Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

Vettes Neckemiah Kalema; Edward T.F. Witkowski

doi:10.1080/21513732.2012.681070

Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

Kalema, Vettes Neckemiah; Witkowski, Edward T.F. 2012-09-01 00:00:00 International Journal of Biodiversity Science, Ecosystem Services & Management Vol. 8, No. 3, September 2012, 231–247 Land-use impacts on woody plant density and diversity in an African savanna charcoal production region Vettes Neckemiah Kalema* and Edward T.F. Witkowski Restoration and Conservation Biology Research Group, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, Private Bag 3, WITS 2050, South Africa The density and diversity of woody plant species were studied within grazing, cultivation and charcoal production land-use areas in a multiple-use savanna woodland, central Uganda, using 75 plots with an area of 0.1 ha (Whittaker plots). Plant density was signiﬁcantly higher under charcoal production (7131 ± 755 plants/ha) and cultivation (6612 ± 665 plants/ha) compared with the grazing lands (4152 ± 525 plants/ha). At the plot level, species richness and Fisher’s alpha diversity (α) were relatively low, ranging 2–31 species and 0.34–6.34, respectively, but both were signiﬁcantly higher under charcoal production and cultivation compared with grazing. Similarly, cumulative species richness and Fisher’s alpha diversity were higher under charcoal production and cultivation compared with grazing. Community species composition differed signiﬁ- cantly (Global R = 0.14, p = 0.001; ANOSIM, ANalysis Of SIMilarity) among land uses. However, the distance of ANOSIM sampling plots away from households, the assumed source of human disturbance to woodlands, accounts for a very small fraction (<14.2%) of the variation in woody species diversity within this multiple-use savanna. Beta diversity was highest under grazing, followed by cultivation and charcoal production, suggesting a more heterogeneous spatial distribution of species under grazing. Within each land use, mean similarities were low, ranging 25–31%. Mean pairwise dissimilarities between land uses were relatively high, ranging 73–81%. This suggests that variations in species composition and diversity are to a great extent inﬂuenced by land-use and anthropogenic disturbances. The relatively low woody species diversity and richness in this savanna indicates woodland degradation, fragmentation and local species loss resulting from unsustainable harvesting for charcoal, and short interval shifting cultivation. Keywords: ANOSIM; anthropogenic disturbance; cultivation; grazing; land degradation; species richness; sustainable land management Introduction et al. 2004; Mwavu and Witkowski 2008a). They are rapidly undergoing severe large-scale changes, through Savanna woodlands make up most of the tropical and sub- indiscriminate burning or conversion to other land uses and tropical woodland cover in sub-Saharan Africa and provide cover types (Rennolls and Laumonier 2000; Millennium a wide range of beneﬁts and products to local and national Ecosystem Assessment 2005a, 2005b). The development production. They provide the major source of energy for of more sustainable land-use systems necessitates an the majority of households (Luoga et al. 2000a; Kituyi understanding of the nature, dynamics and production 2004; Millennium Ecosystem Assessment 2005a) and are potential of these savanna woodland systems. An under- the focus of numerous livelihood activities in marginal- standing of the patterns of woody plant species diversity ized communities (Luoga et al. 2000b; Dovie et al. 2002, within the prevailing land uses and responses to changes 2005; Venter and Witkowski 2011). These savanna wood- in the environment is essential for long-term sustainability lands have numerous wild plant species that are important and to aid decisions on conservation priorities (Folke et al. in the subsistence sector, both for meeting a wide range 2004). of household needs and through increasing commercial- Relatively little is known about the woody plant diver- ization, generating incomes (Braedt and Stranda-Gunda sity in African savannas outside southern Africa and the 2000; Dovie et al. 2005). The southern and eastern African miombo ecoregion, and this is particularly the case in miombo woodlands are economically important for sup- Uganda. Most diversity studies in Uganda have focused plying timber, poles, ﬁrewood, charcoal, medicines, food, on tropical rainforests (e.g. Eilu et al. 2004; Mwavu ﬁbre and carvings for both rural and urban populations and Witkowski 2008a). Studies of savanna woodland in (Luoga et al. 2000a, 2000b). Uganda have mainly focused on biomass and bioenergy; There is, however, a widespread concern that the wood- management of ranching schemes (National Environment land ecosystems with unique and valuable biodiversity Management Authority 2002); and the growth, use and resources are being lost (Rennolls and Laumonier 2000; management of woodland resources (e.g. Namaalwa et al. Coetzer et al. 2010) as a result of both natural and 2005). Ugandan woodlands also play a major (often anthropogenic disturbances and mismanagement (Luoga *Corresponding author. Email: ykagemwa@yahoo.co.uk ISSN 2151-3732 print/ISSN 2151-3740 online © 2012 Taylor & Francis http://dx.doi.org/10.1080/21513732.2012.681070 http://www.tandfonline.com 232 V.N. Kalema and E.T.F. Witkowski unaccounted) role in the economy by providing fuel (char- The vegetation of the area is classiﬁed as Albizia– coal and ﬁrewood), grazing resources for livestock, land for Combretum woodland (Langdale-Brown et al. 1964). This cultivation and numerous other services. The charcoal is is a natural savanna woodland or woodland of mixed decid- transported to major commercial centres such as Kampala. uous trees, 3–12 m in height and grasses, 0.3–1.3 m in Woodland conversion to farmland, selective harvesting height at maturity. The cover of the grass layer varies of woody plants for ﬁrewood and charcoal production, with season, is often patchy and subordinate to the seasonal ﬁres, livestock grazing and hunting of native her- tree layer. Most of the grazing lands occur on hydro- bivores are major mechanisms of woodland degradation, morphic grasslands that are only suitable for grazing. habitat change and biodiversity loss in many parts of Africa There are thicket patches dominated by Acacia hockii, (Luoga et al. 2005; Banda et al. 2006). Acacia gerradii, Acacia kirkii ssp. mildbraedii, Acacia This study aims to assess woody plant density and senegal and Euphorbia candelabrum established in sec- species diversity (richness, alpha diversity and beta diver- ondary wooded grasslands as a consequence of anthro- sity) in response to the three main land uses (grazing, cul- pogenic disturbances (White 1983). The vegetation in tivation and charcoal production) in the extensive savanna Nakasongola District is mainly open woodland in transi- woodlands of Nakasongola District, central Uganda. The tion to thicket/shrubland, as woodland cover has decreased, increasing human pressure on these tropical ecosystems while areas under cultivation/settlements have corre- makes information on their patterns of plant diversity (i.e. spondingly greatly increased since 1984 (Kalema 2010). species richness, alpha diversity and beta diversity) and In Nakasongola District, 70–80% of households not only distributions more critical today than ever before in order engage in charcoal production but also livestock hus- to protect and conserve the remaining species effectively bandry, and subsistence agriculture, mainly shifting cul- and efﬁciently (e.g. Cadotte et al. 2002; Natta et al. 2002; tivation, provides 85% of the food supply, and more than Zapfack et al. 2002). Alpha diversity and beta diversity 50% of monetary income (Nakasongola Local Government together provide a generally good overall assessment of 2002; Figure 1). plant diversity or biotic heterogeneity of an area. Beta diversity is important in at least indicating the degree to Sampling design which ecosystems have been partitioned by species. There is a sequence of land-use change over time, with most areas used for slash and burn agriculture; char- Materials and methods coal production areas are subsequently used for cultiva- Study area tion (they are burnt and hence have temporarily raised The savanna woodlands of Nakasongola District occur soil nutrient levels suitable for crops), and may then ◦ ◦ south of Lake Kyoga, central Uganda (0 40 –1 41 N, be used for grazing for a short period, allowing the ◦ ◦ 2 31 57 –32 48 E). The district covers 3424 km , 90% of woody plants to recover by basal resprouting from the cut which is woodland and grassy savanna, with 322 km stumps (Luoga et al. 2004; Mwavu and Witkowski 2008a). (∼10%) of open water and wetlands. It comprises The current land use was identiﬁed for the purposes of eight subcounties (administrative subdivisions), namely this study. Representative villages (and surroundings) in Kakooge, Kalongo, Wabinyonyi, Kalungi, Nabiswera, each of the eight subcounties were selected (with the Nakitoma, Lwampanga and Lwabiyata. Subcounties con- help of local leaders and ofﬁcials from the Department sist of villages, ranging from 15–77 to 1741–4877 house- of Natural Resources and Environment) during March holds. By 2001, the district had a total human population 2006 for woody vegetation sampling. In each subcounty of 128,126 (41 people/km ), with 50.2% males and 49.8% at least three transects were established. Transects were females. About 95% of the population are in rural areas laid radiating away from the villages/households where (Uganda Bureau of Statistics 2002). subsistence activities are paramount, often resulting in Annual rainfall ranges from 500 to 1000 mm and gradients of increasing resource availability or decreas- is concentrated within two wet seasons (March–May ing human disturbance with distance from village (Fisher and August–November). Reliability of rainfall received is et al. 2011). Each transect represented one of the three higher in the south and declines gradually towards the major land uses, with the exception of Nabiswera, which north. The mean monthly maximum temperature ranges had four transects. The additional transect was an attempt ◦ ◦ from 25 Cto35 C, and the mean monthly minimum tem- to include the most degraded grazing area. Transect loca- ◦ ◦ perature ranges from 18 Cto21 C. The topography of tions were selected considering the homogeneous nature of the area undulates from 1036 to 1160 m above sea level. the area for a particular land use and of sufﬁciently large The major geological formations are characterized by the extent to accommodate at least three 20 × 50 m (0.1 ha) presence of young intrusive rocks, mostly acidic and less plots, with a minimum separation distance of 200 m. The commonly basic. The youngest formations date from the 20 ×50 m (Whittaker) plot size has been widely used Pleistocene era and are represented by sands, quartz and for assessment of shrublands, grasslands, tropical savan- clays of alluvial or lacustrine (i.e. formed at the bottom or nas, woodlands and forests (Cowling and Witkowski 1994; along the shores of lakes as geological strata) origin (Parker Luoga et al. 2002; Beater et al. 2008; Dovie et al. 2008; et al. 1967). Witkowski and Garner 2008). Hence, 24 plots with an area International Journal of Biodiversity Science, Ecosystem Services & Management 233 Uganda Africa Uganda Nakasongola Lwabiyata Nakitoma Lwampanga Lkyoga Nabiswera Kalungi Population density Wabinyonyi 18–21/km 22–29/km Kalongo 30–38/km 39–77/km Kakooge 78–130/km Waterbodies km Figure 1. Map of Nakasongola District showing the eight constituent subcounties and their human population density. Inset is a map of Africa showing Uganda and a map of Uganda showing Nakasongola District shaded (TC: Town centre; Lkyoga: Lake Kyoga). of 0.1 ha were sampled for each of the cultivation and Data analysis charcoal production land-use types, and 27 plots were sam- Alpha diversity pled for grazing. In total, 25 transects with 75 plots were Fisher’s alpha (α) and Shannon–Wiener (H ) diversity established (Figure 2). indices were employed to quantify alpha diversity at the Within each 0.1 ha plot, woody plant species, number 0.1 ha scale, while rarefaction was used to estimate the of individuals and height and stem diameter at refer- number of species expected (E(Sn)) to be present in a ence height (1.3 m, except for seedlings and shrubs) of random sample (i.e. plot) of individuals taken from any each individual were recorded. Based on stem diameter given collection, and provides conﬁdence limits of species and height, woody plants were categorized as trees or richness (Magurran 2004). Plotting the rarefaction curves shrubs (USDA Forest Service 1989). Seedlings had a sin- facilitates improved interpretation of species richness from gle stem with stem diameter of ≤0.5 cm, were ≤1min sample plots of varying size and number and from differ- height and had not previously resprouted, while saplings ent communities (Gotelli and Colwell 2001; Williams et al. or juvenile trees were >0.5–5 cm dbh and >1min 2005). The sample plots were randomized 100 times to height. However, the seedling data were not included in compute the mean estimator and expected species richness this assessment. Species identiﬁcation in the ﬁeld was for each sample plot accumulation level using EstimateS supported by identiﬁcation guides mainly based on the (Colwell 2006). Flora of Tropical East Africa (Polhill 1952 and subse- Fisher’s alpha diversity index is not inﬂuenced by the quent volumes), Katende et al. (1995) as well as the size of the sampling area (i.e. plot) and is less affected assistance of a botanist familiar with the ﬂora of the area. by the abundance of the rarest or commonest species Voucher species were collected and subsequently identiﬁed compared with other diversity measures (Magurran 2004). in the Botany Department Herbarium, Makerere University Fisher’s alpha was, however, not calculated separately for (MHU), Kampala, Uganda. 234 V.N. Kalema and E.T.F. Witkowski (a) (b) (c) Figure 2. Photographs of the major land-use practices: (a) wood stacked in preparation for charcoal production, (b) cattle grazing in a wetland and (c) cultivation fallow in a multiple land-use equatorial African savanna, central Uganda. both the tree and shrub data due to the high number of index of similarity (C ). The Morisita–Horn index MH singletons in the individual data sets, which resulted in assesses similarity in species composition between plots number of individuals (N) divided by number of species (Colwell et al. 2004; Magurran 2004), and is a quantitative (S) being ≤1.44. Fisher’s alpha cannot be calculated when similarity index that is not strongly inﬂuenced by species N /S ≤ 1.44 (Magurran 2004). Diversity indices were richness and sample size. For each land-use type, C was MH calculated using Species Diversity and Richness version calculated by averaging all the plot pairwise values for each IV (Pisces Conservation Ltd., Lymington, UK) (Seaby land-use type. Morisita–Horn index varies from 1 (com- and Henderson 2007) and EstimateS version 8.0 (Colwell plete similarity) to 0 (complete dissimilarity) in species 2006). The sample plots were randomized 100 times in composition. EstimateS to compute the cumulative H and Fisher’s α Plots were also arranged according to land-use type and to construct the curves. Differences in tree and shrub and variations in community species composition were species richness and diversity between the three land-use tested by employing ANalysis Of SIMilarity (ANOSIM), types were compared using one-way Analysis of Variance a permutation test in CAP 4 (Pisces Conservation Ltd.) and Tukey’s Honestly Signiﬁcant Difference (HSD) for (Seaby et al. 2007). ANOSIM computes a test statistic unequal sample sizes (i.e. different number of plots per (R ) reﬂecting the observed differences among repli- ANOSIM land-use type). We also tested for the relationship between cates (i.e. plots) between sites (in this case land-use types), woody plant diversity (i.e. species richness and alpha diver- contrasted with differences among replicates within sites. sity) and the ‘distance of the sampling plot along the A zero (0) occurs if the high and low similarities are transect radiating away from the households’, the assumed perfectly mixed and bears no relationship to the group source of human disturbance, using regression analysis. (i.e. plots within a land-use type). A value of minus one The regression analyses were performed separately for (i) (−1) indicates that the most similar sample plots are all total woody (i.e. trees and shrubs combined), (ii) trees outside of the group. A value of positive one (+1) indi- and (iii) shrubs at both the whole savanna and land-use cates that the most similar sample plots are within the same type scales. group (Seaby et al. 2007). The percentage similarity among land uses was also analysed using SIMilarity PERcentages (SIMPER) in CAP 4. SIMPER breaks down the con- Beta diversity tribution of each species to the observed similarity (or Beta diversity at the plot level was assessed using dissimilarity) between sample plots. It allows the user to Whittaker’s beta diversity index (β ), Wilson and W identify the species that are most important in creating Schmida’s index (β ) and the modiﬁed Morisita–Horn T the observed pattern of similarity. The method uses the International Journal of Biodiversity Science, Ecosystem Services & Management 235 Table 1. Brief description of the indices and measures applied to the data. Index/measure Description Diversity indices Fisher’s alpha (α) (Magurran 2004) This is a parametric index of diversity that assumes that the abundance of species follows the log series distribution Shannon–Wiener (H ) (Seaby and Henderson 2007) Shannon index gives a measure of both species numbers and the evenness of their abundance; the resulting ﬁgure does not give an absolute description of a site’s biodiversity. It is particularly useful when comparing similar ecosystems or habitats, as it can highlight one example being richer or more even than another Species richness Rarefaction (Gotelli and Colwell 2001; Colwell et al. 2004) Rarefaction is used to produce a smoothed curve that is the statistical expectation of corresponding accumulation curve. Rarefying a sample estimates its expected species richness at different values of n samples or N individuals from the poo- led total species richness after randomizing the sample order Whittaker’s β diversity index (Colwell et al. 2004) Used to test the degree to which heterogeneity in species composition varies among functional groups or among different regions for which gradients are difﬁcult to compare Wilson and Schmida’s (β ) (Colwell et al. 2004) Reﬂects species turnover by calculating the gain and loss of species along a gradient standardized by the average number of species in each plot Morisita–Horn index of similarity (C ) (Magurran 2004) Assesses similarity in species composition between plots. Not MH inﬂuenced by sample size or species richness ANalysis Of SIMilarities (ANOSIM) (Seaby et al. 2007) It is a multivariate, non-parametric measure that provides a way to test statistically whether there is a signiﬁcant difference between two or more groups of sampling units SIMilarity PERcentages (SIMPER) (Seaby et al. 2007) Breaks down the contribution of each species to the observed similarity (or dissimilarity) between samples. It allows the user to identify the species that are most important in creating the observed pattern of similarity Bray–Curtis method (Seaby et al. 2007) The Bray–Curtis method operates at the species level, and therefore the mean similarity between groups 1 and 2 can be obtained for each species. It is widely employed in multivariate analysis of assemblage data. It reﬂects differences between two samples due both to differing community composition and/or differing total abundance Bray–Curtis measure of similarity, comparing in turn, each excelsa and Pouteria sp. are near threatened (International sample in Group 1 with each sample in Group 2. The Bray– Union for Conservation of Nature classiﬁcation; Pomeroy Curtis method operates at the species level and therefore et al. 2002). Calliandra sp., Artocarpus heterophyllus, the mean similarity between groups 1 and 2 can be obtained Senna siamea and Lantana camara are introduced and the for each species (Table 1). latter is also invasive (Appendix 1). The species accumulation curves for the combined 75 plots with an area of 0.1 ha, and for each land-use type Results asymptotes are reached, show that sampling was sufﬁcient Woody plant community composition (Figure 3). In addition, the species accumulation curve A total of 99 woody plant species, from 67 genera within was below the rarefaction curve, suggesting heterogeneity 31 families, were recorded from the 75 plots with an area among samples. of 0.1 ha. The most species-rich families were Mimosaceae Community species composition was signiﬁcantly dif- ferent among land uses (ANOSIM, Global R = (13 species), Rubiaceae (9), Moraceae (7), Euphorbiaceae ANOSIM 0.14, p = 0.001). Pairwise comparisons showed signiﬁcant (7), Anacardiaceae (6), Combretaceae (5) and Verbenaceae (5), with 15 others comprising 2–4 species and 9 with one differences in species composition between cultivation and species each (Appendix 1). The most species-rich genera grazing, as well as grazing and charcoal production, but were Acacia (8 species) Combretum (4), Ficus (4), Albizia not between cultivation and charcoal production (Table 2). (3), Pavetta (3) and Tricalysia (3), with the rest each hav- Woody plant density across all land-use types was 5893 ing 1–2 species (Appendix 1). None of the 99 species has ± 399 plants/ha. Density differed signiﬁcantly (F = 2,72 a restricted range as they all occur in more than one of the 6.3, p = 0.003) among land uses, with charcoal pro- four ﬂoral regions of Uganda (Flora of Tropical East Africa duction and cultivation signiﬁcantly higher than grazing (Polhill 1952 and more recent volumes). However, Milicia (Table 3). 236 V.N. Kalema and E.T.F. Witkowski Grazing (n = 27) Total (n = 75) Expected Observed Expected Observed 0 0 1 5 9 131721 252933 37414549 53576165 6973 1 3 5 7 9 1113 15 1719 21 23 2527 Charcoal (n = 24) Cultivation (n = 24) 60 60 Expected Expected Observed Observed 40 40 1 2 3 4 5 6 7 8 9 1011 1213 1415 1617 1819 202122 2324 1 2 3 4 5 6 7 8 9 1011 1213 1415 1617 1819 202122 2324 Sample plots (n) Sample plots (n) Figure 3. Rarefaction (expected) and species accumulation (observed) curves for the total woody species recorded in the 0.1 ha plots throughout the area (total), and for the grazing, cultivation and charcoal production land-use types, within this multiple-use equatorial African savanna, central Uganda. Table 2. ANOSIM in community species composition among higher for charcoal production and cultivation than grazing the different land-use types in a multiple-use equatorial African (Figure 4). savanna, central Uganda. Across all the plots alpha diversity ranged from 0.34 to 6.34 and from 0.14 to 2.64 for Fisher’s alpha (α) and Land-use type Charcoal production Grazing Shannon–Wiener index (H ), respectively. However, plot Cultivation 0.04 (0.063) 0.21 (0.001) values for both indices did not show a clear and uni- Grazing 0.15 (0.001) form increase with increasing distance along the transect Note: The ANOSIM sample statistic (R ) is reported with signiﬁ- (i.e. ﬁrst to last plot) radiating away from the households, ANOSIM cance level (p-value) in parentheses. the assumed source of human disturbance. Both H and alpha diversity were signiﬁcantly different (H : F = 2,72 7.31, p < 0.001: α: F = 7.29, p < 0.001) among 2,72 Woody plant species richness and alpha diversity land uses (Table 3). H was highest under cultivation and At the plot level, species richness differed (F = charcoal production and signiﬁcantly lower under graz- 2,72 10.7, p < 0.0001) among land uses, with charcoal pro- ing. Cumulative H followed the same trend, being similar duction and cultivation being signiﬁcantly higher than between cultivation (2.95) and charcoal production (2.93), grazing (Table 3). Cumulative species richness was also with grazing considerably lower (2.49, Figure 5a). Fisher’s Table 3. Plot-level (0.1 ha) woody plant density, and species diversity and richness (means ± SE) in a multiple-use equatorial African savanna, central Uganda. Diversity indices Land-use Number of Density types plots (plants/ha) SH Fisher’sαβ β C w T MH a a a a a Grazing 27 4152 ± 525 14 ± 1.1 1.2 ± 0.1 3.0 ± 0.3 3.1 3.1 0.37 ± 0.02 b b b b a Cultivation 24 6612 ± 665 20 ± 1.2 2.1 ± 0.1 4.1 ± 0.2 2.8 3.0 0.33 ± 0.02 b b b b a Charcoal 24 7131 ± 755 21 ± 1.1 2.0 ± 0.1 4.1 ± 0.2 2.7 2.8 0.37 ± 0.02 production Notes: Values in the same column accompanied by the same superscript do not differ signiﬁcantly (Tukey, p < 0.05). H , Shannon–Wiener index; S, species richness; β , Whittaker’s beta diversity; β , Wilson and Schmida; C , Morisita–Horn index of similarity. W T MH Number of species Number of species Number of species Number of species International Journal of Biodiversity Science, Ecosystem Services & Management 237 (a) (a) 120 3.5 Cultivation, 2.95 Overall land uses, 99 Overall land uses, 3.0 Charcoal, 2.93 2.5 Grazing, 2.49 Cultivation, 76 Charcoal, 77 1.5 Grazing, 57 0.5 20 0 0 1020304050607080 Number of individuals Number of samples (b) (b) Overall land uses, 12.06 Cultivation, 10.36 Charcoal, 10.43 Overall land uses, 99 Grazing, 7.85 Cultivation, 76 Charcoal, 77 Grazing, 57 Number of individuals Figure 5. The cumulative diversity curves plotted against num- ber of individuals for (a) Shannon–Wiener diversity index and Number of individuals (b) Fisher’s alpha diversity for the total woody plants for all land uses combined (overall), and for the grazing, cultivation Figure 4. The cumulative species richness curves for the total and charcoal production land-use types, within this multiple-use woody species based on (a) sample plots and (b) number of indi- equatorial African savanna, central Uganda. viduals for all land uses combined (overall), and for the grazing, cultivation and charcoal production land-use types, within this multiple-use equatorial African savanna, central Uganda. grazing (Table 4). The most abundant tree species with high average number of plants per plot were alpha diversity was also higher for cultivation and charcoal Combretum collinum (147 plants/plot), Capparis fascic- production, and signiﬁcantly lower for grazing (Table 3). ularis (120), Combretum molle (97), Combretum capit- The cumulative alpha diversity was again higher under uliﬂorum (82) and Combretum ghasalense (80), whereas charcoal production (10.43) and cultivation (10.36), and the most frequent were C. collinum (in 63 of 75 plots), lower under grazing (7.85, Figure 5b). The overall trend C. molle (60), C. ghasalense (59) and A. hockii (49). is that species diversity was higher in the cultivation and Acacia seyal, Commiphora africana and Commiphora charcoal production and lower in the grazing land use. The dawei were only encountered under grazing, Albizia cori- regression results showed insigniﬁcant weak correlations aria, Albizia malacophylla, Zanthoxylum chalybeum and (with r spanning 0.004–0.095; p > 0.1) between woody Erythrina abyssinica in cultivation, while Pavetta cras- species diversity (i.e. richness and alpha diversity) and the sipes, Dombeya dawei and Zanthoxylum rubescens were ‘distance of the sampling plot along the transect radiating only recorded within charcoal production areas. away from the households’ at both the whole savanna and Tree species H diversity at the plot level ranged from land-use type scales. This suggests that the distance along 0.0 to 2.6, and differed signiﬁcantly among land uses (F 2,72 the transect away from the households, the assumed source = 15.9, p < 0.0001), being higher in both cultivation and of woodland human disturbance, accounts for a very small charcoal production compared with grazing (Table 4). The fraction of the variation in woody species diversity within regression results showed insigniﬁcant weak correlations this multiple-use savanna. (with r spanning 0.001–0.079; p > 0.18) between tree species diversity (i.e. richness and alpha diversity) and the ‘distance of the sampling plot along the transect radiat- Tree species richness and alpha diversity ing away from the source of human disturbance’ at both Tree species richness differed among the land uses the whole savanna and land-use type scales. This suggests (F = 16.6, p < 0.0001), being higher under that the distance of sampling plots away from the house- 2,72 cultivation and charcoal production and lower under holds, the source of woodland disturbance, accounts for a 10,000 15,000 20,000 25,000 10,000 30,000 15,000 35,000 20,000 40,000 25,000 45,000 30,000 50,000 35,000 40,000 45,000 10,000 50,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 Number of species (S) Number of species (S) Fisher's alpha Shannon diversity index (H′) 238 V.N. Kalema and E.T.F. Witkowski Table 4. Plot-level (0.1 ha) tree and shrub species diversity and richness (means ± SE) among the different land-use types in a multiple-use equatorial African savanna, central Uganda. Species richness and diversity Tree Shrub Land-use type Number of plots SH SH a a a a Grazing 27 3.6 ± 0.3 1.0 ± 0.1 1.3 ± 0.3 0.3 ± 0.1 b b b b Cultivation 24 7.8 ± 0.7 1.7 ± 0.1 3.4 ± 0.5 0.9 ± 0.1 b b b b Charcoal production 24 7.5 ± 0.7 1.7 ± 0.1 2.7 ± 0.4 0.7 ± 0.1 Notes: Values in the same column accompanied by the same superscript do not differ signiﬁcantly (Tukey, p < 0.05). S, species richness; H , Shannon–Wiener diversity index. very small fraction (<7.9%) of the variation in tree species very high between land-use dissimilarities. The within diversity within this multiple-use savanna. land-use type similarities were low (ranging 25.3–30.5%), being highest for charcoal production (mean = 30.5%), followed by grazing (25.4%), and then cultivation (25.3%). Shrub species richness and alpha diversity Furthermore, SIMPER analysis showed relatively high Shrub species richness differed among land uses (F = 2,72 pairwise dissimilarities between land uses, ranging 8.28, p = 0.0006), being signiﬁcantly higher under cul- 73.2–81.2%. The highest mean dissimilarity was for tivation and charcoal production compared with grazing cultivation versus grazing (81.2%), followed by charcoal (Table 3). Overall, the most abundantly shared shrub versus grazing (76.7%) and lowest for charcoal versus species among land uses were Harrisonia abyssinica cultivation (73.2%). These results are corroborated by (26 plants/plot), Rhus natalensis (21), L. camara (20) and lower similarity percentages within land uses. Annona senegalensis (18). The most frequent shrubs were Indeed, SIMPER showed that the number of species R. natalensis (in 68 of 75 plots), H. abyssinica (65), making up 90% of the observed similarity per land use Grewia mollis (53), Gardenia ternifolia (46) and A. sene- was 12 for both cultivation and charcoal production and galensis (43). Clerodendrum cordifolia, Flueggea virosa, 9 for grazing (Appendix 3, Figure 6). The top two species Microglossa pyrifolia and Phyllanthus ovalifolius were contributing most to the percentage similarity in commu- recorded only in the grazing areas. Shrub H diversity nity species composition within cultivation and charcoal ranged from 0.0 to 2.0, and differed among land uses (F 2,72 production were C. collinum and C. molle. However, for = 7.08, p = 0.002), being signiﬁcantly higher for cultiva- grazing, the second species was Piliostigma thonningii tion and charcoal production relative to grazing (Table 4). (Appendix 3). SIMPER analysis indicated that 24 species The regression results showed insigniﬁcant weak correla- between charcoal production and cultivation, 22 species tions (with r spanning 0.002–0.141; p > 0.18) between between charcoal and grazing and 23 species between cul- shrub species diversity (i.e. richness and alpha diversity) tivation and grazing contributed most to the dissimilarity and the ‘distance of the plot along the transect radiating between land uses, reﬂecting the overall differences in away from the households’, the assumed source of human community composition (Appendix 3). disturbance at both the whole savanna and land-use type scales. This suggests that the distance of sampling plots Grazing away from the human sources of woodland disturbance Cultivation accounts for a very small fraction (<14.1%) of the vari- Charcoal ation in shrub species diversity within this multiple-use 80 savanna. Beta diversity Plot-level pairwise Morisita–Horn (C ) ranged MH 0–0.979 under grazing, 0.005–0.972 for charcoal production and 0.001–0.961 under cultivation. C MH tended to differ (F = 2.43, p = 0.09) between land 2,900 uses, with charcoal production and grazing being higher than cultivation. β and β were highest under grazing, 123456789 10 11 12 W T Number of species followed by cultivation and lowest for charcoal production (Table 3). Hence, the β , β and C values show an W T MH Figure 6. Cumulative percentage contribution to overall overall higher beta diversity for the grazing land use similarity from ANOSIM within the three land-use types in compared with others. These results are corroborated by relation to the number of species contributing to at least 90% the very low within land-use SIMPER similarities, and similarity in savanna woodland of Nakasongola, central Uganda. Cumulative similarity (%) International Journal of Biodiversity Science, Ecosystem Services & Management 239 Discussion consequences for plant community development (Hanley 1998). Community composition and structure Anthropogenic factors (charcoal production and shift- Generally, C. collinum, C. fascicularis, C. molle, C. capit- ing cultivation) have similarly been reported to be causative uliﬂorum, C. ghasalense, G. mollis and A. hockii were the agents of degradation in the central Ethiopian highlands most abundant and frequent species across all land uses. (Yirdaw and Luukkanen 2003). However, in this study, the This agrees with Nangendo et al. (2006) that C. molle, differences among land uses may be the result of the extent G. mollis, A. senegalensis and Grewia bicolor are com- (intensity and frequency) and duration of anthropogenic monly found in burned areas and in open savanna wood- disturbances and particular land-use practices taking place lands in Uganda. Fires are common in these multiple-use in a given area. Changes in land-use practice may result savannas, and ﬁre is used as a management tool in both in continuously or more abruptly deteriorating environ- subsistence crop cultivation and livestock grazing. About mental conditions for some plant species, causing their 20–50% of the grazing areas in the studied multiple-use decline in abundance and distribution. The chopping down savannas are burned towards the end of the two dry sea- of trees for charcoal production on a relatively short rota- sons before the onset of rainfall (in February and again tion has clearly resulted in local species loss. Some of the in July) to allow fresh pastures and kill ticks. Similarly, highly utilized species for charcoal production, ﬁrewood Morris (1995) observed that people in the miombo wood- and poles for fences and houses are A. hockii, A. polyacan- lands of Malawi burn the bush for preparing their gardens tha, A. seyal, Acacia sieberiana, A. coriaria, Albizia zygia, for planting, hunting and calling the rains. Since ﬁres occur C. capituliﬂorum, C. collinum, C. ghasalense, C. molle, at more than one time of the year, some speciﬁc patches of G. mollis, Hymenocardia acida, Maytenus senegalensis, land may be burnt more than once in a year. These numer- P. thonningii, Terminalia glaucescens and Vepris nobilis ous ﬁres result in relatively low ﬁre intensities because fuel (Namaalwa et al. 2005; Kalema 2010). However, the most does not accumulate to any large extent, and maintains adversely affected species that were decreasing in abun- much of the woodlands as a shrub transition. Fire is indeed dance (Kalema 2010) are Albizia spp. and Terminalia spp. an important factor for the maintenance of African savanna This is probably because they are highly preferred for ecosystems (Bond and Van Wilgen 1996). poles, timber and charcoal production, and perhaps also Over the last 30 years the woodland cover of due to their relatively poor regenerative capacities (few Nakasongala District has decreased and is now mostly open resprouting stumps and relatively low recruitment; Kalema woodland in transition to thicket/shrubland, while areas 2010). under cultivation and settlements have increased (Kalema 2010), mirroring patterns seen in other African savannas Species richness (Luoga et al. 2005; Mwavu and Witkowski 2008b; Coetzer et al. 2010). Total woody plant species richness differed signiﬁcantly The high density and number of Acacia spp. are among land uses with charcoal production and cultivation probably facilitated by seed dispersal by ruminants such being higher than grazing. Differences in species rich- as the abundant cattle that graze in this multiple-use ness between land uses may be the result of the different savanna. Certain Acacia spp. also form persistent seed land use practices per se, or because of differences in banks (Witkowski and Garner 2000), with animal faeces the number of individuals counted (Gotelli and Colwell also providing favourable germination beds (Schultka and 2001). Charcoal production and cultivation were equally Cornelius 1997). Seasonal bush burning may be a contribu- well sampled (24 plots each) and had an almost equal num- tory factor to the high abundances of acacias in the studied ber of species (77 vs. 76), while grazing with 27 plots savanna, since their germination is generally enhanced had only 57 species. However, the grazing lands include when subjected to the heat of ﬁre (Mbalo and Witkowski some hydromorphic grasslands, which typically have lower 1997; Teketay 1997). tree densities. Woody species richness in a Tanzanian Some of the species encountered were restricted to par- miombo woodland also differed between shifting cultiva- ticular land-use types, suggesting the inﬂuence of land-use tion and more permanently cultivated areas (Luoga et al. practices in the distribution of woody plants. For example, 2005). The patchwork in the landscape after abandonment the higher abundances of P. thonningii and A. seyal in the of the land provides opportunities for different functional livestock grazing areas may be attributed to them not being groups of species without the disappearance of the original palatable or preferred species by mammalian herbivores species (Luoga et al. 2004). Indeed, richness and diver- (Anderson et al. 2007), high resprouting ability and animal sity may increase with increasing heterogeneity within a seed dispersal. On the other hand, the presence of Acacia range of patch sizes (Cabral et al. 2003). However, the mellifera, H. abyssinica, L. camara, R. natalensis and ever-expanding shifting cultivation, leading to fragmenta- Carissa edulis, which are encroacher species in disturbed tion of the remaining natural habitats may result in local vegetation is not surprising (Van Vegten 1983). These extinction of small, isolated populations (Tilman et al. species are neither browsed by herbivores nor harvested 2002). Thus, shifting cultivation can play either a posi- for charcoal production. Indeed, selective predation of tive or a negative role, depending on how it is managed. preferred seedling species by herbivores has far-reaching Variation in species richness between land uses may also be 240 V.N. Kalema and E.T.F. Witkowski explained by a variety of other factors that include habitat herbivory and extent of bush ﬁres than in the other land quality, spatio-temporal dynamics, boundary characteris- uses. Both ﬁres and herbivory may inhibit establishment of tics and neighbourhood effects (e.g. Waldhardt and Otte seedlings and recruitment of saplings (Helm et al. 2011), 2003). consequently affecting the population structure and regen- The overall sampled woody species richness of eration status of the species. Tree density at a site may Nakasongola (99 species, 31 families within 75 plots change rapidly with changes in the frequency or intensity with an area of 0.1 ha) is lower than the forest– of herbivory and ﬁre (Bond and van Wilgen 1996). Such woodland–savanna mosaic of northern Budongo Forest changes can be extensive, inﬂuencing vegetation dynamics Reserve, north-west Uganda (121 species, 38 families at the landscape scale (Sinclair and Arcese 1995). In some within 594 plots with an area of 0.05 ha; Nangendo et al. places at Nakasongola where livestock grazing and termite 2006). Although both occur within the same ecological damage were heavy, bare patches were common. zone, the latter is a reserve, where human disturbances are Compared with other African savannas, H diversity restricted. Species richness of Nakasongola is also lower (0.41–2.64) in Nakasongola tended to be higher than south- than the woodlands of Katavi–Rukwa ecosystem in western ern Malawian miombo woodlands (0.55–1.26; Mwase et al. Tanzania (229 species, 45 families within 50 plots with an 2007), but lower than the Kitulangalo miombo woodland area of 0.1 ha; Banda et al. 2008), the Kitulangalo Forest of Tanzania (2.9–3.13; Malimbwi et al. 1994) and South Reserve and surrounding communal lands of Tanzania African communal savannas (2.5–3.9; Dovie et al. 2008). (133 species, 31 families within 64 plots with an area of 0.1 ha; Luoga et al. 2000b) and communal savanna Beta diversity woodlands in three South African provinces (135 species, 42 families within 90 plots with an area of 0.1 ha; Dovie In spite of the low alpha diversity, the multiple-use savan- et al. 2008). These comparisons suggest loss of species nas of Nakasongola have relatively high beta diversity. The from Nakasongola through habitat degradation. The rich- relatively high values for all the beta diversity indices and ness of only 2–31 species per 0.1 ha in Nakasongola is low low similarities between plots and land-use types are indi- relative to those reported elsewhere. However, it is similar cators of gradients in the species composition of these to 1–28 species per 0.1 ha plot in the woodlands of western savanna woodlands. The general absence of signiﬁcant dif- Tanzania (Banda et al. 2008). ferences in species composition between the charcoal pro- duction and cultivated areas also suggests the inﬂuence of an environmental gradient rather than differences between Alpha diversity the two land-use types. The lack of differences is probably Woody plant alpha diversity (H and Fisher’s) did not gen- due to the cyclic sequence of land use over time. The high erally increase with increasing distance along the transect contribution of C. collinum, C. molle and C. ghasalense to away from households, the assumed source of disturbance. the similarity in species composition among plots under the Indeed, regression analyses revealed that the distance of charcoal production land use, despite them being the most sampling plots away from households, the assumed source utilized species for charcoal production, shows their ability of human disturbance, to woodlands accounted for a very to recover from disturbance and to occupy a wide variety small fraction (<14.2%) of the variation in woody species of habitats. These results generally point to inﬂuence of an diversity within this multiple-use savanna. This suggests environmental gradient, in addition to anthropogenic dis- that there is no clear gradient of increasing resource avail- turbance, in the variation of species composition within ability or decreasing human disturbance with increasing this multiple-use savanna. Species composition and dis- distance from homesteads or villages. Indeed, charcoal tribution of plant communities are shaped not only by burning, a major source of disturbance to woody species, anthropogenic disturbances but also by environmental con- is not inﬂuenced by the distances from homesteads or vil- ditions, spatial factors and species competition (Cousins lages in this region, but rather the availability of suitable and Eriksson 2002). Among these is below ground avail- and sizeable woody individuals for charcoal production. ability of soil nutrients that plays an important role in the However, woody plant alpha diversity was signiﬁcantly assembly of tropical tree communities at local scales (John higher under cultivation and charcoal compared with graz- et al. 2007). Other broader scale studies have illustrated ing. Similarly, cumulative Fisher’s alpha was higher under how historical or climatic factors may also act to constrain charcoal and cultivation than under grazing. These results diversity (e.g. Kleidon and Mooney 2000; Sarr et al. 2005). suggest that species composition and distribution of plant Within these savannas, natural and anthropogenic dis- communities in this savanna are to a great extent shaped turbances from subsistence harvesting of poles and com- by anthropogenic disturbances. On the other hand, these mercial charcoal production are scattered in space and results are consistent with Hayek and Buzas’ (1997) sug- time, contributing to habitat heterogeneity. This habi- gestion that the more species that are present, and the tat heterogeneity may favour the coexistence of species more evenly the individuals are spread across the species, with different ecological requirements, thus contributing the higher the resulting H . Fisher’s alpha is low when to the maintenance of community diversity (Mwavu and the number of species is low. The low species diversity Witkowski 2009) and variation in species composition in the grazing lands may be a consequence of greater among the plots along a transect. Anthropogenic land-use International Journal of Biodiversity Science, Ecosystem Services & Management 241 change is one of the most important factors contributing to that supply fuelwood to East African urban areas. Together global change (Sala et al. 2000), and changes in landscape with this understanding of diversity patterns in relation to structure and agricultural land-use intensity are likely to anthropogenic factors in the woodlands, a detailed study of inﬂuence plant community composition and similarity. The the inﬂuence of other environmental factors, particularly studied multiple-use savanna is characterized by anthro- topo-edaphic variability, would provide a more complete pogenic disturbances which have been patchy and have understanding of species distribution patterns. different inﬂuences on community species composition. Such intrinsic disturbances may lead to abrupt changes in Acknowledgements habitat, consequently greatly contributing to heterogeneity This study was ﬁnancially supported by the Third World in this savanna environment and result in reversal or delay Organization for Women in Science (TWOWS), the South of successional states. The high beta diversity under graz- African National Research Foundation (NRF 2069152), the Andrew Mellon Postgraduate Mentorship Award and the Post ing compared with other land uses in this savanna may be Graduate Merit Award from the University of the Witwatersrand, attributed to the more heterogeneous spatial distribution, Johannesburg. We thank Vivienne Williams for guidance with the and varying levels and intensities of grazing (stocking rates EstimateS analyses. We thank Edward Mwavu for valuable com- between villages) that contribute to greater environmen- ments on the manuscript. We thank Nyesiga Grace, Lunkuraite tal heterogeneity. Livestock grazing impacts are typically Alex, Mukasa Ivan and Sembatya Tadeo for their assistance with ﬁeld data collection, our driver Robert, the District Resource, not uniform across a landscape because herbivores are Environment and Livestock Ofﬁcers in Nakasongola, all chiefs highly selective of areas with higher soil fertility (soil of subcounties and all those in one way or another who helped to type), new grass growth from burnt areas and particular make this study a success. landscape positions (Senft et al. 1987; O’Connor et al. 2011). Abrupt changes in site conditions that are accom- panied by changes in the physical and chemical nature References of soil nutrient dynamics and microclimate may inﬂuence Anderson TM, Ritchie ME, Mc Naughton SJ. 2007. Rainfall and soils modify plant community response to grazing in plant community composition and species diversity pat- Serengeti National Park. 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Benth. 76 15 Markhamia lutea K. Schum. 15 3 Stereospermum kunthianum Cham. 105 16 Burseraceae Commiphora africana (A. Rich) Engl 45 10 Commiphora dalzielii Hutch. 50 2 Caesalpiniaceae Piliostigma thonningii (Schumach.) Milne-Redh. 2275 43 Senna siamea (Lamarck) H.S. Irwin & Barneby 62 Capparidaceae Capparis fascicularis DC. 361 3 Crateva adansonii DC. 4 1 Maerua triphylla A. Rich. 2 2 Celastraceae Mystroxylon aethiopicum (Thunb.) Loes. 11 2 Maytenus senegalensis (Lam) Exell 418 30 Combretaceae Combretum capituliﬂorum Fenzl ex Schweinf. 1801 22 Combretum collinum Fresen 9241 63 Combretum ghasalense Engl. & Diels 4725 59 Combretum molle Engl. & Diels 5814 60 Terminalia glaucescens Planch. ex Benth. 521 32 Ebenaceae Euclea latidens Stapf 252 31 Euphorbiaceae Bridelia scleroneura Müll. Arg. 87 12 Euphorbia candelabrum Tremaut ex Kotschy 29 11 Flueggea virosa (Willd.) Voigt 1 1 Hymenocardia acida Tul. 2191 40 Phyllanthus ovalifolius Forssk. 3 1 Securinega sp. Comm. Ex Juss. 1 1 Securinega virosa (Roxb. ex Willd) Baill. 62 15 Hypericaceae Psorospermum febrifugum Spach 1 1 Lamiaceae Clerodendrum cordifolium A. Rich. 1 1 Vitex doniana Sweet 365 7 Vitex ferruginea Schumach. & Thonn. 510 21 Vitex ﬁscheri Gürke 26 2 Loganiaceae Strychnos innocua Delile 455 30 Meliaceae Ekebergia capensis Sparrm. 33 3 Pseudocedrela kotschyi Harms 186 16 Trichilia dregeana Harv. & Sond. 1 1 Trichilia emetica Vahl 2 2 Mimosaceae Acacia hamulosa Benth. 74 15 Acacia hockii De Wild. 1708 49 Acacia malacocephala Harms 7 2 Acacia mellifera Benth. 2 1 Acacia polyacantha Willd. 894 47 Acacia senegal Willd. 113 8 Acacia seyal Delile 139 4 Acacia sieberiana DC. 384 36 Albizia coriaria Welw. 106 14 Albizia malacophylla Walp. 64 7 Albizia zygia J.F. Macbr. 1738 38 Calliandra sp. Benth. 32 2 Dichrostachys glomerata Chiov. 179 15 (Continued) International Journal of Biodiversity Science, Ecosystem Services & Management 245 Appendix 1. (Continued). Frequency Families Species Number of individuals within plots Moraceae Antiaris toxicaria Lesch 62 10 Artocarpus heterophyllus Lam. 21 Ficus dicranostyla Mildbr. 1 1 Ficus natalensis Hochst. 29 8 Ficus ovata Vahl 1 1 Ficus sp. L. 33 2 Milicia excelsa (Welw.) C.C. Berg 91 5 Olaceae Ximenia aegyptiaca L. 4 1 Ximenia americanaL9 2 Papilionaceae Erythrina abyssinica Lam. 6 3 Lonchocarpus laxiﬂorus Guill. & Perr. 3 2 Rhamnaceae Ziziphus mauritiana Lam. 56 3 Rubiaceae Canthium vulgare (K. Schum.) Bullock 2 1 Gardenia ternifolia Schumach. & Thonn. 380 46 Pavetta crassipes K. Schum. 22 4 Pavetta gardeniifolia Hochst. ex A. Rich 56 4 Pavetta insignis Bremek. 6 1 Tricalysia bagshawei S. Moore 4 2 Tricalysia niamniamensis Schweinf. ex. Hiern 1 1 Vangueria apiculata K. Schum. 23 3 Vangueria tomentosa Hochst. 18 1 Rutaceae Vepris nobilis (Delile) W. Mziray 1320 24 Zanthoxylum chalybeum Engl. 88 9 Zanthoxylum rubescens Planch. Ex Hook. 33 5 Sapindaceae Allophylus abyssinicus Radlk. 1 1 Allophylus africanus P. Beauv. 137 23 Sapotaceae Manilkara dawei (Stapf) Chiov. 140 16 Pouteria sp. Aubl. 11 Simaroubaceae Balanites aegyptiacus Delile 17 4 Harrisonia abyssinica Oliv. 1675 65 Sterculiaceae Dombeya dawei Sprague 40 2 Tiliaceae Grewia mollis Juss. 1142 53 Grewia trichocarpa Hochst. ex A. Rich 4 2 Trema guineense (Schumach. & Thonn.) Ficalho 74 11 Umbelliferae Steganotaenia araliacea Hochst. 12 4 Verbenaceae Lantana camara L. 368 18 Unidentiﬁed Enseka 24 2 Kiondo 51 Notes: The total number of individuals and frequencies within plots (number of times present within the 75 plots) are included. Introduced species. Near threatened. Introduced and invasive alien. Local vernacular name. 246 V.N. Kalema and E.T.F. Witkowski Appendix 2. Contribution of individual species to the overall similarity within land-use types (grazing, cultivation and charcoal production). Mean Mean Percentage Cumulative Species abundance similarity contribution percentage Charcoal (mean similarity = 30.5) Combretum collinum 129.9 7.4 24.1 24.1 Combretum molle 104.8 4.8 15.9 40 Combretum ghasalense 70.2 4.7 15.4 55.4 Rhus natalensis 30.2 3.2 10.4 65.8 Hymenocardia acida 43 1.8 6 71.8 Harrisonia abyssinica 23.3 1.6 5.3 77.1 Combretum capituliﬂorum 50.6 0.9 2.8 79.9 Grewia mollis 19.5 0.8 2.7 82.6 Annona senegalensis 15.4 0.7 2.2 84.8 Acacia hockii 21.7 0.7 2.2 87.1 Albizia zygia 13.5 0.6 1.9 89 Vepris nobilis 47.2 0.5 1.6 90.6 Cultivation (mean similarity = 25.3) Combretum collinum 135.7 6.5 25.6 25.6 Combretum molle 102.5 4.2 16.5 42.1 Albizia zygia 58.5 2.6 10.2 52.4 Acacia hockii 42.5 2.2 8.5 60.9 Harrisonia abyssinica 33.4 1.9 7.6 68.5 Combretum ghasalense 31.4 1.5 5.8 74.3 Rhus natalensis 17.7 1.2 4.8 79.1 Grewia mollis 21.3 1.1 4.2 83.4 Acacia polyacantha 20.3 0.6 2.5 85.9 Hymenocardia acida 28.2 0.5 1.9 87.8 Strychnos innocua 14.1 0.4 1.8 89.6 Combretum capituliﬂorum 23.6 0.4 1.5 91 Grazing (mean similarity = 25.4) Combretum collinum 106.2 7.3 28.7 28.7 Piliostigma thonningii 64.4 7 27.7 56.3 Combretum ghasalense 84.7 4.5 17.6 74 Combretum molle 31.1 1.8 7 81 Rhus natalensis 11 0.8 3.3 84.3 Harrisonia abyssinica 11.7 0.6 2.2 86.5 Acacia polyacantha 5.8 0.5 1.8 88.3 Hymenocardia acida 17.9 0.4 1.7 90 Gardenia ternifolia 6.6 0.4 1.6 91.5 Note: Species are ranked according to their percentage contribution to the similarity within each land use. Appendix 3. Results of SIMPER analysis highlighting the species contributing most to the dissimilarity between land-use types. Mean Mean Mean Percentage Cumulative a b Species abundance abundance dissimilarity contribution percentage Charcoal and cultivation (mean dissimilarity = 73.2) Combretum collinum 129.9 135.7 11.5 15.8 15.8 Combretum molle 104.8 102.5 9 12.3 28 Combretum ghasalense 70.2 31.4 5.8 8 36 Hymenocardia acida 43 28.2 4.3 5.9 41.9 Combretum capituliﬂorum 50.6 23.6 4 5.5 47.4 Acacia hockii 21.7 42.5 3.9 5.4 52.8 Albizia zygia 13.5 58.5 3.7 5 57.8 Vepris nobilis 47.2 7.8 3.2 4.4 62.2 Harrisonia abyssinica 23.3 33.4 2.4 3.3 65.5 Acacia polyacantha 10.5 20.3 2.3 3.1 68.6 Rhus natalensis 30.2 17.7 2.2 3 71.6 Grewia mollis 19.5 21.3 2 2.7 74.3 Annona senegalensis 15.4 10.9 1.7 2.4 76.7 Piliostigma thonningii 17.3 5 1.6 2.2 78.9 (Continued) International Journal of Biodiversity Science, Ecosystem Services & Management 247 Appendix 3. (Continued). Mean Mean Mean Percentage Cumulative a b Species abundance abundance dissimilarity contribution percentage Vitex doniana 0 15.2 1.3 1.8 80.6 Strychnos innocua 3.9 14.1 1.1 1.5 82.2 Vitex ferruginea 11 9.3 1.1 1.5 83.7 Terminalia glaucescens 8.9 6.5 0.9 1.3 84.9 Lannea barteri 12.5 2 0.9 1.2 86.1 Capparis fascicularis 15 0 0.8 1.1 87.2 Lantana camara 1.1 9.8 0.8 1 88.2 Acacia sieberiana 7.7 3.7 0.7 1 89.2 Dichrostachy glomerata 0.4 5.3 0.5 0.7 89.9 Carissa edulis 3.3 4.3 0.5 0.6 90.6 Charcoal and grazing (mean dissimilarity = 76.7) Combretum collinum 129.9 106.2 12.6 16.4 16.4 Combretum ghasalense 70.2 84.7 9.5 12.4 28.8 Combretum molle 104.8 31.1 8.1 10.6 39.4 Piliostigma thonningii 17.3 64.4 6.2 8.1 47.5 Hymenocardia acida 43 17.9 4.9 6.4 53.9 Combretum capituliﬂorum 50.6 0.7 3.6 4.7 58.7 Vepris nobilis 47.2 0 3.3 4.3 63 Rhus natalensis 30.2 11 3.1 4 67 Acacia hockii 21.7 6.2 2.3 3 70 Harrisonia abyssinica 23.3 11.7 2.2 2.9 73 Annona senegalensis 15.4 5.9 1.9 2.5 75.4 Grewia mollis 19.5 6.1 1.8 2.4 77.8 Acacia polyacantha 10.5 5.8 1.4 1.8 79.6 Albizia zygia 13.5 0.3 1.4 1.8 81.4 Maytenus senegalensis 4.6 9.6 1.1 1.4 82.8 Terminalia glaucescens 8.9 5.6 1 1.4 84.1 Lannea barteri 12.5 1.8 1 1.3 85.4 Acacia sieberiana 7.7 4.1 0.9 1.2 86.6 Vitex ferruginea 11 0.9 0.9 1.2 87.8 Capparis fascicularis 15 0 0.9 1.2 88.9 Acacia seyal 0 5.1 0.8 1 89.9 Gardenia ternifolia 5 6.6 0.8 1 91 Cultivation and grazing (mean dissimilarity = 81.2) Combretum collinum 135.7 106.2 14.3 17.6 17.6 Combretum molle 102.5 31.1 8.3 10.2 27.8 Combretum ghasalense 31.4 84.7 8 9.8 37.6 Piliostigma thonningii 5 64.4 6.6 8.2 45.8 Albizia zygia 58.5 0.3 4.7 5.8 51.6 Acacia hockii 42.5 6.2 4.6 5.7 57.2 Hymenocardia acida 28.2 17.9 3.4 4.1 61.4 Harrisonia abyssinica 33.4 11.7 3.1 3.8 65.1 Acacia polyacantha 20.3 5.8 2.6 3.2 68.4 Grewia mollis 21.3 6.1 2.1 2.6 71 Combretum capituliﬂorum 23.6 0.7 1.9 2.4 73.3 Rhus natalensis 17.7 11 1.8 2.2 75.6 Vitex doniana 15.2 0 1.7 2.1 77.7 Annona senegalensis 10.9 5.9 1.5 1.8 79.5 Strychnos innocua 14.1 0.9 1.3 1.6 81.2 Lantana camara 9.8 3.9 1.2 1.5 82.7 Acacia seyal 0 5.1 1 1.2 83.9 Maytenus senegalensis 2.1 9.6 1 1.2 85.1 Terminalia glaucescens 6.5 5.6 1 1.2 86.3 Gardenia ternifolia 3.4 6.6 0.8 1 87.3 Vepris nobilis 7.8 0 0.8 1 88.3 Dichrostachys glomerata 5.3 1.5 0.8 0.9 89.3 Vitex ferruginea 9.3 0.9 0.7 0.9 90.2 Notes: Species are ranked according to their percentage contribution to the dissimilarity between land-use types and only those with >2% contribution are shown. Dissimilarity and percentage cumulative dissimilarity are also given. a b Mean abundance for ﬁrst member of the pair. Mean abundance for second member of the pair. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biodiversity Science, Ecosystem Services & Management Taylor & Francis http://www.deepdyve.com/lp/taylor-francis/land-use-impacts-on-woody-plant-density-and-diversity-in-an-african-fBzvC9fZ71

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Publisher: Taylor & Francis
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ISSN: 2151-3732
eISSN: 2151-3740
DOI: 10.1080/21513732.2012.681070
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Abstract

International Journal of Biodiversity Science, Ecosystem Services & Management Vol. 8, No. 3, September 2012, 231–247 Land-use impacts on woody plant density and diversity in an African savanna charcoal production region Vettes Neckemiah Kalema* and Edward T.F. Witkowski Restoration and Conservation Biology Research Group, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, Private Bag 3, WITS 2050, South Africa The density and diversity of woody plant species were studied within grazing, cultivation and charcoal production land-use areas in a multiple-use savanna woodland, central Uganda, using 75 plots with an area of 0.1 ha (Whittaker plots). Plant density was signiﬁcantly higher under charcoal production (7131 ± 755 plants/ha) and cultivation (6612 ± 665 plants/ha) compared with the grazing lands (4152 ± 525 plants/ha). At the plot level, species richness and Fisher’s alpha diversity (α) were relatively low, ranging 2–31 species and 0.34–6.34, respectively, but both were signiﬁcantly higher under charcoal production and cultivation compared with grazing. Similarly, cumulative species richness and Fisher’s alpha diversity were higher under charcoal production and cultivation compared with grazing. Community species composition differed signiﬁ- cantly (Global R = 0.14, p = 0.001; ANOSIM, ANalysis Of SIMilarity) among land uses. However, the distance of ANOSIM sampling plots away from households, the assumed source of human disturbance to woodlands, accounts for a very small fraction (<14.2%) of the variation in woody species diversity within this multiple-use savanna. Beta diversity was highest under grazing, followed by cultivation and charcoal production, suggesting a more heterogeneous spatial distribution of species under grazing. Within each land use, mean similarities were low, ranging 25–31%. Mean pairwise dissimilarities between land uses were relatively high, ranging 73–81%. This suggests that variations in species composition and diversity are to a great extent inﬂuenced by land-use and anthropogenic disturbances. The relatively low woody species diversity and richness in this savanna indicates woodland degradation, fragmentation and local species loss resulting from unsustainable harvesting for charcoal, and short interval shifting cultivation. Keywords: ANOSIM; anthropogenic disturbance; cultivation; grazing; land degradation; species richness; sustainable land management Introduction et al. 2004; Mwavu and Witkowski 2008a). They are rapidly undergoing severe large-scale changes, through Savanna woodlands make up most of the tropical and sub- indiscriminate burning or conversion to other land uses and tropical woodland cover in sub-Saharan Africa and provide cover types (Rennolls and Laumonier 2000; Millennium a wide range of beneﬁts and products to local and national Ecosystem Assessment 2005a, 2005b). The development production. They provide the major source of energy for of more sustainable land-use systems necessitates an the majority of households (Luoga et al. 2000a; Kituyi understanding of the nature, dynamics and production 2004; Millennium Ecosystem Assessment 2005a) and are potential of these savanna woodland systems. An under- the focus of numerous livelihood activities in marginal- standing of the patterns of woody plant species diversity ized communities (Luoga et al. 2000b; Dovie et al. 2002, within the prevailing land uses and responses to changes 2005; Venter and Witkowski 2011). These savanna wood- in the environment is essential for long-term sustainability lands have numerous wild plant species that are important and to aid decisions on conservation priorities (Folke et al. in the subsistence sector, both for meeting a wide range 2004). of household needs and through increasing commercial- Relatively little is known about the woody plant diver- ization, generating incomes (Braedt and Stranda-Gunda sity in African savannas outside southern Africa and the 2000; Dovie et al. 2005). The southern and eastern African miombo ecoregion, and this is particularly the case in miombo woodlands are economically important for sup- Uganda. Most diversity studies in Uganda have focused plying timber, poles, ﬁrewood, charcoal, medicines, food, on tropical rainforests (e.g. Eilu et al. 2004; Mwavu ﬁbre and carvings for both rural and urban populations and Witkowski 2008a). Studies of savanna woodland in (Luoga et al. 2000a, 2000b). Uganda have mainly focused on biomass and bioenergy; There is, however, a widespread concern that the wood- management of ranching schemes (National Environment land ecosystems with unique and valuable biodiversity Management Authority 2002); and the growth, use and resources are being lost (Rennolls and Laumonier 2000; management of woodland resources (e.g. Namaalwa et al. Coetzer et al. 2010) as a result of both natural and 2005). Ugandan woodlands also play a major (often anthropogenic disturbances and mismanagement (Luoga *Corresponding author. Email: ykagemwa@yahoo.co.uk ISSN 2151-3732 print/ISSN 2151-3740 online © 2012 Taylor & Francis http://dx.doi.org/10.1080/21513732.2012.681070 http://www.tandfonline.com 232 V.N. Kalema and E.T.F. Witkowski unaccounted) role in the economy by providing fuel (char- The vegetation of the area is classiﬁed as Albizia– coal and ﬁrewood), grazing resources for livestock, land for Combretum woodland (Langdale-Brown et al. 1964). This cultivation and numerous other services. The charcoal is is a natural savanna woodland or woodland of mixed decid- transported to major commercial centres such as Kampala. uous trees, 3–12 m in height and grasses, 0.3–1.3 m in Woodland conversion to farmland, selective harvesting height at maturity. The cover of the grass layer varies of woody plants for ﬁrewood and charcoal production, with season, is often patchy and subordinate to the seasonal ﬁres, livestock grazing and hunting of native her- tree layer. Most of the grazing lands occur on hydro- bivores are major mechanisms of woodland degradation, morphic grasslands that are only suitable for grazing. habitat change and biodiversity loss in many parts of Africa There are thicket patches dominated by Acacia hockii, (Luoga et al. 2005; Banda et al. 2006). Acacia gerradii, Acacia kirkii ssp. mildbraedii, Acacia This study aims to assess woody plant density and senegal and Euphorbia candelabrum established in sec- species diversity (richness, alpha diversity and beta diver- ondary wooded grasslands as a consequence of anthro- sity) in response to the three main land uses (grazing, cul- pogenic disturbances (White 1983). The vegetation in tivation and charcoal production) in the extensive savanna Nakasongola District is mainly open woodland in transi- woodlands of Nakasongola District, central Uganda. The tion to thicket/shrubland, as woodland cover has decreased, increasing human pressure on these tropical ecosystems while areas under cultivation/settlements have corre- makes information on their patterns of plant diversity (i.e. spondingly greatly increased since 1984 (Kalema 2010). species richness, alpha diversity and beta diversity) and In Nakasongola District, 70–80% of households not only distributions more critical today than ever before in order engage in charcoal production but also livestock hus- to protect and conserve the remaining species effectively bandry, and subsistence agriculture, mainly shifting cul- and efﬁciently (e.g. Cadotte et al. 2002; Natta et al. 2002; tivation, provides 85% of the food supply, and more than Zapfack et al. 2002). Alpha diversity and beta diversity 50% of monetary income (Nakasongola Local Government together provide a generally good overall assessment of 2002; Figure 1). plant diversity or biotic heterogeneity of an area. Beta diversity is important in at least indicating the degree to Sampling design which ecosystems have been partitioned by species. There is a sequence of land-use change over time, with most areas used for slash and burn agriculture; char- Materials and methods coal production areas are subsequently used for cultiva- Study area tion (they are burnt and hence have temporarily raised The savanna woodlands of Nakasongola District occur soil nutrient levels suitable for crops), and may then ◦ ◦ south of Lake Kyoga, central Uganda (0 40 –1 41 N, be used for grazing for a short period, allowing the ◦ ◦ 2 31 57 –32 48 E). The district covers 3424 km , 90% of woody plants to recover by basal resprouting from the cut which is woodland and grassy savanna, with 322 km stumps (Luoga et al. 2004; Mwavu and Witkowski 2008a). (∼10%) of open water and wetlands. It comprises The current land use was identiﬁed for the purposes of eight subcounties (administrative subdivisions), namely this study. Representative villages (and surroundings) in Kakooge, Kalongo, Wabinyonyi, Kalungi, Nabiswera, each of the eight subcounties were selected (with the Nakitoma, Lwampanga and Lwabiyata. Subcounties con- help of local leaders and ofﬁcials from the Department sist of villages, ranging from 15–77 to 1741–4877 house- of Natural Resources and Environment) during March holds. By 2001, the district had a total human population 2006 for woody vegetation sampling. In each subcounty of 128,126 (41 people/km ), with 50.2% males and 49.8% at least three transects were established. Transects were females. About 95% of the population are in rural areas laid radiating away from the villages/households where (Uganda Bureau of Statistics 2002). subsistence activities are paramount, often resulting in Annual rainfall ranges from 500 to 1000 mm and gradients of increasing resource availability or decreas- is concentrated within two wet seasons (March–May ing human disturbance with distance from village (Fisher and August–November). Reliability of rainfall received is et al. 2011). Each transect represented one of the three higher in the south and declines gradually towards the major land uses, with the exception of Nabiswera, which north. The mean monthly maximum temperature ranges had four transects. The additional transect was an attempt ◦ ◦ from 25 Cto35 C, and the mean monthly minimum tem- to include the most degraded grazing area. Transect loca- ◦ ◦ perature ranges from 18 Cto21 C. The topography of tions were selected considering the homogeneous nature of the area undulates from 1036 to 1160 m above sea level. the area for a particular land use and of sufﬁciently large The major geological formations are characterized by the extent to accommodate at least three 20 × 50 m (0.1 ha) presence of young intrusive rocks, mostly acidic and less plots, with a minimum separation distance of 200 m. The commonly basic. The youngest formations date from the 20 ×50 m (Whittaker) plot size has been widely used Pleistocene era and are represented by sands, quartz and for assessment of shrublands, grasslands, tropical savan- clays of alluvial or lacustrine (i.e. formed at the bottom or nas, woodlands and forests (Cowling and Witkowski 1994; along the shores of lakes as geological strata) origin (Parker Luoga et al. 2002; Beater et al. 2008; Dovie et al. 2008; et al. 1967). Witkowski and Garner 2008). Hence, 24 plots with an area International Journal of Biodiversity Science, Ecosystem Services & Management 233 Uganda Africa Uganda Nakasongola Lwabiyata Nakitoma Lwampanga Lkyoga Nabiswera Kalungi Population density Wabinyonyi 18–21/km 22–29/km Kalongo 30–38/km 39–77/km Kakooge 78–130/km Waterbodies km Figure 1. Map of Nakasongola District showing the eight constituent subcounties and their human population density. Inset is a map of Africa showing Uganda and a map of Uganda showing Nakasongola District shaded (TC: Town centre; Lkyoga: Lake Kyoga). of 0.1 ha were sampled for each of the cultivation and Data analysis charcoal production land-use types, and 27 plots were sam- Alpha diversity pled for grazing. In total, 25 transects with 75 plots were Fisher’s alpha (α) and Shannon–Wiener (H ) diversity established (Figure 2). indices were employed to quantify alpha diversity at the Within each 0.1 ha plot, woody plant species, number 0.1 ha scale, while rarefaction was used to estimate the of individuals and height and stem diameter at refer- number of species expected (E(Sn)) to be present in a ence height (1.3 m, except for seedlings and shrubs) of random sample (i.e. plot) of individuals taken from any each individual were recorded. Based on stem diameter given collection, and provides conﬁdence limits of species and height, woody plants were categorized as trees or richness (Magurran 2004). Plotting the rarefaction curves shrubs (USDA Forest Service 1989). Seedlings had a sin- facilitates improved interpretation of species richness from gle stem with stem diameter of ≤0.5 cm, were ≤1min sample plots of varying size and number and from differ- height and had not previously resprouted, while saplings ent communities (Gotelli and Colwell 2001; Williams et al. or juvenile trees were >0.5–5 cm dbh and >1min 2005). The sample plots were randomized 100 times to height. However, the seedling data were not included in compute the mean estimator and expected species richness this assessment. Species identiﬁcation in the ﬁeld was for each sample plot accumulation level using EstimateS supported by identiﬁcation guides mainly based on the (Colwell 2006). Flora of Tropical East Africa (Polhill 1952 and subse- Fisher’s alpha diversity index is not inﬂuenced by the quent volumes), Katende et al. (1995) as well as the size of the sampling area (i.e. plot) and is less affected assistance of a botanist familiar with the ﬂora of the area. by the abundance of the rarest or commonest species Voucher species were collected and subsequently identiﬁed compared with other diversity measures (Magurran 2004). in the Botany Department Herbarium, Makerere University Fisher’s alpha was, however, not calculated separately for (MHU), Kampala, Uganda. 234 V.N. Kalema and E.T.F. Witkowski (a) (b) (c) Figure 2. Photographs of the major land-use practices: (a) wood stacked in preparation for charcoal production, (b) cattle grazing in a wetland and (c) cultivation fallow in a multiple land-use equatorial African savanna, central Uganda. both the tree and shrub data due to the high number of index of similarity (C ). The Morisita–Horn index MH singletons in the individual data sets, which resulted in assesses similarity in species composition between plots number of individuals (N) divided by number of species (Colwell et al. 2004; Magurran 2004), and is a quantitative (S) being ≤1.44. Fisher’s alpha cannot be calculated when similarity index that is not strongly inﬂuenced by species N /S ≤ 1.44 (Magurran 2004). Diversity indices were richness and sample size. For each land-use type, C was MH calculated using Species Diversity and Richness version calculated by averaging all the plot pairwise values for each IV (Pisces Conservation Ltd., Lymington, UK) (Seaby land-use type. Morisita–Horn index varies from 1 (com- and Henderson 2007) and EstimateS version 8.0 (Colwell plete similarity) to 0 (complete dissimilarity) in species 2006). The sample plots were randomized 100 times in composition. EstimateS to compute the cumulative H and Fisher’s α Plots were also arranged according to land-use type and to construct the curves. Differences in tree and shrub and variations in community species composition were species richness and diversity between the three land-use tested by employing ANalysis Of SIMilarity (ANOSIM), types were compared using one-way Analysis of Variance a permutation test in CAP 4 (Pisces Conservation Ltd.) and Tukey’s Honestly Signiﬁcant Difference (HSD) for (Seaby et al. 2007). ANOSIM computes a test statistic unequal sample sizes (i.e. different number of plots per (R ) reﬂecting the observed differences among repli- ANOSIM land-use type). We also tested for the relationship between cates (i.e. plots) between sites (in this case land-use types), woody plant diversity (i.e. species richness and alpha diver- contrasted with differences among replicates within sites. sity) and the ‘distance of the sampling plot along the A zero (0) occurs if the high and low similarities are transect radiating away from the households’, the assumed perfectly mixed and bears no relationship to the group source of human disturbance, using regression analysis. (i.e. plots within a land-use type). A value of minus one The regression analyses were performed separately for (i) (−1) indicates that the most similar sample plots are all total woody (i.e. trees and shrubs combined), (ii) trees outside of the group. A value of positive one (+1) indi- and (iii) shrubs at both the whole savanna and land-use cates that the most similar sample plots are within the same type scales. group (Seaby et al. 2007). The percentage similarity among land uses was also analysed using SIMilarity PERcentages (SIMPER) in CAP 4. SIMPER breaks down the con- Beta diversity tribution of each species to the observed similarity (or Beta diversity at the plot level was assessed using dissimilarity) between sample plots. It allows the user to Whittaker’s beta diversity index (β ), Wilson and W identify the species that are most important in creating Schmida’s index (β ) and the modiﬁed Morisita–Horn T the observed pattern of similarity. The method uses the International Journal of Biodiversity Science, Ecosystem Services & Management 235 Table 1. Brief description of the indices and measures applied to the data. Index/measure Description Diversity indices Fisher’s alpha (α) (Magurran 2004) This is a parametric index of diversity that assumes that the abundance of species follows the log series distribution Shannon–Wiener (H ) (Seaby and Henderson 2007) Shannon index gives a measure of both species numbers and the evenness of their abundance; the resulting ﬁgure does not give an absolute description of a site’s biodiversity. It is particularly useful when comparing similar ecosystems or habitats, as it can highlight one example being richer or more even than another Species richness Rarefaction (Gotelli and Colwell 2001; Colwell et al. 2004) Rarefaction is used to produce a smoothed curve that is the statistical expectation of corresponding accumulation curve. Rarefying a sample estimates its expected species richness at different values of n samples or N individuals from the poo- led total species richness after randomizing the sample order Whittaker’s β diversity index (Colwell et al. 2004) Used to test the degree to which heterogeneity in species composition varies among functional groups or among different regions for which gradients are difﬁcult to compare Wilson and Schmida’s (β ) (Colwell et al. 2004) Reﬂects species turnover by calculating the gain and loss of species along a gradient standardized by the average number of species in each plot Morisita–Horn index of similarity (C ) (Magurran 2004) Assesses similarity in species composition between plots. Not MH inﬂuenced by sample size or species richness ANalysis Of SIMilarities (ANOSIM) (Seaby et al. 2007) It is a multivariate, non-parametric measure that provides a way to test statistically whether there is a signiﬁcant difference between two or more groups of sampling units SIMilarity PERcentages (SIMPER) (Seaby et al. 2007) Breaks down the contribution of each species to the observed similarity (or dissimilarity) between samples. It allows the user to identify the species that are most important in creating the observed pattern of similarity Bray–Curtis method (Seaby et al. 2007) The Bray–Curtis method operates at the species level, and therefore the mean similarity between groups 1 and 2 can be obtained for each species. It is widely employed in multivariate analysis of assemblage data. It reﬂects differences between two samples due both to differing community composition and/or differing total abundance Bray–Curtis measure of similarity, comparing in turn, each excelsa and Pouteria sp. are near threatened (International sample in Group 1 with each sample in Group 2. The Bray– Union for Conservation of Nature classiﬁcation; Pomeroy Curtis method operates at the species level and therefore et al. 2002). Calliandra sp., Artocarpus heterophyllus, the mean similarity between groups 1 and 2 can be obtained Senna siamea and Lantana camara are introduced and the for each species (Table 1). latter is also invasive (Appendix 1). The species accumulation curves for the combined 75 plots with an area of 0.1 ha, and for each land-use type Results asymptotes are reached, show that sampling was sufﬁcient Woody plant community composition (Figure 3). In addition, the species accumulation curve A total of 99 woody plant species, from 67 genera within was below the rarefaction curve, suggesting heterogeneity 31 families, were recorded from the 75 plots with an area among samples. of 0.1 ha. The most species-rich families were Mimosaceae Community species composition was signiﬁcantly dif- ferent among land uses (ANOSIM, Global R = (13 species), Rubiaceae (9), Moraceae (7), Euphorbiaceae ANOSIM 0.14, p = 0.001). Pairwise comparisons showed signiﬁcant (7), Anacardiaceae (6), Combretaceae (5) and Verbenaceae (5), with 15 others comprising 2–4 species and 9 with one differences in species composition between cultivation and species each (Appendix 1). The most species-rich genera grazing, as well as grazing and charcoal production, but were Acacia (8 species) Combretum (4), Ficus (4), Albizia not between cultivation and charcoal production (Table 2). (3), Pavetta (3) and Tricalysia (3), with the rest each hav- Woody plant density across all land-use types was 5893 ing 1–2 species (Appendix 1). None of the 99 species has ± 399 plants/ha. Density differed signiﬁcantly (F = 2,72 a restricted range as they all occur in more than one of the 6.3, p = 0.003) among land uses, with charcoal pro- four ﬂoral regions of Uganda (Flora of Tropical East Africa duction and cultivation signiﬁcantly higher than grazing (Polhill 1952 and more recent volumes). However, Milicia (Table 3). 236 V.N. Kalema and E.T.F. Witkowski Grazing (n = 27) Total (n = 75) Expected Observed Expected Observed 0 0 1 5 9 131721 252933 37414549 53576165 6973 1 3 5 7 9 1113 15 1719 21 23 2527 Charcoal (n = 24) Cultivation (n = 24) 60 60 Expected Expected Observed Observed 40 40 1 2 3 4 5 6 7 8 9 1011 1213 1415 1617 1819 202122 2324 1 2 3 4 5 6 7 8 9 1011 1213 1415 1617 1819 202122 2324 Sample plots (n) Sample plots (n) Figure 3. Rarefaction (expected) and species accumulation (observed) curves for the total woody species recorded in the 0.1 ha plots throughout the area (total), and for the grazing, cultivation and charcoal production land-use types, within this multiple-use equatorial African savanna, central Uganda. Table 2. ANOSIM in community species composition among higher for charcoal production and cultivation than grazing the different land-use types in a multiple-use equatorial African (Figure 4). savanna, central Uganda. Across all the plots alpha diversity ranged from 0.34 to 6.34 and from 0.14 to 2.64 for Fisher’s alpha (α) and Land-use type Charcoal production Grazing Shannon–Wiener index (H ), respectively. However, plot Cultivation 0.04 (0.063) 0.21 (0.001) values for both indices did not show a clear and uni- Grazing 0.15 (0.001) form increase with increasing distance along the transect Note: The ANOSIM sample statistic (R ) is reported with signiﬁ- (i.e. ﬁrst to last plot) radiating away from the households, ANOSIM cance level (p-value) in parentheses. the assumed source of human disturbance. Both H and alpha diversity were signiﬁcantly different (H : F = 2,72 7.31, p < 0.001: α: F = 7.29, p < 0.001) among 2,72 Woody plant species richness and alpha diversity land uses (Table 3). H was highest under cultivation and At the plot level, species richness differed (F = charcoal production and signiﬁcantly lower under graz- 2,72 10.7, p < 0.0001) among land uses, with charcoal pro- ing. Cumulative H followed the same trend, being similar duction and cultivation being signiﬁcantly higher than between cultivation (2.95) and charcoal production (2.93), grazing (Table 3). Cumulative species richness was also with grazing considerably lower (2.49, Figure 5a). Fisher’s Table 3. Plot-level (0.1 ha) woody plant density, and species diversity and richness (means ± SE) in a multiple-use equatorial African savanna, central Uganda. Diversity indices Land-use Number of Density types plots (plants/ha) SH Fisher’sαβ β C w T MH a a a a a Grazing 27 4152 ± 525 14 ± 1.1 1.2 ± 0.1 3.0 ± 0.3 3.1 3.1 0.37 ± 0.02 b b b b a Cultivation 24 6612 ± 665 20 ± 1.2 2.1 ± 0.1 4.1 ± 0.2 2.8 3.0 0.33 ± 0.02 b b b b a Charcoal 24 7131 ± 755 21 ± 1.1 2.0 ± 0.1 4.1 ± 0.2 2.7 2.8 0.37 ± 0.02 production Notes: Values in the same column accompanied by the same superscript do not differ signiﬁcantly (Tukey, p < 0.05). H , Shannon–Wiener index; S, species richness; β , Whittaker’s beta diversity; β , Wilson and Schmida; C , Morisita–Horn index of similarity. W T MH Number of species Number of species Number of species Number of species International Journal of Biodiversity Science, Ecosystem Services & Management 237 (a) (a) 120 3.5 Cultivation, 2.95 Overall land uses, 99 Overall land uses, 3.0 Charcoal, 2.93 2.5 Grazing, 2.49 Cultivation, 76 Charcoal, 77 1.5 Grazing, 57 0.5 20 0 0 1020304050607080 Number of individuals Number of samples (b) (b) Overall land uses, 12.06 Cultivation, 10.36 Charcoal, 10.43 Overall land uses, 99 Grazing, 7.85 Cultivation, 76 Charcoal, 77 Grazing, 57 Number of individuals Figure 5. The cumulative diversity curves plotted against num- ber of individuals for (a) Shannon–Wiener diversity index and Number of individuals (b) Fisher’s alpha diversity for the total woody plants for all land uses combined (overall), and for the grazing, cultivation Figure 4. The cumulative species richness curves for the total and charcoal production land-use types, within this multiple-use woody species based on (a) sample plots and (b) number of indi- equatorial African savanna, central Uganda. viduals for all land uses combined (overall), and for the grazing, cultivation and charcoal production land-use types, within this multiple-use equatorial African savanna, central Uganda. grazing (Table 4). The most abundant tree species with high average number of plants per plot were alpha diversity was also higher for cultivation and charcoal Combretum collinum (147 plants/plot), Capparis fascic- production, and signiﬁcantly lower for grazing (Table 3). ularis (120), Combretum molle (97), Combretum capit- The cumulative alpha diversity was again higher under uliﬂorum (82) and Combretum ghasalense (80), whereas charcoal production (10.43) and cultivation (10.36), and the most frequent were C. collinum (in 63 of 75 plots), lower under grazing (7.85, Figure 5b). The overall trend C. molle (60), C. ghasalense (59) and A. hockii (49). is that species diversity was higher in the cultivation and Acacia seyal, Commiphora africana and Commiphora charcoal production and lower in the grazing land use. The dawei were only encountered under grazing, Albizia cori- regression results showed insigniﬁcant weak correlations aria, Albizia malacophylla, Zanthoxylum chalybeum and (with r spanning 0.004–0.095; p > 0.1) between woody Erythrina abyssinica in cultivation, while Pavetta cras- species diversity (i.e. richness and alpha diversity) and the sipes, Dombeya dawei and Zanthoxylum rubescens were ‘distance of the sampling plot along the transect radiating only recorded within charcoal production areas. away from the households’ at both the whole savanna and Tree species H diversity at the plot level ranged from land-use type scales. This suggests that the distance along 0.0 to 2.6, and differed signiﬁcantly among land uses (F 2,72 the transect away from the households, the assumed source = 15.9, p < 0.0001), being higher in both cultivation and of woodland human disturbance, accounts for a very small charcoal production compared with grazing (Table 4). The fraction of the variation in woody species diversity within regression results showed insigniﬁcant weak correlations this multiple-use savanna. (with r spanning 0.001–0.079; p > 0.18) between tree species diversity (i.e. richness and alpha diversity) and the ‘distance of the sampling plot along the transect radiat- Tree species richness and alpha diversity ing away from the source of human disturbance’ at both Tree species richness differed among the land uses the whole savanna and land-use type scales. This suggests (F = 16.6, p < 0.0001), being higher under that the distance of sampling plots away from the house- 2,72 cultivation and charcoal production and lower under holds, the source of woodland disturbance, accounts for a 10,000 15,000 20,000 25,000 10,000 30,000 15,000 35,000 20,000 40,000 25,000 45,000 30,000 50,000 35,000 40,000 45,000 10,000 50,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 Number of species (S) Number of species (S) Fisher's alpha Shannon diversity index (H′) 238 V.N. Kalema and E.T.F. Witkowski Table 4. Plot-level (0.1 ha) tree and shrub species diversity and richness (means ± SE) among the different land-use types in a multiple-use equatorial African savanna, central Uganda. Species richness and diversity Tree Shrub Land-use type Number of plots SH SH a a a a Grazing 27 3.6 ± 0.3 1.0 ± 0.1 1.3 ± 0.3 0.3 ± 0.1 b b b b Cultivation 24 7.8 ± 0.7 1.7 ± 0.1 3.4 ± 0.5 0.9 ± 0.1 b b b b Charcoal production 24 7.5 ± 0.7 1.7 ± 0.1 2.7 ± 0.4 0.7 ± 0.1 Notes: Values in the same column accompanied by the same superscript do not differ signiﬁcantly (Tukey, p < 0.05). S, species richness; H , Shannon–Wiener diversity index. very small fraction (<7.9%) of the variation in tree species very high between land-use dissimilarities. The within diversity within this multiple-use savanna. land-use type similarities were low (ranging 25.3–30.5%), being highest for charcoal production (mean = 30.5%), followed by grazing (25.4%), and then cultivation (25.3%). Shrub species richness and alpha diversity Furthermore, SIMPER analysis showed relatively high Shrub species richness differed among land uses (F = 2,72 pairwise dissimilarities between land uses, ranging 8.28, p = 0.0006), being signiﬁcantly higher under cul- 73.2–81.2%. The highest mean dissimilarity was for tivation and charcoal production compared with grazing cultivation versus grazing (81.2%), followed by charcoal (Table 3). Overall, the most abundantly shared shrub versus grazing (76.7%) and lowest for charcoal versus species among land uses were Harrisonia abyssinica cultivation (73.2%). These results are corroborated by (26 plants/plot), Rhus natalensis (21), L. camara (20) and lower similarity percentages within land uses. Annona senegalensis (18). The most frequent shrubs were Indeed, SIMPER showed that the number of species R. natalensis (in 68 of 75 plots), H. abyssinica (65), making up 90% of the observed similarity per land use Grewia mollis (53), Gardenia ternifolia (46) and A. sene- was 12 for both cultivation and charcoal production and galensis (43). Clerodendrum cordifolia, Flueggea virosa, 9 for grazing (Appendix 3, Figure 6). The top two species Microglossa pyrifolia and Phyllanthus ovalifolius were contributing most to the percentage similarity in commu- recorded only in the grazing areas. Shrub H diversity nity species composition within cultivation and charcoal ranged from 0.0 to 2.0, and differed among land uses (F 2,72 production were C. collinum and C. molle. However, for = 7.08, p = 0.002), being signiﬁcantly higher for cultiva- grazing, the second species was Piliostigma thonningii tion and charcoal production relative to grazing (Table 4). (Appendix 3). SIMPER analysis indicated that 24 species The regression results showed insigniﬁcant weak correla- between charcoal production and cultivation, 22 species tions (with r spanning 0.002–0.141; p > 0.18) between between charcoal and grazing and 23 species between cul- shrub species diversity (i.e. richness and alpha diversity) tivation and grazing contributed most to the dissimilarity and the ‘distance of the plot along the transect radiating between land uses, reﬂecting the overall differences in away from the households’, the assumed source of human community composition (Appendix 3). disturbance at both the whole savanna and land-use type scales. This suggests that the distance of sampling plots Grazing away from the human sources of woodland disturbance Cultivation accounts for a very small fraction (<14.1%) of the vari- Charcoal ation in shrub species diversity within this multiple-use 80 savanna. Beta diversity Plot-level pairwise Morisita–Horn (C ) ranged MH 0–0.979 under grazing, 0.005–0.972 for charcoal production and 0.001–0.961 under cultivation. C MH tended to differ (F = 2.43, p = 0.09) between land 2,900 uses, with charcoal production and grazing being higher than cultivation. β and β were highest under grazing, 123456789 10 11 12 W T Number of species followed by cultivation and lowest for charcoal production (Table 3). Hence, the β , β and C values show an W T MH Figure 6. Cumulative percentage contribution to overall overall higher beta diversity for the grazing land use similarity from ANOSIM within the three land-use types in compared with others. These results are corroborated by relation to the number of species contributing to at least 90% the very low within land-use SIMPER similarities, and similarity in savanna woodland of Nakasongola, central Uganda. Cumulative similarity (%) International Journal of Biodiversity Science, Ecosystem Services & Management 239 Discussion consequences for plant community development (Hanley 1998). Community composition and structure Anthropogenic factors (charcoal production and shift- Generally, C. collinum, C. fascicularis, C. molle, C. capit- ing cultivation) have similarly been reported to be causative uliﬂorum, C. ghasalense, G. mollis and A. hockii were the agents of degradation in the central Ethiopian highlands most abundant and frequent species across all land uses. (Yirdaw and Luukkanen 2003). However, in this study, the This agrees with Nangendo et al. (2006) that C. molle, differences among land uses may be the result of the extent G. mollis, A. senegalensis and Grewia bicolor are com- (intensity and frequency) and duration of anthropogenic monly found in burned areas and in open savanna wood- disturbances and particular land-use practices taking place lands in Uganda. Fires are common in these multiple-use in a given area. Changes in land-use practice may result savannas, and ﬁre is used as a management tool in both in continuously or more abruptly deteriorating environ- subsistence crop cultivation and livestock grazing. About mental conditions for some plant species, causing their 20–50% of the grazing areas in the studied multiple-use decline in abundance and distribution. The chopping down savannas are burned towards the end of the two dry sea- of trees for charcoal production on a relatively short rota- sons before the onset of rainfall (in February and again tion has clearly resulted in local species loss. Some of the in July) to allow fresh pastures and kill ticks. Similarly, highly utilized species for charcoal production, ﬁrewood Morris (1995) observed that people in the miombo wood- and poles for fences and houses are A. hockii, A. polyacan- lands of Malawi burn the bush for preparing their gardens tha, A. seyal, Acacia sieberiana, A. coriaria, Albizia zygia, for planting, hunting and calling the rains. Since ﬁres occur C. capituliﬂorum, C. collinum, C. ghasalense, C. molle, at more than one time of the year, some speciﬁc patches of G. mollis, Hymenocardia acida, Maytenus senegalensis, land may be burnt more than once in a year. These numer- P. thonningii, Terminalia glaucescens and Vepris nobilis ous ﬁres result in relatively low ﬁre intensities because fuel (Namaalwa et al. 2005; Kalema 2010). However, the most does not accumulate to any large extent, and maintains adversely affected species that were decreasing in abun- much of the woodlands as a shrub transition. Fire is indeed dance (Kalema 2010) are Albizia spp. and Terminalia spp. an important factor for the maintenance of African savanna This is probably because they are highly preferred for ecosystems (Bond and Van Wilgen 1996). poles, timber and charcoal production, and perhaps also Over the last 30 years the woodland cover of due to their relatively poor regenerative capacities (few Nakasongala District has decreased and is now mostly open resprouting stumps and relatively low recruitment; Kalema woodland in transition to thicket/shrubland, while areas 2010). under cultivation and settlements have increased (Kalema 2010), mirroring patterns seen in other African savannas Species richness (Luoga et al. 2005; Mwavu and Witkowski 2008b; Coetzer et al. 2010). Total woody plant species richness differed signiﬁcantly The high density and number of Acacia spp. are among land uses with charcoal production and cultivation probably facilitated by seed dispersal by ruminants such being higher than grazing. Differences in species rich- as the abundant cattle that graze in this multiple-use ness between land uses may be the result of the different savanna. Certain Acacia spp. also form persistent seed land use practices per se, or because of differences in banks (Witkowski and Garner 2000), with animal faeces the number of individuals counted (Gotelli and Colwell also providing favourable germination beds (Schultka and 2001). Charcoal production and cultivation were equally Cornelius 1997). Seasonal bush burning may be a contribu- well sampled (24 plots each) and had an almost equal num- tory factor to the high abundances of acacias in the studied ber of species (77 vs. 76), while grazing with 27 plots savanna, since their germination is generally enhanced had only 57 species. However, the grazing lands include when subjected to the heat of ﬁre (Mbalo and Witkowski some hydromorphic grasslands, which typically have lower 1997; Teketay 1997). tree densities. Woody species richness in a Tanzanian Some of the species encountered were restricted to par- miombo woodland also differed between shifting cultiva- ticular land-use types, suggesting the inﬂuence of land-use tion and more permanently cultivated areas (Luoga et al. practices in the distribution of woody plants. For example, 2005). The patchwork in the landscape after abandonment the higher abundances of P. thonningii and A. seyal in the of the land provides opportunities for different functional livestock grazing areas may be attributed to them not being groups of species without the disappearance of the original palatable or preferred species by mammalian herbivores species (Luoga et al. 2004). Indeed, richness and diver- (Anderson et al. 2007), high resprouting ability and animal sity may increase with increasing heterogeneity within a seed dispersal. On the other hand, the presence of Acacia range of patch sizes (Cabral et al. 2003). However, the mellifera, H. abyssinica, L. camara, R. natalensis and ever-expanding shifting cultivation, leading to fragmenta- Carissa edulis, which are encroacher species in disturbed tion of the remaining natural habitats may result in local vegetation is not surprising (Van Vegten 1983). These extinction of small, isolated populations (Tilman et al. species are neither browsed by herbivores nor harvested 2002). Thus, shifting cultivation can play either a posi- for charcoal production. Indeed, selective predation of tive or a negative role, depending on how it is managed. preferred seedling species by herbivores has far-reaching Variation in species richness between land uses may also be 240 V.N. Kalema and E.T.F. Witkowski explained by a variety of other factors that include habitat herbivory and extent of bush ﬁres than in the other land quality, spatio-temporal dynamics, boundary characteris- uses. Both ﬁres and herbivory may inhibit establishment of tics and neighbourhood effects (e.g. Waldhardt and Otte seedlings and recruitment of saplings (Helm et al. 2011), 2003). consequently affecting the population structure and regen- The overall sampled woody species richness of eration status of the species. Tree density at a site may Nakasongola (99 species, 31 families within 75 plots change rapidly with changes in the frequency or intensity with an area of 0.1 ha) is lower than the forest– of herbivory and ﬁre (Bond and van Wilgen 1996). Such woodland–savanna mosaic of northern Budongo Forest changes can be extensive, inﬂuencing vegetation dynamics Reserve, north-west Uganda (121 species, 38 families at the landscape scale (Sinclair and Arcese 1995). In some within 594 plots with an area of 0.05 ha; Nangendo et al. places at Nakasongola where livestock grazing and termite 2006). Although both occur within the same ecological damage were heavy, bare patches were common. zone, the latter is a reserve, where human disturbances are Compared with other African savannas, H diversity restricted. Species richness of Nakasongola is also lower (0.41–2.64) in Nakasongola tended to be higher than south- than the woodlands of Katavi–Rukwa ecosystem in western ern Malawian miombo woodlands (0.55–1.26; Mwase et al. Tanzania (229 species, 45 families within 50 plots with an 2007), but lower than the Kitulangalo miombo woodland area of 0.1 ha; Banda et al. 2008), the Kitulangalo Forest of Tanzania (2.9–3.13; Malimbwi et al. 1994) and South Reserve and surrounding communal lands of Tanzania African communal savannas (2.5–3.9; Dovie et al. 2008). (133 species, 31 families within 64 plots with an area of 0.1 ha; Luoga et al. 2000b) and communal savanna Beta diversity woodlands in three South African provinces (135 species, 42 families within 90 plots with an area of 0.1 ha; Dovie In spite of the low alpha diversity, the multiple-use savan- et al. 2008). These comparisons suggest loss of species nas of Nakasongola have relatively high beta diversity. The from Nakasongola through habitat degradation. The rich- relatively high values for all the beta diversity indices and ness of only 2–31 species per 0.1 ha in Nakasongola is low low similarities between plots and land-use types are indi- relative to those reported elsewhere. However, it is similar cators of gradients in the species composition of these to 1–28 species per 0.1 ha plot in the woodlands of western savanna woodlands. The general absence of signiﬁcant dif- Tanzania (Banda et al. 2008). ferences in species composition between the charcoal pro- duction and cultivated areas also suggests the inﬂuence of an environmental gradient rather than differences between Alpha diversity the two land-use types. The lack of differences is probably Woody plant alpha diversity (H and Fisher’s) did not gen- due to the cyclic sequence of land use over time. The high erally increase with increasing distance along the transect contribution of C. collinum, C. molle and C. ghasalense to away from households, the assumed source of disturbance. the similarity in species composition among plots under the Indeed, regression analyses revealed that the distance of charcoal production land use, despite them being the most sampling plots away from households, the assumed source utilized species for charcoal production, shows their ability of human disturbance, to woodlands accounted for a very to recover from disturbance and to occupy a wide variety small fraction (<14.2%) of the variation in woody species of habitats. These results generally point to inﬂuence of an diversity within this multiple-use savanna. This suggests environmental gradient, in addition to anthropogenic dis- that there is no clear gradient of increasing resource avail- turbance, in the variation of species composition within ability or decreasing human disturbance with increasing this multiple-use savanna. Species composition and dis- distance from homesteads or villages. Indeed, charcoal tribution of plant communities are shaped not only by burning, a major source of disturbance to woody species, anthropogenic disturbances but also by environmental con- is not inﬂuenced by the distances from homesteads or vil- ditions, spatial factors and species competition (Cousins lages in this region, but rather the availability of suitable and Eriksson 2002). Among these is below ground avail- and sizeable woody individuals for charcoal production. ability of soil nutrients that plays an important role in the However, woody plant alpha diversity was signiﬁcantly assembly of tropical tree communities at local scales (John higher under cultivation and charcoal compared with graz- et al. 2007). Other broader scale studies have illustrated ing. Similarly, cumulative Fisher’s alpha was higher under how historical or climatic factors may also act to constrain charcoal and cultivation than under grazing. These results diversity (e.g. Kleidon and Mooney 2000; Sarr et al. 2005). suggest that species composition and distribution of plant Within these savannas, natural and anthropogenic dis- communities in this savanna are to a great extent shaped turbances from subsistence harvesting of poles and com- by anthropogenic disturbances. On the other hand, these mercial charcoal production are scattered in space and results are consistent with Hayek and Buzas’ (1997) sug- time, contributing to habitat heterogeneity. This habi- gestion that the more species that are present, and the tat heterogeneity may favour the coexistence of species more evenly the individuals are spread across the species, with different ecological requirements, thus contributing the higher the resulting H . Fisher’s alpha is low when to the maintenance of community diversity (Mwavu and the number of species is low. The low species diversity Witkowski 2009) and variation in species composition in the grazing lands may be a consequence of greater among the plots along a transect. Anthropogenic land-use International Journal of Biodiversity Science, Ecosystem Services & Management 241 change is one of the most important factors contributing to that supply fuelwood to East African urban areas. Together global change (Sala et al. 2000), and changes in landscape with this understanding of diversity patterns in relation to structure and agricultural land-use intensity are likely to anthropogenic factors in the woodlands, a detailed study of inﬂuence plant community composition and similarity. The the inﬂuence of other environmental factors, particularly studied multiple-use savanna is characterized by anthro- topo-edaphic variability, would provide a more complete pogenic disturbances which have been patchy and have understanding of species distribution patterns. different inﬂuences on community species composition. Such intrinsic disturbances may lead to abrupt changes in Acknowledgements habitat, consequently greatly contributing to heterogeneity This study was ﬁnancially supported by the Third World in this savanna environment and result in reversal or delay Organization for Women in Science (TWOWS), the South of successional states. The high beta diversity under graz- African National Research Foundation (NRF 2069152), the Andrew Mellon Postgraduate Mentorship Award and the Post ing compared with other land uses in this savanna may be Graduate Merit Award from the University of the Witwatersrand, attributed to the more heterogeneous spatial distribution, Johannesburg. We thank Vivienne Williams for guidance with the and varying levels and intensities of grazing (stocking rates EstimateS analyses. We thank Edward Mwavu for valuable com- between villages) that contribute to greater environmen- ments on the manuscript. We thank Nyesiga Grace, Lunkuraite tal heterogeneity. Livestock grazing impacts are typically Alex, Mukasa Ivan and Sembatya Tadeo for their assistance with ﬁeld data collection, our driver Robert, the District Resource, not uniform across a landscape because herbivores are Environment and Livestock Ofﬁcers in Nakasongola, all chiefs highly selective of areas with higher soil fertility (soil of subcounties and all those in one way or another who helped to type), new grass growth from burnt areas and particular make this study a success. landscape positions (Senft et al. 1987; O’Connor et al. 2011). Abrupt changes in site conditions that are accom- panied by changes in the physical and chemical nature References of soil nutrient dynamics and microclimate may inﬂuence Anderson TM, Ritchie ME, Mc Naughton SJ. 2007. Rainfall and soils modify plant community response to grazing in plant community composition and species diversity pat- Serengeti National Park. 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The impact of land conversion on plant biodiversity analysis of beta-diversity across organisms and environments. in the forest zone of Cameroon. Biodivers Conserv. Ecology. 88(11):2830–2838. 11(11):2047–2061. 244 V.N. Kalema and E.T.F. Witkowski Appendix 1. Species list arranged alphabetically by families for woody plants recorded in 75 plots (0.1 ha) within the savanna woodland of Nakasongola District, central Uganda. Frequency Families Species Number of individuals within plots Acanthaceae Acanthus sp. L. 4 1 Anacardiaceae Lannea barteri Engl 397 21 Lannea schweinfurthii Engl 4 1 Oncoba spinosa Forssk 1 1 Ozoroa insignis Delile 42 3 Rhus natalensis Bernh. ex Krauss 1445 68 Rhus vulgaris Meikle 232 26 Annonaceae Annona senegalensis Pers 791 43 Monanthotaxis ferruginea (Oliv.) Verdc 2 2 Apocynaceae Alstonia boonei De Wild 34 12 Carissa edulis Vahl 219 32 Araliaceae Cussonia arborea Hochst. ex A. Rich 17 4 Asteraceae Microglossa pyrifolia Kuntze 1 1 Bignonaceae Kigelia africana (Lam.) Benth. 76 15 Markhamia lutea K. Schum. 15 3 Stereospermum kunthianum Cham. 105 16 Burseraceae Commiphora africana (A. Rich) Engl 45 10 Commiphora dalzielii Hutch. 50 2 Caesalpiniaceae Piliostigma thonningii (Schumach.) Milne-Redh. 2275 43 Senna siamea (Lamarck) H.S. Irwin & Barneby 62 Capparidaceae Capparis fascicularis DC. 361 3 Crateva adansonii DC. 4 1 Maerua triphylla A. Rich. 2 2 Celastraceae Mystroxylon aethiopicum (Thunb.) Loes. 11 2 Maytenus senegalensis (Lam) Exell 418 30 Combretaceae Combretum capituliﬂorum Fenzl ex Schweinf. 1801 22 Combretum collinum Fresen 9241 63 Combretum ghasalense Engl. & Diels 4725 59 Combretum molle Engl. & Diels 5814 60 Terminalia glaucescens Planch. ex Benth. 521 32 Ebenaceae Euclea latidens Stapf 252 31 Euphorbiaceae Bridelia scleroneura Müll. Arg. 87 12 Euphorbia candelabrum Tremaut ex Kotschy 29 11 Flueggea virosa (Willd.) Voigt 1 1 Hymenocardia acida Tul. 2191 40 Phyllanthus ovalifolius Forssk. 3 1 Securinega sp. Comm. Ex Juss. 1 1 Securinega virosa (Roxb. ex Willd) Baill. 62 15 Hypericaceae Psorospermum febrifugum Spach 1 1 Lamiaceae Clerodendrum cordifolium A. Rich. 1 1 Vitex doniana Sweet 365 7 Vitex ferruginea Schumach. & Thonn. 510 21 Vitex ﬁscheri Gürke 26 2 Loganiaceae Strychnos innocua Delile 455 30 Meliaceae Ekebergia capensis Sparrm. 33 3 Pseudocedrela kotschyi Harms 186 16 Trichilia dregeana Harv. & Sond. 1 1 Trichilia emetica Vahl 2 2 Mimosaceae Acacia hamulosa Benth. 74 15 Acacia hockii De Wild. 1708 49 Acacia malacocephala Harms 7 2 Acacia mellifera Benth. 2 1 Acacia polyacantha Willd. 894 47 Acacia senegal Willd. 113 8 Acacia seyal Delile 139 4 Acacia sieberiana DC. 384 36 Albizia coriaria Welw. 106 14 Albizia malacophylla Walp. 64 7 Albizia zygia J.F. Macbr. 1738 38 Calliandra sp. Benth. 32 2 Dichrostachys glomerata Chiov. 179 15 (Continued) International Journal of Biodiversity Science, Ecosystem Services & Management 245 Appendix 1. (Continued). Frequency Families Species Number of individuals within plots Moraceae Antiaris toxicaria Lesch 62 10 Artocarpus heterophyllus Lam. 21 Ficus dicranostyla Mildbr. 1 1 Ficus natalensis Hochst. 29 8 Ficus ovata Vahl 1 1 Ficus sp. L. 33 2 Milicia excelsa (Welw.) C.C. Berg 91 5 Olaceae Ximenia aegyptiaca L. 4 1 Ximenia americanaL9 2 Papilionaceae Erythrina abyssinica Lam. 6 3 Lonchocarpus laxiﬂorus Guill. & Perr. 3 2 Rhamnaceae Ziziphus mauritiana Lam. 56 3 Rubiaceae Canthium vulgare (K. Schum.) Bullock 2 1 Gardenia ternifolia Schumach. & Thonn. 380 46 Pavetta crassipes K. Schum. 22 4 Pavetta gardeniifolia Hochst. ex A. Rich 56 4 Pavetta insignis Bremek. 6 1 Tricalysia bagshawei S. Moore 4 2 Tricalysia niamniamensis Schweinf. ex. Hiern 1 1 Vangueria apiculata K. Schum. 23 3 Vangueria tomentosa Hochst. 18 1 Rutaceae Vepris nobilis (Delile) W. Mziray 1320 24 Zanthoxylum chalybeum Engl. 88 9 Zanthoxylum rubescens Planch. Ex Hook. 33 5 Sapindaceae Allophylus abyssinicus Radlk. 1 1 Allophylus africanus P. Beauv. 137 23 Sapotaceae Manilkara dawei (Stapf) Chiov. 140 16 Pouteria sp. Aubl. 11 Simaroubaceae Balanites aegyptiacus Delile 17 4 Harrisonia abyssinica Oliv. 1675 65 Sterculiaceae Dombeya dawei Sprague 40 2 Tiliaceae Grewia mollis Juss. 1142 53 Grewia trichocarpa Hochst. ex A. Rich 4 2 Trema guineense (Schumach. & Thonn.) Ficalho 74 11 Umbelliferae Steganotaenia araliacea Hochst. 12 4 Verbenaceae Lantana camara L. 368 18 Unidentiﬁed Enseka 24 2 Kiondo 51 Notes: The total number of individuals and frequencies within plots (number of times present within the 75 plots) are included. Introduced species. Near threatened. Introduced and invasive alien. Local vernacular name. 246 V.N. Kalema and E.T.F. Witkowski Appendix 2. Contribution of individual species to the overall similarity within land-use types (grazing, cultivation and charcoal production). Mean Mean Percentage Cumulative Species abundance similarity contribution percentage Charcoal (mean similarity = 30.5) Combretum collinum 129.9 7.4 24.1 24.1 Combretum molle 104.8 4.8 15.9 40 Combretum ghasalense 70.2 4.7 15.4 55.4 Rhus natalensis 30.2 3.2 10.4 65.8 Hymenocardia acida 43 1.8 6 71.8 Harrisonia abyssinica 23.3 1.6 5.3 77.1 Combretum capituliﬂorum 50.6 0.9 2.8 79.9 Grewia mollis 19.5 0.8 2.7 82.6 Annona senegalensis 15.4 0.7 2.2 84.8 Acacia hockii 21.7 0.7 2.2 87.1 Albizia zygia 13.5 0.6 1.9 89 Vepris nobilis 47.2 0.5 1.6 90.6 Cultivation (mean similarity = 25.3) Combretum collinum 135.7 6.5 25.6 25.6 Combretum molle 102.5 4.2 16.5 42.1 Albizia zygia 58.5 2.6 10.2 52.4 Acacia hockii 42.5 2.2 8.5 60.9 Harrisonia abyssinica 33.4 1.9 7.6 68.5 Combretum ghasalense 31.4 1.5 5.8 74.3 Rhus natalensis 17.7 1.2 4.8 79.1 Grewia mollis 21.3 1.1 4.2 83.4 Acacia polyacantha 20.3 0.6 2.5 85.9 Hymenocardia acida 28.2 0.5 1.9 87.8 Strychnos innocua 14.1 0.4 1.8 89.6 Combretum capituliﬂorum 23.6 0.4 1.5 91 Grazing (mean similarity = 25.4) Combretum collinum 106.2 7.3 28.7 28.7 Piliostigma thonningii 64.4 7 27.7 56.3 Combretum ghasalense 84.7 4.5 17.6 74 Combretum molle 31.1 1.8 7 81 Rhus natalensis 11 0.8 3.3 84.3 Harrisonia abyssinica 11.7 0.6 2.2 86.5 Acacia polyacantha 5.8 0.5 1.8 88.3 Hymenocardia acida 17.9 0.4 1.7 90 Gardenia ternifolia 6.6 0.4 1.6 91.5 Note: Species are ranked according to their percentage contribution to the similarity within each land use. Appendix 3. Results of SIMPER analysis highlighting the species contributing most to the dissimilarity between land-use types. Mean Mean Mean Percentage Cumulative a b Species abundance abundance dissimilarity contribution percentage Charcoal and cultivation (mean dissimilarity = 73.2) Combretum collinum 129.9 135.7 11.5 15.8 15.8 Combretum molle 104.8 102.5 9 12.3 28 Combretum ghasalense 70.2 31.4 5.8 8 36 Hymenocardia acida 43 28.2 4.3 5.9 41.9 Combretum capituliﬂorum 50.6 23.6 4 5.5 47.4 Acacia hockii 21.7 42.5 3.9 5.4 52.8 Albizia zygia 13.5 58.5 3.7 5 57.8 Vepris nobilis 47.2 7.8 3.2 4.4 62.2 Harrisonia abyssinica 23.3 33.4 2.4 3.3 65.5 Acacia polyacantha 10.5 20.3 2.3 3.1 68.6 Rhus natalensis 30.2 17.7 2.2 3 71.6 Grewia mollis 19.5 21.3 2 2.7 74.3 Annona senegalensis 15.4 10.9 1.7 2.4 76.7 Piliostigma thonningii 17.3 5 1.6 2.2 78.9 (Continued) International Journal of Biodiversity Science, Ecosystem Services & Management 247 Appendix 3. (Continued). Mean Mean Mean Percentage Cumulative a b Species abundance abundance dissimilarity contribution percentage Vitex doniana 0 15.2 1.3 1.8 80.6 Strychnos innocua 3.9 14.1 1.1 1.5 82.2 Vitex ferruginea 11 9.3 1.1 1.5 83.7 Terminalia glaucescens 8.9 6.5 0.9 1.3 84.9 Lannea barteri 12.5 2 0.9 1.2 86.1 Capparis fascicularis 15 0 0.8 1.1 87.2 Lantana camara 1.1 9.8 0.8 1 88.2 Acacia sieberiana 7.7 3.7 0.7 1 89.2 Dichrostachy glomerata 0.4 5.3 0.5 0.7 89.9 Carissa edulis 3.3 4.3 0.5 0.6 90.6 Charcoal and grazing (mean dissimilarity = 76.7) Combretum collinum 129.9 106.2 12.6 16.4 16.4 Combretum ghasalense 70.2 84.7 9.5 12.4 28.8 Combretum molle 104.8 31.1 8.1 10.6 39.4 Piliostigma thonningii 17.3 64.4 6.2 8.1 47.5 Hymenocardia acida 43 17.9 4.9 6.4 53.9 Combretum capituliﬂorum 50.6 0.7 3.6 4.7 58.7 Vepris nobilis 47.2 0 3.3 4.3 63 Rhus natalensis 30.2 11 3.1 4 67 Acacia hockii 21.7 6.2 2.3 3 70 Harrisonia abyssinica 23.3 11.7 2.2 2.9 73 Annona senegalensis 15.4 5.9 1.9 2.5 75.4 Grewia mollis 19.5 6.1 1.8 2.4 77.8 Acacia polyacantha 10.5 5.8 1.4 1.8 79.6 Albizia zygia 13.5 0.3 1.4 1.8 81.4 Maytenus senegalensis 4.6 9.6 1.1 1.4 82.8 Terminalia glaucescens 8.9 5.6 1 1.4 84.1 Lannea barteri 12.5 1.8 1 1.3 85.4 Acacia sieberiana 7.7 4.1 0.9 1.2 86.6 Vitex ferruginea 11 0.9 0.9 1.2 87.8 Capparis fascicularis 15 0 0.9 1.2 88.9 Acacia seyal 0 5.1 0.8 1 89.9 Gardenia ternifolia 5 6.6 0.8 1 91 Cultivation and grazing (mean dissimilarity = 81.2) Combretum collinum 135.7 106.2 14.3 17.6 17.6 Combretum molle 102.5 31.1 8.3 10.2 27.8 Combretum ghasalense 31.4 84.7 8 9.8 37.6 Piliostigma thonningii 5 64.4 6.6 8.2 45.8 Albizia zygia 58.5 0.3 4.7 5.8 51.6 Acacia hockii 42.5 6.2 4.6 5.7 57.2 Hymenocardia acida 28.2 17.9 3.4 4.1 61.4 Harrisonia abyssinica 33.4 11.7 3.1 3.8 65.1 Acacia polyacantha 20.3 5.8 2.6 3.2 68.4 Grewia mollis 21.3 6.1 2.1 2.6 71 Combretum capituliﬂorum 23.6 0.7 1.9 2.4 73.3 Rhus natalensis 17.7 11 1.8 2.2 75.6 Vitex doniana 15.2 0 1.7 2.1 77.7 Annona senegalensis 10.9 5.9 1.5 1.8 79.5 Strychnos innocua 14.1 0.9 1.3 1.6 81.2 Lantana camara 9.8 3.9 1.2 1.5 82.7 Acacia seyal 0 5.1 1 1.2 83.9 Maytenus senegalensis 2.1 9.6 1 1.2 85.1 Terminalia glaucescens 6.5 5.6 1 1.2 86.3 Gardenia ternifolia 3.4 6.6 0.8 1 87.3 Vepris nobilis 7.8 0 0.8 1 88.3 Dichrostachys glomerata 5.3 1.5 0.8 0.9 89.3 Vitex ferruginea 9.3 0.9 0.7 0.9 90.2 Notes: Species are ranked according to their percentage contribution to the dissimilarity between land-use types and only those with >2% contribution are shown. Dissimilarity and percentage cumulative dissimilarity are also given. a b Mean abundance for ﬁrst member of the pair. Mean abundance for second member of the pair.

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International Journal of Biodiversity Science, Ecosystem Services & Management – Taylor & Francis

Published: Sep 1, 2012

Keywords: ANOSIM; anthropogenic disturbance; cultivation; grazing; land degradation; species richness; sustainable land management

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Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

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Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

Land-use impacts on woody plant density and diversity in an African savanna charcoal production region

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