A Substantial Population of Low Mass Stars in Luminous Elliptical Galaxies

The stellar initial mass function (IMF) describes the mass distribution of stars at the time of their formation and is of fundamental importance for many areas of astrophysics. The IMF is reasonably well constrained in the disk of the Milky Way but we have very little direct information on the form of the IMF in other galaxies and at earlier cosmic epochs. Here we investigate the stellar mass function in elliptical galaxies by measuring the strength of the Na I doublet and the Wing-Ford molecular FeH band in their spectra. These lines are strong in stars with masses <0.3 Msun and weak or absent in all other types of stars. We unambiguously detect both signatures, consistent with previous studies that were based on data of lower signal-to-noise ratio. The direct detection of the light of low mass stars implies that they are very abundant in elliptical galaxies, making up >80% of the total number of stars and contributing >60% of the total stellar mass. We infer that the IMF in massive star-forming galaxies in the early Universe produced many more low mass stars than the IMF in the Milky Way disk, and was probably slightly steeper than the Salpeter form in the mass range 0.1 - 1 Msun.Comment: To appear in Natur

Uncertainties in Simulating Crop Performance in Degraded Soils and Low Input Production Systems

Many factors interact to determine crop production. Cropping systems have evolved or been developed to achieve high yields, relying on practices that eliminate or minimize yield reducing factors. However, this is not entirely the case in many developing countries where subsistence farming is common. The soils in these countries are mainly coarse-textured, have low water holding capacity, and are low in fertility or fertility declines rapidly with time. Apart from poor soils, there is considerable annual variability in climate, and weeds, insects and diseases may damage the crop considerably. In such conditions, the gap between actual and potential yield is very large. These complexities make it difficult to use cropping system models, due not only to the many inputs needed for factors that may interact to reduce yield, but also to the uncertainty in measuring or estimating those inputs. To determine which input uncertainties (weather, crop or soil) dominate model output, we conducted a global sensitivity analysis using the DSSAT cropping system model in three contrasting production situations, varying in environments and management conditions from irrigated high nutrient inputs (Florida, USA) to rainfed crops with manure application (Damari, Niger) or with no nutrient inputs (Wa, Ghana). Sensitivities to uncertainties in cultivar parameters accounted for about 90% of yield variability under the intensive management system in Florida, whereas soil water and nutrient parameters dominated uncertainties in simulated yields in Niger and Ghana, respectively. Results showed that yield sensitivities to soil parameters dominated those for cultivar parameters in degraded soils and low input cropping systems. These results provide strong evidence that cropping system models can be used for studying crop performance under a wide range of conditions. But our results also show that the use of models under low-input, degraded soil conditions requires accurate determination of soil parameters for reliable yield predictions

Decision support tools for site-specific fertilizer recommendations and agricultural planning in selected countries in sub-Sahara Africa

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