Abstract:
Globally there is a surfeit of invasive alien species that affects ecological process and results to loss of biodiversity from native ecosystem. The increase in the concentration of Green House Gas in the atmosphere change various individual component of individual component system with abroad range of response with time. The threat posed by the invasive species to the biodiversity maybe exacerbated by the climate change. Lantana camara L, is woody shrub that is highly invasive in most part of the world. It has a profound impact in economy and environment worldwide. Therefore knowledge of the current and potential future distribution helps in planning strategies and management to curb their spread.Modeling of current and predicting on potential spread of lantana camara was carried out in Tetu and Nyeri town sub counties located in Nyeri county central province in Kenya using MaxEnt. The occurrence data of lantana presence collected in the field were further post processed to remove spatial auto correlation using SDM toolbox, the threshold was 1km square in so that there is only one sample per pixel and finally 35 occurrence points were retained for modeling. In addition this project used the worldclim bioclimatic variable under current climatic scenario, the Abiotic variable include the soil, and Dem. The standard 19 bioclimatic variables that were highly correlated were removed using Pearson correlation coefficient of a threshold of (r) ≥0.80 and a total of 8 variables were retain (bio1, bio3, bio4, bio10, bio12, bio13, bio14 and bio18) to model current distribution of lantana camara the accuracies were 0.8738 and 0.9526 AUC test data and prediction accuracy respectively. Under current prediction 8% of the area is very highly suitable for lantana and 42% is very low suitable due to large area covered by the forest. But in Nyeri alone the very high suitable class covers 12% of the total area. For the future prediction worldclim 19 bioclimatic variables and 19 bioclimatic predictor variables from four global climatic models viz. (i.e. NCAR_CCSM 4, ipsl, BCC_CSM1, and Miroc_esm_chem) were used under the RCP 2.6 and RCP 8.5. The models predicted differently and the results shows there is a potential increase in the spread of the species under both trajectories. However, the spread is higher on the highest emission of the GHG (RCP 8.5) than the lowest emission (RCP2.6). There is high invasion in parts of Muringato municipalities, Kinganjo conservancy, some part of Kabiruini show ground on the quarry site and some part of Mathera near kamwenja teachers training college. There is a moderate spread in some other parts such Gatitu, Nyeri hills, some most part in Nyeri town Sub County. However there is very low spread in Tetu Sub County due to Aberdare forest