domain: sde sdv

text:
Sigrun Wagner
email: sigrun.k.wagner@stu.mmu.ac.uk

Clément Rigal

Theresa Liebig
email: theresa.liebig@gmail.com

Rudolf Mremi
email: rmremi@mwekawildlife.ac.tz

Andreas Hemp
email: andreas.hemp@uni-bayreuth.de

Martin Jones
email: m.jones@mmu.ac.uk

Elizabeth Price
email: e.price@mmu.ac.uk

Richard Preziosi
email: r.preziosi@mmu.ac.uk

Clement Rigal
email: clement.rigal@cirad.fr

Ecosystem Services and Importance of Common Tree Species in Coffee-Agroforestry Systems: Local Knowledge of Small-Scale Farmers at Mt. Kilimanjaro, Tanzania

Keywords: shade tree species, farmers' knowledge, East Africa

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Introduction

Agroforestry is a promising agricultural production system due to its potential for climate change mitigation and adaptation [START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF][START_REF] Mbow | Achieving mitigation and adaptation to climate change through sustainable agroforestry practices in Africa[END_REF][START_REF] Rahn | Climate change adaptation, mitigation and livelihood benefits in coffee production: Where are the synergies? Mitig[END_REF]. Besides carbon sequestration [START_REF] Jose | Agroforestry for biomass production and carbon sequestration: An overview[END_REF], shade trees also improve local climatic conditions and reduce variability in microclimate and soil moisture [START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF]. Agroforestry is particularly important for coffee (Coffea arabica L.) production as climate change is expected to reduce the suitable production area for crops such as coffee [START_REF] Adhikari | Climate change and eastern Africa: A review of impact on major crops[END_REF][START_REF] Bunn | A bitter cup: Climate change profile of global production of Arabica and Robusta coffee[END_REF][START_REF] Craparo | Coffea arabica yields decline in Tanzania due to climate change: Global implications[END_REF]. In addition to regulatory services, the associated shade tree species can provide various direct ecosystem services (ESs) such as food, fodder, or fuelwood [START_REF] Reed | Trees for life: The ecosystem service contribution of trees to food production and livelihoods in the tropics[END_REF]. Furthermore, due to their diversity, agroforestry systems have the potential to provide diverse income sources which may act as social safety nets, increasing farmers' economic resilience in the face of coffee price volatility in global markets and possible crop failures [START_REF] Reed | Trees for life: The ecosystem service contribution of trees to food production and livelihoods in the tropics[END_REF][START_REF] Bacon | Confronting the Coffee Crisis: Can Fair Trade, Organic, and Specialty Coffees Reduce Small-Scale Farmer Vulnerability in Northern Nicaragua?[END_REF][START_REF] Tscharntke | Multifunctional shade-tree management in tropical agroforestry landscapes-A review[END_REF][START_REF] Charles | Agroforestry as Adaptation Strategy under Climate Change in Mwanga District, Kilimanjaro, Tanzania[END_REF]. However, ecological conditions, competition among associated species in the system, and farmers' individual objectives need to be considered in designing agroforestry systems to maximize the benefits and minimize the shortcomings of these systems [START_REF] Beer | Shade management in coffee and cacao plantations[END_REF][START_REF] Schroth | V Plant-soil interactions in multistrata agroforestry in the humid tropics[END_REF].

Farmers can be very knowledgeable on factors that influence coffee productivity. From experience, they are aware of interaction(s) between shade tree species and coffee, as well as many direct ESs provided by specific tree species [START_REF] Cerdán | Local knowledge of impacts of tree cover on ecosystem services in smallholder coffee production systems[END_REF][START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. In some areas, however (e.g., the impact of individual tree species on pests and diseases), their knowledge might be limited [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Liebig | Towards a collaborative research: A case study on linking science to farmers' perceptions and knowledge on Arabica Coffee Pests and Diseases and Its Management[END_REF][START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]. Nevertheless, exploring farmers' knowledge might provide novel insights into interactions between shade tree species and coffee productivity. This local knowledge is vital in tailoring recommendations to local conditions.

Although several studies have investigated how the Chagga people living on Mt. Kilimanjaro in Tanzania use their natural environment [START_REF] Fernandes | The Chagga home gardens: A multi-storeyed agro-forestry cropping system on Mt. Kilimanjaro, northern Tanzania[END_REF][START_REF] Hemp | An ethnobotanical study on Mt. Kilimanjaro[END_REF][START_REF] Hemp | Environment and Worldview: The Chaga Homegardens Part I: Ethnobotany and Ethnozoology[END_REF][START_REF] Mollel | Usable wild plant species in relation to elevation and land use at Mount Kilimanjaro, Tanzania[END_REF], research has so far not identified which tree species are considered superior in providing relevant ESs for the local coffee farmers. Our aim is to assess indigenous knowledge of local farmers on Mt. Kilimanjaro regarding selection of shade trees that enhance coffee production and provide other ESs. A participatory approach based on van der Wolf et al. [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF] allowed us to collect and study farmers' knowledge regarding shade tree species' provision of ESs. Following this approach, we identified shade tree species with high potential for coffee agroforestry systems on the southern slopes of Mt. Kilimanjaro. Similar studies have been conducted in other East African countries and the differences in findings [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF][START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Bukomeko | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda[END_REF][START_REF] Dumont | The utility of farmer ranking of tree attributes for selecting companion trees in coffee production systems[END_REF] demonstrate the importance of locally specific investigations.

In this study, we explore the ESs provided by different shade tree species as perceived by farmers. We further examine if elevation, gender, and membership in local farmers' groups influence the perceived ESs provided, and the planting density of different shade tree species. Farm management may be based on farmers' knowledge and preference for specific shade tree species [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. Therefore, we expect that the planting density of tree species will depend on the perceived ESs the tree species provides, as well as farmers' ESs preference.

The study aims to contribute to expanding the database of the online decision-support tool for tree selection in smallholder farming systems (shadetreeadvice.org) [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF] and help tailor recommendations for important shade tree species for coffee farmers on Mt. Kilimanjaro.

Materials and Methods

Study Site

The research took place on the southern slopes of Mt. Kilimanjaro in Tanzania (Latitude 3 • 13 9" S-3 • 17 41" S; Longitude 37 • 9 24" E-37 • 25 19" E) (Figure 1). Here, the Chagga people have cultivated and converted the former forest into an agroforestry system (the so-called Chagga homegardens) over several centuries [START_REF] Hemp | Environment and Worldview: The Chaga Homegardens Part I: Ethnobotany and Ethnozoology[END_REF]. The main cultivation zone of C. arabica in these traditional coffee-banana plantations is located between 1000 m and 1800 m asl [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF] and covers an area of nearly 80,000 ha [START_REF] Hemp | Physiographic map with land use and vegetation[END_REF]. Kilimanjaro National Park prevents expansion of coffee cultivation into higher elevations [START_REF] Fernandes | The Chagga home gardens: A multi-storeyed agro-forestry cropping system on Mt. Kilimanjaro, northern Tanzania[END_REF]. For our study area, Hemp [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF] reports annual rainfall in the lower slopes (800 m to 1300 m asl) of between

Identification of Common Tree Species and Important Ecosystem Services

To identify the most common tree species and most important ESs for coffee farmers of the study area for subsequent data collection, we conducted focus group discussions (FGDs) [START_REF] Smithson | Chapter 21: Focus Groups[END_REF]. In March 2019, we conducted three FGDs in the west (Isuki, Masama Mula and Mudio) and two FGDs in the east (Kiwakabo and Mbokomo). Participants were coffee farmers representing farmers' groups and independent farmers from the same community. Each FGD had between 9 and 15 attendees, leading to a total of 56 attendees.

The list of tree species that participants could choose from was based on Hemp [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF], and the results of an investigation of 40 plots of Chagga homegardens in Narum and Mweka (unpublished data). As small-scale farmers in this region commonly intercropped coffee and banana (Musa spp.), we included the latter as a shade species. This resulted in an initial list of 58 shade tree species. We prepared technical sheets for each shade tree species showing pictures of the plant or plant parts, as well as the local name. We presented these sheets to the focus groups and asked them to rank the shade tree species according to their frequency in coffee fields in their area. Tree species shown to each FGD were then added or removed from the presented list of trees based on their rankings during previous FDGs. In subsequent data collection interviews with individual farmers, we only used the most common shade tree species. This list was composed of 22 tree species that were either ranked in the top 20 in at least three FGDs or in the top 10 of any single FGD (see the species listed in Table S1).

For identification of the locally most important ESs for farmers, we presented 25 ESs to the focus groups and asked the participants to add any additional ESs they considered important. The groups then ranked the services according to their perceived importance, giving us the final list of the 12 locally most important ESs for subsequent data collection interviews. The list included nine ESs that were ranked in the top 12 of at least four FGDs (food provision, shade provision, protection against wind, protection from heat, fodder supply, mulch provision, increased coffee yield, soil fertility improvement, and weed suppression); one ES ranked number four in one FGD and in the top 10 of two other FGDs (increasing coffee quality); one ES ranked as number two in two FGDs, but below 10 in all other FGDs (firewood supply); and one ES ranked as number one in one FGD, but only in the top 10 in one other FGD (soil moisture enhancement) (see all ESs listed in Table S2).

Shade Tree Species Ranking for Ecosystem Services

Identification of Common Tree Species and Important Ecosystem Services

To identify the most common tree species and most important ESs for coffee farmers of the study area for subsequent data collection, we conducted focus group discussions (FGDs) [START_REF] Smithson | Chapter 21: Focus Groups[END_REF]. In March 2019, we conducted three FGDs in the west (Isuki, Masama Mula and Mudio) and two FGDs in the east (Kiwakabo and Mbokomo). Participants were coffee farmers representing farmers' groups and independent farmers from the same community. Each FGD had between 9 and 15 attendees, leading to a total of 56 attendees.

The list of tree species that participants could choose from was based on Hemp [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF], and the results of an investigation of 40 plots of Chagga homegardens in Narum and Mweka (unpublished data). As small-scale farmers in this region commonly intercropped coffee and banana (Musa spp.), we included the latter as a shade species. This resulted in an initial list of 58 shade tree species. We prepared technical sheets for each shade tree species showing pictures of the plant or plant parts, as well as the local name. We presented these sheets to the focus groups and asked them to rank the shade tree species according to their frequency in coffee fields in their area. Tree species shown to each FGD were then added or removed from the presented list of trees based on their rankings during previous FDGs. In subsequent data collection interviews with individual farmers, we only used the most common shade tree species. This list was composed of 22 tree species that were either ranked in the top 20 in at least three FGDs or in the top 10 of any single FGD (see the species listed in Table S1).

For identification of the locally most important ESs for farmers, we presented 25 ESs to the focus groups and asked the participants to add any additional ESs they considered important. The groups then ranked the services according to their perceived importance, giving us the final list of the 12 locally most important ESs for subsequent data collection interviews. The list included nine ESs that were ranked in the top 12 of at least four FGDs (food provision, shade provision, protection against wind, protection from heat, fodder supply, mulch provision, increased coffee yield, soil fertility improvement, and weed suppression); one ES ranked number four in one FGD and in the top 10 of two other FGDs (increasing coffee quality); one ES ranked as number two in two FGDs, but below 10 in all other FGDs (firewood supply); and one ES ranked as number one in one FGD, but only in the top 10 in one other FGD (soil moisture enhancement) (see all ESs listed in Table S2).

Shade Tree Species Ranking for Ecosystem Services

Ranking the most common tree species according to the most important ESs was the focus of data collection interviews with 263 small-scale coffee farmers along the southern slope of Mt. Kilimanjaro (Figure 1). In March and April 2019, we conducted at least 30 individual interviews in each community (Figure 1). We began with farmers that participated in the FGDs or whose farm we investigated; we then interviewed occupants of the fifth house away in each direction along the road. If the person in the fifth house was not a coffee farmer, declined participation, or was absent at the time, we asked at the next house(s) until a respondent was identified.

The respondents were asked to select the 10 tree species that they knew best out of the list of 22 most common shade tree species [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF]. They were then asked to rank the 10 chosen shade tree species for each of the 12 locally most important ESs from the best (high provision of this ES) to the least performing (low provision of this ES) [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF]. We also recorded gender, membership of the HRNS, and elevation of the respondents' home (using a GARMIN GPSMAP 64). We asked the respondents to name the three most important ESs for their household and the estimated number of individuals of the different tree species they had on their coffee fields, as well as the size of their coffee farm.

Data Analysis

We noted the number of tree species each farmer had of the 22 most common shade tree species, the percentage of farmers having each tree species in their fields, and the planting density of each tree species, using farmers' estimated number of trees and farm size. To identify the influence of elevation on the tree planting density of different tree species, we did linear regressions for each common shade tree species in R 3.5.0 [START_REF] Core | R: A Language and Environment for Statistical Computing[END_REF]. We summarized the ESs respondents considered most important and tested gender differences with a chi-square test in R 3.5.0 [START_REF] Core | R: A Language and Environment for Statistical Computing[END_REF].

Based on the method of van der Wolf, et al. [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF], we used the BradleyTerry2 package in R 3.5.0 [START_REF] Core | R: A Language and Environment for Statistical Computing[END_REF] to identify shade tree species best at providing specific ESs, as perceived by the farmers. We excluded interview respondents with less than five years of experience as well as tree species that were ranked less than 10 times for a particular ESs [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]; this left 20 of the 22 tree species in the analysis. As explained by Rigal el al. [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF], the ranks for each ESs need to be converted into pairwise comparisons to fit the Bradley-Terry model. For each tree species and ES, this model calculates scores, which are comparative values representing the likelihood that one tree species performs better than another tree species in providing an ES [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]. We normalized the scores between 0 and 1 to be able to compare them [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]. Besides the scores, quasi-standard errors were calculated to indicate how frequently a species was included in the ranking and how consistently the respondents ranked this species [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]. We compared the scores pairwise using a Wald test. The more pairs that are significantly different, the more it reflects an agreement of farmers upon the ranking of the tree species. Therefore, large numbers of pairs that are significantly different indicate that the analysis is robust [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF]. In our results, the lowest percent of pairs that were different was 67%, and the highest was 89%.

To assess the influence of farmers' objectives on their management practices, we compared shade tree densities on coffee farms between groups of farmers with different sets of priorities. More specifically, we split respondents into two groups: those who had selected the combination of the three most important ESs for small-scale coffee farmer households at Mt. Kilimanjaro as their top three priorities and those who had not. We then compared the shade tree density of species perceived to perform high for the combination of these ESs and tested differences between the two farmer groups using t-tests in R 3.5.0 [START_REF] Core | R: A Language and Environment for Statistical Computing[END_REF].

To identify if gender, affiliation to a farmers' group, or elevation influenced perceived provision of ESs by shade tree species, we split the data sets by gender, membership of the HRNS, and into two elevation groups (threshold was the median 1336 m asl). We ran the BradleyTerry analysis for these subgroups of respondents and compared the resulting scores [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF][START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF].

Ethical Approval

Ethical approval for this study was obtained from the Faculty Research Ethics and Governance Committees of the Manchester Metropolitan University, Faculty of Science and Engineering, on 26 May 2017, with application code SE1617108C.

Results

Main Characteristics of Respondent

Of the total respondents, 96 were women (36.5%) and 167 men (63.5%). The farm size ranged between 0.1 and 8 ha, the average farm size was 0.7 ha with 83.3% (219 respondents) having less than 1 ha. The elevation ranged from 1148 m to 1748 m asl, with an average elevation of 1343 m asl and a median elevation of 1336 m asl (Figure 2). Ninety-seven respondents (37%) were members of the HRNS, while 166 were non-members (63%).

Forests 2019, 10, x FOR PEER REVIEW 5 of 16

Results

Main Characteristics of Respondent

Of the total respondents, 96 were women (36.5%) and 167 men (63.5%). The farm size ranged between 0.1 and 8 ha, the average farm size was 0.7 ha with 83.3% (219 respondents) having less than 1 ha. The elevation ranged from 1148 m to 1748 m asl, with an average elevation of 1343 m asl and a median elevation of 1336 m asl (Figure 2). Ninety-seven respondents (37%) were members of the HRNS, while 166 were non-members (63%).

Tree Species Distribution

Sixty percent of the farmers reported that they had 10 or more of the 22 most common shade tree species on their coffee farms. The most common shade tree species is Musa spp. grown by all respondents, followed by Grevillea robusta A. Cunn. ex R. Br., Albizia schimperiana Oliv., and Persea americana Miller with 94.3%, 90.9%, and 83.7%, respectively (Figure 3). Musa spp. is by far the shade species with the highest density (1089 ± 106 tree ha -1 ) (Figure 3). Grevillea robusta is second densest (39.1 ± 3.29 tree ha -1 ), closely followed by Markhamia lutea (Benth.) K. Schum. (26.6 ± 4.90 tree ha -1 ). Just a few farmers (about 20 percent) grow M. lutea. However, those that do grow it have a high density of the species on their fields. Despite their presence on more than 83% of coffee farms, the densities of A. schimperiana (7.9 ± 0.46 tree ha -1 ) and P. americana (12.3±0.98 tree ha -1 ) are significantly lower than those of the above species (Figure 3).

Neither the total shade tree density nor the Musa spp. density are significantly influenced by elevation. However, we observed differences in density of some tree species. Linear regressions show significant reduction in densities of Cordia africana Lam. (F(1,261) = 12.91, p < 0.001), Mangifera indica L. (F(1,261) = 5.03, p = 0.026) and Senna siamea (Lam.) H. S. Irwin & Barneby (F(1,261) = 3.96, p = 0.048) with increasing elevation-the densities are reduced by 1.1 tree ha -1 , 0.4 tree ha -1 and 0.3 tree ha -1 respectively for every 100 m increase. We detected a significant increase in density towards higher elevations for Margaritaria discoidea (Baill.) G. L. Webster (F(1,261) = 30.88, p < 0.001) and P. americana (F(1,261) = 11.77, p < 0.001) (with an increase of 100 m, the density increases by 2.4 tree ha -1 and 2.7 tree ha -1 respectively).

Tree Species Distribution

Sixty percent of the farmers reported that they had 10 or more of the 22 most common shade tree species on their coffee farms. The most common shade tree species is Musa spp. grown by all respondents, followed by Grevillea robusta A. Cunn. ex R. Br., Albizia schimperiana Oliv., and Persea americana Miller with 94.3%, 90.9%, and 83.7%, respectively (Figure 3). Musa spp. is by far the shade species with the highest density (1089 ± 106 tree ha -1 ) (Figure 3). Grevillea robusta is second densest (39.1 ± 3.29 tree ha -1 ), closely followed by Markhamia lutea (Benth.) K. Schum. (26.6 ± 4.90 tree ha -1 ). Just a few farmers (about 20 percent) grow M. lutea. However, those that do grow it have a high density of the species on their fields. Despite their presence on more than 83% of coffee farms, the densities of A. schimperiana (7.9 ± 0.46 tree ha -1 ) and P. americana (12.3±0.98 tree ha -1 ) are significantly lower than those of the above species (Figure 3).

Neither the total shade tree density nor the Musa spp. density are significantly influenced by elevation. However, we observed differences in density of some tree species. Linear regressions show significant reduction in densities of Cordia africana Lam. (F (1,261) = 12.91, p < 0.001), Mangifera indica L. (F (1,261) = 5.03, p = 0.026) and Senna siamea (Lam.) H. S. Irwin & Barneby (F (1,261) = 3.96, p = 0.048) with increasing elevation-the densities are reduced by 1.1 tree ha -1 , 0.4 tree ha -1 and 0.3 tree ha -1 respectively for every 100 m increase. We detected a significant increase in density towards higher elevations for Margaritaria discoidea (Baill.) G. L. Webster (F (1,261) = 30.88, p < 0.001) and P. americana (F (1,261) = 11.77, p < 0.001) (with an increase of 100 m, the density increases by 2.4 tree ha -1 and 2.7 tree ha -1 respectively).

Important Ecosystem Services

On the southern slope of Mt. Kilimanjaro, food provisioning is by far the most essential ES for coffee farmers. Of the 263 respondents, more than 75% selected food provision as the most important ES for their household, and more than 95% ranked it in the top three (Table 1). The second locally most important ESs is fuelwood supply, which was ranked first by 10% of the respondents and within the top three ESs by nearly 60% of the respondents (Table 1). More than 50% of the respondents also ranked fodder supply among the top three ESs, followed by shade provision, soil fertility improvement and increased coffee yield (Table 1). A chi-square test showed no significant differences in ES preference between genders. The only significant difference between the two elevation groups was that respondents at a higher elevation included soil moisture enhancement more often in the top three ESs than respondents at lower elevation (4.4% and 1.0% respectively, X 2 = 7.2, p < 0.01).

Important Ecosystem Services

On the southern slope of Mt. Kilimanjaro, food provisioning is by far the most essential ES for coffee farmers. Of the 263 respondents, more than 75% selected food provision as the most important ES for their household, and more than 95% ranked it in the top three (Table 1). The second locally most important ESs is fuelwood supply, which was ranked first by 10% of the respondents and within the top three ESs by nearly 60% of the respondents (Table 1). More than 50% of the respondents also ranked fodder supply among the top three ESs, followed by shade provision, soil fertility improvement and increased coffee yield (Table 1). A chi-square test showed no significant differences in ES preference between genders. The only significant difference between the two elevation groups was that respondents at a higher elevation included soil moisture enhancement more often in the top three ESs than respondents at lower elevation (4.4% and 1.0% respectively, X 2 = 7.2, p < 0.01).

Pairwise Comparison

The analysis shows that the ranking of shade tree species is consistent for most ESs. We observed the clearest discrimination between tree species in the ranking for mulch provision and protection from heat with 89.1% and 87.9% of the pairwise comparisons of tree species' scores being significantly different (p < 0.05), followed by increase in coffee yield and quality (Table 2). Most difficult to rank were weed suppression, food provision, and protection against wind with 66.7%, 71.1%, and 72.5% of all pairs being significantly different (p < 0.05) (Table 2).

Tree Ranking

Scores of the tree species ranked according to the three most important ESs for small-scale coffee farmers at the southern slopes of Mt. Kilimanjaro show major differences (Figure 4). Of the most common tree species providing food, all are exotic. Firewood is mainly obtained from indigenous species, except for G. robusta, which is exotic.

Pairwise Comparison

The analysis shows that the ranking of shade tree species is consistent for most ESs. We observed the clearest discrimination between tree species in the ranking for mulch provision and protection from heat with 89.1% and 87.9% of the pairwise comparisons of tree species' scores being significantly different (p < 0.05), followed by increase in coffee yield and quality (Table 2). Most difficult to rank were weed suppression, food provision, and protection against wind with 66.7%, 71.1%, and 72.5% of all pairs being significantly different (p < 0.05) (Table 2).

Tree Ranking

Scores of the tree species ranked according to the three most important ESs for small-scale coffee farmers at the southern slopes of Mt. Kilimanjaro show major differences (Figure 4). Of the most common tree species providing food, all are exotic. Firewood is mainly obtained from indigenous species, except for G. robusta, which is exotic. For a better recommendation of tree species regarding multiple regulatory ESs associated with coffee production, the following ESs were combined into three categories: (a) coffee production enhancement (combining increase in coffee yield and quality), (b) protection from climatic hazards (combining protection from heat, wind and shade provision), (c) soil quality enhancement (combining mulch provision, soil fertility and soil moisture enhancement). For each ES category, the scores of shade tree species were averaged over the set of combined ESs (Figure 5). (combining protection from heat, wind and shade provision), (c) soil quality enhancement (combining mulch provision, soil fertility and soil moisture enhancement). For each ES category, the scores of shade tree species were averaged over the set of combined ESs (Figure 5). Albizia schimperiana is the highest ranked tree species for all three ES categories. Also within the top five for all three ES categories are C. africana, Croton macrostachyus Hochst. ex Delile, and Rauvolfia caffra Sond.. All of these tree species are indigenous. Musa spp. is important for coffee yield and quality, as well as for soil enhancement, while G. robusta contributes to protection from climatic hazards and soil quality enhancement.

Effect of Priorites on Shade Tree Density

Food, fodder, and firewood are the most important ESs for small-scale coffee farmer households (99 respondents (37.8%) selected this combination). To assess the influence ES priorities have on tree species selection, we averaged the scores of each shade tree species for the combination of these three ESs and compared the density of the five best performing tree species between two groups: respondents that selected these three ESs as most important versus those that did not. The planting density of three of these five tree species is significantly higher (t-test, p < 0.05) for respondents that selected these ESs as most important compared to those that did not (Figure 6). We found differences for exotic, but not indigenous species. Albizia schimperiana is the highest ranked tree species for all three ES categories. Also within the top five for all three ES categories are C. africana, Croton macrostachyus Hochst. ex Delile, and Rauvolfia caffra Sond.. All of these tree species are indigenous. Musa spp. is important for coffee yield and quality, as well as for soil enhancement, while G. robusta contributes to protection from climatic hazards and soil quality enhancement.

Effect of Priorites on Shade Tree Density

Food, fodder, and firewood are the most important ESs for small-scale coffee farmer households (99 respondents (37.8%) selected this combination). To assess the influence ES priorities have on tree species selection, we averaged the scores of each shade tree species for the combination of these three ESs and compared the density of the five best performing tree species between two groups: respondents that selected these three ESs as most important versus those that did not. The planting density of three of these five tree species is significantly higher (t-test, p < 0.05) for respondents that selected these ESs as most important compared to those that did not (Figure 6). We found differences for exotic, but not indigenous species.

Elevation, Gender, and Farmer Group Affiliation

The ranking in higher elevations was not significantly different from the lower elevations. The only deviation we observed is that M. indica was included in the ranking of shade tree species providing fodder for the lower elevations, while R. caffra was included in the higher elevations (Figure S1). Farmers did, however, rank both of these tree species low for this ES.

There were slight differences considering gender and affiliation to a farmers group of the HRNS. Women included Annona reticulata L. in their ranking for food provision, and they ranked Musa spp. significantly higher for shade provision and soil fertility compared to men. Men ranked G. robusta significantly higher for shade provision, while R. caffra was ranked higher for soil fertility (Figure S2). Respondents that were members of HRNS ranked M. discoidea significantly higher than non-members for protection from heat (Figure S3). For coffee quality, members of HRNS ranked C. macrostachyus significantly higher and Musa spp. significantly lower than non-members (Figure S3).

Food, fodder, and firewood are the most important ESs for small-scale coffee farmer households (99 respondents (37.8%) selected this combination). To assess the influence ES priorities have on tree species selection, we averaged the scores of each shade tree species for the combination of these three ESs and compared the density of the five best performing tree species between two groups: respondents that selected these three ESs as most important versus those that did not. The planting density of three of these five tree species is significantly higher (t-test, p < 0.05) for respondents that selected these ESs as most important compared to those that did not (Figure 6). We found differences for exotic, but not indigenous species.

Discussion

Improtant Ecosystem Services

Nearly all the farmers in our study area considered food provision by shade trees their top priority, followed by the provisioning services fodder and fuelwood supply (Table 1). These ESs were considered more important than regulatory services for coffee production such as shade provision, soil fertility improvement, and increased coffee yield. ES priorities were not significantly different between genders. Respondents of other studies have various priorities. At Mt. Elgon (Uganda), farmers rather prioritized ESs such as mulch provision, erosion control and temperature regulation [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF], coffee yield, soil moisture enhancement, and quick leaf decomposition in Central Uganda [START_REF] Bukomeko | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda[END_REF]. Differences in the importance of ESs may reflect differences in environmental conditions, as well as market access [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Graefe | Evaluating Farmers' Knowledge of Shade Trees in Different Cocoa Agro-Ecological Zones in Ghana[END_REF]. One reason participants of the FGDs mentioned for excluding timber from the list of important ESs was the political limitation of tree harvesting [START_REF]Parliament of the United Republic of Tanzania[END_REF]. The complexity of agroforestry systems and diverse interactions between different pests and predators on a land-scale level [START_REF] Staver | Designing pest-suppressive multistrata perennial crop systems: Shade-Grown coffee in Central America[END_REF][START_REF] Teodoro | Agroforestry management affects coffee pests contingent on season and developmental stage[END_REF][START_REF] De La Mora | Local, landscape, and diversity drivers of predation services provided by ants in a coffee landscape in Chiapas, Mexico[END_REF][START_REF] Martínez-Salinas | Bird functional diversity supports pest control services in a Costa Rican coffee farm[END_REF] might be the reason coffee farmers at Mt. Kilimanjaro did not observe any effect of shade tree species on pests and did not consider it an important ESs provided by shade trees.

Highly Ranked Tree Species

Albizia schimperiana is the most important shade tree species for coffee production on the southern slope of Mt. Kilimanjaro for the provision of most ESs included in this study. Several studies also report the importance of A. schimperiana for coffee production in Ethiopia [START_REF] Belay | Woody species diversity and coffee production in remnant semi-natural dry Afromontane Forest in Zegie Peninsula, Ethiopia[END_REF][START_REF] Tadesse | Effects of land-use changes on woody species distribution and aboveground carbon storage of forest-coffee systems[END_REF][START_REF] De Beenhouwer | Biodiversity and carbon storage co-benefits of coffee agroforestry across a gradient of increasing management intensity in the SW Ethiopian highlands[END_REF]. As a leguminous plant, A. schimperiana can form a symbiotic relationship with rhizobia bacteria to fix atmospheric nitrogen, resulting in increased soil fertility. Other studies also show that, with an open wide-spreading crown, A. schimperiana provides good shade cover for coffee production, leading to improved microclimate and coffee yield [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF][START_REF] Kufa | Yield performance of Coffea arabica cultivars under different shade trees at Jimma Research Center, southwest Ethiopia[END_REF]. Another advantage of A. schimperiana is that its leaves emerge in the dry season [START_REF] Belay | Woody species diversity and coffee production in remnant semi-natural dry Afromontane Forest in Zegie Peninsula, Ethiopia[END_REF]. This means it can provide shade when there is a lot of sun and prevents coffee from being too densely shaded during the rainy season.

Despite the benefits of A. schimperiana and the perceived provision of multiple regulatory ESs by coffee farmers at Mt. Kilimanjaro, other tree species occurred at a much higher density (Figure 3). From general observations, it seems that the farms have mostly mature trees and that a new generation of A. schimperiana is missing. More research on the population structure of A. schimperiana in this area is required to get a better understanding of future development and challenges. Belay, et al. [START_REF] Belay | Woody species diversity and coffee production in remnant semi-natural dry Afromontane Forest in Zegie Peninsula, Ethiopia[END_REF] found for their study region in Ethiopia that the population structure of A. schimperiana had a U-shape with more stems in lower and higher diameter classes, showing selective cutting or extraction of medium sized individuals. Potential explanations could be the increased exploitation of A. schimperiana for timber and fuelwood, and its low growth rate [START_REF] Tadesse | Effects of land-use changes on woody species distribution and aboveground carbon storage of forest-coffee systems[END_REF][START_REF] Mbuya | Useful Trees and Shrubs for Tanzania-Identification, Propagation and Management for Agricultural and Pastoral Communities[END_REF]. Other important aspects to examine are natural regeneration and the success of propagation.

A closely related species that commercial coffee plantations commonly include in their fields is Albizia gummifera (J. F. Gmel.) C. A. Sm. This species is favored by farmers in Ethiopia [START_REF] Ango | Balancing ecosystem services and disservices: Smallholder farmers' use and management of forest and trees in an agricultural landscape in southwestern Ethiopia[END_REF][START_REF] Denu | The role of traditional coffee management in forest conservation and carbon storage in the Jimma Highlands, Ethiopia. For[END_REF]. Other Albizia species are considered important for providing multiple ESs in East Africa, such as, but not limited to, mulch, shade, improvement of microclimate, coffee yield and soil moisture in Uganda [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Bukomeko | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda[END_REF]. Unfortunately some Albizia species are also alternative hosts for black coffee twig borer in the closely related Robusta coffee (Coffea canephora Pierre ex Froehn.) posing a potential risk [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF].

The other three shade tree species associated with improvements of conditions for coffee production are also indigenous (C. africana, C. macrostachyus and R. caffra). Rauvolfia caffra ranked as an important shade tree species which is in line with other findings from Mt. Kilimanjaro [START_REF] Mollel | Usable wild plant species in relation to elevation and land use at Mount Kilimanjaro, Tanzania[END_REF][START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF]. Fernandes, et al. [START_REF] Fernandes | The Chagga home gardens: A multi-storeyed agro-forestry cropping system on Mt. Kilimanjaro, northern Tanzania[END_REF] report the potential of R. caffra to suppress various coffee pests. Its contribution to the production of traditional banana beer underlines its importance in traditional Chagga homegardens [START_REF] Fernandes | The Chagga home gardens: A multi-storeyed agro-forestry cropping system on Mt. Kilimanjaro, northern Tanzania[END_REF][START_REF] Mollel | Usable wild plant species in relation to elevation and land use at Mount Kilimanjaro, Tanzania[END_REF][START_REF] Mbuya | Useful Trees and Shrubs for Tanzania-Identification, Propagation and Management for Agricultural and Pastoral Communities[END_REF]. Croton macrostachyus provides good litter, preserves soil moisture, facilitating high coffee yield and high bean weight [START_REF] Ebisa | Effect of Dominant Shade Trees on Coffee Production in Manasibu District, West Oromia, Ethiopia[END_REF]. Cordia africana is also reported as an essential shade tree in coffee production in Kenya [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF], Uganda [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF] and Ethiopia [START_REF] Denu | The role of traditional coffee management in forest conservation and carbon storage in the Jimma Highlands, Ethiopia. For[END_REF][START_REF] Teketay | Traditional tree crop based agroforestry in coffee producing areas of Harerge, Eastern Ethiopia[END_REF]. Even though Kufa, et al. [START_REF] Kufa | Yield performance of Coffea arabica cultivars under different shade trees at Jimma Research Center, southwest Ethiopia[END_REF] found high coffee yields under C. africana, they also reported the highest yield variations under this tree species. As C. africana is a high quality timber tree, the economic value might be a major reason for farmers to grow it [START_REF] Denu | The role of traditional coffee management in forest conservation and carbon storage in the Jimma Highlands, Ethiopia. For[END_REF][START_REF] Ebisa | Effect of Dominant Shade Trees on Coffee Production in Manasibu District, West Oromia, Ethiopia[END_REF].

Even though the four tree species discussed above (A. schimperiana, C. africana, C. macrostachyus, and R. caffra) are multipurpose tree species and considered the best to enhance soil quality, create a suitable environment for coffee production and benefit coffee yield and quality, their densities in coffee farms were lower than that of the exotic fast growing G. robusta (Figure 3). In Kenya, native tree species were also considered to provide a healthy environment, but their abundance was low due to their slow growth rate [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. In Tanzania, another reason for the preference of G. robusta might be that the wood can be utilized more easily than for native tree species, as native tree species require a permit to be cut down [START_REF]Parliament of the United Republic of Tanzania[END_REF][START_REF] Nath | Why do farmers plant more exotic than native trees? A case study from the Western Ghats, India[END_REF].

Farmers' management decisions to plant or remove a certain tree species in their plantations is usually based on their knowledge or tree preference [START_REF] Cerdán | Local knowledge of impacts of tree cover on ecosystem services in smallholder coffee production systems[END_REF][START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF][START_REF] Valencia | The use of farmers' knowledge in coffee agroforestry management: Implications for the conservation of tree biodiversity[END_REF]. We therefore need to look at their ESs priorities as socio-economic factors might influence farmers' choices for on-field composition. Our results confirm that the density of exotic tree species perceived to provide food, fodder and fuelwood are higher when farmers prioritize these ESs (Figure 6). This is especially the case when the tree species are exotic, as their presence in the field is usually due to management rather than natural occurrences. Some other studies also show the importance of shade tree species for coffee production is matched with their planting densities [START_REF] Belay | Woody species diversity and coffee production in remnant semi-natural dry Afromontane Forest in Zegie Peninsula, Ethiopia[END_REF][START_REF] Denu | The role of traditional coffee management in forest conservation and carbon storage in the Jimma Highlands, Ethiopia. For[END_REF]. Bukomenko, et al. [START_REF] Bukomeko | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda[END_REF], however, found a mismatch between ESs that are important for respondents and the trees they have on their fields. Graefe, et al. [START_REF] Graefe | Evaluating Farmers' Knowledge of Shade Trees in Different Cocoa Agro-Ecological Zones in Ghana[END_REF] used a similar methodology for cocoa production in Ghana and also reported disparities between higher ranked tree species suitable for cocoa intercropping and their abundance in the northern part of the cocoa belt with marginal conditions for cocoa production. This might be an adaptation strategy to diversify income, since they confirmed our findings for farms in the wetter southern region with optimal cocoa production conditions [START_REF] Graefe | Evaluating Farmers' Knowledge of Shade Trees in Different Cocoa Agro-Ecological Zones in Ghana[END_REF]. The match between shade tree density and prioritized ESs appears to be more consistent with direct short-or mid-term benefits for farmers, such as food, fodder, and firewood supply, rather than regulatory service provisioning, such as climate modification and soil fertility improvement [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. This becomes evident from the lower density of A. schimperiana (the most highly ranked tree species for regulatory services) in comparison to G. robusta and P. americana, which provide direct outputs like fuelwood and food (Figure 3). Our findings stress the importance of understanding the socio-economic component when investigating tree species distribution.

Factors Influencing Tree Species Ranking and Distribution

The first factor influencing tree species distribution, as just discussed, is farmers' preference and the ESs they consider important for their household.

In general, there is agreement on the ranking of tree species among small-scale coffee farmers at Mt. Kilimanjaro. We can confirm the finding by Gram, et al. [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF] that local knowledge regarding ranking of tree species is gender blind, as there were negligible differences in our study. Besides gender, participation in a farmer group did not influence the ranking. Farmers participating in farmer groups meet regularly, receive trainings and exchange knowledge and therefore might have better access to different information sources. This could have led to ranking differences, as other researchers have shown the influence of promotion activities of certain tree species on the perception and distribution of those species [START_REF] Rigal | Using farmers' local knowledge of tree provision of ecosystem services to strengthen the emergence of coffee-agroforestry landscapes in southwest China[END_REF][START_REF] Valencia | The use of farmers' knowledge in coffee agroforestry management: Implications for the conservation of tree biodiversity[END_REF]. In Kenya, G. robusta was considered suitable for intercropping with coffee, despite having similar traits to those of tree species believed to negatively affect coffee production [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. For example, the root system for both Eucalyptus spp. and G. robusta are perceived to be wide spreading [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. This discrepancy in perception of different tree species could be due to promotion activities from extension services [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. Such biases need to be considered when using local knowledge to inform recommendations. Some studies report an influence of elevation on the distribution and ranking of tree species in East Africa [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF]. However, we found that neither the presence nor density of tree species in the coffee fields of small-scale farmers at Mt. Kilimanjaro varied much across elevations for most investigated species. The reason could be that our focus was on the most common tree species that are well known by many farmers rather than the whole natural flora as reported by Hemp [START_REF] Hemp | The banana forests of Kilimanjaro: Biodiversity and conservation of the Chagga homegardens[END_REF]. Mangifera indica and S. siamea are known to grow better at lower elevations [START_REF] Mbuya | Useful Trees and Shrubs for Tanzania-Identification, Propagation and Management for Agricultural and Pastoral Communities[END_REF]; it is therefore not surprising that their density is higher at lower elevations. Rather unexpected is the reduced presence and density of C. africana with increased elevation as the suitable range for this tree species in the Kilimanjaro regions is reported to be between 1200 m and 2000 m asl. [START_REF] Mbuya | Useful Trees and Shrubs for Tanzania-Identification, Propagation and Management for Agricultural and Pastoral Communities[END_REF]. We therefore conclude that the density of C. africana is influenced by socio-economic factors rather than by environmental factors. In Uganda, C. africana was perceived to perform well for all ESs [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF] and is therefore found in farms at all elevations. Even though this tree species is also perceived to perform highly for regulatory services at Mt. Kilimanjaro, this was not a priority for most farmers. Food being the highest priority explains the presence of either M. indica or P. americana in 90% of the coffee farms, and the climatic needs for these two species explain the decrease in density of M. indica and the increase of density of P. americana along the elevation gradient [START_REF] Mbuya | Useful Trees and Shrubs for Tanzania-Identification, Propagation and Management for Agricultural and Pastoral Communities[END_REF]. Another influencing aspect might be increased distance to markets at higher elevations and therefore increased importance of self-sufficiency to farmers. The increased density of M. discoidea with increased elevation might be due to its importance for fodder supply. At lower elevations, farmers might have better access to other sources of fodder.

Rankings were not influenced by elevation, despite the relationship between shade tree distribution and elevation. This confirms the findings of Lamond, et al. [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF] that farmers' knowledge of tree attributes affecting field interactions between shade tree and coffee is consistent along an elevation gradient.

Tree Species Ranking in East Africa

Shade tree species in coffee agroforestry systems vary greatly among regions and even within East Africa; hence, it is not possible to generalize findings for the region. Studies with a similar approach to farmers' knowledge of tree species have been carried out in Rwanda [START_REF] Dumont | The utility of farmer ranking of tree attributes for selecting companion trees in coffee production systems[END_REF], Uganda [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF][START_REF] Bukomeko | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda[END_REF], and Kenya [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF]. Figure 7 combines the tree species included in the rankings and shows the overlaps in the species reported. Only seven shade tree species were commonly recorded in all countries and most of them are exotic. There are also very important tree species that only appear in the ranking of one country, for example A. schimperiana, the most important shade tree species for the Mt. Kilimanjaro region.

generalized. Including an approach based on functional ecology, linking the scores of shade tree species with their attributes can help generalizing results in future studies. This may lead to recommendations of characteristics of tree species that are generally more acceptable. Lamond, et al. [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF] already focused more on ranking attributes rather than tree species and Albertin, et al. [START_REF] Albertin | Perspectives on the Role of Shade Trees in Coffee Production Systems: An Assessment from the Nicoya Peninsula, Costa Rica[END_REF] investigated which tree characteristics are important for coffee farmers. Focusing on tree characteristics might also help to recommend shade tree species that are not very common, but might be a good fit for farmers since ranking is limited to the most common shade tree species, neglecting the importance of rather rare species.

Resilience of Coffee Agroforestry Systems

Some of the ESs shade tree species can provide, such as temperature regulation or soil moisture enhancement, might help mitigate the impacts of climate change [START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF][START_REF] Mbow | Achieving mitigation and adaptation to climate change through sustainable agroforestry practices in Africa[END_REF]. However, not all shade tree species are perceived as similarly effective in providing said services as the scores show (Figure 5). Tree species not influenced by elevation are considered more climate change resilient [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF]. This is the case for all investigated shade tree species for our study area within the investigated elevation range, besides C. africana, M. indica, S. siamea, P. americana, and M. discoidea.

A challenge of the present methodology is the small number of shade tree species that can be included in ES rankings. In order to enhance the ability of the agroforestry system to recover from external pressure and be more resilient in the face of climate change, it is important to protect the biodiversity of the farming systems [START_REF] Fischer | Biodiversity, ecosystem function, and resilience: Ten guiding principles for commodity production landscapes[END_REF]. It is therefore important to not only recommend the common species mentioned in this paper, but to retain a variety of tree species in the local ecosystem.

A better understanding of the optimal shade intensity and therefore the optimal shade tree density is also essential to tailor advice to farmers. Even though A. schimperiana can provide several services, knowledge of the optimal planting density and best management practices in terms of The comparison of our results with those from similar research done in other East African countries shows the importance of considering the local context in this type of research based on local knowledge. The results linked to specific shade tree species are specific to locations and cannot be generalized. Including an approach based on functional ecology, linking the scores of shade tree species with their attributes can help generalizing results in future studies. This may lead to recommendations of characteristics of tree species that are generally more acceptable. Lamond, et al. [START_REF] Lamond | Local knowledge of tree attributes underpins species selection on coffee farms[END_REF] already focused more on ranking attributes rather than tree species and Albertin, et al. [START_REF] Albertin | Perspectives on the Role of Shade Trees in Coffee Production Systems: An Assessment from the Nicoya Peninsula, Costa Rica[END_REF] investigated which tree characteristics are important for coffee farmers. Focusing on tree characteristics might also help to recommend shade tree species that are not very common, but might be a good fit for farmers since ranking is limited to the most common shade tree species, neglecting the importance of rather rare species.

Resilience of Coffee Agroforestry Systems

Some of the ESs shade tree species can provide, such as temperature regulation or soil moisture enhancement, might help mitigate the impacts of climate change [START_REF] Lin | Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture[END_REF][START_REF] Mbow | Achieving mitigation and adaptation to climate change through sustainable agroforestry practices in Africa[END_REF]. However, not all shade tree species are perceived as similarly effective in providing said services as the scores show (Figure 5). Tree species not influenced by elevation are considered more climate change resilient [START_REF] Gram | Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda[END_REF]. This is the case for all investigated shade tree species for our study area within the investigated elevation range, besides C. africana, M. indica, S. siamea, P. americana, and M. discoidea.

A challenge of the present methodology is the small number of shade tree species that can be included in ES rankings. In order to enhance the ability of the agroforestry system to recover from external pressure and be more resilient in the face of climate change, it is important to protect the biodiversity of the farming systems [START_REF] Fischer | Biodiversity, ecosystem function, and resilience: Ten guiding principles for commodity production landscapes[END_REF]. It is therefore important to not only recommend the common species mentioned in this paper, but to retain a variety of tree species in the local ecosystem.

A better understanding of the optimal shade intensity and therefore the optimal shade tree density is also essential to tailor advice to farmers. Even though A. schimperiana can provide several services, knowledge of the optimal planting density and best management practices in terms of pruning will still be required to achieve optimal shade levels and utilize all potential benefits for coffee production.

For socio-economic resilience, it is important to consult with farmers about their preferences prior to recommending a list of shade tree species, to ensure that the advice fits with their objectives and their constraints. The online decision-support tool for tree selection (shadetreeadvice.org) [START_REF] Van Der Wolf | Turning local knowledge on Agroforestry into an online decision-support tool for tree selection in smallholders[END_REF] is a first step in tailoring recommendations for important shade tree species to farmers' preferences. It also needs to be considered that with recurring low coffee prices, focusing primarily on shade tree species that optimize coffee production might not be economically sustainable. The emphasis might shift towards other ESs and shade tree species that increase the economic resilience of coffee farms.

Conclusions

This study demonstrated the link between farmers' preference for certain ESs and the planting density of shade tree species that provide these ESs. This shows the importance of understanding the factors underlying farmers' management decisions before recommending shade tree species. Despite being aware of negative crop-tree interactions, farmers might include tree species that are not necessarily beneficial to coffee production in order to acquire other services such as food, fodder, and firewood provisioning, all considered priorities for farmers on the southern slopes of Mt. Kilimanjaro.

Local knowledge of tree species' benefits can be very valuable to local producers; however, it needs to be complemented with expert knowledge to identify biases and fill in knowledge gaps. Even though our study has confirmed that local knowledge of tree species is gender blind, it could still be influenced by other factors such as differences in access to information, access to markets, and/or other socio-economic factors. Contrary to other studies, we did not observe an influence of elevation on the perceptions of tree species' provisioning of ESs. Nevertheless, it will be important to consider environmental aspects in future studies. Another limitation of this methodology is that it only includes the most common shade tree species, leaving aside rare indigenous species with high potential for agroforestry systems. This underestimates the importance of less common species, which might even be superior in providing certain ESs. It may also give the impression that the common tree species alone are enough to support a resilient coffee production system. One approach to improving recommendations might be focusing on the traits shown by highly ranked tree species. This will not only help comparing results from different regions and generalizing recommendations, but also ensure that a wider range of species are included.

Supplementary Materials:

The following are available online at http://www.mdpi.com/1999-4907/10/11/963/s1, Table S1: Tree species used for the ranking, Table S2: Ecosystem services used for the ranking, Figure S1: Scores and quasi-standard errors of tree species for fodder supply at (a) lower elevations (1148-1335 m asl) and (b) higher elevations (1336-1748 m asl). Red bars show tree species with significantly different scores between the two groups, Figure S2: Scores and quasi-standard errors of tree species for food provision (a,b), shade provision (c,d), and soil fertility (e,f) divided by gender (women are presented in a, c and e; men are presented in b, d and f). Red bars show tree species with significantly different scores between the two groups, Figure S3: Scores and quasi-standard errors of tree species for protection from heat (a,b), and increasing coffee quality (c,d) divided by affiliation to a farmers group (non-members are presented in a and c; members are presented in b and d). Red bars show tree species with significantly different scores between the two groups.

Author Contributions: Conceptualization, S.W.; Data curation, S.W. and T.L.; Formal analysis, S.W. and C.R.; Funding acquisition, S.W. and R.P.; Investigation, S.W.; Methodology, S.W.; Project administration, S.W., M.J., E.P. and R.P.; Software, S.W., C.R. and T.L.; Supervision, M.J., E.P. and R.P.; Visualization, S.W.; Writing-Original Draft, S.W.; Writing-Review & Editing, S.W., C.R., T.L., R.M., A.H., M.J., E.P. and R.P.

Forests

  1580 mm, and 1580 mm to 2200 mm at the higher slopes (1300 m to 1800 m asl) and mean annual temperatures of 23.4 to 18.8 • C and 18.8 to 16.1 • C, respectively.Coffee farmers from eight communities participated in this study. Six communities work with the non-government organization Hanns R. Neumann Stiftung (HRNS) (Isuki, Lemira Mroma, Masama Mula, Mudio, Kiwakabo, and Mbokomu); two communities have no connection to the HRNS, are located in the center of the southern slope (Narum and Mweka), and were included in the study to have a wider representation of the study area (Figure1).

Forests 2019 ,

 2019 10, x FOR PEER REVIEW 3 of 16Coffee farmers from eight communities participated in this study. Six communities work with the non-government organization Hanns R. Neumann Stiftung (HRNS) (Isuki, Lemira Mroma, Masama Mula, Mudio, Kiwakabo, and Mbokomu); two communities have no connection to the HRNS, are located in the center of the southern slope (Narum and Mweka), and were included in the study to have a wider representation of the study area (Figure1).

Figure 1 .

 1 Figure 1. Location of the research area within Tanzania (a) and the distribution of the respondents along the southern slope of Mt. Kilimanjaro, divided into the eight communities (b).

Figure 1 .

 1 Figure 1. Location of the research area within Tanzania (a) and the distribution of the respondents along the southern slope of Mt. Kilimanjaro, divided into the eight communities (b).

Forests

Figure 2 .

 2 Figure 2. Distribution of respondents along elevation.

Figure 2 .

 2 Figure 2. Distribution of respondents along elevation.

Forests 2019 , 16 Figure 3 .

 2019163 Figure 3. Percent of respondents reporting each species on their farm and average (+SE) tree density on those farms. The density of Musa spp. is much higher than the scale shown in the graph (1089 trees per ha on average).

Figure 3 .

 3 Figure 3. Percent of respondents reporting each species on their farm and average (+SE) tree density on those farms. The density of Musa spp. is much higher than the scale shown in the graph (1089 trees per ha on average).

Figure 4 .

 4 Figure 4. Scores and quasi-standard errors of tree species for (a) food provision, (b) fodder supply and (c) firewood supply. Dark blue bars represent exotic, and green bars indigenous tree species.For a better recommendation of tree species regarding multiple regulatory ESs associated with coffee production, the following ESs were combined into three categories: (a) coffee production enhancement (combining increase in coffee yield and quality), (b) protection from climatic hazards

Figure 4 .

 4 Figure 4. Scores and quasi-standard errors of tree species for (a) food provision, (b) fodder supply and (c) firewood supply. Dark blue bars represent exotic, and green bars indigenous tree species.

Forests 2019, 10

 10

Forests 2019 ,

 2019 10, x FOR PEER REVIEW 8 of 16

Figure 5 .

 5 Figure 5. Scores and quasi-standard errors of the tree species ranked according to: (a) increase of coffee yield and quality, (b) protection from heat, wind and shade provision and (c) mulch provision, soil fertility and soil moisture enhancement. Green bars represent indigenous, and dark blue bars exotic tree species.

Figure 5 .

 5 Figure 5. Scores and quasi-standard errors of the tree species ranked according to: (a) increase of coffee yield and quality, (b) protection from heat, wind and shade provision and (c) mulch provision, soil fertility and soil moisture enhancement. Green bars represent indigenous, and dark blue bars exotic tree species.

Figure 6 .

 6 Figure 6. Average (+SE) plant density of the five highest ranked tree species providing the services food, fodder and firewood. The dark bars show respondents who selected the three ESs as the three most important for their family, while the light bars indicate the plant density for respondents who did not select all three. Significant difference between plant density is shown by difference in letters (a and b) (p < 0.05). Blue bars represent exotic, and green bars indigenous species.

Figure 7 .

 7 Figure 7. Shade species included in different rankings in East Africa [15,16,24,25].

Figure 7 .

 7 Figure 7. Shade species included in different rankings in East Africa [15,16,24,25].

Table 1 .

 1 Ranking of Ecosystem services on a household level.

	Ecosystem services (ESs)	Selected as first ES	Among the first 3 ESs
	Food provision	76.4%	95.4%
	Firewood supply	10.3%	59.5%
	Fodder supply	2.7%	55.3%
	Shade provision	3.4%	31.7%
	Soil fertility improvement	2.7%	17.2%
	Increased coffee yield	0.0%	15.6%
	Soil moisture enhancement	1.5%	8.0%
	Increased coffee quality	0.8%	5.7%
	Protection against wind	1.1%	5.3%

Table 1 .

 1 Ranking of Ecosystem services on a household level.

	Ecosystem Services (ESs)	Selected as First ES	Among the First 3 ESs
	Food provision	76.4%	95.4%
	Firewood supply	10.3%	59.5%
	Fodder supply	2.7%	55.3%
	Shade provision	3.4%	31.7%
	Soil fertility improvement	2.7%	17.2%
	Increased coffee yield	0.0%	15.6%
	Soil moisture enhancement	1.5%	8.0%
	Increased coffee quality	0.8%	5.7%
	Protection against wind	1.1%	5.3%
	Mulch provision	0.8%	3.4%
	Protection from heat	0.0%	1.5%
	Weed suppression	0.4%	1.1%

Table 2 .

 2 Percent of significantly different pairwise comparisons of species' scores.

	Ecosystem Service	Number of Tree Species Included in the Ranking	Percent of Significant Differences between Pairs (p < 0.05)
	Mulch provision	11	89.1
	Protection from heat	12	87.9
	Increased coffee yield	11	87.3
	Increased coffee quality	10	86.7
	Soil moisture enhancement	11	85.5
	Shade provision	12	84.8
	Fodder supply	11	83.6
	Firewood supply	13	82.1
	Soil fertility improvement	13	76.9
	Protection against wind	16	72.5
	Food provision	10	71.1
	Weed suppression	13	66.7

Table 2 .

 2 Percent of significantly different pairwise comparisons of species' scores.

	Ecosystem

service Number of tree species included in the ranking Percent of significant differences between pairs (p < 0.05)

	Mulch provision	11	89.1
	Protection from heat	12	87.9
	Increased coffee yield	11	87.3
	Increased coffee quality	10	86.7
	Soil moisture enhancement	11	85.5
	Shade provision	12	84.8
	Fodder supply	11	83.6
	Firewood supply	13	82.1
	Soil fertility improvement	13	76.9
	Protection against wind	16	72.5
	Food provision	10	71.1
	Weed suppression	13	66.7

Funding: This research received no external funding.

Acknowledgments: This research would not have been possible without the participation of coffee farmers at Mt. Kilimanjaro. We thank all respondents for their time and for sharing their experience. Special thanks to Laurence Jassogne for her support during the research design and Happyness Thadei Mwenda, Thomas Terosi and Emmanuel Ruheta for their assistance in communicating with the farmers. We are grateful for the logistical support from the Hanns R. Neumann Stiftung. We thank the Manchester Metropolitan University for their financial support, the College for African wildlife management (MWEKA), the Kilimanjaro Research Group and the International Institute of Tropical Agriculture (IITA) for their collaboration and the Tanzania Commission for Science and Technology (COSTECH) for granting us the research permit.

Conflicts of Interest:

The authors declare no conflict of interest.


1

Algeria and Tunisia

Katia Boissevain 1

Christianity has a long presence in this part of the Mediterranean, dating back to the Roman Empire. Its activities were later reenacted during the French colonial period with the arrival of men and women of French, Spanish, Italian or Maltese origin. In the late nineteenth century, the Roman Catholic Church embarked on a vast mission of church building, to help and assist the colonial endeavour. This took effect in different ways, according to the political arrangement that France imposed on the country: colony for Algeria and protectorate for Tunisia . Alongside the establishment of Catholic churches, the Reformed Protestants also ensured that places of worship were available. During this particular period of the French conquest, Cardinal Charles Lavigerie, Archbishop of Algiers, hoped and aimed to convert Muslim subjects.

Nowadays, aside from minor Christian groups (Europeans who stayed on after independence, American or African expatriates working there), small communities of local converts are emerging in Algeria and Tunisia. Over the last twenty years, conversion to Christianity has been developing, mainly in Algeria and to a lesser extent in Tunisia, in the form of Evangelical Protestantism or neo-Evangelical churches. More recently, since 2003, Sub-Saharan African workers or students have also contributed to the revitalisation of the Church, both Catholic and Protestant.

States and "New" Religious Minorities

In Algeria, a discreet conversion movement has been at work since the early 1990s but received significant press coverage for the first time in 2004. The press campaign (by national media) highlighted the effectiveness of proselytism in Kabylia, the Berber region in the north of Algeria. The numbers were intentionally inflated (30% of the population in the region of Tizi-Ouzou) in order to inflame public concern and thus force the State to take measures. The main step was the passing of the law concerning 'non-Muslim religions ' (2006), which forbids religious celebrations outside defined religious buildings (and only with an administrative authorisation) and proselytism. With no official numbers, conversions are difficult to estimate, but the Eglise Protestante d'Algérie (EPA, founded in 1972) is a federation of around 25 churches, comprising Reformed, Methodists, Lutherans and Evangelicals. The Anglicans and Adventist converts are outside this federation. It is thought that the members within the federation number between 10,000 and 15,000, and those outside around the same numbers. Despite the legal framework (since 2011, the EPA has been officially recognised by the State), regular attacks on Christian places of worship are reported and Christians are frequently taken to court on charges of proselytism.

In Tunisia, the numbers seem to be fewer still. Here again, official numbers are unavailable and the number of local Christian converts is estimated to be between 2,000 and 10,000. In contrast to Algeria, they are mainly to be found in urban settings, where they openly congregate in churches. Administrative intimidation also occurs and a subtle balance is at work between 'freedom of conscience, of belief and free expression of religion' (Article 6 of the 2014 Constitution) and the prohibition of proselytism. The Catholics, on the other hand, all of whom are foreigners, number around 20,000.

Leaving Islam and Becoming Christian

In both countries, when conversion to Christianity is discussed with Muslims, the question raised is that of apostasy (the negative side of the process), which is considered an act of religious treason. Indeed, it is common knowledge that were Sharia law followed, religious conversion would be punished by death. The fact that this sanction is a subject of debate and that no consensus emerges among Muslim scholars does not nuance opinion at the popular level. It is considered that the apostate (murtad) has turned his or her back on Islam, and thus on the Umma (Muslim religious community) as a whole. The accusations of religious treason are debated in the press, both in Algeria and Tunisia, through vast campaigns that portray the converts as a menace to the stability of the country. How do the men and women who have chosen to change religion counter the accusations of treason on the political and social levels?

Since independence both Algeria and Tunisia have based their national construction on the idea of the strict equation between one country, one language and one religion, putting aside any social reality that contradicted this ideology, such as the Berber linguistic specificity. In Algeria, this ideology of unity has been shaken by the Berberist movement, but in Tunisia, nothing apart from the acknowledgment of its small Jewish community has come to contradict the equation 'Tunisian = Muslim'. Today, Protestantism, especially in its Evangelical form, is perceived as a religion imported from the USA. As such, it is not welcomed, since the United States is perceived to be a friend and supporter of Israel. This perception and 'Israel's' centrality in Evangelical theology are no doubt the main reasons for the strong reactions Protestantism provokes.

Apostates/converts (depending on the point of view) are most often considered traitors: in an evolutionary understanding of religion, Islam is the last and most complete of the three revelations (Judaism and Christianity being the previous two). Converting to Christianity is therefore perceived as a pointless regression. When a conversion is announced, or discovered, families feel they have been cheated upon and abandoned and are often stunned by a secretly matured decision. Becoming Christian is interpreted by the others as a choice formulated against everything for which they have been raised. If it is a mistake to think that most Algerians or Tunisians conscientiously practise their ritual obligations, still it remains the case that a Muslim rhythm marks the day, the yearly calendar and the life rituals. Stepping aside and choosing the Christian religion is not only a break with the social body, it also breaks with the social rhythm. When families interpret this change as an allegiance to the 'God of the French' or, worse still, the USA, new converts often find themselves excluded, sometimes willingly, from family gatherings with religious connotations, such as circumcision ceremonies, weddings, birth or death rituals, Eid al-Fitr, Eid al-Adha and Mouled (birth of the Prophet Muhammed).

The other reproach formulated against converts is that they maintain an ambiguous relation with 'abroad' and are not loyal to their homeland. Critics might allege that many converts secretly hope that conversion will help them acquire a visa or a marriage with a foreigner (preferably a Westerner). As a result of these accusations, Algerian and Tunisian converts are constantly reaffirming their love for their nation and for their culturewhich they dissociate from their religion. Whether on the 'Christians in Tunisia' website, where it is stated that we 'are Tunisian, we were born in Tunisia and we live in Tunisia' or in interviews collected by Karima Dirèche in Algeria, where Kabyle converts assure that they could never leave the beauty of their land, the important issue is to demonstrate that one's religious identity was chosen spontaneously and not because of transnational Evangelical networks which are, in any case, most of the time unknown to the converts themselves.

Intertwined Histories of Christianity

Contemporary Evangelical movements in Algeria and Tunisia reactivate discourses and representations of the ancient Christianity of North Africa as a mean of legitimisation. In the fourth and fifth centuries, this form of Christianity was linked to Rome and allowed for the development of the Church of Africa, directed by the Bishop of Carthage. Today, during their worship, pastors often make reference to the ancient Christian martyrs in a compression of historical time, thus bridging the gap between the tortures endured by the first Christians and the vexations faced by converts. The figures of Cyprian, Tertullian and Saint Augustine are regularly called upon, and the theme of persecution and courage becomes a powerful ferment for converts' identity.

Much later, the Church of Algeria was founded by the creation of the Bishopric of Algiers in 1838. It was then mainly a Catholic Christianity linked to the Algerian colonial project, which it was hoped would expand throughout the country. The Berber regions attracted the greatest attention as they were considered to be less fully Islamised. This idea guided the action of the Archbishop of Algiers, Cardinal Charles de Lavigerie, who in 1868 founded the Missionaries of Africa, commonly known as the White Fathers and Sisters, devoted to the conversion of the Arabs and the peoples of Central Africa. As early as 1840, a Reformed mission followed, to serve soldiers and farmers who were settling.

Today, the Catholic churches in Algeria and Tunisia are not much solicited for religious conversions. Muslims turn more willingly toward the Evangelicals. There can be several reasons for this. In 1957, the year of Tunisian independence, the Catholic Church still possessed around one hundred church buildings and a lot of land. In 1964, the Vatican and the new Bourguiba government signed an agreement called the Modus Vivendi, in which the Tunisian government allowed the Catholic Church to remain in the country in exchange for much of the land and religious buildings in its possession. Seven churches were left open for worship. Additionally, the Church was required to officially renounce proselytism and solely direct its religious activities toward the existing Catholic community. The Church was also allowed to maintain educational and health-oriented activities (hospitals) aimed at serving the Tunisian population.

Contrasting with this is the situation of the Protestant churches. Even though the Reformed Church was present in the region from the late nineteenth century (the first Protestant military chaplain, Georges Durmeyer, founded the Reformed Church of Tunis in 1882), no such agreement was passed, maybe for lack of a single interlocutor. As a consequence, the Protestants did not find themselves tied to this formal prohibition. In the 1990s when Evangelical missionary networks came into play alongside the mainstream Protestants, they did not feel constrained in their desire to spread the Christian message, as their theology requires of them.

In both Algeria and Tunisia, the Catholics are identified with the colonial period, whereas Evangelicals are perceived to be in a modern call to Jesus, both worldwide and local: worldwide because rhetoric insists on its supposed 'tidal wave' effect (in Latin America, Africa or Asia), and local because it taps into the ancient history of North Africa, particularly the pre-Arab, pre-Muslim, 'original' Berber identity. This Berber discourse is particularly effective in Algeria.

Furthermore, it has to be stressed that aside from the pastors and the formal religious hierarchy, local converts rarely make an issue of their denominational identity. Whether they are Methodists, Pentecostals or some other denomination, most of them just define themselves as 'Christians', at best 'Evangelicals', embraced by the love of Jesus. They build their new religious identity in opposition to Islam and generally remain aloof from the theological differences between Christian denominations.

In Algiers, Monsignor Henri Teissier was the Catholic Archbishop until 2008, when he was succeeded by Ghaleb Bader. The leader of the Eglise Protestante d'Algérie was the American Hugh Johnson from 1972 to 2008; he was succeeded by Mustapha Krireche, who served until 2016, when he in turn was succeeded by Noureddine Benzid. In the Catholic Church in Tunisia, Illarion Antoniazi succeeded the Palestinian Maroun Lahham, who had been Bishop of Tunis from 2005 and then Archbishop from 2010 to 2012. The main Protestant churches in Tunis are the Reformed Church (led by 8 pastors) and St George's Anglican Church. Their main mission is to provide for Western or African believers. Alongside this worship, during separate services, Tunisian pastors offer worship in the Tunisian dialect for the local converts. In order to be able to remain in the country without trouble, the foreign pastors must not undertake any proselytism toward the Tunisian community and are best advised to have very little contact.

Who are the Christians?

Converts come from diverse sociological categories: young or old; men or women; highly educated, middle-class or socially fragile. People in their late teens or early twenties in Tunisia turn to Christianity with deep mystical passion and find in their new-found love of Jesus a way to affirm their own choices and differences with the social environment. In Algeria and more specifically in Kabylia, Karima Dirèche has shown how the religious choice is also a political one, set in the debate about Berber specificity, distinct from the Arab identity and therefore from the Muslim one. Their claim to a specific Algerian identity is consequently strengthened.

Moreover, the arrival of Christian Sub-Saharan African migrants, be they students, workers or refugees, has had a great effect on the make-up of Christianity in the region. Having been quiet churches up to the 1990s, today they are loud and joyous places with singing and passionate praising. Churches have had to adapt and call upon African priests and pastors to help lead this movement. Alongside these changes there has been an increase in intentional evangelistic outreach. As a consequence, African Pentecostal pastors (mainly from Nigeria and Côte d'Ivoire) convinced some locals to join their churches of different denominations.

Conclusion

Converts usually claim to have been attracted to Christianity either 'spontaneously', through a discussion with a friend, or thanks to radio, TV or the Internet. The myth of endogenous calling is very strong and is deployed with the aim of counteracting accusations of being the toy of outside interests. For example, a Korean missionary is identified as an Arabic language student, a touching Christian song on the radio is heard as a personal call from God, and the mobile recording studio used for encouraging local Christian artists to write Christian songs is interpreted as 'really nice people here to help'. Local discourse makes every effort to minimise the implication that transnational Christian organisations (such as MENA -Ministère Evangélique parmi les Nations Arabophones) are behind the conversion of local people, who have supposedly been caught unawares. However, Christian media are broadcast in the region and are listened to on the radio, watched on TV and followed on the Internet. The existence of small communities of local converts to Christianity, despite their relatively small numbers, has a clear impact on public debates concerning freedom of thought or the way to deal legally with religious diversity.

Aix Marseille Univ, CNRS, IDEMEC, Aix-en-Provence, France