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1. Local and Landscape Factors Influence Plant-Pollinator Networks and Bee Foraging Behavior across an Urban Corridor

   https://doi.org/10.3390/land12020362  

   Pardee, Gabriella L; Ballare, Kimberly M; Neff, John L; Do, Lauren Q; Ojeda, DianaJoyce; Bienenstock, Elisa J; Brosi, Berry J; Grubesic, Tony H; Miller, Jennifer A; Tong, Daoqin; et al (February 2023, Land)

   Given widespread concerns over human-mediated bee declines in abundance and species richness, conservation efforts are increasingly focused on maintaining natural habitats to support bee diversity in otherwise resource-poor environments. However, natural habitat patches can vary in composition, impacting landscape-level heterogeneity and affecting plant-pollinator interactions. Plant-pollinator networks, especially those based on pollen loads, can provide valuable insight into mutualistic relationships, such as revealing the degree of pollination specialization in a community; yet, local and landscape drivers of these network indices remain understudied within urbanizing landscapes. Beyond networks, analyzing pollen collection can reveal key information about species-level pollen preferences, providing plant restoration information for urban ecosystems. Through bee collection, vegetation surveys, and pollen load identification across ~350 km of urban habitat, we studied the impact of local and landscape-level management on plant-pollinator networks. We also quantified pollinator preferences for plants within urban grasslands. Bees exhibited higher foraging specialization with increasing habitat heterogeneity and visited fewer flowering species (decreased generality) with increasing semi-natural habitat cover. We also found strong pollinator species-specific flower foraging preferences, particularly for Asteraceae plants. We posit that maintaining native forbs and supporting landscape-level natural habitat cover and heterogeneity can provide pollinators with critical food resources across urbanizing ecosystems. 

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2. Phenological shifts in plants and pollinators over a century disrupt interaction persistence

   Zoller, L; Vázquez, DP; Resasco, J (September 2025, The American naturalist)

   Mutualistic interactions between plants and pollinators play an important role in supporting biodiversity and ecosystem stability. However, these interactions are increasingly threatened by climate change, which can alter the phenology of species and cause temporal mismatches between interacting partners. Leveraging historical and contemporary datasets collected more than a century apart, we investigated phenological shifts in plants and pollinators and the impact of changes in temporal overlap of the interaction partners on the persistence of their interactions. We found that generally, the onset of flowering and insect activity started earlier and has lasted longer in the present. We also found that greater temporal overlap of plant and pollinator species predicted a higher probability of persistence of their interaction between time periods. Our results document phenological shifts over a century, and emphasize the importance of maintaining phenological matching for the persistence of plant-pollinator interactions. This illustrates the value of historical data sets for understanding long-term ecological dynamics in the face of accelerating environmental change. 

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3. Experimental evidence of the importance of multitrophic structure for species persistence

   https://doi.org/10.1073/pnas.2023872118  

   Bartomeus, Ignasi; Saavedra, Serguei; Rohr, Rudolf P.; Godoy, Oscar (March 2021, Proceedings of the National Academy of Sciences)

   Ecological theory predicts that species interactions embedded in multitrophic networks shape the opportunities for species to persist. However, the lack of experimental support of this prediction has limited our understanding of how species interactions occurring within and across trophic levels simultaneously regulate the maintenance of biodiversity. Here, we integrate a mathematical approach and detailed experiments in plant–pollinator communities to demonstrate the need to jointly account for species interactions within and across trophic levels when estimating the ability of species to persist. Within the plant trophic level, we show that the persistence probability of plant species increases when introducing the effects of plant–pollinator interactions. Across trophic levels, we show that the persistence probabilities of both plants and pollinators exhibit idiosyncratic changes when experimentally manipulating the multitrophic structure. Importantly, these idiosyncratic effects are not recovered by traditional simulations. Our work provides tractable experimental and theoretical platforms upon which it is possible to investigate the multitrophic factors affecting species persistence in ecological communities. 

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

   https://doi.org/10.1093/icb/icae074  

   Anderson, Christopher_R; Curtsdotter, Alva_R_K; Staniczenko, Phillip_P_A; Valdovinos, Fernanda_S; Brosi, Berry_J (June 2024, Integrative And Comparative Biology)

   Synopsis 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. 

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5. Mutualistic networks: moving closer to a predictive theory

   https://doi.org/10.1111/ele.13279  

   Valdovinos, Fernanda_S; Hillebrand, ed., Helmut (June 2019, Ecology Letters)

   Abstract 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. 

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