scholarly journals Climate Change May Imperil Tea Production in the Four Major Tea Producers According to Climate Prediction Models

Agronomy ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1536
Author(s):  
Sadeeka Layomi Jayasinghe ◽  
Lalit Kumar
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Precipitation Seasonality ◽  
Maxent Modelling ◽  
Climatic Scenarios ◽  
The Impact

The threat of accelerating climate change on species distribution now and in the future is a topic of increasing research interest. However, little work has been undertaken to assess how shifting climates will affect the suitability of tea cultivation. Therefore, we used MaxEnt modelling to project the impact of current and future climatic scenarios on the potential distribution of tea across the four tea-producing countries of China, India, Kenya and Sri Lanka. Projections were made for the years 2050 and 2070 with three Representative Concentration Pathways (RCPs) using seven bioclimatic predictors under three global circulation models (GCMs). The current and future habitat suitability for tea predicted by the models produced a high accuracy rate, with high areas under the receiver operating characteristic curve (AUCs) for all tested RCPs under the three GCMs for the four countries. The mean true skill statistic (TSS) values for tea in Sri Lanka, Kenya, India and China were 0.80, 0.91, 0.91, and 0.74, respectively. The kappa values (k) of the current and future models for all four countries ranged from 0.40 to 0.75, which indicates that the overall performance of the model was good. The precipitation seasonality and annual precipitation were found to be the most influential variables in Sri Lanka and India, respectively, while annual mean temperature was the most effective contributor for determining the suitability of habitat for tea in Kenya and China. An important proviso is that some existing tea-growing areas will face reduced suitability for future tea cultivation suggesting that by 2050 there will be a drastic reduction in the optimal suitability by averages of 26.2%, 14%, and 4.7% in Kenya, Sri Lanka and China, respectively. The optimal suitability will be reduced by 15.1%, 28.6% and 2.6% in Kenya, Sri Lanka and China, respectively, by 2070. India displays an advantage in projected future climates as it gains optimal suitability areas of 15% by 2050 and 25% by 2070.

scholarly journals Reservoir yield intercomparison of large dams in Jaguaribe Basin-CE in climate change scenarios

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Renato de Oliveira Fernandes ◽  
Cleiton da Silva Silveira ◽  
Ticiana Marinho de Carvalho Studart ◽  
Francisco de Assis de Souza Filho
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Great Divergence ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Reservoir Yield

ABSTRACT Climate changes can have different impacts on water resources. Strategies to adapt to climate changes depend on impact studies. In this context, this study aimed to estimate the impact that changes in precipitation, projected by Global Circulation Models (GCMs) in the fifth report by the Intergovernmental Panel on Climate Change (IPCC-AR5) may cause on reservoir yield (Q90) of large reservoirs (Castanhão and Banabuiú), located in the Jaguaribe River Basin, Ceará. The rainfall data are from 20 GCMs using two greenhouse gas scenarios (RCP4.5 and RCP8.5). The precipitation projections were used as input data for the rainfall-runoff model (SMAP) and, after the reservoirs’ inflow generation, the reservoir yields were simulated in the AcquaNet model, for the time periods of 2040-2069 and 2070-2099. The results were analyzed and presented a great divergence, in sign (increase or decrease) and in the magnitude of change of Q90. However, most Q90 projections indicated reduction in both reservoirs, for the two periods, especially at the end of the 21th century.

scholarly journals Citizen science and niche modeling to track and forecast the expansion of the brown marmorated stinkbug Halyomorpha halys (Stål, 1855)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jean-Claude Streito ◽  
Marguerite Chartois ◽  
Éric Pierre ◽  
François Dusoulier ◽  
Jean-Marc Armand ◽  
...  
Keyword(s):  
Climate Change ◽  
Citizen Science ◽  
Habitat Preferences ◽  
Halyomorpha Halys ◽  
Eastern Asia ◽  
Invasive Pests ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Set Up ◽  
The Impact

AbstractHalyomorpha halys (Stål, 1855), the Brown Marmorated StinkBug (BMSB) is a highly successful invasive species native to eastern Asia that managed to spread into North America and Europe in recent decades. We set up a citizen science survey to monitor BMSB expansion in France in 2012 and analyzed the data it yielded between 2012 and 2019 to examine the local expansion of the insect. These data were gathered with occurrences form various sources (GBIF, literature) to calibrate a species niche model and assess potential current BMSB range. We evaluated the potential changes to the BMSB range due to climate change by projecting the model according to 6 global circulation models (GCM) and the shared socio-economic pathways SSP245 in two time periods 2021–2040 and 2041–2060. Citizen science allowed to track BMSB expansion in France and provided information about its phenology and its habitat preferences. The model highlighted the potential for further range expansion in Europe and illustrated the impact of climate change. These results could help managing the current BMSB invasion and the framework of this survey could contribute to a better preparedness of phytosanitary authorities either for the BMSB or other invasive pests.

scholarly journals Climate Change impacts the <i>Water Highway</i> project in Morocco

2019 ◽  
Author(s):  
Nabil El Moçayd ◽  
Suchul Kang ◽  
Elfatih A. B. Eltahir
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Study Region ◽  
Global Circulation ◽  
Global Circulation Models ◽  
The North ◽  
Local Water ◽  
The Impact

Abstract. The hydrology of Morocco is characterized by a significant spatial variability. Precipitation follows a sharp gradient decreasing from the North to the South. In order to redistribute water, a project is proposed to transfer 860 million m3 per year from the wet north to the arid southern regions, {Water Highway}. The present study aims to address the viability of the project including the effects of climate change in the watersheds located in the North. We perform Regional Climate Model (RCMs) simulations over the study region using boundary conditions from five different global circulation models (GCMs) and following two emissions scenarios RCP4.5 (with mitigation) and RCP8.5 (business as usual). The impact on precipitation is assessed and the decrease of available water quantity is estimated. Under RCP8.5 the project is likely unfeasible. However, under the RCP4.5 a rescaled version of this project may be feasible depending on how much water is allocated to satisfy the local water demand.

scholarly journals Selection of the Optimum Global Circulation Model that Mimics the Circumstances of Egypt

2020 ◽  
Vol 9 (1) ◽  
pp. 784-793
Keyword(s):  
Climate Change ◽  
Performance Indicators ◽  
Circulation Model ◽  
Mean Bias Error ◽  
Bias Error ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Average Absolute Relative Error ◽  
The Impact ◽  
Precipitation And Temperature

Egyptian researchers in the field of climatic changes and their effects on various sectors, such as agriculture, water resources, health and social usually operate one of the Global Circulation Models (GCMs) and rely on its results. They considered its results as facts and real and they study the impact without reference to the uncertainty in their results. This is a major drawback to study the effect of climate changes on different sectors since there is a persuasive variation in the results of different models. Therefore, the impact analysis may result in building policies and develop alternatives in a way that is related to the real situation of the area under study. It has been found that the best global model or recycling models for the case of Egypt must be neutralized. It is an imperative component for building future policies to study the impact of climate change properly. The current study focuses on assessing the results of GCMs in Egypt. Previous reviews showed that there is no study to address this issue on Egypt. Thus, the following methodology was followed. Forty GCMs in Coupled Model Inter-comparing Project (CMIP5), are analyzed for the variable’s precipitation and temperature. These GCMs were Evaluated for Egypt for the climate variable precipitation rate through dividing the entire Egypt area to 110 cells each cell is square 100 km x 100 km. The precipitation and temperature were evaluated through applying five performance indicators. These indicators are listed as follow: i) coefficient of correlation (CoC) , ii) normalized root mean (NRMSE), absolute normalized mean bias error (ANMBE), average absolute relative error (AARE) and skill score (SS).The Payoff matrix (40 GCMs versus 5 indicators) is developed and then the entropy technique for determination of the performance indicators’ weights is applied. The Normalization technique was applied for each season out of 4 seasons that are winter, spring, summer and autumn on the performance indicators. These weights are applied to assist for ranking the 40 GCMs. The Ranking of these GCMs were obtained through a multi-criterion decision-making outranking method (PROMETHEE-2). Finally, it is proven that the “MPI-ESM-LR” GCM is found to be the best model for predicting the climate change parameters, (precipitation and temperature), all over Egypt compared to the other 39 models. The MPI-ESM-LR GCM model is developed by the Max Planck Institute for Meteorology in Germany. It is recommended that the results of climate change projects for Egypt up until year 2100 has to apply the output results of the GCM named MPI-ESM-LR rather than other GCMs as long as it gives the most proper results for climate change projection of Egypt.

scholarly journals Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus armandi in China

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 544
Author(s):  
Hang Ning ◽  
Ming Tang ◽  
Hui Chen
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Greenhouse Gas Emission ◽  
Central China ◽  
Qinling Mountains ◽  
Climate Scenarios ◽  
Impact Of Climate Change ◽  
Precipitation Seasonality ◽  
Suitable Area ◽  
The Impact

Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) is a bark beetle native to China and is the most destructive forest pest in the Pinus armandii woodlands of central China. Due to ongoing climate warming, D. armandi outbreaks have become more frequent and severe. Here, we used Maxent to model its current and future potential distribution in China. Minimum temperature of the coldest month and precipitation seasonality are the two major factors constraining the current distribution of D. armandi. Currently, the suitable area of D. armandi falls within the Qinling Mountains and Daba Mountains. The total suitable area is 15.83 × 104 km2. Under future climate scenarios, the total suitable area is projected to increase slightly, while remaining within the Qinling Mountains and Daba Mountains. Among the climate scenarios, the distribution expanded the most under the maximum greenhouse gas emission scenario (representative concentration pathway (RCP) 8.5). Under all assumptions, the highly suitable area is expected to increase over time; the increase will occur in southern Shaanxi, northwest Hubei, and northeast Sichuan Provinces. By the 2050s, the highly suitable area is projected to increase by 0.82 × 104 km2. By the 2050s, the suitable climatic niche for D. armandi will increase along the Qinling Mountains and Daba Mountains, posing a major challenge for forest managers. Our findings provide information that can be used to monitor D. armandi populations, host health, and the impact of climate change, shedding light on the effectiveness of management responses.

scholarly journals Potential Impact of Climate Change on Schistosomiasis: A Global Assessment Attempt

2018 ◽  
Vol 3 (4) ◽  
pp. 117 ◽  
Author(s):  
Guo-Jing Yang ◽  
Robert Bergquist
Keyword(s):  
Climate Change ◽  
Coupled Model ◽  
Maximum Temperature ◽  
Intergovernmental Panel ◽  
Meteorological Model ◽  
Ambient Temperatures ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Parasite Stage ◽  
Near Future

Based on an ensemble of global circulation models (GCMs), four representative concentration pathways (RCPs) and several ongoing and planned Coupled Model Intercomparison Projects (CMIPs), the Intergovernmental Panel on Climate Change (IPCC) predicts that global, average temperatures will increase by at least 1.5 °C in the near future and more by the end of the century if greenhouse gases (GHGs) emissions are not genuinely tempered. While the RCPs are indicative of various amounts of GHGs in the atmosphere the CMIPs are designed to improve the workings of the GCMs. We chose RCP4.5 which represented a medium GHG emission increase and CMIP5, the most recently completed CMIP phase. Combining this meteorological model with a biological counterpart model accounted for replication and survival of the snail intermediate host as well as maturation of the parasite stage inside the snail at different ambient temperatures. The potential geographical distribution of the three main schistosome species: Schistosoma japonicum, S. mansoni and S. haematobium was investigated with reference to their different transmission capabilities at the monthly mean temperature, the maximum temperature of the warmest month(s) and the minimum temperature of the coldest month(s). The set of six maps representing the predicted situations in 2021–2050 and 2071–2100 for each species mainly showed increased transmission areas for all three species but they also left room for potential shrinkages in certain areas.

scholarly journals Variations of Drought Tendency, Frequency, and Characteristics and Their Responses to Climate Change under CMIP5 RCP Scenarios in Huai River Basin, China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2174 ◽  
Author(s):  
Jingcai Wang ◽  
Hui Lin ◽  
Jinbai Huang ◽  
Chenjuan Jiang ◽  
Yangyang Xie ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Eastern China ◽  
Cmip5 Models ◽  
Drought Severity ◽  
Global Circulation Models ◽  
Huai River Basin ◽  
Huai River ◽  
The Future ◽  
The Impact

Huai River Basin (HRB) is an important food and industrial production area and a frequently drought-affected basin in eastern China. It is necessary to consider the future drought development for reducing the impact of drought disasters. Three global circulation models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5), such as CNRM-CM5 (CNR), HadGEM2-ES (Had) and MIROC5 (MIR), were used to assessment the future drought conditions under two Representative Concentration Pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. The standardized precipitation evapotranspiration index (SPEI), statistical method, Mann-Kendall test, and run theory were carried out to study the variations of drought tendency, frequency, and characteristics and their responses to climate change. The research showed that the three CMIP5 models differ in describing the future seasonal and annual variations of precipitation and temperature in the basin and thus lead to the differences in describing drought trends, frequency, and drought characteristics, such as drought severity, drought duration, and drought intensity. However, the drought trend, frequency, and characteristics in the future are more serious than the history. The drought frequency and characteristics tend to be strengthened under the scenario of high concentration of RCP8.5, and the drought trend is larger than that of low concentration of RCP4.5. The lower precipitation and the higher temperature are the main factors affecting the occurrence of drought. All three CMIP5 models show that precipitation would increase in the future, but it could not offset the evapotranspiration loss caused by significant temperature rise. The serious risk of drought in the future is still higher. Considering the uncertainty of climate models for simulation and prediction, attention should be paid to distinguish the effects of different models in the future drought assessment.

Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria

2016 ◽  
Vol 154 (7) ◽  
pp. 1153-1170 ◽  
Author(s):  
E. EBRAHIMI ◽  
A. M. MANSCHADI ◽  
R. W. NEUGSCHWANDTNER ◽  
J EITZINGER ◽  
S. THALER ◽  
...  
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Crop Management ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Management Scenarios ◽  
Global Circulation Models ◽  
Daily Weather Data ◽  
Eastern Austria ◽  
The Impact

SUMMARYClimate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.

scholarly journals Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use

2016 ◽  
Vol 34 (21) ◽  
pp. 2534-2540 ◽  
Author(s):  
Kathleen F. Kerr ◽  
Marshall D. Brown ◽  
Kehao Zhu ◽  
Holly Janes
Keyword(s):  
Prostate Cancer ◽  
Risk Prediction ◽  
Prediction Models ◽  
Risk Model ◽  
Characteristic Curve ◽  
Clinical Impact ◽  
Adjuvant Radiation ◽  
Risk Models ◽  
Personal Benefit ◽  
The Impact

The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man’s risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics.

scholarly journals Assessment of impact of climate change on water resources: a long term analysis of the Great Lakes of North America

2008 ◽  
Vol 12 (1) ◽  
pp. 239-255 ◽  
Author(s):  
E. McBean ◽  
H. Motiee
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Water Resources ◽  
North America ◽  
Great Lakes ◽  
Great Lakes Basin ◽  
Historical Trends ◽  
Global Circulation Models ◽  
The Impact

Abstract. In the threshold of the appearance of global warming from theory to reality, extensive research has focused on predicting the impact of potential climate change on water resources using results from Global Circulation Models (GCMs). This research carries this further by statistical analyses of long term meteorological and hydrological data. Seventy years of historical trends in precipitation, temperature, and streamflows in the Great Lakes of North America are developed using long term regression analyses and Mann-Kendall statistics. The results generated by the two statistical procedures are in agreement and demonstrate that many of these variables are experiencing statistically significant increases over a seven-decade period. The trend lines of streamflows in the three rivers of St. Clair, Niagara and St. Lawrence, and precipitation levels over four of the five Great Lakes, show statistically significant increases in flows and precipitation. Further, precipitation rates as predicted using fitted regression lines are compared with scenarios from GCMs and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are higher than GCM predictions for Lakes Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes particularly for the precipitation in the Great Lakes Basin may be demonstrating influences arising from global warming and climate change.

Sign in / Sign up

Export Citation Format

Share Document