Draft environmental report on Cape Verde

Faced with recurrent drought and famine during five centuries of human occupation, the small and densely populated Cape Verde Islands have a history of severe environmental problems. The arid climate and steep, rocky terrain provide scant resources for traditional subsistance farming under the best conditions, and in years of low rainfall the failure of rainfed crops causes massive food shortages. Agricultural use of steep slopes where rainfall is highest has led to soil erosion, as has removal of the island's vegetation for fuel and livestock. Pressure on the vegetation is particularly severe in dry years. International aid can provide relief from famine, and the introduction of modern agricultural and conservation techniques can improve the land and increase yield, but it is unlikely that Cape Verde can ever be entirely self -sufficient in food. Ultimately, the solution of Cape Verde's economic and environmental problems will probably require the development of productive urban jobs so the population can shift away from the intensive and destructive use of land for subsistance farming. In the meantime, the people of Cape Verde can best be served by instituting fundamental measures to conserve and restore the land so that it can be used to its fullest potential. The primary environmental problems in Cape Verde today are: 1. Soil degradation. Encouraged by brief but heavy rains and steep slopes, soil erosion is made worse by lack of vegetation. Soils are also low in organic matter due to the practice of completely removing crop plants and natural vegetation for food, fuel or livestock feed. 2. Water shortage. Brief and erratic rainfall in combination with rapid runoff makes surface water scarce and difficult to use. Groundwater supplies can be better developed but capabilities are poorly known and the complex nature of the geological substrate makes estimation difficult. Water is the critical limiting factor to the agricultural capability of the islands. 3. Fuel shortage. Demand for fuel is intense and has resulted in the virtual elimination of native vegetation. Fuelwood supplies are becoming more and more scarce and costly. Development of managed fuelwood plantations and alternate energy sources is required. 4. Inappropriate land use. Much of the land now used for raising crops or livestock is too steep or too arid for these purposes, causing erosion and destruction of vegetation. Improving yield in more appropriate areas and encouraging less damaging uses of the remaining marginal lands can help to alleviate this problem.

One-sided tolerance interval in a two-way balanced nested model with mixed effects

In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.