Species Interaction Networks Research Articles

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.

A Critical Evaluation of Network Approaches for Studying Species Interactions

Ecological networks of species interactions are popular and provide powerful analytical tools for understanding variation in community structure and ecosystem functioning. However, network analyses and commonly used metrics such as nestedness and connectance have also attracted criticism. One major concern is that observed patterns are misinterpreted as niche properties such as specialization, whereas they may instead merely reflect variation in sampling, abundance, and/or diversity. As a result, studies potentially draw flawed conclusions about ecological function, stability, or coextinction risks. We highlight potential biases in analyzing and interpreting species-interaction networks and review the solutions available to overcome them, among which we particularly recommend the use of null models that account for species abundances. We show why considering variation across species and networks is important for understanding species interactions and their consequences. Network analyses can advance knowledge on the principles of species interactions but only when judiciously applied.

Unraveling Community Potential Interactions by Environmental DNA in the Hong Kong Coastal Waters

ABSTRACTTraditional approaches for studying potential interactions in marine ecosystems often struggle to fully capture all taxa in a community, especially rare species. This issue is particularly challenging in coastal waters with high biodiversity and spatiotemporal dynamics. In this study, we employed environmental DNA (eDNA) metabarcoding, utilizing multiple marker genes, to comprehensively investigate interspecific interactions across various domains in the subtropical coastal waters of Hong Kong. The southern and eastern regions of Hong Kong waters exhibit distinct environmental seasonality, and our investigation focused on comparing the potential interaction networks and the keystone taxa between these two regions. The putative species interaction networks across various groups (i.e., bacteria, protists, and metazoans) were revealed by using weighted correlation network analysis (WGCNA). Our results showed that primary consumers, mainly dinoflagellates and ciliates, were the dominant actors within the interaction networks, although their distributions varied between the two regions. Bacterial taxa from the Pseudomonadota groups primarily constituted saprobes in the southern region, while exhibiting an even distribution in the eastern region. The interaction network in the southern region was larger but less stable compared to the eastern region. This could be attributed to the stronger responses of keystone taxa to environmental variations and the relatively higher number of connectors (e.g., Akashiwo and Protoperidinium within Dinophyceae) in the eastern region. Our findings highlight the versatility of eDNA metabarcoding for studying potential species interactions, providing critical insights into ecosystem structure and stability, and offering suggestions for marine biodiversity conservation.

Phenology mediates direct and indirect interactions among co-occurring invasive plant species.

Why nonnative invasive plant species commonly co-occur, despite their competitive superiority and propensity to displace native species, remains a paradox in invasion biology. Negative interactions among competitively dominant invaders are potentially alleviated by two understudied mechanisms: seasonal priority effects, where phenological separation weakens the effect of competition on species with early phenology; and indirect facilitation, where competition between two species is mitigated by a third species. Although phenological separation has been speculated as a mechanism for explaining co-occurrence patterns of invasive plants, it has never been directly tested. In a greenhouse experiment, we tested the effect of phenological separation on direct and indirect interactions between three co-occurring invasive plant species found in the riparian forests of North America. These species have distinct natural phenological separation with reproduction in early spring (Ficaria verna), mid-spring (Alliaria petiolata), and late summer (Microstegium vimineum). When phenology was experimentally synchronized, direct pairwise interactions among invasive species were overwhelmingly negative, asymmetric, and unlikely to promote co-occurrence. However, increasing phenological separation generated seasonal priority effects, which weakened the effect of competition on species with early phenology. Furthermore, the addition of a third species generated indirect facilitative effects, which balanced competitive outcomes among the two weakest competitors. Based on these findings, we conclude that phenological separation modulates the strength of both seasonal priority effects and indirect facilitation within species interaction networks and may promote the co-occurrence of three common invasive species within this study system. We articulate how future studies can test the external validity of these findings in more complex environmental conditions and with a larger range of invasive plants.

Disentangling the complexity of plant-bird relationships: From monolayer to multilayer network perspectives

Most plant-bird interaction research employing complex ecological networks focuses on pollination and seed dispersal interactions. However, birds and plants are immersed in a great variety and complexity of direct and indirect relationships. Therefore, the use of multilayer networks (i.e., species interaction networks involving different types of interactions) could provide new insights into the ecological and coevolutionary dynamics of plant-bird relationships. Here, we used a multilayer network approach to determine how a bird-plant interaction network involving different types of interactions (i.e., foraging for invertebrates on plants, frugivory, nectarivory, and perching) is organized in a peri-urban Mexican cloud forest. Moreover, we added information about the interactive roles of the winter migratory and resident birds in the multilayer network. In general, we found that the bird-plant multilayer network exhibits modular but a non-nested structure. We also observed that interactions involving perching and foraging for invertebrates on plants are more frequent than frugivory and nectarivory. Moreover, just a small proportion of birds and plant species were important to the network organization and for connecting different interaction types. In this case, we observed that only two bird species, Cardellina pusilla (Parulidae) and Dumetella carolinesis (Mimidae), and the plant species Telanthophora grandifolia (Asteraceae) and Platanus mexicanus (Platanaceae) presented higher centrality values (i.e., an interactive role). Finally, we found that betweenness values (i.e., the number of times a species acts as a bridge along the shortest path between two species) and network structure's contributions are similar for both migratory and resident bird species. Our results highlight the importance of key interacting species that connect other interacting species for the preservation of community cohesion and to the persistence of species-rich assemblages.

The impact of extraction method and pollen concentration on community composition for pollen metabarcoding

AbstractPremisePlants and pollinators closely interact with each other to form complex networks of species interactions. Metabarcoding of pollen collections has recently been proposed as an advantageous method for the construction of such networks, but the extent to which diversity and community analyses depend on the extraction method and pollen concentration used remains unclear.MethodsIn this study, we used a dilution series of two pollen mixtures (a mock community and pooled natural pollen loads from bumblebees) to assess the effect of mechanical homogenization and two DNA extraction kits (spin column DNA extraction kit and magnetic bead DNA extraction kit) on the detected pollen richness and community composition.ResultsAll species were successfully detected using the three methods, even in the most dilute samples. However, the extraction method had a significant effect on the detected pollen richness and community composition, with simple mechanical homogenization introducing an extraction bias.DiscussionOur findings suggest that all three methods are effective for detecting plant species in the pollen loads on insects, even in cases of very low pollen loads. However, our results also indicate that extraction methods can have a profound impact on the ability to correctly assess the community composition of the pollen loads on insects. The choice of extraction methodology should therefore be carefully considered to ensure reliable and unbiased results in pollen diversity and community analyses.

Stronger together: different community science platforms all contribute to wildlife research

Context Engaging the general public can increase spatio-temporal coverage of wildlife monitoring. Given the potentially substantial costs, we need to evaluate the contribution of known and planned initiatives and confirm whether multiple platforms increase the efficiency of data collection. As observer behaviour affects data quantity and quality, users of specialised and generalist platforms are expected to behave differently, resulting in more connected networks for specialised and higher nestedness for generalist platforms. Specialist observers are expected to contribute a balanced ratio of rare and common species, whereas non-specialist contribution will depend more on species detectability. Aims We aim to evaluate whether the combined contribution of observers from different platforms can improve the quality of occurrence and distribution data of 218 endemic Atlantic Forest bird species in Brazil. We also describe and compare observer-bird species interaction networks to illustrate observer behaviour on different platforms. Methods On the basis of data from five community science platforms in Brazil, namely, eBird, WikiAves, Biofaces, iNaturalist and Táxeus, we compared the spatial distribution of bird observations, the number of observers, the presence of the same observers on various platforms, bird species coverage, and the proportion of duplicate observations within and among platforms. Key results Although species coverage of the joint dataset increased by up to 100%, spatial completeness among the five platforms was low. The network of individual platforms had low values of clustering, and the network of the joint dataset had low connectance and high nestedness. Conclusions Each platform had a somewhat unique contribution. Pooling these datasets and integrating them with standardised data can inform our knowledge on bird distributions and trends in this fragile biome. Nevertheless, we encourage observers to provide precise coordinates, dates and other data (and platforms to accommodate such data) and recommend submitting data from all platforms into the Global Biodiversity Information Facility to support wildlife research and conservation. Implications If new platforms engage more and different people, new initiatives can cover poorly represented areas and successfully expand monitoring effort for Atlantic Forest endemic bird species.

Disturbance-mediated changes to boreal mammal spatial networks in industrializing landscapes.

Compound effects of anthropogenic disturbances on wildlife emerge through a complex network of direct responses and species interactions. Land-use changes driven by energy and forestry industries are known to disrupt predator-prey dynamics in boreal ecosystems, yet how these disturbance effects propagate across mammal communities remains uncertain. Using structural equation modeling, we tested disturbance-mediated pathways governing the spatial structure of multipredator multiprey boreal mammal networks across a landscape-scale disturbance gradient within Canada's Athabasca oil sands region. Linear disturbances had pervasive direct effects, increasing site use for all focal species, except black bears and threatened caribou, in at least one landscape. Conversely, block (polygonal) disturbance effects were negative but less common. Indirect disturbance effects were widespread and mediated by caribou avoidance of wolves, tracking of primary prey by subordinate predators, and intraguild dependencies among predators and large prey. Context-dependent responses to linear disturbances were most common among prey and within the landscape with intermediate disturbance. Our research suggests that industrial disturbances directly affect a suite of boreal mammals by altering forage availability and movement, leading to indirect effects across a range of interacting predators and prey, including the keystone snowshoe hare. The complexity of network-level direct and indirect disturbance effects reinforces calls for increased investment in addressing habitat degradation as the root cause of threatened species declines and broader ecosystem change.

Plant interactions can lead to emergent relationships between plant community diversity, productivity and vulnerability to invasion

Understanding what makes a community vulnerable to invasion is integral to the successful management of invasive species. Our understanding of how characteristics of resident plant interactions, such as the network architecture of interactions, can affect the invasibility of plant communities is limited. Using a simulation model, we tested how successfully a new plant invader established in communities with different network architectures of species interactions. We also investigated whether species interaction networks lead to relationships between invasibility and other community properties also affected by species interaction networks, such as diversity, species dominance, compositional stability and the productivity of the resident community. We found that higher invasibility strongly related with a lower productivity of the resident community. Plant interaction networks influenced diversity and invasibility in ways that led to complex but clear relationships between the two. Heterospecific interactions that increased diversity tended to decrease invasibility. Negative conspecific interactions always increased diversity and invasibility, but increased invasibility more when they increased diversity less. This study provides new theoretical insights into the effects of plant interaction networks on community invasibility and relationships between diversity and invasibility. Combined with increasing empirical evidence, these insights could have useful implications for the management of invasive plant species.

Scaling approaches and macroecology provide a foundation for assessing ecological resilience in the Anthropocene.

In the Anthropocene, intensifying ecological disturbances pose significant challenges to our predictive capabilities for ecosystem responses. Macroecology-which focuses on emergent statistical patterns in ecological systems-unveils consistent regularities in the organization of biodiversity and ecosystems. These regularities appear in terms of abundance, body size, geographical range, species interaction networks, or the flux of matter and energy. This paper argues for moving beyond qualitative resilience metaphors, such as the 'ball and cup', towards a more quantitative macroecological framework. We suggest a conceptual and theoretical basis for ecological resilience that integrates macroecology with a stochastic diffusion approximation constrained by principles of biological symmetry. This approach provides an alternative novel framework for studying ecological resilience in the Anthropocene. We demonstrate how our framework can effectively quantify the impacts of major disturbances and their extensive ecological ramifications. We further show how biological scaling insights can help quantify the consequences of major disturbances, emphasizing their cascading ecological impacts. The nature of these impacts prompts a re-evaluation of our understanding of resilience. Emphasis on regularities of ecological assemblages can help illuminate resilience dynamics and offer a novel basis to predict and manage the impacts of disturbance in the Anthropocene more efficiently. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Interaction network rewiring and species' contributions to community-scale flexibility.

The architecture of species interaction networks is a key factor determining the stability of ecological communities. However, the fact that ecological network architecture can change through time is often overlooked in discussions on community-level processes, despite its theoretical importance. By compiling a time-series community dataset involving 50 spider species and 974 Hexapoda prey species/strains, we quantified the extent to which the architecture of predator-prey interaction networks could shift across time points. We then developed a framework for finding species that could increase the flexibility of the interaction network architecture. Those "network coordinator" species are expected to promote the persistence of species-rich ecological communities by buffering perturbations in communities. Although spiders are often considered as generalist predators, their contributions to network flexibility vary greatly among species. We also found that detritivorous prey species can be cores of interaction rewiring, dynamically interlinking below-ground and above-ground community dynamics. We further found that the predator-prey interactions between those network coordinators differed from those highlighted in the standard network-analytical framework assuming static topology. Analyses of network coordinators will add a new dimension to our understanding of species coexistence mechanisms and provide platforms for systematically prioritizing species in terms of their potential contributions in ecosystem conservation and restoration.

Plant neighbourhood effects on insect herbivores associated with Junipers and Pistacia in Cyrenaica- Libya

This research set out to test whether there are neighbourhood effects on insect herbivory among the plants of the Al Jabal Al Akhdar region of Libya. Neighbouring plants in the locale of an individual plant might help or hinder it in the task of defence against insect herbivores, depending on their levels of defence (chemical or physical), and their interactions with potential herbivores. Such ‘neighbourhood effects’ are part of the complex network of species interactions that structure ecological communities. Having chosen to concentrate on the two main species of three study sites, Juniperus phoenicea and Pistacia atlantica, nine plots were mapped in detail and the insect herbivores sampled from focal plants, and then from all plants. Plant leaves of Juniperus and Pistacia were sampled for chemical analysis of their phenol content. Phenol levels were much higher in Pistacia (2308 ± 43 ppm, n = 45), than in Juniperus (1516 ± 43 ppm, n = 45), and there were effects of elevation as well, plants from middle elevation plots had the highest levels, while those from the lowest elevation at the coast had the lowest levels of tannins. The number of individual insects per plant was affected by the neighbourhood in both Pistacia No. individuals on the nearest conspecific (x2 = 5.22, df = 1, P = 0.022) and No. individuals on the nearest allospecific (x2 = 52.12, df = 1, P = 0.00) and Juniperus No. individuals on the nearest conspecific (x2 = 43.89, df = 1, P = <.001) and No. individuals on the nearest allospecific (x2 = 93.89, df = 1, P = <.001). There were clear effects of neighbouring plants on the density of insects of individual plants, in both Pistacia and Juniperus. From analysis result we found that the number of insect herbivores were a strongly affected by the local neighbourhood plant species, which attacked the focal shrubs (Juniperus sp and Pistacia sp) in the study sites, where the number of insect herbivores were not affected by the same neighbourhood (surroundings) plant species, however, the different neighbourhood plant species affected in each insect herbivores. There were no signs of any protective neighbourhood effects of tannin levels. Thus in the plant communities of Al Jabal Al Akhdar, associational avoidance appears to be the major mechanism of neighbourhood effects, rather than associational resistance.

Transgenerational coexistence history attenuates negative direct interactions and strengthens facilitation

Abstract Interactions among species are a fundamental aspect of biodiversity and drive ecosystem functioning and services. Species interactions include direct (pairwise) interactions among two species and indirect interactions that occur when a third species interacts and changes the pairwise direct interaction. In a three‐species interaction network, these interactions can be transitive (where one species outperforms all others) or intransitive (where each species outperforms another). Here, we investigate how direct and indirect interactions influence ecosystem functions in crop systems and how diversification and evolutionary adaptation can influence those interactions and therefore ecosystem functions. A common garden experiment was conducted with crop communities in monocultures, 2‐ and 3‐species mixtures that had either a common or no coexistence history (i.e. co‐adaptation) for the three previous years. Net, direct and indirect interaction intensities were estimated and compared between the diversity levels and coexistence histories. Furthermore, species interaction networks were inspected for transitive/intransitive interactions. We found evidence for less intense competition in mixtures and for reduced negative direct interaction intensity and enhanced facilitative effects upon co‐adaptation. We could further show that indirect interactions were generally less important for co‐adaptation than direct interactions. Additionally, we showed that co‐adaptation has the potential to shift interactions in the species interaction networks from competitive intransitive into pairwise competitive interactions where interactions occurred mainly between two species. Synthesis. Co‐adapted crop species with reduced negative interactions might have the potential to enhance productivity, especially in more diverse cropping systems. This supports the notion that intercropping is a vital part towards a more sustainable agriculture and one with further yield potential when developing cultivars optimised for growth in mixtures.

The Restructuring of Ecological Networks by the Pleistocene Extinction

Most terrestrial large mammals went extinct on different continents at the end of the Pleistocene, between 50,000 and 10,000 years ago. Besides the loss in species diversity and the truncation of body mass distributions, those extinctions were even more impactful to interaction diversity. Along with each extinction, dozens of ecological interactions were lost, reorganizing species interaction networks, which attained species-poor configurations with low functional redundancy. Extinctions of most large herbivores impacted energy flow and the rates of nutrient cycling, reconfiguring ecosystem-level networks. Because large mammals have high mobility, their loss also shortened seed-dispersal distance and reduced nutrient diffusivity, disrupting spatial networks. This review examines the recent advances in understanding how different types of ecological networks have been restructured by megafaunal extinctions and how this reorganization affected ecosystem functions. ▪Megafaunal extinctions resulted in the loss of multiple ecological interactions in terrestrial systems.▪Interaction loss reshaped different types of ecological networks including food webs and spatial networks.▪The reorganization of ecological networks changed how terrestrial ecosystems are structured and function.

Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs.

Sponges are widely spread organisms in the tropical reefs of the American Northwest-Atlantic Ocean, they structure ecosystems and provide services such as shelter, protection from predators, and food sources to a wide diversity of both vertebrates and invertebrates species. The high diversity of sponge-associated fauna can generate complex networks of species interactions over small and large spatial-temporal gradients. One way to start uncovering the organization of the sponge host-guest complex networks is to understand how the accumulated geographic area, the sponge morphology and, sponge taxonomy contributes to the connectivity of sponge species within such networks. This study is a meta-analysis based on previous sponge host-guest literature obtained in 65 scientific publications, yielding a total of 745 host-guest interactions between sponges and their associated fauna across the Caribbean Sea and the Gulf of Mexico. We analyzed the sponge species contribution to network organization in the Northwest Tropical Atlantic coral reefs by using the combination of seven complementary species-level descriptors and related this importance with three main traits, sponge-accumulated geographic area, functional sponge morphology, and sponges' taxonomy bias. In general, we observed that sponges with a widespread distribution and a higher accumulated geographic area had a greater network structural contribution. Similarly, we also found that Cup-like and Massive functional morphologies trend to be shapes with a greater contribution to the interaction network organization compared to the Erect and Crust-like morphos. Lastly, we did not detect a taxonomy bias between interaction network organization and sponges' orders. These results highlight the importance of a specific combination of sponge traits to promote the diversity of association between reef sponges and their guest species.

Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe

Identifying areas that contain species assemblages not found elsewhere in a region is central to conservation planning.1,2 Species assemblages contain networks of species interactions that underpin species dynamics,3,4 ecosystem processes, and contributions to people.5,6,7 Yet the uniqueness of interaction networks in a regional context has rarely been assessed. Here, we estimated the spatial uniqueness of 10,000 terrestrial vertebrate trophic networks across Europe (1,164 species, 50,408 potential interactions8) based on the amount of similarity between all local networks mapped at a 10km resolution. Our results revealed more unique networks in the Arctic bioregion, but also in southern Europe and isolated islands. We then contrasted the uniqueness of trophic networks with their vulnerability to human footprint and future climate change and measured their coverage within protected areas. This analysis revealed that unique networks situated in southern Europe were particularly exposed to human footprint and that unique networks in the Arctic might be at risk from future climate change. However, considering interaction networks at the level of trophic groups, rather than species, revealed that the general structure of trophic networks was redundant across the continent, in contrast to species' interactions. We argue that proactive European conservation strategies might gain relevance by turning their eyes toward interaction networks that are both unique and vulnerable.

Inferring microbial interactions with their environment from genomic and metagenomic data.

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized, and so name our tool MetConSIN: Metabolically Contextualized Species Interaction Networks.

A network prediction model to quantify relationship between biodiversity and ecosystem functioning (BEF)

Abstract Biodiversity loss has a large impact on many ecosystem functions (EFs). It is urgent to quantify the effect of biodiversity loss on EFs, and much efforts are needed to determine quantitatively the relationship between biodiversity and ecosystem functions (BEF). In this review, we first summarised the mechanistic models commonly applied in current BEF studies, and proposed a new BEF model based on species interaction networks. The ‘network attenuation model’, which is built up by an unsaturated network, quantifies BEF. Then, the implication of network attenuation model for the scale dependence of BEF has been studied. Finally, the network attenuation model has been tested using data from the BIODEPTH project. We found that fitting models with the network attenuation model provided better results than other common fitting methods. The model fitting results revealed the scale dependence in BEF relationships, and demonstrated nonlinear changes in the BEF‐slope with the spatial scale. We conclude that the network attenuation model can be used as an alternative approach to estimate BEF, and the information from this model can provide meaningful guidance for the allocation of resources for conservation efforts worldwide. More efforts will be necessary assess the effect of biodiversity on various EFs as the importance of interactions among species and species richness may also vary over time.

Graph embedding and transfer learning can help predict potential species interaction networks despite data limitations

Abstract Metawebs (networks of potential interactions within a species pool) are a powerful abstraction to understand how large‐scale species interaction networks are structured. Because metawebs are typically expressed at large spatial and taxonomic scales, assembling them is a tedious and costly process; predictive methods can help circumvent the limitations in data deficiencies, by providing a first approximation of metawebs. One way to improve our ability to predict metawebs is to maximize available information by using graph embeddings, as opposed to an exhaustive list of species interactions. Graph embedding is an emerging field in machine learning that holds great potential for ecological problems. Here, we outline how the challenges associated with inferring metawebs line‐up with the advantages of graph embeddings; followed by a discussion as to how the choice of the species pool has consequences on the reconstructed network, specifically as to the role of human‐made (or arbitrarily assigned) boundaries and how these may influence ecological hypotheses.

Impacts of land use change on native plant-butterfly interaction networks from central Mexico.

Land use change is a key catalyst of global biodiversity loss and ecosystem degradation. Deforestation and conversion of natural habitats to agricultural or urban areas can profoundly disrupt plant-flower visitor interactions by altering their abundances and distribution. Yet, specific studies analyzing the effects of land use change on the structure of networks of the interactions between particular groups of flower visitors and their plants are still scarce. Here, we aimed to analyze how converting native habitats affects the species composition of butterfly communities and their plants, and whether this, in turn, leads to changes in the structure of interaction networks in the modified habitats. We performed bi-monthly censuses for a year to record plant-butterfly interactions and assess species diversity across three habitat types, reflecting a land-use change gradient. From original native juniper forest to urban and agricultural zones in central Mexico, one site per land use type was surveyed. Interactions were summarized in matrices on which we calculated network descriptors: connectance, nestedness and modularity. We found highest butterfly diversity in native forest, with the most unique species (i.e., species not shared with the other two sites). Agricultural and urban sites had similar diversity, yet the urban site featured more unique species. The plant species richness was highest in the urban site, and the native forest site had the lowest plant species richness, with most of the plants being unique to this site. Butterfly and plant compositions contrasted most between native forest and modified sites. Network analysis showed differences between sites in the mean number of links and interactions. The urban network surpassed agriculture and native forest networks in links, while the native forest network had more interactions than the agriculture and urban networks. Native plants had more interactions than alien species. All networks exhibited low connectance and significant nestedness and modularity, with the urban network featuring the most modules (i.e., 10 modules). Converting native habitats to urban or agricultural areas reshapes species composition, diversity and interaction network structure for butterfly communities and plants. The urban network showed more links and modules, suggesting intricate urban ecosystems due to diverse species, enhanced resources, and ecological niches encouraging interactions and coexistence. These findings emphasize the impacts of land use change on plant-butterfly interactions and the structure of their interaction networks.