Impacts of climate and farming management on maize yield in southern Tanzania

Climate is one of the major factors controlling agricultural productivity in Africa. Changes in meteorological variables such as rising temperatures, changes in precipitation and increase in atmospheric carbon dioxide levels affect crop production. The objective of this study was to evaluate the impacts of climate change and variability, and crop management on yield of maize ( Zea mays L. ) grown in the southern part of Tanzania. Using the Decision Support System for Agrotechnology Transfer Cropping System Model (DSSAT-CSM), a series of sensitivity experiments were conducted to evaluate the response of maize yields to a range of principal changes in rainfall and temperatures. The sensitivities were estimated under two management practices, one with traditional farming practices, and the other with application of external farm inputs. Dry-spells during the growing season caused yield losses of all cultivars of up to 43% for the prolonged dry-spells of 20 days. Increased rainfall intensity, during vegetative and reproductive stages, caused the decrease in yield of 5 and 2%, respectively. A 50-100% decrease in rainfall intensity during the growing season caused a loss of yields between 40-100%. Increased or decreased temperatures from the baseline values reduced or increased days to flowering and to physiological maturity, respectively. In addition, a decrease in temperature from the baseline values to 2 \ub0C had an overall impact of yields loss for all cultivars. However, yields increased with an increase of temperature by up to 2.5 \ub0C (UH6303 and H628) and 4.5 \ub0C (PAN691). Growing seasons with lower total rainfall (<50 mm) and temperature (<1\ub0C) from their climatological values, caused yield loss as much as 71 and 15%, respectively for PAN691 cultivar. Generally, the impacts depended on the management, cultivar, soil characteristics, magnitude, timing and duration of the stress.Le Climat est l\u2019un des facteurs majeurs contr\uf4lant la productivit\ue9 agricole en Afrique. Les changements de donn\ue9es m\ue9t\ue9orologiques tels que l\u2019\ue9l\ue9vation des temp\ue9ratures, variabilit\ue9 dans les pr\ue9cipitations et l\u2019augmentation du CO2 atmosph\ue9rique affecte la production agricole. L\u2019objectif de cette \ue9tude \ue9tait d\u2019\ue9valuer les impacts du changement climatique, de variabilit\ue9, et des pratiques agronomiques sur le rendement du ma\uefs ( Zea mays L. ) cultiv\ue9 dans la partie Sud de la Tanzanie. Une s\ue9rie d\u2019exp\ue9rimentations sur la sensibilit\ue9 a \ue9t\ue9 conduite au moyen du Syst\ue8me d\u2019appui \ue0 la prise de d\ue9cisions pour les transferts agro technologiques (DSSAT) afin d\u2019\ue9valuer la r\ue9ponse en terme de rendement de ma\uefs \ue0 une range de variabilit\ue9s majeures dans les pr\ue9cipitations et les temp\ue9ratures. Les sensibilit\ue9s ont \ue9t\ue9 estim\ue9es sous deux pratiques culturales, l\u2019une avec les pratiques de culture traditionnelle et l\u2019autre avec apport ext\ue9rieur d\u2019intrants agricoles. Des p\ue9riodes durant la saison culturales a caus\ue9 des pertes de rendement au niveau de tous les cultivars et ceci allant jusqu\u2019\ue0 43% pour des p\ue9riodes s\ue8ches prolong\ue9es de 20 jours. Les augmentations de l\u2019intensit\ue9 de pr\ue9cipitations durant les p\ue9riodes v\ue9g\ue9tative et reproductive ont caus\ue9 respectivement une diminution de 5 \ue0 2% du rendement. Une r\ue9duction de l\u2019intensit\ue9 des pr\ue9cipitations de 50-100% durant la saison culturale a caus\ue9 une perte de rendement entre 40-100%. L\u2019augmentation ou la diminution des temp\ue9ratures r\ue9duit ou augmente la date de floraison et de maturit\ue9. De plus, une diminution de temp\ue9rature de 2 \ub0C par rapport \ue0 la valeur moyenne a un impact significatif sur le rendement au niveau de tous les cultivars. N\ue9anmoins, le rendement augmente lorsque la temp\ue9rature augmente de 2.5 \ub0C (UH6303 and H628) et 4.5 \ub0C (PAN691). Les saisons culturales avec des pr\ue9cipitations globales (<50 mm) et (<1\ub0C) par rapport \ue0 leur valeurs climatologiques, ont caus\ue9 respectivement une perte de rendement aussi \ue9lev\ue9e que 71 et 15% pour le cultivar PAN691. De fa\ue7on g\ue9n\ue9rale, les impacts d\ue9pendent des pratiques culturales, du cultivar, des caract\ue9ristiques de sol, de la magnitude, du moment et de la dur\ue9e du stress

Air temperature variations and gradients along the coast and fjords of western Spitsbergen

Daily temperature measurements from six meteorological stations along the coast and fjords of western Spitsbergen have been digitized and quality controlled in a Norwegian, Russian and Polish collaboration. Complete daily data series have been reconstructed back to 1948 for all of the stations. One of the station’s monthly temperature series has previously been extended back to 1898 and is included in this study. The long-term series show large temperature variability on western Spitsbergen with colder periods in the 1910s and 1960s and warmer periods in the 1930s, 1950s and in the 21st century. The most recent years are the warmest ones in the instrumental records. There is a positive and statistically significant trend in the annual times series for all of the stations; however, the strongest warming is seen in winter and spring. For the period 1979-2015, the linear trends range from 1.0 to 1.38°C/decade for the annual series and from 2.0 to 2.38°C/decade in winter. Threshold statistics demonstrate a decrease in the number of cold days per year and an increase in the number of warm days. A decreasing inter-annual variability is observed. In winter, spring and autumn, the stations in the northernmost areas of west Spitsbergen and in the innermost parts of Isfjorden are the coldest ones. In summer, however, the southernmost station is the coldest one

A Bayesian Analysis of the Correlations Among Sunspot Cycles

Sunspot numbers form a comprehensive, long-duration proxy of solar activity and have been used numerous times to empirically investigate the properties of the solar cycle. A number of correlations have been discovered over the 24 cycles for which observational records are available. Here we carry out a sophisticated statistical analysis of the sunspot record that reaffirms these correlations, and sets up an empirical predictive framework for future cycles. An advantage of our approach is that it allows for rigorous assessment of both the statistical significance of various cycle features and the uncertainty associated with predictions. We summarize the data into three sequential relations that estimate the amplitude, duration, and time of rise to maximum for any cycle, given the values from the previous cycle. We find that there is no indication of a persistence in predictive power beyond one cycle, and conclude that the dynamo does not retain memory beyond one cycle. Based on sunspot records up to October 2011, we obtain, for Cycle 24, an estimated maximum smoothed monthly sunspot number of 97 +- 15, to occur in January--February 2014 +- 6 months.Comment: Accepted for publication in Solar Physic

On using principal components to represent stations in empirical-statistical downscaling

We test a strategy for downscaling seasonal mean temperature for many locations within a region, based on principal component analysis (PCA), and assess potential benefits of this strategy which include an enhancement of the signal-to-noise ratio, more efficient computations, and reduced sensitivity to the choice of predictor domain. These conditions are tested in some case studies for parts of Europe (northern and central) and northern China. Results show that the downscaled results were not highly sensitive to whether a PCA-basis or a more traditional strategy was used. However, the results based on a PCA were associated with marginally and systematically higher correlation scores as well as lower root-mean-squared errors. The results were also consistent with the notion that PCA emphasises the large-scale dependency in the station data and an enhancement of the signal-to-noise ratio. Furthermore, the computations were more efficient when the predictands were represented in terms of principal components

On using principal components to represent stations in empirical-statistical downscaling

We test a strategy for downscaling seasonal mean temperature for many locations within a region, based on principal component analysis (PCA), and assess potential benefits of this strategy which include an enhancement of the signal-to-noise ratio, more efficient computations, and reduced sensitivity to the choice of predictor domain. These conditions are tested in some case studies for parts of Europe (northern and central) and northern China. Results show that the downscaled results were not highly sensitive to whether a PCA-basis or a more traditional strategy was used. However, the results based on a PCA were associated with marginally and systematically higher correlation scores as well as lower root-mean-squared errors. The results were also consistent with the notion that PCA emphasises the large-scale dependency in the station data and an enhancement of the signal-to-noise ratio. Furthermore, the computations were more efficient when the predictands were represented in terms of principal components

Potential biosignatures in super-Earth atmospheres II. Photochemical responses

Spectral characterization of super-Earth atmospheres for planets orbiting in the habitable zone of M dwarf stars is a key focus in exoplanet science. A central challenge is to understand and predict the expected spectral signals of atmospheric biosignatures (species associated with life). Our work applies a global-mean radiative-convective-photochemical column model assuming a planet with an Earth-like biomass and planetary development. We investigated planets with gravities of 1g and 3g and a surface pressure of 1 bar around central stars with spectral classes from M0 to M7. The spectral signals of the calculated planetary scenarios have been presented in an earlier work by Rauer and colleagues. The main motivation of the present work is to perform a deeper analysis of the chemical processes in the planetary atmospheres. We apply a diagnostic tool, the Pathway Analysis Program, to explore the photochemical pathways that form and destroy biosignature species. Ozone is a potential biosignature for complex life. An important result of our analysis is a shift in the ozone photochemistry from mainly Chapman production (which dominates in Earth's stratosphere) to smog-dominated ozone production for planets in the habitable zone of cooler (M5–M7)-class dwarf stars. This result is associated with a lower energy flux in the UVB wavelength range from the central star, hence slower planetary atmospheric photolysis of molecular oxygen, which slows the Chapman ozone production. This is important for future atmospheric characterization missions because it provides an indication of different chemical environments that can lead to very different responses of ozone, for example, cosmic rays. Nitrous oxide, a biosignature for simple bacterial life, is favored for low stratospheric UV conditions, that is, on planets orbiting cooler stars. Transport of this species from its surface source to the stratosphere where it is destroyed can also be a key process. Comparing 1g with 3g scenarios, our analysis suggests it is important to include the effects of interactive chemistry