Understanding the processes driving ecological resilience, that is the extent to which systems retain their structure while absorbing perturbations, is a central challenge for theoretical and applied ecologists. Plant-insect assemblages are well-suited for the study of ecological resilience as they are species-rich and encompass a variety of ecological interactions that correspond to essential ecosystem functions. Mechanisms affecting community response to perturbations depend on both the natural history and structure of ecological interactions. Natural history attributes of the interspecific interactions, for example whether they are mutualistic or antagonistic, may affect the ecological resilience by controlling the demographic feedbacks driving ecological dynamics at the community level. Interaction generalisation may also affect resilience, by defining opportunities for interaction rewiring, the extent to which species are able to switch interactions in fluctuating environments. These natural history attributes may also interact with network structure to affect ecological resilience. Using adaptive network models, we investigated the resilience of plant-pollinator and plant-herbivore networks to species loss. We specifically investigated how fundamental natural history differences between these systems, namely the demographic consequences of the interaction and their level of generalisation-mediating rewiring opportunities-affect the resilience of dynamic ecological networks to extinctions. We also create a general benchmark for the effect of network structure on resilience simulating extinctions on theoretical networks with controlled structures. When network structure was static, pollination networks were less resilient than herbivory networks; this is related to their high levels of nestedness and the reciprocally positive feedbacks that define mutualisms, which made co-extinction cascades more likely and longer in plant-pollinator assemblages. When considering interaction rewiring, the high generalisation and the structure of pollination networks boosted their resilience to extinctions, which approached those of herbivory networks. Simulation results using theoretical networks suggested that the empirical structure of herbivory networks may protect them from collapse. Elucidating the ecological and evolutionary processes driving interaction rewiring is key to understanding the resilience of plant-insect assemblages. Accounting for rewiring requires ecologists to combine natural history with network models that incorporate feedbacks between species abundances, traits and interactions. This combination will elucidate how perturbations propagate at community level, reshaping biodiversity structure and ecosystem functions.
Compreender os processos que governam a resiliência dos sistemas ecológicos, i.e. o quanto sistemas ecológicos conservam sua estrutura enquanto absorvem perturbações, é um desafio central para ecólogos teóricos e aplicados. Comunidades de insetos e plantas são bons modelos para o estudo da resiliência ecológica pois são ricos em espécies, representando uma grande diversidade de interações ecológicas que correspondem a serviços ecossistêmicos essenciais. Os mecanismos que afetam a resposta de comunidades ecológicas a perturbações dependem tanto da história natural quanto da estrutura das interações ecológicas. A história natural de interações interespecíficas, e.g. se a interação é mutualística ou antagonística, pode afetar a resiliência do sistema ao controlar as retroalimentações demográficas que governam a dinâmica ecológica no nível da comunidade. Generalismo nas interações também pode afetar resiliência ao definir as oportunidades de rewiring de interações, i.e. o quanto espécies são capazes de mudar interações em ambientes instáveis. Atributos da história natural das interações podem também interagir com a estrutura de redes ecológicas de forma a influenciar a resiliência de sistemas ecológicos. Usando modelos de redes adaptativas, investigamos a resiliência de redes polinizador-planta e herbívoro-planta à perda de espécies. Especificamente, investigamos como diferenças fundamentais na história natural dos dois sistemas, isto é, as consequências demográficas da interação e seu grau de generalização - que mediam as oportunidades de rewiring - afetam a resiliência de redes ecológicas dinâmicas a extinções. Também criamos um referencial teórico e abrangente para o efeito da estrutura das redes em sua resiliência, simulando extinções em redes teóricas com estruturas controladas. Quando a estrutura das redes foi considerada estática, redes de polinização foram menos resilientes do que redes de herbivoria; o que está associado aos maiores níveis de aninhamento e aos efeitos demográficos positivos e recíprocos que definem mutualismos, aumentando a probabilidade e o comprimento das cascatas de extinção em redes polinizador-planta. Ao incorporar rewiring de interações, a alta generalização e a estrutura das redes de polinização impulsionou sua resiliência a extinções, que se aproximou da resiliência de redes de herbivoria. Os resultados das simulações com redes teóricas sugerem que estrutura de redes de herbivoria protegem esses sistemas do colapso. Compreender quais processos ecológicos e evolutivos governam o rewiring de interações é chave se queremos prever a resiliência de sistemas inseto-planta. Para incorporar rewiring de interações, será necessário combinar conhecimento sobre história natural com modelos de rede que incorporem a retroalimentação entre abundâncias, atributos e interações das espécies envolvidas. Essa combinação elucidará como perturbações se propagam no nível de comunidades ecológicas, reconfigurando a estrutura da biodiversidade e suas funções ecossistêmicas.

UNASSIGNED: Plant-pollinator mutualistic networks show non-random structural properties that promote species coexistence. However, these networks show high variability in the interacting species and their connections. Mismatch between plant and pollinator attributes can prevent interactions, while trait matching can enable exclusive access, promoting pollinators\' niche partitioning and, ultimately, modularity. Thus, plants belonging to specialized modules should integrate their floral traits to optimize the pollination function. Herein, we aimed to analyze the biological processes involved in the structuring of plant-hummingbird networks by linking network morphological constraints, specialization, modularity and phenotypic floral integration.
UNASSIGNED: We investigated the understory plant-hummingbird network of two adjacent habitats in the Lacandona rainforest of Mexico, one characterized by lowland rainforest and the other by savanna-like vegetation. We performed monthly censuses to record plant-hummingbird interactions for 2 years (2018-2020). We also took hummingbird bill measurements and floral and nectar measurements. We summarized the interactions in a bipartite matrix and estimated three network descriptors: connectance, complementary specialization (H2\'), and nestedness. We also analyzed the modularity and average phenotypic floral integration index of each module.
UNASSIGNED: Both habitats showed strong differences in the plant assemblage and network dynamics but were interconnected by the same four hummingbird species, two Hermits and two Emeralds, forming a single network of interaction. The whole network showed low levels of connectance (0.35) and high specialization (H2\' = 0.87). Flower morphologies ranged from generalized to specialized, but trait matching was an important network structurer. Modularity was associated with morphological specialization. The Hermits Phaethornis longirostris and P. striigularis each formed a module by themselves, and a third module was formed by the less-specialized Emeralds: Chlorestes candida and Amazilia tzacatl. The floral integration values were higher in specialized modules but not significantly higher than that formed by generalist species.
UNASSIGNED: Our findings suggest that biological processes derived from both trait matching and \"forbidden\" links, or nonmatched morphological attributes, might be important network drivers in tropical plant-hummingbird systems while morphological specialization plays a minor role in the phenotypic floral integration. The broad variety of corolla and bill shapes promoted niche partitioning, resulting in the modular organization of the assemblage according to morphological specialization. However, more research adding larger datasets of both the number of modules and pollination networks for a wider region is needed to conclude whether phenotypic floral integration increases with morphological specialization in plant-hummingbird systems.

Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap and species abundances. How these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographical scale. For 24 quantitative networks sampled throughout the Americas, we found that the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low-temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.

Plant-animal mutualistic networks sustain terrestrial biodiversity and human food security. Global environmental changes threaten these networks, underscoring the urgency for developing a predictive theory on how networks respond to perturbations. Here, I synthesise theoretical advances towards predicting network structure, dynamics, interaction strengths and responses to perturbations. I find that mathematical models incorporating biological mechanisms of mutualistic interactions provide better predictions of network dynamics. Those mechanisms include trait matching, adaptive foraging, and the dynamic consumption and production of both resources and services provided by mutualisms. Models incorporating species traits better predict the potential structure of networks (fundamental niche), while theory based on the dynamics of species abundances, rewards, foraging preferences and reproductive services can predict the extremely dynamic realised structures of networks, and may successfully predict network responses to perturbations. From a theoretician\'s standpoint, model development must more realistically represent empirical data on interaction strengths, population dynamics and how these vary with perturbations from global change. From an empiricist\'s standpoint, theory needs to make specific predictions that can be tested by observation or experiments. Developing models using short-term empirical data allows models to make longer term predictions of community dynamics. As more longer term data become available, rigorous tests of model predictions will improve.

One of the major challenges in ecology is to understand the relative importance of neutral- and niche-based processes structuring species interactions within communities. The concept of neutral-based processes posits that network structure is a result of interactions between species based on their abundance. On the other hand, niche-based processes presume that network structure is shaped by constraints to interactions. Here, we evaluated the relative importance of neutral-based process, represented by species\' abundance (A) and fruit production (F) models, and niche-based process, represented by spatial overlap (S), temporal overlap (T) and morphological barrier (M) models, in shaping the structure of a bird-seed dispersal network from the Brazilian Atlantic Forest. We evaluated the ability of each model, singly or in combination, to predict the general structure [represented by connectance, nestedness (NODF), weight nestedness (WNODF), interaction evenness and complementary specialization] and microstructure of the network (i.e., the frequency of pairwise interactions). Only nestedness (both NODF and WNODF) was predicted by at least one model. NODF and WNODF were predicted by a neutral-based process (A), by a combination of niche-based processes (ST and STM) and by both neutral- and niche-based processes (AM). NODF was also predicted by F and FM model. Regarding microstructure, temporal overlap (T) was the most parsimonious model able to predict it. Our findings reveal that a combination of neutral- and niche-based processes is a good predictor of the general structure (NODF and WNODF) of the bird-seed dispersal network and a niche-based process is the best predictor of the network\'s microstructure.

Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 \'), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks.