{"metadata":{"id":"0153fe6d555dd04ece6ce3a4a9ba2b47","source":"gardian_index","url":"https://data.worldagroforestry.org/api/access/datafile/:persistentId/?persistentId=doi:10.34725/DVN/CBHCKS/JXIKHR"},"pageCount":33,"title":"UNDERTAKING A BIOPHYSICAL BASELINE SURVEY AND ANNUAL TRACKING OF ECOSYSTEM HEALTH FOR THE KENYA CEREAL ENHANCEMENT PROGRAMME-CLIMATE RESILIENT AGRICULTURAL LIVELIHOODS WINDOW","keywords":[],"chapters":[{"head":"Background on the Land Degradation Surveillance Framework (LDSF)","index":1,"paragraphs":[{"index":1,"size":49,"text":"The project will identify and measure key indicators of land and soil health in order to understand drivers of degradation, and monitor changes over time using the Land Degradation Surveillance Framework (LDSF) methodology (http://landscapeportal.org/blog/2015/03/25/the-land-degradation-surveillance-framework-ldsf/). The LDSF provides a field protocol for measuring indicators of the \"health\" of an ecosystem."},{"index":2,"size":109,"text":"The LDSF was developed by the World Agroforestry Centre (ICRAF) in response to the need for consistent field methods and indicator frameworks to assess land health in landscapes. The framework has been applied in projects across the global tropics, and is currently one of the largest land health databases globally with more than 30,000 observations, shared at http://landscapeportal.org. This project will benefit from existing data in the LDSF database, while at the same time contributing to these critically important global datasets through on-going data collection. Earth Observation (EO) data will be combined with the LDSF framework to develop the outputs for the project, including land degradation and soil health."},{"index":3,"size":196,"text":"Specifically, the LDSF is a field methodology to collect data on key biophysical characteristics across the landscape. This includes quantifying the percent of the landscape that is cultivated, as well as identifying which crops and management practices are being used. The LDSF also assesses land ownership, vegetation structure and dominant land use. Understanding the woody vegetation cover is also an important component of the LDSF. This is done by quantifying the tree and shrub densities and diversity at each plot. Analysis on tree density and diversity within cultivated systems is also conducted and provides insights into the \"climate-smartness\" of the system. A key indicator of land degradation is soil erosion prevalence, therefore, soil erosion is quantified and classified at each subplot (n=4) per plot, as well as the quantification of soil water conservation measures. Finally, infiltration capacity is measured using single ring infiltrometers. Infilitration capacity of the soil has important implications for compaction and water erosion through runoff. All of these data are presented in the report. Still pending are the analyses of the soil properties. This is ongoing as the soil samples collected at each site are currently in the soil analytical laboratory being processed."}]},{"head":"Specific Activities on the ICRAF Component as Stated in the Agreement","index":2,"paragraphs":[{"index":1,"size":77,"text":"1. Develop survey methodology detailing study design, methodology, tools, work plan and timelines documented 2. Procure of assorted LDSF Field Survey equipment 3. Conduct five LDSF surveys across the KCEP-CRAL action areas 4. Process, analyse and document the soil samples 5. Conduct Earth Observation-based assessment of biophysical indicators over time 6. Conduct capacity development opportunities with members of the PCU M&E staff and Government counterparts on LDSF field methodology 7. Share outputs and data from the LDSF"}]},{"head":"Timeline of Activities","index":3,"paragraphs":[{"index":1,"size":162,"text":"1. The MoU between the Government of Kenya and ICRAF was signed 23 July 2018 2. A partner meeting between the KCEP-CRAL PCU, FAO and ICRAFheld at ICRAF to discuss and share details on the field survey methodology and collaboration. 3. The LDSF methodology was approved by IFAD, KCEP-CRAL and partners in September 2018. 4. LDSF sites were co-located with HH Baseline surveys in Nov 2018. Household survey coordinates were shared with ICRAF and five LDSF field sites were randomized to be co-located with household surveys across the KCEP-CRAL project action sites (see map below). 5. Procurement of equipment from Aug-Dec 2018. 6. LDSF field surveys and trainings commenced in November 2018 with Muminji and finished in June 2019 in Chasimba (see below). In each site, government authorities and KCEP-CRAL representatives were consulted and engaged. These in-the-field trainings contributed to the capacity building aspect of the project. 7. Presentation of LDSF results to KCEP-CRAL project team during IFAD mission in May 2019."},{"index":2,"size":36,"text":"A special acknowledgement to John Thiongo Maina, the lead technician and Anthony Njuguna, the lead driver and field assisant who conducted the field surveys and led the trainings for the KCEP-CRAL representatives on the LDSF methodology."},{"index":3,"size":12,"text":"This report highlights the preliminary data analysis of the LDSF field data.  "}]},{"head":"Landscape Characteristics","index":4,"paragraphs":[{"index":1,"size":61,"text":"Slope was measured in each plot, using a clinometer and measured in degrees. In general, landscapes with slopes less than ~10 degrees are considered gently sloping. Muminji had the highest average slope across the site, with 12 degrees, compared to Thange, which had the lowest slope and and the smallest variation in slope (2.4 degrees) as shown in the below boxplots. "}]},{"head":"Cultivation","index":5,"paragraphs":[{"index":1,"size":35,"text":"Each sampled plot is classified as cultivated or non-cultivated. Seventy-four percent of the sampled plots in Chasimba were classified as cultivated, 42% in Gatunga, 57% in KuboSouth, 47% in Muminji, and 61 % in Thange."},{"index":2,"size":102,"text":"The main crops in Muminji included maize, beans, cow peas, green grams, and some khat. Most plots were cultivated for more than 25 years, on average. Main crops in Gatunga included green grams, cow pea, and millet. In Thange, main crops included maize, pigeon pea, green gram, and cow peas. In KuboSouth main crops included maize, cow pea, green gramm but also perrenial crops such as cashew, coco, citrus. In Chasimba, main crops included maize, cassava, cow pea, and coco. Most of the non-cultivated plots were used primarily for grazing land for more than 30 or 40 years or were fallow land."}]},{"head":"Land Ownership","index":6,"paragraphs":[{"index":1,"size":27,"text":"The land ownership of each plot was classified as either private, communual, or governement. The Land ownership was predominately private across the five LDSF sites (Table 1). "}]},{"head":"Vegetation Structure","index":7,"paragraphs":[{"index":1,"size":53,"text":"The LDSF uses the FAO Land Cover Classification System (LCCS), which was developed in the context of the FAO-AFRICOVER project. Each sampled plot was classified by the vegetation structure. Figure 3 shows the number of each plots per category. The most common land cover class was cropland, which is the annual cropping system. "}]},{"head":"Dominant Land Use","index":8,"paragraphs":[{"index":1,"size":36,"text":"The land use of the plots were also classified as either pasture/rangeland, annual cropping system, perennial cropping system, annual crops with trees (annual agroforestry), perennial cropping system with trees (perennial agroforestry), fallow, protected areas, or woodlots."},{"index":2,"size":50,"text":"In Chasimba, annual crops grown with the incorporation of the trees (annual agroforestry) was the dominant land use, while in Gatunga and Thange, both pasture/rangeland and annual cropping systems were most common. In KuboSouth, annual agroforestry systems were most common. In Muminji, we did not assess the land use categories.  "}]},{"head":"Tree and Shrub Densities","index":9,"paragraphs":[{"index":1,"size":24,"text":"In the LDSF, shrubs are classified as woody vegetation between 1.5m and 3.0m tall, and trees are classified as woody vegetation above 3.0m tall."},{"index":2,"size":34,"text":"Averages shrub density was higher in non-cultivated plots in all sites. The table below shows the average tree and shrub densities in plots classifed as cultivated (PlotCultMgd = yes) and non-cultivated (PlotCultMgd = no)."},{"index":3,"size":88,"text":"Chasimba and Muminji had the highest average shrub densities in non-cultivated plots. The Muminji LDSF had an average of 250 shrubs per ha in non-cultivated plots compared to an average of 89 shrubs per ha in cultivated plots. Average shrub density in Chasimba was 270 shrubs per ha in non-cultivated plots compared to 43 shrubs per ha in cultivated plots. Gatunga had the lowest shrub densities in non-cultivated plots, an average of 108 trees per ha in non-cultivated plots compared to 21 shrubs per ha in cultivated plots."},{"index":4,"size":53,"text":"KuboSouth had the highest shrub density in cultivated plots. Average shrub density in KuboSouth was 163 shrubs per ha in non-cultivated plots compared to 101 shrubs per ha in cultivated plots. Average shrub density in Thange was 150 shrubs per ha in non-cultivated plots compared to 34 shrubs per ha in cultivated plots."},{"index":5,"size":54,"text":"Muminji and KuboSouth had the highest tree densities in cultivated plots. Average tree density in Muminji was 249 trees per ha in non-cultivated plots compared to 100 trees per ha in cultivated plots. KuboSouth had an average of 177 trees per ha in culitvated plots compared to 243 tree per ha in non-cultivated plots."},{"index":6,"size":67,"text":"Average tree density in Gatunga was 146 trees per ha in non-cultivated plots compared to 33 trees per ha in cultivated plots. Average tree density in Thange was 198 trees per ha in non-cultivated plots compared to 33 trees per ha in cultivated plots. Chasimba had the lowest tree densities overall with 76 trees per ha in non-cultivated plots and 62 trees per ha in cultivated plots.  "}]},{"head":"Tree Species Diversity","index":10,"paragraphs":[{"index":1,"size":69,"text":"Tree species diveristy is an indicator of biodiversity. Higher diversity of tree species is important for a number of different ecosystem services as well as for the overall resilience of the system. This includes natural systems as well as cropping systems. In agroforesty systems, diversity can be harnessed to provide a diverse range of products and services to people and is an indicator the overall health of the land."},{"index":2,"size":54,"text":"Trees were identified in each 100-m2 subplot (n=4 per plot). The below graphics demonstrate the abundance of each tree species per site. In total, 89 unique tree species were identified in the Muminji LDSF site, 47 at the Gatunga site, 59 at the Thange site, 50 at Chasimba, and 126 at the KuboSouth site."},{"index":3,"size":40,"text":"While it is important to note the number of tree species, it is also critical to acknowledge if the tree species is exotic or indigenous, and also if the species is considered invasive. For example, the most common species at  "}]},{"head":"Tree Species Diversity in Cultivated and Non-cultivated Plots","index":11,"paragraphs":[{"index":1,"size":88,"text":"Differences were observed in the species composition in cultivated vs non-cultivated plots. For example, in Muminji, there were 47 unique tree species encountered in non-cultivated plots and 38 tree species in cultivated plots. Grevillea robusta and Euphorbia tirucalli were only found in cultivated plots. In contrast, Gymnosporia buxifolia, Faurea saligna, Acacia nilotica, Acacia nubica and Acacia hockii were only found in non-cultivated plots in Muminji. The below graphic illustrates the frequency of species in the cultivated and non-cultivated plots (for all species that had more than three counts)."},{"index":2,"size":17,"text":"In Gatunga, 36 tree species were observed in non-cultivated plots and 18 tree species in cultivated plots. "}]},{"head":"Erosion Prevalence","index":12,"paragraphs":[{"index":1,"size":107,"text":"Erosion is the most widespread form of land degradation. Erosion was scored and classified in each subplot (n=4) per plot. Plots that had three or more subplots with erosion were classified as having severe erosion. The below graphics demonstrate the erosion prevalence across the sites. The bar chart shows the number of plots per cluster that had severe erosion. In general, 10 plots per cluster were sampled. Therefore a cluster with 10 plots having severe erosion such as Chasimba cluster four had high erosion prevalence across that cluster (which is 1 km2), compared to KuboSouth cluster one which only had two plots classified as having severe erosion."},{"index":2,"size":46,"text":"The violin boxplots show the same data at the site level. KuboSouth had the lowest erosion prevalence, only 5% of the sampled plots, followed by Thange (32%). In contrast, Chasimba had 65% of the site with severe erosion. The average erosion across the sites was 41%.  "}]},{"head":"Soil Water Conservation Measures","index":13,"paragraphs":[{"index":1,"size":86,"text":"Soil water conservation (SWC) measures were classified and counted at each plot. Examples of SWC measures could be stone bunds or zai pits (labeled as structural), contour tree planting (labeled as vegetative), or a combination of both vegetative and structural (labeled as both). The below graphic demonstrates the overall low use of SWC measures across the sites. Thange had the highest number of SWC measures and Chasimba had the lowest. These data have implications for soil erosion and opportunities to employ options to curb erosion prevalence. "}]},{"head":"Infiltration Capacity","index":14,"paragraphs":[{"index":1,"size":53,"text":"Infiltration capacity was measured at three plots per cluster in each site. These data will be used to model saturated hydraulic conductivity and to understand how land use and land management influence infiltration capacity of water into the soil. The below graphic shows the variation in infiltration rates within and between the sites."},{"index":2,"size":72,"text":"The infiltration rate is defined as the volume flux of water flowing into the profile per unit of soil surface area. For the special condition in which rainfall rate (or the rate in which water is made available at the soil surface) exceeds the ability of the soil to absorb water, i.e. under ponding, infiltration proceeds at a maximal rate, which is known as soil infiltration capacity or soil infiltrability [@Hillel1971, @Horton1940]."},{"index":3,"size":15,"text":"Therefore, soil infiltrability can be measured using soil controlled infiltration tests such as ring infiltrometers."},{"index":4,"size":45,"text":"In general, soil infiltrability into dry soils follows a predictable temporal pattern: it is high in the early stages of infiltration and tends to decline gradually with time until it eventually approaches a nearly constant rate known as (quasi-) steady-state infiltrability or final infiltration capacity."},{"index":5,"size":42,"text":"Downward infiltration into an initially unsaturated soil is typically driven by two main gradients: the gravitational head and the pressure head -or matric suction head when it is negative, i.e. unsaturated soil-. This is reflected in Darcy's law for 1D downward flow:"},{"index":6,"size":1,"text":"where:"},{"index":7,"size":12,"text":"• q is the flux density, in our case the infiltration rate"},{"index":8,"size":171,"text":"is the hydraulic conductivity of the wetted zone for a given pression head h [L t -1 ] • δH δz is the hydraulic head gradient, which in turn consists of: • δz δz or gravitational head gradient [L L -1 ] • δh δz or pressure head gradient [L L -1 ] The decline in infiltrability over time results from the gradual decrese in the pressure head gradient ( δh δz ) and the increase in the depth of the wetting front as infiltration goes on. Eventually, the pressure head gradient becomes negligible and thereafter, the gravitational head ( δz δz ), which equals 1, becomes the main driving force. This explains why the infiltration rate tends to assymptotically approach the hydraulic conductivity as a limiting value. In a uniform profile with prolonged ponding, the water content of the wetted zone should approach saturation. Hence, the infiltration rate in such conditions will tend assymptotically to the saturated hydraulic conductivity (k sat ), which will represent the (quasi-) steady-state infiltrability [@Hillel2004a]:"}]},{"head":"Reynolds & Elrick steady-state single ring model to estimate Kfs","index":15,"paragraphs":[{"index":1,"size":26,"text":"Reynolds & Elrick [-@Reynolds1990] developed a method to analyse steady (or quasi-steady-state) ponded infiltration from within a single ring and determine the field-saturated hydraulic conductivity (Kfs)."},{"index":2,"size":20,"text":"Quasi-steady infiltration through a single ring can be described using the Reynolds and Elrick relationship [@Reynolds1990] expression written as [@Reynolds2002]:"},{"index":3,"size":12,"text":"+ 1 which can also be applied directly for determination of Kfs:"},{"index":4,"size":1,"text":"where:"},{"index":5,"size":8,"text":"• q s is the quasi-steady infiltration rate"},{"index":6,"size":14,"text":"• H is the steady depth (head) of ponded water in the ring [L]"},{"index":7,"size":12,"text":"• d is the depth of ring insertion into the soil [L]"},{"index":8,"size":111,"text":"• C 1 and C 2 are dimensionless quasi-emprirical constants. C 1 = 0.316 π and C 2 = 0.184 π. These constants apply for d>= 3cm and H>= 5cm • α * is the soil macroscopic capillary length, also known as sorptive number of the porous medium [L -1 ] The term quasi-steady state is used here because the approach to \"true\" steady state for ring infiltrometers in some cases can be slow to the point to be near asymptotic. Quasi-steady flow in the near-surface soil under the measuing cylinder is assumed when the discharge becomes effectively constant. This equation identifies three main components of quasi-steady flow from ring infiltrometers:"},{"index":9,"size":80,"text":"• Flow due to hydrostatic pressure of the ponded water in the cylinder (first term of the right side of the equation), this is, the positive pressure of the water column • Flow due to the capillarity (capillary suction) of the unsaturated soil under and adjacent to the cylinder (second term) • Flow due to gravity (third term) Lateral divergence of flow due to hydrostatic pressure and capillarity is accounted for implicitly in the (C 1 d+C 2 a) term."},{"index":10,"size":84,"text":"Darcy's law assumes that Kf s = qs, which is also what is assumed in the traditional constant head ring infiltrometer analysis. But, if we consider hydrostatic and capilarity effects, it is then clear that Kf s < qs [@Reynolds2002]. Thus, q s is often substantially greater than K fs [@Reynolds2002], or in other words, q s overestimates K fs . Such overestimation is larger the smaller the ring diameter, the higher the ponding depth and the lower the capillary length (α * )."},{"index":11,"size":241,"text":"The soil macroscopic capillary length parameter (α * , also known as sorptive number of the porous medium) represents the relative importance of gravity and capillarity forces during ponded infiltration. Large (α * ) indicates a dominance of gravity over capillarity, which occurs primarily in coarse-textured soils an/or highly structured porous media. Small (α * ), on the other hand, indicates dominance of capillarity over gravity, which occurs in fine-textured and/or unstructured porous media. The connection between the magnitude of (α * ) and porous medium texture makes it possible to estimate (α * ) from soil texture and structure categories.   The violin plots demonstrate the median field-saturated hydraulic conductivity (Kfs) for each site. Gatunga had the lowest Kfs and KuboSouth had the highest KfS and high variation across the site. Further analysis will be conducted on these data to assess what is driving the Kfs, for example, is it land use, vegetation structure, land degradation status or soil properities such as sand content or soil organic carbon content. In addition to quantifying the rate of water infiltration into the soil, it is also important to understand how water is flowing through the soil. To do this, Aida Tobella, a postdoctoral fellow at SLU and ICRAF is using the blue dye experiments at the KCEP-CRAL LDSF sites. The below photo demontrates matrix flow, for example at KuboSouth cluster 10 plot 4 compared to perferential flow at KuboSouth cluster 3 plot 2."}]}],"figures":[{"text":"Figure 1 : Figure 1: Location of the household surveys and LDSF sites. 4 "},{"text":"Figure 2 : Figure 2: Average slope each LDSF site. "},{"text":"Figure 3 : Figure 3: Cultivated plots in each LDSF site. "},{"text":"Figure 4 : Figure 4: Vegetation structure of each of the sampled plots. "},{"text":"Figure 5 : Figure 5: Dominant land use of each of the sampled plots. "},{"text":"Figure 6 :Figure 7 : Figure 6: Shrub Densities in Cultivated and Non-cultivated Plots. "},{"text":"Figure 12 : Figure 12: Tree Species Frequency at the Chasimba LDSF Site. "},{"text":"Figure 16 :Figure 17 : Figure 16: Number of plots with severe erosion per cluster per LDSF site. "},{"text":"Figure 18 : Figure 18: Soil Water Conservation Measures Employed at each Site. "},{"text":"Figure 19 : Figure 19: Infiltration Capacity at the Muminji LDSF Site. "},{"text":"Figure 20 : Figure 20: Infiltration Capacity at the Gatunga LDSF site. "},{"text":"Figure 21 : Figure 21: Infiltration Capacity at the Thange LSDF site. "},{"text":"Figure 22 : Figure 22: Average Saturated Conductivity at the each LDSF Site "},{"text":"  "},{"text":"  "},{"text":"Table 1 : Land ownership of each of the sampled plots. Site LandOwnership count SiteLandOwnership count Chasimba communal 3 Chasimbacommunal3 Chasimba private 156 Chasimbaprivate156 Gatunga communal 1 Gatungacommunal1 Gatunga government 6 Gatungagovernment6 Gatunga private 152 Gatungaprivate152 KuboSouth government 1 KuboSouth government1 KuboSouth not_known 3 KuboSouth not_known3 KuboSouth private 150 KuboSouth private150 Muminji communal 2 Muminjicommunal2 Muminji government 1 Muminjigovernment1 Muminji private 155 Muminjiprivate155 Thange communal 3 Thangecommunal3 Thange government 3 Thangegovernment3 Thange private 152 Thangeprivate152  "},{"text":"Table 2 : Average tree and shrub densities in cultivated and non-cultivated plots. Site PlotCultMgd count mean.avtreeden mean.avshrubden SitePlotCultMgd count mean.avtreeden mean.avshrubden Chasimba no 41 76 271 Chasimbano4176271 Chasimba yes 118 62 43 Chasimbayes1186243 Gatunga no 92 146 108 Gatungano92146108 Gatunga yes 67 32 21 Gatungayes673221 KuboSouth no 67 243 163 KuboSouth no67243163 KuboSouth yes 87 177 101 KuboSouth yes87177101 Muminji no 84 249 251 Muminjino84249251 Muminji yes 74 101 90 Muminjiyes7410190 Thange no 61 198 150 Thangeno61198150 Thange yes 97 33 34 Thangeyes973334  "},{"text":" Muminji were: Combretum molle, Lantana spp., and Gymnosporia buxifolia, Faurea saligna and Commiphora spp. The high prevalence of Lantana spp. in Muminji identifies a need for control measures.The most common species at Thange were Combretum fragrans, Combretum spp, Acacia tortillis and Croton dichogamous. The most common species at Gatunga were: Commiphora spp., Acacia senegal, Acacia nilotica, and Mimosa pigra. The most common species in Chasimba were fruit tree species including Cocos nucifera, Magnifera indica, Bracgtystegia spiciformis, Anacardium occidentales, and Azadirachta indica. The most common species in KuboSouth were woodlot and fruit tree species, most notably Casuarina equisetifolia, Annona senegalennisis, Margaritaria discoidea, Psidium guajava, Citrus sinensis and Cocos nucifera.   Tree Species at Gatunga Tree Species at Thange Tree Species at KuboSouth Tree Species at Chasimba Tree Species at Gatunga Tree Species at Thange Tree Species at KuboSouth Tree Species at Chasimba  0.20  0.20 Frequency Frequency Frequency Frequency 0.05 0.10 0.15 0.20 0.05 0.10 0.15 0.05 0.10 0.1 0.2  Frequency Frequency Frequency Frequency0.05 0.10 0.15 0.20 0.05 0.10 0.15 0.05 0.10 0.1 0.2  0.00 0.0  0.00 0.0  0.00 0.00 Tree Species at Muminji Commiphora spp Acacia senegal Acacia nilotica Mimosa pigra Terminalia brownii Acacia brevispica Grewia bicolor Lawsonia inermis Murigicha Dombeya spp Acacia tortilis Muricha Muruti Muriti Acacia mellifera Boscia coriacea Bridelia taitensis Mathigora Combretum fragrans Acacia tortilis Combretum spp Croton dichogamous Commiphora spp Combretum molle Acacia mellifera Acacia nilotica Albizia spp Acacia senegal Senna siamea Melia volkensii Acacia drepanolobium Mimosa pigra Terminalia brownii Acacia hockii Anisotes spp Boscia angustifolia Grewia bicolor Thevetia spp Adansonia digitata Grewia villosa Ekebergia capensis Parinari curatellifolia Steganotaenia araliacea Combretum aculeatum Flueggea virosa Mutungura Grewia spp Flueggea virosa Leucaena spp Sterculia spp Crotalaria agatiflora Adansonia digitata Dichrostachys cinerea Magnifera indica Azadirachta indica Senna abbreviata Balanites glabra Senna spectablis Melia volkensii Annona spp Meyee Bridelia micrantha Mukarakara Dombeya spp Ornocarpus trachycarpum Ochna spp Acacia seyal Parinari curatellifolia Albizia amara Lanea spp Lawsonia inermis Boscia angustifolia Lonchocarpus spp Euphorbia bussei Anisotes ukam Euphorbia tirucalli Azadirachta indica Lonchocarpus eriocalyx Boscia coriacea Muthigiriri Cassia abbreviata Mwambatangao Cordia monoica Rhus vulgaris Euphorbia spp Tamarindus indica Lannea spp Casuarina equisetifolia Margaritaria discoidea Annona senegalensis Psidium guajava Citrus sinensis Anacardium occidentale Cocos nucifera Casuarina angustifolia Lantana camara Antidesma venosum Ozoroa insignis Bridelia micrantha Bixa spp Albizia versicolor Syzygium cordatum Flueggea virosa Keetia venosa Hyphaene compressa Crossopteryx febrifuga Keetia zanzibarica Bauhinia thoningii Suregada zanzibariensis Albizia adianthifolia Erythrophloem suaveolens Grewia plagiophyla Senna spectablis Thevetia thevetioides Blighia unijugata Bridelia carthartica Xylopia parviflora Ficus sur Securidaca longipedunculata Vitex doniana Harungana madagascariensis Stereospermum kunthianum Afzelia quanzensis Apodytes dimidiata Borassus aethiopum Dalbergia melanoxylon Eucalyptus spp Lonchocarpus bussei Mangifera indica Sancepalam brevipes Sorindeia madagascariensia Tectona grandis Tetracera boiviniana Trema orientalis Zanthoxylum chalybeum Deinbollia spp Lannea welwitschii Markhamia zanzibarica Ormocarpum spp Parkia filicoidea Phoenix reclinata Premna chrysoclada Strychnos madascariensis Tabernaemontana elegans Terracera boiviniana Trichilia emetica Cocos nucifera Mangifera indica Brachystegia spiciformis Anacardium occidentale Azadirachta indica Eucalyptus spp Gmelina arborea Citrus sinensis Senna siamea Grewia plagiophylla Annona senegalensis Thevetia peruviana Catunaregam indica Dichostachys cinerea Phyllanthus reticulatus Artocarpus heterophyllus Flueggea virosa Lannea welwitschii Leucaena spp Harrisonia abyssinica Jatropha curcas Manilkara zanzibarica Psidium guajava Apodytes dimidiata Dalbergia vaccinifolia Gyminallia spp Ozoroa insignis Syzygium spp Albizia anthilmetica Bridelia cathartica Cajanua cajan Keetia zanzibarica Senna singuema Ximenia Americana Albizia adiantifolia Bauhinia thoningii Bivinia jalbertii Brackenridgea zanguebarica Citrus tangerina Croton megalocarpus Ehretia spp Hoslundia opposita Mangifera Indica Melia volkensii Milicia excelsa Strychnos madagascariensis Terminalia catappa Wrightia spp Zanthoxylum chalybeum 0.00 0.00Tree Species at Muminji Commiphora spp Acacia senegal Acacia nilotica Mimosa pigra Terminalia brownii Acacia brevispica Grewia bicolor Lawsonia inermis Murigicha Dombeya spp Acacia tortilis Muricha Muruti Muriti Acacia mellifera Boscia coriacea Bridelia taitensis Mathigora Combretum fragrans Acacia tortilis Combretum spp Croton dichogamous Commiphora spp Combretum molle Acacia mellifera Acacia nilotica Albizia spp Acacia senegal Senna siamea Melia volkensii Acacia drepanolobium Mimosa pigra Terminalia brownii Acacia hockii Anisotes spp Boscia angustifolia Grewia bicolor Thevetia spp Adansonia digitata Grewia villosa Ekebergia capensis Parinari curatellifolia Steganotaenia araliacea Combretum aculeatum Flueggea virosa Mutungura Grewia spp Flueggea virosa Leucaena spp Sterculia spp Crotalaria agatiflora Adansonia digitata Dichrostachys cinerea Magnifera indica Azadirachta indica Senna abbreviata Balanites glabra Senna spectablis Melia volkensii Annona spp Meyee Bridelia micrantha Mukarakara Dombeya spp Ornocarpus trachycarpum Ochna spp Acacia seyal Parinari curatellifolia Albizia amara Lanea spp Lawsonia inermis Boscia angustifolia Lonchocarpus spp Euphorbia bussei Anisotes ukam Euphorbia tirucalli Azadirachta indica Lonchocarpus eriocalyx Boscia coriacea Muthigiriri Cassia abbreviata Mwambatangao Cordia monoica Rhus vulgaris Euphorbia spp Tamarindus indica Lannea spp Casuarina equisetifolia Margaritaria discoidea Annona senegalensis Psidium guajava Citrus sinensis Anacardium occidentale Cocos nucifera Casuarina angustifolia Lantana camara Antidesma venosum Ozoroa insignis Bridelia micrantha Bixa spp Albizia versicolor Syzygium cordatum Flueggea virosa Keetia venosa Hyphaene compressa Crossopteryx febrifuga Keetia zanzibarica Bauhinia thoningii Suregada zanzibariensis Albizia adianthifolia Erythrophloem suaveolens Grewia plagiophyla Senna spectablis Thevetia thevetioides Blighia unijugata Bridelia carthartica Xylopia parviflora Ficus sur Securidaca longipedunculata Vitex doniana Harungana madagascariensis Stereospermum kunthianum Afzelia quanzensis Apodytes dimidiata Borassus aethiopum Dalbergia melanoxylon Eucalyptus spp Lonchocarpus bussei Mangifera indica Sancepalam brevipes Sorindeia madagascariensia Tectona grandis Tetracera boiviniana Trema orientalis Zanthoxylum chalybeum Deinbollia spp Lannea welwitschii Markhamia zanzibarica Ormocarpum spp Parkia filicoidea Phoenix reclinata Premna chrysoclada Strychnos madascariensis Tabernaemontana elegans Terracera boiviniana Trichilia emetica Cocos nucifera Mangifera indica Brachystegia spiciformis Anacardium occidentale Azadirachta indica Eucalyptus spp Gmelina arborea Citrus sinensis Senna siamea Grewia plagiophylla Annona senegalensis Thevetia peruviana Catunaregam indica Dichostachys cinerea Phyllanthus reticulatus Artocarpus heterophyllus Flueggea virosa Lannea welwitschii Leucaena spp Harrisonia abyssinica Jatropha curcas Manilkara zanzibarica Psidium guajava Apodytes dimidiata Dalbergia vaccinifolia Gyminallia spp Ozoroa insignis Syzygium spp Albizia anthilmetica Bridelia cathartica Cajanua cajan Keetia zanzibarica Senna singuema Ximenia Americana Albizia adiantifolia Bauhinia thoningii Bivinia jalbertii Brackenridgea zanguebarica Citrus tangerina Croton megalocarpus Ehretia spp Hoslundia opposita Mangifera Indica Melia volkensii Milicia excelsa Strychnos madagascariensis Terminalia catappa Wrightia spp Zanthoxylum chalybeum   Species Name Species Name Species Name Species Name Species Name Species Name Species Name Species Name  0.09  0.09 Frequency 0.03 0.06 Figure 9: Tree Species Frequency at the Gatunga LDSF Site. Figure 10: Tree Species Frequency at the Thange LDSF Site. Figure 11: Tree Species Frequency at the KuboSouth LDSF Site. Frequency0.03 0.06Figure 9: Tree Species Frequency at the Gatunga LDSF Site. Figure 10: Tree Species Frequency at the Thange LDSF Site. Figure 11: Tree Species Frequency at the KuboSouth LDSF Site.  0.00  0.00   Combretum molle Lantana spp. Gymnosporia buxifolia Faurea saligna Commiphora spp. Acacia nilotica Acacia spp. Lannea schweinfurthii Melia volkensii Terminalia brownii Acacia hockii Acacia nubica Combretum zeyheri Combretum collinum Acacia seyal Bridelia spp. Muriti Teclea spp. Tamarindus indica Grevillea spp. Gnidia latifolia Euphorbia tirucalli Muthemeki Vitex keniensis Rhus spp. Acacia mellifera Bauhinia acuminata Zanthoxylum chalybeum Euphorbia kibwezensis Lonchocarpus eriocalyx Meyna tetraphylla Mutavayo Dichrostachys cinerea Ficus spp. Mimosa pigra Polyscias spp. Euphorbia pseudograntii Oncoba spp. treespecies_scientific Croton spp. Polyscias fulva Sterculia spp. Balanites aegyptiaca Kiva Mutororo Parinari curatellifolia Pentanisia ouranogyne Rotheca spp.. Sclerocarya birrea Combretum molle Lantana spp. Gymnosporia buxifolia Faurea saligna Commiphora spp. Acacia nilotica Acacia spp. Lannea schweinfurthii Melia volkensii Terminalia brownii Acacia hockii Acacia nubica Combretum zeyheri Combretum collinum Acacia seyal Bridelia spp. Muriti Teclea spp. Tamarindus indicaGrevillea spp. Gnidia latifolia Euphorbia tirucalli Muthemeki Vitex keniensis Rhus spp. Acacia mellifera Bauhinia acuminata Zanthoxylum chalybeum Euphorbia kibwezensis Lonchocarpus eriocalyx Meyna tetraphylla Mutavayo Dichrostachys cinerea Ficus spp. Mimosa pigra Polyscias spp. Euphorbia pseudograntii Oncoba spp. treespecies_scientific Croton spp. Polyscias fulva Sterculia spp. Balanites aegyptiaca Kiva Mutororo Parinari curatellifolia Pentanisia ouranogyne Rotheca spp.. Sclerocarya birrea   Species Name Species Name   Figure 8: Tree Species Frequency at the Muminji LDSF Site. Figure 8: Tree Species Frequency at the Muminji LDSF Site.  "},{"text":" Acacia brevispica, Murigicha, Dombeya spp, among other species were only found in non-cultivated plots.Combretum aculeatum, Sterculia spp., Azadirachta indica, Melia volkensii and Albizia amara, among others were only found in cultivated plots.There were 47 unique tree species encountered in non-cultivated plots in Thange, and 38 tree species in cultivated plots. Combretum spp, Croton dichogamous, Combretum molle and Acacia drepanolobium, Mimosa pigra, Acacia hokii, Anisotes spp, among others were only found in non-cultivated plots. Ekebergia capensis, Magnifera indica, Senna spectablis, Annona spp, Fluggea virosa, Leucaena spp, among others were only encountered in cultivated plots.There were 97 unique tree species encountered in non-cultivated plots in KuboSouth, and 82 tree species in cultivated plots. Casuarina equisetifolia was the most common in cultivated plots, and only Citrus sinensis, Casuarina angustifolia, Bixa spp, Albizia adianthifolia, and Senna spectablis, among others were found in cultivated plots. Antidesma venosum, Crossopteryx febrifuga, Keetia venosa and zanzibarica and Suregada zanzibariensis, among others were only found in non-cultivated plots.  Muminji Tree Species in Cultivated (yes) and Non−cultivated (no) Thange Tree Species in Cultivated (yes) and Non−cultivated (no) Tree Species at KuboSouth in Cultivated and Non−Cultivated Plots Muminji Tree Species in Cultivated (yes) and Non−cultivated (no) Thange Tree Species in Cultivated (yes) and Non−cultivated (no) Tree Species at KuboSouth in Cultivated and Non−Cultivated Plots                      no no no                   no no no Frequency Frequency Frequency 0.000 0.025 0.050 0.075 0.100 0.125 0.050 0.075 0.100 0.125 0.00 0.05 0.10 0.15 0.20 0.10 0.15 0.20 0.00 0.05 0.25 0.20 0.15 0.10 0.00 0.05 0.10 0.15 0.20 0.25                    yes yes yes                  Frequency Frequency Frequency0.000 0.025 0.050 0.075 0.100 0.125 0.050 0.075 0.100 0.125 0.00 0.05 0.10 0.15 0.20 0.10 0.15 0.20 0.00 0.05 0.25 0.20 0.15 0.10 0.00 0.05 0.10 0.15 0.20 0.25yes yes yes  0.000 0.025 0.00 0.05 Combretum molle Gymnosporia buxifolia Lantana spp Grevillea spp Acacia spp Melia volkensii Commiphora spp Euphorbia tirucalli Faurea saligna Acacia nilotica Lannea schweinfurthii Acacia nubica Acacia hockii Terminalia brownii Combretum collinum Muriti Bridelia spp Teclea spp Acacia seyal Combretum zeyheri Mimosa pigra Oncoba spp Tamarindus indica Gnidia latifolia Muthemeki Vitex keniensis Mukengeta Rhus spp Zanthoxylum chalybeum Bauhinia acuminata Euphorbia kibwezensis Lonchocarpus eriocalyx Acacia mellifera Meyna tetraphylla Dichrostachys cinerea Euphorbia pseudograntii Mutavayo Combretum fragrans Acacia tortilis Combretum spp Croton dichogamous Combretum molle Commiphora spp Acacia mellifera Albizia spp Melia volkensii Senna siamea Acacia nilotica Acacia senegal Ekebergia capensis Magnifera indica Senna spectablis Annona spp Flueggea virosa Leucaena spp Terminalia brownii Acacia drepanolobium Dichrostachys cinerea Mimosa pigra Boscia angustifolia Grewia bicolor Thevetia spp Adansonia digitata Acacia hockii Anisotes spp Casuarina equisetifolia Margaritaria discoidea Annona senegalensis Citrus sinensis Casuarina angustifolia Psidium guajava Anacardium occidentale Cocos nucifera Bixa spp Lantana camara Antidesma venosum Crossopteryx febrifuga Ozoroa insignis Bridelia micrantha Suregada zanzibariensis Syzygium cordatum Albizia versicolor Flueggea virosa Senna spectablis Keetia venosa Hyphaene compressa Grewia plagiophyla Xylopia parviflora Keetia zanzibarica Blighia unijugata Bauhinia thoningii Thevetia thevetioides Albizia adianthifolia Ficus sur Stereospermum kunthianum Erythrophloem suaveolens Borassus aethiopum Mangifera indica Vitex doniana Apodytes dimidiata Harungana madagascariensis Lonchocarpus bussei Securidaca longipedunculata Sorindeia madagascariensia Dalbergia melanoxylon Eucalyptus spp Markhamia zanzibarica Tectona grandis Terracera boiviniana Bridelia carthartica Phoenix reclinata Sancepalam brevipes Strychnos madascariensis Tabernaemontana elegans Tetracera boiviniana Steganotaenia araliacea Croton spp Polyscias fulva Polyscias spp Sterculia spp Terminalia prunioides Balanites aegyptiaca Ficus spp Pavetta lanceolata Pentanisia ouranogyne Rotheca spp Grewia spp Senna abbreviata Ochna spp Crotalaria agatiflora Dombeya spp Lanea spp Lawsonia inermis Acacia stuhlmanii Dalbergia boehmii Jatropa curcas Ormocarpum spp Trichilia emetica Zanthoxylum chalybeum Afzelia quanzensis Barringtonia racemosa Brackenridgea zanguebarica Grewia tristis Heinsia crinita Parkia filicoidea Polysphaeria parvifolia Trema orientalis 0.000 0.025 0.00 0.05Combretum molle Gymnosporia buxifolia Lantana spp Grevillea spp Acacia spp Melia volkensii Commiphora spp Euphorbia tirucalli Faurea saligna Acacia nilotica Lannea schweinfurthii Acacia nubica Acacia hockii Terminalia brownii Combretum collinum Muriti Bridelia spp Teclea spp Acacia seyal Combretum zeyheri Mimosa pigra Oncoba spp Tamarindus indica Gnidia latifolia Muthemeki Vitex keniensis Mukengeta Rhus spp Zanthoxylum chalybeum Bauhinia acuminata Euphorbia kibwezensis Lonchocarpus eriocalyx Acacia mellifera Meyna tetraphylla Dichrostachys cinerea Euphorbia pseudograntii Mutavayo Combretum fragrans Acacia tortilis Combretum spp Croton dichogamous Combretum molle Commiphora spp Acacia mellifera Albizia spp Melia volkensii Senna siamea Acacia nilotica Acacia senegal Ekebergia capensis Magnifera indica Senna spectablis Annona spp Flueggea virosa Leucaena spp Terminalia brownii Acacia drepanolobium Dichrostachys cinerea Mimosa pigra Boscia angustifolia Grewia bicolor Thevetia spp Adansonia digitata Acacia hockii Anisotes spp Casuarina equisetifolia Margaritaria discoidea Annona senegalensis Citrus sinensis Casuarina angustifolia Psidium guajava Anacardium occidentale Cocos nucifera Bixa spp Lantana camara Antidesma venosum Crossopteryx febrifuga Ozoroa insignis Bridelia micrantha Suregada zanzibariensis Syzygium cordatum Albizia versicolor Flueggea virosa Senna spectablis Keetia venosa Hyphaene compressa Grewia plagiophyla Xylopia parviflora Keetia zanzibarica Blighia unijugata Bauhinia thoningii Thevetia thevetioides Albizia adianthifolia Ficus sur Stereospermum kunthianum Erythrophloem suaveolens Borassus aethiopum Mangifera indica Vitex doniana Apodytes dimidiata Harungana madagascariensis Lonchocarpus bussei Securidaca longipedunculata Sorindeia madagascariensia Dalbergia melanoxylon Eucalyptus spp Markhamia zanzibarica Tectona grandis Terracera boiviniana Bridelia carthartica Phoenix reclinata Sancepalam brevipes Strychnos madascariensis Tabernaemontana elegans Tetracera boiviniana Steganotaenia araliacea Croton spp Polyscias fulva Polyscias spp Sterculia spp Terminalia prunioides Balanites aegyptiaca Ficus spp Pavetta lanceolata Pentanisia ouranogyne Rotheca spp Grewia spp Senna abbreviata Ochna spp Crotalaria agatiflora Dombeya spp Lanea spp Lawsonia inermis Acacia stuhlmanii Dalbergia boehmii Jatropa curcas Ormocarpum spp Trichilia emetica Zanthoxylum chalybeum Afzelia quanzensis Barringtonia racemosa Brackenridgea zanguebarica Grewia tristis Heinsia crinita Parkia filicoidea Polysphaeria parvifolia Trema orientalis                   Species Name Species Name Species Name               Species Name Species Name Species Name                      no                   no  0.20     Figure 14: Species Frequency in Cultivated and Non-cultivated Plots Figure 15: Species Frequency in Cultivated and Non-cultivated Plots      0.20Figure 14: Species Frequency in Cultivated and Non-cultivated Plots Figure 15: Species Frequency in Cultivated and Non-cultivated Plots  0.15                                        0.15  0.10                                        0.10  0.05                                        0.05  0.00                                        0.00                      yes                   yes  0.20                                        0.20  0.15                                        0.15  0.10                                        0.10  0.05                                        0.05  0.00                                        0.00   Commiphora spp Terminalia brownii Acacia senegal Acacia nilotica Mimosa pigra Lawsonia inermis Acacia brevispica Combretum aculeatum Murigicha Sterculia spp Grewia bicolor Dombeya spp Muricha Muruti Azadirachta indica Melia volkensii Muriti Boscia coriacea Acacia tortilis Acacia mellifera Albizia amara Mathigora Bridelia taitensis Parinari curatellifolia Grewia villosa Flueggea virosa Mutungura Adansonia digitata Balanites glabra Meyee Mukarakara Ornocarpus trachycarpum Acacia seyal Boscia angustifolia Euphorbia bussei Euphorbia tirucalli Lonchocarpus eriocalyx Muthigiriri Mwambatangao Rhus vulgaris Tamarindus indica Commiphora sppTerminalia browniiAcacia senegalAcacia niloticaMimosa pigraLawsonia inermisAcacia brevispicaCombretum aculeatumMurigichaSterculia sppGrewia bicolorDombeya sppMurichaMurutiAzadirachta indicaMelia volkensiiMuritiBoscia coriaceaAcacia tortilisAcacia melliferaAlbizia amaraMathigoraBridelia taitensisParinari curatellifoliaGrewia villosaFlueggea virosaMutunguraAdansonia digitataBalanites glabraMeyeeMukarakaraOrnocarpus trachycarpumAcacia seyalBoscia angustifoliaEuphorbia busseiEuphorbia tirucalliLonchocarpus eriocalyxMuthigiririMwambatangaoRhus vulgarisTamarindus indica                   Species Name                Species Name  "}],"sieverID":"4bbfe939-a3ce-4cf9-affe-035000343ee7","abstract":""}