scholarly journals Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 460
Author(s):  
Amna M. Al Ruheili ◽  
Alaba Boluwade ◽  
Ali M. Al Subhi
Keyword(s):  
Climate Change ◽  
Arable Land ◽  
Geographical Information ◽  
Climate Change Scenarios ◽  
Entropy Model ◽  
Bioclimatic Variables ◽  
Entire Country ◽  
Climatic Scenarios ◽  
Broom Disease ◽  
The Impact

Witches’ broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches’ broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift in the climatic niche of the distribution of the disease across the different geographical areas of the entire country (309,501 km²). The maximum entropy model (MaxEnt) and geographical information system were used to investigate the potential suitability of habitats for the phytoplasma disease. This study used current (1970–2000) and future projected climatic scenarios (2021–2040, 2041–2060, 2061–2080, and 2081–2100) to model the distribution of phytoplasma for lime trees and alfalfa in Oman. Bioclimatic variables were downloaded from WorldClim with ± 60 occurrence points for lime trees and alfalfa. The area under the curve (AUC) was used to evaluate the model’s performance. Quantitatively, the results showed that the mean of the AUC values for lime (16SrII-B) and alfalfa (16SrII-D) future distribution for the periods of 2021–2040, 2041–2060, 2061–2080, and 2081–2100 were rated as “excellent”, with the values for the specified time periods being 0.859, 0.900, 0.931, and 0.913 for 16SrII-B; and 0.826, 0.837, 08.58, and 0.894 for 16SrII-D respectively. In addition, this study identified the hotspots and proportions of the areas that are vulnerable under the projected climate-change scenarios. The area of current (2021–2040) highly suitable distribution within the entire country for 16SrII-D was 19474.2 km2 (7.1%), while for 16SrII-B, an area of 8835 km2 (3.2%) was also highly suitable for the disease distribution. The proportions of these suitable areas are very significant from the available arable land standpoint. Therefore, the results from this study will be of immense benefit and will also bring significant contributions in mapping the areas of witches’ broom diseases in Oman. The results will equally aid the development of new strategies and the formulation of agricultural policies and practices in controlling the spread of the disease across Oman.

Estimating the impact of climate change on the occurrence of selected pests at a high spatial resolution: a novel approach

2011 ◽  
Vol 149 (2) ◽  
pp. 185-195 ◽  
Author(s):  
E. KOCMÁNKOVÁ ◽  
M. TRNKA ◽  
J. EITZINGER ◽  
M. DUBROVSKÝ ◽  
P. ŠTĚPÁNEK ◽  
...  
Keyword(s):  
Climate Change ◽  
Colorado Potato Beetle ◽  
European Corn Borer ◽  
Arable Land ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Pest Species ◽  
Corn Borer ◽  
Potato Beetle ◽  
The Impact

SUMMARYThe present study is focused on the potential occurrence of the Colorado potato beetle (Leptinotarsa decemlineata, Say 1824), an important potato pest, and the European corn borer (Ostrinia nubilalis, Hübner 1796), the most important maize pest, during climate change. Estimates of the current potential distribution of both pest species as well as their distribution in the expected climate conditions are based on the CLIMEX model. The study covers central Europe, including Austria, the Czech Republic, Hungary, and parts of Germany, Poland, Romania, Slovakia, Switzerland, Ukraine, Slovenia, the northern parts of Serbia, parts of Croatia and northern Italy. The validated model of the pests’ geographical distribution was applied within the domain of the regional climate model (RCM) ALADIN, at a resolution of 10 km. The weather series that was the input for the CLIMEX model was prepared by a weather generator (WG) which was calibrated with the RCM-simulated weather series (for the period of 1961–90). To generate a weather series for two future time periods (2021–50 and 2071–2100), the WG parameters were modified according to 12 climate change scenarios produced by the pattern scaling method. The standardized scenarios derived from three global climate models (HadCM, NCAR-PCM and ECHAM) were scaled by low, middle and high values of global temperature change estimated by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) model (assuming three combinations of climatic sensitivity and emission scenarios). The results of present study suggest the likely widening of the pests’ habitats and an increase in the number of generations per year. According to the HadCM-high scenario, the area of arable land affected by a third generation per season of Colorado potato beetle in 2050 is c. 45% higher, and by a second generation of the European corn borer is nearly 61% higher, compared to present levels.

scholarly journals Modeling the Potential Distribution of Three Taxa of Akebia Decne. under Climate Change Scenarios in China

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1710
Author(s):  
Xiuting Wang ◽  
Wenwen Zhang ◽  
Xin Zhao ◽  
Huiqin Zhu ◽  
Limiao Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Potential Distribution ◽  
Habitat Destruction ◽  
Climate Change Scenarios ◽  
Sustainable Utilization ◽  
Entropy Model ◽  
Climate Conditions ◽  
Diurnal Range ◽  
The Impact

Akebia trifoliata (Thunb.) Koidz., Akebia trifoliata subsp. australis (Diels) T. Shimizu and Akebia quinata (Houtt.) Decne. are the source plants of the traditional Chinese medicines AKEBIAE CAULIS and AKEBIAE FRUCTUS, and have high pharmaceutical value. However, the resource reserve of these plants has dramatically declined due to habitat destruction, which has seriously affected their adequate supply and sustainable utilization. A poor knowledge of the potential distribution of these medicinal materials would seriously constrain the protective exploitation of wild resources and the establishment of new cultivations. In this study, based on the scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, the maximum entropy model was used to predict the potential distribution of these three Akebia taxa under current and future (2030s, 2050s, 2070s and 2090s) climate conditions. Our findings showed that the potentially suitable areas of these three Akebia taxa were mainly distributed in China at 101.8–121.9° E and 23.5–34.6° N. Temperature played a more significant role than precipitation in affecting the distribution. The dominant bioclimatic variable that affected the distribution of A. trifoliata and A. quinata in China was the minimum temperature of the coldest month (BIO06). For A. trifoliata subsp. australis, the mean diurnal range (BIO02) was the dominant variable influencing its distribution. Compared with current conditions, the moderate- and high-suitability areas of these three Akebia taxa were predicted to shrink towards the core areas, while the low-suitability areas were all observed to increase from the 2030s to the 2090s. With the increase in radiative forcing of SSP, the low-impact areas of these three Akebia taxa showed a decreasing trend as a whole. Our results illustrate the impact of climate change on the distribution of Akebia, and would provide references for the sustainable utilization of Akebia’s resources.

scholarly journals Algerian Inuleae tribe species distribution modeling underinfluence of current and future climate conditions

2020 ◽  
Vol 57 (1) ◽  
pp. 23-31
Author(s):  
Djilali Tahri ◽  
Fatiha Elhouiti ◽  
Mohamed Ouinten ◽  
Mohamed Yousfi
Keyword(s):  
Predictive Power ◽  
Species Distribution Modeling ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Climatic Zones ◽  
Climate Conditions ◽  
Mean Values ◽  
Bioclimatic Variables ◽  
Climatic Scenarios ◽  
The Impact

AbstractThis study aims to predict the impact of bioclimatic variables in current and future climatic scenarios on the distribution of Inuleae tribe species. Modeling the distribution of 30 species of the Inuleae tribe in Algeria was carried out with a maximum entropy model. Two models with 99 occurrence points were obtained with mean values of Area Under a Curve (AUC) of 0.987±0.01 and 0.971±0.02, reflecting excellent predictive power. Three bioclimatic variables contributed mainly to the first model and four - to the second one with cumulative contributions of 83.8% and 79%, respectively elucidating differences between species of the two major climatic zones in Algeria: the Tell and the Sahara. Two-dimensional niches of Algerian Inuleae species allowed to distinguish these two groups with the distribution of 18 Tell species, characterized by high rainfall (14-18°C, 400-1000 mm) and the other 12 species – distributed in hot and dry environments (17-24°C, 20-200 mm). Modeling the distribution under future conditions showed that habitats of the Saharan region would be much less suitable for these species with a variation in the annual mean temperature increase up to 20% and a decrease in annual precipitation, which could raise to 11 and 15%.

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

2015 ◽  
Vol 154 (5) ◽  
pp. 765-781 ◽  
Author(s):  
P. PHELAN ◽  
E. R. MORGAN ◽  
H. ROSE ◽  
J. GRANT ◽  
P. O'KIELY
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Season Length ◽  
The West ◽  
Grazing Season ◽  
North East ◽  
Bioclimatic Variables ◽  
The Impact

SUMMARYGrazing season length (GSL) on grassland farms with ruminant production systems can influence farm economics, livestock disease transmission, environmental impact, milk and meat quality, and consumer choice. Bioclimatic variables are biologically meaningful climate variables that may enable predictions of the impact of future climate change on GSL on European farms. The present study investigated the spatial relationship between current GSL (months) measured by EUROSTAT on dairy, beef and sheep farms in 706, 774 and 878 regions, respectively, and bioclimatic variables. A stepwise multiple regression model revealed a highly significant association between observed GSL and bioclimatic variables across Europe. Mean GSL was positively associated with the mean temperature of the coldest quarter and isothermality, and negatively associated with precipitation in the wettest month. Extrapolating these relationships to future climate change scenarios, most European countries were predicted to have a net increase in GSL with the increase being largest (up to 2·5 months) in the north-east of Europe. However, there were also predictions of increased variability between regions and decreases in GSL of up to 1·5 months in some areas such as the west of France, the south-west of Norway and the west coast of Britain. The study quantified and mapped the potential impact of climate change on GSL for dairy, beef and sheep farms across Europe.

scholarly journals Predicting Mango Sudden Decline Due to Ceratocystis fimbriata Under a Changing Climate

2021 ◽  
Vol 39 (3) ◽  
pp. 215-223
Author(s):  
Amna M. Al-Ruheili ◽  
◽  
Alaba Boluwade ◽  
Ali M. Al-Subhi ◽  
◽  
...  
Keyword(s):  
Climate Change ◽  
Fruit Trees ◽  
Climate Change Scenarios ◽  
Ceratocystis Fimbriata ◽  
Jackknife Test ◽  
Maxent Model ◽  
Diurnal Range ◽  
Bioclimatic Variables ◽  
Climatic Scenarios ◽  
Suitable Area

Mango fruit trees are an important fruit crop due to their high value. Mango sudden decline (MSD) is a major disease that threatens mango trees in Oman and worldwide. The objective of this study was to identify those areas in northern Oman in which Ceratocystis fimbriata (a plant fungal pathogen causing MSD) may establish itself under various climate change scenarios. The MaxEnt model used in this study was based on data for the period 1970-2000 and then projected to future climate periods. This study modeled the future distribution of C. fimbriata for 2021–2040, 2041–2060, 2061–2080, and 2081–2100 climatic scenarios. Fifteen affected locations and seven bioclimatic variables were investigated in this study. The model showed values between 0.896 and 0.913 (habitat suitability) which represented a good model outcome. The jackknife test showed that the mean diurnal range in temperature, precipitation of the driest month, and elevation contributed to C. fimbriata distribution. From 2021 through 2040, a total area of 1,889 km2 was found to be highly suitable for C. fimbriata in Northern Oman. Compared with the 2021–2040 period, the poorly suitable area would increase in both 2041–2060 and 2081–2100 periods. The moderately suitable regions for C. fimbriata would decrease under all scenarios investigated. However, the total area of the suitable areas, with all scenarios, would increase, except during the 2041-2060 period. This research offers a tool to better manage and prevent the possible Ceratocystis blight (C. fimbriata) and bark beetle (Hypocryphalus mangiferae) invasions under future projected climatic scenarios. Keywords: Mango sudden decline (MSD), “Ceratocystis fimbriata”, bioclimatic variables, climate change, Sultanate of Oman, Maxent.

scholarly journals Predicting the current and future distribution of four original plants of Gentianae Macrophyllae Radix in China under climate change scenarios

2021 ◽  
Author(s):  
Houkang Cao ◽  
Xiaohui Ma ◽  
Li Liu ◽  
Shaoyang Xi ◽  
Yanxiu Guo ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Future Climate ◽  
Climate Change Scenarios ◽  
Climate Scenarios ◽  
Distribution Models ◽  
Bioclimatic Variables ◽  
Gentiana Macrophylla ◽  
Suitable Habitats ◽  
The Impact

AbstractThe wild resources of the four original plants (Gentiana crasicaulis Duthie ex Burk, Gentiana daurica Fisch, Gentiana straminea Maxim, and Gentiana macrophylla Pall) of Gentianae Macrophyllae Radix are becoming exhausted. Predicting the distribution under current and future climate scenarios is of significance for the sustainable utilization of resources and ecological protection. In this study, we constructed four species distribution models (SDMs) combining species distribution informations, 19 bioclimatic variables, and the maximum entropy (MaxEnt) model. The results showed that these 4 plants prefer a cool and humid climate. Under the future climate scenarios, the areas of the highly suitable habitats for Gentiana crasicaulis Duthie ex Burk and Gentiana daurica Fisch were likely to decrease, while Gentiana straminea Maxim was likely to expand, and Gentiana macrophylla Pall was less affected. In addition, the centroids of the highly suitable habitats for the four species shifted north or west. Most notably, most of the highly suitable habitats for the four species remained unchanged, which would be the preferred area for semi-artificial cultivation. The above information in this study would contribute to the development of reasonable strategies to reduce the impact of climate change on the four original plants.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Urban Geometry Optimization to Mitigate Climate Change: Towards Energy-Efficient Buildings

2020 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Hatem Mahmoud ◽  
Ayman Ragab
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Thermal Efficiency ◽  
Energy Demand ◽  
Building Blocks ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Urban Geometry ◽  
Outdoor Spaces ◽  
The Impact

The density of building blocks and insufficient greenery in cities tend to contribute dramatically not only to increased heat stress in the built environment but also to higher energy demand for cooling. Urban planners should, therefore, be conscious of their responsibility to reduce energy usage of buildings along with improving outdoor thermal efficiency. This study examines the impact of numerous proposed urban geometry cases on the thermal efficiency of outer spaces as well as the energy consumption of adjacent buildings under various climate change scenarios as representative concentration pathways (RCP) 4.5 and 8.5 climate projections for New Aswan city in 2035. The investigation was performed at one of the most underutilized outdoor spaces on the new campus of Aswan University in New Aswan city. The potential reduction of heat stress was investigated so as to improve the thermal comfort of the investigated outdoor spaces, as well as energy savings based on the proposed strategies. Accordingly, the most appropriate scenario to be adopted to cope with the inevitable climate change was identified. The proposed scenarios were divided into four categories of parameters. In the first category, shelters partially (25–50% and 75%) covering the streets were used. The second category proposed dividing the space parallel or perpendicular to the existing buildings. The third category was a hybrid scenario of the first and second categories. In the fourth category, a green cover of grass was added. A coupling evaluation was applied utilizing ENVI-met v4.2 and Design-Builder v4.5 to measure and improve the thermal efficiency of the outdoor space and reduce the cooling energy. The results demonstrated that it is better to cover outdoor spaces with 50% of the overall area than transform outdoor spaces into canyons.

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

scholarly journals Impact of an accelerated melting of Greenland on malaria distribution over Africa

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alizée Chemison ◽  
Gilles Ramstein ◽  
Adrian M. Tompkins ◽  
Dimitri Defrance ◽  
Guigone Camus ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Ice Sheet ◽  
Transmission Risk ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Climate Change Risk ◽  
System A ◽  
Climate Simulations ◽  
The Impact

AbstractStudies about the impact of future climate change on diseases have mostly focused on standard Representative Concentration Pathway climate change scenarios. These scenarios do not account for the non-linear dynamics of the climate system. A rapid ice-sheet melting could occur, impacting climate and consequently societies. Here, we investigate the additional impact of a rapid ice-sheet melting of Greenland on climate and malaria transmission in Africa using several malaria models driven by Institute Pierre Simon Laplace climate simulations. Results reveal that our melting scenario could moderate the simulated increase in malaria risk over East Africa, due to cooling and drying effects, cause a largest decrease in malaria transmission risk over West Africa and drive malaria emergence in southern Africa associated with a significant southward shift of the African rain-belt. We argue that the effect of such ice-sheet melting should be investigated further in future public health and agriculture climate change risk assessments.

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