DOI: 10.5061/dryad.4xgxd258c
title: Prosopis invasion and management scenarios for Baringo County, Kenya

description: 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.
description: Impacts of
 <i>Prosopis</i> invasion and grassland degradation and
 restoration on soil organic carbon To understand the
 impacts of <i>Prosopis</i> 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
 <i>Prosopis</i> 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 <i>Prosopis</i> (Ps)
 (&lt;50% coverage), and (5) dense <i>Prosopis</i> (Pd)
 (&gt;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 <i>Prosopis</i>, 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 <i>Prosopis</i> 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
 <i>Prosopis</i> management scenarios for four selected
 sublocations were mapped.
description: 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.