Jarad P Mellard, J. Henden, Å. Pedersen, F. Marolla, S. Hamel, N. Yoccoz, R. Ims
Scientists and wildlife managers implementing adaptive monitoring and management schemes, are tasked with providing predictions of population responses to harvest and environmental changes. Such predictions are useful not only to forecast direct effects of climate, productivity, land use, or habitat degradation, but also changes in the food web, such as expanding/ increasing species that are predators, prey, and competitors of populations of concern. Explicit consideration of food webs and their dynamics in more complex models could provide better predictions of future changes, and allow us to better assess the influence of management actions. Here, we present our perspective on what we have learned from conducting a number of case studies using such a food web approach with a focus on climate and harvest impacts and their implications for management. We found empirical support for many of our hypothesized food web effects, and were able in some cases to obtain short-term forecasts with slightly lower prediction error using models that account for food web dynamics compared with simpler models. Predictions are the foundation of adaptive management because they allow quantitative assessment of the effects of management actions; however, evaluating predictions requires adequate and highquality monitoring data. Results from our case studies show that a combination of long-term monitoring and different types of study designs coupled with models of adequate complexity are likely required to better understand populations’ responses to environmental changes and harvest, as well as the consequences for food webs.
{"title":"Food web approach for managing Arctic wildlife populations in an era of rapid environmental change","authors":"Jarad P Mellard, J. Henden, Å. Pedersen, F. Marolla, S. Hamel, N. Yoccoz, R. Ims","doi":"10.3354/CR01638","DOIUrl":"https://doi.org/10.3354/CR01638","url":null,"abstract":"Scientists and wildlife managers implementing adaptive monitoring and management schemes, are tasked with providing predictions of population responses to harvest and environmental changes. Such predictions are useful not only to forecast direct effects of climate, productivity, land use, or habitat degradation, but also changes in the food web, such as expanding/ increasing species that are predators, prey, and competitors of populations of concern. Explicit consideration of food webs and their dynamics in more complex models could provide better predictions of future changes, and allow us to better assess the influence of management actions. Here, we present our perspective on what we have learned from conducting a number of case studies using such a food web approach with a focus on climate and harvest impacts and their implications for management. We found empirical support for many of our hypothesized food web effects, and were able in some cases to obtain short-term forecasts with slightly lower prediction error using models that account for food web dynamics compared with simpler models. Predictions are the foundation of adaptive management because they allow quantitative assessment of the effects of management actions; however, evaluating predictions requires adequate and highquality monitoring data. Results from our case studies show that a combination of long-term monitoring and different types of study designs coupled with models of adequate complexity are likely required to better understand populations’ responses to environmental changes and harvest, as well as the consequences for food webs.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"81 1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86455287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Di Ma, Q. Jing, Yue‐Ping Xu, Alex J. Cannon, T. Dong, M. Semenov, B. Qian
Using climate scenarios from only 1 or a small number of global climate models (GCMs) in climate change impact studies may lead to biased assessment due to large uncertainty in climate projections. Ensemble means in impact projections derived from a multi-GCM ensemble are often used as best estimates to reduce bias. However, it is often time consuming to run process-based models (e.g. hydrological and crop models) in climate change impact studies using numerous climate scenarios. It would be interesting to investigate if using a reduced number of climate scenarios could lead to a reasonable estimate of the ensemble mean. In this study, we generated a single ensemble-mean climate scenario (En-WG scenario) using ensemble means of the change factors derived from 20 GCMs included in CMIP5 to perturb the parameters in a weather generator, LARS-WG, for selected locations across Canada. We used En-WG scenarios to drive crop growth models in DSSAT ver. 4.7 to simulate crop yields for canola and spring wheat under RCP4.5 and RCP8.5 emission scenarios. We evaluated the potential of using the En-WG scenarios to simulate crop yields by comparing them with crop yields simulated with the LARS-WG generated climate scenarios based on each of the 20 GCMs (WG scenarios). Our results showed that simulated crop yields using the En-WG scenarios were often close to the ensemble means of simulated crop yields using the 20 WG scenarios with a high probability of outperforming simulations based on a randomly selected GCM. Further studies are required, as the results of the proposed ap proach may be influenced by selected crop types, crop models, weather generators, and GCM ensembles.
{"title":"Using ensemble-mean climate scenarios for future crop yield projections: a stochastic weather generator approach","authors":"Di Ma, Q. Jing, Yue‐Ping Xu, Alex J. Cannon, T. Dong, M. Semenov, B. Qian","doi":"10.3354/CR01646","DOIUrl":"https://doi.org/10.3354/CR01646","url":null,"abstract":"Using climate scenarios from only 1 or a small number of global climate models (GCMs) in climate change impact studies may lead to biased assessment due to large uncertainty in climate projections. Ensemble means in impact projections derived from a multi-GCM ensemble are often used as best estimates to reduce bias. However, it is often time consuming to run process-based models (e.g. hydrological and crop models) in climate change impact studies using numerous climate scenarios. It would be interesting to investigate if using a reduced number of climate scenarios could lead to a reasonable estimate of the ensemble mean. In this study, we generated a single ensemble-mean climate scenario (En-WG scenario) using ensemble means of the change factors derived from 20 GCMs included in CMIP5 to perturb the parameters in a weather generator, LARS-WG, for selected locations across Canada. We used En-WG scenarios to drive crop growth models in DSSAT ver. 4.7 to simulate crop yields for canola and spring wheat under RCP4.5 and RCP8.5 emission scenarios. We evaluated the potential of using the En-WG scenarios to simulate crop yields by comparing them with crop yields simulated with the LARS-WG generated climate scenarios based on each of the 20 GCMs (WG scenarios). Our results showed that simulated crop yields using the En-WG scenarios were often close to the ensemble means of simulated crop yields using the 20 WG scenarios with a high probability of outperforming simulations based on a randomly selected GCM. Further studies are required, as the results of the proposed ap proach may be influenced by selected crop types, crop models, weather generators, and GCM ensembles.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"32 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86423843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessing the impact of Land-use and Land-cover changes on the climate over India using a Regional Climate Model (RegCM4)","authors":"S. Nayak, M. Mandal, S. Maity","doi":"10.3354/cr01666","DOIUrl":"https://doi.org/10.3354/cr01666","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"114 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77766819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling snowfall in southern Italy: a historical perspective in the Benevento Valley (1645–2018)","authors":"N. Diodato, I. Gómara, G. Bellocchi","doi":"10.3354/cr01681","DOIUrl":"https://doi.org/10.3354/cr01681","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"64 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77948342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Association between El Niño and extreme temperatures in southern South America in CMIP5 models. Part 2: future climate projections","authors":"Soledad Collazo, Mariana Barrucand, M. Rusticucci","doi":"10.3354/cr01673","DOIUrl":"https://doi.org/10.3354/cr01673","url":null,"abstract":"Abstract","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"6 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82489023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RG de Moura, F. Correia, J. Veiga, V. Capistrano, PY Kubota
{"title":"Influence of isolated interannual and decadal scales on the water balance of the Amazon basin","authors":"RG de Moura, F. Correia, J. Veiga, V. Capistrano, PY Kubota","doi":"10.3354/cr01685","DOIUrl":"https://doi.org/10.3354/cr01685","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"92 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72769526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Rajkumar, C. S. Shaijumon, B. Gopakumar, D. Gopalakrishnan
{"title":"Recent patterns of extreme temperature events over Tamil Nadu, India","authors":"R. Rajkumar, C. S. Shaijumon, B. Gopakumar, D. Gopalakrishnan","doi":"10.3354/CR01655","DOIUrl":"https://doi.org/10.3354/CR01655","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"3 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72886407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Mirzaei, H. Azarm, M. Yazdanpanah, M. Mardani Najafabadi
{"title":"Socio-economic, social-capital and psychological characteristics and climate change adaptive behavior of farmers in Iran","authors":"A. Mirzaei, H. Azarm, M. Yazdanpanah, M. Mardani Najafabadi","doi":"10.3354/cr01683","DOIUrl":"https://doi.org/10.3354/cr01683","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"25 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81586995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Preconditions for CMIP6 models to reproduce the relationship between wintertime ENSO and subsequent East Asian summer rainfall","authors":"Y. Fu, Z. Lin, T. Wang","doi":"10.3354/cr01663","DOIUrl":"https://doi.org/10.3354/cr01663","url":null,"abstract":"","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"25 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81277109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Zhang, J. Wang, X. Zou, Rui Mao, D. Gong, X. Feng, J. Zhu
Wind erosion is largely determined by wind erosion climatic erosivity. In this study, we examined changes in wind erosion climatic erosivity during 4 seasons across northern China from 1981-2016 using 2 models: the wind erosion climatic erosivity of the Wind Erosion Equation (WEQ) model and the weather factor from the Revised Wind Erosion Equation (RWEQ) model. Results showed that wind erosion climatic erosivity derived from the 2 models was highest in spring and lowest in winter with high values over the Kumtag Desert, the Qaidam Basin, the boundary between Mongolia and China, and the Hulunbuir Sandy Land. In spring and summer, wind erosion climatic erosivity showed decreasing trends in whole of northern China from 1981-2016, whereas there was an increasing trend in wind erosion climatic erosivity over the Gobi Desert from 1992-2011. For the weather factor of the RWEQ model, the difference between northern Northwest China and the Gobi Desert and eastern-northern China was much larger than that of the wind erosion climatic erosivity of the WEQ model. In addition, in contrast to a decreasing trend in the weather factor of the RWEQ model over southern Northwest China during spring and summer from 1981-2016, the wind erosion climatic erosivity of the WEQ model showed a decreasing trend for 1981-1992 and an increasing trend for 1992-2011 over southern Northwest China. According to a comparison between dust emission and wind erosion climatic erosivity, the 2 models have the ability to project changes in future wind erosion in northern China.
{"title":"Changes in wind erosion climatic erosivity in northern China from 1981-2016: a comparison of two climate/weather factors of wind erosion models","authors":"F. Zhang, J. Wang, X. Zou, Rui Mao, D. Gong, X. Feng, J. Zhu","doi":"10.3354/CR01640","DOIUrl":"https://doi.org/10.3354/CR01640","url":null,"abstract":"Wind erosion is largely determined by wind erosion climatic erosivity. In this study, we examined changes in wind erosion climatic erosivity during 4 seasons across northern China from 1981-2016 using 2 models: the wind erosion climatic erosivity of the Wind Erosion Equation (WEQ) model and the weather factor from the Revised Wind Erosion Equation (RWEQ) model. Results showed that wind erosion climatic erosivity derived from the 2 models was highest in spring and lowest in winter with high values over the Kumtag Desert, the Qaidam Basin, the boundary between Mongolia and China, and the Hulunbuir Sandy Land. In spring and summer, wind erosion climatic erosivity showed decreasing trends in whole of northern China from 1981-2016, whereas there was an increasing trend in wind erosion climatic erosivity over the Gobi Desert from 1992-2011. For the weather factor of the RWEQ model, the difference between northern Northwest China and the Gobi Desert and eastern-northern China was much larger than that of the wind erosion climatic erosivity of the WEQ model. In addition, in contrast to a decreasing trend in the weather factor of the RWEQ model over southern Northwest China during spring and summer from 1981-2016, the wind erosion climatic erosivity of the WEQ model showed a decreasing trend for 1981-1992 and an increasing trend for 1992-2011 over southern Northwest China. According to a comparison between dust emission and wind erosion climatic erosivity, the 2 models have the ability to project changes in future wind erosion in northern China.","PeriodicalId":10438,"journal":{"name":"Climate Research","volume":"29 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81378042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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