Miguel Alvarez1, Samuel Kiboi2, Mathias Becker1 and Itambo Malombe3
1INRES-Plant Nutrition, University of Bonn, Germany
2School of Biological Sciences, University of Nairobi, Kenya
3East African Herbarium, National Museums of Kenya
The spread of Prosopis juliflora in the Marigat Plains at the Kenyan Rift Valley has led to severe environmental changes with negative socioeconomic impacts. While many publications have dealt with Prosopis invasion, none of them have proposed an objective way for the quantification of invasion degrees, which is essential for assessment and modelling purposes.
We developed a methodology for characterizing and classifying degrees of Prosopis infestation on the basis of relative vegetation cover. This methodology is correlated with a classification of stands on the basis of different metrics, such as height, density and absolute cover. For the estimation of potential invasion by Prosopis in the Marigat Plains, we calculated univariate correlation models using either a logistic function for monotonic responses or a Gaussian function for unimodal responses. In all those cases, we applied a quantile regression for a better description of the potential response. The outcomes of the models were than reclassified according to the proposed invasion scale.
The described procedure was suitable for the estimation of potential invasivity of Prosopis in univariate ecological dimensions. From the assessed factors, the distance of invaded stands from original plantations and environmental attributes related to water availability (i.e. ground water table, rainfall and soil water-holding capacity) are the most suitable for the prediction of potential and future invasion risks. In this contribution, we will also discuss upscaling models and using assembly procedures for considering multiple factors.