Global contribution of climate variability and trends to maize yield change in observations and crop models during 1980-2010

2020 ◽  
Author(s):  
Xiaomeng Yin ◽  
Guoyong Leng
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Statistical Model ◽  
Yield Loss ◽  
Climate Change Impacts ◽  
Maize Yield ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Crop Models ◽  
Process Based Models

<p>Understanding historical crop yield response to climate change is critical for projecting future climate change impacts on yields. Previous assessments rely on statistical or process-based crop models, but each has its own strength and weakness. A comprehensive comparison of climate impacts on yield between the two approaches allows for evaluation of the uncertainties in future yield projections. Here we assess the impacts of historical climate change on global maize yield for the period 1980-2010 using both statistical and process-based models, with a focus on comparing the performances between the two approaches. To allow for reasonable comparability, we develop an emulator which shares the same structure with the statistical model to mimic the behaviors of process-based models. Results show that the simulated maize yields in most of the top 10 producing countries are overestimated, when compared against FAO observations. Overall, GEPIC, EPIC-IIASA and EPIC-Boku show better performance than other models in reproducing the observed yield variations at the global scale. Climate variability explains 42.00% of yield variations in observation-based statistical model, while large discrepancy is found in crop models. Regionally, climate variability is associated with 55.0% and 52.20% of yield variations in Argentina and USA, respectively. Further analysis based on process-based model emulator shows that climate change has led to a yield loss by 1.51%-3.80% during the period 1980-1990, consistent with the estimations using the observation-based statistical model. As for the period 1991-2000, however, the observed yield loss induced by climate change is only captured by GEPIC and pDSSAT. In contrast to the observed positive climate impact for the period 2001-2010, CLM-Crop, EPIC-IIASA, GEPIC, pAPSIM, pDSSAT and PEGASUS simulated negative climate effects. The results point to the discrepancy between process-based and statistical crop models in simulating climate change impacts on maize yield, which depends on not only the regions, but also the specific time period. We suggest that more targeted efforts are required for constraining the uncertainties of both statistical and process-based crop models for future yield predictions. </p>

scholarly journals Quantitative Modeling of Climate Change Impacts on Mycotoxins in Cereals: A Review

Toxins ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 276
Author(s):  
Cheng Liu ◽  
H. J. Van der Fels-Klerx
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Quantitative Modeling ◽  
Cereal Grains ◽  
Future Climate Change ◽  
Crop Models ◽  
Scenario Analyses ◽  
Cereal Grain ◽  
And Shifts ◽  
Local Weather

Our climate is projected to change gradually over time. Mycotoxin occurrence in cereal grains is both directly and indirectly related to local weather and to climate changes. Direct routes are via the effects of precipitation, relative humidity, and temperatures on both fungal infection of the grain and mycotoxin formation. Indirect routes are via the effects of the wind dispersal of spores, insect attacks, and shifts in cereal grain phenology. This review aimed to investigate available modeling studies for climate change impacts on mycotoxins in cereal grains, and to identify how they can be used to safeguard food safety with future climate change. Using a systematic review approach, in total, 53 relevant papers from the period of 2005–2020 were retrieved. Only six of them focused on quantitative modeling of climate change impacts on mycotoxins, all in pre-harvest cereal grains. Although regional differences exist, the model results generally show an increase in mycotoxins in a changing climate. The models do not give an indication on how to adapt to climate change impacts. If available models were linked with land use and crop models, scenario analyses could be used for analyzing adaptation strategies to avoid high mycotoxin presence in cereal grains and to safeguard the safety of our feed and food.

scholarly journals Improving the Assessment of Potential and Actual Impacts of Climate Change and Extreme Events Through a Parallel Modeling of Climatic and Societal Changes at Different Scales

2017 ◽  
Vol 04 (04) ◽  
pp. 1850003 ◽  
Author(s):  
Stefan Greiving ◽  
Sophie Arens ◽  
Dennis Becker ◽  
Mark Fleischhauer ◽  
Florian Hurth
Keyword(s):  
Climate Change ◽  
Case Studies ◽  
Climate Change Impacts ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Land Use Patterns ◽  
Intergovernmental Panel ◽  
Adaptation Measures ◽  
Modeling Approach ◽  
Recent Climate

Any adaptation activity needs a reliable evidence basis for the climate itself as well as for the exposition and sensitivity of the social, economic or ecological system and its elements. This requires an assessment of recent climate impacts as well as potential future climate change impacts in order to select tailor-made adaptation measures. For a methodologically coherent assessment, the Intergovernmental Panel on Climate Change (IPCC) had introduced the requirement of a parallel modeling approach which means that demographic and socioeconomic changes are projected in parallel to the changes of the climatic system. This paper discusses a conceptual framework of a parallel modeling approach and presents its application in four case studies of climate change impact assessments in Germany, covering the national, regional and local scale. The results from the different applications prove the hypothesis that the change in sensitivity (i.e., demographic change, economic change and change in land-use patterns) often determines the magnitude of climate- and weather-related impacts in the near future significantly. The case studies, however, also show that adaptation processes have to be organized in a collaborative way, which takes the knowledge, and also the concerns of the addressees into full account. A broad mandate from all social groups is especially needed when political decisions are based on uncertain knowledge — which is the case whenever climate change impacts are assessed.

scholarly journals Challenges in simulating economic effects of climate change on global agricultural markets

2021 ◽  
Vol 166 (3-4) ◽  
Author(s):  
Angelo C. Gurgel ◽  
John Reilly ◽  
Elodie Blanc
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Agricultural Sector ◽  
Crop Yields ◽  
Agricultural Research ◽  
Climate Change Impacts ◽  
Well Being ◽  
Climate Impacts ◽  
Agricultural Markets ◽  
Crop Models

AbstractMany approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets.

scholarly journals Different Time Windows Provide Divergent Estimates of Climate Variability and Change Impacts on Maize Yield in Northeast China

2019 ◽  
Vol 11 (23) ◽  
pp. 6659 ◽  
Author(s):  
Xi Deng ◽  
Yao Huang ◽  
Wenjuan Sun ◽  
Lingfei Yu ◽  
Xunyu Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Northeast China ◽  
Regression Models ◽  
Time Window ◽  
Time Windows ◽  
Maize Yield ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Climate Variability And Change

Maize is the main crop in Northeast China (NEC), but is susceptible to climate variations. Using county-level data from 1980 to 2010, we established multiple linear regression models between detrended changes in maize yield and climate variables at two time windows—whole-season and vegetative and reproductive (V&R) phases. Based on climate change trends, these regression models were used to assess climate variability and change impacts on maize yield in different regions of NEC. The results show that different time windows provide divergent estimates. Climate change over the 31 years induced a 1.3% reduction in maize yield at the time window of whole-season, but an increase of 9.1% was estimated at the time window of V&R phases. The yield improvement is attributed to an increase in minimum temperature at the vegetative phase when the temperatures were much lower than the optimum. Yield fluctuations due to inter-annual climate variability were estimated to be ±9% per year at the time window of V&R phases, suggesting that the impact of climate variability on maize yield is much greater than climate change. Trends in precipitation were not responsible for the yield change, but precipitation anomalies contributed to the yield fluctuations. The impacts of warming on maize yield are regional specific, depending on the local temperatures relative to the optimum. Increase in maximum temperature led to a reduction of maize yield in western NEC, but to an increase in mid-east part of NEC. Our findings highlight the necessity of taking into account the phenological phase when assessing the climate impacts on crop yield, and the importance of buffering future crop production from climate change in NEC.

scholarly journals Modeling the Impacts of Future Climate Change on Irrigation over China: Sensitivity to Adjusted Projections

2014 ◽  
Vol 15 (5) ◽  
pp. 2085-2103 ◽  
Author(s):  
Guoyong Leng ◽  
Qiuhong Tang
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
General Circulation ◽  
Southern China ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Community Land Model ◽  
The Impact

Abstract Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China.

scholarly journals Amplified Impact of Climate Change on Fine-Sediment Delivery to a Subsiding Coast, Humboldt Bay, California

2021 ◽  
Author(s):  
Jennifer A. Curtis ◽  
Lorraine E. Flint ◽  
Michelle A. Stern ◽  
Jack Lewis ◽  
Randy D. Klein
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Baseline Period ◽  
Climate Impacts ◽  
Sediment Supply ◽  
Balance Model ◽  
Climate Projections ◽  
Sediment Delivery ◽  
Beneficial Reuse ◽  
Coastal Margin

AbstractIn Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsidence and SLR must be balanced by an adequate sediment supply. This study used an ensemble of plausible future scenarios to predict potential climate change impacts on suspended-sediment discharge (Qss) from fluvial sources. Streamflow was simulated using a deterministic water-balance model, and Qss was computed using statistical sediment-transport models. Changes relative to a baseline period (1981–2010) were used to assess climate impacts. For local basins that discharge directly to the bay, the ensemble means projected increases in Qss of 27% for the mid-century (2040–2069) and 58% for the end-of-century (2070–2099). For the Eel River, a regional sediment source that discharges sediment-laden plumes to the coastal margin, the ensemble means projected increases in Qss of 53% for the mid-century and 99% for the end-of-century. Climate projections of increased precipitation and streamflow produced amplified increases in the regional sediment supply that may partially or wholly mitigate sediment demand caused by the combined effects of subsidence and SLR. This finding has important implications for coastal resiliency. Coastal regions with an increasing sediment supply may be more resilient to SLR. In a broader context, an increasing sediment supply from fluvial sources has global relevance for communities threatened by SLR that are increasingly building resiliency to SLR using sediment-based solutions that include regional sediment management, beneficial reuse strategies, and marsh restoration.

scholarly journals Future climate change vulnerability of endemic island mammals

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Camille Leclerc ◽  
Franck Courchamp ◽  
Céline Bellard
Keyword(s):  
Climate Change ◽  
Pacific Ocean ◽  
Adaptive Capacity ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Vulnerability ◽  
Vulnerability To Climate Change ◽  
Insular Ecosystems

Abstract Despite their high vulnerability, insular ecosystems have been largely ignored in climate change assessments, and when they are investigated, studies tend to focus on exposure to threats instead of vulnerability. The present study examines climate change vulnerability of islands, focusing on endemic mammals and by 2050 (RCPs 6.0 and 8.5), using trait-based and quantitative-vulnerability frameworks that take into account exposure, sensitivity, and adaptive capacity. Our results suggest that all islands and archipelagos show a certain level of vulnerability to future climate change, that is typically more important in Pacific Ocean ones. Among the drivers of vulnerability to climate change, exposure was rarely the main one and did not explain the pattern of vulnerability. In addition, endemic mammals with long generation lengths and high dietary specializations are predicted to be the most vulnerable to climate change. Our findings highlight the importance of exploring islands vulnerability to identify the highest climate change impacts and to avoid the extinction of unique biodiversity.

Projecting future climate change impacts on heat-related mortality in large urban areas in China

2018 ◽  
Vol 163 ◽  
pp. 171-185 ◽  
Author(s):  
Ying Li ◽  
Ting Ren ◽  
Patrick L. Kinney ◽  
Andrew Joyner ◽  
Wei Zhang
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Related Mortality
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