Dissecting the nonlinear response of maize yield to high temperature stress with model‐data integration

Evidence suggests that global maize yield declines with a warming climate, particularly with extreme heat events. However, the degree to which important maize processes such as biomass growth rate, growing season length (GSL) and grain formation are impacted by an increase in temperature is uncertain. Such knowledge is necessary to understand yield responses and develop crop adaptation strategies under warmer climate. Here crop models, satellite observations, survey, and field data were integrated to investigate how high temperature stress influences maize yield in the U.S. Midwest. We showed that both observational evidence and crop model ensemble mean (MEM) suggests the nonlinear sensitivity in yield was driven by the intensified sensitivity of harvest index (HI), but MEM underestimated the warming effects through HI and overstated the effects through GSL. Further analysis showed that the intensified sensitivity in HI mainly results from a greater sensitivity of yield to high temperature stress during the grain filling period, which explained more than half of the yield reduction. When warming effects were decomposed into direct heat stress and indirect water stress (WS), observational data suggest that yield is more reduced by direct heat stress (?4.6 ± 1.0%/°C) than by WS (?1.7 ± 0.65%/°C), whereas MEM gives opposite results. This discrepancy implies that yield reduction by heat stress is underestimated, whereas the yield benefit of increasing atmospheric CO₂ might be overestimated in crop models, because elevated CO₂ brings yield benefit through water conservation effect but produces limited benefit over heat stress. Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the effects of heat stress.     

Characterizing drought stress and trait influence on maize yield under current and future conditions

Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought‐stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis‐silking synchrony, maturity and kernel number on yield in different drought‐stress scenarios, under current and future climates. Under historical conditions, a low‐stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late‐season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO₂ on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis‐silking synchrony had the greatest effect on yield in low drought‐stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early‐terminal drought stress. Segregating drought‐stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought‐stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses.     

Tree rings and ‘El Año del Hambre’ in Mexico

Mexico has a wealth of historical information regarding extreme climate, famine and disease in the colonial period and even in prehispanic times. The recent development of long tree-ring chronologies throughout Mexico now allows comparison between records of past climate and socioeconomic conditions. North American tree-ring data indicate that, for the 3 consecutive years from 1785 to 1787, a major drought occurred across Mexico and the central United States with the most intense conditions extending north from Zacatecas into Texas. This period included the infamous ‘El Año del Hambre,’ one of greatest famines in Mexican history. The tree-ring data are also correlated with maize yield in central Mexico and with the value of Church tithes normally paid with agricultural goods. Drought and crop failure caused the dramatic inflation of crop value and Church tithes in 1786–1787 when tree-ring data indicate that the 1780s drought was most extreme.     

Analyzing the Impact of Agave Cultivation on Famine Risk in Arid Pre-Hispanic Northern Mexico

Cultivation of agave was common in pre-Hispanic northern Mexico and the American Southwest, and scholars generally accept that it was a strategy to ensure food supply during years of drought when the maize crop failed. Some even suggest that incorporating agave cultivation make large, nucleated settlements possible in arid northern Mexico ca. 500–900 CE. Yet the environmental circumstances under which farmers could reasonably expect such a strategy to decrease the chances of agricultural failure are not well understood. We explore the potential of this crop complementarity by assessing the risk of famine-induced migration events in different idealized environmental settings. We use Monte Carlo simulation to analyze a simple discrete-time, age-structured stochastic model for maize and agave agroecology, deriving the climatological conditions under which agave could have significantly reduced the probability of short- and long-term famine events. Investments in agave production made the most sense where average annual rainfall was between the levels that would ensure maximum maize yield and those that would mean loss of the maize crop due to drought-related mortality. Cultivating agave had little impact on famine risk at high (maize yields sufficient) and low (failure of both maize and agave) rainfall levels. Perhaps more surprisingly, it had its highest impact at moderate rainfall levels when variance in rainfall was relatively low. While a higher variance in rainfall increased the number of ‘good’ years for maize—where production would exceed demand and allow for storage—it also increased the probability of simultaneous failures in both agave and maize production. These findings are difficult to apply to specific times and places in the past, because rainfall distribution in complex, environments change, and it is difficult to take all relevant human interventions into account. The analysis does, however, offer support for the proposition that agave cultivation could have significantly enhanced survival probabilities of large, nucleated settlements in certain circumstances. It remains for further study to identify such circumstances more precisely geographically and temporally.

Morphological and biochemical changes in maize under drought and salinity stresses in a semi-arid environment

Abstract

This study investigated some morphological and biochemical responses of maize to drought and salinity in open field in Tunisia with the aim of gaining insights into tolerance mechanisms. After seedling emergence, five treatments were applied until maturity: optimal water supply (control, 100% of maximum evapotranspiration - ETM); irrigation at 70% ETM (moderate drought) and at 35% ETM (severe drought); optimal supply of water containing 3?g NaCl L^?1 (moderate salinity) and 6?g NaCl L^?1 (severe salinity). Here, we demonstrated that extreme drought and salinity severely decreased the leaf area (?74% and ?55%, respectively) and the above-ground biomass (?35% and ?31%, respectively) at silking stage, indicating that the photosynthetic leaf apparatus is highly sensitive and that drought has a greater effect than salinity. Grain yield losses were also exacerbated under extreme stress conditions, viz. severe drought (?85% versus controls) and severe salinity (?73%), while productivity under moderate salinity approximated that of moderate drought, possibly due to increases in leaf chlorophyll and carotenoid content and K/Na ratio. The leaf area and its relative water content were positively correlated with grain yield under both salinity and drought stresses, and may therefore be used as markers for effective screening of maize genotypes for better stress tolerance.     

1961-2010年潜在干旱对我国夏玉米产量影响的模拟分析

玉米是我国重要的粮食和饲料作物,旱灾是玉米生产中常见的气象灾害。采用CERES-Maize作物模拟模型,模拟了1961—2010年潜在干旱对我国夏玉米产量影响的时空变化趋势,并分析了其与大气环流因子间的关系,以期了解我国50年来夏玉米受旱的变化情况,并为干旱的研究方法提供一些参考。结果表明:(1)1961—2010年我国夏玉米的潜在产量损失呈略微下降的趋势,不同时期表现不同,其中20世纪60年代、90年代表现为上升趋势。(2)在过去50年里,我国夏玉米潜在旱灾损失中心有向东北移动的趋势,华北地区受旱程度的减轻和东北地区受旱程度的增强是造成损失中心移动的主要原因。(3)我国夏玉米潜在旱灾产量损失中心的经纬度和影响我国夏季降水的北极涡、副热带高压系统的部分指数具有显著的相关关系。当北极涡在生长季前期或同期偏小、偏弱时,我国夏玉米潜在旱灾产量损失中心将偏东、偏北,而副热带高压系统影响更为复杂。     

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

Understanding large‐scale crop growth and its responses to climate change are critical for yield estimation and prediction, especially under the increased frequency of extreme climate and weather events. County‐level corn phenology varies spatially and interannually across the Corn Belt in the United States, where precipitation and heat stress presents a temporal pattern among growth phases (GPs) and vary interannually. In this study, we developed a long short‐term memory (LSTM) model that integrates heterogeneous crop phenology, meteorology, and remote sensing data to estimate county‐level corn yields. By conflating heterogeneous phenology‐based remote sensing and meteorological indices, the LSTM model accounted for 76% of yield variations across the Corn Belt, improved from 39% of yield variations explained by phenology‐based meteorological indices alone. The LSTM model outperformed least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) approaches for end‐of‐the‐season yield estimation, as a result of its recurrent neural network structure that can incorporate cumulative and nonlinear relationships between corn yield and environmental factors. The results showed that the period from silking to dough was most critical for crop yield estimation. The LSTM model presented a robust yield estimation under extreme weather events in 2012, which reduced the root‐mean‐square error to 1.47 Mg/ha from 1.93 Mg/ha for LASSO and 2.43 Mg/ha for RF. The LSTM model has the capability to learn general patterns from high‐dimensional (spectral, spatial, and temporal) input features to achieve a robust county‐level crop yield estimation. This deep learning approach holds great promise for better understanding the global condition of crop growth based on publicly available remote sensing and meteorological data.     

Phenological responses to extreme droughts in a Mediterranean forest

Mediterranean regions are projected to experience more frequent, prolonged and severe drought as a consequence of climate change. We used a retractable rainfall shelter, to investigate the impact of extreme droughts on the development of Quercus ilex leaves, flowers and fruit. In 2008, 97% of rainfall was excluded from a forest plot during the autumn, representing 50% of the 1127 mm of rain that fell during the year. In 2009, 87% of rainfall was excluded during the spring, representing 58% of the 749 mm that fell during the year. The rainfall shelter did not impact neither incident radiation nor air temperature. Autumn rainfall exclusion did not significantly affect leaf, flowers or fruit development. Spring rainfall exclusion resulted in larger and more sustained depression of leaf water potential during the key phases of foliar and floral development. Consequently, only half of the sampled trees (6) reached the shoot lengthening stage which leads to functionally mature leaves (phenophase 4), with one abandoning leaf development at budburst (phenophase 3) and the other two at the bud swelling stage (phenophase 2). All trees of the control plot passed phenophase 4, with most reaching complete leaf development. The impact of extreme droughts on flower development differed between the sexes. The spring exclusion had no effect on male flower, but only one of six trees completed female fruit maturation, compared with four in the control plot. The difference between the male and female drought impacts is likely attributable to the occurrence of male floral development before the period of lowest leaf water potential, and to the lower resource allocation requirements of male flowers. The information provided by our experimental approach may constitute a crucial step to evaluate the impact of increasing drought due to climate change on the most dominant Mediterranean tree species and to help drawing a full picture of the ecological consequences of the decline in water resource on forest dynamics under changing conditions.     

Responses of soil pH to no-till and the factors affecting it: A global meta-analysis

No-till (NT) is a sustainable option because of its benefits in controlling erosion, saving labor, and mitigating climate change. However, a comprehensive assessment of soil pH response to NT is still lacking. Thus, a global meta-analysis was conducted to determine the effects of NT on soil pH and to identify the influential factors and possible consequences based on the analysis of 114 publications. When comparing tillage practices, the results indicated an overall significant decrease by 1.33 ± 0.28% in soil pH under NT than that under conventional tillage (p < .05). Soil texture, NT duration, mean annual temperature (MAT), and initial soil pH are the critical factors affecting soil pH under NT. Specifically, with significant variations among subgroups, when compared to conventional tillage, the soil under NT had lower relative changes in soil pH observed on clay loam soil (?2.44%), long-term implementation (?2.11% for more than 15 years), medium MAT (?1.87% in the range of 8–16℃), neutral soil pH (?2.28% for 6.5 < initial soil pH < 7.5), mean annual precipitation (?1.95% in the range of 600–1200 mm), in topsoil layers (?2.03% for 0–20 cm), with crop rotation (?1.98%), N fertilizer input (the same for NT and conventional tillage) of 100–200 kg N ha^?1 (?1.83%), or crop residue retention (?1.52%). Changes in organic matter decomposition under undisturbed soil and with crop residue retention might lead to a higher concentration of H⁺ and lower of basic cations (i.e., calcium, magnesium, and potassium), which decrease the soil pH, and consequently, impact nutrient dynamics (i.e., soil phosphorus) in the surface layer under NT. Furthermore, soil acidification may be aggravated by NT within site-specific conditions and improper fertilizer and crop residue management and consequently leading to adverse effects on soil nutrient availability. Thus, there is a need to identify strategies to ameliorate soil acidification under NT to minimize the adverse consequences.     

How efficiently do corn‐ and soybean‐based cropping systems use water? A systems modeling analysis

Agricultural systems are being challenged to decrease water use and increase production while climate becomes more variable and the world's population grows. Low water use efficiency is traditionally characterized by high water use relative to low grain production and usually occurs under dry conditions. However, when a cropping system fails to take advantage of available water during wet conditions, this is also an inefficiency and is often detrimental to the environment. Here, we provide a systems‐level definition of water use efficiency (sWUE) that addresses both production and environmental quality goals through incorporating all major system water losses (evapotranspiration, drainage, and runoff). We extensively calibrated and tested the Agricultural Production Systems sIMulator (APSIM) using 6 years of continuous crop and soil measurements in corn‐ and soybean‐based cropping systems in central Iowa, USA. We then used the model to determine water use, loss, and grain production in each system and calculated sWUE in years that experienced drought, flood, or historically average precipitation. Systems water use efficiency was found to be greatest during years with average precipitation. Simulation analysis using 28 years of historical precipitation data, plus the same dataset with ± 15% variation in daily precipitation, showed that in this region, 430 mm of seasonal (planting to harvesting) rainfall resulted in the optimum sWUE for corn, and 317 mm for soybean. Above these precipitation levels, the corn and soybean yields did not increase further, but the water loss from the system via runoff and drainage increased substantially, leading to a high likelihood of soil, nutrient, and pesticide movement from the field to waterways. As the Midwestern United States is predicted to experience more frequent drought and flood, inefficiency of cropping systems water use will also increase. This work provides a framework to concurrently evaluate production and environmental performance of cropping systems.     

Species richness effects on grassland recovery from drought depend on community productivity in a multisite experiment

Biodiversity can buffer ecosystem functioning against extreme climatic events, but few experiments have explicitly tested this. Here, we present the first multisite biodiversity × drought manipulation experiment to examine drought resistance and recovery at five temperate and Mediterranean grassland sites. Aboveground biomass production declined by 30% due to experimental drought (standardised local extremity by rainfall exclusion for 72–98 consecutive days). Species richness did not affect resistance but promoted recovery. Recovery was only positively affected by species richness in low‐productive communities, with most diverse communities even showing overcompensation. This positive diversity effect could be linked to asynchrony of species responses. Our results suggest that a more context‐dependent view considering the nature of the climatic disturbance as well as the productivity of the studied system will help identify under which circumstances biodiversity promotes drought resistance or recovery. Stability of biomass production can generally be expected to decrease with biodiversity loss and climate change.     

Invader presence disrupts the stabilizing effect of species richness in plant community recovery after drought

Higher biodiversity can stabilize the productivity and functioning of grassland communities when subjected to extreme climatic events. The positive biodiversity–stability relationship emerges via increased resistance and/or recovery to these events. However, invader presence might disrupt this diversity–stability relationship by altering biotic interactions. Investigating such disruptions is important given that invasion by non‐native species and extreme climatic events are expected to increase in the future due to anthropogenic pressure. Here we present one of the first multisite invader × biodiversity × drought manipulation experiment to examine combined effects of biodiversity and invasion on drought resistance and recovery at three semi‐natural grassland sites across Europe. The stability of biomass production to an extreme drought manipulation (100% rainfall reduction; BE: 88 days, BG: 85 days, DE: 76 days) was quantified in field mesocosms with a richness gradient of 1, 3, and 6 species and three invasion treatments (no invader, Lupinus polyphyllus, Senecio inaequidens). Our results suggest that biodiversity stabilized community productivity by increasing the ability of native species to recover from extreme drought events. However, invader presence turned the positive and stabilizing effects of diversity on native species recovery into a neutral relationship. This effect was independent of the two invader's own capacity to recover from an extreme drought event. In summary, we found that invader presence may disrupt how native community interactions lead to stability of ecosystems in response to extreme climatic events. Consequently, the interaction of three global change drivers, climate extremes, diversity decline, and invasive species, may exacerbate their effects on ecosystem functioning.     

Closing the global ozone yield gap: Quantification and cobenefits for multistress tolerance

Increasing both crop productivity and the tolerance of crops to abiotic and biotic stresses is a major challenge for global food security in our rapidly changing climate. For the first time, we show how the spatial variation and severity of tropospheric ozone effects on yield compare with effects of other stresses on a global scale, and discuss mitigating actions against the negative effects of ozone. We show that the sensitivity to ozone declines in the order soybean > wheat > maize > rice, with genotypic variation in response being most pronounced for soybean and rice. Based on stomatal uptake, we estimate that ozone (mean of 2010–2012) reduces global yield annually by 12.4%, 7.1%, 4.4% and 6.1% for soybean, wheat, rice and maize, respectively (the “ozone yield gaps”), adding up to 227 Tg of lost yield. Our modelling shows that the highest ozone‐induced production losses for soybean are in North and South America whilst for wheat they are in India and China, for rice in parts of India, Bangladesh, China and Indonesia, and for maize in China and the United States. Crucially, we also show that the same areas are often also at risk of high losses from pests and diseases, heat stress and to a lesser extent aridity and nutrient stress. In a solution‐focussed analysis of these results, we provide a crop ideotype with tolerance of multiple stresses (including ozone) and describe how ozone effects could be included in crop breeding programmes. We also discuss altered crop management approaches that could be applied to reduce ozone impacts in the shorter term. Given the severity of ozone effects on staple food crops in areas of the world that are also challenged by other stresses, we recommend increased attention to the benefits that could be gained from addressing the ozone yield gap.     

Rapid warming and drought negatively impact population size and reproductive dynamics of an avian predator in the arid southwest

Avian communities of arid ecosystems may be particularly vulnerable to global climate change due to the magnitude of projected change for desert regions and the inherent challenges for species residing in resource limited ecosystems. How arid‐zone birds will be affected by rapid increases in air temperature and increased drought frequency and severity is poorly understood because avian responses to climate change have primarily been studied in the relatively mesic northern temperate regions. We studied the effects of increasing air temperature and aridity on a Burrowing Owl (Athene cunicularia) population in the southwestern United States from 1998 to 2013. Over 16 years, the breeding population declined 98.1%, from 52 pairs to 1 pair, and nest success and fledgling output also declined significantly. These trends were strongly associated with the combined effects of decreased precipitation and increased air temperature. Arrival on the breeding grounds, pair formation, nest initiation, and hatch dates all showed significant delays ranging from 9.4 to 25.1 days over 9 years, which have negative effects on reproduction. Adult and juvenile body mass decreased significantly over time, with a loss of 7.9% mass in adult males and 10.9% mass in adult females over 16 years, and a loss of 20.0% mass in nestlings over 8 years. Taken together, these population and reproductive trends have serious implications for local population persistence. The southwestern United States has been identified as a climate change hotspot, with projections of warmer temperatures, less winter precipitation, and an increase in frequency and severity of extreme events including drought and heat waves. An increasingly warm and dry climate may contribute to this species' decline and may already be a driving force of their apparent decline in the desert southwest.     

Plastic pollution in croplands threatens long‐term food security

Plastic pollution is a global concern given its prevalence in aquatic and terrestrial ecosystems. Studies have been conducted on the distribution and impact of plastic pollution in marine ecosystems, but little is known on terrestrial ecosystems. Plastic mulch has been widely used to increase crop yields worldwide, yet the impact of plastic residues in cropland soils to soil health and crop production in the long term remained unclear. In this paper, using a global meta‐analysis, we found that the use of plastic mulch can indeed increase crop yields on average by 25%–42% in the immediate season due to the increase of soil temperature (+8%) and moisture (+17%). However, the unabated accumulation of film residues in the field negatively impacts its physicochemical properties linked to healthy soil and threatens food production in the long term. It has multiple negative impacts on plant growth including crop yield (at the mean rate of ?3% for every additional 100 kg/ha of film residue), plant height (?2%) and root weight (?5%), and soil properties including soil water evaporation capacity (?2%), soil water infiltration rate (?8%), soil organic matter (?0.8%) and soil available phosphorus (?5%) based on meta‐regression. Using a nationwide field survey of China, the largest user of plastic mulch worldwide, we found that plastic residue accumulation in cropland soils has reached 550,800 tonnes, with an estimated 6%–10% reduction in cotton yield in some polluted sites based on current level of plastic residue content. Immediate actions should be taken to ensure the recovery of plastic film mulch and limit further increase in film residue loading to maintain the sustainability of these croplands.     

基于降水利用比较分析的四川省种植制度优化

比较分析四川8个农业生态区典型站点及其主要种植模式的降水盈亏产量降低率、产量降低率风险指数、降水利用效率和降水经济效率。结果表明:(1)四川省不同区域、不同种植模式、不同作物及其不同生育阶段基于降水盈亏的产量降低率多年均值差异较大。区域分布上,雅安最低,仅23％,攀西最高,达50％以上,其余地区30％-40％;种植制度上,麦-玉-苕等旱三熟低于麦-稻等水旱轮作两熟制;作物种类上,冬小麦、冬油菜、秋播马铃薯等作物普遍高于水稻、玉米、棉花、红薯和大豆作物;生育阶段上,冬小麦、冬油菜、秋播马铃薯作物开花前后普遍较高,各种作物生育末期较低。(2)基于自然降水,攀西地区遭遇旱灾的风险极大,麦-玉-苕等旱三熟的产量降低率风险指数相对较小;雅安等盆地内部多数区域由于阶段性降水过多引起湿害偏重,导致麦-稻等水旱轮作两熟制略优于旱三熟。基于降水利用效率和降水经济效率,各地比较一致,较优的种植制度首先是麦(油、薯)-稻两熟制,其次才是麦(油)-玉-苕(豆)旱三熟。(3)综合旱涝灾害风险、降水利用效率和降水经济效率,以及复杂地形等因素,有较好灌溉条件的农田应以麦(油、薯)-稻水旱轮作两熟制为主,而无水源保障的旱地则以麦(油)-玉-苕(豆)旱三熟为主。     

Fruiting phenology is linked to rainfall variability in a tropical rain forest

As the influence of climate change on tropical forests becomes apparent, more studies are needed to understand how changes in climatic variables such as rainfall are likely to affect tree phenology. Using a twelve‐year dataset (2005–2016), we studied the impact of seasonal rainfall patterns on the fruiting phenology of 69 tree species in the rain forest of southeastern Madagascar. We found that average annual rainfall in this region has increased by >800 mm (23%) during this period relative to that recorded for the previous 40 years and was highly variable both within and between years. Higher monthly measures of fruiting richness and the intensity of fruiting in our sample community were associated with significantly higher levels of rainfall. We also found that less rainfall during the dry season, but not the wet season, was associated with a significant shift toward later timing of peak richness and peak intensity of fruiting in the subsequent 12 months; however, this pattern was driven primarily by an extreme drought event that occurred during the study period. Longer time scales of phenology data are needed to see whether this pattern is consistent. Madagascar is expected to experience more extremes in rainfall and drought with increasing climate change. Thus, the linkages between variable precipitation and the fruiting phenology of forest trees will have important consequences for understanding plant reproduction and the ability of Madagascar's wildlife to cope with a changing climate.     

Modelling crop yield response to precipitation redistribution on slopes

In undulating or sloping land, water distribution in soil has a major influence on crop yield through stresses on vegetation. It is difficult to predict the impacts, however, so a crop model is required to simulate topography-related horizontal redistribution of summer precipitation and its effect on yield. This study uses a potato model (POMOD), operating with the concept of meteorologically possible yield (MPY). It was supplemented to assess precipitation redistribution by runoff on a sloping surface. Slope incline, soil moisture and rainfall intensity were environmental parameters, with rainfall intensities replaced empirically with more convenient daily rainfall sums. Differences in the water balance, as compared to a non-sloping level surface, were computed for three different parts of a notional slope 3°. Modelled differences from long-term meteorological data allowed computation of comparative long-term series of MPY in two climatologically different localities in Estonia. These were the generally moister Tallinn and the frequently dry Kuressaare regions. The locations responded differently, but there was a significant influence in both of slope on potato yield. In the frequently dry Kuressaare, yield was limited by water deficiency, as was characterized by the change in MPY through slope. However, the moister Tallinn had the worst growing conditions at the foothill due to excess water. Tallinn had the greatest topography-related differences, leading to the conclusion that excess water causes more loss in potato yield than drought in Estonia. Events of extreme rainfall drive these losses.     

Multi‐century tree‐ring precipitation record reveals increasing frequency of extreme dry events in the upper Blue Nile River catchment

Climate‐related environmental and humanitarian crisis are important challenges in the Great Horn of Africa (GHA). In the absence of long‐term past climate records in the region, tree‐rings are valuable climate proxies, reflecting past climate variations and complementing climate records prior to the instrumental era. We established annually resolved multi‐century tree‐ring chronology from Juniperus procera trees in northern Ethiopia, the longest series yet for the GHA. The chronology correlates significantly with wet‐season (r = .64, p < .01) and annual (r = .68, p < .01) regional rainfall. Reconstructed rainfall since A.D. 1811 revealed significant interannual variations between 2.2 and 3.8 year periodicity, with significant decadal and multidecadal variations during 1855–1900 and 1960–1990. The duration of negative and positive rainfall anomalies varied between 1–7 years and 1–8 years. Approximately 78.4% (95%) of reconstructed dry (extreme dry) and 85.4% (95%) of wet (extreme wet) events lasted for 1 year only and corresponded to historical records of famine and flooding, suggesting that future climate change studies should be both trend and extreme event focused. The average return periods for dry (extreme dry) and wet (extreme wet) events were 4.1 (8.8) years and 4.1 (9.5) years. Extreme‐dry conditions during the 19th century were concurrent with drought episodes in equatorial eastern Africa that occurred at the end of the Little Ice Age. El Niño and La Niña events matched with 38.5% and 50% of extreme‐dry and extreme‐wet events. Equivalent matches for positive and negative Indian Ocean Dipole events were weaker, reaching 23.1 and 25%, respectively. Spatial correlations revealed that reconstructed rainfall represents wet‐season rainfall variations over northern Ethiopia and large parts of the Sahel belt. The data presented are useful for backcasting climate and hydrological models and for developing regional strategic plans to manage scarce and contested water resources. Historical perspectives on long‐term regional rainfall variability improve the interpretation of recent climate trends.