Pathways for Novel Epidemiology: Plant–Pollinator–Pathogen Networks and Global Change
Authors: Willem Proesmans, Matthias Albrecht, Anna Gajda, Peter Neumann, Robert J. Paxton, Maryline Pioz, Christine Polzin, Oliver Schweiger, Josef Settele, Hajnalka Szentgyörgyi, Hans-Hermann Thulke, Adam J. Vanbergen
Journal: Trends in Ecology & Evolution (2021)

Flower sharing amongst pollinator species represents a conduit for interspecific insect pathogen transmission.Plant–pollinator network structure and species traits shape pathogen dynamics in the pollinator community.Global change (climate change, invasive species, agricultural intensification, and urbanisation) can modulate species interactions, host susceptibility, and pathogen virulence, thereby creating novel epidemiological risks.Multiple global change effects can interact in synergistic or antagonistic ways, creating additional risks and complicating predictions of pathogen dynamics and evolution.Flower-mediated insect pathogen transmission provides a model framework to understand the interplay of interspecific pathogen dynamics under global change. Multiple global change pressures, and their interplay, cause plant–pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant–pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover–spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host–pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing. Multiple global change pressures, and their interplay, cause plant–pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant–pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover–spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host–pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing. Wild and managed pollinators provide crucial ecosystem services and diverse economic and noneconomic values that support ecosystem health, agricultural production, and human wellbeing [1.Potts S.G. et al.Safeguarding pollinators and their values to human well-being.Nature. 2016; 540: 220-229Crossref PubMed Scopus (558) Google Scholar]. Multiple, potentially interacting, anthropogenic pressures threaten and drive declines in managed and wild pollinators [1.Potts S.G. et al.Safeguarding pollinators and their values to human well-being.Nature. 2016; 540: 220-229Crossref PubMed Scopus (558) Google Scholar,2.Vanbergen A.J. the Insect Pollinators Initiative Threats to an ecosystem service: pressures on pollinators.Front. Ecol. Environ. 2013; 11: 251-259Crossref Scopus (644) Google Scholar]. Intra- or interspecific spread of pathogens (viruses, microsporidian fungi, bacteria, protozoa, and parasitic invertebrates) in novel host communities assembled under global changes are a likely emerging threat [1.Potts S.G. et al.Safeguarding pollinators and their values to human well-being.Nature. 2016; 540: 220-229Crossref PubMed Scopus (558) Google Scholar,3.Brown M.J.F. et al.A horizon scan of future threats and opportunities for pollinators and pollination.PeerJ. 2016; 4e2249Crossref PubMed Google Scholar]. Horizontal transmission of pathogens occurs when individual insects share flowers providing nectar and pollen resources [4.Durrer S. Schmid-Hempel P. Shared use of flowers leads to horizontal pathogen transmission.Proc. R. Soc. London B. 1994; 258: 299-302Crossref Scopus (206) Google Scholar,5.McArt S.H. et al.Arranging the bouquet of disease: floral traits and the transmission of plant and animal pathogens.Ecol. 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Given the importance of pollinators and pollination [1.Potts S.G. et al.Safeguarding pollinators and their values to human well-being.Nature. 2016; 540: 220-229Crossref PubMed Scopus (558) Google Scholar], it is vital to understand how anthropogenic pressures such as land use change [13.Figueroa L.L. et al.Landscape simplification shapes pathogen prevalence in plant–pollinator networks.Ecol. Lett. 2020; 23: 1212-1222Crossref PubMed Scopus (6) Google Scholar], chemical stressors [14.Fine J.D. et al.An inert pesticide adjuvant synergizes viral pathogenicity and mortality in honey bee larvae.Sci. Rep. 2017; 7: 40499Crossref PubMed Scopus (35) Google Scholar], altered habitat resources [15.Graystock P. et al.Dominant bee species and floral abundance drive parasite temporal dynamics in plant–pollinator communities.Nat. Ecol. Evol. 2020; 4: 1358-1367Crossref PubMed Scopus (8) Google Scholar], climate change [16.Cornelissen B. et al.Global warming promotes biological invasion of a honey bee pest.Glob. Chang. Biol. 2019; 25: 3642-3655Crossref PubMed Scopus (9) Google Scholar], and alien species [17.Schweiger O. et al.Multiple stressors on biotic interactions: how climate change and alien species interact to affect pollination.Biol. Rev. 2010; 85: 777-795PubMed Google Scholar] modulate pollinator–pathogen dynamics. Such pressures may raise pollinator disease risk by altering the dominance, distribution, and interaction of primary or secondary host species and asymptomatic pathogen vectors. Understanding this interplay between host–pathogen dynamics and global change will be crucial to predicting impacts on pollinator populations, communities, and pollination functions underpinning ecosystems and human wellbeing (Figure 1). The distribution, diversity, and abundance of floral resources in a landscape are key to concentrating or diluting interspecific pollinator interactions and potential pathogen transfer. Pollinator species are obligate flower visitors, foraging and feeding on pollen and/or nectar for at least part of their life cycle, and therefore both compete for and share floral resources in time and space [1.Potts S.G. et al.Safeguarding pollinators and their values to human well-being.Nature. 2016; 540: 220-229Crossref PubMed Scopus (558) Google Scholar]. This makes flowers hotspots of co-occurrence, direct contact, or indirect interaction (mediated by pollen or nectar) between pollinator species in a habitat or landscape [4.Durrer S. Schmid-Hempel P. Shared use of flowers leads to horizontal pathogen transmission.Proc. R. Soc. London B. 1994; 258: 299-302Crossref Scopus (206) Google Scholar,5.McArt S.H. et al.Arranging the bouquet of disease: floral traits and the transmission of plant and animal pathogens.Ecol. Lett. 2014; 17: 624-636Crossref PubMed Scopus (112) Google Scholar,15.Graystock P. et al.Dominant bee species and floral abundance drive parasite temporal dynamics in plant–pollinator communities.Nat. Ecol. Evol. 2020; 4: 1358-1367Crossref PubMed Scopus (8) Google Scholar,18.Graystock P. et al.Parasites in bloom: flowers aid dispersal and transmission of pollinator parasites within and between bee species.Proc. R. Soc. B. 2015; 28220151371Crossref PubMed Scopus (126) Google Scholar]. Accordingly, flowers can serve as hubs of pathogen transmission within and between species and pathogens may 'travel' through the network of plant–pollinator interactions, potentially crossing species boundaries and infecting new hosts [18.Graystock P. et al.Parasites in bloom: flowers aid dispersal and transmission of pollinator parasites within and between bee species.Proc. R. Soc. B. 2015; 28220151371Crossref PubMed Scopus (126) Google Scholar]. Studying this tripartite plant–pollinator–pathogen network can therefore help to identify potential flower-mediated transmission routes and elucidate how anthropogenic disruptions to network structure may alter or create novel pathogen dynamics. Pollinator species traits determine their susceptibility to different environmental pressures and their potential to transmit pathogens [19.Williams N.M. et al.Ecological and life-history traits predict bee species responses to environmental disturbances.Biol. Conserv. 2010; 143: 2280-2291Crossref Scopus (417) Google Scholar]. Species' diet breadth and preference may modulate the probability of encountering pathogens in nectar/pollen, on infected hosts, or deposited on flowers. Relatively specialised pollinators that forage on few plant taxa may have a lower exposure risk than species with broader floral diets. Less specialised species function as generalist pollinators in interaction networks, being highly connected to multiple forage plant species and thus indirectly to other pollinators [13.Figueroa L.L. et al.Landscape simplification shapes pathogen prevalence in plant–pollinator networks.Ecol. Lett. 2020; 23: 1212-1222Crossref PubMed Scopus (6) Google Scholar]. Consequently, generalists may have a greater probability of pathogen exposure or infection (novel or otherwise) and accordingly vector multiple pathogens across the network. Generalist species, however, may differ in foraging preferences and individual foragers of a generalist species may select for specific subsets of forage plant species, both of which may mitigate the risk of flower-mediated pathogen spread through a community [20.Ellner S.P. et al.Individual specialization and multihost epidemics: disease spread in plant–pollinator networks.Am. Nat. 2020; 195: 118-131Crossref Scopus (2) Google Scholar]. Moreover, generalist pollinators may dilute the risk of transmission per plant species [13.Figueroa L.L. et al.Landscape simplification shapes pathogen prevalence in plant–pollinator networks.Ecol. Lett. 2020; 23: 1212-1222Crossref PubMed Scopus (6) Google Scholar] and an emergent community epidemic by spreading their flower visits over multiple plant species. Sociality is a key trait affecting disease dynamics. Eusocial pollinators (Apis, Bombus, Meliponini) play a disproportionately large role due to their life history, cooperative brood care, and overlapping generations in densely populated colonies exacerbating intra-colony disease spread [15.Graystock P. et al.Dominant bee species and floral abundance drive parasite temporal dynamics in plant–pollinator communities.Nat. Ecol. Evol. 2020; 4: 1358-1367Crossref PubMed Scopus (8) Google Scholar]. Along with their generalised floral diets and long flying season bridging the phenology of other pollinator species, eusocial bees likely elevate the probability of interspecific contact and pathogen spillover. However, eusocial species may also mitigate the risk of increased pathogen burden through social immunity (e.g., behaviours to combat disease such as removing diseased larvae and dead workers from the colony [21.Meunier J. Social immunity and the evolution of group living in insects.Philos. Trans. R. Soc. B Biol. Sci. 2015; 37020140102Crossref PubMed Scopus (94) Google Scholar]). Elucidating how gradients in foraging traits (e.g., pollen uptake and deposition rates, pollen transportation mode), colony sizes, and trait plasticity (e.g., facultative sociality in Halictidae) among taxa affect pathogen transmission, remains largely unexplored and is an important future direction for pollinator eco-epidemiology. Plant traits may also modulate pollinator disease risk, with the potential for both facilitation and inhibition of pathogen transfer [5.McArt S.H. et al.Arranging the bouquet of disease: floral traits and the transmission of plant and animal pathogens.Ecol. Lett. 2014; 17: 624-636Crossref PubMed Scopus (112) Google Scholar]. Floral architecture, by constraining access to pollen and nectar to pollinator species with the requisite morphological adaptations, filters insect visitor interactions and contacts [5.McArt S.H. et al.Arranging the bouquet of disease: floral traits and the transmission of plant and animal pathogens.Ecol. Lett. 2014; 17: 624-636Crossref PubMed Scopus (112) Google Scholar]. Plants with structurally simple, large floral displays (e.g., Apiaceae, Rosaceae) attract numerous pollinator species and may serve as hubs facilitating interspecific pathogen transmission [22.Truitt L.L. et al.Trait-based modeling of multi-host pathogen transmission: plant–pollinator networks.Am. Nat. 2019; 193: 149-167Crossref PubMed Scopus (11) Google Scholar]. Additionally, plants with a more central position in a plant–pollinator network often contain a high pathogen load [23.Piot N. et al.Network centrality as an indicator for pollinator parasite transmission via flowers.Insects. 2020; 11: 872Crossref Scopus (0) Google Scholar]. More specialised plants with complex flower structures requiring intimate and sustained contact with a specialised pollinator may limit transmission to a particular species or functional group [5.McArt S.H. et al.Arranging the bouquet of disease: floral traits and the transmission of plant and animal pathogens.Ecol. Lett. 2014; 17: 624-636Crossref PubMed Scopus (112) Google Scholar]. Alternatively, other floral characteristics, such as organic volatiles produced by plants to attract mutualists, may be toxic to certain pathogens [24.Hammerbacher A. et al.Roles of plant volatiles in defence against microbial pathogens and microbial exploitation of volatiles.Plant Cell Environ. 2019; 42: 2827-2843Crossref PubMed Scopus (56) Google Scholar]. Nectar and pollen rewards may contain phytochemicals that inhibit pathogens when consumed by the host (e.g., reducing Crithidia sp. infection in bumble bees [25.Giacomini J.J. et al.Medicinal value of sunflower pollen against bee pathogens.Sci. Rep. 2018; 8: 14394Crossref PubMed Scopus (32) Google Scholar]), potentially reducing pathogen loads and community spread. Combined with limited pathogen resistance to environmental degradation (e.g., temperature, UV-radiation), such plant traits may limit pathogen survival on or within floral resources and subsequent pollinator infections [26.Adler L.S. et al.Disease where you dine: plant species and floral traits associated with pathogen transmission in bumble bees.Ecology. 2018; 99: 2535-2545Crossref PubMed Scopus (23) Google Scholar,27.Figueroa L.L. et al.Bee pathogen transmission dynamics : deposition , persistence, and acquisition on flowers.Proc. R. Soc. Lond. B. 2019; 28620190603PubMed Google Scholar]. The interaction between the physiology of a pathogen and alternative hosts also has implications for epidemiological dynamics at population and community levels. Certain pollinator individuals or species may be immune to a particular pathogen or function as asymptomatic vectors, whereas others suffer from disease, leading to physiological stress, altered behaviour, and reduced fitness or death [28.Manley R. et al.Contrasting impacts of a novel specialist vector on multihost viral pathogen epidemiology in wild and managed bees.Mol. Ecol. 2020; 29: 380-393Crossref PubMed Scopus (3) Google Scholar]. Additionally, pathogen infections may differ in their effects according to the host insect nutritional status, influence of other stressors, and environmental context [29.Brown M.J.F. et al.Strong context-dependent virulence in a host-parasite system: reconciling genetic evidence with theory.J. Anim. Ecol. 2003; 72: 994-1002Crossref Scopus (208) Google Scholar]. While pathogen research in pollinators is heavily biased towards honey bees and bumble bees, recent studies point to broader pathogen host ranges, such as Crithidia bombi infections in multiple bee families [30.Ngor L. et al.Cross-infectivity of honey and bumble bee-associated parasites across three bee families.Parasitology. 2020; 147: 1290-1304Crossref PubMed Scopus (11) Google Scholar]. Pathogen strains or taxa can behave as specialists or generalists in terms of host range, virulence, and infectivity, affecting their fitness and ability to cross species boundaries [28.Manley R. et al.Contrasting impacts of a novel specialist vector on multihost viral pathogen epidemiology in wild and managed bees.Mol. Ecol. 2020; 29: 380-393Crossref PubMed Scopus (3) Google Scholar]. Single-stranded RNA viruses tend to pose the highest risk of co-infecting multiple species due to their high mutation rate, short generation time, and ability to cross phylogenetic boundaries [31.McMahon D.P. et al.A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees.J. Anim. Ecol. 2015; 84: 615-624Crossref PubMed Scopus (129) Google Scholar, 32.Dobelmann J. et al.Genetic strain diversity of multi-host RNA viruses that infect a wide range of pollinators and associates is shaped by geographic origins.Viruses. 2020; 12: 358Crossref Scopus (1) Google Scholar, 33.Dalmon A. et al.Possible spillover of pathogens between bee communities foraging on the same floral resource.Insects. 2021; 12: 122Crossref PubMed Scopus (0) Google Scholar]. Multiple co-infections of pathogens and parasites (RNA viruses, microsporidia, Acari) may further alter dynamics. For example, colonies of Apis mellifera infested with Varroa destructor mites can show a higher viral load and virulence of the RNA virus Deformed wing virus (DWV) [34.Wilfert L. et al.Deformed wing virus is a recent global epidemic in honeybees driven by Varroa mites.Science. 2016; 351: 594-597Crossref PubMed Scopus (184) Google Scholar]. Alternatively, pathogen co-infections may be asymmetric with intra-host competition inhibiting infection and disease manifestation [35.Doublet V. et al.Within-host competition among the honey bees pathogens Nosema ceranae and Deformed wing virus is asymmetric and to the disadvantage of the virus.J. Invertebr. Pathol. 2015; 124: 31-34Crossref PubMed Scopus (32) Google Scholar]. Pathogens may also alter pollinator host behaviour to increase transmission potential. For example, bumble bees infected with trypanosomatid parasites defecate more frequently on flowers thus spreading the pathogen [27.Figueroa L.L. et al.Bee pathogen transmission dynamics : deposition , persistence, and acquisition on flowers.Proc. R. Soc. Lond. B. 2019; 28620190603PubMed Google Scholar] and fungal pathogens may alter floral scent to lure pollinators [36.Cellini A. et al.Pathogen-induced changes in floral scent may increase honeybee-mediated dispersal of Erwinia amylovora.ISME J. 2019; 13: 847-859Crossref PubMed Scopus (18) Google Scholar]. Certain pathogens (e.g., Nosema spp.) increase their infectivity by forming cysts or spores that promote environmental persistence and probability of encountering susceptible hosts [37.Evison S.E.F. Jensen A.B. The biology and prevalence of fungal diseases in managed and wild bees.Curr. Opin. Insect Sci. 2018; 26: 105-113Crossref PubMed Scopus (11) Google Scholar]. Beyond pathogens, other biota (e.g., gut microbiota) interacting with the host in mutualistic, commensal, or antagonistic ways, may modify pathogen dynamics. Lactobacilli inadvertently collected with pollen during flower visits may improve bee resistance to pathogens [38.McFrederick Q.S. et al.Environment or kin: whence do bees obtain acidophilic bacteria?.Mol. Ecol. 2012; 21: 1754-1768Crossref PubMed Scopus (95) Google Scholar]. Arbuscular mycorrhizal fungi infecting plant roots can interact with soil fertility to alter nectar chemistry (e.g., alkaloids) in ways that influence pathogen prevalence [39.Davis J.K. et al.From plant fungi to bee parasites: mycorrhizae and soil nutrients shape floral chemistry and bee pathogens.Ecology. 2019; 100e02801Crossref PubMed Scopus (3) Google Scholar]. Interactions between virus-vectoring and non-vector herbivores mediated by changes in plant secondary chemicals (e.g., reduction of flavonoids) can indirectly influence plant virus transmission [40.Su Q. et al.A non-vector herbivore indirectly increases the transmission of a vector-borne virus by reducing plant chemical defences.Funct. Ecol. 2020; 34: 1091-1101Crossref Scopus (3) Google Scholar]. It remains unknown whether similar complex trophic interactions might affect pathogens infecting pollinators. Plant–pollinator networks describe the community of interacting species [41.Nielsen A. Bascompte J. Ecological networks, nestedness, and sampling effort.J. Ecol. 2007; 95: 1134-1141Crossref Scopus (148) Google Scholar,42.Thébault E. Fontaine C. Stability of ecological communities and the architecture of mutualistic and trophic networks.Science. 2010; 329: 853-856Crossref PubMed Scopus (826) Google Scholar]. The pool of species traits in a habitat or landscape, pollinator behaviour, metabolic and dietary needs, and the phenological synchrony of potential mutualisms dictate the architecture of a network [43.Vázquez D.P. et al.Uniting pattern and process in plant-animal mutualistic networks: a review.Ann. Bot. 2009; 103: 1445-1457Crossref PubMed Scopus (369) Google Scholar] (Figure 1A). Plant–pollinator networks are typically asymmetrical in form (Box 1). Specialist pollinators tend to forage on a limited number of plant taxa (e.g., within a single family) that represent a subset of the plants visited by generalist species leading to a nested structure of the community network [41.Nielsen A. Bascompte J. Ecological networks, nestedness, and sampling effort.J. Ecol. 2007; 95: 1134-1141Crossref Scopus (148) Google Scholar,42.Thébault E. Fontaine C. Stability of ecological communities and the architecture of mutualistic and trophic networks.Science. 2010; 329: 853-856Crossref PubMed Scopus (826) Google Scholar]. Plant–pollinator networks can also consist of weakly interlinked subsets of species modules that comprise sets of strongly interacting species [44.Olesen J.M. et al.The modularity of pollination networks.Proc. Natl. Acad. Sci. U. S. A. 2007; 104: 19891-19896Crossref PubMed Scopus (957) Google Scholar]. This modularity can arise from convergent trait sets and mutualist coevolution, caused for example by inter- and intraspecific competition among generalist pollinators, driving flexible foraging at the individual level and concentrating visitation on a subset of the available floral species [45.Spiesman B.J. Gratton C. Flexible foraging shapes the topology of plant–pollinator interaction networks.Ecology. 2016; 97: 1431-1441Crossref PubMed Scopus (19) Google Scholar].Box 1Key Network Metrics affecting Pathogen TransmissionPlant–pollinator interactions can be displayed as bipartite networks, in which species are nodes and interactions connecting lines. Connectance, nestedness, and modularity (Figure I) are arguably the most important metrics predicting pathogen transmission throughout a network [13.Figueroa L.L. et al.Landscape simplification shapes pathogen prevalence in plant–pollinator networks.Ecol. Lett. 2020; 23: 1212-1222Crossref PubMed Scopus (6) Google Scholar]. While often used for unweighted (binary) networks, indices exist for these metrics that can characterise weighted networks (i.e., where the interactions are weighted by their frequency), which is the most common and most accurate way to display plant–pollinator networks.Connectance is the proportion of realised ecological interactions to potential ecological interactions. Hence, a plant–pollinator network containing five pollinator species and ten plant species, with ten realised interactions, has a connectance of 0.20, since 50 interactions are theoretically possible.Modularity refers to the division of a network in separate modules, which have a high within-module connectance, but few interactions between modules. As for nestedness, multiple indices exist to express the level of modularity. Newman's modularity (Q), for example, is calculated as the fraction of interactions within each module minus the fraction of expected interactions in a random network with the same connectance [115.Newman M.E.J. Modularity and community structure in networks.Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 8577-8582Crossref PubMed Scopus (6380) Google Scholar].Nestedness in bipartite networks is described as the tendency for specialist species to interact with generalist species, resulting in specialist species' interactions being a subset of generalist species' interactions [116.Bascompte J. et al.The nested assembly of plant–animal mutualistic networks.Proc. Natl. Acad. Sci. U. S. A. 2003; 100: 9383-9387Crossref PubMed Scopus (1355) Google Scholar]. There are several nestedness indices, of which nestedness metric based on overlap and decreasing fill (NODF) is considered the most robust [117.Almeida-Neto M. et al.A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement.Oikos. 2008; 117: 1227-1239Crossref Scopus (960) Google Scholar]. Plant–pollinator interactions can be displayed as bipartite networks, in which species are nodes and interactions connecting lines. Connectance, nestedness, and modularity (Figure I) are arguably the most important metrics predicting pathogen transmission throughout a network [13.Figueroa L.L. et al.Landscape simplification shapes pathogen prevalence in plant–pollinator networks.Ecol. Lett. 2020; 23: 1212-1222Crossref PubMed Scopus (6) Google Scholar]. While often used for unweighted (binary) networks, indices exist for these metrics that can characterise weighted networks (i.e., where the interactions are weighted by their frequency), which is the most common and most accurate way to display plant–pollinator networks. Connectance is the proportion of realised ecological interactions to potential ecological interactions. Hence, a plant–pollinator network containing five pollinator species and ten plant species, with ten realised interactions, has a connectance of 0.20, since 50 interactions are theoretically possible. Modularity refers to the division of a network in separate modules, which have a high within-module connectance, but few interactions between modules. As for nestedness, multiple indices exist to express the level of modularity. Newman's modularity (Q), for example, is calculated as the fraction of interactions within each module minus the fraction of expected interactions in a random network with the same connectance [115.Newman M.E.J. Modularity and community structure in networks.Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 8577-8582Crossref PubMed Scopus (6380) Google Scholar]. Nestedness in bipartite networks is described as the tendency for specialist species to interact with generalist species, resulting in specialist species' interactions being a subset of generalist species' interactions [116.Bascompte J. et al.The nested assembly of plant–animal mutualistic networks.Proc. Natl. Acad. Sci. U. S. A. 2003; 100: 9383-9387Crossref PubMed Scopus (1355) Google Scholar]. There are several nestedness indices, of which nestedness metric based on overlap and decreasing fill (NODF) is considered the most robust [117.Almeida-Neto M. et al.A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement.Oikos. 2008; 117: 1227-1239Crossref Scopus (960) Google Scholar]. Stochastic or environmentally driven variation in this fundamental process of community assembl