Interaction rewiring and the rapid turnover of plant–pollinator networks

CaraDonna, Paul J.; Petry, William K.; Brennan, Ross M.; Cunningham, J L; Bronstein, Judith L.; Waser, Nickolas M.; Sanders, Nathan J.

doi:10.1111/ele.12740

Cited by 293 publications

(402 citation statements)

References 54 publications

(56 reference statements)

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“…While previous studies based on temporal dynamics have focused on the seasonal turnover of interactions ( e.g. Olesen et al ; CaraDonna et al ), this is the first study to provide a quantitative description of the seasonal changes in the metrics of a plant–visitor interaction network. To our knowledge, it is also the first study to assess the effect of temporal data aggregation on quantitative network descriptors.…”

Section: Discussionmentioning

confidence: 97%

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Sajjad

Saeed

Ali

et al. 2017

Entomological Research

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Seasonal turnover in plant and floral visitor communities changes the structure of the network of interactions they are involved in. Despite the dynamic nature of plant–visitor networks, a usual procedure is to pool year‐round interaction data into a single network which may result in a biased depiction of the real structure of the interaction network. The annual temporal dynamics and the effect of merging monthly data have previously been described for qualitative data (i.e. describing the occurrence of interactions) alone, while its quantitative aspect (i.e. the actual frequency with which interactions occur) remain little explored. For this, we built a set of 12 monthly networks describing year‐round plant–floral visitor interactions in a 30‐hectare planted forest and its adjacent agricultural landscape at Bahauddin Zakariya University Multan, Pakistan. A total of 80 plant and 162 insect species, which engaged in 1573 unique interactions, were recorded. Most network properties (particularly the number of plants, visitors and unique interactions) varied markedly during the year. Data aggregation showed that while animal species, plant species, unique interaction, weighted nestedness, interaction diversity and robustness increased, connectance and specialization decreased. The only metric which seemed relatively unaffected by data pooling was interaction evenness. In general, quantitative metrics were relatively less affected by temporal data aggregation than qualitative ones. Avoiding data aggregation not only gives a more realistic depiction of the dynamic nature of plant–visitor community networks, but also avoids biasing network metrics and, consequently, their expected response to disturbances such as the loss of species.

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Section: Discussionmentioning

confidence: 97%

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Sajjad

Saeed

Ali

et al. 2017

Entomological Research

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“…It is alarming that during disassembly processes following habitat loss competitive release seems to promote rewiring of generalized rather than specialized interactions, which may decrease resilience to environmental change (CaraDonna et al. ).…”

Section: Discussionmentioning

confidence: 99%

Partitioning wild bee and hoverfly contributions to plant–pollinator network structure in fragmented habitats

Jauker

Graß

et al. 2019

Ecology

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The risk of ecosystem function degradation with biodiversity loss has emerged as a major scientific concern in recent years. Possible relationships between taxonomic diversity and magnitude and stability of ecosystem processes build upon species' functional characteristics, which determine both susceptibility to environmental change and contribution to ecosystem properties. The functional diversity within communities thus provides a potential buffer against environmental disturbance, especially for properties emerging from interactions among species. In complex plant–pollinator networks, distantly related taxa spanning a great trait diversity shape network architecture. Here, we address the question of whether network properties are maintained after habitat loss by complementary contributions of phylogenetically distant pollinator taxa. We quantified contributions of wild bees and hoverflies to network structure (connectance, network specialization, specialization asymmetry) in 32 calcareous grassland fragments varying in size. Although hoverflies are often regarded less susceptible to environmental change than wild bees, species richness of both taxa was similarly affected by habitat loss. The associated loss of 80% of interactions resulted in small and tightly connected networks, which was more strongly attributed to wild bee loss than hoverfly loss. Networks in small fragments were less specialized due to equivalent losses of species and interactions in both pollinators and plants. Because wild bee and hoverfly loss contributed similarly to declining network specialization, we conclude that trait diversity among distantly related pollinators does not necessarily provide insurance against functional homogenization during community disassembly following habitat loss.

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“…In pollination networks, for example, studies have suggested that it will be essential to know the match between plant and pollinator traits in order to understand how the interaction network works, as well as for predicting changes in their structure (Garibaldi et al., ; Maglianesi, Blüthgen, Böhning‐Gaese, & Schleuning, ), but see Bartomeus, Cariveau, Harrison, and Winfree (); CaraDonna et al. (). Likewise, results from experiments have shown that body mass can largely influence biotic interactions, in particular predator–prey links (Brose, ; Brousseau, Gravel, & Handa, ; Gravel et al., ).…”

Section: Introductionmentioning

confidence: 99%

Assessing changes in arthropod predator–prey interactions through DNA‐based gut content analysis—variable environment, stable diet

et al. 2018

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Analysing the structure and dynamics of biotic interaction networks and the processes shaping them is currently one of the key fields in ecology. In this paper, we develop a novel approach to gut content analysis, thereby deriving a new perspective on community interactions and their responses to environment. For this, we use an elevational gradient in the High Arctic, asking how the environment and species traits interact in shaping predator-prey interactions involving the wolf spider Pardosa glacialis. To characterize the community of potential prey available to this predator, we used pitfall trapping and vacuum sampling. To characterize the prey actually consumed, we applied molecular gut content analysis. Using joint species distribution models, we found elevation and vegetation mass to explain the most variance in the composition of the prey community locally available. However, such environmental variables had only a small effect on the prey community found in the spider's gut. These observations indicate that Pardosa exerts selective feeding on particular taxa irrespective of environmental constraints. By directly modelling the probability of predation based on gut content data, we found that neither trait matching in terms of predator and prey body size nor phylogenetic or environmental constraints modified interaction probability. Our results indicate that taxonomic identity may be more important for predator-prey interactions than environmental constraints or prey traits. The impact of environmental change on predator-prey interactions thus appears to be indirect and mediated by its imprint on the community of available prey.

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Interaction rewiring and the rapid turnover of plant–pollinator networks

Cited by 293 publications

References 54 publications

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Partitioning wild bee and hoverfly contributions to plant–pollinator network structure in fragmented habitats

Assessing changes in arthropod predator–prey interactions through DNA‐based gut content analysis—variable environment, stable diet

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