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Abstract

The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Niño/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Niño likely improves the global-mean soybean yield by 2.1-5.4% but appears to change the yields of maize, rice and wheat by -4.3 to +0.8%. The global-mean yields of all four crops during La Niña years tend to be below normal (-4.5 to 0.0%). Our findings highlight the importance of ENSO to global crop production.

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... Such modifications on weather regimes modify the distribution of precipitation and temperature patterns in the Tropics and Sub-Tropics areas mainly. Often negative impacts, such as drought periods or floods are produced (Rojas et al., 2014) and their effects are transferred on crop production (see for example Iizumi et al., 2014a) affecting global food. ...
... Hereinafter, we use the term 'crop sowing' to distinguish between winter and spring sowing. Furthermore, since "yield is more important in determining production because of the large year-to-year variability of yield associated with climatic factors" (Iizumi et al., 2014a), in the analysis of ENSO correlation with wheat production, we analyse yield instead of production. The components of the approach adopted to this end are explained either in the following paragraphs or in the Appendix. ...
... In the future development of the model, this will require a further investigation of the climate variability at the local level. Nevertheless, in general, these results are consistent with the findings of other studies, for example Iizumi et al. (2014a) and Iizumi et al. (2018) where it clearly appears that the impact of such effects on production strictly depends on local factors such as climate mechanism and the harvested area devoted to wheat cultivation in each geographic unit. ...
... C limate variability is increasingly recognized as a key determinant of health outcomes 1 and a major concern for global climate policy and international public health 2 , with the Intergovernmental Panel on Climate Change warning that anthropogenic climate change will very likely increase the frequency and intensity of extreme events 3,4 . The El Niño Southern Oscillation (ENSO) is a major source of climate variability known to affect key social, economic, and health outcomes [5][6][7][8][9][10][11][12][13][14] ; however, the systematic effects that these correlated shifts in the tropical climate have on global health remain understudied. ENSO's adverse large-scale effects have been documented for hundreds of years 15 . ...
... ENSO has destabilizing effects on agriculture 6,15 , economic production 7 , and social stability 8 throughout areas of the global tropics that are teleconnected to it. It has been linked to human health outcomes directly through its effects on vector-and waterborne infectious diseases [9][10][11][12][13] , as well as indirectly by decreasing agricultural yields and increasing food insecurity 14 and the likelihood of conflict 8 . ...
... It has been linked to human health outcomes directly through its effects on vector-and waterborne infectious diseases [9][10][11][12][13] , as well as indirectly by decreasing agricultural yields and increasing food insecurity 14 and the likelihood of conflict 8 . ENSO's adverse effects on yields are particularly acute in the tropics 6 , where the vulnerable population of food-insecure children is larger and temperatures are closer to critical crop collapse thresholds 18,19 . Our interest is in the total influence of ENSO variability through all plausible mechanismsfrom agricultural productivity to infectious disease to conflictthat are known to affect human nutrition, as well as the systematic differences in ENSO response across places with different precipitation responses to ENSO, across continents and across decades. ...
Article
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The El Niño Southern Oscillation (ENSO) is a principal component of global climate variability known to influence a host of social and economic outcomes, but its systematic effects on human health remain poorly understood. We estimate ENSO’s association with child nutrition at global scale by combining variation in ENSO intensity from 1986-2018 with children’s height and weight from 186 surveys conducted in 51 teleconnected countries, containing 48% of the world’s under-5 population. Warmer El Niño conditions predict worse child undernutrition in most of the developing world, but better outcomes in the small number of areas where precipitation is positively affected by warmer ENSO. ENSO’s contemporaneous effects on child weight loss are detectable years later as decreases in height. This relationship looks similar at both global and regional scale, and has not appreciably weakened over the last four decades. Results imply that almost 6 million additional children were underweight during the 2015 El Niño compared to a counterfactual of neutral ENSO conditions in 2015. This demonstrates a pathway through which human well-being remains subject to predictable climatic processes.
... Better quantifying the climate effects on the yield of global major crops from historical data is propaedeutic to any estimate of future climate impacts on agriculture and its connected sectors and systems (food, energy). There is consolidated knowledge about associations between climate and crop yield anomalies 11-23 , in some cases projected along future time horizons 24-28 , adopting different approaches and climate predictors, taken either as primary variables [11][12][13][14][15][18][19][20][21][22][23][24][25] or after combination into indices 16,17,[26][27][28] . All these efforts are valuable but remain fragmented as they consider one or two drought attributes, only part of the cropping season, or they focus on limited regions. ...
... Our consideration of drought at multiple timescales (durations and timings) during the farming season (encompassing pre-sowing until harvesting) complements the usual practice of considering, for global scale evaluations, either the SPEI or other climate indicators only for a few, short and/or fixed periods (e.g. the growing season, several months before harvesting-the reproductive period-or 1 year) 13,14,16,17,26 , while neglecting sowing antecedent moisture conditions which are also important for the soil workability and crop development 36,37 . ...
... Our results reveal as globally susceptible to complex drought patterns, with different significance, the years 1983/1984 (maize and rice), 1989 (winter wheat), 1992 (maize, rice, and soybean), 2000 (maize), 2003 (maize and winter wheat), 2008 (wheat), and 2011 and 2015 (rice). Interestingly, these years were interested by weak to strong El Niño (1992, 2003 and 2015) and strong La Niña (2000) and by consecutive El Niño and La Niña (1983/1984, 1989, 2008, 2011), already recognized affecting yield in some world areas, in different ways function of the crop considered 13 . In particular, our work consolidates these years as critical for yields especially in terms of complex drought patterns and at global level, which is important for the food system given that food consumption is not only based on local production, but international trade has strong importance 61 . ...
Article
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Multi-purpose crops as maize, rice, soybean, and wheat are key in the debate concerning food, land, water and energy security and sustainability. While strong evidence exists on the effects of climate variability on the production of these crops, so far multifaceted attributes of droughts—magnitude, frequency, duration, and timing—have been tackled mainly separately, for a limited part of the cropping season, or over small regions. Here, a more comprehensive assessment is provided on how droughts with their complex patterns—given by their compound attributes—are consistently related to negative impacts on crop yield on a global scale. Magnitude and frequency of both climate and yield variability are jointly analysed from 1981 to 2016 considering multiscale droughts, i.e., dry conditions occurring with different durations and timings along the whole farming season, through two analogous and standardized indicators enabling comparison among crops, countries, and years. Mainly winter wheat and then spring wheat, soybean and the main maize’s season reveal high susceptibility of yield under more complex drought patterns than previously assessed. The second maize’s season and rice present less marked and more uncertain results, respectively. Overall, southern and eastern Europe, the Americas and sub-Saharan Africa presents multi-crop susceptibility, with eastern Europe, Middle East and Central Asia appearing critical regions for the most vulnerable crop, which is wheat. Finally, yield losses for wheat and soybean clearly worsen when moving from moderate to extreme multiscale droughts.
... They merge crop statistics datasets with existing biophysical parameters. Two important gridded crop yields datasets are commonly used in the scientific community: the one developed by Iizumi et al. (2014), referred to here as the GDHY dataset, and the one compiled by Ray et al. (2012). ...
... Many global crop yield studies are based on the GDHY v1.2 dataset (Iizumi et al., 2014;Iizumi and Ramankutty, 2016). Apart from the difference in coverage period, the GDHY v1.2 differs from the GDHY v1.3 by the type of satellite products and solar radiation datasets. ...
... The influence of ENSO in West Africa has been much documented (Mohino et al., 2011;Losada et al., 2012), explaining between 24 and 29 % of the total precipitation of the region. Its impact on maize yield variability has also been reported, but at national and local levels in many published papers (Hansen et al., 2004;Iizumi et al., 2014). A strong connection between maize yield and ENSO has been observed in Zimbabwe and Kenya Hansen et al. (2004). ...
Thesis
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Climate change is undeniable and constitutes one of the major threats of the 21st century. It impacts sectors of our society, usually negatively, and is likely to worsen towards the middle and end of the century. The agricultural sector is of particular concern, for it is the primary source of food and is strongly dependent on the weather. Considerable attention has been given to the impact of climate change on African agriculture because of the continent’s high vulnerability, which is mainly due to its low adaptation capac- ity. Several studies have been implemented to evaluate the impact of climate change on this continent. The results are sometimes controversial since the studies are based on different approaches, climate models and crop yield datasets. This study attempts to contribute substantially to this large topic by suggesting specific types of climate pre- dictors. The study focuses on tropical Africa and its maize yield. Maize is considered to be the most important crop in this region. To estimate the effect of climate change on maize yield, the study began by developing a robust cross-validated multiple linear regression model, which related climate predictors and maize yield. This statistical trans- fer function is reputed to be less prone to overfitting and multicollinearity problems. It is capable of selecting robust predictors, which have a physical meaning. Therefore, the study combined: large-scale predictors, which were derived from the principal component analysis of the monthly precipitation and temperature; traditional local-scale predictors, mainly, the mean precipitation, mean temperature, maximum temperature and minimum temperature; and the Water Requirement Satisfaction Index (WRSI), derived from the specific crop (maize) water balance model. The projected maize-yield change is forced by a regional climate model (RCM) REMO under two emission scenarios: high emission scenario (RCP8.5) and mid-range emission scenario (RCP4.5). The different effects of these groups of predictors in projecting the future maize-yield changes were also assessed. Furthermore, the study analysed the impact of climate change on the global WRSI. The results indicate that almost 27 % of the interannual variability of maize production of the entire region is explained by climate variables. The influence of climate predictors on maize-yield production is more pronounced in West Africa, reaching 55 % in some areas. The model projection indicates that the maize yield in the entire region is expected to decrease by the middle of the century under an RCP8.5 emission scenario, and from the middle of the century to the end of the century, the production will slightly recover but will remain negative (around -10 %). However, in some regions of East Africa, a slight increase in maize yield is expected. The maize-yield projection under RCP4.5 remains relatively unchanged compared to the baseline period (1982-2016). The results further indicate that large-scale predictors are the most critical drivers of the global year-to-year maize-yield variability, and ENSO – which is highly correlated with the most important predictor (PC2) – seems to be the physical process underlying this variability. The effects of local predictors are more pronounced in the eastern parts of the region. The impact of the future climate change on WRSI reveals that the availability of maize water is expected to decrease everywhere, except in some parts of eastern Africa.
... Many aspects of agricultural production are related to the SOI in the Argentinian Pampas and other cropping regions of the globe (Bert, Satorre, Toranzo, & Podestá, 2006;Podestá et al., 2002;Zhang, Zhu, Yang, & Zhang, 2008). Forecasts of crop yield, such as corn, sorghum, and wheat, have been made based on SOI episodes (de la Casa & Ovando, 2006;Iizumi et al., 2014). In the same way, SOI episodes have been used to set the termination date of cover crops before corn sowing to prioritise the soil water reserve in relation to biomass accumulation of the cover crop (Renzi & Cantamutto, 2013). ...
... SOI data based on a threshold of ±0.5 C were used to divide the after-ripening and emergence phases of each year into warm, cold and neutral episodes (commonly identified as "Niño", "Niña" and "Neutral"). The SOI is moderately correlated with future seasonal rainfall in some regions (Iizumi et al., 2014;Stone et al., 1996) Linear regression analyses among precipitation or mean minimum temperature from 1977 to 2015 were performed using Gra-phPad Prism Software version 6.0 (GraphPad, San Diego, CA). ...
... The SOI episodes could be used to quantify future precipitation probabilities in the semiarid Pampean region of Argentina, reducing the potential risk of "bad" years not only on the impact of crop yield but also on the weed management strategy (Iizumi et al., 2014;Monzon et al., 2012;Stone et al., 1996). The selection of the crop type according to the SOI episodes with some months of advanced warning, and the adjustment of the crop sowing date plus conventional or alternative weed control methods based on emergence prediction models could improve long-term weed management strategies. ...
Article
Climate events modulate weed population dynamics mainly by influencing field seedling emergence patterns. Field experiments aiming to study the influence of climate on the early‐stage establishment of weeds are of utmost importance from a practical and strategic decision‐making management point of view. The objective of this work was to analyse the effect of climate variations on the field emergence dynamics of Avena fatua in the southwest area of the semiarid Pampean region of Argentina. Field emergence patterns of A. fatua were monitored from 1977–2015. Seedling counts were destructively sampled at weekly intervals. Three quadrats (1 m2 each) were randomly distributed on a 5 ha experimental field with a high natural population density of A. fatua in the absence of a crop. Results show that the emergence strategy of this species is highly plastic with a striking variation in response to year‐to‐year climate signals. Avena fatua field emergence strategies were classified as staggered, early, medium and late based on both chronological and hydrothermal‐time parameters. In the short‐term, precipitation regimes during both the after‐ripening and emergence phases largely explained the resulting emergence strategy. In the long‐term, the combined effect of a reduction in both the precipitation frequency and the mean minimum temperature correlated with an increase in the staggered emergence pattern. Results also point out the adaptability of A. fatua in the area under study, further suggesting a bet‐hedging fitness strategy that could diminish the risk of population decline under changing climate scenarios. From an agronomic perspective, the occurrence of staggered emergence patterns with an extended emergence window would complicate the definition of the optimal time for weed control. Thus, tailoring decisions based on the Southern Oscillation Index (SOI) episodes (neutral, negative or positive) forecast plus the implementation of weed emergence models could lead to more accurate and sustainable weed management decisions.
... To meet this growing demand, it is important to understand and mitigate climate-induced variations on crop yields and production. The world soybean production is generally negatively affected by La Niña years and positively affected by El Niño years (Iizumi et al., 2014). The La Niña effects on the world soybean production is mainly driven by the negative effects of the phenomenon on soybean production in southern Brazil (Figure 6), which currently accounts for about 11% of the world production (IBGE, 2019). ...
... Also, these results indicated that the high altitudes ( Figure S3 and Table 1) of this region are an important factor in differentiating the effects of ENSO in this group. Many authors correlated lower soybean yields in southern Brazil with La Niña years (Alberto et al., 2006;Iizumi et al., 2014), but their analysis targeted specific locations where these negatives impacts were strong (e.g. Bagé, RS), and for a single sowing date. ...
Article
With current annual production of over 110 million metric tons, US soybean [Glycine max (L.) Mer.] grain production can drop drastically due to extreme weather. The record heat and drought of 2012, a La Niña year, caused a 10% decline in national soybean yield. Inclement years are often linked to El Niño-Southern Oscillation (ENSO) phenomenon, causing drought, heavy rainfall, or extreme temperatures. Thus, management strategies to minimize impact of extreme weather events (EWE) on soybean crop growth are important for the sustainability of farming systems. In this study, we evaluate how soybean sowing date and maturity group (MG) can mitigate the effects of ENSO on yield variability in the Southeastern US. A calibrated DSSAT-CROPGRO-Soybean crop model for three MGs (5.6, 6.1, and 7.0) was used to simulate yield and quantify the occurrence of extreme weather events (EWE) during vegetative and reproductive soybean stages. Historical (36 years, between 1984 and 2019) soybean yield simulations were conducted using ten different sowing dates ranging from April to early August, at eight locations across the Southeastern US. Additionally, data analyses were performed using principal component analysis to understand the major factors of soybean yield variability in this region and which management conditions could reduce the impact of EWE. Our results showed that soybean yield variability could be minimized through the adjustment of sowing dates according to ENSO phases that also impact the occurrence of EWE during reproductive and vegetative stages in this region.
... El Niño events bring hot weather to the terrestrial tropics, often accompanied by reduced rainfall 5 ; the resulting droughts reduce vegetative productivity and have increased in severity under climate warming 2 . The impact of ENSO phase on crop production has been demonstrated at spatial resolutions from smallscale farm studies (e.g. in rice 6 , coffee 7 , cocoa 8 ) disentangling vegetative responses to management, pests, disease and climate, to regional and national production 9,10 exploring the substantial geographic variation within responses 57 58 3 at regional and global scales 11 . Much crop-ENSO research has focused on annuals, the source of the majority of the world's food, and the short life cycle of these crops allows for direct inference of the impact of climate shocks. ...
... The larger body of research into ENSO impacts on annual crops includes many studies using long time series, reporting high heterogeneity in space and among crops 11,23,24 . However, there appears to be little examination of changes in the direction and magnitude of ENSO responses over time; thus our findings are timely and signal that further research is needed to examine how changing climates may force novel extreme climatic conditions and shift response patterns to ENSO phase. ...
Preprint
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Anthropogenic climate change causes more frequent and intense fluctuations in the El Niño Southern Oscillation (ENSO). Understanding the effects of ENSO on agricultural systems is crucial for predicting and ameliorating impacts on lives and livelihoods, particularly in perennial tree crops, which may show both instantaneous and delayed responses. Using cocoa production in Ghana as a model system, here we show that in recent times, El Niño years experience reductions in cocoa production followed by several years of increased production, a significantly different pattern than prior to the 1980s. ENSO phase affects the climate in Ghana, and over the same time period, we see concomitant significant shifts in the climatic conditions resulting from ENSO extremes, with increasing temperature and water stress. Our results illustrate the big data analyses necessary to improve understanding of perennial crop responses to climate change in general, and climate extremes in particular.
... These data are based on country-level crop statistics, which are disaggregated to 0.5º resolution using satellite-based net primary productivity estimates and spans 1981-2016 (data for 1984-2009 is utilized here). These data have also been used extensively in global studies about drivers of interannual crop yield variability (50,51). ...
... To remove temporal trends related to for example changes in management conditions, and thus to isolate interannual variability, for each raster cell the crop yield data was de-trended. The detrending was conducted by subtracting a five-year moving average from the annual values, similarly to several previously conducted studies about yield variability (4,50). The anomalies were then divided by five-year averages to obtain proportional annual deviation from the normal values. ...
Preprint
Full-text available
Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980-2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.
... However, recent research suggests that even metropolitan areas in developed countries can have emerging leptospirosis cases, which are more common during times of heavy rainfall and flooding [4], or after natural disasters such as hurricanes, which can trigger disease outbreaks [5]. Despite Colombia's diverse environment, a significant portion of the country has a tropical climate with the potential for constant rainfall and flooding due to the El Niño Southern Oscillation [6,7]. As a result, the Colombian territory is vulnerable to a high incidence of leptospirosis [8]. ...
Article
Full-text available
Gram-negative spirochete Leptospira spp. causes leptospirosis. Leptospirosis is still a neglected disease, even though it can cause potentially fatal infections in a variety of species including humans. The purpose of this study was to determine the seroprevalence of leptospirosis in pig farm captured rodents and characterize the isolated samples. Rats were captured, sampled, and euthanized in the vicinity of pig farms to obtain serum for microagglutination tests (MAT) and kidney tissues for PCR amplification of the 16S rRNA and LipL32 genes. A fraction of the 16S rRNA PCR product was sequenced and phylogenetically analyzed. The results showed a Leptospira seroprevalence of 13.8% (77/555) among the 555 captured rats. PCR positivity for Leptospira spp. reached 31.2% (156/500), and the positivity for pathogenic Leptospira spp. was 4% (22/500). Phylogenetic analysis matched eight samples with L. interrogans serovar icterohaemorrhagiae and two with L. interrogans serovar pyrogenes. Two sequences were located within the pathogenic Leptospira clade but did not match with any specific strain. The seroprevalence found in the rats around swine farms indicates a potential risk of transmission to the pigs. The identification of pathogenic Leptospira outlines the importance of more research as well as updating the current strategies for the diagnosis, control, and prevention of porcine leptospirosis in Colombia.
... The El Niño-Southern Oscillation (ENSO) is the Earth's most prominent driver for interannual climate variability, as highlighted by the occurrence of the latest extreme El Niño event in 2015/16 (Blunden and Arndt, 2016;Santoso et al., 2017). The pronounced global impacts of ENSO extend to social stability, food security, and marine habitats (e.g., Glantz, 2001;Iizumi et al., 2014;Barnard et al., 2015;Hardi-man et al., 2018), thus underscoring the necessity to improve understanding of ENSO dynamics for its accurate prediction and disaster risk reduction. ...
Article
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The 2015/16 El Niño displayed a distinct feature in the SST anomalies over the far eastern Pacific (FEP) compared to the 1997/98 extreme case. In contrast to the strong warm SST anomalies in the FEP in the 1997/98 event, the FEP warm SST anomalies in the 2015/16 El Niño were modest and accompanied by strong southeasterly wind anomalies in the southeastern Pacific. Exploring possible underlying causes of this distinct difference in the FEP may improve understanding of the diversity of extreme El Niños. Here, we employ observational analyses and numerical model experiments to tackle this issue. Mixed-layer heat budget analysis suggests that compared to the 1997/98 event, the modest FEP SST warming in the 2015/16 event was closely related to strong vertical upwelling, strong westward current, and enhanced surface evaporation, which were caused by the strong southeasterly wind anomalies in the southeastern Pacific. The strong southeasterly wind anomalies were initially triggered by the combined effects of warm SST anomalies in the equatorial central and eastern Pacific (CEP) and cold SST anomalies in the southeastern subtropical Pacific in the antecedent winter, and then sustained by the warm SST anomalies over the northeastern subtropical Pacific and CEP. In contrast, southeasterly wind anomalies in the 1997/98 El Niño were partly restrained by strong anomalously negative sea level pressure and northwesterlies in the northeast flank of the related anomalous cyclone in the subtropical South Pacific. In addition, the strong southeasterly wind and modest SST anomalies in the 2015/16 El Niño may also have been partly related to decadal climate variability.
... and thus the interannual variations in the WF are mainly driven by Y s response to climatic variability. For example, the WF peaks around 1988 and 2012 (see Fig. 6) are likely due to extreme La Niña-driven droughts in major maize-producing areas which caused substantial drops in crop yields (Iizumi et al., 2014;Rippey, 2015). A summary of global average annual WFs and main contributing factors during 1986-2016 is provided in Table S4. ...
Article
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Crop water productivity is a key element of water and food security in the world and can be quantified by the water footprint (WF). Previous studies have looked at the spatially explicit distribution of crop WFs, but little is known about their temporal dynamics. Here, we present AquaCrop-Earth@lternatives (ACEA), a new process-based global gridded crop model that can simulate three consumptive WF components: green (WFg), blue from irrigation (WFbi), and blue from capillary rise (WFbc). The model is applied to analyse global maize production in 1986–2016 at 5×5 arcmin spatial resolution. Our results show that over the 2012–2016 period, the global average unit WF of maize is 728.0 m3 t−1 yr−1 (91.2 % WFg, 7.6 % WFbi, and 1.2 % WFbc), with values varying greatly around the world. Regions with high-input agriculture (e.g. Western Europe and Northern America) show small unit WFs and low interannual variability, while low-input regions show opposite outcomes (e.g. Middle and Eastern Africa). From 1986 to 2016, the global average unit WF reduced by a third, mainly due to the historical increase in maize yields. However, due to the rapid expansion of rainfed and irrigated areas, the global WF of maize production increased by half, peaking at 768.3×109 m3 yr−1 in 2016. As many regions still have a high potential in closing yield gaps, unit WFs are likely to reduce further. Simultaneously, humanity's rising demand for food and biofuels may further expand maize areas and hence increase WFs of production. Thus, it is important to address the sustainability and purpose of maize production, especially in those regions where it might endanger ecosystems and human livelihoods.
... Four food crops (i.e., maize, rice, soybean, and wheat), and alfalfa, a fodder crop, were selected as these are widely produced and consumed across Africa. These crops are equally important as commodity crops for international trade (Lizumi et al., 2014). The CSI considered climate constraints, crop calendar, agroclimatic yields, and agro-ecological suitability and productivity for cultivated land areas. ...
Article
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Agricultural land area is increasing globally despite the loss of productive agricultural lands in some world regions. We examine the case of Africa where the knowledge about major agricultural land transitions and the impacts on the quality of land is still very limited. A comprehensive assessment of change in agricultural landscapes was conducted at the African continental scale. We identify influencing factors and model the quality of land associated with agricultural land gains and losses between 2000 and 2018. Land quality was established based on spatially-explicit analysis of varying Net Primary Productivity, soil organic carbon content, crop suit-ability and percent yield change for major crops of global importance grown across Africa such as maize, rice, soybean, wheat, and alfalfa. Distance to settlements was important in explaining agricultural land dynamics. Most land areas that transitioned to cropland in Africa were associated with large distances away from major roads. Poor access to major roads suggests the remoteness of gained croplands. Land quality was better in gained croplands than in those lost, whereas gained grasslands were of lesser quality compared to areas of grassland loss. Five typologies of African countries were developed based on net yield and amount of land cultivated per crop in cropland change areas. Type 1 typifies net yield increase and cultivated land decrease, while type 2 is characterized by yield increase consequent upon cropland expansion. Net yield and land remain unchanged in type 3, while in type 4 cultivated land increased but yield decreased as in 40% of African countries for maize, and in type 5, both yield and land area decreased. This study thus provides evidence about the quality of land in gained and lost agricultural areas and generalizable insights on their dynamics across Africa.
... In the context of the rapid increase in the global population, quantitative assessment of the impact of climate change on crop production is of great significance to ensure a stable supply of food [8,9]. A large number of studies have shown that climate extremes related to temperature and precipitation, such as heat, cold and drought, could severely reduce crop production from regional to global scale [10][11][12][13][14][15][16][17][18]. Adverse weather conditions will further exacerbate the gap between the rapidly increasing population and the limited food supply. ...
Article
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In the era of global climate change, extreme weather events frequently occur. Many kinds of agro-meteorological disasters that are closely related to environmental conditions (such as sunshine hours, temperature, precipitation, etc.) are witnessed all over the word. However, which factor dominates winter wheat production in the middle and lower reaches of the Yangtze River remains unresolved. Quantifying the key limiting meteorological factor could deepen our understanding of the impact of climate change on crops and then help us to formulate disaster prevention and mitigation measures. However, the relative role of precipitation, sunshine hours and maximum daily temperature in limiting winter wheat yield in the middle and lower reaches of the Yangtze River is not clear and difficult to decouple. In this study, we used statistical methods to quantify the effect of precipitation, maximum temperature and sunshine hours extremes on winter wheat (Triticum aestivum L.) yield based on long time-series, county-level yield data and a daily meteorological dataset. According to the winter wheat growing season period (October of the sowing year to May of the following year), anomaly values of cumulative precipitation, average sunshine hours and average daily maximum temperature are calculated. With the range of −3 σ to 3 σ of anomaly and an interval of 0.5 σ (σ is the corresponding standard deviation of cumulative precipitation, mean maximum temperature and mean sunshine hours, respectively), the corresponding weighted yield loss ratio (WYLR) represents the impact of this kind of climate condition on yield. The results show that excessive rainfall is the key limiting meteorological factor that can reduce winter wheat yield to −18.4% in the middle and lower reaches of the Yangtze River, while it is only −0.24% in extreme dry conditions. Moreover, yield loss under extreme temperature and sunshine hours are negligible (−0.66% for extremely long sunshine hours and −8.29% for extreme cold). More detailed analysis results show that the impact of excessive rainfall on winter wheat yield varies regionally, as it causes severe yield reductions in the Huai River basin and the middle to southern part with low elevation and rainy areas of the study area, while for drier areas in the Hubei province, there is even an increase in yield. Our results disclosed with observational evidence that excessive precipitation is the key meteorological limiting factor leading to the reduction in winter wheat yield in the middle and lower reaches of the Yangtze River. The knowledge of the possible impact of climate change on winter wheat yield in the study area allows policy-makers, agronomists and economists to better forecast a plan that differs from the past. In addition, our results emphasized the need for better understanding and further process-based model simulation of the excessive rainfall impact on crop yield.
... Extreme climatic events, especially El Nino or La Nina, result in (1) crop failure, reducing IP which leads to decreases productivity and production; (2) damage to agricultural land resources; (3) increasing frequency, area, and weight/intensity of drought; (4) increasing humidity; and (5) increased intensity of disturbance of plant pest organisms (OPT) (Skendžić, Zovko, Živković, Lešić, & Lemić, 2021). Iizumi et al. (2014) indicated that climatic anomalies such as El Nino have a negative impact on agricultural productivity. Climate change affects productivity and production in the agricultural sector, which has a negative socio-economic impact (Ketema & Negeso, 2020). ...
Article
Climate change is an extreme natural change condition due to global warming that cannot be avoided, and will have a broad impact on various aspects of life, including the agricultural sector. The impact of climate change that occurs in the agricultural sector, namely flood and drought that cause plants to crop failure , is becoming greater, causing significant reduction in agricultural production, especially rice, requiring that farmers have the ability to adapt to climate change. The purposes of this study are to analyze the relationship between the performance level of agricultural extension workers and the capacity level of farmers in regard to climate change adaptation, and to analyze the relationship between the level of farmer capacity in climate change adaptation and rice productivity. The research was conducted in Central Lampung Regency in 2019 using a total of 100 rice farmers. The data analysis method used is Spearman rank correlation analysis. The results show that the performance level of agricultural instructors is significantly related to the level of knowledge capacity, attitude, and skills of farmers in climate change adaptation. Knowledge capacity, attitude, and skills of farmers in climate change adaptation are significantly related to rice productivity.
... But we still need to pay more attention to regional grain self-sufficiency. Regional grain self-sufficiency can minimize the impact of adverse emergencies , such as the supply chain disruption caused by the recent COVID-19 epidemic and grain production decline in main grain producing areas caused by extreme weather events (Iizumi et al., 2014). Over-reliance on regional grain trade may lead to insufficient regional grain supply. ...
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China has implemented the world's largest‐ever vegetation restoration program in marginal mountainous areas to sustain life on land. However, land competition between the demand for grain and the need for green has threatened sustainable vegetation restoration. Here, focusing on China's marginal mountainous areas with the highest density of slope cropland, we explore the optimal solution in the trade‐offs between green and grain. We find that current vegetation restoration strategies are not sufficiently optimized, which may threaten the survival and development of local farmers and in turn destroy existing vegetation restoration achievements. Through adjusting vegetation restoration objectives carefully tailored to local conditions, the population experiencing grain shortages can be greatly reduced by 51–66% (from 18.26 million to 6.29–8.90 million) compared with the current scheme. The optimal design will alleviate the conflict between grain and green, thereby promoting sustainable ecological restoration in China. Our research provides an important reference for the world's mountainous areas to achieve a win‐win situation between green and grain.
... These modes interact with one another to drive complex and considerable interannual fluctuations in precipitation. They are often associated with extreme events over monsoon regions (Kane 1999;Kirono et al., 1999) with major impacts on water resources, crop production (Iizumi et al. 2014;Phillips et al. 2012;Ray et al. 2015) and long-term impacts on health (Bouma and Kaay, 1996;Gagnon et al. 2001;Hashizume et al. 2012). ...
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Modern observations show considerable interannual to interdecadal variability in monsoon precipitation. However, there are few reconstructions of variability at this timescale through the Holocene, and there is therefore less understanding of how changes in external forcing might have affected monsoon variability in the past. Here, we reconstruct the evolution of the amplitude of interannual to interdecadal variability (IADV) in the East Asian, Indian and South American monsoon regions through the Holocene using a global network of high-resolution speleothem oxygen isotope (δ ¹⁸ O) records. We reconstruct changes in IADV for individual speleothem records using the standard deviation of δ ¹⁸ O values in sliding time windows after correcting for the influence of confounding factors such as variable sampling resolution, growth rates and mean climate. We then create composites of IADV changes for each monsoon region. We show that there is an overall increase in δ ¹⁸ O IADV in the Indian monsoon region through the Holocene, with an abrupt change to present-day variability at ~2 ka. In the East Asian monsoon, there is an overall decrease in δ ¹⁸ O IADV through the Holocene, with an abrupt shift also seen at ~2 ka. The South American monsoon is characterised by large multi-centennial shifts in δ ¹⁸ O IADV through the early and mid-Holocene, although there is no overall change in variability across the Holocene. Our regional IADV reconstructions are broadly reproduced by transient climate-model simulations of the last 6 000 years. These analyses indicate that there is no straightforward link between IADV and changes in mean precipitation, or between IADV and orbital forcing, at a regional scale.
... However, ENSO is represented through the Oceanic Index of El Niño used to verify the relationships between the variability of SST and El Niño / La Niña events with environmental and socio-economic impacts felt worldwide (Koslow and Allen, 2011;Iizumi et al., 2014). However, the space-time in relation to the CPUE of the sardine (Faccin, 2013), the participation of areas further to the south (Santa Catarina and Parana), and areas more to the north (São Paulo and Rio de Janeiro) prevailed. ...
Preprint
Cephalopod fishing in Brazil has been on the rise as a result of the growing demand for high quality food. Therefore, for the sustainable exploitation of this resource, adequate evaluation and scientifically supported management strategies are necessary. Notably, the squid which belongs to the family Loliginidae are fishery resources of increasing importance in the marine ecosystem of the Continental Shelf Southeast and South of Brazil. However, information about stock status, knowledge of life history, ecology and the distribution of the early stages of its life cycle is still very insufficient. The present review analyzed more than 100 scientific articles, related to the history of life and ecology, the identification of the occurrence of cephalopods of the Loliginidae family in the region between Cabo de São Tomé (RJ) and Cananeia (SP), the patterns of family distribution to oceanographic processes that were identified from horizontal and vertical maps of abundance, temperature and salinity in plankton sampling collected by 11 oceanographic cruises conducted by the Oceanographic Institute of the University of São Paulo (USP) and published in 2013. Respectively, Generalized Linear Models (GLM) were used to detect the factors that would explain the occurrence and abundance of Loliginidae, which indicated the depth and sea surface temperature (SST), height of the sea surface (HSS), salinity of the sea surface (SSS), chlorophyll-a concentration Sea Surface Temperature (SST) and plankton density (PD). Also, a Redundancy Analysis (RDA) revealed the main distribution patterns observed for the three main species of Loliginidae in relation to the oceanographic variables. Doryteuthis sanpaulensis predominated in the northern region of the sampling area, associated with cold waters and resurgence events. Doryteuthis pleii occurred mainly in the southern region of the study area in warmer waters. Lolliguncul brevis was found only in the estuarine region of Santos, i.e in the shallow and less saline waters. The results obtained represents a relevant contribution to sustainable management for the exploitation of these resources and also contributes to the knowledge about squid fishing oceanography in the regional marine ecosystem.
... This result is supported by the research of [20] which stated that rice production during El Nino decreased by 4.15% compared to normal but increased by 1.45% during La Nina. [21] also revealed that El Nino negatively affects rice production in Southeast Asia, China, India, Central Asia, Sub Saharan Africa, and some parts in Brazil. ...
Article
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Climate change has become an pivotal issue and impacted on the socio-economic community because it contributes not only to prolonged land droughts and fires in the dry season but also to increased rainfall and flooding in the wet season. One of the climate change phenomena in Indonesia is El Nino Southern Oscillation (ENSO) consisting of El Nino and La Nina. The ENSO phenomenon drives rainfall variability that impacts on the agricultural sector which depends on water availability. The objective of this study was to analyse the impact of El Nino and La Nina on the prices of six agricultural food crops using static panel data. The data used consist of 23 provinces affected by El Nino and La Nina in 2010-2017. Rainfall is used as a proxy for El Nino and La Nina, supported by a negative and significant correlation between Oceanic Nino Index (ONI) and rainfall. The results showed that El Nino has greater impacts on food prices than La Nina by increasing the price of rice, sweet potato, and mung bean. While La Nina has a significant impact in increasing the price of cassava. Considering the importance of food crops for Indonesians, efforts can be made to improve community resilience, such as using adaptive varieties of climate, developing agricultural insurance, time and planting patterns adjustment and agroforestry patterns for communities nearby the forests in the framework of climate change mitigation and adaptation. Ultimately, this study can provide important insights to formulate effective mitigation and adaptation strategies to minimize the climate change impact.
... Variations in this gradient produce the El Niño-Southern Oscillation-a dominant mode of interannual climate variability in the tropics and beyond 18 . In addition, vigorous upwelling in the eastern tropical Pacific brings low-pH, nutrient-rich water up into the surface ocean, supporting highly productive marine ecosystems that are important to the economic health and food security of adjacent nations 19,20 . ...
Article
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Ocean dynamics in the equatorial Pacific drive tropical climate patterns that affect marine and terrestrial ecosystems worldwide. How this region will respond to global warming has profound implications for global climate, economic stability and ecosystem health. As a result, numerous studies have investigated equatorial Pacific dynamics during the Pliocene (5.3–2.6 million years ago) and late Miocene (around 6 million years ago) as an analogue for the future behaviour of the region under global warming1–12. Palaeoceanographic records from this time present an apparent paradox with proxy evidence of a reduced east–west sea surface temperature gradient along the equatorial Pacific1,3,7,8—indicative of reduced wind-driven upwelling—conflicting with evidence of enhanced biological productivity in the east Pacific13–15 that typically results from stronger upwelling. Here we reconcile these observations by providing new evidence for a radically different-from-modern circulation regime in the early Pliocene/late Miocene¹⁶ that results in older, more acidic and more nutrient-rich water reaching the equatorial Pacific. These results provide a mechanism for enhanced productivity in the early Pliocene/late Miocene east Pacific even in the presence of weaker wind-driven upwelling. Our findings shed new light on equatorial Pacific dynamics and help to constrain the potential changes they will undergo in the near future, given that the Earth is expected to reach Pliocene-like levels of warming in the next century.
... Long-term climatic cycles, such as El Niño Southern Oscillation (ENSO) events, could also play a role, particularly in rainfed systems that we may expect to exhibit stronger variability than their irrigated counterparts. ENSO phases have been shown to induce synchrony in masting systems [35,[65][66][67], but knowledge of ENSO effects on crop plants is largely limited to annual crops [68,69]. As a primary source of climate variation in Brazil and Iran, ENSO could be a cause of periodic yield in Brazilian tangerine and Iranian apricot (figure 4e,f; [70,71]). ...
Article
Cyclical fluctuations in reproductive output are widespread among perennial plants, from multi-year masting cycles in forest trees to alternate bearing in horticultural crops. In natural systems, ecological drivers such as climate and pollen limitation can result in synchrony among plants. Agricultural practices are generally assumed to outweigh ecological drivers that might synchronize alternate-bearing individuals, but this assumption has not been rigorously assessed and little is known about the role of pollen limitation as a driver of synchrony in alternate-bearing crops. We tested whether alternate-bearing perennial crops show signs of alternate bearing at a national scale and whether the magnitude of national-scale alternate bearing differs across pollination syndromes. We analysed the Food and Agriculture Organization of the United Nations time series (1961–2018) of national crop yields across the top-producing countries of 27 alternate-bearing taxa, 6 wind-pollinated and 21 insect-pollinated. Alternate bearing was common in these national data and more pronounced in wind-pollinated taxa, which exhibited a more negative lag-1 autocorrelation and a higher coefficient of variation (CV). We highlight the mutual benefits of integrating ecological theory and agricultural data for (i) advancing our understanding of perennial plant reproduction across time, space and taxa, and (ii) promoting stable farmer livelihoods and global food supply. This article is part of the theme issue ‘The ecology and evolution of synchronized seed production in plants’.
... This may be due to insufficient observation or experience by farmers to cope with unprecedented situations in time, posing a risk of loss of productivity and increased pro-unprecedented situations in time, posing a risk of loss of productivity and increased production costs [3]. ENSO-related climate variability exerts strong influences on agricultural production in different regions, including in Thailand [4][5][6][7][8][9]. ...
Article
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The purpose of this research is to study the spatial and temporal groupings of 124 meteorological stations in Thailand under ENSO. The multivariate climate variables are rainfall, relative humidity, temperature, max temperature, min temperature, solar downwelling, and horizontal wind from the conformal cubic atmospheric model (CCAM) in years of El Niño (1987, 2004, and 2015) and La Niña (1999, 2000, and 2011). Euclidean distance timed and spaced with average linkage for clustering and silhouette width for cluster validation were employed. Five spatial clusters (SCs) and three temporal clusters (TCs) in each SC with different average precipitation were compared by El Niño and La Niña. The pattern of SCs and TCs was similar for both events except in the case when severe El Niño occurred. This method could be applied using variables forecasted in the future to be used for planning and managing crop cultivation with the climate change in each area.
... E l Niño-Southern Oscillation (ENSO) is the leading mode of tropical climate variability, with impacts on ecosystems, agriculture, freshwater supplies and hydropower production spanning much of the globe [1][2][3] . The majority of impact studies, including seasonal to multi-year predictions, has developed from a canonical representation of ENSO, as characterised by seasurface-temperature anomalies (SSTa) in the central-eastern Pacific [4][5][6] . ...
Article
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El Niño-Southern Oscillation (ENSO) shows a large diversity of events that is modulated by climate variability and change. The representation of this diversity in climate models limits our ability to predict their impact on ecosystems and human livelihood. Here, we use multiple observational datasets to provide a probabilistic description of historical variations in event location and intensity, and to benchmark models, before examining future system trajectories. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. Some climate models are capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century.
... El Niño-related effects on freshwater and brackish-water fishes have already been reported for Suriname [5]. Iizumi et al. [6] highlighted the importance of ENSO for global crop production. The effects of El Niño climate change on forest resources tend to be less dramatic than for annual crops due to the longevity of trees. ...
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In this study, we used retrospective dendroclimatological analyses to explore whether El Niño Southern Oscillation (ENSO) and local precipitation patterns have an influence on tree growth in Suriname, a country located on the Guiana Shield, as annual precipitation patterns on the Guiana Shield are related to ENSO. Discs were taken from 20 trees of Cedrela odorata, whose stem forms very distinct annual growth rings, for tree ring analyses. The trees grew in unmanaged tropical wet forests of Suriname. The tree-ring series of individual trees started between 1836 and 1931 and extended over a period of 84–180 years. The 20 dated series were utilized for constructing a tree-ring chronology. Unlike many other studies that used local anomalies such as flood pulse, precipitation, and drought events to describe the influence of El Niño on tree growth, we used monthly precipitation and ENSO indices as predictors of tree growth to calculate response and correlation functions. The study observed that tree ring growth of Cedrela odorata is influenced by precipitation in August and June of the current year and in August of the previous year, as well as by the ENSO indices SSTA, TSA, TNA, and NAO. Systematic increases in the strength of the El Niño southern oscillation (ENSO) teleconnection due to climate change could affect the growth of trees on the Guiana Shield.
... En particular se han identificado importantes impactos del fenómeno ENSO (El Niño-Oscilación del Sur) sobre la agricultura mundial, generando pérdidas o ganancias en la actividad de acuerdo a la región y fase del fenómeno (Anderson-teixeira et al., 2012;Iizumi et al., 2014). El interés por la relación entre los rendimientos y el ENSO se basa en la posibilidad de disponer de pronósticos climáticos estacionales para un determinado ciclo del cultivo con varios meses de anticipación (Ceglar et al. 2017). ...
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Resumen La variabilidad climática es el principal determinante de las fluctuaciones en los resultados productivos y económicos de la agricultura. Debido al Cambio Climático, se espera que en los próximos años ocurran eventos extremos con mayor frecuencia e intensidad. Ante este escenario, los estudios relacionados con los efectos de la variabilidad climática sobre la producción agropecuaria son de especial interés. Este estudio analiza las series de tiempo de rendimientos a nivel de partido de los principales cultivos en la provincia de Buenos Aires, en el período 2000/01-2020/21. Se identifica la tendencia y ocurrencia de valores extremos en los rendimientos de trigo, maíz y soja. Las frecuencias de valores extremos se relacionan con las fases del fenómeno ENSO (El Niño-Oscilación del Sur) observadas para cada campaña. Se estiman los valores económicos de las pérdidas/ganancias en la producción de los tres cultivos con respecto a los valores esperados para cada campaña. Los rendimientos muestran tendencias positivas significativas en 78%, 46% y 30% de los partidos para trigo, maíz y soja, respectivamente. Hay una relación significativa entre las frecuencias de valores extremos de rendimientos y las fases del ENSO, siendo esta relación más importante en los cultivos de verano. Se destaca, en particular, una frecuencia relativa del 38 y 41% para rendimientos extremadamente bajos o muy bajos, en campañas clasificadas como segunda La Niña consecutiva, para maíz y soja, respectivamente. Mientas que las frecuencias de rendimientos extremadamente bajos o muy bajos en campañas clasificadas como año neutro o El Niño son entre 0%-3%. En cuanto al valor económico de las cosechas de los tres cultivos, las diferencias entre los valores obtenidos vs. esperados acumuladas en el período, son valores positivos de +3285 y +872 mill usd en años "El Niño" para las regiones norte y sur, respectivamente, y negativas de-3387 y-388 mill usd, en años "La Niña" para ambas zonas respectivamente. Los resultados aportan evidencia sobre el potencial valor de los pronósticos estacionales basados en el ENSO para la agricultura. Sin embargo, es necesario profundizar en el análisis sobre los efectos del ENSO y otros fenómenos estacionales sobre los rendimientos. Siendo también necesaria más información sobre las actitudes de los productores pampeanos y las distintas alternativas de manejo disponibles frente a estos pronósticos.
... The drought conditions during an El Niño phase within the Philippines is induced by the late onset of the rainy season, early termination of the rainy season, or a weak monsoon system characterized by isolated heavy rainfall events of short-durations (Lansigan et al., 2000). The large agronomic sectors in multiple tropical Pacific Ocean island nations rely on seasonal rainfall for crop production with multiple studies highlighting the loss in crop production during El Niño events (Lansigan et al., 2000;Naylor et al., 2001;Iizumi et al., 2014;Stuecker et al., 2018). With data spanning 1987-2016 C.E., Stuecker et al. (2018) demonstrate that a decrease in rice production as a response to soil-moisture deficits is associated with the El Niño phase of ENSO for the Philippines. ...
Article
Study region Western Tropical Pacific Ocean (Philippines) Study focus El Niño Southern Oscillation (ENSO) modulates rainfall amount variability and, by extension, river discharge for the Philippines on seasonal to interannual temporal scales. The El Niño phase of ENSO considerably decreases rainfall amounts on a seasonal scale with varying degrees of heterogeneity across the Philippines. The hydrological response of El Niño on an interannual scale is relatively immature. To investigate the hydrological response, a composite time series of 29 rainfall and 61 river discharge stations spanning 1901–2020 and 1908–2017 C.E., respectively, and covering the four major climate types in the Philippines were critically assessed. New hydrological insights for the region Our statistical analyses results of a 100-year dataset demonstrate a decreasing trend compared to pre-El Niño conditions for both river discharge and rainfall. The median response suggests the decreasing trend can last up to 7 years regardless of climate type. Rainfall amount returns to pre-El Niño conditions faster than river discharge. The sign (increasing or decreasing) of the hydrological response is either decreasing, if at conception of an El Niño phase, or increasing, if at the termination of an El Niño phase. Our results have implications for water resource management and water resiliency of island nations that strongly rely on the timely delivery of rainfall amount. Further, our results highlight the legacy effects of El Niño events that likely initiate long-term droughts for island nations in western tropical Pacific Ocean.
... Lubinga et al. (2019) found that variation in the yields of maize was much more influenced by the increase in minimum temperature and soil management practices than other climatic variables, including El Nino and La Nina in Mpongwe, a district in the same agroecological zone III as Chingola district on the Copperbelt province, Zambia. Iizumi et al. (2014) ascertained that with supplementary irrigation, the effect of El Nino on maize yield can be mitigated. However, considering the level of income, this option will be limited to the majority of the population living below the poverty line. ...
Article
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This study uses remote sensing and GIS techniques to examine the intensity and dynamics of land use/cover change and environmental indices across a four-decade period in the Chingola district of Zambia, from 1972 to 2020 using five classification stages (1972, 1992, 2001, 2013, and 2020). A total of 10 key climate change detection monitoring indices were generated using RClimDex to examine the implications of land degradation on the bioclimatic factors from 1983 to 2020. The findings revealed a significant expansion in Built-ups (7.3%/year), farmlands (3.18%/year), and mining areas (0.82%/year) at the expense of natural resources. The highest human pressure was exerted on Savannah woodlands (À0.78), through agriculture (0.76) and infrastructure development (0.44) between 1992 and 2001.The analysis of the bioclimatic indices revealed a significant decline in rainfall quantity and intensity, and a rising in temperature (warmer days and nights). The Annual rainfall has decreased by À3.25%, while the potential evapotranspiration has increased by 0.04% from 1983 to 2020, resulting in an Aridity Index of 0.60 and a moisture deficit index of À0.42. To offset agriculture's propensity to spatially expand and further encroach into savannah woodlands and forests , urban containment policies and programs that stimulate agricultural intensification are needed to reduce urban sprawl and protect the city's remaining forestlands. HIGHLIGHTS The most significant changes in LULC in Chingola occurred between 2001 and 2013 with a CLUDI of (623). It was observed that the days and nights are becoming warmer given the trend TX90p and TN90p. The PET analysis showed the years A declining trend was observed in NDVI, NDWI, NDMI, and NDSI over the study period (1972-2020). The highest human pressure was exerted on Savannah woodlands with an urban sprawl index of (À0.78). The year 1998 was identified as the hottest and driest of 1983-2020 timeseries.
... It is common knowledge that the crop yield and the N fates were strongly affected by climate factors (Saddique et al., 2020), and understanding the major pathways of N loss could promote the development of best management practices (Jing et al., 2017). The climate factors are sensitive to global weather pattern with a cycle lasts for 6-8 years, i.e., EI Niño and La Niña events (Li et al., 2020;Iizumi et al., 2014). Results based on multi-year research can provide convincing evidence to clarify the general role of yield stability and N fates (Körschens, 2006). ...
Article
Rainfed agriculture is important to meet the increasing demands of food production. However, there is a lack of knowledges for the rainfed wheat systems in abundant rainfall areas, where the erratic rainfall may constrain the wheat yield and increases N losses from wheat fields with excessive fertilizer inputs. In the present study, a 6 consecutive years field experiments were conducted to investigate the wheat yield and N losses responses to different N fertilizer rates in the Taihu Lake region. Despite the fluctuations in the wheat yield, a 10–30% reduction of the district average N input sustained the current-level of wheat yield for the 6 consecutive years. The N rate of 168 kg ha⁻¹ might be the threshold N application rate, because if it was exceeded, it was no longer the predominant factor determining the wheat yield, but significantly increased the N losses fluxes. The seasonal total N losses fluxes were 69.2 kg N ha⁻¹, which accounted for 28.8% of district averaged N input. Runoff was the predominant pathway of N loss from the wheat field, followed by ammonia volatilization and leaching. Nitrate was the predominant form in the runoff and leakage water. Seasonal cumulative nitrate losses via runoff and ammonia volatilization averaged 25.2 and 20.1 kg ha⁻¹ per wheat season, respectively, corresponding to 10.5% and 8.38% of the regional N application rates. However, the seasonal nitrate loss via leakage was the lowest, less than 8.98 kg ha⁻¹. Reducing the fertilizer N rates significantly decreased the N losses via runoff and ammonia volatilization, but not by leaching. Our findings indicated that reducing N fertilizer was impressive for the sustainable development of agriculture in Eastern China and 168 kg N ha⁻¹ was recommended for the rainfed wheat.
... However, it would be a mistake to think of El Niño as a slight warming of ocean temperatures in the Pacific accompanied by storms, heavy precipitation, and unusual weather patterns. A large number of studies highlight the potential economic implications of such global climatic fluctuations resulting in a downturn phase of the business cycle, to some extent, but primarily having an inflationary impact via increases in agricultural commodity and crude oil prices (see for example, Handler and Handler (1983); Changnon (1999); Brunner (2002); Laosuthi and Selover (2007); Ubilava (2012Ubilava ( , 20172018); Ubilava and Holt (2013); Iizumi et al. (2014); Cashin et al. (2017); Smith and Ubilava (2017); Peersman (2020); Qin et al. (2020); De Winne and Peersman (2021a), and references cited therein). ...
Article
Recent studies show that El Niño episodes are generally inflationary because they tend to increase the prices of agricultural commodities and crude oil. Given this, in this paper we examine the inflation-hedging property of gold (along with silver) from a novel perspective by analysing the impact of a negative shock to the negative component of Southern Oscillation Index (SOI) anomalies, i.e., El Niño shock. To this end, we apply a large-scale global vector autoregressive (GVAR) model to 33 countries covering both developed and emerging markets using quarterly data from 1980:Q2 to 2019:Q4. The GVAR methodology provides an appropriate framework to capture the transmission of global climate-related shocks while simultaneously accounting for individual country peculiarities. The results show that both gold and silver serve as good hedges in periods of inflation and rare disaster risks resulting from El Niño negative shocks. Interestingly, silver is a better hedge than gold, as implied by bigger positive real returns in response to El Niño shock. At the same time, La Niña shocks, captured by a positive effect to the positive component of SOI anomalies, fail to have a statistically significant impact on either gold or silver real returns. Overall, our results confirm the inflation-hedging benefits offered by the two precious metals, suggesting that investors can offset losses resulting from inflation-related risks stemming from El Niño events by investing not only in gold, but more so in silver.
... In the Pacific Northwest (PNW) of North America, the climate is influenced by multiple ocean-atmosphere teleconnections that vary seasonally, annually and decadally. Important teleconnections that prevail in the Pacific region are the Pacific Decadal Oscillation (PDO), El Niño-Southern Oscillation (ENSO) and the Northern Annular Mode (NAM), which can have severe and wide-reaching influences on ecosystems (Mantua et al. 1997;Iizumi et al. 2014). Furthermore, across the PNW, the North Pacific High (NPH) and the Aleutian Low (AL) modulate the strong seasonality in the region. ...
Article
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A diatom record from Moss Lake, Washington, USA spans the last 14,500 cal year and revealed Holocene climate change in the Pacific Northwest (PNW), including evidence for periodicities related to ocean-atmosphere teleconnections and/or variations in solar output. Three main climate phases were identified: (i) Late Pleistocene to early Greenlandian (until 10,800 cal year BP, spanning GI-1, GS-1), with a cold climate and low diatom abundance; (ii) early Greenlandian to Northgrippian (10,800–7500 cal year BP), shifting to a warmer climate; and (iii) late Northgrippian and Meghalayan from 7500 cal year BP onwards, with a cooler, moist climate. These climate shifts are in good agreement with the pollen record from the same core and other regional studies. Fluctuations in Discostella pseudostelligera and Aulacoseira taxa suggest climate cycles of different frequency and amplitude throughout the record. Spectral and wavelet analyses revealed periodicities of approximately 1400 and 400–500 years. We interpret the ~ 1400-year and ~ 400–500-year cycles to reflect alternating periods of enhanced (and reduced) convective mixing in the water column, associated with increased (and decreased) storms, resulting from ocean–atmosphere teleconnections in the wider Pacific region. The ~ 1400-year periodicity is evident throughout the Late Pleistocene and late Northgrippian/Meghalayan, reflecting high-amplitude millennial shifts from periods of stable thermal stratification of the water column (weak wind intensity) to periods of convective mixing (high wind intensity). The millennial cycle diminishes during the Greenlandian, in association with the boreal summer insolation maximum, consistent with suppression of ENSO-like dynamics by enhanced trade winds. Ocean–atmosphere teleconnection suppression is recorded throughout the PNW, but there is a time discrepancy with other records, some that reveal suppression during the Greenlandian and others during the Northgrippian, suggesting endogenic processes may also modulate the Moss Lake diatom record. The large amplitude of millennial variability indicated by the lake data suggests that regional climate in the PNW was characterised over the longer term by shifting influences of ocean–atmosphere dynamics and that an improved understanding of the external forcing is necessary for understanding past and future climate conditions in western North America.
... Second, previous efforts to estimate crop yield based on ML or DL models were mainly conducted within a nation, or even at a sub-national scale (Cai et al., 2019;Gomez et al., 2021). Mapping spatially explicit crop production for the global major breadbaskets is of great significance, especially for assessing climate change impact and planning effective adaptations, but has not been conducted so far (Iizumi et al., 2014a). ...
Article
Assessing global food security and developing sustainable production systems need spatially explicit information on crop harvesting areas and yields; however the available datasets are spatially and temporally coarse. Here, we developed a general framework, Global Wheat Production Mapping System (GWPMS), to map the spatial distribution of wheat harvesting area and estimate yield using data-driven models across eight major wheat-producing countries worldwide. We found GWPMS could not only generate robust wheat maps with R² consistently greater than 0.8, but also successfully captured a substantial fraction of yield variations with an average of 76%. The developed long short-term memory model outperformed other machine learning algorithms because it characterized the nonlinear and cumulative impacts of meteorological factors on yield. Using the derived wheat maps improved R² by 6.7% compared to a popularly used dataset. GWPMS is able to map spatial distribution of harvesting areas in a scalable way and further estimate gridded-yield robustly, and it can be applied globally using publicly available data. GWPMS and the resultant datasets will greatly accelerate our understanding and studies on global food security.
... In this sense, El Niño-Southern Oscillation phenomenon (ENSO) influences rainfall amount and its pattern in some regions of the Southern Cone (Grimm et al., 2000). Generally, the "El Niño" phase generates an increase in spring/summer rainfalls, resulting in high yields in the summer crops, while the opposite occurs with "La Niña" phase (Iizumi et al., 2014;Podestá et al., 1999). Likewise, soil water holding capacity which depends on the effective depth (i.e. ...
Article
Soybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.
... The El Niño Southern Oscillation (ENSO), with its alternating warming (El Niño), cooling (La Niña), and neutral phases, is one of the most important climate phenomena due to its ability to modify the global atmospheric circulation and the temperature and precipitation patterns across the globe [5]. The ENSO has significant cascade effects on ecosystems [6][7][8] and agriculture productivity [9]. ENSO-related climate variability is also a known driver of the emergence and outbreaks of infectious diseases [3,10]. ...
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... This was shown to happen for a wide range of systems: primary production in oceans [25], crop yield [26], malaria [27] and fisheries [28]. This higher predictability increases the prospects of predicting climatic variability effects on populations [26][27][28][35][36][37]. ...
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... ENSO is a climate pattern that is associated with changes in the temperatures of waters in the central and eastern tropical Pacific Ocean and influences weather, and rainfall. El Niño and La Niña are extreme phases of this cycle and El Niño is linked to crop production (Handler and Handler, 1983;Iizumi et al., 2014;Hsiang and Meng, 2015). Moreover, ENSO plays an important role in real commodity price fluctuations and influences not only certain geographical areas, but also the world economy. ...
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Chapter
Asia-RiCE collaborates and jointly works with the ASEAN Food Security Information System (AFSIS) to provide Rice Growth Outlook (RGO). This activity uses satellite derived agrometeorological information such as precipitation, Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), solar radiation and soil moisture collected and shared through JAXA’s Satellite-based Monitoring Network (JASMIN), a system developed by JAXA. In this study, the regional collaborative activities among space agencies and agricultural ministries in developing monthly RGO is summarized. RGO is published through the collaborative efforts and it provides rice-growing conditions and yield prospects by combining field information with satellite data. Monthly RGO information is provided to Crop Monitor, operated by GEOGLAM; then the Crop Monitor and the RGO are submitted to Agricultural Market Information System (AMIS) endorsed at the meeting of G20 Agricultural Ministers in 2011. Finally, a Market Monitor, including the Crop Monitor, is published by AMIS ten times a year.
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The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. This book uses a decade of primary research to examine how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in food-insecure regions of the world. The author reviews environmental, economics and multidisciplinary research to describe the connection between global environmental change, changing weather conditions and local staple food price variability. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation’s World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. These datasets are used to describe the connection, and to demonstrate the importance of these metrics in overall outcomes in food-insecure communities. © 2014 United States Government as represented by the Administrator of the National Aeronautics and Space Administration.
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El Niño-Southern Oscillation (ENSO) contributes to climate anomalies, especially those related to regional rainfall, which affect crop production. Although the North China Plain (NCP) is the most important agricultural production region in China, the impact of ENSO events on local climate and crop production has received only limited attention. Therefore, the impact of different phases of ENSO on local climate and production of winter wheat and summer maize, both rain fed and irrigated, was investigated at three sites using the agricultural production systems simulator model. Data on daily temperature, precipitation, and sunshine hours for 50 years (1956–2006) were analysed to build climate scenarios for three categories of ENSO: years with El Niño events, years with La Niña events, and neutral years. The pattern of climate change was generally similar across the three sites: annual precipitation decreased slightly and annual mean sunshine hours decreased significantly, whereas annual mean minimum temperature increased significantly, leading to a significant increase in mean air temperature. Precipitation decreased and temperature and sunshine hours increased in both El Niño and La Niña years but remained stable in neutral years. Under full irrigation, the probability of exceeding distribution that crop yield would be higher was not markedly affected (P > 0.05), although the yields in both El Niño and La Niña years differed markedly from those in neutral years, especially in maize. Under rain-fed conditions, the yield of maize was decreased greatly (P < 0.05), the probability distribution of such reduction being the highest in La Niña years at all the sites (P < 0.05). At the provincial level, yields from well-managed fields differed (P > 0.05) with the ENSO category: production of maize was more vulnerable than that of wheat in El Niño and La Niña years. El Niño and La Niña had similar effects on climatic variables across the NCP: low yields in El Niño and La Niña years due to lower precipitation and high yields in neutral years due to longer sunshine hours and additional irrigation.
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A principal component decomposition of monthly sea surface temperature (SST) variability in the tropical Pacific Ocean demonstrates that nearly all of the linear trends during 1950–2010 are found in two leading patterns. The first SST pattern is strongly related to the canonical El Niño-Southern Oscillation (ENSO) pattern. The second pattern shares characteristics with the first pattern and its existence solely depends on the presence of linear trends across the tropical Pacific Ocean. The decomposition also uncovers a third pattern, often referred to as ENSO Modoki, but the linear trend is small and dataset dependent over the full 61-year record and is insignificant within each season. ENSO Modoki is also reflected in the equatorial zonal SST gradient between the Niño-4 region, located in the west-central Pacific, and the Niño-3 region in the eastern Pacific. It is only in this zonal SST gradient that a marginally significant trend arises early in the Northern Hemisphere spring (March–May) during El Niño and La Niña and also in the late summer (July–September) during El Niño. Yet these SST trends in the zonal gradient do not unequivocally represent an ENSO Modoki-like dipole because they are exclusively associated with significant positive SST trends in either the eastern or western Pacific, with no corresponding significant negative trends. Insignificant trends in the zonal SST gradient are evident during the boreal wintertime months when ENSO events typically mature. Given the presence of positive SST trends across much of the equatorial Pacific Ocean, using fixed SST anomaly thresholds to define ENSO events likely needs to be reconsidered.
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Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
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Impacts of Indian Ocean Dipole mode (IOD) events on global climate are estimated by correlation/regression analysis. The analysis examined land rain and temperature and 3-dimensional atmospheric variables for a 42 yr period from January 1958 to December 1999. The correlation between IOD and the El Niño Southern Oscillation (ENSO) is accounted for using the multiple regression technique. We used partial correlation coefficients to describe the unique contribution of IOD to climate variability, independent of ENSO. In the Indian Ocean rim countries, IOD is associated with significant temperature and rain variability manifesting 2 large-scale patterns. In one, land tem- perature and rain are anomalously high over countries west of the Indian Ocean and anomalously low to its east. In the second pattern, enhanced rainfall is found over the Asian monsoon trough, extending from Pakistan up to southern China. Also noted are IOD impacts on several regions remote from the Indian Ocean. Strong correlation is found over Europe, northeast Asia, North and South America and South Africa concurrent with IOD events. Over these regions, positive IOD events are associated with warm land surface anomalies and reduced rainfall. The troposphere above the Indian Ocean exhibits strong variability during IOD events characterized by the following structures: (1) a Walker cell anomaly over the equator; (2) a deep modulation of monsoon westerlies; and (3) a Hadley cell anomaly over the Bay of Bengal. In the extratropics, IOD is associated with equivalent barotropic geopotential anomalies. These assume annular structure in the northern hemisphere, but Rossby wave train structure in the southern hemisphere.
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Predicting how the El Niño/Southern Oscillation (ENSO) will change with global warming is of enormous importance to society. ENSO exhibits considerable natural variability at interdecadal-centennial timescales. Instrumental records are too short to determine whether ENSO has changed and existing reconstructions are often developed without adequate tropical records. Here we present a seven-century-long ENSO reconstruction based on 2,222 tree-ring chronologies from both the tropics and mid-latitudes in both hemispheres. The inclusion of tropical records enables us to achieve unprecedented accuracy, as attested by high correlations with equatorial Pacific corals and coherent modulation of global teleconnections that are consistent with an independent Northern Hemisphere temperature reconstruction. Our data indicate that ENSO activity in the late twentieth century was anomalously high over the past seven centuries, suggestive of a response to continuing global warming. Climate models disagree on the ENSO response to global warming, suggesting that many models underestimate the sensitivity to radiative perturbations. Illustrating the radiative effect, our reconstruction reveals a robust ENSO response to large tropical eruptions, with anomalous cooling in the east-central tropical Pacific in the year of eruption, followed by anomalous warming one year after. Our observations provide crucial constraints for improving climate models and their future projections.
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The United States is currently responsible for 40%–45% of the world’s corn supply and 70% of total global exports [the U.S. Department of Agriculture–National Agricultural Statistics Service (USDA–NASS)]. Therefore, analyses of the spatial and temporal patterns of historical U.S. corn yields might provide insight into future crop-production potential and food security. In this study, county-level maize yield data from 1910 to 2001 were used to characterize the spatial heterogeneity of yield growth rates and interannual yield variability across the U.S. Corn Belt. Widespread decadal-scale changes in corn yield variability and yield growth rates have occurred since the 1930s across the Corn Belt, but the response has varied substantially with geographic location. Northern portions of the Great Plains have experienced consistently high interannual corn yield variability, averaging 30%–40% relative to the mean. Increasing usage of irrigation in Nebraska, Kansas, and Texas, since the 1950s, has helped boost yields by 75%–90% over rain-fed corn, creating a yield gap of 2–4 T ha−1 between irrigated and nonirrigated corn that could potentially be exploited in other regions. Furthermore, irrigation has reduced interannual variability by a factor of 3 in these same regions. A small region from eastern Iowa into northern Illinois and southern Wisconsin has experienced minimal interannual yield variability, averaging only 6%–10% relative to mean yields. This paper shows that the choice of time period used for statistical analysis impacted conclusions drawn about twentieth-century trends in corn yield variability. Widespread increases in yield variability were apparent from 1950 onward, but were not significant over the entire 1930–2001 period. There is also evidence that yield variability decreased from the early 1990s to 2001. Corn yield growth rates peaked at an annual-average rate of 3%–5% in the 1960s (124.5 kg ha−1 yr−1), but have steadily declined to a relative rate of 0.78% yr−1 (49.2 kg ha−1 yr−1) during the 1990s. A general inverse relationship between increasing corn yield and decreasing yield growth rates was noted after county-level yields reached 4 T ha−1, suggesting that widespread, significant increases in corn yield are not likely to take place in the future, particularly on irrigated land, without a second agricultural revolution.
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We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.
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For the tropical Pacific and Atlantic oceans, internal modes of variability that lead to climatic oscillations have been recognized, but in the Indian Ocean region a similar ocean-atmosphere interaction causing interannual climate variability has not yet been found. Here we report an analysis of observational data over the past 40 years, showing a dipole mode in the Indian Ocean: a pattern of internal variability with anomalously low sea surface temperatures off Sumatra and high sea surface temperatures in the western Indian Ocean, with accompanying wind and precipitation anomalies. The spatio-temporal links between sea surface temperatures and winds reveal a strong coupling through the precipitation field and ocean dynamics. This air-sea interaction process is unique and inherent in the Indian Ocean, and is shown to be independent of the El Niño/Southern Oscillation. The discovery of this dipole mode that accounts for about 12% of the sea surface temperature variability in the Indian Ocean--and, in its active years, also causes severe rainfall in eastern Africa and droughts in Indonesia--brightens the prospects for a long-term forecast of rainfall anomalies in the affected countries.
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The Earth's climate is constantly changing. Some of the changes are progressive, while others fluctuate at various time scales. The El Niño-la Niña cycle is one such fluctuation that recurs every few years and has far-reaching impacts. It generally appears at least once per decade, but this may vary with our changing climate. The exact frequency, sequence, duration and intensity of El Niño's manifestations, as well as its effects and geographic distributions, are highly variable. The El Niño-la Niña cycle is particularly challenging to study due to its many interlinked phenomena that occur in various locations around the globe. These worldwide teleconnections are precisely what makes studying El Niño-la Niña so important. Cynthia Rosenzweig and Daniel Hillel describe the current efforts to develop and apply a global-to-regional approach to climate-risk management. They explain how atmospheric and social scientists are cooperating with agricultural practitioners in various regions around the world to determine how farmers may benefit most from new climate predictions. Specifically, the emerging ability to predict the El Niño-Southern Oscillation (ENSO) cycle offers the potential to transform agricultural planning worldwide. Biophysical scientists are only now beginning to recognize the large-scale, globally distributed impacts of ENSO on the probabilities of seasonal precipitation and temperature regimes. Meanwhile, social scientists have been researching how to disseminate forecasts more effectively within rural communities. Consequently, as the quality of climatic predictions have improved, the dissemination and presentation of forecasts have become more effective as well. This book explores the growing understanding of the interconnectedness of climate predictions and productive agriculture for sustainable development, as well as methods and models used to study this relationship.
Book
Climate variability has major impacts in many parts of the world, including Australia. Developments in understanding of the El Niño - Southern Oscillation Phenomenon have introduced some skill in seasonal to inter-annual climate forecasting. Can this skill be harnessed to advantage? Or do we just continue to observe these impacts? How does a decision-maker managing an agricultural or natural ecosystem modify decisions in response to a skillful, but imprecise, seasonal climate forecast? Using Australian experience as a basis, this book focuses on these questions in pursuing means to better manage climate risks. The state of the science in climate forecasting is reviewed before considering detailed examples of applications to: • farm scale agricultural decisions (such as management of cropping and grazing systems); • regional and national scale agricultural decisions (such as commodity trading and government policy); and • natural systems (such as water resources, pests and diseases, and natural fauna). Many of the examples highlight the participatory and inter-disciplinary approach required among decision-makers, resource systems scientists/analysts, and climate scientists to bring about the effective applications. The experiences discussed provide valuable insights beyond the geographical and disciplinary focus of this book. The book is ideally suited to professionals and postgraduate students in ecology, agricultural climatology, environmental planning, and climate science.
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For the tropical Pacific and Atlantic oceans, internal modes of variability that lead to climatic oscillations have been recognized1, ², but in the Indian Ocean region a similar ocean–atmosphere interaction causing interannual climate variability has not yet been found³. Here we report an analysis of observational data over the past 40 years, showing a dipole mode in the Indian Ocean: a pattern of internal variability with anomalously low sea surface temperatures off Sumatra and high sea surface temperatures in the western Indian Ocean, with accompanying wind and precipitation anomalies. The spatio-temporal links between sea surface temperatures and winds reveal a strong coupling through the precipitation field and ocean dynamics. This air–sea interaction process is unique and inherent in the Indian Ocean, and is shown to be independent of the El Niño/Southern Oscillation. The discovery of this dipole mode that accounts for about 12% of the sea surface temperature variability in the Indian Ocean—and, in its active years, also causes severe rainfall in eastern Africa and droughts in Indonesia—brightens the prospects for a long-term forecast of rainfall anomalies in the affected countries.
Book
In an age of such uncertainty over climate change, there are few more important issues than that of how we feed ourselves. We need to know more about the potential impact of climate uncertainty on our food supplies and this book is an important addition to the literature in this field. Improved adaptation of food production, particularly in areas where climate variability is large, holds the key to improving food security for human populations. Increasing climate knowledge and improved prediction capabilities facilitate the development of relevant climate information and prediction products for applications in agriculture. This in turn reduces the negative impacts due to climate variations and enhances planning activities based on the developing capacity of climate science. This book, based on an International Workshop held in Geneva in 2005, reviews the advances made so far in seasonal climate predictions and their applications for management and decision-making in agriculture.