Climate change, land degradation and invasive alien species (IAS) threaten grassland ecosystems worldwide. IAS clearing and grassland restoration would help to reduce the negative effects of IAS, restore the original vegetation cover, and sustain livelihoods while contributing to climate change mitigation, but uncertain financial benefits to local stakeholders hamper such efforts. This study assessed where and when net financial benefit could be realised from Prosopis juliflora management and subsequent grassland restoration by combining ecological, social and financial information. Impacts of Prosopis invasion and grassland degradation on soil organic carbon (SOC) in nine sublocations in Baringo County, Kenya, were evaluated. Then the financial impacts of Prosopis removal and grassland restoration in the area were calculated and spatially explicit management scenarios for each sublocation modelled, combining geographic information derived from satellite images taken in different years of the invasion with SOC data and socio-economic data collected in the sublocations.The available budget, based on Baringo households’ average willingness to pay, would enable removal, on average, of one fifth of Prosopis per sublocation in a single year. A larger area can be cleared if Prosopis is sparse than if it is dense. The analyses show that in some sublocations, households’ annual investments could result in restoration of all former grassland areas.

This dataset contains shapefiles of the evolution of Prosopis from 1995-2016 and shapefiles containing three management scenarios for four sublocations in Baringo County, Kenya.

Impacts of Prosopis invasion and grassland degradation and restoration on soil organic carbon

To understand the impacts of Prosopis invasion, land degradation, and grassland restoration on SOC, LULC maps for the years 1995, 2002, 2009, and 2016 were analysed, along with a detailed map of Prosopis fractional cover in 2016. The LULC maps were generated earlier for another study (Mbaabu et al., 2019). For the present analysis, the relevant original LULC classes were regrouped into the following five categories: (1) degraded grassland, (2) pristine grassland, (3) restored grassland, (4) sparse Prosopis (Ps) (<50% coverage), and (5) dense Prosopis (Pd) (>50% coverage). A number of assumptions were made, based on the study area’s LULC and land degradation history. Thus, areas originally classified as “bare” were considered to be degraded grassland. Areas classified as “grassland” were considered pristine grassland if they had been “grassland” since 1995. Restored grassland comprises areas that had been classified as “grassland” in the LULC maps of 2002, 2009, or 2016 but had belonged to a different LULC class before that. All other, less relevant LULC classes were grouped and called “Other”. Then the total area for each LULC type in each of the regrouped LULC maps was calculated.

Modelling and evaluation of spatially explicit management scenarios

Uniform management of all invaded areas is too labour-intense and expensive to be realistic. Moreover, local people prefer prioritizing certain areas over others. For the calculations, areas that had been covered with native flora (grassland, native mixed vegetation consisting of trees, bushes, and forests) before they were invaded by Prosopis, as well as areas invaded more recently over those invaded earlier were prioritized. This assumed that restoration of original plant and tree species is most likely to succeed in areas where stumps or seeds of native trees or grasses are still present. Invaded areas that had formerly been categorized as grassland, native bush- or shrubland, or natural forests were derived from the LULC categorizations for 2009, 2002, and 1995 (Mbaabu et al., 2019). If the available budget per sublocation exceeded the cost of treating these areas, it was assumed that further invaded areas (Ps or Pd not previously covered by grassland, native bush- or shrubland, or natural forest) would be treated until the entire budget was spent, prioritizing larger over smaller patches. Clearing Prosopis from the islands in Lake Baringo that belong to Meisori sublocation was not considered a priority. This process resulted in many differently sized fragments of invaded priority areas to be cleared. The fragments to be cleared were selected based on their size, starting with the largest.

Three management scenarios were defined: (1) The entire budget is used to treat Pd; (2) the entire budget is used to treat Ps; and (3) half of the budget is used to treat Pd and the other half to treat Ps. The calculations for the nine sublocations are provided in Appendix S2. Once the available budget and the respective scenarios for each of the nine sublocations were calculated, the three Prosopis management scenarios for four selected sublocations were mapped.

We uploaded one readme file for each dataset: one for the shapefile with evolution of the invasion since 1996 and one with spatial management scenarios for Prosopis in four sublocations in Baringo County, Kenya.