Comparative analysis of floristic richness and diversity in six central forest reserves of north eastern Uganda

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As such, this study aimed to; (i) determine the floristic richness and diversity in six central forest reserves of north eastern Uganda and (ii) evaluate the similarity and complementarity of floristic composition. Data was collected from nested quadrats (20 x 20 m for trees, 10 x 10 m for shrubs and 5 x 5 m for herbaceous climbers, forbs and grasses) placed at intervals of 100 m along a transect of 1000–1500 m. Species richness, diversity and evenness were determined for each forest reserve. Binary similarity coefficients were computed because only presence/absence data of plant species was recorded. A sum of 417 plant species in 76 families were recorded representing 8.7% of known vascular plants reported in Uganda. All the CFRs had high diversity indices ranging from 4.2 in Kano CFR to 4.47 in Bululu hill CFR. In terms of floristic similarity, the CFRs clustered into two groups namely Onyurut and Ogera hills cluster and Akur, Kano, Bululu hills and Mount Moroto cluster. The CFRs complement one another by supporting plant species not recorded elsewhere. Notably, three CFRs (Bululu hills, Mount Moroto and Onyurut) account for 81.53% of the plant taxa. Addition of the fourth (Ogera hills) accommodates nearly 90% of the species and the fifth (Akur CFR) accounts for more than 95% of the species. The highest threat level on taxa in these CFRs is Vulnerable (4 species) and Near Threatened (4 species) with 137 Least Concern and 270 Not Evaluated. The CFRs in NE Uganda have richness and floristic diversity with up to 8.7% of the known plants in Uganda present. The two similarity clusters depict variation in altitudinal, proximity and climatic conditions. Five CFRs are required to conserve 95% of the species recorded. There is need to assess the population of the threatened species, and investigate the edaphic factors which influence plant distribution. Floristic richness and diversity similarity complementarity central forest reserves north eastern Uganda Figures Figure 1 Figure 2 Figure 3 1.0 Introduction As 2 in 5 (or 39%) of the world’s vascular plant species are threatened with extinction (Nic Lughadha et al. 2020 ), understanding the patterns of distribution (Sosef et al. 2017 ), and identification of areas with a high value for biodiversity protection is paramount (Haq et al. 2023 ). The warm mixed forest, savannahs, shrub, tropical forest, and tropical woodlands are projected to lose the most species (van Vuuren et al. 2006 ) mainly due to anthropogenic activities which endanger the ecosystems (Malhi et al. 2014 ). These activities include habitat loss, introduction of alien species, direct exploitation, climate change and pollution (Hilton-Taylor 2000 , Sala et al. 2000 ). Biodiversity is crucial for ecosystem functioning and human well-being (van Vuuren et al. 2006 ) as nearly 1.5 billion people globally directly depend on tropical forests for food, timber, medicines, and other important ecosystem functions and services (Lewis et al. 2015 ). The recognition of this importance is manifested in the international commitments such as the Convention on Biodiversity (CBD), associated Aichi Biodiversity Targets to halt its decline have been put in place (CBD 2012) and the Kumming-Montreal global biodiversity framework (Joly 2022 ). Notably, there is growing interest among scientists, policy makers, land managers, and the general public to understand the patterns and causes of biodiversity loss across space and time (Vellend et al. 2017 ). The origin of this interest is twofold; first the desire to conserve biodiversity and secondly; the potential for biodiversity changes to have an impact on the benefits that people derive from nature (MEA 2005). The most popular methods for reporting floristic information include species accumulation curves, rarefaction curves and the Shannon–Wiener indices (alpha diversity) and Sørensen, Jaccard or Bray–Curtis indices (beta diversity) (Moreno et al. 2018 ). In terms of comparing the species composition (biodiversity) of two or more assemblages, the similarity (or overlap) or dissimilarity (complementarity, turnover, beta diversity or distance) indices are often used (Magurran 2004 ). These indices are classified into two categories namely; binary similarity coefficients when only presence/absence data are available and quantitative similarity coefficients when some measure of relative abundance is available (Chao et al. 2006 ). The other important components of floristic assessment include species richness and diversity (Pullaiah et al. 2015 ), population structure and distribution (Okia 2010 , Byakagaba et al. 2011 ). The scarcity of this critical information explains why plants are usually not well represented in either global or national conservation planning schemes (Corlett 2016 ). Most often, plant conservation efforts are hampered by lack of suitable data for prioritising conservation actions. Information on the rarest and most threatened plants and habitats, is often diffuse and difficult to access or is outdated (Darbyshire et al. 2017 ). Floristic composition and its distribution remains scarcely known in the species-rich tropical Africa (Sosef et al. 2017 ). In the case of Uganda, the available floristic data in most sites comprises of plant lists for trees and shrubs which were recorded by the Forest Department in 1990’s as indicator taxa (Davenport et al. 1996). In savannah forest reserves (such as Ogera hills, Bululu and Onyurut investigated in this study), there is no record of botanical surveys carried out. In view of this situation, the study sought to (1) to determine the botanical richness and diversity in the six central forest reserves of north eastern Uganda and (ii) to evaluate the similarity and complementarity of these reserves for the conservation of plants. In achieving these objectives, the study presents floristic diversity within communities (alpha diversity) and between communities or the degree of community differentiation (beta diversity) (Whittaker 1960 ). This information will guide resource managers to prioritize conservation strategies since sites with exceptional or poor diversity (Pullaiah et al. 2015 ) are known. Additionally, it can aid in the evaluation of the relative importance of environmental and spatial drivers in shaping species assemblages (Valli et al. 2019 ). 2.0 Materials and methods 2.1 Study area The study was conducted in six CFRs located in north eastern Uganda (Fig. 1 ) in the western range of the Somali-Masai Regional Centre of Endemism (White 1983 , Eustace et al. 2021 ). This region has been poorly surveyed due to prolonged insecurity caused by the armed cattle rustlers (Kalema 2005). Indeed, two CFRs namely Mt. Napak and Mt. Kadam were omitted during floristic surveys due to reports of insecurity. With the exception of Onyurut, all the forest reserves studied are located on either hills or mountains. Onyurut is a small CFR covering 158 ha in Katakwi district. Its vegetation is predominantly woodland savannah with species such as Combretum adenogonium, C. molle, Acacia brevispica and Zanthoxylum leprieurii with patches of grassland dominated by Brachiarria decumbens, Hyparrhenia filipenduda and Hyparrhenia dissoluta. The CFR is encroached by adjacent communities majorly for farming and settlement, brick making, charcoal production, and cattle grazing. It serves as a water catchment area for Lake Bisina. Mount Moroto covers an area of 483 km 2 (Davenport et al. 1996). It is a dormant volcano with an altitudinal range of 960–3084 m. The reserve is perched on the top of the escarpment of the Eastern Rift, directly behind and to the east of the town of Moroto, and its eastern boundaries are also those of the Ugandan border with Kenya. Much of the site is dominated by Afromontane undifferentiated forest, a drier montane forest type characterised by valuable timber trees Podocarpus milanjianus , Afrocarpus (Podocarpus) gracilior , and Juniperus procera (Langdale-Brown et al. 1964 ; Davenport et al. 1996). The mean annual rainfall is 887 mm with the peak period between April to August. Significant areas of the reserve, particularly at lower altitudes in the north and south, have been transformed by farming of crops. Kano CFR is located in Labwor hills in the present day Abim district and covers an area of 8,293 ha. It is a key site for biodiversity conservation, hill reserve, and protects River Amal which serves the communities of Kano and Abim parishes (National Forestry Authority 2008 ). This reserve is faced with various human activities such as collection of Non Timber Forest Products (NTFPs) like Oxytenanthera abyssinica (bamboo), wild edible fruits and vegetables; stone quarrying, charcoal production and firewood collection, bush burning, human settlement and cultivation, illegal timber harvesting, and collection of construction materials. Akur CFR covers an area of 6,434 ha. within the Labwor hills of Abim district. It is a critical site for biodiversity conservation, hill reserve and River Ojulu originates from it (National Forestry Authority 2008 ). In Akur CFR, the hills are not sufficiently high (1200 m above sea level) to cause much differentiation of the vegetation on account of increasing altitude (National Forestry Authority 2008 ). The most important factor limiting the vegetation is most probably soil depth and its associated character of soil moisture (National Forestry Authority 2008 ). The thickest tree growth is found on the deep alluvial soils along the lines of the valleys near the hills; further from the hills, the riparian forest thins out into grass ‘vlei’ with scattered trees. Higher up on the hills, there is usually less soil and the strips of riverine forest are correspondingly narrow, but larger trees occur in the open savanna than on the lower slopes. Ogera hills CFR covers an area of 427 ha and an altitudinal range of 1036–1160 m (National Forestry Authority, 2012). Its vegetation is mainly comprised of high grass and low tree bushes. The trees are mainly combretaceous and are sometimes stunted in form with species such as Combretum molle, C. collinum, C. adenogonium and the grass Loudetia arundinceum mostly on hill slopes. In some parts, tree growth is dense with a tangle of creepers and bushes while some areas with illegal activities like charcoal burning have low tree cover. It serves as a water catchment area of Lake Kyoga in the south. Bululu hills CFR covers an area of 425 ha and is separated from Ogera hills CFR by Lake Kyoga. It serves as a water catchment for the Lake and its surrounding swamps. It is characterized by Euphorbia candelabrum, Harrisonia abyssinica, Terminalia schimperiana, Combretum collinum with Cyperus papyrus and Phragmites mauritianum on the lake shores. This reserve is used for indiscriminate tree cutting for charcoal production, livestock (cattle) grazing, human settlement and cultivation which culminate to soil erosion on the slopes. The situation is further exacerbated by the unclear boundary of the reserve. 2.2 Data collection The nested quadrat method was used with quadrats of 20 x 20 m for trees, 10 x 10 m for shrubs and 5 x 5 m for herbaceous climbers, forbs and grasses were placed at intervals of 100 m along a transect of 1000–1500 m applied. The transects were spaced at an interval of 1000 m. The quadrat method is used for most plant communities (Cox 1990 ) because it allows the more abundant species to be recorded in the smaller quadrats while increasing the likelihood of encountering the less common species in the larger quadrats (Bonham 2013). The transects were located on the ground using the gradient oriented transect (gradsect) sampling (Austin & Heyligers 1989 ) technique. This approach ensures that the environmental variability is adequately represented amidst budget, time and staff constraints. The gradsects have been shown to be superior in capturing information about vegetation attributes than randomly placed transects of similar length (Gillison & Brewer 1985). The gradients considered in the study are topography (bottom-middle-top slope), drainage patterns namely rivers and alignment to the direction of the sun (aspect). The plant parameters measured in each quadrat included species identity and number of individuals present or cover for the herbaceous plants. The trees and shrubs were identified by their local names following the local guides (Katende et al. 1995 , 1999 ) while the grasses were identified following Phillips et al. ( 2003 ). The voucher specimens of plants were collected and pressed for confirmatory taxonomic determination at Makerere University Herbarium. The adequacy of the sampling effort was assessed using the species accumulation curves in each CFR. 2.3 Data analysis The species richness, diversity and evenness were determined for each forest reserve using the Shannon-Index (H / ) and Evenness (E) (Magurran 1988) in Vegan, R Statistical Package (version 4.0.3). The study used binary similarity coefficients because only presence/absence data of plant species was recorded in each CFR following Chao et al. ( 2006 ). Although there are many similarity indices based on presence/absence (incidence-based) data in literature (Chao et al. 2006 ), only the Jaccard and Sørensen indices were used in this study because they are generally functions of three incidence counts namely the number of species shared and the number of species unique to each. Magurran ( 2004 ), assert that these are the most classic, simple and widely indices in comparing species assemblages. They are also modifiable into coefficients of dissimilarity by taking their inverse (Chao et al. 2006 ). However, as a limitation, Chao et al. ( 2006 ) noted that these binary indices do not take into account the abundance of species. In so doing, they treat abundant and rare species equally. They further assert that as a result of this limitation, the estimates are generally biased downward and the bias increases when either sample sizes are small or species richness is high. On the contrary, Krebs ( 1999 ) asserts that it is theoretically possible that the Jaccard and Sorensen indices could be upwardly biased but this seems to be most unusual. 3.0 Results 3.1. Floristic richness and diversity A sum of 417 species in 76 families were recorded in the CFRs of NE Uganda (Appendix 1). Fabaceae had the highest number of species (77) followed by Poaceae (35). The lowest actual species richness was recorded in Akur CFR (142) while the highest was in Bululu hills CFR (187) (Table 1). In terms of richness estimators, Chao 2 estimator values ranged from 136 in Mt. Moroto to 205 in Bululu hills. The Jackknife 1 estimator values ranged from 144 in Mt. Moroto to 176 in Bululu hills (Table 1). A One-way ANOVA showed no significant difference in the actual species richness, Chao 2 and Jackknife 1 estimated values ( df = 2, F = 0.046, p > 0.956) for the sites. The majority of the species are native to Uganda (81.3%), the origin of 9.8% could not be established and 8.9% are introduced. On one hand, Chao 2 under estimated species richness in Ogera hills and Mt. Moroto but overestimated in Akur, Bululu, Kano and Onyurut. On the other, Jackknife 1 under estimated species richness in Bululu hills, Mt. Moroto and Onyurut but overestimated in Akur, Kano and Ogera (Table 1). Bululu hill CFR has the highest Shannon-Wiener diversity index (H / ) of 4.47 followed by Onyurut at 4.43 while Akur and Kano (4.2) have the least (Table 2). These indices are significantly different (t = 85.291, df = 4, p = 0.00). All the CFRs have Equitability indices ranging from 0.83 to 0.86 (Table 2). Table 1: Actual and estimated species richness in the CFRs of north eastern Uganda Central Forest Reserve Actual Species richness Richness Estimated Species Richness Variance Chao 2 Jackknife 1 Chao 2 Jackknife 1 Akur 142 149 161 -7 -19 Bululu Hills 187 205 176 -18 11 Kano 148 163 174 -15 -26 Mount Moroto 160 136 144 24 16 Ogera Hills 161 154 173 7 -12 Onyurut 171 172 169 -1 2 The species accumulation curves for each CFR (Figure 2) were plotted as a function of the number of species detected and number of quadrats sampled. Bululu hills had the highest accumulation of species at less than 100 plots while Akur had the lowest. The curve in Onyurut indicates that there was a possibility of adding new species with additional sampling effort just like in Akur and Ogera hills CFRs. Table 2: Shannon-Wiener diversity indices (H / ) and Equitability of floristic diversity in the CFRs of north eastern Uganda Central Forest Reserve Shannon-Wiener diversity index (H / ) Equitability ( J ) Akur 4.20 0.83 Bululu hill 4.47 0.84 Kano 4.20 0.83 Mount Moroto 4.40 0.86 Ogera Hills 4.27 0.83 Onyurut 4.43 0.84 3.2 Floristic similarity across CFRs The dendogram on the relatedness of the CFRs in NE Uganda depicts two main clusters namely: Onyurut and Ogera hills; Akur, Kano, Bululu hills and Mt. Moroto (Figure 3). However, the latter cluster is branched into two sub-clusters namely; Akur and Kano; and Bululu hills and Mount Moroto. 3.3 Complementarity analysis Table 3 shows that the CFRs complement one another by hosting some plant species not recorded in others. It further shows that three CFRs (Bululu hills, Mt. Moroto and Onyurut) account for 81.53 % of the plant taxa in the sites studied. The addition of the fourth CFR (Ogera hills) accommodates nearly 90 % of the species recorded in this study. In order to account for more than 95% of the species, it would require five CFRs (Bululu hills, Mt. Moroto, Onyurut, Ogera hills and Akur) to be protected whereas a more complete protected-area system (accounting for 100 % of species) would include all the CFRs surveyed. Table 3: Complementarity table for the minimum critical set of CFRs in north eastern Uganda based on plant taxa Central Forest Reserve Species richness Cumulative percentage (%) *** Bululu Hills 187 44.84 Mt. Moroto 91 21.82 Onyurut 62 14.87 Ogera Hills 33 7.91 Akur 27 6.47 Kano 17 4.08 Key: *** shows the percentage added to the total by each Central Forest Reserve through the addition of species not already represented in sites higher on the table 3.4 Conservation status of the plant taxa The 417 species reported in this study (Appendix 1) belong to five IUCN Red list categories. These are summarized in Table 4. More than half of the species recorded (270) have not been evaluated (NE). Amongst those that have been evaluated, Least Concern (LC) comprises the highest number (137). The Vulnerable (VU) species are Albizia malacophylla , Vitex amanuensis, Entandrophragma cylindricum and Vitellaria paradoxa while the Near Threatened (NT) species are Albizia ferruginea, Dalbergia melanoxylon, Eucalyptus grandis and Milicia excelsa. The only Data deficient species recorded is Mangifera indica which is also cosmopolitan . According to the IUCN (https://www.iucnredlist.org/), a taxon is Data Deficient (DD) when there is inadequate information to make a direct, or indirect, assessment of its risk of extinction based on its distribution and/or population status. A taxon in this category may be well studied, and its biology well known, but appropriate data on abundance and/or distribution are lacking. In the national red lists (WCS 2016), the conservation status of some species previously assessed by the IUCN Redlists has been elevated. For example; E. cylindricum is Vulnerable according to IUCN Red lists but Endangered at a national level. Table 4: IUCN Global Conservation Status of plant species in the CFRs of north eastern Uganda IUCN Red list category Total number of species Percentage (%) Central Forest Reserve BUL KAN OGE MOR AKU ONY Vulnerable (VU) 4 1 2 1 0 1 2 0 Near Threatened (NT) 4 1 1 1 2 1 2 1 Least Concern (LC) 137 32.9 68 59 64 58 57 55 Data Deficient (DD) 1 0.2 0 0 0 0 1 0 Not Evaluated (NE) 271 64.9 115 87 95 100 80 115 Total 417 100 187 (3.9) 148 (3.1) 161 (3.4) 160 (3.3) 142 (2.9) 171 (3.5) Key: BUL = Bululu hills, KAN = Kano, OGE = Ogera hills, AKU = Akur and ONY= Onyurut; the figure in brackets () shows the percentage of species in each central forest reserve from known plant species in Uganda. Discussion The CFRs have comparatively high floristic richness and diversity (Table 1) with the recorded species representing about 8.7% of the 4800 plant species known in Uganda (Kalema et al. 2016). The diversity indices within CFRs are above the threshold (2.0) for high diversity (Magurran 2004). Similarly, the equitability values are close to 1 which is considered high and signifies fairly even representation of individuals from different species in the population (Paclibar & Tadiosa 2020). The species accumulation curves (Figure 2) denote that as the size of the sampling area increased, the number of species also increased but the occurrence of new species eventually decreased. Roswell et al. (2021) refer to this reduction in addition of new species as an asymptote. In order to judge whether or not a sampling area is representative, Taherdoost (2016) states that a representative sampling area is reached if the increase of number of species per unit area is below 10% with an additional 10% expansion of the sampling area. In Ogera hills, Bululu hills and Onyurut, the addition of new species reduced after sampling at least 120 plots possibly due to their small sizes. In the case of Mount Moroto CFR, up to 200 sampling plots were required to reach an asymptote because it is the largest CFR surveyed with heterogeneous habitats due to the altitudinal differentiation. These accumulation curves provide a rationale to formalize the ecological survey to allow more rigorous and quantitative comparisons between lists, provide a planning tool for collections expeditions and a predictive tool for the total number of species present in a given area (Roswell et al. 2021). The grouping of CFRs into clusters (Figure 3) suggests a plausible influence of altitudinal differences whereby the CFRs in mountainous or hilly areas (Akur, Kano, Bululu hills and Mt. Moroto) being clustered together. The relationship between Onyurut and Ogera hills can be attributed to propagule exchange (Figure 3). The dissimilarity of sites can also be attributed to the distinct climatic conditions in north eastern Uganda. One part (Teso sub-region) receives a humid and hot climate with rainfall between 1000 and 1350 mm per annum while the other (Karamoja) has a drier and semi-arid climatic pattern with rainfall ranging from 500 to 800 mm per annum although the highlands receive slightly higher amounts (Egeru 2012). The complementarity analysis in Table 3 shows that there is incremental gain of plant species conserved by adding new CFRs into the protected area network. According to Williams et al. (2006), this incremental approach leads to identification of important areas for conservation that can add as much biodiversity as possible to a plan. Although Akur and Kano CFRs contribute only 10.55 % of the species, Howard et al. (2000) assert that it is better to protect the country’s biodiversity in a larger number of sites, if these are areas with potential for other uses and where protection would provide additional complementary benefits such as watershed protection. The results in Table 3 also bring out the aspect of irreplaceability of sites in systematic conservation planning. In particular, it shows the number of species that can be lost due to site loss. For example, Bululu hills, Mount Moroto and Onyurut account for 81.53 % of the plant species in the CFRs of north eastern Uganda. This information is helpful in determining priorities for conservation action (Pressey 1998 cited in Carwardine et al. 2007). The practical limitation of this approach arises when there are many alternative sets of sites that can meet targets, and many of these might be similarly efficient in terms of cost (Carwardine et al. 2007). This however, can be overcome by setting a critical cut off point to facilitate decision making. The conservation status of the plant taxa (Table 4) shows that all the CFRs have taxa of national and global conservation importance albeit in small numbers and low threat categories. In some species, the IUCN conservation assessment rates the extinction risk at low level compared to the national assessment (WCS 2016). For instance, Albizia ferruginea is VU in the IUCN Global Red lists but EN in the national red list (WCS 2016), Milicia excelsa is NT in the IUCN Global Red list while it is EN in WCS (2016), Mondia whitei is NE in IUCN redlist but VU in WCS (2016), and Entandrophragma cylindricum is VU in IUCN Global Red list but EN in WCS (2016). According to WCS (2016), all the threatened species recorded in these CFRs also occur in other parts of Uganda. The DD species in Akur is (Mangifera indica); an introduced species which occurs widely outside the CFRs. The species in the NE category can be reduced if more effort and resources are directed towards investigation of their distribution and conducting conservation assessments. This will facilitate evidence-based conservation planning and management of the CFRs. The information on threat levels is key in applying the Important Plant Areas (IPAs) sub-criterion A(i) for sites which contain one or more globally threatened species (Darbyshire et al. 2017). IPAs are the most important places in the world for wild plant and fungal diversity that can be protected and managed as specific sites. They provide a means for systematic and evidence-based identification of priority areas for plant species in order to promote the conservation and management of these sites. In light of this information, four CFRs namely Bululu hills, Mount Moroto, Kano and Akur would qualify to be IPAs because of presence of one or two VU species. At present, Mount Moroto CFR is already being profiled as an IPA under the Tropical Important Plant Areas (TIPAs) project between Makerere University and Royal Botanic Gardens, Kew (https://www.kew.org/science/our-science/projects/tropical-important-plant-areas-uganda). Conclusion The findings of this study reveal the botanical richness, diversity, similarity and complementary in the six CFRs in NE Uganda. Up to 417 plant species representing nearly 8.7 percent of the known taxa have been recorded. The CFRs are complementary to each other in terms of floristic composition with four sites (Bululu hills, Mt. Moroto, Onyurut and Ogera hills) accounting for 90% of the species. Furthermore, four CFRs (Bululu hills, Mt. Moroto, Kano and Akur) contain Vulnerable species making them candidate IPA sites in Uganda. Although this study has provided baseline information on the floristic composition in the six CFRs of north eastern Uganda. Future research should be geared towards studying the populations (especially structure and regeneration) of the threatened species, environmental parameters that influence plant distribution patterns, developing species management plans to reduce the extinction risk of Vulnerable species, and conducting conservation assessments of the species that are currently not evaluated. Declarations Ethics approval and consent to participate NA Consent for publication All the authors consent to publication Availability of data and materials All the material has been provided Competing interests The authors have no competing interests Funding The study was supported by DAAD In-country/In-Region Programme and IDEA Wild Authors' contributions SO conceptualized the research idea, collected the data and prepared the draft manuscript. EK, PM and JK supervised data collection, data analysis and reviewed the draft manuscript. Acknowledgements We acknowledge the permission for the National Forestry Authority (NFA) to undertake this research within the forest reserves. We also grateful for the support of various forest patrol men during field surveys. Mr. Protase Rwaburindore who helped with determination of voucher specimens at the Makerere University Herbarium is sincerely appreciated. References Austin MP, Heyligers PC. Vegetation survey design for conservation: gradsect sampling of forests in north-eastern New South Wales. Biological conservation. 1989 Jan 1;50(1-4):13-32. Bonham CD. Measurements for terrestrial vegetation. John Wiley & Sons; 2013 Apr 16. Byakagaba P, Eilu G, Okullo JB, Tumwebaze SB, Mwavu EN. Population structure and regeneration status of Vitellaria paradoxa (CF Gaertn.) under different land management regimes in Uganda. Agricultural Journal. 2011 Jan;6(1):14-22. 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Measuring biological diversity. African journal of aquatic science. 2004 Aug;29(2):285-6. Malhi Y, Gardner TA, Goldsmith GR, Silman MR, Zelazowski P. Tropical forests in the Anthropocene. Annual Review of Environment and Resources. 2014 Oct 17;39:125-59. Millennium ecosystem assessment ME. Ecosystems and human well-being. Washington, DC: Island press; 2005 Aug 20. Moreno CE, Calderón‐Patrón JM, Martín‐Regalado N, Martínez‐Falcón AP, Ortega‐Martínez IJ, Rios‐Díaz CL, Rosas F. Measuring species diversity in the tropics: a review of methodological approaches and framework for future studies. Biotropica. 2018 Nov;50(6):929-41. National Forestry Authority. Forest Management Plan for Namatale Central Forest Reserves Management Plan Area (2012-2022). National Forestry Authority, 2012, Kampala, Uganda. National Forestry Authority. Managing Central Forest Reserves for the people of Uganda: Functions of Central Forest Reserves. National Forestry Authority, 2008, Kampala, Uganda Nic Lughadha E, Bachman SP, Leão TC, Forest F, Halley JM, Moat J, Acedo C, Bacon KL, Brewer RF, Gâteblé G, Gonçalves SC. Extinction risk and threats to plants and fungi. Plants, People, Planet. 2020 Sep;2(5):389-408. Okia C. Balanites aegyptiaca: A resource for improving nutrition and income of dryland communities in Uganda. Bangor University (United Kingdom); 2010. Paclibar GC, Tadiosa ER. Plant species diversity and assessment in Quezon Protected Landscape, Southern Luzon, Philippines. Philippine Journal of Systematic Biology. 2020;14(3):1-9. Phillips S, Namaganda M, Lye KA. 115 Ugandan grasses. Kampala: Department of Botany, Makerere University; 2003. Pullaiah T, Bahadur B, Krishnamurthy KV. Plant biodiversity. Plant Biology and Biotechnology: Volume I: Plant Diversity, Organization, Function and Improvement. 2015:177-95. Roswell M, Dushoff J, Winfree R. A conceptual guide to measuring species diversity. Oikos. 2021 Mar;130(3):321-38. Sala OE, Stuart Chapin FI, Armesto JJ, Berlow E, Bloomfield J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, Kinzig A, Leemans R. Global biodiversity scenarios for the year 2100. science. 2000 Mar 10;287(5459):1770-4. Sosef MS, Dauby G, Blach-Overgaard A, van Der Burgt X, Catarino L, Damen T, Deblauwe V, Dessein S, Dransfield J, Droissart V, Duarte MC. Exploring the floristic diversity of tropical Africa. BMC biology. 2017 Dec;15:1-23. Taherdoost H. Sampling methods in research methodology; how to choose a sampling technique for research. How to choose a sampling technique for research (April 10, 2016). 2016 Apr 10. UN I. Convention on biological diversity. Treaty Collection. 1992 Jun. Valli AT, Kougioumoutzis K, Iliadou E, Panitsa M, Trigas P. Determinants of alpha and beta vascular plant diversity in Mediterranean island systems: The Ionian islands, Greece. Nordic Journal of Botany. 2019 Jan;37(1):e02156. van Vuuren DP, Sala OE, Pereira HM. The future of vascular plant diversity under four global scenarios. Ecology and Society. 2006 Dec 1;11(2). Vellend M, Baeten L, Becker-Scarpitta A, Boucher-Lalonde V, McCune JL, Messier J, Myers-Smith IH, Sax DF. Plant biodiversity change across scales during the Anthropocene. Annual review of plant biology. 2017 Apr 28;68:563-86. WCS. Nationally threatened species for Uganda. Wildlife Conservation Society 2016, Kampala Uganda White F. The vegetation of Africa. 1983. Whittaker RH. Vegetation of the Siskiyou mountains, Oregon and California. Ecological monographs. 1960 Jul 1;30(3):279-338. Williams P, Faith D, Manne L, Sechrest W, Preston C. Complementarity analysis: Mapping the performance of surrogates for biodiversity. Biological Conservation. 2006 Mar 1;128(2):253-64. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4556975","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":314630476,"identity":"5edf032b-02c7-422f-899a-c7d7570462bb","order_by":0,"name":"Samuel Ojelel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYNCCAgYGxgbmBoYHFQwMEsRpMQBpYWxgSDhDihaQJobENiK0yLefTpP4YMAgx9ze2Pggcd42eckG5ocfGNtqcZt/Jneb5AwDBmPGnoPNBonbbhvOZmAzlmBsO47HSbnbpHkMGBIbZyS2SQC1MM5jYDBjYGw7htth/W+3Sf8BaZn/sP1H4pzb9vMY2L/h1cJwA2gLA9gWxjaGxIbbibMZeEC21OB22I23my17DCSAfklslkg4djt5ZjNPsUTCuQN4HJa78caPChs5w/bDBz98qLltO+N4+8YPH8rqcDsMAiQYDBtgbGYgTmA4TEgL0Do0PkFbRsEoGAWjYOQAAJ/hVfhTwFqHAAAAAElFTkSuQmCC","orcid":"","institution":"Makerere University","correspondingAuthor":true,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Ojelel","suffix":""},{"id":314630477,"identity":"682aee9e-1096-4a44-8d53-1484b2f4eed5","order_by":1,"name":"Esther Katuura","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"","lastName":"Katuura","suffix":""},{"id":314630478,"identity":"43645635-caac-4e75-8af9-d624bd223fd3","order_by":2,"name":"Patrick Mucunguzi","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Mucunguzi","suffix":""},{"id":314630479,"identity":"859a15cc-b7d8-4907-84e5-15c2732a74d7","order_by":3,"name":"James Kalema","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Kalema","suffix":""}],"badges":[],"createdAt":"2024-06-10 09:12:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4556975/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4556975/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12862-024-02323-1","type":"published","date":"2025-01-18T15:57:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59088649,"identity":"ee263668-f80d-4eff-ad1a-b601cf6ccec2","added_by":"auto","created_at":"2024-06-26 08:26:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":630292,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of forest reserves in north eastern Uganda\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4556975/v1/8d5129dc404aca5c267befb7.png"},{"id":59088647,"identity":"71b83584-5c65-4ad5-a19b-fe833683fe40","added_by":"auto","created_at":"2024-06-26 08:26:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88288,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies accumulation curves in selected central forest reserves of north eastern Uganda.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4556975/v1/f942a76984a370a32aca0c60.png"},{"id":59088648,"identity":"bc16171b-25d2-431e-a885-2b9002604846","added_by":"auto","created_at":"2024-06-26 08:26:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":30154,"visible":true,"origin":"","legend":"\u003cp\u003eCluster analysis of the six Central Forest reserves in north eastern Uganda.\u003c/p\u003e\n\u003cp\u003eKey: 1 = Akur, 2 = Kano, 3 = Bululu hills, 4 = Mt. Moroto, 5 = Onyurut, 6 = Ogera hills.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4556975/v1/12b5ae2f64b1362f87636a53.png"},{"id":74284785,"identity":"40398a52-087e-4aec-acc4-d4099701cb6e","added_by":"auto","created_at":"2025-01-20 16:12:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1251546,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4556975/v1/70b4dfcb-8c50-41b4-b50e-fec5af228cb2.pdf"},{"id":59088651,"identity":"073c0e32-00d3-4d6c-b6ab-288a3d11572f","added_by":"auto","created_at":"2024-06-26 08:26:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":106586,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4556975/v1/4bd8e7e8d8517e922cc0a783.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative analysis of floristic richness and diversity in six central forest reserves of north eastern Uganda","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eAs 2 in 5 (or 39%) of the world\u0026rsquo;s vascular plant species are threatened with extinction (Nic Lughadha et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), understanding the patterns of distribution (Sosef et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and identification of areas with a high value for biodiversity protection is paramount (Haq et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The warm mixed forest, savannahs, shrub, tropical forest, and tropical woodlands are projected to lose the most species (van Vuuren et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) mainly due to anthropogenic activities which endanger the ecosystems (Malhi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These activities include habitat loss, introduction of alien species, direct exploitation, climate change and pollution (Hilton-Taylor \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e, Sala et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiodiversity is crucial for ecosystem functioning and human well-being (van Vuuren et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) as nearly 1.5\u0026nbsp;billion people globally directly depend on tropical forests for food, timber, medicines, and other important ecosystem functions and services (Lewis et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The recognition of this importance is manifested in the international commitments such as the Convention on Biodiversity (CBD), associated Aichi Biodiversity Targets to halt its decline have been put in place (CBD 2012) and the Kumming-Montreal global biodiversity framework (Joly \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, there is growing interest among scientists, policy makers, land managers, and the general public to understand the patterns and causes of biodiversity loss across space and time (Vellend et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The origin of this interest is twofold; first the desire to conserve biodiversity and secondly; the potential for biodiversity changes to have an impact on the benefits that people derive from nature (MEA 2005).\u003c/p\u003e \u003cp\u003eThe most popular methods for reporting floristic information include species accumulation curves, rarefaction curves and the Shannon\u0026ndash;Wiener indices (alpha diversity) and S\u0026oslash;rensen, Jaccard or Bray\u0026ndash;Curtis indices (beta diversity) (Moreno et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In terms of comparing the species composition (biodiversity) of two or more assemblages, the similarity (or overlap) or dissimilarity (complementarity, turnover, beta diversity or distance) indices are often used (Magurran \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). These indices are classified into two categories namely; binary similarity coefficients when only presence/absence data are available and quantitative similarity coefficients when some measure of relative abundance is available (Chao et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The other important components of floristic assessment include species richness and diversity (Pullaiah et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), population structure and distribution (Okia \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Byakagaba et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The scarcity of this critical information explains why plants are usually not well represented in either global or national conservation planning schemes (Corlett \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost often, plant conservation efforts are hampered by lack of suitable data for prioritising conservation actions. Information on the rarest and most threatened plants and habitats, is often diffuse and difficult to access or is outdated (Darbyshire et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Floristic composition and its distribution remains scarcely known in the species-rich tropical Africa (Sosef et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the case of Uganda, the available floristic data in most sites comprises of plant lists for trees and shrubs which were recorded by the Forest Department in 1990\u0026rsquo;s as indicator taxa (Davenport \u003cem\u003eet al.\u003c/em\u003e 1996). In savannah forest reserves (such as Ogera hills, Bululu and Onyurut investigated in this study), there is no record of botanical surveys carried out. In view of this situation, the study sought to (1) to determine the botanical richness and diversity in the six central forest reserves of north eastern Uganda and (ii) to evaluate the similarity and complementarity of these reserves for the conservation of plants. In achieving these objectives, the study presents floristic diversity within communities (alpha diversity) and between communities or the degree of community differentiation (beta diversity) (Whittaker \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1960\u003c/span\u003e). This information will guide resource managers to prioritize conservation strategies since sites with exceptional or poor diversity (Pullaiah et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) are known. Additionally, it can aid in the evaluation of the relative importance of environmental and spatial drivers in shaping species assemblages (Valli et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e"},{"header":"2.0 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThe study was conducted in six CFRs located in north eastern Uganda (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) in the western range of the Somali-Masai Regional Centre of Endemism (White \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1983\u003c/span\u003e, Eustace et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This region has been poorly surveyed due to prolonged insecurity caused by the armed cattle rustlers (Kalema 2005). Indeed, two CFRs namely Mt. Napak and Mt. Kadam were omitted during floristic surveys due to reports of insecurity. With the exception of Onyurut, all the forest reserves studied are located on either hills or mountains.\u003c/p\u003e \u003cp\u003eOnyurut is a small CFR covering 158 ha in Katakwi district. Its vegetation is predominantly woodland savannah with species such as \u003cem\u003eCombretum adenogonium, C. molle, Acacia brevispica\u003c/em\u003e and \u003cem\u003eZanthoxylum leprieurii\u003c/em\u003e with patches of grassland dominated by \u003cem\u003eBrachiarria decumbens, Hyparrhenia filipenduda\u003c/em\u003e and \u003cem\u003eHyparrhenia dissoluta.\u003c/em\u003e The CFR is encroached by adjacent communities majorly for farming and settlement, brick making, charcoal production, and cattle grazing. It serves as a water catchment area for Lake Bisina.\u003c/p\u003e \u003cp\u003eMount Moroto covers an area of 483 km\u003csup\u003e2\u003c/sup\u003e (Davenport \u003cem\u003eet al.\u003c/em\u003e 1996). It is a dormant volcano with an altitudinal range of 960\u0026ndash;3084 m. The reserve is perched on the top of the escarpment of the Eastern Rift, directly behind and to the east of the town of Moroto, and its eastern boundaries are also those of the Ugandan border with Kenya. Much of the site is dominated by Afromontane undifferentiated forest, a drier montane forest type characterised by valuable timber trees \u003cem\u003ePodocarpus milanjianus\u003c/em\u003e, \u003cem\u003eAfrocarpus\u003c/em\u003e (Podocarpus) \u003cem\u003egracilior\u003c/em\u003e, and \u003cem\u003eJuniperus procera\u003c/em\u003e (Langdale-Brown et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Davenport \u003cem\u003eet al.\u003c/em\u003e 1996). The mean annual rainfall is 887 mm with the peak period between April to August. Significant areas of the reserve, particularly at lower altitudes in the north and south, have been transformed by farming of crops.\u003c/p\u003e \u003cp\u003eKano CFR is located in Labwor hills in the present day Abim district and covers an area of 8,293 ha. It is a key site for biodiversity conservation, hill reserve, and protects River Amal which serves the communities of Kano and Abim parishes (National Forestry Authority \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This reserve is faced with various human activities such as collection of Non Timber Forest Products (NTFPs) like \u003cem\u003eOxytenanthera abyssinica\u003c/em\u003e (bamboo), wild edible fruits and vegetables; stone quarrying, charcoal production and firewood collection, bush burning, human settlement and cultivation, illegal timber harvesting, and collection of construction materials.\u003c/p\u003e \u003cp\u003eAkur CFR covers an area of 6,434 ha. within the Labwor hills of Abim district. It is a critical site for biodiversity conservation, hill reserve and River Ojulu originates from it (National Forestry Authority \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In Akur CFR, the hills are not sufficiently high (1200 m above sea level) to cause much differentiation of the vegetation on account of increasing altitude (National Forestry Authority \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The most important factor limiting the vegetation is most probably soil depth and its associated character of soil moisture (National Forestry Authority \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The thickest tree growth is found on the deep alluvial soils along the lines of the valleys near the hills; further from the hills, the riparian forest thins out into grass \u0026lsquo;vlei\u0026rsquo; with scattered trees. Higher up on the hills, there is usually less soil and the strips of riverine forest are correspondingly narrow, but larger trees occur in the open savanna than on the lower slopes.\u003c/p\u003e \u003cp\u003eOgera hills CFR covers an area of 427 ha and an altitudinal range of 1036\u0026ndash;1160 m (National Forestry Authority, 2012). Its vegetation is mainly comprised of high grass and low tree bushes. The trees are mainly combretaceous and are sometimes stunted in form with species such as \u003cem\u003eCombretum molle, C. collinum, C. adenogonium\u003c/em\u003e and the grass \u003cem\u003eLoudetia arundinceum\u003c/em\u003e mostly on hill slopes. In some parts, tree growth is dense with a tangle of creepers and bushes while some areas with illegal activities like charcoal burning have low tree cover. It serves as a water catchment area of Lake Kyoga in the south.\u003c/p\u003e \u003cp\u003eBululu hills CFR covers an area of 425 ha and is separated from Ogera hills CFR by Lake Kyoga. It serves as a water catchment for the Lake and its surrounding swamps. It is characterized by \u003cem\u003eEuphorbia candelabrum, Harrisonia abyssinica, Terminalia schimperiana, Combretum collinum\u003c/em\u003e with \u003cem\u003eCyperus papyrus\u003c/em\u003e and \u003cem\u003ePhragmites mauritianum\u003c/em\u003e on the lake shores. This reserve is used for indiscriminate tree cutting for charcoal production, livestock (cattle) grazing, human settlement and cultivation which culminate to soil erosion on the slopes. The situation is further exacerbated by the unclear boundary of the reserve.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection\u003c/h2\u003e \u003cp\u003eThe nested quadrat method was used with quadrats of 20 x 20 m for trees, 10 x 10 m for shrubs and 5 x 5 m for herbaceous climbers, forbs and grasses were placed at intervals of 100 m along a transect of 1000\u0026ndash;1500 m applied. The transects were spaced at an interval of 1000 m. The quadrat method is used for most plant communities (Cox \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) because it allows the more abundant species to be recorded in the smaller quadrats while increasing the likelihood of encountering the less common species in the larger quadrats (Bonham 2013).\u003c/p\u003e \u003cp\u003eThe transects were located on the ground using the gradient oriented transect (gradsect) sampling (Austin \u0026amp; Heyligers \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) technique. This approach ensures that the environmental variability is adequately represented amidst budget, time and staff constraints. The gradsects have been shown to be superior in capturing information about vegetation attributes than randomly placed transects of similar length (Gillison \u0026amp; Brewer 1985). The gradients considered in the study are topography (bottom-middle-top slope), drainage patterns namely rivers and alignment to the direction of the sun (aspect).\u003c/p\u003e \u003cp\u003eThe plant parameters measured in each quadrat included species identity and number of individuals present or cover for the herbaceous plants. The trees and shrubs were identified by their local names following the local guides (Katende et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1995\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) while the grasses were identified following Phillips et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The voucher specimens of plants were collected and pressed for confirmatory taxonomic determination at Makerere University Herbarium. The adequacy of the sampling effort was assessed using the species accumulation curves in each CFR.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data analysis\u003c/h2\u003e \u003cp\u003eThe species richness, diversity and evenness were determined for each forest reserve using the Shannon-Index (H\u003csup\u003e/\u003c/sup\u003e) and Evenness (E) (Magurran 1988) in Vegan, R Statistical Package (version 4.0.3). The study used binary similarity coefficients because only presence/absence data of plant species was recorded in each CFR following Chao et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Although there are many similarity indices based on presence/absence (incidence-based) data in literature (Chao et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), only the Jaccard and S\u0026oslash;rensen indices were used in this study because they are generally functions of three incidence counts namely the number of species shared and the number of species unique to each. Magurran (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), assert that these are the most classic, simple and widely indices in comparing species assemblages. They are also modifiable into coefficients of \u003cem\u003edissimilarity\u003c/em\u003e by taking their inverse (Chao et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, as a limitation, Chao et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) noted that these binary indices do not take into account the abundance of species. In so doing, they treat abundant and rare species equally. They further assert that as a result of this limitation, the estimates are generally biased downward and the bias increases when either sample sizes are small or species richness is high. On the contrary, Krebs (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) asserts that it is theoretically possible that the Jaccard and Sorensen indices could be upwardly biased but this seems to be most unusual.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.0 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1. Floristic richness and diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA sum of 417 species in 76 families were recorded in the CFRs of NE Uganda (Appendix 1). Fabaceae had the highest number of species (77) followed by Poaceae (35). The lowest actual species richness was recorded in Akur CFR (142) while the highest was in Bululu hills CFR (187) (Table 1). In terms of richness estimators, \u003cem\u003eChao\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e estimator values ranged from 136 in Mt. Moroto to 205 in Bululu hills. The \u003cem\u003eJackknife\u003csub\u003e1\u003c/sub\u003e\u0026nbsp;\u003c/em\u003eestimator values ranged from 144 in Mt. Moroto to 176 in Bululu hills (Table 1). A One-way ANOVA showed no significant difference in the actual species richness, \u003cem\u003eChao\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eand \u003cem\u003eJackknife\u003csub\u003e1\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eestimated values (\u003cem\u003edf\u003c/em\u003e = 2, \u003cem\u003eF\u003c/em\u003e = 0.046, p \u0026gt; 0.956) for the sites. The majority of the species are native to Uganda (81.3%), the origin of 9.8% could not be established and 8.9% are introduced. On one hand, \u003cem\u003eChao\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e under estimated species richness in Ogera hills and Mt. Moroto but overestimated in Akur, Bululu, Kano and Onyurut. On the other, \u003cem\u003eJackknife\u003csub\u003e1\u003c/sub\u003e\u0026nbsp;\u003c/em\u003eunder estimated species richness in Bululu hills, Mt. Moroto and Onyurut but overestimated in Akur, Kano and Ogera (Table 1). \u0026nbsp;Bululu hill CFR has the highest Shannon-Wiener diversity index (H\u003csup\u003e/\u003c/sup\u003e) of 4.47 followed by Onyurut at 4.43 while Akur and Kano (4.2) have the least (Table 2). These indices are significantly different (t = 85.291, df = 4, p = 0.00). All the CFRs have Equitability indices ranging from 0.83 to 0.86 (Table 2). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1:\u0026nbsp;Actual and estimated species richness in the CFRs of north eastern Uganda\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.5%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCentral Forest Reserve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.5%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eActual Species richness Richness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.5%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEstimated Species Richness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.123287671232877%\" valign=\"top\"\u003e\n \u003cp\u003eChao\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.945205479452056%\" valign=\"top\"\u003e\n \u003cp\u003eJackknife\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eChao\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.931506849315067%\" valign=\"top\"\u003e\n \u003cp\u003eJackknife\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eAkur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e-19\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eBululu Hills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eKano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e-26\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eMount Moroto\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eOgera Hills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e-12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.530884808013354%\" valign=\"top\"\u003e\n \u003cp\u003eOnyurut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.534223706176963%\" valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52754590984975%\" valign=\"top\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.02838063439065%\" valign=\"top\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.186978297161936%\" valign=\"top\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe species accumulation curves for each CFR (Figure 2) were plotted as a function of the number of species detected and number of quadrats sampled. Bululu hills had the highest accumulation of species at less than 100 plots while Akur had the lowest. The curve in Onyurut indicates that there was a possibility of adding new species with additional sampling effort just like in Akur and Ogera hills CFRs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Shannon-Wiener diversity indices (H\u003csup\u003e/\u003c/sup\u003e) and Equitability of floristic diversity in the CFRs of north eastern Uganda\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eCentral Forest Reserve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003eShannon-Wiener diversity index \u0026nbsp;(H\u003csup\u003e/\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003eEquitability (\u003cem\u003eJ\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eAkur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eBululu hill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eKano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eMount Moroto\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eOgera Hills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.32969034608379%\" valign=\"top\"\u003e\n \u003cp\u003eOnyurut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"top\"\u003e\n \u003cp\u003e4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.225865209471767%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003e3.2 Floristic similarity across\u0026nbsp;CFRs\u003c/h2\u003e\n\u003cp\u003eThe dendogram on the relatedness of the CFRs in NE Uganda depicts two main clusters namely: Onyurut and Ogera hills; Akur, Kano, Bululu hills and Mt. Moroto (Figure 3). However, the latter cluster is branched into two sub-clusters namely; Akur and Kano; and Bululu hills and Mount Moroto.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.3 Complementarity analysis\u003c/h2\u003e\n\u003cp\u003eTable 3 shows that the CFRs complement one another by hosting some plant species not recorded in others. It further shows that three CFRs (Bululu hills, Mt. Moroto and Onyurut) account for 81.53 % of the plant taxa in the sites studied. The addition of the fourth CFR (Ogera hills) accommodates nearly 90 % of the species recorded in this study. In order to account for more than 95% of the species, it would require five CFRs (Bululu hills, Mt. Moroto, Onyurut, Ogera hills and Akur) to be protected whereas a more complete protected-area system (accounting for 100 % of species) would include all the CFRs surveyed.\u003c/p\u003e\n\u003cp\u003eTable 3: Complementarity table for the minimum critical set of CFRs in north eastern Uganda based on plant taxa\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eCentral Forest Reserve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003eSpecies richness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003eCumulative percentage (%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eBululu Hills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e44.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eMt. Moroto\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e21.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eOnyurut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e14.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eOgera Hills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e7.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eAkur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.18466898954704%\" valign=\"top\"\u003e\n \u003cp\u003eKano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.926829268292686%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.88850174216028%\" valign=\"top\"\u003e\n \u003cp\u003e4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKey: \u003csup\u003e***\u0026nbsp;\u003c/sup\u003eshows the percentage added to the total by each Central Forest Reserve through the addition of species not already represented in sites higher on the table\u003c/p\u003e\n\u003ch2\u003e3.4 Conservation status of the plant taxa\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe 417 species reported in this study (Appendix 1) belong to five IUCN Red list categories. These are summarized in Table 4. More than half of the species recorded (270) have not been evaluated (NE). Amongst those that have been evaluated, Least Concern (LC) comprises the highest number (137). The Vulnerable (VU) species are \u003cem\u003eAlbizia malacophylla\u003c/em\u003e, \u003cem\u003eVitex amanuensis, Entandrophragma cylindricum\u0026nbsp;\u003c/em\u003eand \u003cem\u003eVitellaria paradoxa\u0026nbsp;\u003c/em\u003ewhile the Near Threatened (NT) species are \u003cem\u003eAlbizia ferruginea, Dalbergia melanoxylon, Eucalyptus grandis\u0026nbsp;\u003c/em\u003eand \u003cem\u003eMilicia excelsa.\u0026nbsp;\u003c/em\u003eThe only Data deficient species recorded is \u003cem\u003eMangifera indica\u0026nbsp;\u003c/em\u003ewhich is also cosmopolitan\u003cem\u003e.\u0026nbsp;\u003c/em\u003eAccording to the IUCN (https://www.iucnredlist.org/), a taxon is \u003cstrong\u003eData Deficient (DD)\u003c/strong\u003e when there is inadequate information to make a direct, or indirect, assessment of its risk of extinction based on its distribution and/or population status. A taxon in this category may be well studied, and its biology well known, but appropriate data on abundance and/or distribution are lacking. In the national red lists (WCS 2016), the conservation status of some species previously assessed by the IUCN Redlists has been elevated. For example; \u003cem\u003eE. cylindricum\u0026nbsp;\u003c/em\u003eis Vulnerable according to IUCN Red lists but Endangered at a national level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: IUCN Global Conservation Status of plant species in the CFRs of north eastern Uganda\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.477707006369428%\" rowspan=\"2\"\u003e\n \u003cp\u003eIUCN Red list category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.535031847133759%\" rowspan=\"2\"\u003e\n \u003cp\u003eTotal number of species\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.535031847133759%\" rowspan=\"2\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.452229299363054%\" colspan=\"6\"\u003e\n \u003cp\u003eCentral Forest Reserve\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.50841750841751%\"\u003e\n \u003cp\u003eBUL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.4983164983165%\"\u003e\n \u003cp\u003eKAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.824915824915825%\"\u003e\n \u003cp\u003eOGE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eMOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.4983164983165%\"\u003e\n \u003cp\u003eAKU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.4983164983165%\"\u003e\n \u003cp\u003eONY\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003eVulnerable (VU)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003eNear Threatened (NT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003eLeast Concern (LC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003eData Deficient (DD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003eNot Evaluated (NE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e64.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.518341307814993%\"\u003e\n \u003cp\u003e\u003cem\u003eTotal\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.556618819776714%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e187 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e148 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.496012759170654%\"\u003e\n \u003cp\u003e161 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.133971291866029%\"\u003e\n \u003cp\u003e160 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e142 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.814992025518341%\"\u003e\n \u003cp\u003e171 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKey: BUL = Bululu hills, KAN = Kano, OGE = Ogera hills, AKU = Akur and ONY= Onyurut; the figure in brackets () shows the percentage of species in each central forest reserve from known plant species in Uganda.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe CFRs have comparatively high floristic richness and diversity (Table 1) with the recorded species representing about 8.7% of the 4800 plant species known in Uganda (Kalema et al. 2016). The diversity indices within CFRs are above the threshold (2.0) for high diversity (Magurran 2004). Similarly, the equitability values are close to 1 which is considered high and signifies fairly even representation of individuals from different species in the population (Paclibar \u0026amp; Tadiosa 2020). The species accumulation curves (Figure 2) denote that as the size of the sampling area increased, the number of species also increased but the occurrence of new species eventually decreased. Roswell et al. (2021) refer to this reduction in addition of new species as an asymptote. In order to judge whether or not a sampling area is representative, Taherdoost (2016) states that a representative sampling area is reached if the increase of number of species per unit area is below 10% with an additional 10% expansion of the sampling area. In Ogera hills, Bululu hills and Onyurut, the addition of new species reduced after sampling at least 120 plots possibly due to their small sizes. In the case of Mount Moroto CFR, up to 200 sampling plots were required to reach an asymptote because it is the largest CFR surveyed with heterogeneous habitats due to the altitudinal differentiation. These accumulation curves provide a rationale to formalize the ecological survey to allow more rigorous and quantitative comparisons between lists, provide a planning tool for collections expeditions and a predictive tool for the total number of species present in a given area (Roswell et al. 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe grouping of CFRs into clusters (Figure 3) suggests a plausible influence of altitudinal differences whereby the CFRs in mountainous or hilly areas (Akur, Kano, Bululu hills and Mt. Moroto) being clustered together. \u0026nbsp;The relationship between Onyurut and Ogera hills can be attributed to propagule exchange (Figure 3). The dissimilarity of sites can also be attributed to the distinct climatic conditions in north eastern Uganda. One part (Teso sub-region) receives a humid and hot climate with rainfall between 1000 and 1350 mm per annum while the other (Karamoja) has a drier and semi-arid climatic pattern with rainfall ranging from 500 to 800 mm per annum although the highlands receive slightly higher amounts (Egeru 2012). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe complementarity analysis in Table 3 shows that there is incremental gain of plant species conserved by adding new CFRs into the protected area network. According to Williams et al. (2006), this incremental approach leads to identification of important areas for conservation that can add as much biodiversity as possible to a plan. Although Akur and Kano CFRs contribute only 10.55 % of the species, Howard et al. (2000) assert that it is better to protect the country\u0026rsquo;s biodiversity in a larger number of sites, if these are areas with potential for other uses and where protection would provide additional complementary benefits such as watershed protection. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results in Table 3 also bring out the aspect of irreplaceability of sites in systematic conservation planning. In particular, it shows the number of species that can be lost due to site loss. For example, Bululu hills, Mount Moroto and Onyurut account for 81.53 % of the plant species in the CFRs of north eastern Uganda. This information is helpful in determining priorities for conservation action (Pressey 1998 cited in Carwardine et al. 2007). The practical limitation of this approach arises when there are many alternative sets of sites that can meet targets, and many of these might be similarly efficient in terms of cost (Carwardine et al. 2007). This however, can be overcome by setting a critical cut off point to facilitate decision making. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe conservation status of the plant taxa (Table 4) shows that all the CFRs have taxa of national and global conservation importance albeit in small numbers and low threat categories. In some species, the IUCN conservation assessment rates the extinction risk at low level compared to the national assessment (WCS 2016). For instance, \u003cem\u003eAlbizia ferruginea\u0026nbsp;\u003c/em\u003eis VU in the IUCN Global Red lists but EN in the national red list (WCS 2016), \u003cem\u003eMilicia excelsa\u0026nbsp;\u003c/em\u003eis NT in the IUCN Global Red list while it is EN in WCS (2016), \u003cem\u003eMondia whitei\u0026nbsp;\u003c/em\u003eis NE in IUCN redlist but VU in WCS (2016), and \u003cem\u003eEntandrophragma cylindricum\u0026nbsp;\u003c/em\u003eis VU in IUCN Global Red list but EN in WCS (2016). According to WCS (2016), all the threatened species recorded in these CFRs also occur in other parts of Uganda. The DD species in Akur is (Mangifera indica);\u003cem\u003e\u0026nbsp;\u003c/em\u003ean introduced species which occurs widely outside the CFRs. The species in the NE category can be reduced if more effort and resources are directed towards investigation of their distribution and conducting conservation assessments. This will facilitate evidence-based conservation planning and management of the CFRs.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe information on threat levels is key in applying the Important Plant Areas (IPAs) sub-criterion A(i) for sites which contain one or more globally threatened species (Darbyshire \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e2017). IPAs are the most important places in the world for wild plant and fungal diversity that can be protected and managed as specific sites. They provide a means for systematic and evidence-based identification of priority areas for plant species in order to promote the conservation and management of these sites. In light of this information, four CFRs namely Bululu hills, Mount Moroto, Kano and Akur would qualify to be IPAs because of presence of one or two VU species. At present, Mount Moroto CFR is already being profiled as an IPA under the Tropical Important Plant Areas (TIPAs) project between Makerere University and Royal Botanic Gardens, Kew (https://www.kew.org/science/our-science/projects/tropical-important-plant-areas-uganda). \u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this study reveal the botanical richness, diversity, similarity and complementary in the six CFRs in NE Uganda. Up to 417 plant species representing nearly 8.7 percent of the known taxa have been recorded. \u0026nbsp;The CFRs are complementary to each other in terms of floristic composition with four sites (Bululu hills, Mt. Moroto, Onyurut and Ogera hills) accounting for 90% of the species. Furthermore, four CFRs (Bululu hills, Mt. Moroto, Kano and Akur) contain Vulnerable species making them candidate IPA sites in Uganda. Although this study has provided baseline information on the floristic composition in the six CFRs of north eastern Uganda. Future research should be geared towards studying the populations (especially structure and regeneration) of the threatened species, environmental parameters that influence plant distribution patterns, developing species management plans to reduce the extinction risk of Vulnerable species, and conducting conservation assessments of the species that are currently not evaluated.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eNA\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eAll the authors consent to publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll the material has been provided\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe study was supported by DAAD In-country/In-Region Programme and IDEA Wild\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eSO conceptualized the research idea, collected the data and prepared the draft manuscript. EK, PM and JK supervised data collection, data analysis and reviewed the draft manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe acknowledge the permission for the National Forestry Authority (NFA) to undertake this research within the forest reserves. We also grateful for the support of various forest patrol men during field surveys. Mr. Protase Rwaburindore who helped with determination of voucher specimens at the Makerere University Herbarium is sincerely appreciated.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAustin MP, Heyligers PC. Vegetation survey design for conservation: gradsect sampling of forests in north-eastern New South Wales. Biological conservation. 1989 Jan 1;50(1-4):13-32.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBonham CD. Measurements for terrestrial vegetation. 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Biological Conservation. 2006 Mar 1;128(2):253-64.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-ecology-and-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"evob","sideBox":"Learn more about [BMC Ecology and Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Floristic richness and diversity, similarity, complementarity, central forest reserves, north eastern Uganda","lastPublishedDoi":"10.21203/rs.3.rs-4556975/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4556975/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs the extinction risk of plants increases globally, there is need to prioritize areas with high floristic richness and diversity to inform the design of evidence-based conservation interventions. As such, this study aimed to; (i) determine the floristic richness and diversity in six central forest reserves of north eastern Uganda and (ii) evaluate the similarity and complementarity of floristic composition. Data was collected from nested quadrats (20 x 20 m for trees, 10 x 10 m for shrubs and 5 x 5 m for herbaceous climbers, forbs and grasses) placed at intervals of 100 m along a transect of 1000\u0026ndash;1500 m. Species richness, diversity and evenness were determined for each forest reserve. Binary similarity coefficients were computed because only presence/absence data of plant species was recorded. A sum of 417 plant species in 76 families were recorded representing 8.7% of known vascular plants reported in Uganda. All the CFRs had high diversity indices ranging from 4.2 in Kano CFR to 4.47 in Bululu hill CFR. In terms of floristic similarity, the CFRs clustered into two groups namely Onyurut and Ogera hills cluster and Akur, Kano, Bululu hills and Mount Moroto cluster. The CFRs complement one another by supporting plant species not recorded elsewhere. Notably, three CFRs (Bululu hills, Mount Moroto and Onyurut) account for 81.53% of the plant taxa. Addition of the fourth (Ogera hills) accommodates nearly 90% of the species and the fifth (Akur CFR) accounts for more than 95% of the species. The highest threat level on taxa in these CFRs is Vulnerable (4 species) and Near Threatened (4 species) with 137 Least Concern and 270 Not Evaluated. The CFRs in NE Uganda have richness and floristic diversity with up to 8.7% of the known plants in Uganda present. The two similarity clusters depict variation in altitudinal, proximity and climatic conditions. Five CFRs are required to conserve 95% of the species recorded. There is need to assess the population of the threatened species, and investigate the edaphic factors which influence plant distribution.\u003c/p\u003e","manuscriptTitle":"Comparative analysis of floristic richness and diversity in six central forest reserves of north eastern Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-26 08:26:54","doi":"10.21203/rs.3.rs-4556975/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-12T16:40:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-11T08:03:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-11T08:02:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ecology and Evolution","date":"2024-06-10T09:11:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ecology-and-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"evob","sideBox":"Learn more about [BMC Ecology and Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d495de89-6f07-4af7-90b2-2108dbe39e2c","owner":[],"postedDate":"June 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T16:06:04+00:00","versionOfRecord":{"articleIdentity":"rs-4556975","link":"https://doi.org/10.1186/s12862-024-02323-1","journal":{"identity":"bmc-ecology-and-evolution","isVorOnly":false,"title":"BMC Ecology and Evolution"},"publishedOn":"2025-01-18 15:57:27","publishedOnDateReadable":"January 18th, 2025"},"versionCreatedAt":"2024-06-26 08:26:54","video":"","vorDoi":"10.1186/s12862-024-02323-1","vorDoiUrl":"https://doi.org/10.1186/s12862-024-02323-1","workflowStages":[]},"version":"v1","identity":"rs-4556975","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4556975","identity":"rs-4556975","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}