Mutualistic Networks Research Articles

Urban environments increase generalization of hummingbird–plant networks across climate gradients

Urbanization has reshaped the distribution of biodiversity on Earth, but we are only beginning to understand its effects on ecological communities. While urbanization may have homogenization effects strong enough to blur the large-scale patterns in interaction networks, urban community patterns may still be associated with climate gradients reflecting large-scale biogeographical processes. Using 103 hummingbird-plant mutualistic networks across continental Americas, including 176 hummingbird and 1,180 plant species, we asked how urbanization affects species interactions over large climate gradients. Urban networks were more generalized, exhibiting greater interaction overlap. Higher generalization was also associated with lower precipitation in both urban and natural areas, indicating that climate affects networks irrespective of habitat type. Urban habitats also showed lower hummingbird functional trait diversity and over/underrepresentation of specific clades. From the plant side, urban communities had a higher prevalence of nonnative nectar plants, which were more frequently visited by the hummingbird species occurring in both urban and natural areas. Therefore, urbanization affected hummingbird-plant interactions through both the composition of species and traits, as well as floral resource availability. Taken together, we show that urbanization consistently modifies ecological communities and their interactions, but climate still plays a role in affecting the structure of these novel communities over the scale of continents.

Glacier retreat decreases mutualistic network robustness over spacetime

Glaciers are retreating worldwide at an ever‐increasing rate, exposing new ice‐free areas to ecological succession. This process leads to changes in biodiversity and potentially to novel species interactions. However, we still have a limited understanding of how glacier retreat influences species interaction networks, particularly the structure and robustness of mutualistic networks. After reconstructing plant–pollinator networks along a 140‐years chronosequence on a glacier foreland, we address the effects of glacier retreat on network structure and robustness. Our results show that the prevalence of different network motifs changes over spacetime, leading to a decrease of network robustness. With glacier retreat, mutualistic networks shift from highly connected with diverse specialist interactions to loosely connected with few generalist interactions. Furthermore, despite the turnover of plant species, we find that species structural roles remain constant over spacetime while depending on species identity. Our findings suggest that glacier retreat reshuffles mutualistic networks with motifs posing low robustness, leading to increased fragility. Understanding the assembly and breaking down of species interaction networks provides novel insights into the development and stability of novel, post‐glacial ecological systems facing glacier extinction.

Urbanization as a driver of changes in mutualistic networks between bees and plants

Urbanization as a driver of changes in mutualistic networks between bees and plants

Personality shapes inter- and intraspecific interactions in rodents: a behavioral experiment with Brandt’s voles (Lasiopodomys brandtii)

Abstract Interspecific and intraspecific interactions are integral components of antagonistic and mutualistic networks of all animal species. These interactions are affected by various factors, such as morphological, physiological, and genetic characteristics. However, the impact of personality traits on animal inter- and intraspecific interactions remains unclear. We investigated the role of different personality types (proactive and reactive) in Lasiopodomys brandtii. We examined both intraspecific interactions with Lasiopodomys brandtii and interspecific interactions with Kunming mice. We found that for intraspecific interactions, proactive individuals had higher numbers of contacts with opponents, spent more time in the vicinity of an opponent, and moved greater distances within the vicinity of an opponent. For interspecific interactions, proactive individuals had higher numbers of contacts with opponents than reactive individuals. These results suggest that proactive individuals, especially male voles, tend to occupy dominant positions in both intraspecific and interspecific relationships. Consequently, our study is meaningful in understanding how personality traits affect animal behavior, species niche differentiation, and community dynamics and local biodiversity.

Anthropogenic disturbances alter the trophic niche structure and ecological relationships of understory bat communities in the Ecuadorian Andean Chocó

Human disturbances have reduced the three basic niche dimensions for the survival of some mammalian species (space, time, and resources). Anthropic activities cause the extinction of ecological functionalities faster than species extinctions. In this study, we identified four types of habitats in the Ecuadorian Andean Chocó: primary forest (PF), secondary forest in natural regeneration (SF1), secondary forest in assisted regeneration (SF2), and pastures for cattle (P). The main objective was to determine the responses in the trophic niche and the ecological relationships of understory phyllostomid bat communities. We captured bats with mist nets and obtained fecal samples from 21 species. These were analyzed to quantify seeds, pollen, insects, and vertebrates consumed by each individual, with counts organized by species and habitat type. We conducted an ecological relationship analysis to understand the structure of bat–fruit networks and their dietary preferences. We calculated niche breadth and niche overlap to understand the trophic niche composition of each species. We applied null models to evaluate if there is evidence of trophic niche partitioning among these species. Despite a relatively small sample size, the results obtained are nevertheless interesting. While niche breadth was not useful for detecting the effects of human disturbances, niche overlap was significantly higher in disturbed habitats (SF1, SF2 and P), where ecological relationships were weaker. Most of the species were related to the consumption of seeds from the genus Piper. These results indicate that bat communities and their ecosystem services may be highly endangered due to anthropogenic disturbances. Network interactions in bats are highly variable in geographic space and time, and little is known about the community structure of bat–seed interactions. Studying mutualistic networks in bats and seeds is crucial because of their role in ecosystem support, supply, and regulation services that depend on them.

Reviving collapsed plant-pollinator networks from a single species.

Mutualistic ecological networks can suddenly transition to undesirable states due to small changes in environmental conditions. Recovering from such a collapse can be difficult as restoring the original environmental conditions may be infeasible. Additionally, such networks can also exhibit a phenomenon known as hysteresis, whereby the system could exhibit multiple states under the same environmental conditions, implying that ecological networks may not recover. Here, we attempted to revive collapsed mutualistic networks to a high-functioning state from a single species, using concepts from signal propagation theory and an eco-evolutionary model based on network structures of 115 empirical plant-pollinator networks. We found that restoring the environmental conditions rarely aided in recovery of collapsed networks, but a positive relationship between recovering pollinator density and network nestedness emerged, which was qualitatively supported by empirical plant-pollinator restoration data. In contrast, network resurrection from a collapsed state in undesirable environmental conditions where restoration has minimal impacts could be readily achieved by perturbing a single species or a few species that controls the response of the dynamical networks. Additionally, nestedness in networks and a moderate amount of trait variation could aid in the revival of networks even in undesirable environmental conditions. Our work suggests that focus should be applied to a few species whose dynamics could be steered to resurrect entire networks from a collapsed state and that network architecture could play a crucial role in reviving collapsed plant-pollinator networks.

Seed dispersal by bats (Chiroptera: Phyllostomidae) and mutualistic networks in a landscape dominated by cocoa in the Brazilian amazon

Bats play essential roles in neotropical ecosystems, performing crucial ecological functions such as insect pest control, pollination of plants with significant economic, social, and ecological value, and seed dispersal, including that of pioneer plant species. These animals are directly linked to human well-being, and declines in their populations can even have adverse effects, such as increasing the need for pesticides in regions where natural insect control is reduced. The seed dispersal conducted by bats is fundamental for maintaining neotropical biodiversity, as it supports habitat regeneration and the propagation of various plant species. Moreover, the role of these dispersers is enhanced due to their ability to inhabit a variety of environments, from natural forests to anthropized areas. However, the conversion of natural forests into agricultural production areas, as well as urbanization, has affected the structure of mutualistic networks between bats and plants. In this context, the objective of this study was to identify the pattern of seed dispersal by bats of the Phyllostomidae family in an anthropized landscape of the Brazilian Amazon. Data collection was conducted in different areas of natural forest, cocoa cultivation, and urban areas in the municipalities of the States of Pará. Regarding the results, the most representative subfamilies of bats were Carollinae (72.15%) and Stenodermatinae (21.8%). The botanical families Piperaceae (35.52%) and Solanaceae (19.71%) were the ones most preferred by the bats. Regarding species richness, the general bat-plant interaction network included 15 botanical families and 26 species of bats. The general interaction network was nested (WNODF= 29.8), with low Specialization (H2=0.27), Connectance (0.17), and Modularity corresponding to M=0.21. Thus, we highlight the importance of these species for the restoration of degraded environments. Therefore, through the execution of projects that demonstrate the importance of chiropterochory in the restoration of degraded ecosystems in the Amazon, it will be possible to create measures and subsidies focused on the conservation of bat and plant species that play a role in maintaining the planet's biodiversity.

The Hierarchical Coevolutionary Units of Ecological Networks.

In ecological networks, cohesive groups of species may shape the evolution of interactions, serving as coevolutionary units. Ranging across network scales, from motifs to isolated components, elucidating which cohesive groups are more determinant for coevolution remains a challenge in ecology. We address this challenge by integrating 376 empirical mutualistic and antagonistic networks and coevolutionary models. We identified cohesive groups at four network scales containing a significant proportion of potential direct coevolutionary effects. Cohesive groups displayed hierarchical organisation, and potential coevolutionary effects overflowing lower-scale groups were contained by higher-scale groups, underscoring the hierarchy's impact. However, indirect coevolutionary effects blurred group boundaries and hierarchy, particularly under strong selection from ecological interactions. Thus, under strong selection, indirect effects render networks themselves, and not cohesive groups, as the likely coevolutionary units of ecological systems. We hypothesise hierarchical cohesive groups to also shape how other forms of direct and indirect effects propagate in ecological systems.

Network resilience of plant-bee interactions in the Eastern Afromontane Biodiversity Hotspot

Interaction network resilience can be defined as the ability of interacting organisms to maintain their functions, processes or populations after experiencing a disturbance. Studies on mutualistic interactions between plants and pollinators along environmental gradients are essential to understand the provision of ecosystem services and the mechanisms challenging their network resilience. However, it remains unknown to what level ecological changes along climatic gradients constrain the network resilience of mutualistic organisms, especially along elevation gradients. We surveyed bee species and recorded their interactions with plants throughout the four major seasons (i.e. long and short rainy, and long and short dry) on 50 study sites positioned along an elevation gradient (525 m to 2,530 m asl) in the Eastern Afromontane Biodiversity Hotspots in Kenya, East Africa. We calculated bee and plant network resilience using the network resilience parameter (βeff) and assessed changes in bee and plant network resilience along the elevation gradient using generalised additive models (gams). We quantified the effects of climate, bee and plant diversity, bee functional traits, network structure, and landscape configuration on bee and plant network resilience using a set of multi-model inference frameworks followed by structural equation models (SEM). We found that bee and plant species exhibited higher levels of network resilience at higher elevations. While bee network resilience increased linearly across the elevation gradient, plant network resilience increased exponentially from ∼1500 m and higher. Bee and plant network resilience increased in areas with reduced mean annual temperature (MAT) and decreased in areas with lower mean annual precipitation (MAP). Our SEM model showed that increasing temperatures indirectly influenced plant network resilience via network modularity and community assemblage of bees. We also found that MAP had a direct positive effect on plant diversity and network resilience, while the fragmentation of habitats reduced richness of plant communities and enhanced network modularity. In conclusion, we revealed that mutualistic networks showed higher network resilience at higher elevations. We also unveiled that climate and habitat fragmentation directly or indirectly influences the network resilience of plants and bees via the modulation of community assemblages and interaction networks. These influences are lower at higher elevations such that these systems seem better able to buffer against extinction cascades. We thus suggest that, management efforts should be geared at consolidating natural habitats. In contrast, restoration efforts should aim at mitigating climate change effects and harnessing the ability of mutualists to reconnect broken links to improve the network resilience and functioning of East-African montane ecosystems.

Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities, such as overfishing and deforestation, and the effects of such damage on ecological stability are uncertain. Despite recent advances in experimental and theoretical studies on regime shifts and tipping points, theoretical tools for understanding the extinction chain, which is the sequence of species extinctions resulting from overexploitation, are still lacking, especially for large-scale nonlinear networked systems. In this study, we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and densities. We discovered five phases during the exploitation process: safe, partial extinction, bistable, tristable, and collapse, which enabled the optimal design of restoration strategies for degraded or collapsed systems. We validated our approach using a 20-year dataset from an eelgrass restoration project. Counterintuitively, we also found a specific region in the diagram spanning exploitation rates and competition intensities, where exploiting more species helps increase biodiversity. Our computational tool provides insights into harvesting, fishing, exploitation, or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

The Interplay of Binary and Quantitative Structure on the Stability of Mutualistic Networks.

Understanding how the structure of biological systems impacts their resilience (broadly defined) is a recurring question across multiple levels of biological organization. In ecology, considerable effort has been devoted to understanding how the structure of interactions between species in ecological networks is linked to different broad resilience outcomes, especially local stability. Still, nearly all of that work has focused on interaction structure in presence-absence terms and has not investigated quantitative structure, i.e., the arrangement of interaction strengths in ecological networks. We investigated how the interplay between binary and quantitative structure impacts stability in mutualistic interaction networks (those in which species interactions are mutually beneficial), using community matrix approaches. We additionally examined the effects of network complexity and within-guild competition for context. In terms of structure, we focused on understanding the stability impacts of nestedness, a structure in which more-specialized species interact with smaller subsets of the same species that more-generalized species interact with. Most mutualistic networks in nature display binary nestedness, which is puzzling because both binary and quantitative nestedness are known to be destabilizing on their own. We found that quantitative network structure has important consequences for local stability. In more-complex networks, binary-nested structures were the most stable configurations, depending on the quantitative structures, but which quantitative structure was stabilizing depended on network complexity and competitive context. As complexity increases and in the absence of within-guild competition, the most stable configurations have a nested binary structure with a complementary (i.e., anti-nested) quantitative structure. In the presence of within-guild competition, however, the most stable networks are those with a nested binary structure and a nested quantitative structure. In other words, the impact of interaction overlap on community persistence is dependent on the competitive context. These results help to explain the prevalence of binary-nested structures in nature and underscore the need for future empirical work on quantitative structure.

Stability, resilienceand eco-evolutionary feedbacks of mutualistic networks to rising temperature.

Ecological networks comprising of mutualistic interactions can suddenly transition to undesirable states, such as collapse, due to small changes in environmental conditions such as a rise in local environmental temperature. However, little is known about the capacity of such interaction networks to adapt to a rise in temperature and the occurrence of critical transitions. Here, combining quantitative genetics and mutualistic dynamics in an eco-evolutionary framework, we evaluated the stability and resilience of mutualistic networks to critical transitions as environmental temperature increases. Specifically, we modelled the dynamics of an optimum trait that determined the tolerance of species to local environmental temperature as well as to species interaction. We then evaluated the impact of individual trait variation and evolutionary dynamics on the stability of feasible equilibria, the occurrence of threshold temperatures at which community collapses, and the abruptness of such community collapses. We found that mutualistic network architecture, that is the size of the community and the arrangement of species interactions, interacted with evolutionary dynamics to impact the onset of network collapses. Some networks had more capacity to track the rise in temperatures than others and thereby increased the threshold temperature at which the networks collapsed. However, such a result was modulated by the amount of heritable trait variation species exhibited, with high trait variation in the mean optimum phenotypic trait increasing the environmental temperature at which networks collapsed. Furthermore, trait variation not only increased the onset of temperatures at which networks collapsed but also increased the local stability of feasible equilibria. Our study argued that mutualistic network architecture interacts with species evolutionary dynamics and increases the capacity of networks to adapt to changes in temperature and thereby delayed the occurrence of community collapses.

Structural dynamics of plant-pollinator mutualistic networks.

The discourse surrounding the structural organization of mutualistic interactions mostly revolves around modularity and nestedness. The former is known to enhance the stability of communities, while the latter is related to their feasibility, albeit compromising the stability. However, it has recently been shown that the joint emergence of these structures poses challenges that can eventually lead to limitations in the dynamic properties of mutualistic communities. We hypothesize that considering compound arrangements-modules with internal nested organization-can offer valuable insights in this debate. We analyze the temporal structural dynamics of 20 plant-pollinator interaction networks and observe large structural variability throughout the year. Compound structures are particularly prevalent during the peak of the pollination season, often coexisting with nested and modular arrangements in varying degrees. Motivated by these empirical findings, we synthetically investigate the dynamics of the structural patterns across two control parameters-community size and connectance levels-mimicking the progression of the pollination season. Our analysis reveals contrasting impacts on the stability and feasibility of these mutualistic communities. We characterize the consistent relationship between network structure and stability, which follows a monotonic pattern. But, in terms of feasibility, we observe nonlinear relationships. Compound structures exhibit a favorable balance between stability and feasibility, particularly in mid-sized ecological communities, suggesting they may effectively navigate the simultaneous requirements of stability and feasibility. These findings may indicate that the assembly process of mutualistic communities is driven by a delicate balance among multiple properties, rather than the dominance of a single one.

Beyond the aggregated paradigm: phenology and structure in mutualistic networks

Mutualistic relationships, where species interact to obtain mutual benefits, constitute an essential component of natural ecosystems. The use of ecological networks to represent the species and their ecological interactions allows the study of structural and dynamic patterns common to different ecosystems. However, by neglecting the temporal dimension of mutualistic communities, relevant insights into the organization and functioning of natural ecosystems can be lost. Therefore, it is crucial to incorporate empirical phenology -the cycles of species’ activity within a season- to fully understand the impact of temporal variability on network architecture. In this paper, by using empirical datasets together with a set of synthetic models, we propose a framework to characterize the phenology of plant-pollinator communities and assess how it reshapes their portrayal as a network. Analyses of three empirical cases reveal that non-trivial information is missed when representing the network of interactions as static, which leads to overestimating the value of fundamental structural features. We discuss the implications of our findings for mutualistic relationships and intra-guild competition for common resources. We show that recorded interactions and species’ activity duration are pivotal factors in accurately replicating observed patterns within mutualistic communities. Furthermore, our exploration of synthetic models underscores the system-specific character of the mechanisms driving phenology, increasing our understanding of the complexities of natural ecosystems.

Flower-bee versus pollen-bee metanetworks in fragmented landscapes.

Understanding the organization of mutualistic networks at multiple spatial scales is key to ensure biological conservation and functionality in human-modified ecosystems. Yet, how changing habitat and landscape features affect pollen-bee interaction networks is still poorly understood. Here, we analysed how bee-flower visitation and bee-pollen-transport interactions respond to habitat fragmentation at the local network and regional metanetwork scales, combining data from 29 fragments of calcareous grasslands, an endangered biodiversity hotspot in central Europe. We found that only 37% of the total unique pairwise species interactions occurred in both pollen-transport and flower visitation networks, whereas 28% and 35% were exclusive to pollen-transport and flower visitation networks, respectively. At local level, network specialization was higher in pollen-transport networks, and was negatively related to the diversity of land cover types in both network types. At metanetwork level, pollen transport data revealed that the proportion of single-fragment interactions increased with landscape diversity. Our results show that the specialization of calcareous grasslands' plant-pollinator networks decreases with landscape diversity, but network specialization is underestimated when only based on flower visitation information. Pollen transport data, more than flower visitation, and multi-scale analyses of metanetworks are fundamental for understanding plant-pollinator interactions in human-dominated landscapes.

Telling mutualistic and antagonistic ecological networks apart by learning their multiscale structure

Abstract Characterizing and understanding the processes that shape the structure of ecological networks, which represent who interacts with whom in a community, has many implications in ecology, evolutionary biology and conservation. A highly debated question is whether and how the structure of a bipartite ecological network differs between antagonistic (e.g. herbivory) and mutualistic (e.g. pollination) interaction types. Here, we tackle this question by using a multiscale characterization of network structure, machine learning tools, and a large database of empirical and simulated bipartite networks. Contrary to previous studies focusing on global structural metrics, such as nestedness and modularity, which concluded that antagonistic and mutualistic networks cannot be told apart from only their structure, we find that they can be told apart by combining a meso‐scale characterization of their structure and supervised machine learning. Motif frequencies appear particularly informative, with an over‐representation of densely connected motifs in antagonistic networks and of motifs with asymmetrical specialization in mutualistic networks. These structural properties can be used to predict the type of interaction with relatively good confidence. Beyond this classical mutualism/antagonism dichotomy, we also find significant structural uniqueness linked to specific ecologies (e.g. pollination, parasitism). Our results clarify structural differences between antagonistic and mutualistic networks and suggest the investigation of the structural uniqueness of specific ecologies as a promising approach for characterizing interactions beyond the coarse antagonistic/mutualistic dichotomy.

Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub‐specific plant–pollinator networks

Interaction networks are a widely used tool to understand the dynamics of plant–pollinator ecological communities. However, while most mutualistic networks have been defined at the species level, ecological processes such as pollination take place at different scales, including the individual or patch levels. Yet, current approaches studying fine‐grain sub‐specific plant–pollinator networks only account for interactions among nodes belonging to a single plant species due to the conceptual and mathematical limitations of modeling simultaneously several plant species each composed of several nodes. Here, we introduce a multilayer diffusion network framework that allows modeling simple diffusion processes between nodes pertaining to the same or different layers (i.e. species). It is designed to depict from the network structure the potential conspecific and heterospecific pollen flows among plant individuals or patches. This potential pollen flow is modeled as a transport‐like system, in which pollen grain movements are represented as random‐walkers that diffuse on an ensemble of bipartite layers of conspecific plants and their shared pollinators. We exemplify this physical conceptualization using a dataset of nine fine‐grain sub‐specific plant–pollinator networks from a Mediterranean grassland of annual plants, where plant nodes represent groups of conspecifics within patches of 1 m2. The diffusion networks show pollinators effectively connecting sets of patches of the same and different plant species, forming a modular structure. Interestingly, different properties of the network structure, such as the conspecific pollen arrival probability and the number of conspecific subgraphs in which plants are embedded, are critical for the seed production of different plant species. We provide a simple but robust set of metrics to calculate potential pollen flow and scale down network ecology to functioning properties at the individual or patch level, where most ecological processes take place, hence moving forward the description and interpretation of species‐rich communities across scales.

Flower visits and pollinator pollen load networks reveal the effects of pollinator sharing on heterospecific pollen transfer in a subalpine plant community.

The mutualistic network of plant-pollinator also involves interspecific pollination caused by pollinator sharing. Plant-pollinator networks are commonly based on flower visit observations, which may not adequately represent the actual pollen transfer between co-flowering plant species. Here, we compared the network structure of plant-pollinator interactions based on flower visits (FV) and pollen loads (PL) on the bodies of pollinators and tested how the degree of pollinator sharing in the two networks affected heterospecific pollen transfer (HPT) between plant species in a subalpine meadow. The FV and PL networks were largely overlapped. PL network included more links than FV network. The positions of plant and pollinator species in the FV and PL networks were positively correlated, indicating that both networks could detect major plant-pollinator interactions. The degree of pollinator sharing, based on either the FV or the PL network, positively influenced the amount of heterospecific pollen transferred between plant species pairs. However, the degree of pollinator sharing had a low overall explanatory power for HPT, and the explanatory powers of the FV and PL networks were similar. Overall, our study highlights the importance of FV and PL for understanding the drivers and outcomes of plant-pollinator interactions, as well as their relevance to HPT.

Ranking species in complex ecosystems through nestedness maximization

Identifying the rank of species in a complex ecosystem is a difficult task, since the rank of each species invariably depends on the interactions stipulated with other species through the adjacency matrix of the network. A common ranking method in economic and ecological networks is to sort the nodes such that the layout of the reordered adjacency matrix looks maximally nested with all nonzero entries packed in the upper left corner, called Nestedness Maximization Problem (NMP). Here we solve this problem by defining a suitable cost-energy function for the NMP which reveals the equivalence between the NMP and the Quadratic Assignment Problem, one of the most important combinatorial optimization problems, and use statistical physics techniques to derive a set of self-consistent equations whose fixed point represents the optimal nodes’ rankings in an arbitrary bipartite mutualistic network. Concurrently, we present an efficient algorithm to solve the NMP that outperforms state-of-the-art network-based metrics and genetic algorithms. Eventually, our theoretical framework may be easily generalized to study the relationship between ranking and network structure beyond pairwise interactions, e.g. in higher-order networks.

Importance of plant and fruit traits on the structure of bird seed dispersal networks in different disturbed habitats.

Species functional traits can influence seed dispersal processes and consequently affect species' role in the mutualistic network. Although the effect of animal traits on the structure of the seed dispersal network is well explored, it remains poorly understood how plant and fruit traits contribute to the structure. We here studied the effects of plant and fruit traits on the structure of bird seed dispersal networks across different disturbed habitats in the Meihua Mountain National Nature Reserve, Southeastern China. During the study period, 16, 20, 13, and 15 bird species were recorded foraging on 10, 11, 12, and 8 plant species, resulting in 511, 312, 265, and 201 foraging events in the protected forest, natural forest, village, and bamboo forest, respectively. The composition of these seed dispersal networks is not primarily influenced by a specific group of bulbul species, but rather by the presence of an endangered plant species, Taxus chinensis. As we expected, the structure of the four networks was different among the four disturbed habitats. Furthermore, our results also showed tree height and canopy density were the most important plant traits for structuring the seed dispersal network, while sugar, amylase, dry matter, and alkaloids were identified as significant fruit traits. Overall, our findings highlight the value of integrating trait-based ecology into the framework of the seed dispersal network and provide new insights for mutualistic network conservation in disturbed habitats.