scholarly journals Global distribution of soapberries (Sapindus L.) habitats under current and future climate scenarios

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiming Liu ◽  
Lianchun Wang ◽  
Caowen Sun ◽  
Benye Xi ◽  
Doudou Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Global Climate ◽  
Future Climate ◽  
Environmental Data ◽  
Climate Projections ◽  
Suitable Habitat ◽  
Maxent Model ◽  
Mean Temperature ◽  
Suitable Habitats ◽  
Large Scale Cultivation

AbstractSapindus (Sapindus L.) is a widely distributed economically important tree genus that provides biodiesel, biomedical and biochemical products. However, with climate change, deforestation, and economic development, the diversity of Sapindus germplasms may face the risk of destruction. Therefore, utilising historical environmental data and future climate projections from the BCC-CSM2-MR global climate database, we simulated the current and future global distributions of suitable habitats for Sapindus using a Maximum Entropy (MaxEnt) model. The estimated ecological thresholds for critical environmental factors were: a minimum temperature of 0–20 °C in the coldest month, soil moisture levels of 40–140 mm, a mean temperature of 2–25 °C in the driest quarter, a mean temperature of 19–28 °C in the wettest quarter, and a soil pH of 5.6–7.6. The total suitable habitat area was 6059.97 × 104 km2, which was unevenly distributed across six continents. As greenhouse gas emissions increased over time, the area of suitable habitats contracted in lower latitudes and expanded in higher latitudes. Consequently, surveys and conservation should be prioritised in southern hemisphere areas which are in danger of becoming unsuitable. In contrast, other areas in northern and central America, China, and India can be used for conservation and large-scale cultivation in the future.

scholarly journals Global distribution of Sapindus habitats under current and future climate change scenarios

2021 ◽  
Author(s):  
Jiming Liu ◽  
Lianchun Wang ◽  
Caowen Sun ◽  
Benye Xi ◽  
Doudou Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Future Climate ◽  
Environmental Data ◽  
Future Climate Change ◽  
Climate Projections ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Mean Temperature ◽  
Suitable Habitats

Abstract Sapindus (Sapindus L.) is a widely distributed economically important tree genus that provides biodiesel, biomedical and biochemical products. However, with climate change, deforestation, and economic development, Sapindus germplasm resources have been lost. Therefore, utilising historical environmental data and future climate projections from the BCC-CSM2-MR global climate database, we simulated the present and future global distributions of suitable habitats for Sapindus using a Maximum Entropy (MaxEnt) model. The estimated ecological thresholds for critical environmental factors were: a minimum temperature of 0–20°C in the coldest month, soil moisture levels of 40–140 mm, a mean temperature of 2–25°C in the driest quarter, a mean temperature of 19–28°C in the wettest quarter, and a soil pH of 5.6–7.6. The total suitable habitat area was 6059.97 × 104 km2, which was unevenly distributed across six continents. As greenhouse gas emissions increased over time, the area of suitable habitats contracted in lower latitudes and expanded in higher latitudes. Consequently, surveys and conservation should be prioritised in southern hemisphere areas which are in danger of becoming unsuitable. In contrast, other areas in northern and central America, China, and India can be used for conservation and large-scale cultivation in the future.

scholarly journals Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China

2019 ◽  
Vol 16 (17) ◽  
pp. 3185 ◽  
Author(s):  
Zhang ◽  
Jing ◽  
Li ◽  
Liu ◽  
Fang
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Economic Value ◽  
Distribution Data ◽  
Cinnamomum Camphora ◽  
Jackknife Test ◽  
Maxent Model ◽  
Resource Protection ◽  
Suitable Habitats ◽  
The Impact

Rapid changes in global climate exert tremendous pressure on forest ecosystems. Cinnamomum camphora (L.) Presl is a multi-functional tree species, and its distribution and growth are also affected by climate warming. In order to realize its economic value and ecological function, it is necessary to explore the impact of climate change on its suitable habitats under different scenarios. In this experiment, 181 geographical distribution data were collected, and the MaxEnt algorithm was used to predict the distribution of suitable habitats. To complete the simulation, we selected two greenhouse gas release scenarios, RCP4.5 and RCP8.5, and also three future time periods, 2025s, 2055s, and 2085s. The importance of environmental variables for modeling was evaluated by jackknife test. Our study found that accumulated temperature played a key role in the distribution of camphor trees. With the change of climate, the area of suitable range will increase and continue to move to the northwest of China. These findings could provide guidance for the plantation establishment and resource protection of camphor in China.

scholarly journals Downscale of future climate change scenarios applied to Recife-PE

2020 ◽  
Vol 9 (6) ◽  
pp. 361
Author(s):  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
Rodrigo Lins Da Rocha Júnior
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Future ◽  
Maximum Temperatures

The objective of this work was to analyze and compare results from two generations of global climate models (GCMs) simulations for the city of Recife-PE: CMIP3 and CMIP5. Differences and similarities in historical and future climate simulations are presented for four GCMs using CMIP3 scenarios A1B and A2 and for seven CMIP5 scenarios RCP4.5 and RCP8.5. The scale reduction technique applied to GCMs scenarios is statistical downscaling, employing the same set of large-scale atmospheric variables as predictors for both sets of scenarios, differing only in the type of reanalysis data used to characterize surface variables precipitation, maximum and minimum temperatures. For CMIP3 scenarios the simulated historical climate is 1961-1990 and CMIP5 is 1979-2000, and the validation period is ten years, 1991-2000 for CMIP3 and 2001-2010 for CMIP5. However, for both the future period analyzed is 2021-2050 and 2051-2080. Validation metrics indicated superior results from the historical simulations of CMIP5 over those of CMIP3 for precipitation and minimum and similar temperatures for maximum temperatures. For the future, both CMIP3 and CMIP5 scenarios indicate reduced precipitation and increased temperatures. The potencial evapotranspiration was calculated, projected to increase in scenarios A1B and A2 of CMIP3 and with behavior similar to that observed historically in scenarios RCP4.5 and 8.5.

Potential Distributions of the Invasive Barnacle Scale Ceroplastes cirripediformis (Hemiptera: Coccidae) Under Climate Change and Implications for Its Management

2020 ◽  
Author(s):  
Fang Wang ◽  
Duo Wang ◽  
Ge Guo ◽  
Meixia Zhang ◽  
Jiayi Lang ◽  
...  
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Insect Pest ◽  
Distribution Patterns ◽  
Scientific Basis ◽  
Future Climate ◽  
Suitable Habitat ◽  
Climate Scenarios ◽  
Global Risk ◽  
Mean Temperature

Abstract Ceroplastes cirripediformis Comstock is one of the most destructive invasive pests that have caused various negative impacts to agricultural, ornamental, and greenhouse plants. Since it is time- and labor-consuming to control C. cirripediformis, habitat evaluation of this pest may be the most cost-effective method for predicting its dispersal and avoiding its outbreaks. Here, we evaluated the effects of climatic variables on distribution patterns of C. cirripediformis and produced a global risk map for its outbreak under current and future climate scenarios using the Maximum Entropy (MaxEnt) model. Our results showed that mean temperature of driest quarter (Bio 9), precipitation of coldest quarter (Bio 19), precipitation of warmest quarter (Bio 18), and mean temperature of wettest quarter (Bio 8) were the main factors influencing the current modeled distribution of C. cirripediformis, respectively, contributing 41.9, 29.4, 18.8, and 7.9%. The models predicted that, globally, potential distribution of C. cirripediformis would be across most zoogeographical regions under both current and future climate scenarios. Moreover, in the future, both the total potential distribution region and its area of highly suitable habitat are expected to expand slightly in all representative concentration pathway scenarios. The information generated from this study will contribute to better identify the impacts of climate change upon C. cirripediformis’s potential distribution while also providing a scientific basis for forecasting insect pest spread and outbreaks. Furthermore, this study serves an early warning for the regions of potential distribution, predicted as highly suitable habitats for this pest, which could promote its prevention and control.

Pengembangan Nontransgenik F1 dan Bc1f1 Padi Ciherang Toleran Genangan secara Site-Directed Crossing

2014 ◽  
Vol 1 (3) ◽  
pp. 136-145
Author(s):  
Djarot Sasongko Hami Seno ◽  
Satya Nugroho ◽  
Tri Joko Santoso ◽  
Joel Rivandi Sinaga ◽  
Euis Marlina ◽  
...  
Keyword(s):  
Large Scale ◽  
Agronomic Traits ◽  
Global Climate ◽  
Rice Variety ◽  
Submergence Tolerance ◽  
Rice Varieties ◽  
Global Climate Changes ◽  
Tolerance Gene ◽  
The Stability ◽  
Large Scale Cultivation

The development of submergence tolerant rice varieties is urgently required to maintain the stability of future food production, to anticipate the unpredictable global climate changes. Due to in-economical agronomic traits of native submergence tolerant varieties for large scale cultivation, submergence tolerance gene (sub1) must be introduced into popular high-yielding rice variety, such as Ciherang. To develop new submergence tolerant variety with good agronomic traits as those of Ciherang, in this research, submergence tolerance gene (sub1) was introduced into Ciherang variety. To avoid strict GMO regulation, gene introduction was carried out through site-directed crossing. Donor sub1 was crossed with Ciherang host. The selected F1 progenies were further backcrossed to Ciherang 4 x to obtain BC5F1 progeny having ~98% agronomic traits of those of Ciherang. In every cross/backcross generation, submergence test was performed, followed by sub1 marker-assisted PCR. F1 and BC1F1 submergence-tolerant Ciherang were successfully constructed. Co-dominant RM464A marker was not able to discriminate between host, donor, and progenies (F1 and BC1). Co-dominant RM219 maker showed slightly different size between donor and host amplicon, but it was difficult to see their heterozygous progenies. Both C173 and AEX1 dominant markers were able to show sub1 introgression from donor to host. PCR results confirmed that progenies-submergence tolerance was due to sub1 introgression, not escape mechanisms. AEX1 was chosen for subsequent experiments. Backcross until BC5 is in progress, to obtain maximum host retention for engineering new submergence tolerant varieties with good agronomic traits as those of Ciherang.

UK Climate Projections 2018 (UKCP18): progress towards more information on future weather

2020 ◽  
Author(s):  
David Sexton ◽  
Jason Lowe ◽  
James Murphy ◽  
Glen Harris ◽  
Elizabeth Kendon ◽  
...  
Keyword(s):  
Large Scale ◽  
Future Climate ◽  
Maximum Temperature ◽  
Cmip5 Models ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Projections ◽  
Circulation Index ◽  
Large Contribution ◽  
Probabilistic Projections

<p>UK Climate Projections 2018 (UKCP18) included land and marine projections and were published in 2018 to replace UKCP09. The land projections had three components, and all were designed to provide more information on future weather compared to UKCP09. The first component updated the UKCP09 probabilistic projections by including newer CMIP5 data and focussing on seasonal means from individual years rather than 30-year averages. The probabilistic projections represent the wider uncertainty. The second two components (global and regional projections) both had the aim of providing plausible examples of future climate, but at different resolutions.</p><p>The global projections were a combination of 13 CMIP5 models and a 15-member perturbed parameter ensemble (PPE) of coupled simulations for 1900-2100 using CMIP5 RCP8.5 from 2005 onwards. The PPE was provided at 60km atmosphere, quarter degree ocean and the large-scale conditions from twelve of the members were used to drive the regional model at both 12km and 2.2km resolution. These plausible examples are more useful for providing information about weather in a future climate to support a storyline approach for decision making.</p><p>The talk will present examples of new ways to use UKCP18 compared to UKCP09.  We will show how the global projections can be used to understand that the recent record winter daily maximum temperature in the UK in 2019 had a large contribution from internal variability and what this means for breaking the record in a warming climate. We also use an example from China to demonstrate one way to exploit information at different time scales, looking at how a circulation index, which is predictable and related to tropical cyclone landfall, changes in a future climate.</p><p>Finally, we show that while the enhanced resolution of the global and regional projections has improved our capability to provide climate information linked to the better representation of circulation, they lack diversity in some of the key drivers of future climate. Therefore, a key way forward will be to find an appropriate balance between the need for better diversity (e.g. multiple ensembles such as CMIP or PPEs) and the need for an appropriate resolution to retain this new capability.</p>

Maxent modelling for predicting climate change effects on the potential planting area of tuber mustard in China

2019 ◽  
Vol 157 (5) ◽  
pp. 375-381 ◽  
Author(s):  
H. Q. Li ◽  
X. H. Liu ◽  
J. H. Wang ◽  
L.G. Xing ◽  
Y. Y. Fu
Keyword(s):  
Suitable Habitat ◽  
Maxent Model ◽  
Climate Change Effects ◽  
Mean Temperature ◽  
Chongqing City ◽  
Diurnal Range ◽  
Maxent Modelling ◽  
Shanghai City ◽  
Tuber Mustard ◽  
Model Training

AbstractPotential planting area for tuber mustard was simulated using the Maxent model under current and future conditions based on 591 coordinates and 22 environmental layers. Model accuracy was excellent, with area under the receiving operator curve values of 0.967 and 0.958 for model training and testing, respectively. Dominant factors were mean diurnal range, mean temperature of the coldest quarter, annual mean temperature and minimum temperature of the coldest month, with thresholds of 6.5–7.5, 5.5–9, 16–19 and 2.0–6.5 °C, respectively. Under current conditions, suitable habitat areas (2.16% of total land in China) were concentrated mainly in Central, Southwest and East China, which can be defined as three occurrence and diffusion centres. In the 2050s and 2070s, suitable habitat areas are predicted to change to 3.72 and 3.92%, and 3.60 and 3.73% under scenarios RCP4.5 and RCP6.0, respectively, indicating that suitable habitat areas will increase slightly. However, future distribution of tuber mustard was predicted to differ among provinces or cities, i.e. predicted suitable habitat areas in Sichuan Province increased up to the 2050s but remained relatively unchanged between the 2050s and 2070s; in Chongqing city they first increased and then decreased; in Hunan, Anhui, Jiangsu, Zhejiang and Fujian Provinces they increased continuously; and in Guizhou, Hubei, Jiangxi Provinces and Shanghai city they first decreased, and then increased. The results from the current study provide useful information for management decisions of tuber mustard.

scholarly journals Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics

2016 ◽  
Vol 29 (2) ◽  
pp. 543-560 ◽  
Author(s):  
Ming Zhao ◽  
J.-C. Golaz ◽  
I. M. Held ◽  
V. Ramaswamy ◽  
S.-J. Lin ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Convective Precipitation ◽  
Climate Projections ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Convection Parameterization ◽  
Comparable Quality

Abstract Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the intermodel spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, the authors use a developmental version of the next-generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the model ensemble from phase 5 of CMIP (CMIP5). The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere–land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.

scholarly journals Future Projection of Mean Temperature of Post-Monsoon Season Over Bangladesh Using Statistical Downscaling of Global Climate Models

2020 ◽  
Vol 11 (2) ◽  
pp. 27-35
Author(s):  
Md Bazlur Rashid ◽  
Syed Shahadat Hossain
Keyword(s):  
Statistical Downscaling ◽  
Climate Models ◽  
Monsoon Season ◽  
Future Climate ◽  
Climate Projections ◽  
Post Monsoon ◽  
Mean Temperature ◽  
Post Monsoon Season ◽  
Near Future ◽  
Far Future

In statistical downscaling technique, regional or local information are derived by determining a statistical model which relates large-scale climate variables or predictors generated by Global Climate Models (GCMs) to regional and local variables or predictands. In this paper, the results of GCMs were statistically downscaled to produce future climate projections of mean temperature in the post-monsoon season (October and November), for the time periods 2021-2050 and 2071-2100 for Bangladesh. The future climate projections are based on the three emission scenarios RCP2.6, RCP4.5 and RCP8.5 provided by the fifth Coupled Model Intercomparison Project (CMIP5). This paper established a method to analyze GCMs for use in statistical downscaling and utilized fifteen GCMs. The GCMs were assessed based upon their performance in simulated past climate in Bangladesh and adjoining areas. Downscaling was undertaken by linking large scale climate variables, taken from the ERA-Interim (resolution 79 km) reanalysis temperature, a gridded data set incorporating observations and climate models, to local scale observations. Overall, all fifteen GCMs, via statistical downscaling, show that mean temperature of the post-monsoon season in Bangladesh will increase under future climate scenarios. Comparing the ensemble of future projections with the reference period (1981- 2010), the mean post-monsoon temperature in Bangladesh is projected for RCP8.5 showing warming by 0.310C in near future and 1.790C in far future. On the other hand, estimated warming is 0.390C in near future and 1.140C is far future for RCP4.5. Low emission scenarios RCP2.6, near future temperature is nearly same the far future temperature. Journal of Engineering Science 11(2), 2020, 27-35

scholarly journals Potential Suitable Habitat of Two Economically Important Forest Trees (Acer truncatum and Xanthoceras sorbifolium) in East Asia under Current and Future Climate Scenarios

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1263
Author(s):  
Yaoxing Wu ◽  
Yong Yang ◽  
Chen Liu ◽  
Yixuan Hou ◽  
Suzhi Yang ◽  
...  
Keyword(s):  
East Asia ◽  
Loess Plateau ◽  
Inner Mongolia ◽  
Future Climate ◽  
Suitable Habitat ◽  
Forest Trees ◽  
Climate Scenarios ◽  
Xanthoceras Sorbifolium ◽  
Suitable Habitats ◽  
Inner Mongolia Plateau

Acer truncatum Bunge and Xanthoceras sorbifolium Bunge are small deciduous trees distributed in East Asia and have high ecological and nutrient value due to their strong environmental adaptability and seed oil abundant in nervonic acid and unsaturated fatty acids. However, their natural distribution remains unclear, which will also be affected by the changing climatic conditions. The main purpose of this study was to map and predict the current and future potential suitable habitats of these two species using MaxEnt based on the presence location of species and environmental variables. The results showed that A. truncatum was more suitable for warm and humid climates and was more durable to climate change compared to X. sorbifolium. Under the current environmental conditions, the suitable habitat of A. truncatum was mainly concentrated in Inner Mongolia Plateau, Loess Plateau, Sichuan Basin, Northeast Plain, North China Plain, Korean Peninsula, as well as Japan, with an area of 115.39 × 104 km2. X. sorbifolium was mainly distributed in Inner Mongolia Plateau and Loess Plateau with an area of 146.15 × 104 km2. Under future climate scenarios, the model predicted that higher concentrations of greenhouse gas emissions could result in greater expansion of the potential distribution of both species. Meanwhile, the study also revealed that the two species migrated to the north by east to varying degrees with the change in suitable habitats. This work could provide scientific basis for resource protection and utilization of the two economic forest trees.

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