Distribution of twelve moist forest canopy tree species in Liberia and Côte d'Ivoire: response curves to a climatic gradient

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Abstract
The occurrence and abundance of 12 canopy tree species from the moist tropical forests of West Africa have been studied in relation to a climatic gradient. We focused on environmental factors related to water availability: annual amount of rainfall, the length of the dry season, and cumulative water deficit. Species occurrence and abundance data are used for 39 forest sites in Liberia and southwest Côte d'Ivoire. Species responses are modelled using a set of five increasingly complex models, ranging from a no‐trend model to a skewed bell‐shaped response curve.The study species show different distribution patterns. Most of them suggest a close relationship to climatic conditions. Fitting of species occurrence data to each of the three climatic factors results in most cases in simple models. In only one out of 36 cases a bell‐shaped response curve is needed to describe the data. Four of the 12 species show no response to the climatic factors when only occurrence is evaluated.When abundance data are used, in 33 of the 36 cases significant response models are found. In general these are much more complex than in the cases of species occurrence data: in 10 of the 36 cases a bell‐shaped response model is found to describe the data best. This is in contrast with the widespread belief that species response curves are bell‐shaped: within the forest zone in the area studied this is not generally the case.The importance of the three climatic factors for the distribution of the species is evaluated: for four species mean annual rainfall is the most important variable, for four species the length of the dry period, and for one species cumulative water deficit. Consequently, the assumption that mean annual rainfall is the most important factor determining tree species distribution in West African forests is not correct.Species response models to climatic factors show where species have their geographical optima. Implications for forest management are briefly discussed.