scholarly journals Impacts of Future Climate Changes on Shifting Patterns of the Agro-Ecological Zones in China

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yingzhi Lin ◽  
Anping Liu ◽  
Enjun Ma ◽  
Fan Zhang
Keyword(s):  
Future Climate ◽  
Future Climate Change ◽  
Land Resource ◽  
International Institute ◽  
Climate Data ◽  
Mapping Unit ◽  
Processing Scheme ◽  
Ecological Zones ◽  
Food And Agriculture ◽  
Food And Agriculture Organization

An agroecological zone (AEZ) is a land resource mapping unit, defined in terms of climate, landform, and soils, and has a specific range of potentials and constraints for cropping (FAO, 1996). The shifting patterns of AEZs in China driven by future climatic changes were assessed by applying the agroecological zoning methodology proposed by International Institute for Applied Systems Analysis (IIASA) and Food and Agriculture Organization of the United Nations (FAO) in this study. A data processing scheme was proposed in this study to reduce systematic errors in projected climate data using observed data from meteorological stations. AEZs in China of each of the four periods: 2011–2020, 2021–2030, 2031–2040, and 2041–2050 were drawn. It is found that the future climate change will lead to significant local changes of AEZs in China and the overall pattern of AEZs in China is stable. The shifting patterns of AEZs will be characterized by northward expansion of humid AEZs to subhumid AEZs in south China, eastward expansion of arid AEZs to dry and moist semiarid AEZs in north China, and southward expansion of dry semiarid AEZs to arid AEZs in southwest China.

scholarly journals PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

Projected climate change impacts on tropical life zones in Costa Rica

2021 ◽  
pp. 030913332110470
Author(s):  
Christian Birkel ◽  
Joni Dehaspe ◽  
Andrés Chavarría-Palma ◽  
Nelson Venegas-Cordero ◽  
Rene Capell ◽  
...  
Keyword(s):  
Climate Change ◽  
Costa Rica ◽  
Costa Rican ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Biological Corridors ◽  
Ecosystem Indicators ◽  
Near Future

Efforts to protect tropical ecosystems aim at implementing biological corridors across the national territory of Costa Rica. However, potential near-future climate change challenges the effectiveness of such conservation measures. For this purpose, we developed near-future climate change scenarios at high spatial resolution using open-access global data from the Copernicus Climate Data Store (CDS). These projections resulted from downscaling (to a 1km2 national grid) and quantile-mapping bias-correction of the Essential Climate Variables Global Circulation Model (ECV_GCM) ensemble mean from the CDS using a moderate Representative Concentration Pathway 4.5 (RCP4.5). Projections were evaluated with limited local station data and applied to generate future ecosystem indicators (Holdridge Life Zones, HLZs). We show significantly increasing temperatures of 2.6°C with a spatial variability of ± 0.4°C for Costa Rica until 2040 with local differences (higher temperatures projected for the southern Costa Rican Caribbean). The future mean annual precipitation showed slightly wetter conditions (120 ± 43 mm/year) and most prominently in the Costa Rican Caribbean and south Pacific, but no significant drying in the north of Costa Rica by 2040. The bias-corrected climate data were aggregated to decadal and 30-year average (1971–2040) life zone ecosystem indicators that could potentially show ecosystem shifts. Changes in the life zones are most likely due to warmer temperatures and to a lesser extent caused by projected wetter conditions. Shifts are more likely to occur at higher elevations with a potential loss of the sub-tropical rainforest ecosystem. The projections support diminishing tropical dry forests and slightly increasing tropical rain and wet forests in the biological corridors of the driest and wettest regions, respectively. A countrywide spatial uniformity of dominating tropical moist forests (increase from 24% to 49%) at the expense of other HLZs was projected by 2040.

Climate change and its impact on tea in Northeast India

2014 ◽  
Vol 5 (4) ◽  
pp. 625-632 ◽  
Author(s):  
Rishiraj Dutta
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Northeast India ◽  
Future Climate ◽  
Future Climate Change ◽  
Monthly Precipitation ◽  
Productivity Analysis ◽  
Climate Data ◽  
Tea Production ◽  
Production Period

The analysis of this study focused on the tea growing areas of Northeast India to provide predictions for future climate scenarios and its impact on tea production by 2050. The applied methodology involves a combination of current climate data with future climate change predictions from different models for 2050 as derived by WorldClim and IPCC4 (CIAT recommended). The results showed the possibility of an increase in average temperature by 2 °C in 2050, while not much variation is observed in the rainfall pattern. A change in tea production period is also expected by 2050 making tea planters look for alternative crops as an adaptive measure to keep the industry on its feet. With such expected impacts on tea production, the planters would need to make changes in their management practices to adapt to the evolving conditions and environment. In this study, the climate data were used as input to DIVA GIS Model. Monthly climate data were fed into Cranfield University Plantation Productivity Analysis for Tea Model (CUPPA Tea Model) to simulate observed and predicted yields. The study further shows that the overall climate will become less seasonal in terms of variation through the years followed by expected variations in monthly precipitation during the peak production months.

scholarly journals PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment

2014 ◽  
Vol 7 (1) ◽  
pp. 433-451 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS (Planet Simulator coupled with the efficient numerical terrestrial scheme). Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and non-CO2 radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

scholarly journals Phylogeography and niche modelling: reciprocal enlightenment

Mammalia ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. 10-25 ◽  
Author(s):  
Govan Pahad ◽  
Claudine Montgelard ◽  
Bettine Jansen van Vuuren
Keyword(s):  
Climate Change ◽  
Genetic Diversity ◽  
Ecological Niche ◽  
Spatial Genetic Structure ◽  
Distribution Patterns ◽  
Future Climate ◽  
Future Climate Change ◽  
Environmental Niche ◽  
Climate Data ◽  
Niche Modelling

Abstract Phylogeography examines the spatial genetic structure of species. Environmental niche modelling (or ecological niche modelling; ENM) examines the environmental limits of a species’ ecological niche. These two fields have great potential to be used together. ENM can shed light on how phylogeographical patterns develop and help identify possible drivers of spatial structure that need to be further investigated. Specifically, ENM can be used to test for niche differentiation among clades, identify factors limiting individual clades and identify barriers and contact zones. It can also be used to test hypotheses regarding the effects of historical and future climate change on spatial genetic patterns by projecting niches using palaeoclimate or future climate data. Conversely, phylogeographical information can populate ENM with within-species genetic diversity. Where adaptive variation exists among clades within a species, modelling their niches separately can improve predictions of historical distribution patterns and future responses to climate change. Awareness of patterns of genetic diversity in niche modelling can also alert conservationists to the potential loss of genetically diverse areas in a species’ range. Here, we provide a simplistic overview of both fields, and focus on their potential for integration, encouraging researchers on both sides to take advantage of the opportunities available.

scholarly journals Warm climates of the past—a lesson for the future?

2013 ◽  
Vol 371 (2001) ◽  
pp. 20130146 ◽  
Author(s):  
D. J. Lunt ◽  
H. Elderfield ◽  
R. Pancost ◽  
A. Ridgwell ◽  
G. L. Foster ◽  
...  
Keyword(s):  
Climate Change ◽  
Numerical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Comprehensive Overview ◽  
Past Climate ◽  
The Past ◽  
The Future ◽  
Warm Climates

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

scholarly journals Soil Distribution in Nepal

NUTA Journal ◽  
2020 ◽  
Vol 7 (1-2) ◽  
pp. 79-89
Author(s):  
Sher Bahadur Gurung
Keyword(s):  
Climatic Factors ◽  
Soil Classification ◽  
The United States ◽  
Soil Types ◽  
Land Resource ◽  
Reference Base ◽  
Soil Map ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Glacier Ice

Soil is the important natural recourse for living things of the world and regulates its ecosystem. Soil types are depending on physiographic and climatic factors. The study discussed soil types of Nepal prepared by Land Resource Mapping Project (LRMP) based on world reference base developed by Food and Agriculture Organization of the United States  (FAO)  and Soil and Terrain (SOTER) soil type of Nepal by ISRIC-World soil Information based on universal soil classification system developed by United State Department of Agriculture (USDA)  using Geographic information system (GIS). According to LRMP the soil types of Nepal are as follow: Dystrochrepts Haplumbrepts Haplustalfs, Dystrochrepts Haplustalfs Rhodustalfs, Haplumbrepts Dystrochrepts Cryumbrepts, Udipsamments Dystrochrepts Rhodustalfs, Glaciated Mountain, Haplaquents Haplaqepts Eutrocrepts, Udorthents Ustorthents Haplaquents, Dystrochrepts Halpumbrepts Haplustalfs-calcarious Materials, Rhodustalfs Dystrochrepts Haplustalfs, Dystrochrepts Eutrochrepts Argiudolls, Dystrochrepts Hapludalfs Haplustalfs-Calcarious Materials, Haplaquents Psammaquents Ustorthents, Haplaquents Eutrocrepts Heplaquents-calcareous Materials and Haplaquepts Dystrochrepts Haplaquents covering four soil order i.e. Entisols, Inseptisols. Mollisols and Alfisols. According the SOTER map, the soil types are as follow: Gelic LEPTOSOLS, Eutric CAMBISOLS, Eutric REGOSOLS, Humic CAMBISOLS, Chromic CAMBISOLS, Dystric REGOSOLS, Eutric GLEYSOLS Calcaric, PHAEOZEMS, Gleyic CAMBISOLS, Haplic PHAEOZEMS, Calcaric FLUVISOLS and other are glacier, ice, rock croup, lake and water. These types of soils are controlled by physiography and climatic factors. The SOTER soil types are more familiar than LRMP soil map although in LRMP soil map is useful to understand the soil characteristics and soil forming processes of Nepal. The soil degradation mitigation and adaptive strategies should consider the soil diversity types and its controlling factors such as physiography and climate.

Sign in / Sign up

Export Citation Format

Share Document