CERES-Rice model-based simulations of climate change impacts on rice yields and efficacy of adaptive options in Northeast China

2014 ◽  
Vol 65 (12) ◽  
pp. 1267 ◽  
Author(s):  
Wenxiang Wu ◽  
Qian Fang ◽  
Quansheng Ge ◽  
Mengzi Zhou ◽  
Yumei Lin

Global temperatures are rising, and concerns about the response of agricultural production to climate change are increasing. Adaptation is a key factor that will shape the severity of impacts of future climate change on food production. Based on actual meteorological, soil and agricultural management data at site scale, the CERES-Rice model, combined with the Regional Climate Model (RCM)-PRECIS, was used to simulate both the effects of climate change on rice yields and the efficacy of adaptive options in Northeast China. The impact simulation showed that rice yield changes ranged from +0.1% to –44.9% (A2 scenario) and from –0.3% to –40.1% (B2 scenario) without considering CO2 fertilisation effects. When considering CO2 fertilisation effects, rice yield reductions induced by temperature increases were decreased at all sites. The CO2 fertilisation effects may partly offset the negative impacts of climate change on rice yields. Adaptive option results revealed that the adverse impacts of climate change on rice yields could be mitigated by advancing the planting dates, transplanting mid–late-maturing rice cultivars to replace early-maturing ones, and breeding new rice cultivars with high thermal requirements. Our findings provide insight into the possible impacts of climate change on rice production, and we suggest which adaptive strategies could be used to cope with future climate change, thus providing evidence-based suggestions for government policy on adaptive strategies.

2006 ◽  
Vol 27 ◽  
pp. 103-110 ◽  
Author(s):  
LP Amgain ◽  
NR Devkota ◽  
J Timsina ◽  
B Bijay-Singh

Recent trends of a decline or stagnation in the yield of rice and wheat in rice-wheat (RW) systems of the Indo-Gangetic Plains (IGP) have raised serious concerns about the regional food security. The effect of future climate change on crop production adds to this complex problem. The validated CSM-CERES-Rice and CSM-CERES-Wheat (Ver. 4.0) data were used to test the sensitivity of the models in Punjab, India. The models were sensitive to climatic parameters (temperature, CO2 concentration, solar radiation and rainfall) on yields of both crops. Simulated rice yields were sensitive to weather as there was 13% less yield of rice in 1999 than in 2001. Similarly, simulated wheat yields were also sensitive to weather, with the highest yield in 2001, and the lowest in 2003. Increments in both maximum and minimum temperatures by 4°C, decreased rice yield by 34% and wheat yield by 4% as compared to base scenario with current weather data. By increasing 4°C for both maximum and minimum temperature along with an increase in solar radiation by 1MJ/m2/day, rice yield decreased by 32% as compared to base scenario while wheat yields were not affected. With the increase in maximum and minimum temperatures by 4°C, and also an increase in CO2 concentration by 20 ppm from the standard CO2 concentration of 335 ppm, the reduction in rice yield was 33%, but in wheat yield was only 3%. Rainfed wheat yield increased by 7%, by increasing daily rainfall by 1.5 times, and by 13%, by doubling the rainfall, both after 96 days of sowing (DAS) to maturity. Lowering rainfall to zero, for each day after 96 DAS to until maturity reduced wheat yield by 18%. The increasing maximum and minimum temperatures irrespective of whether the CO2 concentration increased or not, seemed to have more adverse effects on rice than to wheat. Simulations demonstrated that CSM-CERES-Rice and CSM-CERES- Wheat are sensitive to CO2 and climatic parameters, and can be used to study the impact of future climate change on rice and wheat productivity in RW systems in Asia. Key words: CSM-CERES-Rice, CSM-CERES-Wheat, climate change, yield, phenology J. Inst. Agric. Anim. Sci. 27:103-110 (2006)


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rong Jiang ◽  
Wentian He ◽  
Liang He ◽  
J. Y. Yang ◽  
B. Qian ◽  
...  

AbstractMaize (Zea mays L.) production in Northeast China is vulnerable to climate change. Thus, exploring future adaptation measures for maize is crucial to developing sustainable agriculture to ensure food security. The current study was undertaken to evaluate the impacts of climate change on maize yield and partial factor productivity of nitrogen (PFPN) and explore potential adaptation strategies in Northeast China. The Decision Support System for Agrotechnology Transfer (DSSAT) model was calibrated and validated using the measurements from nine maize experiments. DSSAT performed well in simulating maize yield, biomass and N uptake for both calibration and validation periods (normalized root mean square error (nRMSE) < 10%, −5% < normalized average relative error (nARE) < 5% and index of agreement (d) > 0.8). Compared to the baseline (1980–2010), the average maize yields and PFPN would decrease by 7.6–32.1% and 3.6–14.0 kg N kg−1 respectively under future climate scenarios (2041–2070 and 2071–2100) without adaptation. Optimizing N application rate and timing, establishing rotation system with legumes, adjusting planting dates and breeding long-season cultivars could be effective adaptation strategies to climate change. This study demonstrated that optimizing agronomic crop management practices would assist to make policy development on mitigating the negative impacts of future climate change on maize production.


2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  

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.


Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.


Author(s):  
Hevellyn Talissa dos Santos ◽  
Cesar Augusto Marchioro

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.


Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.


2017 ◽  
Vol 17 ◽  
pp. 139-154 ◽  
Author(s):  
A. Araya ◽  
I. Kisekka ◽  
X. Lin ◽  
P.V. Vara Prasad ◽  
P.H. Gowda ◽  
...  

2021 ◽  
Author(s):  
Laura Dziomber ◽  
Lisa Gurtner ◽  
Maria Leunda ◽  
Christoph Schwörer

&lt;p&gt;Current and future climate change is a serious threat to biodiversity and ecosystem stability. With a rapid increase of global temperatures by 1.5&amp;#176;C since the pre-industrial period and a projected warming of 1.5-4&amp;#176;C by the end of this century, plant species are forced to either adapt to these changes, shift their distribution range to higher elevation, or face population decline and extinction. Today, there is an urgent need to better understand the responses of mountain vegetation to climate change in order to predict the consequences of the human-driven global change currently occurring during the Anthropocene and maintain species diversity and ecosystem services. However, most predictions are based on short-term experiments. There is, in general, an insufficient use of longer time scales in conservation biology to understand long-term processes. Palaeoecological data are a great source of information to infer past species responses to changing environmental factors, such as climate or anthropogenic disturbances.&lt;/p&gt;&lt;p&gt;The last climate change of a similar magnitude and rate as projected for this century was the transition between the last Ice Age and the Holocene interglacial (ca. 11,700 years ago). By analyzing subfossil plant remains such as plant macrofossils, charcoal and pollen from natural archives, we can study past responses to climate change. However, until recently it was not possible to reconstruct changes at the population level. With the development of new methods to extract ancient DNA (aDNA) from plant remains and next generation DNA-sequencing techniques, we can now infer past population dynamics by analyzing the genetic variation through time. Ancient DNA might also be able to reveal if species could adapt to climatic changes by identifying intraspecific variation of specific genes related to climatic adaptations.&lt;/p&gt;&lt;p&gt;We are currently investigating a palaeoecological archive from a high-altitude mountain lake, Lai da Vons (1991 m a.s.l), situated in Eastern Switzerland. We are presenting preliminary macrofossil, pollen and charcoal results to reconstruct local to regional vegetation and fire dynamics with high chronological precision and resolution. In a next step, we will use novel molecular methods, in order to track adaptive and neutral genetic diversity through the Holocene by analyzing aDNA from subfossil conifer needles. The overarching goal of this large-scale, multiproxy study is to better understand past vegetation dynamics and the impact of future climate change on plants at multiple scales; from the genetic to the community level.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;


2021 ◽  
pp. 26-31
Author(s):  
Cyril Caminade

Abstract This expert opinion provides an overview of mathematical models that have been used to assess the impact of climate change on ticks and tick-borne diseases, ways forward in terms of improving models for the recent context and broad guidelines for conducting future climate change risk assessment.


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