How geographic distance and depth drive ecological variability and isolation of demersal fish communities in an archipelago system (Cape Verde, Eastern Atlantic Ocean)

Cape Verde is a tropical oceanic ecosystem, highly fragmented and dispersed, with islands physically isolated by distance and depth. To understand how isolation affects the ecological variability in this archipelago, we conducted a research project on the community structure of the 18 commercially most important demersal fishes. An index of ecological distance based on species relative dominance (Di) is developed from Catch Per Unit Effort, derived from an extensive database of artisanal fisheries. Two ecological measures of distance between islands are calculated: at the species level, DDi, and at the community level, DD (sum of DDi). A physical isolation factor (Idb) combining distance (d) and bathymetry (b) is proposed. Covariance analysis shows that isolation factor is positively correlated with both DDi and DD, suggesting that Idb can be considered as an ecological isolation factor. The effect of Idb varies with season and species. This effect is stronger in summer (May to November), than in winter (December to April), which appears to be more unstable. Species react differently to Idb, independently of season. A principal component analysis on the monthly (DDi) for the 12 islands and the 18 species, complemented by an agglomerative hierarchical clustering, shows a geographic pattern of island organization, according to Idb. Results indicate that the ecological structure of demersal fish communities of Cape Verde archipelago, both in time and space, can be explained by a geographic isolation factor. The analytical approach used here is promising and could be tested in other archipelago systems.

Novas Pragas Agrícolas na Ilha de São Nicolau - Cabo Verde - Tuta absoluta (Meyrick) (Lep - Gelechiidae) e Bactrocera invadens (Drew, Tsuruta & White) (Dipt - Tephritidae)

Em algumas das ilhas do Arquipélago de Cabo Verde entraram, nos últimos dois anos, espécies invasoras que constituem pragas de culturas agrícolas e que têm apresentado elevada repercussão económica. Entre elas contam-se a traça do tomateiro, Tuta absoluta (Meyrick) (Lepidoptera: Gelechidae) e Bactrocera invadens (Drew, Tsuruta & White) (Diptera: Tephritidae). Com o objectivo de avaliar a presença destas pragas na ilha de São Nicolau, foram instaladas armadilhas com atractivos em quatro zonas com bananeiras (Ribeira Prata, Fajã, Maiama e Campo de Preguiça) para a monitorização da mosca da fruta. Foram também instaladas ensaios em seis parcelas de tomateiro para a comparação de estratégias de protecção contra T. absoluta, armadilha com feromona sexual para captura em massa em conjunto com Bacillus thuringiensis e tratamento com deltametrina. Das quatro zonas monitorizadas, B. invadens só foi encontrada no Vale da Fajã. No que diz respeito a T. absoluta, fez-se a comparação entre a população presente em três estratos do tomateiro e não se encontraram diferenças significativas. As estratégias de protecção contra T. absoluta também não diferiram significativamente no que se refere ao número de minas nas folhas e frutos furados. Nesidiocoris tenuis foi identificado como inimigo natural de T. absoluta presente na ilha.

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.