DOI: 10.5061/dryad.573n5tb6s
title: Stakeholder priorities determine the impact of an alien tree invasion on ecosystem multifunctionality

description: 1. While the ecological impact of environmental change drivers, such as
 alien plant invasions, is relatively well-described, quantitative
 social-ecological studies detailing how these changes impact multiple
 ecosystem services, and subsequently stakeholders, are lacking. 2. We used
 a social-ecological approach to assess how Prosopis juliflora (Prosopis
 henceforth)¸ an invasive tree, affects the provision of multiple ecosystem
 services to different stakeholder groups in a degraded East African
 dryland. We combined plot-based ecological data on the impacts of the tree
 on indicators of ecosystem service supply with questionnaire survey data
 describing ecosystem service priorities from eight different stakeholder
 groups. This data was then used to quantify how tree invasion impacted
 individual ecosystem services, and the overall supply of services,
 relative to the priorities of each stakeholder group, using an ecosystem
 service multifunctionality metric. 3. In the study area, we found that
 Prosopis significantly increased the supply of shade, wood production and
 honey production, but reduced the supply of water availability, tourism
 potential and biodiversity protection. 4. Priorities for specific services
 differed between stakeholder groups. Although most groups assigned a high
 priority to provisioning services, such as water and crop production, it
 was either provisioning or cultural services which were a primary source
 of income, that were deemed most important. 5. Combining supply and
 priority data, showed that most stakeholder groups saw a net decrease in
 ecosystem service multifunctionality with increasing Prosopis invasion, or
 no significant change overall. Increasing Prosopis cover increased
 multifunctionality for only two stakeholder groups, charcoal producers and
 NGO’s involved in regional development. 6. Synthesis &
 applications: Our research highlights the need to account for stakeholder
 priorities in studies of how global change impacts ecosystem
 multifunctionality. We found that there are conflicting patterns of
 ecosystem service priority between different stakeholder groups, resulting
 in large variation in how different groups were impacted by the invasive
 tree. Our approach also highlights possible synergies and conflicts when
 managing this tree invasion. More broadly, we recommend that future
 studies of ecosystem multifunctionality explicitly consider differing
 stakeholder priorities, as these strongly influence the perceived impact
 of environmental and land management change.
description: <strong>Ecological data</strong>
 Ecological data was used to estimate levels of ecosystem service
 supply and the extent of <i>Prosopis</i> invasion. Data on the
 ecological impact of Prosopis on ecosystem properties were collected along
 a Prosopis cover gradient ranging from 0-80% cover in 15 x 15 m plots. A
 total of 67 plots were sampled in the rainy seasons of 2016 and 2017. 5-8
 plots were selected in each of 10 sub-locations, the smallest
 administrative unit in Kenya. Within each sub-location, plots were
 selected along a Prosopis cover gradient and plots within one sub-location
 all had a similar land use history, though land use history could differ
 between sub-locations; see Linders et al. (2019) for more
 details. Total Prosopis woody biomass was
 used as an indicator for wood production and was measured by extrapolating
 basal diameter of each individual Prosopis stem; for details see Linders
 et al. (2020). Plant species richness was used as an indicator for
 biodiversity conservation, as it is known to correlate with the diversity
 of many other taxa (e.g. Manning et al., 2015; Sauberer et al., 2004) and
 measures of larger and more mobile taxa are more difficult to obtain
 reliably at the plot scale. For livestock production we used a combination
 of herbaceous fodder and Prosopis pods as supply indicators to generate a
 measure of total fodder production (g/ plot). There was a linear
 relationship between basal diameter and number of pods (number of pods =
 5.781*basal diameter (mm) – 64.197; based on 28 trees:
 r<sup>2</sup>=0.51; P&lt;0.0001). Prosopis pods weigh on
 average three grams (Sharma, Burman, Tewari, Bohra, & Harsh, 1994)
 and so we summed estimated Prosopis<i> </i>pod weight for each
 plot. Prosopis<i> </i>pods are only a healthy component of a
 livestock diet when they make up 20% or less of it (Mahgoub et al., 2004).
 Therefore, Prosopis pods only contributed to total fodder production when
 they were ≤ 20% total fodder weight. For details on the sampling of
 herbaceous biomass and plant species richness see Linders et al. (2019).
 Two indicators were used for honey production: abundance of
 Prosopis<i> </i>inflorescences and abundance of flowers in the
 herbaceous layer. Approximately, 1.48% of Prosopis flowers become pods
 (Oliveira & Pires, 1988) and Prosopis has, on average, 344 flowers
 per inflorescence (Zaitoun, Al-ghzawi, Samarah, & Mullen, 2009).
 Based on pod number we could thus estimate the total number of Prosopis
 inflorescences. The abundance of each herbaceous flowering species was
 also estimated from ground cover estimates, see (Linders et al., 2019) for
 details. Each species, including Prosopis, was then given a honeybee
 attractiveness score between zero and three, with three the highest, based
 on flower size and palatability (when known). For each species,
 attractiveness scores were multiplied with abundance to get an indication
 of flower availability. This method is likely to overestimate total
 herbaceous flower abundance as the abundance data included seedlings and
 non-flowering plants, which are often eaten before flowering. Therefore,
 the <i>Prosopis</i> flowers were given double weight. Tree
 cover was used as an indicator for shade by estimating visually both
 <i>Prosopis</i> and native woody plant cover (typically less
 than 5% of total cover) from 0-100%, which was done by two people
 independently. Most tourism activities in the region involve wildlife
 watching. Therefore, tourism potential was estimated by assessing habitat
 suitability for the four large charismatic mammal and bird species that
 could potentially occur in the plot and be seen by tourists: Ostrich
 (<i>Struthio camelus</i>), Günther’s Dik-dik (<i>Madoqua
 guentherii</i>), Plains Zebra (<i>Equus quagga</i>) and
 Vervet Monkey (<i>Chlorocebus pygerthrus</i>). For each plot
 it was assessed whether these species could occur here based on their
 habitat requirements, based on scientific literature (Cooper et al., 2009;
 Mittermeier, Rylands, & Wilson, 2013; Wilson &
 Mittermeier, 2011) and personal observations of the authors. For Ostrich,
 all plots with &lt;50% tree cover were deemed suitable. Günther’s
 Dik-dik are browsers, with a habitat preference for woody cover but as
 Prosopis leaves are unpalatable we only deemed plots with &gt;40%
 native tree cover as suitable. Plains Zebra are grazers, only occurring in
 open areas, &lt;50% tree cover and at least medium grass cover,
 &gt;25%. Vervet Monkeys need at least some trees, defined as
 &gt;30%, but were never observed in Prosopis monocultures, so plots
 were only deemed suitable if there was at least some native tree cover.
 Each plot was given a score from zero to four depending on how many of
 these species could occur there. As we only scored services that the plots
 currently provide (i.e. current rather than potential supply), we did not
 measure how Prosopis affects crop farming. Although the plots could be
 converted to crop farming, this would mean the plots cannot supply the
 services listed above. We therefore gave each plot a value of zero for
 crop farming. Water consumption of Prosopis was
 based on measurements taken in the Ethiopian Rift Valley, a region with
 similar climate (9.160 to 9.210N and 40.080 to 40.120E at 740 m.a.s.l.) as
 part of a wider project. The amount of water used, determined by sap flow
 volume of individual Prosopis trees was determined using the heat ratio
 method of the heat pulse velocity technique (Burgess et al., 2001; Dzikiti
 et al., 2017). In total, four sap flow stations were established, each
 with three trees of varying diameter. The individual tree sap flow volume
 in litres per hour were converted to stand level transpiration (in mm per
 hour) using the approach described by Dzikiti et al. (2017). To study the
 dynamics of total actual evapotranspiration from Prosopis stands, and to
 triangulate the estimate obtained from the sap flow set up, an open path
 eddy covariance system was installed in one of the sites (Shiferaw et al.,
 2021). <strong>Stakeholder
 data</strong> Data on the ecosystem service
 priorities of different stakeholders were gathered via individual
 face-to-face interviews, conducted in August 2019. To ensure that our
 research was conducted ethically we took the following steps: 1) All
 interviewees were informed about the purposes of the study and gave their
 informed consent orally before the start of each interview, as a
 proportion of the interviewees was illiterate, this was not done in
 written form. Interviewees were also given the option to halt the
 interview at any time. 2) Data were treated anonymously and are presented
 in the article in a way in which individual participants cannot be
 identified. 3) When uploading the data upon acceptance, individual level
 data will not be made available, thus ensuring anonymity of the
 interviewees. The Senckenberg BIK-F Institute, by whose employees the
 research was led, does not have an ethics committee for social science
 work. In total, 234 questionnaires were successfully completed, spread
 across eight stakeholder groups, each with their own interests in land
 management and income source. Relevant stakeholder groups were pre-defined
 based on discussions with local inhabitants and scientists familiar with
 the region, and represented the main land users and managers of the
 region. These groups were: conservationists, tourism industry, crop
 farmers, pastoralists, government officials, developmental NGO employees,
 charcoal producers and teachers, see Table 1 for affiliations and
 distinguishing characteristics of these groups. Stakeholder sampling was
 done in two different ways: by visiting villagers in their homes and by
 visiting institutions. Villages were selected throughout the study region,
 to cover all accessible areas (limited by road conditions and tribal
 conflicts) and included all areas where ecological sampling was done. In
 total, 60 villages were visited and in each village 2-10 interviews were
 conducted based on presence of stakeholders in their homes. Additionally,
 hotels, tourism guide associations, conservation organisations, government
 offices and NGO offices were visited throughout the study area. Within
 each institution 3-10 people were interviewed separately, depending on the
 size of the institution. In institutions the interviewees were selected by
 a supervisor to cover different hierarchical layers (e.g., from desk
 clerks to general managers) and interviewees were selected on
 availability. All interviewees were adults at the time of the study.
 Interviews were performed by a team of ten trained enumerators, who had
 previous experience in administering questionnaires and who were fluent in
 the local languages, and the questionnaire was pre-tested on roughly 15
 villagers and natural resource management specialists. Each stakeholder was asked which
 of the pre-defined stakeholder groups they identified as belonging to most
 closely. To measure the relative priority of multiple ecosystem services
 each stakeholder was then asked to divide twenty points, represented by
 dried beans, across fifteen potentially relevant ecosystem services (see
 Table 2). The meaning of all ecosystem services was explained by the
 enumerators. In addition, ecosystem services were represented by pictures
 depicting examples of this service when possible (see supplementary
 information 1). Ecosystem services were selected a priori by researchers
 with experience in the region, and a group of local people, based on the
 Common International Classification of Ecosystem Services (CICES)
 classification (Potschin & Haines-Young, 2016). We included only
 services with a direct link to final benefits (as defined in the cascade
 model, Potschin-Young et al., 2018), to minimise the misallocation of
 points between final benefits and the regulating services which underpin
 these. Interviewees were also given the option to name additional services
 which they deemed important and allocate points to them. The number of
 points to be distributed was limited to encourage stakeholders to
 prioritize, as otherwise stakeholders could assign high or low scores to
 all services (e.g. Washbourne et al., 2020). This method, which we term
 ecosystem service priority assessment (ESPA) was adapted from previous
 measures of ecosystem service priority (Washbourne et al., 2020) but
 tailored to generate values that can be used in the ecosystem service
 multifunctionality approach described above. This approach also allows
 multiple values of a single service (e.g. relational and material; Chan,
 Satterfield, & Goldstein, 2012) to be integrated without double
 counting. Discussion with stakeholders while conducting the interviews
 indicated that stakeholders were aware of interdependencies between
 services and allocated their points accordingly. E.g. those from the
 ecotourism sector gave points to both tourism and conservation, and
 farmers and pastoralists gave points to water. Nevertheless, overlap
 between certain services, e.g. (eco)tourism and biodiversity, and water
 and crop production could not be avoided altogether, meaning some points
 may be misallocated, and, the demand for regulating services that underpin
 these final benefits may be underrepresented. The priority some services
 that are currently at high supply may also be ‘taken for granted’ and so
 their priority underestimated.
description: The raw (anonymized data) is accompanied by readme files, which
 describes what is seen in each column. Data is
 complete, there are no missing values.