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Good quality data on precipitation are a prerequisite for applications like short-term weather forecasts, medium-term humanitarian assistance, and long-term climate modelling. In Sub-Saharan Africa, however, the meteorological station networks are frequently insufficient, as in the Cuvelai-Basin in Namibia and Angola. This paper analyses six rainfall products (ARC2.0, CHIRPS2.0, CRU-TS3.23, GPCCv7, PERSIANN-CDR, and TAMSAT) with respect to their performance in a crop model (APSIM) to obtain nutritional scores of a household’s requirements for dietary energy and further macronutrients. All products were calibrated to an observed time series using Quantile Mapping. The crop model output was compared against official yield data. The results show that the products (i) reproduce well the Basin’s spatial patterns, and (ii) temporally agree to station records (r = 0.84). However, differences exist in absolute annual rainfall (range: 154 mm), rainfall intensities, dry spell duration, rainy day counts, and the rainy season onset. Though calibration aligns key characteristics, the remaining differences lead to varying crop model results. While the model well reproduces official yield data using the observed rainfall time series (r = 0.52), the products’ results are heterogeneous (e.g., CHIRPS: r = 0.18). Overall, 97% of a household’s dietary energy demand is met. The study emphasizes the importance of considering the differences among multiple rainfall products when ground measurements are scarce.
We analyzed the possibility of introducing a single stochastic scaling parameter a to describe the spatial variability of soil hydraulic properties, using the soil hydraulic properties of the Hamra field (Russo and Bresler 1981) and the Panache field (Nielsen, Biggar, and Erh 1973). In the traditional approach (Peck, Luxmoore, and Stolzy 1977; Russo and Bresler 1980; Warrick, Mullen, and Nielsen 1977), sets of scaling factors are estimated from the h(s) and K(s) functions. For "perfectly similar media," the two sets of a should be identical. Even though the sets of a in these studies were found to be correlated (table 2), they possessed different statistical properties, and were not identical. Results of structural analyses of the sets of a from the two fields suggested that the spatial structures of the two a-sets are quite distinct, reflecting the different spadal behavior of the h(θ) and the K(θ) functions. Moreover, there was poor correlation between the uncorrelated residuals of the a-sets, indicating that part of the high correlation between the a-sets found in earlier work must stem from the presence of an undetected drift and from correlation between nearby measurements. Under field conditions, the saturated hydraulic conductivity is controlled by the flow of water through large structural voids (macropores), which drain at very small negative values of water pressure. Because of this, we tried eliminating Ks by using relative hydraulic properties instead of the hydraulic properties themselves to estimate the scaling factor sets. For the Hamra field, for which we assumed that the hydraulic properties could be described by the model of Brooks and Corey (1964), we found the resultant sets of scaling factors to be highly correlated (R2 = 0.996) with the same spatial structure, but with slightly different variance. By examining the relationships between the two a-sets implied by the Brooks and Corey (1964) model we saw that (1) in general, both sets will be functions of the range of water saturation values used to estimate them, (2) the correlation between the two sets can be improved for media with broad pore-size distributions, and (3) the two sets will be identical if and only if the relative hydraulic conductivity function K,.(hr) is described by the deterministic function Kr(hr) = hy -2 ("strictly similar media"). This analysis suggests that, for media that are not well described by Kr = hr -2, a scaling factor would be required in addition to a in order to achieve agreement between scaled values of hr(θ) and Kr(θ) at all points. A general model Kr = hr -η was proposed, with η as a second stochastic scaling factor for media that do not obey the restrictive assumptions of macroscopic Miller similitude. In the Hamra field, this modified scaling procedure produced perfect agreement between the scaling hydraulic properties. In the Panache field, with values of η determined from linear regression analysis of the logarithmic transformations of Kr and h,., agreement was improved considerably between the scaled hydraulic properties as compared to the more restrictive scaling procedure. In contrast to the Hamra field, however, there remained some significant differences between the scaled properties. These differences may have been artifacts of the different methods used to estimate the hIs) and the K(s) functions for the Panache field. The results of our analysis suggest that in any transient transport problem involving both K(s) and h(s), the description of their spatial variability requires the use of at least three stochastic variates-Ks , α, and η-not a alone.
The Nigerian agricultural sector deserves to be studied not less for the contribution of such knowledge to our understanding of the past, and present, but more for the usefulness of such knowledge in shaping the sector. The role that agriculture plays in Nigeria’s national economy since her independence may be determined by considering first, the changing structure of the national economy. As the national economy changes, also the role of agriculture. The observed structure at successive periods thus reveals the contribution that agriculture makes to the national economy. A total picture could also be presented through an examination of the contribution of agriculture to the gross domestic product GDP, over the years. It is also possible to add to the above presentation, the annual production of each agricultural crop over the period, or the productivity of the individual farmer as the years pass by. No doubt, the role of agriculture shall not remain static, for as deliberate efforts are made to develop the economy, the agricultural sector is also affected, although several endogenous factors also influence development within the sector. An emperical approach to the understanding of what is happening within the sector is to be prefered and such is documented in small scale studies conducted already by such scolars as FRICKE (1965), TIFFEN (1976) and MALCHAU (1999a+b).
In Nigeria terrace agriculture can mainly be found in the so called "Middle Belt Economy" as FORDE (1946)1 coined this type which lies between the grain economy of males in the north and tuber cultivation of females in the south. The people - lacking a hierarchically social and territorial organisation - are called acephalous or segmentary societies. From the geographical point of view the Middle Belt is seen as a zone of transition. Because of the variability of the climate (sometimes it is too wet for grains, sometimes too dry for tubers) a strategy of mixed cropping enables the farmers to overcome these hazards. Their strategy can be seen in the frame of the game theory. A low population density and a lack of sufficient accessibility limited the innovation of cash crops at that time. The papers on the Tangale-Waja Region will reveal manifold facets of the culture and agriculture. In a first step we learn by the research of J. Heinrich that the natural environment is - from the genetic point of view - a prerequisite for the establishing of terraces, but it is still today an important provision to the modern farmers in their resettlement areas.
The estimation model PhytoCalc allows a non-destructive quantification of dry weight and nutrient pools of understorey plants in forests by using the relationship between species biomass, cover and mean shoot length. The model has been validated with independent samples in several German forest types and can be a useful tool in forest monitoring. However, in open areas within forests (e.g. clearcuts), the current model version underestimates biomass and produces unreliable nutrient pool estimations. Thus, tissue density, as approximated by leaf dry matter content (LDMC), is systematically higher under high light compared to low light conditions. We demonstrate that the ratio of LDMC under clearcut conditions to LDMC under forest conditions can be used to adjust the PhytoCalc model to clearcut conditions. We investigated the LDMC ratio of five exemplary species commonly occurring on clearcuts. Integrating the square of the ratio as a correction factor improved estimates of biomass to more than 70% fit between observations and predictions. Results also suggest this ratio can be used to correct nutrient concentrations modelled in PhytoCalc, which tend to be overestimated in clearcuts. As morphological groups of plant species exhibit significantly different ratios, we advise using group-specific correction factors for clearcut adjustments in the future.
In October 2015, the Cluster of Excellence 'Image Knowledge Gestaltung. An Interdisciplinary Laboratory' at Humboldt Universität zu Berlin staged a symposium entitled Science meets Comics. Academics from various disciplines converged along with artists from all over the world in order to discuss the future of global nutrition – and the medium of the comic strip as a communication tool for the complex issues in this field. The open two-day symposium was followed by a closed, three-day workshop wherein the artists and cluster members took up the issues raised at the symposium and worked on possible directions for the future.
Summary:
1) Three types of forest, evergreen seasonal forest, heath forest and Melaleuca swamp forest, were distinguished and studied in the vicinity of Cheko in southwestern Cambodia, where moist tropical climate with a pronounced dry season in three winter months prevails.
2) These three forest types respectively occupied deep latosol derived from sandstone, very sandy soil around the swamp forest, and deep deposit of silica sand with underground hardpan in shallow valleys.
3) Total plant biomass was estimated by the allometric method based on some 140 sample trees (DBH24.5 cm) which were felled in four sample plots (two 50 mX50 m plots in the evergreen seasonal forest, and each one 20 m x 50 m plot in the other two types). Biomass of ground vegetation was estimated separately by similar technique and clipping.
4) The biomass of evergreen seasonal forest was estimated as follows. Stem 215 ton/ha, branch 99 ton/ha, root 61 ton/ha, leaf 7.3 ton/ha, leaf area index 7.4 ha/ha, density of trees over 4.5 cm DBH 1,280/ha, relative basal area of Whole stand 3.19 o/oo.
5) The biomass of heath forest was as follows. Stem 111 ton/ha, branch 35 ton/ha·, root 19 ton/ha, leaf 7.7 ton/ha, leaf area index 7.1 ha/ha, tree density 2,570/ha, relative basal area 2.3 o/oo.
6) The biomass of M elaleuca swamp forest was as follows. Stem 7.4 ton/ha, branch 3.9 ton/ha, root 2.6 ton/ha, leaf 0.79 ton/ha, leaf area index 0.37, undergrowth of sedge 2.57 ton/ha, tree density 200/ha, relative basal area of trees 0.35 o/oo.
7) It was found that the biomass of small trees (4.5 cm>DBH>1 cm) and ground vegetation (4.5 cm <= DBH) was so unevenly distributed over the forest floor that a few hundred square meters of sample area would be needed for estimating them at a moderate level of statistical reliability.
8) The estimated biomass of the evergreen seasonal forest was compared with the data hitherto obtained in moist tropical forests of Cote d'Ivoire and Thailand. The forest of Cheko was found to have the biomass equivalent to other rain forests, but to be characterized by a specific DBH-tree height curve, a rather small leaf area index and a high value of leaf area/leaf weight ratio.