Sustainable Management of Rangelands: An Assessment of Invasion Cover Trajectories and Their Contribution to Invasion Management in Marigat Sub-County, Kenya
Invasive alien species have complex spatiotemporal patterns of spread beyond geographical and jurisdictional boundaries. This calls for a coordinated management approach that is spatially explicit, extends beyond individual plot levels, and incorporates land users’ perceptions and decisions. This study, therefore, aims at assessing spatiotemporal invasion trajectories of the invasive tree Prosopis juliflora in Baringo County, Kenya, and evaluating their possible relation to land users’ management decisions. Pre-classified land cover data over a seven-year time period (1988–2016) were reclassified based on the presence or absence of P. juliflora and integrated into ArcGIS to produce P. juliflora cover trajectories for analysis. The spatiotemporal analysis of Prosopis invasion dynamics yields trajectories that can be linked to underlying land users’ management decisions. Areas that remained free of Prosopis since their first clearance were primarily areas where the invasion would cause the highest loss in terms of income or opportunity costs; areas that were never cleared since they were first invaded tended to be areas where no one could be personally held accountable for their management, while the abandonment of management followed by re-invasion appeared to be linked to different drivers, including diversification of livelihoods and lower market prices for horticultural products. Our findings indicate that invasion trajectories are useful in informing existing management strategies to adopt context-based invasive species management practices. The study recommends scaling up the trajectory analysis approach to be replicated in large-scale invasion management strategies. Since it requires considerable finances and time to conduct such analyses on raw satellite imagery, we suggest further research on how to simplify the approach to make it easily and efficiently replicable for large-scale applications