Disturbance of coastal forests in East Africa: elephants promote forest butterflies while human impact supports Savannah species

Disturbance of coastal forests in East Africa: elephants promote forest butterflies while human impact supports Savannah species | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Disturbance of coastal forests in East Africa: elephants promote forest butterflies while human impact supports Savannah species Jan Christian Habel, Thomas Schmitt, Maria Fungomeli, Mike Teucher, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6553277/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Anthropogenic and natural disturbances can alter the structure and composition of forest ecosystems and thereby reshape the composition of plants and animals. Conservation management needs to disentangle the impact of both types of disturbance and their effects on biodiversity. Here, we use butterfly survey data from the Arabuko Sokoke dry coastal forest (south-eastern Kenya) to infer the disturbance effects of human and elephant activities. Butterflies were assessed in primary forest with and without elephants and secondary forest with elephants using bait traps (24 traps, eight per forests type). In total, we recorded 30 butterfly species, 23 in the primary forest with elephants, 19 in the primary forest without elephants, and 25 species in the secondary forest. The three forests types with different disturbance histories differed significantly in their butterfly communities. Although secondary forest had a higher butterfly species richness than primary forest, this higher richness was solely due to a higher proportion of Savannah species. In turn, primary forests had considerably higher proportions of forest species than secondary forests, with the highest proportions in the primary forest with elephant disturbance. Our findings hence underline that habitat disturbance can cause quite different outcomings. Conservation implications : While anthropogenic disturbance is negatively impacting the forest butterfly community, the natural disturbance by elephant activities seems to result in habitat structures even better for the performance of the typical forest butterflies than the undisturbed and hence more dense forest. This also calls for the idea that elephants and their activities were typical for the formerly continuous East African coastal forest belt. East African dry coastal forest disturbance primary forest secondary forest habitat parameters butterfly diversity community structure traits Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Numerous tropical forest ecosystems are classified as biodiversity hotspots (Mittermeier et al., 2011 ). In East Africa, they are represented by cloud forests in the mountains and dry coastal forests along the Indian Ocean (Burgess et al., 2007 ). While representing a rather high diversity of endemic plant and animal species, the advanced process of forest degradation and destruction due to increasing agriculture, urbanisation, and deforestation is a severe problem for nature conservation (Newmark and McNeally, 2018 , Teucher et al. 2020 ). Thus, the most important disturbing species is Homo sapiens . In East African forests, human disturbance includes selective logging, large-scale clearing, as well as the partial urban sprawl of a once contiguous forests (Aleman et al., 2017 , Fungomeli et al. 2025 ). These activities can either cause a complete destruction of the forest or its transformation from primary into secondary forest. In general, diversity and composition of plant and animal species differ significantly between primary and secondary forests (Barlow et al., 2007a ). However, respective diversity assessments returned mixed results and did not unequivocally point to primary forests as being more species rich than secondary forests in the same area (Barlow et al., 2007a ; Castillo-Campos et al., 2008 ; Espinosa-Palomeque et al., 2020 ; Turner et al., 1997 ). Apart from anthropogenic pressure, natural factors add to forest disturbance. In particular mega-herbivores such as elephants are known as major ecosystem engineers and to cause severe habitat modifications and may affect the local abundance and composition of plant and animal species (Fritz, 2017 ; Jones et al., 1994 ; Viljur et al., 2022 ). Such, ecosystem engineers constantly disturb the natural vegetation succession and thus contribute to the maintenance of a high level of habitat heterogeneity (Jones et al., 1997 ) On the other hand, Viljur et al. ( 2022 ) also provided examples where natural disturbance contributed to the extinction of typical forest species. Elephants are known to destroy African woodland sites (Jachmann and Bell, 1984 ) and to decrease forest tree diversity (Maicher et al., 2020 ). However, at the same time they can also contribute to an increase in overall species diversity due to the formation of forest clearings, colonised by light-loving plant and animal species. These clearings open opportunities for many insects, particularly pollinators like bees and butterflies (Maicher et al., 2020 ). We selected the Arabuko Sokoke forest as study areas to address these aspects. This forest is one of the largest remnants of the East African dry coastal forest and has a long history of forest management and the use of forest resources (Muriithi and Kenyon, 2002 ). One part of the Arabuko Sokoke forest (the Mida forest area) was transformed into settlement area during the 1920s, later developing into a secondary forest after being designated a protected area in the late 1970s (Mutangah and Mwaura 1992 , Githitho 2021 , Ann Robertson, unpublished data). This secondary forest (below termed sec + e ), along with other parts of Arabuko Sokoke less affected by anthropogenic impacts (below prim + e ), hosts a viable population of elephants fenced in 2006, leading to population increase (Banks et al. 2010 ). The activity of elephants strongly affects the tree composition, the tree age structure, and hence many animal and plant communities (Habel et al., 2017 ). In a smaller part of Arabuko Sokoke primary forest, elephants have been excluded by the fencing resulting in a stronger understorey than in the elephant areas (below prim-e ). This variety of disturbance conditions creates a unique setup to analyse the effects of human and elephant activity on local biodiversity. In this study, we focused on butterfly (Papilionoidea) diversity in the three mentioned forest types. Butterflies are important pollinators and often depend on specific larval food plants (Boggs et al., 2003 ). Therefore, changes in plant composition due to disturbance regimes directly affect butterfly abundance, diversity, and community composition (e.g. Moranz et al., 2012 ). We assessed the butterfly fauna using bait traps and compiled data on important species traits. Our major aim was to infer which of the three forest types with different disturbance histories was most diverse with respect to butterflies and where most typical forest species can be found. Second, given that elephant disturbances increase plant diversity, we expected the sec + e forest being most species rich and the primary forest without elephant access ( prim-e ) being less diverse. We also analysed which ecological groups were affected in which way by the different disturbance regimes. Therefore, our study adds knowledge about the influence of elephants on forest ecosystems. MATERIAL AND METHODS Study area The Arabuko Sokoke forest is a 416 km 2 remnant of the East African dry coastal forest (Arabuko-Sokoke Forest Management Team, 2002). The heterogeneous geology of coastal Kenya led to the development of different forest types (Muriithi & Kenyon 2002 ). Here, we focus on the Mixed forest dominated by Afzelia quanzensis , Hymenaea verrucosa , Combretum schumannii , Manilkara sansibarensis and Encephalartos hildebrandtii (Robertson and Luke, 1993 , Fungomeli et al. 2020 ). The Arabuko-Sokoke forest has a very long history of forest management and use of forest resources. Parts of the forest were settled during the 1920s, but became later protected as a forest reserve leading to reforestation (Robertson and Luke, 1993 ). Ongoing forest use comprises mining of siliceous sands, selective logging, removal of dead wood, and charcoal production (Habel et al., 2017 ). The increasing number of elephants causes strong disturbance of forest structures and modifies floral composition across major parts of the forest (Banks et al. 2010 ). Recording of butterflies The butterfly fauna was recorded using bait traps. Bait traps are particularly suitable in tropical forest ecosystems to study butterflies, as many of them are attracted to rotten i.e. fermented fruits (Freitas et al., 2014 ). We run eight traps in parallel in each of the three forest types (24 in total) and checked them daily between 9 am and 5 pm in the same order. The tramps were controlled after about 24 hours (one day and one night), and were activated for eight days. Minimum distance among traps was 200 m. The traps were placed in mostly shaded but rather open areas in 1.5 m height (e.g. under a tree) to ensure that butterflies can easily access traps but also not suffer from heat and sun-exposure. Species that could not be identified directly in the field (mainly representatives of the family Pieridae and of the nymphalid genus Neptis ) were photographed and identified later using appropriate literature (Larsen, 1991 ). The bait consisted of overripe bananas, sugar, yeast, water and palm wine (Habel et al. 2022 ). The complete list of species and individuals collected in respective traps is given in the Appendix, Table A1. Traits Based on Larsen ( 1991 ) and Habel et al. ( 2018 , 2024 ), each butterfly species was classified according to ecological characteristics (caterpillar food plant: monophagous: one plant species/ genus; oligophagous: various genera, one family; polyphagous: various families), geographical distribution (local: endemic to East African coastal forests, regional: restricted to eastern and southern Africa, continental: also found elsewhere in Africa or even beyond), habitat preferences, and wingspan (in mm, males only). We classified habitat preferences into typical forest dwellers, species associated with woodlands but also shrublands in savannahs, i.e. more open and anthropogenic habitats (e.g. gardens, plantations), and ubiquitous species without clear preferences. Additionally, we classified species based on five important traits: the larval diet type (mainly grasses and herbs, mixed, mainly bushes and trees), the water index (arid, intermediate, not in arid habitats), the tree association index (does not need trees, needs trees, only in forests), and the savannah and hemeroby indices. Savannah association was classified into not occurring in savannah, mainly outside savannahs, occurring in savannahs and forests, and mainly in savannahs. Hemeroby quantifies the anthropogenic influences on habitats (Jalas, 1955 ; Hill et al., 2002 ). A low hemeroby score indicates a species' strong association with natural habitats, while a high score reflects a greater reliance on anthropogenic environments. Based on their hemeroby scores, species were classified into four categories: 1) occurring exclusively in natural habitats, 2) tolerating disturbed natural habitats, 3) inhabiting both natural and anthropogenic habitats, and 4) being more prevalent in anthropogenic environments than in natural ones (Larsen 1991 ; Schmitt et al., 2020 ; Schmitt et al., 2021 ). Classifications for all species are given in the Appendix, Table A2. Statistics We used individual based rarefaction to compare species numbers among the three habitat types and estimated total richness using iChao1 (Hsieh et al., 2016 ). Evenness was assessed from the Pielou index J = e H /S with H being the Shannon entropy and S the total number of observed species. Estimates of standard errors in iChao and J came from 9999 bootstrap samples. Abundances were estimated from total samples sizes of each species. Assessments of differences in species composition among the investigated sites were done by correspondence analysis (seriation) of the abundance matrix in R (v. 4.2.2; R Core Team 2024 ) using ade4 (v. 1.7–23; Dray and Dufour 2007 ). A plot representing the relative abundance of species by sites was used to illustrate the organisation of butterfly communities. Therefore, sites and species were reordered along the plot-axes according to the first correspondence axis. RESULTS In total, we recorded 30 butterfly species, 23 species in the primary forest with elephants ( prim + e ), 19 species in the primary forest without elephants ( prim-e ), and 25 species in the secondary forest with elephants ( sec + e ) (Table 1 , Fig. 2 ). iChao1 richness estimates indicated a total of 26 species in prim + e , 39 species in sec + e , and 28 species in prim-e (Fig. 2 a). Rarefaction curves of prim + e and sec + e intersect, in line with a fast accumulation of richness in prim + e and therefore a higher evenness compared to sec + e . These differences were mainly due to the six Pieridae species of which five exclusively were caught in sec + e (Fig. 2 c). The Pielou evenness of sec + e was J = 0.21 ± 0.03, of prim + e it was J = 0.38 ± 0.03, and 0.34 ± 0.02 for prim-e , making sec + e significantly more diverse and less even than both primary forests that did not significantly differ in richness and evenness at the 95% error level. Species overlap among the three study sites was 53.3% (Fig. 2 b). This percentage increased to 66.7% when excluding Pieridae (Fig. 2 d). Only the forest specialist Pseudacraea boisduvali was trapped exclusively in prim-e . Table 1 Numbers of records and species of major species trait categories in three forest types ( prim + e , prim-e , and sec + e ). In bold are given contingency table significances among groups at P < 0.01. Variable Records Species prim + e prim-e sec + e prim + e prim-e sec + e Total numbers 782 964 1100 23 19 25 Family Nymphalidae 781 964 1091 22 19 19 Pieridae 1 0 9 1 0 6 Phagy Monophagous 3 1 4 1 1 2 Oligophagous 276 302 393 7 6 9 Polyphagous 503 661 703 16 13 16 Colour class Dark 566 567 326 10 8 8 Medium 211 382 763 12 10 11 Light 5 15 11 1 1 6 Habitat Forest 365 384 157 9 8 8 Ubiquitous 338 353 419 8 8 10 Woodland 79 227 524 6 3 7 Distribution Local 406 380 445 13 12 14 Regional 3 0 2 1 0 1 Continental 373 584 653 9 7 10 Wing length Wing length 37.4 ± 2.7 39.7 ± 2.2 35.1 ± 2.5 - - - Sample sizes were highest in sec + e (1,100 records), intermediate in prim-e (964), and lowest in prim + e (782) (Table 1 ). Six nymphalid species, i.e. four Charaxinae ( Charaxes protoclea, C. varanes, C. cithaeron, C. jahlusa ), one Satyrinae ( Bicyclus safitza ) and one Biblidinae ( Byblia ilithyia ), reached high abundances in all forest types and in total accounted in each of the three type for more than 50% of all records (Table A1). Of these, C. cithaeron was the only species more frequent in prim-e than in the two other forest types; C. varanes was most common in prim + e ; B. ilithyia and C. jahlusa were the dominant species in sec + e , while C. protoclea and B. safitza were more common in the two primary forest types than in the secondary forest (Table A1). Overlap (Fig. 2 b, d) and correspondence analyses (Fig. 3 ) clearly separated the three forest types with respect to butterfly community composition. These differences are reflected in the distribution of species traits, and functional trait composition significantly (at the 1% error level of contingency probabilities) differed among the three habitat types (Table 1 , 2 ). More in detail, monophagous species were largely absent from the three habitat types, while polyphagous were the dominant group, but no significant difference was obtained among the habitat types (Table 1 ). Both primary forest types were dominated by darker colour types, while lighter coloured individuals were most common in sec + e . Species associated more with open landscapes (i.e. the categories wood- & shrubland, ubiquitous) were most common in sec + e (Table 1 ). In the latter, species of continental or even wider distribution dominated, while species restricted to eastern and southern Africa were more common in prim + e (Table 1 ). We did not find significant differences in average wing length among the forest types, but the largest average wing size was obtained in prim-e (Table 1 ). Table 2 Numbers of records and species of the hemeroby, tree, savannah, water, and larval diet type index categories in three forest types ( prim + e , prim-e , and sec + e ). In bold are given contingency table significances among groups at P < 0.01. Variable Records Species prim + e prim-e second + e prim + e prim-e second + e Hemeroby Natural habitats 74 59 33 4 4 4 Disturbed natural habitats 406 602 663 12 8 11 Natural and anthropogenic habitats 293 298 393 6 6 8 Common in anthropogenic habitats 9 5 11 1 1 2 Tree index Does not need trees 89 129 249 6 5 8 Needs trees 295 446 674 5 4 6 Only in forests 398 389 177 12 10 11 Savannah index No savannah 50 31 9 3 4 4 Mainly outside savannahs 315 329 144 8 5 7 Savannahs and forests 114 84 68 7 6 7 Mainly savannahs 303 520 879 5 4 7 Water index Arid habitats 90 134 238 4 4 5 Intermediate 586 765 822 11 9 13 Not in arid habitats 106 65 40 8 6 7 Larval diet type index Grasses and herbs 271 289 385 5 4 5 Trees and Shrubs 39 13 14 4 2 2 Both 472 662 701 14 13 18 Tree and savannah indices revealed contrary patterns with savannah associated species being most common in sec + e (Table 2 ). Species of intermediate water index occurred similarly in all three forest types. Species associated with forests (even disturbed ones) were more common in prim + e and prim-e than in sec + e (Table 2 ). Larval diets differed among the forest types although this was only due to some species strictly associated with trees and shrubs (Table 2 ). Species occurring also in anthropogenic habitats were significantly more abundant in the sec + e forest than in both other forest types (Table 2 ). DISCUSSION Richness estimates did not exceed 40 butterfly species, and rarefaction analyses revealed a high degree of saturation of species numbers after just a few days of data collection for all three forest types with diverging disturbance histories (Fig. 2 a, c). Our study design thus was able to estimate the numbers of fruit-feeding butterfly species with sufficient precision. The total number of reported species is similar to prior studies using bait traps conducted in the Arabuko Sokoke Forest (Habel et al., unpublished data) and the savannahs of southern Kenya (Habel et al. 2022 ). Importantly, these studies mostly report species belonging to the family Nymphalidae (particularly the genus Charaxes ); in addition, some few individuals of the family Pieridae were retained in our study, while representatives of the families Hesperidae, Lycaenidae, and Papilionidae were not encountered in the traps (Fig. 3 ). These findings go in line with data from other studies using bait traps in the Neotropics (DeVries et al. 2012 , Freitas et al. 2014 , Checa et al. 2019 , Álvarez et al. 2021 ), South-East Asia (Sari et al. 2025 ) and in Europe (Jakubikova & Kadlec 2015 ). Thus, the overall species diversity (including nectar-feeding butterflies) definitively is much higher than the here reported numbers (see below). Secondary forests are “second choice” for tropical butterfly conservation Comparing butterfly diversity in the three different forest types, it was highest in the secondary forest with elephant disturbance and lowest in the primary forest without elephants (Fig. 2 a), a forest type that contains herb, shrub and tree layers and a plant species composition significantly differing from the two disturbed forest types (Robertson and Luke 1993 , Abdallah 2017 ). The here obtained results are consistent with findings from other studies analysing the effects of forest disturbance on species richness (Veddeler et al. 2005 , Koh 2007 ). Apparently, forest disturbance enhances plant species richness (Rosenfield et al. 2023 ) and subsequently various arthropod groups, including butterflies (Basset et al. 1998 , Wood and Gillman 1998 ). Disturbance also changes microclimatic conditions and promotes habitat heterogeneity as well as light exposure, factors important for many herbivorous insects (Viljur et al. 2022 , Wood and Gillman 1998 ). In turn, the shadier forest climax stage is characterised by a more homogeneous vegetation structure and a lower plant species diversity (Viljur et al. 2022 ). However, we obtained a different picture if excluding Pieridae, a family not typically attracted by bait traps and therefore often excluded in the analyses of their results (DeVries et al. 2012 , Freitas et al. 2014 ). All six Pieridae species entering our traps were encountered in the secondary forest, none in prim-e and one in prim + e (Fig. 3 ). Thus, the higher diversity of the secondary forest was solely based on them. For Nymphalidae, i.e. the typical fruit-feeding butterflies (see above), the highest species number of 22, in contrast, was obtained in prim + e , while the other two forest types had 19 species. This picture also holds true for extrapolations of species numbers and other diversity estimates (Fig. 2 c). Thus, if only taking the typical fruit-feeding species into account, the primary forest with elephant disturbance was most species rich, while the undisturbed primary forest and the secondary forest performed similarly. Despite the difference in vegetation, the butterfly communities overlapped in their composition among the three forest types. Even in the secondary forest, only 6 out of 25 species were not found in the other forest types (Fig. 2 b), i.e. five of the six Pieridae species as well as the Nymphalid Junonia oenone . Correspondence analysis clearly separated the forest types according to family membership (Fig. 3 b). Most of the Pierids are generalists and predominantly found in more open ecosystems beyond closed forests; Junonia oenone even is a typical savannah species (Larsen 1991 ). Vice versa, we recorded typical forest species like Charaxes brutus , Charaxes etesipe and Pseudacraea boisduvali only or predominantly (e.g. Charaxes cithaeron , Euryphura achlys ) in the primary forest (Fig. 3 ). Differences in community structures were even more obvious when including species abundances with prim + e and sec + e being most distinguished (Fig. 3 ). For instance, the savannah species Byblia ilithyia and the wood- and bushland species Charaxes jahlusa (Larsen 1991 ) were most dominant in the secondary forest, while the forest specialists Euxanthe wakefieldi , Euryphura achlys and Charaxes cithaeron (Larsen 1991 ) occurred in much higher abundances in the primary forest (with and without elephants). These results clearly underline the long-lasting effects of human disturbance, well reflected in the higher proportion of disturbance indicators in the secondary forest if compared with the two types of primary forest (Table 2 ). Although the secondary forest is regaining many of the forest elements from the adjoining primary forests, several specialist forest species still were not observed there or at least at considerably lower densities, hence supporting the non-substitutable value of true primary forests. Previous studies in the Arabuko Sokoke forest based on line transects showed similar trends, with typical forest butterflies mainly inside of intact forests (Habel et al. 2018 ); similar findings were also made in the cloud forests of the Taita Hills (Kenya) (Schmitt et al. 2020 ), but also in the Amazon rainforest (Barlow et al. 2007b ). In conclusion, the higher species richness in disturbed tropical forests mostly results from the strong increase of taxa typical for more open landscapes overcompensating the loss of typical forest species (Basset et al. 1998 ). This again is well reflected in our data by the reducing need of the species for forests and even trees; thus, 32.9% of the species and 22.6% of the individuals in the secondary forest are not in need of trees; in the primary forest, it was 25.0% (species) and 12.5% (individuals). Hence, the typical forest species are more predominant in the primary forest, hereby underlining its considerably higher conservation value if compared with the secondary forest. Furthermore, species with smaller distribution areas dominate in the primary forest (Table 1 ). This example again highlights that the structure of a species community is a better indicator for defining the conservation value of a habitat than the total number of species which can rapidly change due to seasonal shifts (Devries & Walla 2008). The “positive” and the “negative” disturbance: elephants versus humans Some species in our study showed a generally positive response on disturbance. However, these species in most cases are common generalists like Melanitis leda which might have been favoured by the higher availability of grasses, i.e. its larval food plant (Larsen 1991 ), or even disturbance indicators like Hypolimnas misippus (Larsen 1991 ). However, also some forest species apparently benefited from forest disturbance in general, thus the gliding species Neptis saclava which due to its behaviour prefers less dense forest structures, and Charaxes guderiana , a species typical for the more open, hall-like Brachystegia forests (Larsen 1991 ). However, several true forest species (almost) missing in the secondary forest, like Charaxes brutus , Charaxes etesipe and Euxanthe wakefieldi , were considerably more common in the primary forest with elephant disturbance than in the parts excluding them. This is well reflected in the percentage of individuals belonging to the truly specialised forest species, which was 14.3% in secondary forests, 38.8% in prim-e and 46.7% in prim + e (Table 2 ). This difference between the two primary forest types at the first glance seems counterintuitive. However, elephants apparently have been a permanent and long-lasting source of natural disturbance in the forests of Africa (Johnson et al. 2007 ). Thus, the primary forest with elephant disturbance might be the forest type closest to the typical coastal forest prior to human impact, so that forest species might have adapted more to these “elephant forests” along their evolution than to the “elephant-free forests”. Consequently, natural elephant disturbance and anthropogenic disturbance might have opposed influence on specialised forest butterfly species. Darker butterflies in “darker“ forests Comparatively more species with dark wings occurred in the denser forest, while those with light coloured wings were found more in the disturbed forests with lightest colours observed in the secondary forest where tree cover was lowest. A similar pattern, i.e. a positive correlation between forest density and darkness of wings, was found in tropical forests in Australia (Xing et al. 2016 ). The reasons for this pattern are disputed. Referring to thermoregulation, Xing et al. ( 2016 ) argued that cooler habitats support darker colours as these reflect less heat, as generally shown also on the continental scale (Stelbrink et al. 2019 ). Although our study sites are characterised by rather similar temperature regimes with average maximum temperatures ranging above 30°C, heat nevertheless is more buffered in the shadier forest types than in the more open disturbed ones, giving at least some support for this hypothesis also in our case. However, Schirmer et al. ( 2023 ) also discussed differences in predator avoidance as a possible cause. They speculated that colour differences of ventral but not of dorsal wing sites might be caused by habitat specific predation risks; but this hypothesis still lacks confirmation. In addition, darker colours also seem to be related to more humid habitats at the continental scale (Stelbrink et al. 2019 ); this goes in line with our results as the drying after the end of the rains is slowed down with increasing shading by trees. In any case, further physiological and evolutionary studies are needed to unravel the ultimate causes behind the reported colour differences. Declarations Author Contribution JCH and TS developed the study design, JCH, MF and MT collected data, WU and JE did statistical analyses, all contributed while writing this manuscript. 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BMC Evol Biol 7:244 Jones CG, Lawton JH, Shachak M (1994) Organisms as Ecosystem Engineers. Oikos 69(3):373. https://doi.org/10.2307/3545850 Jones CG, Lawton JH, Shachak M (1997) Positive and Negative Effects of Organisms as Physical Ecosystem Engineers. Ecology , 78 (7), 1946–1957. https://doi.org/10.1890/0012-9658 (1997)078[1946:PANEOO]2.0.CO;2 Koh LP (2007) Impacts of land use change on South-east Asian forest butterflies: A review. J Appl Ecol 44(4):703–713. https://doi.org/10.1111/j.1365-2664.2007.01324.x Larsen TB (1991) The butterflies of Kenya and their natural history. Oxford University Press Maicher V, Delabye S, Murkwe M, Doležal J, Altman J, Kobe IN, Desmist J, Fokam EB, Pyrcz T, Tropek R (2020) Effects of disturbances by forest elephants on diversity of trees and insects in tropical rainforests on Mount Cameroon. Sci Rep 10(1):21618. https://doi.org/10.1038/s41598-020-78659-7 Mittermeier RA, Turner WR, Larsen FW, Brooks TM, Gascon C (2011) Global Biodiversity Conservation: The Critical Role of Hotspots. In: Zachos FE, Habel JC (eds) Biodiversity Hotspots. Springer, Berlin Heidelberg, pp 3–22. https://doi.org/10.1007/978-3-642-20992-5_1 Moranz RA, Debinski DM, McGranahan DA, Engle DM, Miller JR (2012) Untangling the effects of fire, grazing, and land-use legacies on grassland butterfly communities. Biodivers Conserv 21(11):2719–2746. https://doi.org/10.1007/s10531-012-0330-2 Muriithi S, Kenyon W (2002) Conservation of biodiversity in the Arabuko Sokoke Forest, Kenya. Biodivers Conserv 11(8):1437–1450. https://doi.org/10.1023/A:1016234224819 Mutangah JG, Mwaura PK (1992) A vegetation survey report, Arabuko Sokoke forest management and conservation project. East African Herbarium, National Museums of Kenya, Kenya Newmark WD, McNeally PB (2018) Impact of habitat fragmentation on the spatial structure of the Eastern Arc forests in East Africa: Implications for biodiversity conservation. Biodivers Conserv 27(6):1387–1402. https://doi.org/10.1007/s10531-018-1498-x R Core Team (2024) R: A Language and Environment for Statistical Computing [Software]. https://www.R-project.org/ Robertson SA, Luke WRQ (1993) Kenya Coastal Forests: Report of the NMK/WWF Coast Forest Survey. World Wide Fund for Nature Rosenfield MF, Jakovac CC, Vieira DLM, Poorter L, Brancalion PHS, Vieira ICG, De Almeida DRA, Massoca P, Schietti J, Albernaz ALM, Ferreira MJ, Mesquita RCG (2023) Ecological integrity of tropical secondary forests: Concepts and indicators. Biol Rev 98(2):662–676. https://doi.org/10.1111/brv.12924 Sari HPE, Putri KA, Persada AY, Peggie D, Wafa IY (2025) Bait Preference and Butterfly Diversity (Lepidoptera: Papilionidea) caught by Bait Trap in Langsa urban Forest, Langsa, Aceh. Indonesia Treubia 50(2):125–136. https://doi.org/10.14203/treubia.v50i2.4688 Schirmer SC, Gawryszewski FM, Cardoso MZ, Pessoa DMA (2023) Melanism and color saturation of butterfly assemblages: A comparison between a tropical rainforest and a xeric white forest. Front Ecol Evol 11:932755. https://doi.org/10.3389/fevo.2023.932755 Schmitt T, Ulrich W, Büschel H, Bretzel J, Gebler J, Mwadime L, Habel JC (2020) The relevance of cloud forest fragments and their transition zones for butterfly conservation in Taita Hills, Kenya. Biodivers Conserv 29(11–12):3191–3207. https://doi.org/10.1007/s10531-020-02017-2 Schmitt T, Ulrich W, Delic A, Teucher M, Habel JC (2021) Seasonality and landscape characteristics impact species community structure and temporal dynamics of East African butterflies. Sci Rep 11(1):15103. https://doi.org/10.1038/s41598-021-94274-6 Stelbrink P, Pinkert S, Brunzel S, Kerr J, Wheat CW, Brandl R, Zeuss D (2019) Colour lightness of butterfly assemblages across North America and Europe. Sci Rep 9:1760 Teucher M, Schmitt CB, Wiese A, Apfelbeck B, Maghenda M, Pellikka P, Lens L, Habel JC (2020) Behind the fog: Forest degradation despite logging bans in an East African cloud forest. Global Ecol Conserv e01024. https://doi.org/10.1016/j.gecco.2020.e01024 Turner IM, Wong YK, Chew PT, Ibrahim AB (1997) Tree species richness in primary and old secondary tropical forest in Singapore. Biodivers Conserv 6(4):537–543. https://doi.org/10.1023/A:1018381111842 Veddeler D, Schulze CH, Steffan-Dewenter I, Buchori D, Tscharntke T (2005) The Contribution of Tropical Secondary Forest Fragments to the Conservation of Fruit-feeding Butterflies: Effects of Isolation and Age. Biodivers Conserv 14(14):3577–3592. https://doi.org/10.1007/s10531-004-0829-2 Viljur M, Abella SR, Adámek M, Alencar JBR, Barber NA, Beudert B, Burkle LA, Cagnolo L, Campos BR, Chao A, Chergui B, Choi C, Cleary DFR, Davis TS, Dechnik-Vázquez YA, Downing WM, Fuentes‐Ramirez A, Gandhi KJK, Gehring C, Thorn S (2022) The effect of natural disturbances on forest biodiversity: An ecological synthesis. Biol Rev 97(5):1930–1947. https://doi.org/10.1111/brv.12876 Wood B, Gillman MP (1998) The effects of disturbance on forest butterflies using two methods of sampling in Trinidad. Biodivers Conserv 7(5):597–616. https://doi.org/10.1023/A:1008800317279 Xing S, Bonebrake TC, Tang CC, Pickett EJ, Cheng W, Greenspan SE, Williams SE, Scheffers BR (2016) Cool habitats support darker and bigger butterflies in Australian tropical forests. Ecol Evol 6(22):8062–8074. https://doi.org/10.1002/ece3.2464 Additional Declarations No competing interests reported. Supplementary Files AppendixA.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6553277","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":465864037,"identity":"e7a6dfda-3e89-49bc-92e8-d992fb7b9f15","order_by":0,"name":"Jan Christian Habel","email":"data:image/png;base64,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","orcid":"","institution":"University of Salzburg","correspondingAuthor":true,"prefix":"","firstName":"Jan","middleName":"Christian","lastName":"Habel","suffix":""},{"id":465864038,"identity":"6bc4b658-9a48-4c1e-88d8-c86ee39bc73e","order_by":1,"name":"Thomas Schmitt","email":"","orcid":"","institution":"Senckenberg German Entomological Institute","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Schmitt","suffix":""},{"id":465864039,"identity":"42004da2-530e-425b-8ed6-834b650cf2da","order_by":2,"name":"Maria Fungomeli","email":"","orcid":"","institution":"National Museums of Kenya","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Fungomeli","suffix":""},{"id":465864042,"identity":"e2459d9b-2c36-47ac-b3e7-7ea2647ad6b6","order_by":3,"name":"Mike Teucher","email":"","orcid":"","institution":"Martin Luther University Halle-Wittenberg","correspondingAuthor":false,"prefix":"","firstName":"Mike","middleName":"","lastName":"Teucher","suffix":""},{"id":465864045,"identity":"19f8fa3c-e3e9-4709-a706-a67cda513d29","order_by":4,"name":"Jonas Eberle","email":"","orcid":"","institution":"University of Salzburg","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"","lastName":"Eberle","suffix":""},{"id":465864046,"identity":"dcb7b82c-b417-4ea3-82f7-c9814770ae96","order_by":5,"name":"Maximilian Hanusch","email":"","orcid":"","institution":"Philipps-University Marburg","correspondingAuthor":false,"prefix":"","firstName":"Maximilian","middleName":"","lastName":"Hanusch","suffix":""},{"id":465864048,"identity":"27e18dcc-50f3-41a6-9755-15d2abe5d799","order_by":6,"name":"Werner Ulrich","email":"","orcid":"","institution":"Nicolaus Copernicus University Toruń","correspondingAuthor":false,"prefix":"","firstName":"Werner","middleName":"","lastName":"Ulrich","suffix":""}],"badges":[],"createdAt":"2025-04-29 06:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6553277/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6553277/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84018925,"identity":"c988b48a-e48f-4005-b830-af9e22be7bff","added_by":"auto","created_at":"2025-06-05 19:21:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":237284,"visible":true,"origin":"","legend":"\u003cp\u003eStudy area in Kenya (star in small inlet map) and the locations of the 24 bait traps (white squares in large map) in the three different forest types, primary forest with elephants (traps 1‒8), primary forest without elephants (traps 9‒16), and secondary forest with elephants (traps 17‒24). Numbers coincide with the numbering used throughout this article.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6553277/v1/ccf7cad41f1f57b72784cc74.png"},{"id":84019407,"identity":"517aaaa7-f55f-4159-9f78-4e35e130be39","added_by":"auto","created_at":"2025-06-05 19:29:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88784,"visible":true,"origin":"","legend":"\u003cp\u003ea) Rarefaction curves (with 95 % confidence limits) for butterflies from the primary forest with elephants (blue), the primary forest without elephants (red) and the secondary forest with elephants (yellow). a), b): all species, c), d): Nymphalidae only. The numbers indicate the iChao1 richness estimates with bootstrapped lower and upper 95 % confidence limits. B) Venn diagram (colours as in a) showing the total numbers of species and the species overlap between the three habitat types.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6553277/v1/f5569419519bbea87be097e6.png"},{"id":84018834,"identity":"96dc715e-effc-43b2-a14e-bc90ba68ff94","added_by":"auto","created_at":"2025-06-05 19:13:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95851,"visible":true,"origin":"","legend":"\u003cp\u003eCorrespondence analysis of sites (a) and species (b) separated the three forest types (yellow: \u003cem\u003esec+e\u003c/em\u003e, red: \u003cem\u003eprim-e\u003c/em\u003e, blue: \u003cem\u003eprim +e\u003c/em\u003e) and the butterfly families (yellow: 6 Pieridae species, green: 24 Nymphalidae species) according to the first CA axis. c) Table plot of species communities and abundance classes (numbers of records) at the investigated sites in the three forest types. Species and sites were arranged according to the first axes of a correspondence analysis of the community data. In bold are marked three outlining plots.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6553277/v1/d026b45469d29c5f4e4f6952.png"},{"id":109759454,"identity":"a0cbc4c5-c814-414c-a736-5dcb4235b236","added_by":"auto","created_at":"2026-05-22 07:27:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":716450,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6553277/v1/84329f9a-f97f-49f1-ac73-655d1f0d9eb6.pdf"},{"id":84018839,"identity":"4d4b9781-d78b-4b7a-b2e0-20f06ccf75c4","added_by":"auto","created_at":"2025-06-05 19:13:17","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":18955,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6553277/v1/4a7684578dd34d542fd00adc.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disturbance of coastal forests in East Africa: elephants promote forest butterflies while human impact supports Savannah species","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eNumerous tropical forest ecosystems are classified as biodiversity hotspots (Mittermeier et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In East Africa, they are represented by cloud forests in the mountains and dry coastal forests along the Indian Ocean (Burgess et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). While representing a rather high diversity of endemic plant and animal species, the advanced process of forest degradation and destruction due to increasing agriculture, urbanisation, and deforestation is a severe problem for nature conservation (Newmark and McNeally, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Teucher et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, the most important disturbing species is \u003cem\u003eHomo sapiens\u003c/em\u003e. In East African forests, human disturbance includes selective logging, large-scale clearing, as well as the partial urban sprawl of a once contiguous forests (Aleman et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Fungomeli et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These activities can either cause a complete destruction of the forest or its transformation from primary into secondary forest. In general, diversity and composition of plant and animal species differ significantly between primary and secondary forests (Barlow et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007a\u003c/span\u003e). However, respective diversity assessments returned mixed results and did not unequivocally point to primary forests as being more species rich than secondary forests in the same area (Barlow et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007a\u003c/span\u003e; Castillo-Campos et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Espinosa-Palomeque et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1997\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApart from anthropogenic pressure, natural factors add to forest disturbance. In particular mega-herbivores such as elephants are known as major ecosystem engineers and to cause severe habitat modifications and may affect the local abundance and composition of plant and animal species (Fritz, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jones et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Viljur et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Such, ecosystem engineers constantly disturb the natural vegetation succession and thus contribute to the maintenance of a high level of habitat heterogeneity (Jones et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) On the other hand, Viljur et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) also provided examples where natural disturbance contributed to the extinction of typical forest species. Elephants are known to destroy African woodland sites (Jachmann and Bell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) and to decrease forest tree diversity (Maicher et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, at the same time they can also contribute to an increase in overall species diversity due to the formation of forest clearings, colonised by light-loving plant and animal species. These clearings open opportunities for many insects, particularly pollinators like bees and butterflies (Maicher et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe selected the Arabuko Sokoke forest as study areas to address these aspects. This forest is one of the largest remnants of the East African dry coastal forest and has a long history of forest management and the use of forest resources (Muriithi and Kenyon, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). One part of the Arabuko Sokoke forest (the Mida forest area) was transformed into settlement area during the 1920s, later developing into a secondary forest after being designated a protected area in the late 1970s (Mutangah and Mwaura \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1992\u003c/span\u003e, Githitho \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Ann Robertson, unpublished data). This secondary forest (below termed \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e), along with other parts of Arabuko Sokoke less affected by anthropogenic impacts (below \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e), hosts a viable population of elephants fenced in 2006, leading to population increase (Banks et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The activity of elephants strongly affects the tree composition, the tree age structure, and hence many animal and plant communities (Habel et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In a smaller part of Arabuko Sokoke primary forest, elephants have been excluded by the fencing resulting in a stronger understorey than in the elephant areas (below \u003cem\u003eprim-e\u003c/em\u003e). This variety of disturbance conditions creates a unique setup to analyse the effects of human and elephant activity on local biodiversity.\u003c/p\u003e \u003cp\u003eIn this study, we focused on butterfly (Papilionoidea) diversity in the three mentioned forest types. Butterflies are important pollinators and often depend on specific larval food plants (Boggs et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Therefore, changes in plant composition due to disturbance regimes directly affect butterfly abundance, diversity, and community composition (e.g. Moranz et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). We assessed the butterfly fauna using bait traps and compiled data on important species traits. Our major aim was to infer which of the three forest types with different disturbance histories was most diverse with respect to butterflies and where most typical forest species can be found. Second, given that elephant disturbances increase plant diversity, we expected the \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e forest being most species rich and the primary forest without elephant access (\u003cem\u003eprim-e\u003c/em\u003e) being less diverse. We also analysed which ecological groups were affected in which way by the different disturbance regimes. Therefore, our study adds knowledge about the influence of elephants on forest ecosystems.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThe Arabuko Sokoke forest is a 416 km\u003csup\u003e2\u003c/sup\u003e remnant of the East African dry coastal forest (Arabuko-Sokoke Forest Management Team, 2002). The heterogeneous geology of coastal Kenya led to the development of different forest types (Muriithi \u0026amp; Kenyon \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Here, we focus on the Mixed forest dominated by \u003cem\u003eAfzelia quanzensis\u003c/em\u003e, \u003cem\u003eHymenaea verrucosa\u003c/em\u003e, \u003cem\u003eCombretum schumannii\u003c/em\u003e, \u003cem\u003eManilkara sansibarensis\u003c/em\u003e and \u003cem\u003eEncephalartos hildebrandtii\u003c/em\u003e (Robertson and Luke, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, Fungomeli et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Arabuko-Sokoke forest has a very long history of forest management and use of forest resources. Parts of the forest were settled during the 1920s, but became later protected as a forest reserve leading to reforestation (Robertson and Luke, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Ongoing forest use comprises mining of siliceous sands, selective logging, removal of dead wood, and charcoal production (Habel et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The increasing number of elephants causes strong disturbance of forest structures and modifies floral composition across major parts of the forest (Banks et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRecording of butterflies\u003c/h3\u003e\n\u003cp\u003eThe butterfly fauna was recorded using bait traps. Bait traps are particularly suitable in tropical forest ecosystems to study butterflies, as many of them are attracted to rotten i.e. fermented fruits (Freitas et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). We run eight traps in parallel in each of the three forest types (24 in total) and checked them daily between 9 am and 5 pm in the same order. The tramps were controlled after about 24 hours (one day and one night), and were activated for eight days. Minimum distance among traps was 200 m. The traps were placed in mostly shaded but rather open areas in 1.5 m height (e.g. under a tree) to ensure that butterflies can easily access traps but also not suffer from heat and sun-exposure. Species that could not be identified directly in the field (mainly representatives of the family Pieridae and of the nymphalid genus \u003cem\u003eNeptis\u003c/em\u003e) were photographed and identified later using appropriate literature (Larsen, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The bait consisted of overripe bananas, sugar, yeast, water and palm wine (Habel et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The complete list of species and individuals collected in respective traps is given in the Appendix, Table A1.\u003c/p\u003e\n\u003ch3\u003eTraits\u003c/h3\u003e\n\u003cp\u003eBased on Larsen (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and Habel et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), each butterfly species was classified according to ecological characteristics (caterpillar food plant: monophagous: one plant species/ genus; oligophagous: various genera, one family; polyphagous: various families), geographical distribution (local: endemic to East African coastal forests, regional: restricted to eastern and southern Africa, continental: also found elsewhere in Africa or even beyond), habitat preferences, and wingspan (in mm, males only). We classified habitat preferences into typical forest dwellers, species associated with woodlands but also shrublands in savannahs, i.e. more open and anthropogenic habitats (e.g. gardens, plantations), and ubiquitous species without clear preferences. Additionally, we classified species based on five important traits: the larval diet type (mainly grasses and herbs, mixed, mainly bushes and trees), the water index (arid, intermediate, not in arid habitats), the tree association index (does not need trees, needs trees, only in forests), and the savannah and hemeroby indices. Savannah association was classified into not occurring in savannah, mainly outside savannahs, occurring in savannahs and forests, and mainly in savannahs. Hemeroby quantifies the anthropogenic influences on habitats (Jalas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1955\u003c/span\u003e; Hill et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A low hemeroby score indicates a species' strong association with natural habitats, while a high score reflects a greater reliance on anthropogenic environments. Based on their hemeroby scores, species were classified into four categories: 1) occurring exclusively in natural habitats, 2) tolerating disturbed natural habitats, 3) inhabiting both natural and anthropogenic habitats, and 4) being more prevalent in anthropogenic environments than in natural ones (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Schmitt et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Schmitt et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Classifications for all species are given in the Appendix, Table A2.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eWe used individual based rarefaction to compare species numbers among the three habitat types and estimated total richness using iChao1 (Hsieh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Evenness was assessed from the Pielou index \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003ee\u003c/em\u003e\u003csup\u003e\u003cem\u003eH\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/S\u003c/em\u003e with \u003cem\u003eH\u003c/em\u003e being the Shannon entropy and \u003cem\u003eS\u003c/em\u003e the total number of observed species. Estimates of standard errors in iChao and \u003cem\u003eJ\u003c/em\u003e came from 9999 bootstrap samples. Abundances were estimated from total samples sizes of each species.\u003c/p\u003e \u003cp\u003eAssessments of differences in species composition among the investigated sites were done by correspondence analysis (seriation) of the abundance matrix in R (v. 4.2.2; R Core Team \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) using \u003cem\u003eade4\u003c/em\u003e (v. 1.7\u0026ndash;23; Dray and Dufour \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A plot representing the relative abundance of species by sites was used to illustrate the organisation of butterfly communities. Therefore, sites and species were reordered along the plot-axes according to the first correspondence axis.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn total, we recorded 30 butterfly species, 23 species in the primary forest with elephants (\u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e), 19 species in the primary forest without elephants (\u003cem\u003eprim-e\u003c/em\u003e), and 25 species in the secondary forest with elephants (\u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). iChao1 richness estimates indicated a total of 26 species in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, 39 species in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, and 28 species in \u003cem\u003eprim-e\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Rarefaction curves of \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e and \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e intersect, in line with a fast accumulation of richness in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e and therefore a higher evenness compared to \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e. These differences were mainly due to the six Pieridae species of which five exclusively were caught in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The Pielou evenness of \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e was J\u0026thinsp;=\u0026thinsp;0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, of \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e it was J\u0026thinsp;=\u0026thinsp;0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, and 0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 for \u003cem\u003eprim-e\u003c/em\u003e, making \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e significantly more diverse and less even than both primary forests that did not significantly differ in richness and evenness at the 95% error level. Species overlap among the three study sites was 53.3% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). This percentage increased to 66.7% when excluding Pieridae (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Only the forest specialist \u003cem\u003ePseudacraea boisduvali\u003c/em\u003e was trapped exclusively in \u003cem\u003eprim-e\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumbers of records and species of major species trait categories in three forest types (\u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, \u003cem\u003eprim-e\u003c/em\u003e, and \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e). In bold are given contingency table significances among groups at P\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eRecords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eprim-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eprim-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal numbers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNymphalidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePieridae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003ePhagy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonophagous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOligophagous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolyphagous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eColour class\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e566\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e567\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e326\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e211\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e382\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e763\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eHabitat\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e365\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e384\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e157\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUbiquitous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e338\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e353\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e419\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWoodland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e79\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e227\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e524\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eDistribution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e406\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e380\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e445\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e373\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e584\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e653\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eWing length\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWing length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSample sizes were highest in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (1,100 records), intermediate in \u003cem\u003eprim-e\u003c/em\u003e (964), and lowest in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (782) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Six nymphalid species, i.e. four Charaxinae (\u003cem\u003eCharaxes protoclea, C. varanes, C. cithaeron, C. jahlusa\u003c/em\u003e), one Satyrinae (\u003cem\u003eBicyclus safitza\u003c/em\u003e) and one Biblidinae (\u003cem\u003eByblia ilithyia\u003c/em\u003e), reached high abundances in all forest types and in total accounted in each of the three type for more than 50% of all records (Table A1). Of these, \u003cem\u003eC. cithaeron\u003c/em\u003e was the only species more frequent in \u003cem\u003eprim-e\u003c/em\u003e than in the two other forest types; \u003cem\u003eC. varanes\u003c/em\u003e was most common in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e; \u003cem\u003eB. ilithyia\u003c/em\u003e and \u003cem\u003eC. jahlusa\u003c/em\u003e were the dominant species in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, while \u003cem\u003eC. protoclea\u003c/em\u003e and \u003cem\u003eB. safitza\u003c/em\u003e were more common in the two primary forest types than in the secondary forest (Table A1). Overlap (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, d) and correspondence analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) clearly separated the three forest types with respect to butterfly community composition.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese differences are reflected in the distribution of species traits, and functional trait composition significantly (at the 1% error level of contingency probabilities) differed among the three habitat types (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). More in detail, monophagous species were largely absent from the three habitat types, while polyphagous were the dominant group, but no significant difference was obtained among the habitat types (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Both primary forest types were dominated by darker colour types, while lighter coloured individuals were most common in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e. Species associated more with open landscapes (i.e. the categories wood- \u0026amp; shrubland, ubiquitous) were most common in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the latter, species of continental or even wider distribution dominated, while species restricted to eastern and southern Africa were more common in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We did not find significant differences in average wing length among the forest types, but the largest average wing size was obtained in \u003cem\u003eprim-e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumbers of records and species of the hemeroby, tree, savannah, water, and larval diet type index categories in three forest types (\u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, \u003cem\u003eprim-e\u003c/em\u003e, and \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e). In bold are given contingency table significances among groups at P\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eRecords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eprim-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esecond\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eprim-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esecond\u0026thinsp;+\u0026thinsp;e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eHemeroby\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisturbed natural habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e406\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e602\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e663\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural and anthropogenic habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e293\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e298\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e393\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon in anthropogenic habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eTree index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoes not need trees\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e129\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e249\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeeds trees\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e295\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e446\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e674\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly in forests\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e398\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e389\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e177\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eSavannah index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo savannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMainly outside savannahs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e315\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e329\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e144\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannahs and forests\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e114\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e68\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMainly savannahs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e303\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e520\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e879\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eWater index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e134\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e238\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e586\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e765\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e822\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot in arid habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e106\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eLarval diet type index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrasses and herbs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e271\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e289\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e385\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrees and Shrubs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e472\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e662\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e701\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTree and savannah indices revealed contrary patterns with savannah associated species being most common in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Species of intermediate water index occurred similarly in all three forest types. Species associated with forests (even disturbed ones) were more common in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e and \u003cem\u003eprim-e\u003c/em\u003e than in \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Larval diets differed among the forest types although this was only due to some species strictly associated with trees and shrubs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Species occurring also in anthropogenic habitats were significantly more abundant in the \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e forest than in both other forest types (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eRichness estimates did not exceed 40 butterfly species, and rarefaction analyses revealed a high degree of saturation of species numbers after just a few days of data collection for all three forest types with diverging disturbance histories (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, c). Our study design thus was able to estimate the numbers of fruit-feeding butterfly species with sufficient precision.\u003c/p\u003e \u003cp\u003eThe total number of reported species is similar to prior studies using bait traps conducted in the Arabuko Sokoke Forest (Habel et al., unpublished data) and the savannahs of southern Kenya (Habel et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Importantly, these studies mostly report species belonging to the family Nymphalidae (particularly the genus \u003cem\u003eCharaxes\u003c/em\u003e); in addition, some few individuals of the family Pieridae were retained in our study, while representatives of the families Hesperidae, Lycaenidae, and Papilionidae were not encountered in the traps (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings go in line with data from other studies using bait traps in the Neotropics (DeVries et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Freitas et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Checa et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u0026Aacute;lvarez et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), South-East Asia (Sari et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and in Europe (Jakubikova \u0026amp; Kadlec \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Thus, the overall species diversity (including nectar-feeding butterflies) definitively is much higher than the here reported numbers (see below).\u003c/p\u003e\n\u003ch3\u003eSecondary forests are “second choice” for tropical butterfly conservation\u003c/h3\u003e\n\u003cp\u003eComparing butterfly diversity in the three different forest types, it was highest in the secondary forest with elephant disturbance and lowest in the primary forest without elephants (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), a forest type that contains herb, shrub and tree layers and a plant species composition significantly differing from the two disturbed forest types (Robertson and Luke \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, Abdallah \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The here obtained results are consistent with findings from other studies analysing the effects of forest disturbance on species richness (Veddeler et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, Koh \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Apparently, forest disturbance enhances plant species richness (Rosenfield et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and subsequently various arthropod groups, including butterflies (Basset et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998\u003c/span\u003e, Wood and Gillman \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Disturbance also changes microclimatic conditions and promotes habitat heterogeneity as well as light exposure, factors important for many herbivorous insects (Viljur et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wood and Gillman \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In turn, the shadier forest climax stage is characterised by a more homogeneous vegetation structure and a lower plant species diversity (Viljur et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, we obtained a different picture if excluding Pieridae, a family not typically attracted by bait traps and therefore often excluded in the analyses of their results (DeVries et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Freitas et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). All six Pieridae species entering our traps were encountered in the secondary forest, none in \u003cem\u003eprim-e\u003c/em\u003e and one in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Thus, the higher diversity of the secondary forest was solely based on them. For Nymphalidae, i.e. the typical fruit-feeding butterflies (see above), the highest species number of 22, in contrast, was obtained in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e, while the other two forest types had 19 species. This picture also holds true for extrapolations of species numbers and other diversity estimates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Thus, if only taking the typical fruit-feeding species into account, the primary forest with elephant disturbance was most species rich, while the undisturbed primary forest and the secondary forest performed similarly.\u003c/p\u003e \u003cp\u003eDespite the difference in vegetation, the butterfly communities overlapped in their composition among the three forest types. Even in the secondary forest, only 6 out of 25 species were not found in the other forest types (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), i.e. five of the six Pieridae species as well as the Nymphalid \u003cem\u003eJunonia oenone\u003c/em\u003e. Correspondence analysis clearly separated the forest types according to family membership (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Most of the Pierids are generalists and predominantly found in more open ecosystems beyond closed forests; \u003cem\u003eJunonia oenone\u003c/em\u003e even is a typical savannah species (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Vice versa, we recorded typical forest species like \u003cem\u003eCharaxes brutus\u003c/em\u003e, \u003cem\u003eCharaxes etesipe\u003c/em\u003e and \u003cem\u003ePseudacraea boisduvali\u003c/em\u003e only or predominantly (e.g. \u003cem\u003eCharaxes cithaeron\u003c/em\u003e, \u003cem\u003eEuryphura achlys\u003c/em\u003e) in the primary forest (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferences in community structures were even more obvious when including species abundances with \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e and \u003cem\u003esec\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e being most distinguished (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For instance, the savannah species \u003cem\u003eByblia ilithyia\u003c/em\u003e and the wood- and bushland species \u003cem\u003eCharaxes jahlusa\u003c/em\u003e (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) were most dominant in the secondary forest, while the forest specialists \u003cem\u003eEuxanthe wakefieldi\u003c/em\u003e, \u003cem\u003eEuryphura achlys\u003c/em\u003e and \u003cem\u003eCharaxes cithaeron\u003c/em\u003e (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) occurred in much higher abundances in the primary forest (with and without elephants).\u003c/p\u003e \u003cp\u003eThese results clearly underline the long-lasting effects of human disturbance, well reflected in the higher proportion of disturbance indicators in the secondary forest if compared with the two types of primary forest (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the secondary forest is regaining many of the forest elements from the adjoining primary forests, several specialist forest species still were not observed there or at least at considerably lower densities, hence supporting the non-substitutable value of true primary forests. Previous studies in the Arabuko Sokoke forest based on line transects showed similar trends, with typical forest butterflies mainly inside of intact forests (Habel et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); similar findings were also made in the cloud forests of the Taita Hills (Kenya) (Schmitt et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), but also in the Amazon rainforest (Barlow et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, the higher species richness in disturbed tropical forests mostly results from the strong increase of taxa typical for more open landscapes overcompensating the loss of typical forest species (Basset et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). This again is well reflected in our data by the reducing need of the species for forests and even trees; thus, 32.9% of the species and 22.6% of the individuals in the secondary forest are not in need of trees; in the primary forest, it was 25.0% (species) and 12.5% (individuals). Hence, the typical forest species are more predominant in the primary forest, hereby underlining its considerably higher conservation value if compared with the secondary forest. Furthermore, species with smaller distribution areas dominate in the primary forest (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This example again highlights that the structure of a species community is a better indicator for defining the conservation value of a habitat than the total number of species which can rapidly change due to seasonal shifts (Devries \u0026amp; Walla 2008).\u003c/p\u003e\n\u003ch3\u003eThe “positive” and the “negative” disturbance: elephants versus humans\u003c/h3\u003e\n\u003cp\u003eSome species in our study showed a generally positive response on disturbance. However, these species in most cases are common generalists like \u003cem\u003eMelanitis leda\u003c/em\u003e which might have been favoured by the higher availability of grasses, i.e. its larval food plant (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), or even disturbance indicators like \u003cem\u003eHypolimnas misippus\u003c/em\u003e (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). However, also some forest species apparently benefited from forest disturbance in general, thus the gliding species \u003cem\u003eNeptis saclava\u003c/em\u003e which due to its behaviour prefers less dense forest structures, and \u003cem\u003eCharaxes guderiana\u003c/em\u003e, a species typical for the more open, hall-like \u003cem\u003eBrachystegia\u003c/em\u003e forests (Larsen \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, several true forest species (almost) missing in the secondary forest, like \u003cem\u003eCharaxes brutus\u003c/em\u003e, \u003cem\u003eCharaxes etesipe\u003c/em\u003e and \u003cem\u003eEuxanthe wakefieldi\u003c/em\u003e, were considerably more common in the primary forest with elephant disturbance than in the parts excluding them. This is well reflected in the percentage of individuals belonging to the truly specialised forest species, which was 14.3% in secondary forests, 38.8% in \u003cem\u003eprim-e\u003c/em\u003e and 46.7% in \u003cem\u003eprim\u0026thinsp;+\u0026thinsp;e\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This difference between the two primary forest types at the first glance seems counterintuitive. However, elephants apparently have been a permanent and long-lasting source of natural disturbance in the forests of Africa (Johnson et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Thus, the primary forest with elephant disturbance might be the forest type closest to the typical coastal forest prior to human impact, so that forest species might have adapted more to these \u0026ldquo;elephant forests\u0026rdquo; along their evolution than to the \u0026ldquo;elephant-free forests\u0026rdquo;. Consequently, natural elephant disturbance and anthropogenic disturbance might have opposed influence on specialised forest butterfly species.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDarker butterflies in \u0026ldquo;darker\u0026ldquo; forests\u003c/h2\u003e \u003cp\u003eComparatively more species with dark wings occurred in the denser forest, while those with light coloured wings were found more in the disturbed forests with lightest colours observed in the secondary forest where tree cover was lowest. A similar pattern, i.e. a positive correlation between forest density and darkness of wings, was found in tropical forests in Australia (Xing et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The reasons for this pattern are disputed. Referring to thermoregulation, Xing et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) argued that cooler habitats support darker colours as these reflect less heat, as generally shown also on the continental scale (Stelbrink et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Although our study sites are characterised by rather similar temperature regimes with average maximum temperatures ranging above 30\u0026deg;C, heat nevertheless is more buffered in the shadier forest types than in the more open disturbed ones, giving at least some support for this hypothesis also in our case.\u003c/p\u003e \u003cp\u003eHowever, Schirmer et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) also discussed differences in predator avoidance as a possible cause. They speculated that colour differences of ventral but not of dorsal wing sites might be caused by habitat specific predation risks; but this hypothesis still lacks confirmation. In addition, darker colours also seem to be related to more humid habitats at the continental scale (Stelbrink et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); this goes in line with our results as the drying after the end of the rains is slowed down with increasing shading by trees. In any case, further physiological and evolutionary studies are needed to unravel the ultimate causes behind the reported colour differences.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJCH and TS developed the study design, JCH, MF and MT collected data, WU and JE did statistical analyses, all contributed while writing this manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank the German Academic Exchange Service for funding this activity in the framework of the Biodiversity Network Biocult.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdallah AA (2017) \u003cem\u003eQuantification of change in forest structure before and after the confinement of elefants (\u003c/em\u003eLoxodanta africana, \u003cem\u003eBlumenbach) in Arabuko Sokoke Forest. Master Thesis\u003c/em\u003e. Pwani University\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAleman JC, Jarzyna MA, Staver AC (2017) Forest extent and deforestation in tropical Africa since 1900. Nat Ecol Evol 2(1):26\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41559-017-0406-1\u003c/span\u003e\u003cspan address=\"10.1038/s41559-017-0406-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Aacute;lvarez CF, Clavijo-Giraldo A, In\u0026eacute;s Uribe S, Pyrcz TW, Iserhard CA, Freitas L, A. V., Mar\u0026iacute;n MA (2021) Sampling performance of bait traps in high Andean fruit-feeding butterflies. 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Ecol Evol 6(22):8062\u0026ndash;8074. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.2464\u003c/span\u003e\u003cspan address=\"10.1002/ece3.2464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"East African dry coastal forest, disturbance, primary forest, secondary forest, habitat parameters, butterfly diversity, community structure, traits","lastPublishedDoi":"10.21203/rs.3.rs-6553277/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6553277/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnthropogenic and natural disturbances can alter the structure and composition of forest ecosystems and thereby reshape the composition of plants and animals. Conservation management needs to disentangle the impact of both types of disturbance and their effects on biodiversity. Here, we use butterfly survey data from the Arabuko Sokoke dry coastal forest (south-eastern Kenya) to infer the disturbance effects of human and elephant activities. Butterflies were assessed in primary forest with and without elephants and secondary forest with elephants using bait traps (24 traps, eight per forests type). In total, we recorded 30 butterfly species, 23 in the primary forest with elephants, 19 in the primary forest without elephants, and 25 species in the secondary forest. The three forests types with different disturbance histories differed significantly in their butterfly communities. Although secondary forest had a higher butterfly species richness than primary forest, this higher richness was solely due to a higher proportion of Savannah species. In turn, primary forests had considerably higher proportions of forest species than secondary forests, with the highest proportions in the primary forest with elephant disturbance. Our findings hence underline that habitat disturbance can cause quite different outcomings. \u003cem\u003eConservation implications\u003c/em\u003e: While anthropogenic disturbance is negatively impacting the forest butterfly community, the natural disturbance by elephant activities seems to result in habitat structures even better for the performance of the typical forest butterflies than the undisturbed and hence more dense forest. This also calls for the idea that elephants and their activities were typical for the formerly continuous East African coastal forest belt.\u003c/p\u003e","manuscriptTitle":"Disturbance of coastal forests in East Africa: elephants promote forest butterflies while human impact supports Savannah species","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-05 19:13:12","doi":"10.21203/rs.3.rs-6553277/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dad3d99c-1e5e-4cc2-9100-a091980e3a78","owner":[],"postedDate":"June 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T23:23:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-05 19:13:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6553277","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6553277","identity":"rs-6553277","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}