2.3.1 Vegetation data collection and analysis
We collected vegetation data from 189 plots (each 63 plots) based on the plot based vegetation assessment protocol as mostly used in many studies in southwest Ethiopia (Senbeta and Denich 2006, Schmitt et al. 2010, Hundera et al. 2015). A plot size of 20 m by 20 m (400m2 ) were laid systematically where the first plot is randomly or arbitrarily selected and the next locations spaced homogeneously throughout the survey. We selected coffee agroforest first and then coffee forest and natural forest subsequently along the transect line. The distance between the plot varies along the transect as a result of forest condition.
Data were analyzed using the most commonly used metrics to estimate diversity such as richness, Shannon-Wiener index and Simpson index. This is because richness is affected by sample size, Shannon-Wiener index is affected by rare species and Simpson index is affected by common species, hence, parallel use of these diversity measures are a general practice in ecological study (Yeom and Kim 2011, Morris et al. 2014).
Woody species richness was computed for overall richness and woody plants with diameter greater than or equal to 10cm from recorded vegetation data in the coffee agroforest, coffee forest and natural forest. We computed richness per plot for each forest type (coffee agroforest, coffee forest and natural forest). All woody species recorded within 400m2 were converted into presence-absence data. Woody species richness is expressed as the number of species per each forest types: the coffee agroforest, coffee forest and natural forest (Magurran 2004, Magurran and McGill 2011).
To test the difference of diversity for three sample groups (coffee agroforest, coffee forest and natural forest) data were tested for normality and homogeneity of variance before the analysis. Where these met, One way analysis of variance (ANOVA) was used to compare diversity between the three forest types. When the assumptions were violated, the Non parametric Kruskal Wallis H test was employed to compare the woody species richness between the three forest types. Data were organized in Microsoft Excel, and analyzed in SPSS version 25 and PAST software 3.24.
Diversity analysis was conducted for woody species with diameter greater than or equal to 10 cm. Shannon-Wiener index, Shannon Evenness and Simpson index were computed to compare the coffee agroforest, coffee forest and natural forest (Magurran 2004, Magurran and McGill 2011). Shannon-Wiener index (H') was calculated as :
\({H}^{{\prime }}=-\sum _{i=1}^{s}pi*\text{ln}pi\) , where pi is the proportion of individuals found in the ith species and ln is the natural logarithm.
Shannon evenness (E') was calculated as \({E}^{{\prime }}=\frac{H}{\text{ln}s}\) where H is Shannon diversity and S is the number of species.
Simpson diversity index (1-D) was calculated as \(1-D=\sum {pi}^{2}\) where pi is the proportion of individuals found in the ith species. Data were organized in Microsoft Excel and imported for analyzed in SPSS version 25 and PAST software 3.24.
Ecological importance of woody plants were studied through the relative importance of the species IVI) (Cottam and Curtis 1956, Kacholi et al. 2014, Teketay et al. 2018, Asigbaase et al. 2019). It was computed based on basal area, frequency and density of woody plants (Cottam and Curtis 1956, Asigbaase et al. 2019, Kunwar et al. 2020) with the equation \(IVI=DO+RD+RF\), where DO is the relative dominance calculated as basal area per forest types, RD is the relative density calculated as the number of individual per ha, RF is the relative frequency calculated as the proportion of individual per forest types. Importance Value Index (IVI) was used as a proxy for a change in ecological important of the coffee agroforest, coffee forest and natural forest during coffee management intensification. The higher the value the greater the importance of woody species in the forest.
2.3.2 Ethnoecological data collection and analysis
Ethnoecological data collection started with consulting the forest user group committee. It was guided by generating the required information rather than recruiting a representative informants to the whole population. In this regard purposive or convenience sampling was used to recruit the informants (Martin 1995, Tongco 2007, Longhurst 2016, Kunwar et al. 2020). A potential participants were suggested by the forest user group committee. There was no payment for the participants except refreshment in a form of coffee and tea. The interview and discussion were carried out in the informants residential area because here the interviewee would be most relaxed and this has also been suggested by Dawson et al. (1993). The interview was held in local language (Afaan Oromo and sometimes Amharic) and the researcher took notes in English or translated into English soon after the discussion.
Resampling, and the concept of saturation and triangulation were used to reduce self bias selection and respondent bias, respectively. Resampling refers the selection of the right informant each time. The study activities were divided into case by case and participants were selected for each case. Data saturation refers the point where in-depth information is captured and there is no further new information obtained when interviewing a new respondent (Wray et al. 2007, Fusch and Ness 2015). Data triangulation refers collecting data from multiple sources (Wray et al. 2007, Fusch and Ness 2015). Albuquerque et al. (2017) suggested a mix of methods to triangulate ethnoecological data. Effort was made to cross check collected data through informal discussion among the informants and analyzed normatively.
Free listing and semi-structured interviews were ethnoecological tools employed to generate data (Albuquerque et al. 2017, Furusawa et al. 2014, Dorji et al. 2019). Prior to free listing the informants were briefed on the objective of the study. They were asked about the three types of forest identified for the study and all participants were in a position to distinguish coffee agroforest, coffee forest and natural forest. Eight focus group discussions were undertaken with groups of forest users from four sites consisting of 4 to 6 individuals divided by age, either 18 to 35 years (youth) or greater than 35 years (old). During the interview process the groups were asked about their perception of the benefits of the forest in their livelihoods. The question asked was stated as what is/are the benefits of the forest in your surrounding? Which forest type is more important to suggested forest benefits? The groups listed the general ecosystem services of the forest they have experienced in their surroundings and rank the relative importance of each forest type out of 100. Initially it was thought to use beans for estimating the relative importance. Fortunately participated informants had grade and junior high school education and they wrote down on a paper. The relative importance was estimated based on percentage out of 100. The researcher distributed paper and played a facilitator role during the process.
Cited ecosystem services were grouped into provisioning, regulating, cultural and supporting ecosystems services as per millennium ecosystem assessment (MEA 2005). Provisioning ecosystem services were aggregated into major categories and a semi-structured checklist was prepared for further individual interview (Martin 1995).
A checklist for semi- structured interview was prepared based on the preliminary findings of the free listing. The checklist included but was not limited to questions such as, do you collect forest product x (local name of the product)? Where do you collect them? A total of 136 forest users (107 males and 29 women) were interviewed. Furthermore 15 focus group discussions (5 groups old, 5 groups youth, 5 groups women) were conducted to assess the relative importance of provisioning ecosystem services and forest types (coffee agroforest, coffee forest and natural forest). The size of a group varied between 4 to 5 individuals. The duration of an interview and a focus group discussion differed case by case (an hour for focus group discussion and 30 minutes to 40 minutes for an interview).
The proportion of citations and ranking were used to organize and analyze the relative importance of provisioning ecosystem services and forest types (Martin 1995). Indicators of forest products were used to associate forest products with the coffee agroforest, coffee forest and natural forest (Gardener 2014). The association was estimated based on Pearson residual (Person residual= \((Observed-Expected)/\surd Expected\)). Gardener (2014) stated a Pearson residual is normally distributed and a value of -2 as a significant.
The use value of woody plants was estimated based on number of citations. Woody species recorded during the inventory were organized and listed for use value estimation.
Semi-structured interviews were conducted to assess the uses of woody plants. Forest users were asked but not limited to the statement as following questions, Local name of a plant (1st, 2nd, 3rd ,----------- 64th ), Do you know the species x (local name of the plant)?, What is/are the uses of the plant? (The use of planted coffee in coffee agroforest were not recorded) and Do you remove or maintain the plant in your coffee agroforest. A total of 96 forest users (85 man and 11 women) were interviewed. Previous studies by Gueze et al. (2014) and Soares et al. (2017) employed similar approaches to assess the uses of plants. The number of uses were calculated from use categories of woody species developed by Albuquerque and Oliveira (2007) and Albuquerque et al. (2009). The number of woody plant uses were expressed as the total number of citation of uses. The number of use citation helped to order or rank the relative importance of woody plant species for specific uses. The number of uses were used to categorize woody plants into three categories generalist, specialist and versatile following Albuquerque et al. (2009). Woody plants were considered as specialist with at most 2 uses, generalist with at least 3 to 5 uses and versatile with more than 5 (Albuquerque et al. 2009). The number of woody species per use categories were used to categorize woody plants into three categories highly redundant(> 75%), redundant (25–75%), not redundant (< 25%) (Albuquerque et al. 2007). The concept of redundancy is adopted from ecological redundancy for utilitarian concept (Albuquerque et al. 2007). The concept refers to species with similar uses to distinguish from woody plant species with specific use (Albuquerque et al. 2007,Santoro et al. 2015). In forest resources use the presence of redundant species guarantees the resilience of a given system (Albuquerque et al. 2007,Santoro et al. 2015).
A change in provisioning ecosystem services across the coffee agroforest, coffee forest and natural forest were assessed based on plant use value (Phillips and Gentry 1993, Castaneda and Stepp 2007, Andrade-Cetto and Heinrich 2011, Faruque et al. 2018). Use value was calculated as \(UV=\sum u/n\) where u refers the number of uses mentioned by forest users and n refers the total number of forest users interviewed (Phillips and Gentry 1993, Faruque et al. 2018). The total uses value of the coffee agroforest, coffee forest and natural forest were calculated as the summation of the use value of all woody species recorded within each forest types (Andrade-Cetto and Heinrich 2011, Ouedraogo et al. 2014). A Kruskal Wallis H test was used to compare a difference in the ecosystem services (benefits) between the natural forest, coffee forest and coffee agroforest.
Relative frequency citations (RFC) was used as consensus of woody species that were retained or removed from coffee agroforest. Relative frequency citations were expressed as the number of times a particular species was mentioned to be retained divided by the total number of interviewees (Faruque et al. 2018). One way of understanding the effect of forest modification to coffee is to relate ecologically important woody species and the uses of woody species (Gueze et al. 2014). A Spearman's rank correlation was conducted to investigate the relationship between the availability of woody species and plant uses (Sop et al. 2012, Gueze et al. 2014). Woody species availability across the coffee agroforest, coffee forest and natural forest were based on phytosociological metrics (relative density, relative frequency, dominance) (Albuquerque et al. 2009). Ethnoecological data were summarised descriptively (Jalilova and Vacik 2012, Ahammad et al. 2019) using Microsoft Excel and imported to SPSS version 25 for non parametric analytical Spearman's rank correlation test.