Butterfly-plant network in urban landscape: Implication for conservation and urban greening

Acta Oecologica 92 (2018) 16–25

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Butterfly-plant network in urban landscape: Implication for conservation and urban greening

T

Swarnali Mukherjeea, Soumyajit Banerjeea,b, Parthiba Basua, Goutam K. Sahaa, Gautam Adityaa,∗ a b

Department of Zoology, 35, Ballygunge Circular Road, University of Calcutta, Kolkata, 700019, India P.G. Department of Zoology, Serampore College, Serampore, West Bengal, 712201, India

A R T I C LE I N FO

A B S T R A C T

Keywords: Mutualistic networks Butterfly-plant interaction Nestedness Specialization index Conservation

Butterflies (Insecta: Lepidoptera) contribute to the ecosystem services and thereby qualify as a group deserving conservation effort. Information on the butterfly-plant links is used as a foundation to sustain population and enhance conservation and management. Thus, in the present study, the structure of a butterfly-plant network in an urban landscape like Kolkata, India, was deciphered highlighting metrics like degree distribution, nestedness, and interaction strength and specialization index. A total of forty eight butterfly species associated with thirty different angiosperm plant species were observed during the study period of one year. While Lantana camara was observed to be the dominant plant species with 37 links to different butterflies, the Catopsilia pyranthe butterfly species was dominant in terms of the generalist pattern of links (21 links) with the plants. Differential ability of the shrubs and herbs in the sustenance of the butterflies was reflected in the network indices using the herbs and the shrubs, separately. In urban landscapes with restricted variety of flowering plants, an estimate of relative strength of interactions enables identification and further use of the concerned species in sustaining butterfly populations. In accordance with these propositions, the butterfly-plant network illustrated in the present instance may prove useful in selection of plant species required for the enhancement of population of desired butterfly species in urban areas like Kolkata, India.

1. Introduction Insect mediated pollination is a key ecosystem service that facilitates the sexual reproduction of different crops (Nabhan and Buchmann, 1997; Westerkamp and Gottsberger, 2000) and wild plants (Larson and Barrett, 2000; Ashman et al., 2004). As a result, food security and environmental quality are retained, benefiting human wellbeing (Knight et al., 2005). Among insects, butterfly qualifies as an important pollinator of different plants. Coevolution of many plants and butterflies has resulted in development of specific plant features which in turn encourage the butterflies to utilize the flowers (Edger et al., 2015). Butterflies serve as indicator of the climate change as well as changes associated with natural and anthropogenic disturbances (Vickery, 2008). In many instances, the decline in the butterfly fauna is attributed to a corresponding decline in nectar-rich and economically important wild plant species (Gillespie and Wratten, 2012). The distribution and diversity of the butterflies and plants are pre-requisite for framing the strategies of conservation, particularly for the urban ecosystems. This proposition is based on the previous studies that indicate

that urbanization affects biodiversity patterns (Pauchard et al., 2006) including diversity of butterflies (Bergerot et al., 2011). Empirical studies have shown that the small patches of gardens (Fontaine et al., 2016; Tam and Bonebrake, 2016) and forests (Soga and Koike, 2012; Lee et al., 2015) in the urban areas are valued spaces for sustenance of butterflies. However, conservation planning in such habitat patches requires the information on the butterfly and plant species assemblages of the concerned area. In Kolkata, India, the diversity of the butterfly and associated plants has been recorded in the recent past (Mukherjee et al., 2015, 2016). An extension of such study was made in the present instance, where the links between the specific butterfly species and the plant species are highlighted through a network of butterfly-plant interactions. Ecological network analysis characterizes the interactions among species or guilds and provides complementary information on species organization and community structure (Ings et al., 2009; Fortuna et al., 2010). Analysis of ecological interaction network aid in determining community assemblage and robustness, resource partitioning, and associations among component species (Montoya et al., 2006; Santamaría

∗

Corresponding author. E-mail addresses: [email protected] (S. Mukherjee), [email protected] (S. Banerjee), [email protected] (P. Basu), gkszoo@rediffmail.com (G.K. Saha), [email protected] (G. Aditya). https://doi.org/10.1016/j.actao.2018.08.003 Received 11 March 2018; Received in revised form 24 July 2018; Accepted 6 August 2018 1146-609X/ © 2018 Elsevier Masson SAS. All rights reserved.

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2.3. Sampling techniques

and Rodríguez-Gironés, 2007). Network ecology is useful in framing the conservation strategies (Kaiser-Bunbury and Blüthgen, 2015; Harvey et al., 2017) as it provides a basic architecture to the levels of biodiversity of the groups involved in mutualistic interactions. Using the indices like connectance and links, the network facilitates identification of the degree of specialization among the interacting species. As a consequence, the network may help decipher the architecture and the functional diversity of the species concerned at the proximate level. In the recent past, network analysis has been widely useful to the study of plant–pollinator or plant‒insect interactions (Bascompte et al., 2003; Vázquez and Aizen, 2004; Santamaría and Rodríguez-Gironés, 2007; Ramos-Jiliberto et al., 2009; Olesen et al., 2011). Among the various networks, the bipartite network (in ecology mainly interaction networks with two trophic levels) utilizes newer indices (Bersier et al., 2002; Blüthgen et al., 2006) that facilitates portrayal of the relationships among the constituents of the ecological community (Blüthgen et al., 2007, 2008) and the connection between land use/landscape structure, network structure and ecosystem function (Kaiser-Bunbury and Blüthgen, 2015; Harvey et al., 2017). In the present instance, information on the richness and abundance of butterflies and plants of Kolkata, India, was used to construct a bipartite network. The indices of the network were used to justify the specialist or generalist nature of the butterflies in the context of plant resources utilization pattern. In addition, the nestedness feature of the network would reflect the extent of the generalist butterflies present in the community. Information obtained through the network analysis would be useful in conservation management of butterflies in the long run, since the role of the specific plants as organizer of the butterfly species assemblage can be identified and subsequently used in the enhancement of the butterfly community. In urban ecosystem, the anthropogenic activities decrease the butterfly diversity due to systemic elimination of several nectar rich and economically important wild species (Gillespie and Wratten, 2012). Further, owing to space limitation (Fontaine et al., 2016; Tam and Bonebrake, 2016), conservation effort in urban areas calls for selection of plant species that are preferred by the butterflies. Thus, one of the objectives of the study will include identification of the flowering plants and their relative importance in the sustenance of the butterflies as deduced through the indices of the bipartite network. Apart from indicating the abundance of the generalist species of butterflies, the results are expected to highlight whether the herbs and the shrubs bear differential consequences to the status of butterflies as generalist or specialist. The information will be useful for the conservation and enhancement of the ecosystem services attributable to the butterfly in urban scenario of Kolkata metropolis.

In each sampling site the butterflies were recorded following ‘Pollard Walk’ method (Pollard, 1977; Pollard and Yates, 1993) with required modifications. For each site, five transect paths were considered, comprising of 1000 m in length with a minimum of 500 m gap between two transects (Mukherjee et al., 2015, 2016). Among the butterflies, those that placed their proboscis within the respective flowers of a plant were taken into consideration only. In instances where the butterfly sat on the flower without any activity, were not counted and excluded from analysis. During each visit, a single plant species was observed for 15 min for recording butterfly species. Observations of butterflies were restricted to only flowering branches of the plants positioned up to 4 m height (Smith-Ramírez et al., 2005). Data on plant habits, flowering period and flower colour were also recorded for the present study. The plants were identified up to their respective families and species using appropriate keys (Kehimkar, 2000; Paria, 2005, 2010). 2.4. Data analysis The interaction matrix of plant and butterfly was arranged in two ways. The weighted matrix included frequency of interaction of each butterfly species on each plant species and the unweighted or qualitative matrix with data of presence/absence of the butterfly species on plant species. The indices like connectance, generality, vulnerability, nestedness, degree of distribution were used for qualitative analysis (Blüthgen et al., 2008) and the indices namely weighted connectance, links per species, weighted NODF, specialization asymmetry, degree of complementary specialization (H2’), number of shared partner, interaction strength, interaction evenness were used for weighted matrix (Blüthgen et al., 2008; Dormann et al., 2008, 2009). The connectance, C, was calculated as C = L/IJ, where, L describes the number of realized links, I and J were the number of plant and butterfly species respectively (Jordano, 1987). The connectance was interpreted as the degree of generalization or redundancy in a system, with consequences for community stability (Estrada, 2007). Therefore, in the absence of sampling limitation, the expected connectance was assumed to be, C = 1. The nestedness was calculated by comparing system temperature, T (Atmar and Patterson, 1993) with values ranging from 0° to 100° the level of nestedness, N = N (100 - T)/100, with values ranging from 0 to 1 (maximum nestedness) (Bascompte et al., 2003). The nestedness was calculated using the NESTEDNESS CALCULATOR software and was represented graphically with the plant species and butterfly species were denoted by x-axis and y-axis respectively (Atmar and Patterson, 1993). In addition to the graph, a z-score was used to test the probability levels (using software package NeD (nestedness for dummies) (Strona and Fattorini, 2014)). Usually NODF (nestedness measure based on overlap and decreasing fills) (Almeida-Neto et al., 2008) and matrix temperature were used to measure nestedness (Almeida-Neto et al., 2008; Strona et al., 2014a; b). The degree distribution of each species was calculated on the basis of the number of links per species in the unweighted matrix. However, the unweighted matrix represented the scenario of plant–animal network in a limited way. In this qualitative approach, interactions between a consumer and a resource species are only scored in a binary way as 'present' or 'absent', ignoring any distinction between strong interactions and weak or occasional ones (Blüthgen et al., 2006). In interaction networks, the quantitative interaction strength (bij) represents the proportion of interactions involving ith species with a specific partner (jth species) among the total possible interactions. (Jordano, 1987; Bascompte et al., 2006). The weighted matrix was treated as bipartite network and the bipartite graph and all the indices were calculated in the R software (Chambers, 2008) with bipartite package (Dormann et al., 2008, 2009). As, level of community, the degree of complementary species (H2′) for entire network was

2. Materials and methods 2.1. Sampling site Three sampling sites were randomly selected from Kolkata Metropolitan Area (KMA), Kolkata, India. The survey was conducted around a central point of selected study sites. The central points were Talapark (22° 36′ 28.9692″ N, 88° 23′ 1.878″ E), Rabindra Sarobar (22° 30′ 44.0028″ N, 88° 21′ 49.482″ E) and Beliaghata (22° 34′ 1.3224″ N, 88° 23′ 34.908″ E), Kolkata.

2.2. Sampling period and time The nectar feeding butterflies were observed in the sampling sites for a period of one year between September 2012 and August 2013. Each study site was visited once in a month and transects ware observed from early morning (07:00 h) to afternoon (17:00 h) during good weather periods without heavy rain or strong wind. 17

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Table 1 The list of the butterflies observed in the urban areas of Kolkata, India, during the study period. The acronym and the family of the butterflies are also mentioned apart from the scientific names and the common names. Scientific Name

Acronym

Common Name

Family

Graphium doson (Felder and Felder, 1864) Graphium agamemnon (Linnaeus, 1758) Chilasa clytia (Linnaeus, 1758) Papilio polytes (Linnaeus, 1758) Papilio polymnestor (Cramer, 1775) Papilio demoleus (Linnaeus, 1758) Pachliopta aristolochiae (Fabricius, 1775) Eurema hecabe (Linnaeus, 1758) Catopsilia pomona (Fabricius, 1775) Catopsilia pyranthe (Linnaeus, 1758) Ixias pyrene (Linnaeus, 1764) Pareronia valeria (Cramer, 1776) Appias libythea (Fabricius, 1775) Cepora nerissa (Fabricius, 1775) Delias eucharis (Drury, 1773) Leptosia nina (Fabricius, 1793) Tirumala limniace (Cramer, 1775) Danaus genutia (Cramer, 1779) Danaus chrysippus (Linnaeus,1758) Euploea klugii (Moore and Horsfield, 1857) Euploea core (Cramer, 1780) Elymnias hypermnestra (Linnaeus, 1763) Ypthima baldus (Fabricius, 1775) Ypthima huebneri (Kirby, 1871) Acraea violae (Fabricius, 1775) Phalanta phalantha (Drury, 1773) Euthalia aconthea (Cramer, 1779) Ariadne ariadne (Linnaeus, 1763) Ariadne merione (Cramer, 1779) Junonia almana (Linnaeus, 1758) Junonia atlites (Linnaeus, 1763) Junonia lemonias (Linnaeus, 1758) Hypolimnas bolina (Linnaeus, 1758) Hypolimnas misippus (Linnaeus, 1764) Rathinda amor (Fabricius, 1775) Spindasis vulcanus (Fabricius, 1775) Anthene lycaenina (Felder, 1868) Anthene emolus (Godart, 1824) Castalius rosimon (Fabricius, 1775) Tarucus nara (Kollar, 1848) Neopithecops zalmora (Butler, 1870) Tarucus plinius (Fabricius, 1793) Badamia exclamationis (Fabricius, 1775) Hasora chromus (Cramer, 1780) Parnara guttatus (Bremer and Gray, 1853) Borbo cinnara (Wallace, 1866) Iambrix salsala (Moore, 1865) Suastus gremius (Fabricius, 1798)

GDO GAG CCL PPO PPOL PDE PAR EHE CPO CPY IPY PVA ALI CNE DEU LNI TLI DGE DCH EKU ECO EHY YBA YHU AVI PPH EAC AAR AME JAL JAT JLE HBO HMI RAM SVU ALY AEM CRO TNA NZA TPL BEX HCH PGU BCI ISA SGR

Common jay Tailed Jay Common Mime Common Mormon Blue Mormon Lime Butterfly Common Rose Common Grass Yellow Common Emigrant Mottled Emigrant Yellow Orange-tip Common Wanderer Striped Albatross Common Gull Common Jezebel Psyche Blue Tiger Striped Tiger Plain Tiger Brown King Crow Common Crow Common Palmfly Common Five-ring Common Four-ring Tawny Coster Common Leopard Common Baron Angled Castor Common Castor Peacock Pansy Gray Pansy Lemon Pansy Great Eggfly Danaid Eggfly Monkey Puzzle Common Silverline Pointed Ciliate Blue Common Ciliate Blue Common Pierrot Striped Pierrot Quaker Zebra Blue Brown Awl Common Banded Awl Straight Swift Rice Swift Chestnut Bob Indian Palm Bob

Papilionidae Papilionidae Papilionidae Papilionidae Papilionidae Papilionidae Papilionidae Pieridae Pieridae Pieridae Pieridae Pieridae Pieridae Pieridae Pieridae Pieridae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Nymphalidae Lycaenidae Lycaenidae Lycaenidae Lycaenidae Lycaenidae Lycaenidae Lycaenidae Lycaenidae Hesperiidae Hesperiidae Hesperiidae Hesperiidae Hesperiidae Hesperiidae

3. Results

measured, derived from Shannon-Weiner diversity index, and compared for the deviation from null model I or Paterfield algorithm (Blüthgen et al., 2006, 2007, 2008) which indicates the value 0 (maximum generalization) to 1 (maximum specialization). The degree of specialization (d’) (also called Kullback-Leibler distance) of the butterfly species was calculated to represent the specialization on the basis of the frequency of the total number of the interactions in the network (Blüthgen et al., 2006). Low interaction evenness (E2) depicts a high variation in interaction frequencies between different species pairs. This may translate into relative contributions to ecological functions, particularly when the recorded interactions are representative for the community. The importance of wild herb and shrub for maintaining butterfly population and the effects of each group loss on the network topology were evaluated through nestedness and different indices through removal and substitution for each of the plant group following Ramos-Jiliberto et al. (2009) with required modifications.

In the present study, 48 species of butterflies belonging to 5 families (Table 1) were recorded from the urban areas of Kolkata, India. At the family level, 18 (37.5%) out of 48 species belonged to Nymphalidae, while, 9 (18.75%) species to Pieridae, 8 (16.66%) species to Lycaenidae, 7 (14.58%) species to Papilionidae and 6 (12.5%) species to Hesperiidae. Among the plants, there were 15 herbs, 11 shrubs and 4 species of woody trees under 18 families (Table 2), which were considered as food resource by the adult butterflies. The butterfly-plant network included 48 butterfly species and 30 plants species (nodes) showing 417 mutualistic interactions (links). The results of the unweighted matrix (Table 3a) indicate that the network connectance was 0.62 and this metric was bent towards generalization (> 0.5). The same effect applies to metrics such as generality, vulnerability, or linkage density of unweighted links, as they are directly related to C for a given network size. The actual interaction matrix was presented in Fig. 1 where shaded box indicated the actual interacting pair. Nestedness was represented

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Table 2 The list of the plant species observed during the study in the urban areas of Kolkata. The name of the plant species along with the acronym, the family and the flowering time and flower colour are also mentioned. Scientific Name

Acronym

Family

Habit

Flowering Time

Flower colour

Lantana camara L Mikania cordata (Burm.f.) Roxb Zizyphus mauritiana var. fruticosa (Haines) Seb. and Balak Tridax procumbens L Clerodendrum viscosum vent Ixora coccinea L. Pluchea indica Less Ageratum conyzoides L. Gomphrena globosa. L. Citrus limon L. Glycosmis pentaphylla Hook. f. Zizyphus oenoplia L. Heliotropium indicum L. Polygonum barbatum L. Cleome rutidosperma DC Cleome viscosa L. Crotalaria pallida Ait Flacourtia indica (Burm. f.) Merr. Gomphrena celosioides Mart Alternanthera sessilis (L.) DC. Abutilon indicum G.Don Sida rhombifolia L. Vandellia crustacea. L. Vernonia cinerea (L.) Less Leucas aspera (Willd.) Link Terminalia catappa L. Catharanthus roseus (L.) G.Don Parthenium hysterophorus L. Carica papaya L. Kyllinga nemoralis (Forst. & Forst.)

LCA MCO ZMA TPR CVI ICO PIN ACO GGL CLI GPE ZOE HIN PBA CRU CVIS CPA FIN GCE ASE AIN SRH VCR VCI LAS TCA CRO PHY CPAP KNE

Verbenaceae Asteraceae Rhamnaceae Asteraceae Verbenaceae Rubiaceae Asteraceae Asteraceae Amaranthaceae Rutaceae Rutaceae Rhamnaceae Boraginaceae Polygonaceae Cleomaceae Cleomaceae Fabaceae Fabaceae Amaranthaceae Amaranthaceae Malvaceae Malvaceae Linderniaceae Asteraceae Lamiaceae Combretaceae Apocynaceae Asteraceae Caricaceae Cyperaceae

Shrub Herb Tree Herb Shrub Shrub Shrub Herb Herb Tree Shrub Shrub Herb Herb Herb Herb Shrub Shrub Herb Herb Shrub Shrub Herb Herb Herb Tree Shrub Herb tree Herb

Jan–Dec July–Dec Jul–Dec Jan–Dec Feb–Jul Jan–Dec Oct–Jan Aug–Nov Feb–Jun Apr–Jun Jul–Feb Jul–Dec Feb–Oct Apr–Jul Aug–Jan Apr–Jul Oct–Dec Feb–April Dec–May Mar–Jun Aug–Dec Aug–Feb Jun–Nov Sept–Mar Aug–Sept May–Aug Jan–Dec Jan–Dec Jan–Dec Jul–Mar

Orange yellow, pink White Yellow Yellowish white White tinged with violet Red, yellow or pink White to yellow Blue or White Purple, red White White Yellow Purple white White Pink to pale violet Yellow Yellow Yellow White White Orange-yellow Yellow Pink Pinkish violet White Pale yellowish white Rose or white White White White

Lantana camara on Ariadne merione (0.05), Tridax procumbens on Anthene lycaenina (0.10), Glycosmis pentaphylla on Neopithecops zalmora (0.23) and specially Ixora coccinea on Rathindra amor (0.14). As the dependency of a particular butterfly species on a particular plant species and vice versa were not equal, this butterfly-plant network formed asymmetry of interaction strength. Several metrics based on the indices for weighted matrix was presented in Table 3b. Interaction diversity (H2) and interaction evenness (E2) for butterfly species were also measured and presented in Table 3c. H2 and E2 of the whole network were 5.54 and 0.903 suggested that there were low variation in interaction frequencies between different species pairs. The degree of specialization shown by the frequency-based index H2' (standardized twodimensional Shannon entropy, Network-level index) was low in the present study (H2' = 0.27) and the standardized Kullback-Leibler distance, d' (species-level specialization) was also low (d’ butterfly = 0.19) and the whole network was dominated by mostly generalized butterflies and nested. The abundance of butterflies and degree of each butterfly species and strength of each butterfly species was correlated (Fig. 4). The results of the one-way factorial ANOVA indicated significant differences in abundance, degree and interaction strength of different species of butterflies with the family level as explanatory variables (Table 4). The statistical analyses were carried out following Zar (1999) using the SPSS version 10 (Kinnear and Gray, 2000). The removal of herb or shrub group from butterfly –plant community altered the topology of network structure (Table 5). The unweighted matrix showed a higher value of NODF in case of herb-butterfly network than shrub-butterfly network. The value of specialization index (H2’) was increased in shrub-butterfly network indicating presence of more specialized species than herbs-butterfly network.

on the basis of presence absence data. The box of Fig. 2a outlined the central core of maximally packed butterfly-plant network and the left side of the line represented the perfect nestedness. In this network nestedness was 0.73 and the maximally packed metric showed that the butterfly-plant interactions were more or less nested. By using NeD software (Strona et al., 2014a), it is found that the z score (−2.755) of matrix temperature (41.544) was significantly nested (p < 0.01). Degree k also describes the number of links of each species and here butterfly species and their degree k was simply represented in Fig. 2b and pointed out that all 48 species butterfly species had at least one link and one butterfly species had maximum twenty one links. On the basis of weighted links the bipartite representations of butterfly-plant network was shown in the graph (Fig. 3), where butterfly community (maroon) was represented in the upper level and plant community (green) in the lower level. Each butterfly and plant species was indicated through box with its acronym (illustrated in Tables 1 and 2). The box size was proportional to the total number of visits recorded and link breadth to the frequency of the particular association. The graph represented each pair of butterfly plant interaction. The interaction strength (bji and bij) measured the dependence of butterfly species (j) on its plant partner (i) and dependence of plant species (i) on its butterfly partner (j) respectively. Results of (bji), indicated that butterfly species Papilio polymnestor equally depended on Lantana camara and Ixora coccinea (0.5) but dependency of Ixias pyrene on Lantana camara (0.80), Pareronia valeria on Ixora coccinea (0.59), Ariadne merione on Lantana camara (0.65), Anthene lycaenina on Tridax procumbens (0.61), Neopithecops zalmora on Glycosmis pentaphylla (0.88) and Rathindra amor on Ixora coccinea (1.00) were very high (> 0.5) and these butterflies were moved towards specialization on the respective flowering plants. But the results (bij) showed that these plants were not equally dependent on the respective butterflies i.e., interaction strength of Lantana camara and Ixora coccinea on Papilio polymnestor were 0.003 and 0.02 respectively. A similar trend was found for the case of Lantana camara on Ixias pyrene (0.05), Pluchea indica on Pareronia valeria (0.02),

4. Discussion In view of the multifunctional roles and the ecosystem services provided by the butterflies, conservation management is given priority 19

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Table 3 The values of the indices of butterfly-plant network based on the observations from Kolkata, India. (a). Indices based on unweighted links, (b). Indices based on weighted links, and (c). The Shannon diversity of links (Hi) and interaction evenness (Ei) for each species of butterfly. a Connectance Linkage density Generality Vulnerability Nestedness

0.62 2.95 9.2 4.33 0.73

b Connectance Links per species Weighted NODF Specialization asymmetry Shannon diversity H2′ d’ mean.number.of.shared.partners generality interaction strength asymmetry interaction evenness

0.28 5.34 29.41 −0.115 5.62 0.277 0.19 3.68 7.879998 0.040252 0.773047

c

GDO GAG CCL PPO PPOL PDE PAR EHE CPO CPY IPY PVA ALI CNE DEU LNI TLI DGE DCH EKU ECO EHY YBA YHU

Hi

Ei

1.83 1.60 1.54 −1.03 0.60 −0.94 1.51 1.98 −1.53 −0.97 0.50 1.21 2.00 1.58 0.51 0.00 1.98 1.37 1.25 1.24 1.16 1.82 1.65 1.39

0.88 0.77 0.86 −0.42 0.86 −0.37 0.84 0.73 −0.54 −0.32 0.28 0.88 0.87 0.66 0.26 0.00 0.82 0.71 0.49 0.77 0.45 0.87 0.85 0.78

AVI PPH EAC AAR AME JAL JAT JLE HBO HMI RAM SVU ALY AEM CRO TNA NZA TPL BEX HCH PGU BCI ISA SGR

Hi

Ei

1.30 1.55 1.77 0.62 0.78 −0.47 −0.55 1.40 1.43 1.25 0.73 1.39 1.31 1.81 2.48 2.03 0.93 1.34 1.90 1.55 2.00 1.96 1.24 1.03

0.56 0.80 0.85 0.27 0.38 −0.19 −0.21 0.87 0.74 0.78 0.00 0.86 0.73 0.82 0.91 0.85 0.84 0.64 0.86 0.80 0.83 0.82 0.89 0.57

Specialization index

Comparison with random matrices

H2' = 0.27 H2obs = 5.54 H2min = 3.66 H2max = 6.23

Tobs = 4530.94 Tran = 3469.76 ± 18.18 H2obs = 5.54 H2ran = 6.03981 ± 0.0085 H2ran < H2obs: 0% H2ran = H2obs: 0% H2ran > H2obs: 100% (same proportions apply to Tran vs. Tobs) p < 0.0001 (10000 randomizations performed)

in many parts of the world, including India. As a flagship species (New, 1997), butterflies enable sustenance of plants of different taxonomic identity and thereby provide impetus for the development of a better community structure and functions. Estimation of the species diversity of the butterflies in the urban areas of the temperate (Simonson et al., 2001[Colorado, USA]; Kitahara and Sei, 2001 [central Japan], Schneider and Fry, 2001[Sweden], Ouin and Burel, 2002 [France], Öckinger et al., 2009 [Sweden]) and the tropical countries (Ӧzden et al., 2008 [Cyprus], Bossart et al., 2006 [Ghana]) provide evidence of the increasing effort towards conservation of the butterflies in the

respective areas. At the proximate level, the butterfly diversity increases with the heterogeneity of the vegetation (Maccherini et al., 2009; Ferrer-Paris et al., 2013), even for the low intensity agricultural (Loos et al., 2014) and forest landscape (Liivamägi et al., 2014). The agricultural landscapes are dominated by a single or few species of choice in contrast to the open spaces where species colonization and establishment is guided by the natural factors (Loos et al., 2014). In essence, the general norm is that the increase in the plant species assemblages increases the diversity of the butterfly in unit area (Maccherini et al., 2009; Ferrer-Paris et al., 2013). However, in view of 20

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Fig. 1. Matrix showing the interactions between plants and butterflies. The actual interactions were presented by shaded portions.

Fig. 2. a. The nestedness pattern of plant butterfly network. . the degree of distribution of.each butterfly species.

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Fig. 3. The bipartite graph of plants (green) and butterflies (maroon). The links were weighted and each link breadth was proportional to the frequency of the particular association. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

(Porter et al., 1992), habitat fondness with availability of food plants (Tudor et al., 2004; Stefanescu and Traveset, 2009). Although not elaborated, such factors may be crucial in shaping the butterfly-plant interactions as illustrated in the present network. However, the normalised degree and interaction strength of each butterfly were correlated with log abundance of butterflies (Fig. 4) which indicated that the butterflies exploring varied type of flowers were more abundant. Usually, network of floral visitor and plant show a nested pattern and intermediate level of specialization (Blüthgen et al., 2007). The nestedness represents asymmetries in abundance (Blüthgen et al., 2008; Blüthgen, 2010), which reflects few species with many links and many species with few links (Bascompte and Jordano, 2007), in the butterflyplant network of the present instance. The role of the butterflies in the pollination of the concerned plant can be evaluated through the links with the different plant species. In the present study, specialization index (H2’ = 0.27) value indicates the presence of generalist butterfly. Recently, many studies have established that ecological, phylogenetic (Cagnolo et al., 2011), anthropogenic features (Geslin et al., 2013) influence the topology of plant herbivore interaction networks. Even temporal difference in the quality and availability of food (Murakami et al., 2008; Barber and Marquis, 2011) or habitat structure (Lewinsohn et al., 2005) also regulate the properties of species interaction networks.

restricted habitat patches in urban areas (Soga and Koike, 2012; Lee et al., 2015; Fontaine et al., 2016; Tam and Bonebrake, 2016), enhancement of butterfly population can be facilitated through selection of plants that are linked with higher number of butterfly species. Thus, the estimates of the butterfly-plant network appear to be useful in deciphering the species specific information on the links and relative importance. The butterfly species diversity of the concerned area suggests that at least 96 species are available in varying relative density (Mukherjee et al., 2015). Among these, 48 butterfly species were encountered strictly from the urban areas, linked to about 30 plant species (Tables 1 and 2). The links between the constituent butterfly and plant species of this urban assemblage were elaborated through the bipartite network (Figs. 1 and 3). Apart from the differences in the relative abundances of butterfly and plant, the preference for the flowering plants by the butterflies (Hardy et al., 2007), accounted for the differences in the degree distribution and interaction strength (Table 4) features of the network. In a particular area, the preference of butterflies for certain flowers depend on various factors like flower colour (Tiple et al., 2006, 2009; Pohl et al., 2011; Cepero et al., 2015), floral pattern (Jennersten, 1984), nectar concentration (May 1985; Tiple et al., 2006), compatibility between flower traits and butterfly traits (Bauder et al., 2015), synchronization between flowering time and adult butterfly occurrence

Fig. 4. Correlation between log abundance of butterflies and normalised degree (deg, D) and interaction strength (str, S) of each butterfly. 22

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Table 4 The results of one-way factorial ANOVA on the abundance of butterflies (a), on the normalised Degree of butterflies (b), and on the interaction strength of butterflies (c) considering family as explanatory variables along with the results of post hoc Tukey test between the families of butterfly. The values in bold indicate significant at P < 0.05 level.

Table 5 Comparison of herb-butterfly and shrub-butterfly communities based on the nestedness and indices analysis for networks structured following removal of respective plant group (herb and shrub). Unweighted matrix

a Source

Sum of squares

df

Mean squares

F

Abundance Error Total Contrast Papilionidae vs Hesperiidae Papilionidae vs Lycaenidae Papilionidae vs Nymphalidae Papilionidae vs Pieridae Pieridae vs Hesperiidae

4.913 0.418 5.332 |difference| 19.18

4 43 47

1.228 0.01

126.276

Contrast Pieridae vs Lycaenidae Pieridae vs Nymphalidae Nymphalidae vs Hesperiidae Nymphalidae vs Lycaenidae Lycaenidae vs Hesperiidae

|difference| 11.685

15.899 11.536 5.061 15.408

Only herb-butterfly community Only shrub-butterfly community

Only herbbutterfly community Only shrubbutterfly community

7.271 4.523

df

Mean squares

F

Normalised Degree Error Corrected Total Contrast Papilionidae vs Lycaenidae Papilionidae vs Hesperiidae Papilionidae vs Nymphalidae Papilionidae vs Pieridae Pieridae vs Lycaenidae

0.473 0.336 0.809 |difference| 6.869

4 43 47

0.118 0.008

15.138

Contrast Pieridae vs Hesperiidae Pieridae vs Nymphalidae Nymphalidae vs Lycaenidae Nymphalidae vs Hesperiidae Hesperiidae vs Lycaenidae

|difference| 3.418

3.966

1.488 3.106 2.533 0.233

Source

Sum of squares

df

Mean squares

F

Interaction Strength Error Corrected Total Contrast Papilionidae vs Hesperiidae Papilionidae vs Lycaenidae Papilionidae vs Nymphalidae Papilionidae vs Pieridae Pieridae vs Hesperiidae

6.236 6.972 13.207 |difference| 5.335

4 43 47

1.559 0.162

9.615

Contrast Pieridae vs Lycaenidae Pieridae vs Nymphalidae Nymphalidae vs Hesperiidae Nymphalidae vs Lycaenidae Lycaenidae vs Hesperiidae

|difference| 2.264

4.775 3.006 2.758

Nested?

NODF T NODF T

61.565 15.944 47.884 30.233

6.637 5.862 0.722 3.203

0.564 0.625 0.049 0.321

Yes (p < 0.001) Yes (p < 0.001) No (p > 0.05) Yes (p < 0.001)

Weighted nestedness

Weighted NODF

Interaction strength asymmetry

H2

0.293333

0.637746

31.96149

0.117794

0.298

0.375

0.413594

29.66861

0.161894

0.32277

urban landscape like Kolkata, India, was measured by constructing two separate interaction matrices through selection of specific plants of each group (Table 5). The NODF value or nestedness values differed in herb-butterfly network and shrub-butterfly network. The value of specialization index (H2’ = 0.32) was higher in shrub-butterfly network than the value (H2’ = 0.29) of herb-butterfly network, indicating that the wild herbaceous plants support more butterflies. Such disparity in the specialization pattern provides evidence for the prospective impact of the butterflies in alteration of the habitat conditions and the community structure. Urbanization affects herb richness and abundance (Cameron et al., 2015) which facilitates the presence of the arboreal butterflies but reduces the abundance of the grassland butterfly in the urban gardens (Konvicka and Kadlec, 2011). Considering the management of the forests and urban greening, assessment of the plants as the host of the different butterflies is essential, since the plantation system should be developed in such a way that these act as resource for the butterflies and enable sustenance of both the groups in the concerned space. In the present instance, the network (Bascompte et al., 2006; Kaiser-Bunbury and Blüthgen, 2015) enabled recognizing the abundance and species composition that would help selecting the plants required for the conservation of the target butterfly species. The data on the frequency of visit in flowering plants by butterflies may aptly represent the extent of interaction in a butterfly-plant network (Vázquez et al., 2005, 2009), but may not represent the extent of pollination accomplished (King et al., 2013). Nonetheless, the association of the butterflies with the concerned plants is crucial in justifying the requirements of the green plants in enhancement of butterfly populations. The links are important for identifying the plant species required for the propagation and the sustenance of the butterfly species in the concerned area. Assuming the correspondence of the diversity of the plants and butterflies to be a general norm (Maccherini et al., 2009; FerrerParis et al., 2013), the plants with higher number of links to butterflies deserve preference for the enhancement of the butterfly population. Following selection of the plant species, augmentative plantations in the requisite spaces of the urban areas may be initiated. The resultant effort may not only enhance butterfly population but also preserve and boost the much needed urban green. Thus, the information from the butterfly-plant network in an urban landscape like Kolkata, India appears to supplement and facilitate strategies for conservation of butterflies and different wild, naturally growing plants species. Similar studies on the sub-urban and rural areas may be initiated to validate the

c

5.052

RN

11.736

Sum of squares

3.23

Z-Score

Connectance 6.34

Source

5.019

Index

Weighted matrix

b

6.164

Metric

1.5 1.785 1.148 0.655

Tukey's d critical value: 4.026.

The functional role of the butterflies may be related to the pollination of plants and with the oviposition site and larval development. Consequently, the plant species selection for the enhancement of the butterfly population is considered to be significant. In absence of butterflies, pollination may be accomplished by other species associated with the plants, but for the butterflies, the availability of the plants is essential for the propagation and life history completion. Thus the significance of the network analysis is more relevant from the viewpoint of the butterfly species management than considering the propagation of the plants in a concerned landscape. The relative importance of herb and shrub group for maintaining butterflies in an 23

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use of butterfly-plant network as a foundation for conservation butterfly and enhance greenery.

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5. Conclusion A total of 48 butterfly species linked to 30 different flowering plants were observed in the survey of one year in Kolkata, India. The resultant bipartite network constructed on the basis of the links between butterflies and plants indicated high level of generalization and nestedness. All the butterfly species were linked with at least one plant while one butterfly species namely C. pyranthe had 21 links. Among the plants, L. camara was observed to be the dominant plant species with 37 links. Apart from the links with number of food plants, the choice of food plants of each butterfly species differed considerably, reflected in the significant differences in abundance, degree and interaction strength values. An extended analysis reflected that beside shrubs, the herbaceous plants were also very valuable in sustaining butterfly population. The butterfly-plant network analysis may be useful for discriminating the important plant species necessary for the conservation of butterfly species in an urban environment like Kolkata, India. Acknowledgement The authors are grateful to the respective Head of the Department of Zoology, University of Calcutta, Kolkata for the facilities provided including DST-FIST and UGC-SAP (DRS I & II). GKS and SM acknowledge the partial support of West Bengal Biodiversity Board, West Bengal, India (Sanction number (507/3k (Bio) -6/2009), dated 09.12.2009) in executing the research work. SM acknowledges the financial assistance of UGC through SAP-RFSMS and of University of Calcutta through University Research Fellowship in carrying out this work (Sanction No. UGC/1143/Fellow (univ) 25.09.2014). Appendix A. Supplementary data Supplementary data related to this article can be found at https:// doi.org/10.1016/j.actao.2018.08.003. Authors' contributions GA, PB, GKS designed the experiments. SM, GA, SB performed the experiments. GA, SM analyzed the data and wrote the manuscript and prepared the figures and tables. Conflicts of interest As authors of this manuscript we declare no conflict of interest. Ethics approval Not applicable. Consent for publication Not applicable. References Almeida-Neto, M., Guimaraes, P., Guimarães, P.R., Loyola, R.D., Ulrich, W., 2008. A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement. Oikos 117 (8), 1227–1239. Ashman, T.L., Knight, T.M., Steets, J.A., Amarasekare, P., Burd, M., Campbell, D.R., Dudash, M.R., Johnston, M.O., Mazer, S.J., Mitchell, R.J., Morgan, M.T., Wilson, W.G., 2004. Pollen limitation of plant reproduction: ecological and evolutionary causes and consequences. Ecology 85 (9), 2408–2421. Atmar, W., Patterson, B.D., 1993. The measure of order and disorder in the distribution of species in fragmented habitat. Oecologia 96 (3), 373–382. Barber, N.A., Marquis, R.J., 2011. Leaf quality, predators, and stochastic processes in the

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