6 resultados para Coffee plantations

em Publishing Network for Geoscientific


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The moist evergreen Afromontane forest of SW Ethiopia has become extremely fragmented and most remnants are intensively managed for cultivation of coffee (Coffea arabica). We investigated the distributions of epiphytic orchids in shade trees and their understory in forests with contrasting management intensity to determine biodiversity losses associated with coffee cultivation and to determine the capacity of coffee shrubs to act as refugia for orchid species. We studied epiphytic orchids in managed forests and natural forests and recorded orchid diversity and abundance in different tree zones of 339 trees and in the understory. Coffee management was associated with a downward shift of orchid species as orchid species were occurring in significantly lower tree zones in managed forest. The number of shrubs in the understory of managed forest was not higher than in natural forests, yet orchid abundance was higher in the understory of managed forests. Local extinctions of epiphytic orchids and species losses in the outer tree zones (a contraction of habitat) in managed forests are most likely driven by losses of large, complex-structured climax trees, and changes in microclimate, respectively. Coffee shrubs and their shade trees in managed forests are shown here to be a suitable habitat for only a limited set of orchid species. As farmers continue to convert natural forest into managed forest for coffee cultivation, further losses of habitat quality and collateral declines in regional epiphytic orchid diversity can be expected. Therefore, the conservation of epiphytic orchid diversity, as well as other components of diversity of the coffee forests, must primarily rely on avoiding coffee management intensification in the remaining natural forest. Convincing farmers to keep forest-climax trees in their coffee forest and to tolerate orchids on their coffee shrubs may also contribute to a more favorable conservation status of orchids in Ethiopian coffee agroecosystems.

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Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.