Anil Shrestha, John L. Innes
The grasslands of North America are threatened by woody encroachment. Restoring historical fire regimes has been used to manage brush encroachment. However, fire management may be insufficient due to the nonlinear and hysteretic responses of vegetation recovery following encroachment and the social–political constraints affecting fire management. We synthesized the fire thresholds required to control woody encroachment by typical encroaching species in North America, especially the Great Plains region, and identified the social–political constraints facing fire management in selected grassland national parks. Our synthesis revealed the resistance, hysteresis, and irreversibility of encroached grasslands using fire and emphasized the need for a combination of brush management methods if the impacts of climate change are to be addressed. Frequent fires alone may maintain grassland states, reflecting resistance. However, high-intensity fires exceeding fire-mortality thresholds are required to exclude non-resprouting shrubs and trees, indicating hysteresis. Fire alone may be insufficient to reverse encroachment by resprouting species, exhibiting reversibility. In practice, appropriate fire management may restore resistant grassland states. However, social–political constraints have restricted the use of frequent and high-intensity fires, thereby reducing the effectiveness of management actions to control woody encroachment of grasslands in national parks. This research proposes a resilience-based framework to manage woody encroachment in grassland national parks and similar protected areas.
{"title":"Grassland Resilience to Woody Encroachment in North America and the Effectiveness of Using Fire in National Parks","authors":"Han Ling, Guangyu Wang, Wanli Wu, Anil Shrestha, John L. Innes","doi":"10.3390/cli11110219","DOIUrl":"https://doi.org/10.3390/cli11110219","url":null,"abstract":"The grasslands of North America are threatened by woody encroachment. Restoring historical fire regimes has been used to manage brush encroachment. However, fire management may be insufficient due to the nonlinear and hysteretic responses of vegetation recovery following encroachment and the social–political constraints affecting fire management. We synthesized the fire thresholds required to control woody encroachment by typical encroaching species in North America, especially the Great Plains region, and identified the social–political constraints facing fire management in selected grassland national parks. Our synthesis revealed the resistance, hysteresis, and irreversibility of encroached grasslands using fire and emphasized the need for a combination of brush management methods if the impacts of climate change are to be addressed. Frequent fires alone may maintain grassland states, reflecting resistance. However, high-intensity fires exceeding fire-mortality thresholds are required to exclude non-resprouting shrubs and trees, indicating hysteresis. Fire alone may be insufficient to reverse encroachment by resprouting species, exhibiting reversibility. In practice, appropriate fire management may restore resistant grassland states. However, social–political constraints have restricted the use of frequent and high-intensity fires, thereby reducing the effectiveness of management actions to control woody encroachment of grasslands in national parks. This research proposes a resilience-based framework to manage woody encroachment in grassland national parks and similar protected areas.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135935828","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}
Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed.
{"title":"Climate Change Skeptics’ Environmental Concerns and Support for Clean Energy Policy: A Case Study of the US Pacific Northwest","authors":"Dilshani Sarathchandra, Kristin Haltinner","doi":"10.3390/cli11110221","DOIUrl":"https://doi.org/10.3390/cli11110221","url":null,"abstract":"Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"5 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973601","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}
Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km2 for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity.
{"title":"Microclimate and Vegetation Structure Significantly Affect Butterfly Assemblages in a Tropical Dry Forest","authors":"Anirban Mahata, Rajendra Mohan Panda, Padmanava Dash, Ayusmita Naik, Alok Kumar Naik, Sharat Kumar Palita","doi":"10.3390/cli11110220","DOIUrl":"https://doi.org/10.3390/cli11110220","url":null,"abstract":"Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km2 for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"1 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973319","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}
The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios.
{"title":"Climate Risk and Vulnerability Assessment of Georgian Hydrology under Future Climate Change Scenarios","authors":"Aashutosh Aryal, Rieks Bosch, Venkataraman Lakshmi","doi":"10.3390/cli11110222","DOIUrl":"https://doi.org/10.3390/cli11110222","url":null,"abstract":"The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"2 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973470","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}
Evelyn G. Shu, Mariah Pope, Bradley Wilson, Mark Bauer, Mike Amodeo, Neil Freeman, Jeremy R. Porter
Properties in the United States face increasing exposure to tropical storm-level winds due to climate change. Driving this increasing risk are severe hurricanes that are more likely to occur when hurricanes form in the future and the northward shift of Atlantic-formed hurricanes, increasing the estimated exposure of buildings and infrastructure to damaging winds. The wind model presented here combines open data and science by utilizing high-resolution topography, computer-modeled hurricane tracks, and property data to create hyper-local tropical cyclone wind exposure information for the Contiguous United States (CONUS) from current time to 2053 under RCP 4.5. This allows for a detailed evaluation of probable wind speeds by several return periods, probabilities of cyclonic thresholds being reached or surpassed, and a comparison of this cyclone-level wind exposure between the current year and 30 years into the future under climatic changes. The results of this research reveal extensive exposure along the Gulf and Southeastern Atlantic Coasts, with significant growing exposure in the Mid-Atlantic and Northeastern regions of the country.
{"title":"Assessing Property Exposure to Cyclonic Winds under Climate Change","authors":"Evelyn G. Shu, Mariah Pope, Bradley Wilson, Mark Bauer, Mike Amodeo, Neil Freeman, Jeremy R. Porter","doi":"10.3390/cli11110217","DOIUrl":"https://doi.org/10.3390/cli11110217","url":null,"abstract":"Properties in the United States face increasing exposure to tropical storm-level winds due to climate change. Driving this increasing risk are severe hurricanes that are more likely to occur when hurricanes form in the future and the northward shift of Atlantic-formed hurricanes, increasing the estimated exposure of buildings and infrastructure to damaging winds. The wind model presented here combines open data and science by utilizing high-resolution topography, computer-modeled hurricane tracks, and property data to create hyper-local tropical cyclone wind exposure information for the Contiguous United States (CONUS) from current time to 2053 under RCP 4.5. This allows for a detailed evaluation of probable wind speeds by several return periods, probabilities of cyclonic thresholds being reached or surpassed, and a comparison of this cyclone-level wind exposure between the current year and 30 years into the future under climatic changes. The results of this research reveal extensive exposure along the Gulf and Southeastern Atlantic Coasts, with significant growing exposure in the Mid-Atlantic and Northeastern regions of the country.","PeriodicalId":37615,"journal":{"name":"Climate","volume":"49 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135271397","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：