Impact of climate change and variability on maize yield in Tropical Africa

2020 ◽  
Author(s):  
Freddy Bangelesa ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Maize Yield ◽  
Series Data ◽  
Yield Variability ◽  
Model Output ◽  
Tropical Africa ◽  
Climate Change And Variability ◽  
Recent Climate ◽  
Maize Yields

<p> <span><span>Tropical Africa has been experiencing a long term drying trend for the last two decades. Climate change and variability has an influence on rain-fed agriculture under the Tropics. Many studies have investigated on the role of climate change and variability on crop yields, but with a limited number of predictors. We use detailed gridded crop statistics time series data to examine how recent climate inter-annual variability led to variations in maize yields. The added-value of this study is, that it integrates for the first time different sets of variables on different spatial scales, 107 in total: local, regional and global. A cross-validated model output statistics (MOS) approach is applied to choose physically motivated predictors. Both climate variables and maize yields were de-trended. The results revealed that inter-annual climate variability accounts for globally more than 35 percent of the observed maize variability in Tropical Africa. Our study uniquely illustrates spatial patterns in the relationship between climate variability and maize yield variability, highlighting where variations in different group of predictors interact and explain maize yield variability. Overall, temperature and precipitation principal component variables are preferably selected by the model. The next step of the study will consist of using the MOS equation to forecast future maize yield changes based on climate model output. The implication of the study is that, it will generate policy interventions towards buffering future crop production from climate variability.</span></span></p>

scholarly journals Climate change and variability: a review of what is known and ought to be known for Uganda

2018 ◽  
Vol 10 (5) ◽  
pp. 752-771 ◽  
Author(s):  
Francis Wasswa Nsubuga ◽  
Hannes Rautenbach
Keyword(s):  
Climate Change ◽  
Agricultural Sector ◽  
Climate Model ◽  
Regional Climate ◽  
Future Research ◽  
Daily Maximum ◽  
Inter Tropical Convergence Zone ◽  
Content Type ◽  
Climate Change And Variability ◽  
Recent Climate

Purpose In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and change. The purpose of this study is to review what has been documented, thus it gives an overview of what is known and seeks to explain the implications of a changing climate, hence what ought to be known to create a climate resilient environment. Design/methodology/approach Terms such as “climate”, “climate change” and “climate variability” were identified in recent peer-reviewed published literature to find recent climate-related literature on Uganda. Findings from independent researchers and consultants are incorporated. Data obtained from rainfall and temperature observations and from COSMO-CLM Regional Climate Model-Coordinated Regional Climate Downscaling Experiment (CCLM CORDEX) data, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data and Global Precipitation Climatology Centre (GPCC) have been used to generate spatial maps, seasonal outputs and projections using GrADS 2.02 and Geographic Information System (GIS) software for visualization. Findings The climate of Uganda is tropical in nature and influenced by the Inter-Tropical Convergence Zone (ITCZ), varied relief, geo-location and inland lakes, among other factors. The impacts of severe weather and climate trends and variability have been documented substantially in the past 20-30 years. Most studies indicated a rainfall decline. Daily maximum and minimum temperatures are on the rise, while projections indicate a decrease in rainfall and increase in temperature both in the near and far future. The implication of these changes on society and the economy are discussed herein. Cost of inaction is expected to become huge, given factors like, the growing rate of the population and the slow expanding economy experienced in Uganda. Varied forms of adaptation to the impacts of climate change are being implemented, especially in the agricultural sector and at house hold level, though not systematically. Originality/value This review of scientific research findings aims to create a better understanding of the recent climate change and variability in Uganda and provides a baseline of summarized information for use in future research and actions.

scholarly journals Compound Vulnerabilities: The Intersection of Climate Variability and HIV/AIDS in Northwestern Tanzania

2014 ◽  
Vol 6 (1) ◽  
pp. 9-21 ◽  
Author(s):  
Valerie Githinji ◽  
Todd A. Crane
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Social Dynamics ◽  
Lake Victoria ◽  
Rural Livelihoods ◽  
Climate Change And Variability ◽  
Northwestern Tanzania ◽  
Food And Nutrition ◽  
Agricultural Yields ◽  
Hiv Aids

Abstract Drawing on ethnographic research conducted in Nsisha, a rural village located close to the shores of Lake Victoria in northwestern Tanzania, this article analyzes how climate change and variability intersect with other stressors that affect rural livelihoods, particularly HIV/AIDS. The analysis integrates theories of vulnerability from both climate and HIV/AIDS literatures to show how these intersecting stressors compound livelihood vulnerability in complex ways. Climate change and variability are linked to declining agricultural yields and an increase in food and nutrition insecurity and poor health in this region. This situation heightens poverty and susceptibility to HIV/AIDS, compromising people’s abilities to cope and adapt. Because of social dynamics, single mothers and their children are particularly affected by these compound vulnerabilities. Climate change and variability are significant contributing vulnerability factors that sustain and exacerbate asymmetrical poverty, food and nutrition insecurity, and HIV/AIDS. By describing the links between vulnerability to HIV/AIDS and climate variability, findings highlight the importance of holistic and localized approaches to adaptation, instead of trying to isolate single issues. Prioritization of multidisciplinary research focusing on the socially differentiated and gendered distribution of vulnerability specifically in regard to poverty, food and nutrition insecurity, and HIV/AIDS is recommended as a means to enrich the understanding of climate change vulnerability. Adaptation strategies should address how climatic shifts interact with generalized poverty, food and nutrition insecurity, health, and gendered vulnerability in areas most affected.

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 Predicting silage maize yield and quality in Sweden as influenced by climate change and variability

2012 ◽  
Vol 62 (2) ◽  
pp. 151-165 ◽  
Author(s):  
Henrik Eckersten ◽  
Antje Herrmann ◽  
Alois Kornher ◽  
Magnus Halling ◽  
Erik Sindhøj ◽  
...  
Keyword(s):  
Climate Change ◽  
Maize Yield ◽  
Climate Change And Variability ◽  
Silage Maize ◽  
Yield And Quality

scholarly journals Bivariate EMD-Based Data Adaptive Approach to the Analysis of Climate Variability

2011 ◽  
Vol 2011 ◽  
pp. 1-21 ◽  
Author(s):  
Md. Khademul Islam Molla ◽  
Poly Rani Ghosh ◽  
Keikichi Hirose
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Reference Signal ◽  
Complex Signal ◽  
Intrinsic Mode Functions ◽  
Climate Data ◽  
Climate Signal ◽  
Adaptive Approach ◽  
Climate Change And Variability ◽  
Data Adaptive

This paper presents a data adaptive approach for the analysis of climate variability using bivariate empirical mode decomposition (BEMD). The time series of climate factors: daily evaporation, maximum and minimum temperatures are taken into consideration in variability analysis. All climate data are collected from a specific area of Bihar in India. Fractional Gaussian noise (fGn) is used here as the reference signal. The climate signal and fGn (of same length) are combined to produce bivariate (complex) signal which is decomposed using BEMD into a finite number of sub-band signals named intrinsic mode functions (IMFs). Both of climate signal as well as fGn are decomposed together into IMFs. The instantaneous frequencies and Fourier spectrum of IMFs are observed to illustrate the property of BEMD. The lowest frequency oscillation of climate signal represents the annual cycle (AC) which is an important factor in analyzing climate change and variability. The energies of the fGn's IMFs are used to define the data adaptive threshold to separate AC. The IMFs of climate signal with energy exceeding such threshold are summed up to separate the AC. The interannual distance of climate signal is also illustrated for better understanding of climate change and variability.

scholarly journals Quantifying Agroforestry Yield Buffering Potential Under Climate Change in the Smallholder Maize Farming Systems of Ethiopia

2021 ◽  
Vol 3 ◽  
Author(s):  
Abel Chemura ◽  
Amsalu Woldie Yalew ◽  
Christoph Gornott
Keyword(s):  
Climate Change ◽  
National Level ◽  
Climate Change Impacts ◽  
Farming Systems ◽  
Maize Yield ◽  
Agroforestry System ◽  
Climatic Conditions ◽  
Yield Losses ◽  
Climate Regulation ◽  
Maize Yields

Agroforestry is a promising adaptation measure for climate change, especially for low external inputs smallholder maize farming systems. However, due to its long-term nature and heterogeneity across farms and landscapes, it is difficult to quantitatively evaluate its contribution in building the resilience of farming systems to climate change over large areas. In this study, we developed an approach to simulate and emulate the shading, micro-climate regulation and biomass effects of multi-purpose trees agroforestry system on maize yields using APSIM, taking Ethiopia as a case study. Applying the model to simulate climate change impacts showed that at national level, maize yield will increase by 7.5 and 3.1 % by 2050 under RCP2.6 and RCP8.5, respectively. This projected increase in national-level maize yield is driven by maize yield increases in six administrative zones whereas yield losses are expected in other five zones (mean of −6.8% for RCP2.6 and −11.7% for RCP8.5), with yields in the other four zones remaining stable overtime. Applying the emulated agroforestry leads to increase in maize yield under current and future climatic conditions compared to maize monocultures, particularly in regions for which yield losses under climate change are expected. A 10% agroforestry shade will reduce maize yield losses by 6.9% (RCP2.6) and 4.2 % (RCP8.5) while 20% shade will reduce maize yield losses by 11.5% (RCP2.6) and 11% (RCP8.5) for projected loss zones. Overall, our results show quantitatively that agroforestry buffers yield losses for areas projected to have yield losses under climate change in Ethiopia, and therefore should be part of building climate-resilient agricultural systems.

scholarly journals Strategi Peningkatan Produktivitas Kopi serta Adaptasi terhadap Variabilitas dan Perubahan Iklim melalui Kalender Budidaya

2020 ◽  
Vol 14 (2) ◽  
pp. 65
Author(s):  
Yeli Sarvina ◽  
Tania June ◽  
Elza Surmaini ◽  
Rita Nurmalina ◽  
Sutjahjo Surjono Hadi
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Adaptation Strategy ◽  
Climate Forecast ◽  
Climate Variability And Change ◽  
Coffee Production ◽  
Climate Change And Variability ◽  
Potential Strategy ◽  
Coffee Cultivation ◽  
The Impact

<p><strong>Abstrak</strong>. Rendahnya produktivitas kopi merupakan salah satu permasalahan utama dalam sistem produksi kopi Indonesia. Hal ini diantaranya disebabkan tidak adanya perawatan kopi yang optimal dengan memperhatikan fase fenologi kopi, serta dampak variabilitas dan perubahan iklim. Berbagai teknologi adaptasi kopi sudah banyak dihasilkan namun langkah adaptasi dengan memanfaatkan prakiraan iklim dalam bentuk penyesuian kegiatan budidaya dengan fase fenologi atau disebut sebagai kalender budidaya belum dikembangkan. Tulisan ini memaparkan tentang dampak variabilitas dan perubahan iklim pada tanaman kopi, teknologi adaptasi kopi yang sudah tersedia, perlunya pengembangan kalender budidaya kopi sebagai bentuk strategi adaptasi dan peningkatan produktivitas serta potensi dan tantangan pengembangan kalender budidaya kopi di Indonesia. Hasil review ini menunjukkan kalender budidaya kopi berpotensi dikembangkan sebagai strategi peningkatan produktivitas serta adaptasi terhadap variabilitas dan perubahan iklim.</p><p> </p><p><strong>Abstract</strong>. Low productivity is one of the main challenges in Indonesia's coffee production system .It is low due to cultivation management; most of the coffee farmer does not manage their plantation base on the coffee phenology phase.  Moreover climate variability and change also have important effect on coffee productivity. Various technologies on adaptation and measurement to climate change and variability have been identified. Unfortunately, the technology which use climate forecast through adjusting cultivation activity and coffee phenology called as cultivation calendar do not exist yet. This paper provides an overview on the impact of climate variability and change to coffee production, the existing adaptation strategy, and the importance of cultivation calendar as a strategy for adapting and increasing productivity, and the potential and challenges to develop cultivation calendar in Indonesia. This review reveals that coffee cultivation calendar is a potential strategy for increaseing productivity and adapting climate change and variability.</p>

scholarly journals Climate Variability and Livestock Production in Nigeria: Lessons for Sustainable Livestock Production

2016 ◽  
Vol 49 (1-4) ◽  
pp. 30-37
Author(s):  
Grace Zibah Rekwot ◽  
Anosike Francis Ugo ◽  
Oke-Egbodo Brenda Engo
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Time Series Data ◽  
Livestock Production ◽  
Annual Rainfall ◽  
Series Data ◽  
Adaptation Measures ◽  
Augmented Dickey Fuller ◽  
Smart Agriculture ◽  
Adf Test

Abstract The study examined the relationship between climate variability and livestock production and the lessons that can be drawn for achieving sustainable livestock production in Nigeria. The study employed time series data on annual rainfall and livestock production given by index of the aggregate livestock production over the period of 1970 to 2008. The data were obtained from various publications of the Central Bank of Nigeria and the Nigerian Meteorological Agency. The data were analyzed through the instrumentality of econometric tools such as Augmented Dickey Fuller (ADF) test, Vector auto regression (VAR) lag order selection test and Pairwise granger causality. The results of the data analysis revealed the existence of unidirectional causality from climate variability to livestock production in Nigeria and this implies that climate variability has been significant in influencing livestock production over the period under study. Based on the foregoing, it is recommended as a matter of urgency that government should continually sensitize farmers on the challenges of climate change and feasible adaptation measures that they can adhere to in order to avert the detrimental effects of climate change on sustainable livestock production. In other words, implementation of the policy thrust on climate smart agriculture should be pursued vigorously.

scholarly journals A Time-Series Analysis of Climate Variability in Urban and Agricultural Sites (Rome, Italy)

Agriculture ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 103 ◽  
Author(s):  
Luca Salvati ◽  
Ilaria Zambon ◽  
Giuseppe Pignatti ◽  
Andrea Colantoni ◽  
Sirio Cividino ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Air Temperature ◽  
Local Scale ◽  
Series Data ◽  
Urban Site ◽  
Severe Drought ◽  
Temperature And Precipitation ◽  
Dry Spells

Identifying early signals of climate change and latent patterns of meteorological variability requires tools analyzing time series data and multidimensional measures. By focusing on air temperature and precipitation, the present study compares local-scale climate regimes at two sites in Central Italy (urban Rome and a peri-urban cropland 10 km west of Rome), using descriptive and inferential statistics on both variables and a drought index (the Standardized Precipitation Index, hereafter SPI) recorded over the last 60 years (1958–2017). The present work assumes the importance of urban-rural gradients shaping local-scale climate regimes and spatial variability, with differential impacts on individual variables depending on territorial background and intrinsic biophysical characteristics. Considering together precipitations and minimum/maximum air temperature at month and year scale, the analysis developed here illustrates two coexisting climatic trends at distinctive spatial scales: A general trend toward warming—specifically influencing temperature regimes—and a more specific pattern evidencing changes in local-scale climate regime along the urban gradient, with a more subtle impact on both precipitations and temperatures. Empirical results indicate that climate variability increased over the study period, outlining the low predictability of dry spells typical of Mediterranean climate especially in the drier season (spring/summer). On average, absolute annual differences between the two sites amounted to 70 mm (more rainfall in the peri-urban site) and 0.9 °C (higher temperature in the urban site). A similar trend toward warming was observed for air temperature in both sites. No significant trends were observed for annual and seasonal rainfalls. SPI long-term trends indicate high variability in dry spells, with more frequent (and severe) drought episodes in urban Rome. Considering together trends in temperature and precipitation, the ‘urban heat’ effect was more evident, indicating a clearer trend toward climate aridity in urban Rome. These findings support the adoption of integrated strategies for climate change adaptation and mitigation in both agricultural systems and relict natural ecosystems surrounding urban areas.

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