Climate Change and the Future of Himalayan Farming

2017 ◽  
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Farming Systems ◽  
Management Science ◽  
Future Climate ◽  
Climate Projections ◽  
Farming Practices ◽  
The West ◽  
Farming Communities ◽  
Production Conditions

The book asks to what extent Himalayan farmers and their institutions are prepared to face a future when external production conditions change. Because farming is particularly sensitive to climate, the main aim here is to relate present farming practices to projected future climate changes. Intensive, coordinated studies of six farming communities along the Himalayan range, from China in the east to Pakistan in the west, focus on their potentiality to adapt to climate changes that are projected for 2030, 2050, and 2100. But since climate projections are just projections, and since the context of farming is wider than just climate, the book also asks about farmers’ capacity to adapt to uncertainty in general. For that purpose, theories of ‘flexibility’ that have been applied in ecology, economics, and management science are accommodated to the present topic of farming systems. The assertion is that farmers and farming systems that are flexible are best prepared to face a future of climate change and other uncertainties.

scholarly journals Mapping current and potential future distributions of the oak tree (Quercus aegilops) in the Kurdistan Region, Iraq

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Climate Changes ◽  
Future Climate ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Kurdistan Region ◽  
Oak Tree

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.

Realised added value in dynamical downscaling of Australian climate change

2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate ◽  
Added Value ◽  
Climate Projections ◽  
Eastern Australia ◽  
Australian Alps ◽  
Future Climate Projections

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>

scholarly journals Including Variability across Climate Change Projections in Assessing Impacts on Water Resources in an Intensively Managed Landscape

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 286
Author(s):  
Bangshuai Han ◽  
Shawn G. Benner ◽  
Alejandro N. Flores
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Coupled Processes ◽  
Future Climate Change ◽  
Irrigated Agriculture ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Irrigation Amount ◽  
Stochastic Weather Generator ◽  
Intensively Managed

：In intensively managed watersheds, water scarcity is a product of interactions between complex biophysical processes and human activities. Understanding how intensively managed watersheds respond to climate change requires modeling these coupled processes. One challenge in assessing the response of these watersheds to climate change lies in adequately capturing the trends and variability of future climates. Here we combine a stochastic weather generator together with future projections of climate change to efficiently create a large ensemble of daily weather for three climate scenarios, reflecting recent past and two future climate scenarios. With a previously developed model that captures rainfall-runoff processes and the redistribution of water according to declared water rights, we use these large ensembles to evaluate how future climate change may impact satisfied and unsatisfied irrigation throughout the study area, the Treasure Valley in Southwest Idaho, USA. The numerical experiments quantify the changing rate of allocated and unsatisfied irrigation amount and reveal that the projected temperature increase more significantly influences allocated and unsatisfied irrigation amounts than precipitation changes. The scenarios identify spatially distinct regions in the study area that are at greater risk of the occurrence of unsatisfied irrigation. This study demonstrates how combining stochastic weather generators and future climate projections can support efforts to assess future risks of negative water resource outcomes. It also allows identification of regions in the study area that may be less suitable for irrigated agriculture in future decades, potentially benefiting planners and managers.

scholarly journals Bias correction and post-processing under climate change

2011 ◽  
Vol 18 (6) ◽  
pp. 911-924 ◽  
Author(s):  
S. Vannitsem
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
General Circulation ◽  
Climate Changes ◽  
Climate Projections ◽  
Model Errors ◽  
Post Processing ◽  
Straightforward Application ◽  
Potential Impact ◽  
Temperature Climate

Abstract. The statistical and dynamical properties of bias correction and linear post-processing are investigated when the system under interest is affected by model errors and is experiencing parameter modifications, mimicking the potential impact of climate change. The analysis is first performed for simple typical scalar systems, an Ornstein-Uhlenbeck process (O-U) and a limit point bifurcation. It reveals system's specific (linear or non-linear) dependences of biases and post-processing corrections as a function of parameter modifications. A more realistic system is then investigated, a low-order model of moist general circulation, incorporating several processes of high relevance in the climate dynamics (radiative effects, cloud feedbacks...), but still sufficiently simple to allow for an extensive exploration of its dynamics. In this context, bias or post-processing corrections also display complicate variations when the system experiences temperature climate changes up to a few degrees. This precludes a straightforward application of these corrections from one system's state to another (as usually adopted for climate projections), and increases further the uncertainty in evaluating the amplitudes of climate changes.

scholarly journals Energy and indoor thermal comfort performance of a Swedish residential building under future climate change conditions

2020 ◽  
Vol 172 ◽  
pp. 02001
Author(s):  
Ambrose Dodoo
Keyword(s):  
Climate Change ◽  
Thermal Comfort ◽  
Residential Building ◽  
Adaptation Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Projections ◽  
Mean Annual Temperature ◽  
Indoor Thermal Comfort ◽  
Recent Climate

The latest climate change projections for Sweden suggest mean annual temperature increase of up to 5.5 °C by 2100, compared to 1961-1990 levels. In this study we investigate the potential impacts of climate change on the energy demand for space conditioning, overheating risk and indoor thermal comfort of a modern multi-storey residential building in Sweden. We explore climate change adaptation strategies to improve the building’s performance under the climate change conditions, including increased ventilation, solar shading, improved windows and mechanical cooling. The building is analysed under future climate projections for the 2050-2059 time frame, with representative concentration pathway (RCP) 2.6, 4.5 and 8.5 scenarios. The building’s performances under these future climates are compared to those under the historical climate of 1961-1990 and recent climate of 1981-2010. The results suggest that climate change will significantly influence energy performance and indoor comfort conditions of buildings in the Swedish context. Overheating hours and Predicted Percentage of Dissatisfied (PPD) increased significantly under the future climate scenarios. Furthermore space heating demand is reduced and cooling demand is increased for the studied building. However, effective adaptation strategies significantly improved the buildings’ energy and indoor climate performances under both current and future climate conditions.

scholarly journals A comparison between direct and indirect frameworks to evaluate impacts of climate change on streamflows: case study of Karkheh River basin in Iran

2017 ◽  
Vol 8 (4) ◽  
pp. 652-674 ◽  
Author(s):  
Mohsen Nasseri ◽  
Banafsheh Zahraie ◽  
Leila Forouhar
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Hydrological Modeling ◽  
Future Climate ◽  
Multivariate Adaptive Regression Splines ◽  
Group Method ◽  
Climate Projections ◽  
Climate Conditions ◽  
Karkheh River Basin ◽  
Impacts Of Climate Change

Abstract In this paper, two approaches to assess the impacts of climate change on streamflows have been used. In the first approach (direct), a statistical downscaling technique was utilized to predict future streamflows based on large-scale data of general circulation models (GCMs). In the second approach (indirect), GCM outputs were downscaled to produce local climate conditions which were then used as inputs to a hydrological simulation model. In this article, some data-mining methods such as model-tree, multivariate adaptive regression splines and group method of data handling were utilized for direct downscaling of streamflows. Projections of HadCM3 model for A2 and B2 SRES scenarios were also used to simulate future climate conditions. These evaluations were done over three sub-basins of Karkheh River basin in southwest Iran. To achieve a comprehensive assessment, a global uncertainty assessment method was used to evaluate the results of the models. The results indicated that despite simplifications included in the direct downscaling, this approach is accurate enough to be used for assessing climate change impacts on streamflows without computational efforts of hydrological modeling. Furthermore, comparing future climate projections, the uncertainty associated with elimination of hydrological modeling is estimated to be high.

scholarly journals Revisit to Policy Formulation for Climate-Smart Agriculture in India

2019 ◽  
Vol 8 (9S2) ◽  
pp. 109-116
Keyword(s):  
Climate Change ◽  
Supply Chain ◽  
Food Security ◽  
Agricultural Production ◽  
Climate Changes ◽  
Agricultural Productivity ◽  
Small Scale ◽  
Farming Practices ◽  
Economic Implications ◽  
The Impact

Potential influence of water stress, climate change, erosion of fertility, unorganized agro-financing practices in agricultural-yields espoused with incongruity in regulating and developing the credible distribution mechanism for the resilience of computable equilibrium in the supply chain have warranted the continuing negative economic implications relating to agricultural production-patterns as well as ensuring food security of the country. An authoritative introspection for the sustainability of agro-economic policy in consistence with the increasing population becomes the cry of the hour of the country. Sensitivity-variance of different crops to warming though confines the scopes and preferences of territoriality of productivity however, the complexity of impact of climate-change on agricultural productivity necessitates the appraisal and interrelations of physical, economic and social factors as well changing ecological imbalances. The attempt to bring structural reforms in the farming practices in weather variability context in the country requires financial support for the marginal and small-scale farmers as farming practices are predominantly adapted to local climates. The global character of atmospheric circulation and the impact of ecological and climate-changes encourage combined use of climate, crop, and economic models for sustaining growth of supply chain to market. In addition, the increasing deterioration of agricultural production due to the eventuality of climate-change and eventual ecological imbalance considerably would affect the trade balance of the country for the legislative mandate of food security. To transform the progressive move of LPG (Liberalization, Privatization and Globalization) into secured and sustainable agro-economy to save our planet from the ravages of climate change, a comprehensive schematic approach involves configuration of legal and policy tools containing thereof: a) ‘spillover costs’ of agricultural productivity due to increased ecological and climate changes; b) coherent assessment of the modalities of agriculture to harmonize the present-day water-stressed; c) coherent financing mechanism for the farmers, in particular the small-scale and marginal ones who are not only being affected disproportionately rather the changes warrant them to be displaced internally. The present discussion reviews two prime factors: viz; a) Effects of Climate-Change upon agro-economy of the country; and b) Attenuation of Agro-financing measures in the regulatory mechanism for regulating and developing the vibrant supply chain to the market

scholarly journals Future climate changes under different scenarios and their effects on runoff in the upper Taohe River Basin

2021 ◽  
Author(s):  
zhen wang ◽  
Meixue Yang ◽  
xuejia wang ◽  
lizhen cheng ◽  
guoning wan ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Average Method ◽  
Climate Changes ◽  
Hydrological Model ◽  
Moving Average ◽  
Future Climate ◽  
Annual Average ◽  
The Future

Climate changes may pose challenges to water management. Simulation and projection of climate-runoff processes through hydrological models are essential means to assess the impact of global climate change on runoff variations. This study focuses on the upper Taohe River Basin which is an important water sources for arid and semi-arid regions in Northwest China. In order to assess the impacts of environmental changes, outputs from a regional climate model and the SWAT hydrological model were used to analyze the future climate change scenarios to water resources quantitatively. The examined climate changes scenarios results showed that average annual temperature from 2020 to 2099 in this area exhibits a consistent warming trend with different warming rates, at rates of 0.10°C/10a, 0.20°C /10a and 0.54°C /10a under RCP2.6, RCP4.5 and RCP8.5(Representative Concentration Pathways, RCPs), The value of precipitation experiences different trends under different emission scenarios. Under the RCP2.6, average precipitation would decrease at a rate of 3.69 mm/10a, while under the RCP4.5 and RCP8.5, it would increase at rates of 4.97 mm/10a and 12.28 mm/10a, respectively. The calibration and validation results in three in-site observations (Luqu, Xiabagou and Minxian) in the upper Taohe River Basin showed that SWAT hydrological model is able to produce an acceptable simulation of runoff at monthly time-step. In response to future climate changes, projected runoff change would present different decreasing trends. Under RCP2.6, annual average runoff would experience a progress of fluctuating trend, with a rate of-0.6×108m3 by 5-year moving average method; Under the RCP4.5 and RCP8.5, annual average runoff would show steadily increasing trends, with rates of 0.23×108m3 and 0.16×108m3 by 5-year moving average method. The total runoff in the future would prone to drought and flood disasters. Overall, this research results would provide a scientific reference for reginal water resources management on the long term.

scholarly journals Predicting suitability of regions for Zika outbreaks with zero-inflated models trained using climate data

2019 ◽  
Author(s):  
Samantha Roth ◽  
Miranda Teboh-Ewungkem ◽  
Ming Li
Keyword(s):  
Statistical Models ◽  
Birth Defect ◽  
Climate Changes ◽  
Geographic Range ◽  
Future Climate ◽  
Climatic Variables ◽  
Human Populations ◽  
Climate Projections ◽  
Climate Variables ◽  
Climate Suitability

AbstractIn recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barré syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes.We used statistical models to predict regional suitability for autochthonous Zika transmission using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climate’s habitability for Ae. aegypti. We trained zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) regression models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. We determined the two best models to both be ZINB models. The best model’s regressors were winter mean temperature, yearly minimum temperature, and population, and the second-best model’s regressors were winter mean temperature and population.These two models were then run on bias-corrected climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have increasingly mild winters and high human populations. These predictions are based on the most extreme scenario for climate change, which we are currently on track for.Author Summary:In recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barré syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes. We used statistical models to predict regional suitability for locally-acquired Zika cases using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climate’s habitability for Ae. aegypti. We trained statistical models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final two models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. These two models were then run on climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have high human populations and increasingly mild winters.

scholarly journals Expected declines in recruitment of walleye pollock (Theragra chalcogramma) in the eastern Bering Sea under future climate change

2011 ◽  
Vol 68 (6) ◽  
pp. 1284-1296 ◽  
Author(s):  
Franz J. Mueter ◽  
Nicholas A. Bond ◽  
James N. Ianelli ◽  
Anne B. Hollowed
Keyword(s):  
Climate Change ◽  
Bering Sea ◽  
Late Summer ◽  
Walleye Pollock ◽  
Future Climate ◽  
Future Climate Change ◽  
Theragra Chalcogramma ◽  
Climate Projections ◽  
Eastern Bering Sea ◽  
Walleye Pollock Theragra Chalcogramma

Abstract Mueter, F. J., Bond, N. A., Ianelli, J. N., and Hollowed, A. B. 2011. Expected declines in recruitment of walleye pollock (Theragra chalcogramma) in the eastern Bering Sea under future climate change. – ICES Journal of Marine Science, 68: 1284–1296. A statistical model is developed to link recruitment of eastern Bering Sea walleye pollock (Theragra chalcogramma) to variability in late summer sea surface temperatures and to the biomass of major predators. The model is based on recent advances in the understanding of pollock recruitment, which suggest that warm spring conditions enhance the survival of early larvae, but high temperatures in late summer and autumn are associated with poor feeding conditions for young-of-year pollock and reduced recruitment in the following year. A statistical downscaling approach is used to generate an ensemble of late summer temperature forecasts through 2050, based on a range of IPCC climate projections. These forecasts are used to simulate future recruitment within an age-structured stock projection model that accounts for density-dependent effects (stock–recruitment relationship), the estimated effects of temperature and predation, and associated uncertainties. On average, recruitment in 2040–2050 should expectedly decline by 32–58% relative to a random recruitment scenario, depending on assumptions about the temperature relationship, the magnitude of density-dependence, and future changes in predator biomass. The approach illustrated here can be used to evaluate the performance of different management strategies and provide long-term strategic advice to managers confronted with a rapidly changing climate.

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