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Most flowering plants depend on pollinators to reproduce. Thus, evaluating the robustness of plant-pollinator assemblages to species loss is a major concern. How species interaction patterns are related to species sensitivity to partner loss may influence the robustness of plant-pollinator assemblages.
In plants, both reproductive dependence on pollinators breeding system and dispersal ability may modulate plant sensitivity to pollinator loss.
World History: Patterns of Interaction
For instance, species with strong dependence e. We compared the interaction patterns of plants differing in dependence on pollinators and dispersal ability in a meta-dataset comprising plant species from 13 plant-pollinator networks. In addition, network robustness was compared under different scenarios representing sequences of plant extinctions associated with plant sensitivity to pollinator loss.
Species with different dependence on pollinators and dispersal ability showed similar levels of generalization.
Patterns of interaction pdf file
Although plants with low dispersal ability interacted with more generalized pollinators, low-dispersal plants with strong dependence on pollinators i.
Only two assemblages showed lower robustness under the scenario considering plant generalization, dependence on pollinators and dispersal ability than under the scenario where extinction sequences only depended on plant generalization i. Overall, our results support the idea that species generalization and network topology may be good predictors of assemblage robustness to species loss, independently of plant dispersal ability and breeding system.
In contrast, since ecological specialization among partners may increase the probability of disruption of interactions, the fact that the plants most sensitive to pollinator loss interacted with more particular pollinator assemblages suggest that the persistence of these plants and their pollinators might be highly compromised.
The robustness of plant-pollinator assemblages to species loss is a main concern of basic and applied Ecology since Understanding how the organization of plant-pollinator interactions may influence species persistence is central to predict the consequences of species loss [ 4 ].
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Ultimately, ecological interactions are shaped by traits and therefore trait-based descriptions of species interactions may provide insights into the organization of interacting assemblages [ 5 ]. In this context, a main challenge is to understand how traits shaping species interaction patterns also influence the sensitivity of species to the loss of interaction partners [ 6 , 7 ].
Plant-pollinator assemblages show consistent patterns in the organization of interactions among species [ 8 ]. In these assemblages, only a few species of plants and pollinators are extremely generalized i.
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Generalists are central to the nested structure of plant-pollinator assemblages, in which ecologically specialized species interact with subsets of species interacting with more generalized species [ 9 , 10 ]. As a consequence, the loss of generalized species decreases the robustness of plant-pollinator assemblages to subsequent species loss [ 11 — 13 ]. Thus, the persistence of generalists may increase the persistence of the whole assemblage [ 11 — 13 ].
In plants, pollination of generalists should be less affected by pollinator loss due to pollinator redundancy [ 14 — 18 , 19 ]. Indeed, generalized plants tend to interact both with generalized and specialized pollinators [ 20 ], which may lead to lower fluctuation of pollinator service [ 15 ] and to lower risk of reproductive failure when specialized pollinators go extinct [ 21 ]. However, plant sensitivity to pollinator loss is not only affected by interaction patterns among plants and pollinators but also by plant breeding system [ 22 — 24 ].
Plant breeding systems modulate the dependence of plants on pollinators to produce seeds [ 22 , 24 ]. Among biotically pollinated plants, self-incompatible and dioecious species are strongly dependent on pollinator services, since pollination will only occur when pollinators have previously visited flowers of compatible and male conspecific plants, respectively.
In contrast, self-compatible species may be less dependent on pollinators because a single visit of pollinators to each individual flower may allow reproduction. Plants having mechanisms to produce seeds without pollinator visits may be even less dependent. As generalization on pollinators may evolve if it decreases the risk of reproductive failure when pollinators fluctuate in abundance [ 15 ], plants with different breeding systems may show different levels of generalization [ 25 ].
Species depending more on pollinators may interact with multiple pollinator species [ 26 ] whereas plants interacting with fewer pollinator species may be less dependent on pollinators [ 27 — 29 ]. Moreover, pollinator-dependent plants would be expected to interact with more generalized pollinators, minimizing temporal fluctuation in pollination services [ 15 , 29 ].
Plant dispersal ability may also modulate plant sensitivity to pollinator loss. Higher dispersal ability has been associated with lower dependence on pollinators i. In contrast, it has recently been shown in theoretical studies that fluctuations in pollination levels may lead to the evolution of two alternative syndromes: outcrossers with high dispersal ability or selfers with low dispersal [ 32 , 33 ]. Indeed, high dispersal ability may increase the persistence of dioecious species [ 34 ].
In this sense, if strongly dependent species can locally persist by dispersing seeds from sites where pollinators are present, then their persistence may be less dependent on local pollinator services. In this study, we investigated how plant interaction patterns varied with plant sensitivity to pollinator loss.
We also explored how this variation might influence the robustness of plant-pollinator assemblages.
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We compiled information on plant breeding system and dispersal mode for species from 13 published plant-pollinator networks. We described the patterns of interaction for each plant species, i. Specifically, we asked how these patterns were associated with the dependence of plants on pollinators and their dispersal ability.
We predicted that plants with strong dependence on pollinators or low dispersal ability may show higher degree of generalization on pollinators, higher contribution to nestedness and interact with more generalized pollinators.
In addition, we investigated how the association of plant generalization, dependence on pollinators and dispersal ability may affect the robustness of plant-pollinator assemblages by simulating sequences of species extinctions. We expected that scenarios where plant generalization level and biological traits affected the probability of extinction of plants would lead to less robust networks than scenarios only considering plant generalization and as robust as the random scenario—i.
We used three network metrics to characterize the patterns of interaction of each species: plant contribution to nestedness, plant ecological generalization on pollinators hereafter plant generalization and mean ecological generalization of plant interaction partners hereafter mean pollinator generalization. We first calculated the proportion of pollinator species shared between a given plant and each plant species of the network.
Then, for each plant, the average proportion of pollinators shared with the other plant species represented its contribution to nestedness.
The mean pollinator generalization for a given plant species was obtained as the mean of the generalization level of all pollinators interacting with the focal plant species.
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We used information on breeding system and dispersal mode to estimate, respectively, plant dependence on pollinators and dispersal ability. For most of the plant species, data on these traits was extracted from published articles S2 Table.
When different studies were available for the same species, we prioritized information obtained in the same study region where networks were characterized. Dispersal mode was also obtained from seed-trait databases 7. We grouped the large diversity of plant breeding systems in three categories depicting the degree of dependence of plants on pollinators to produce seeds. Species where classified as: i strongly dependent plants, including self-incompatible and dioecious species, and obligate outcrossers; ii intermediately dependent plants, including self-compatible species and facultative outcrossers; and iii slightly dependent plants, including autonomous self-pollinating, agamospermous, cleistogamous, and facultative autogamous species.
Dispersal mode was coded in two classes depicting dispersal ability: i low-dispersal plants, including species dispersed by gravity with or without diaspore explosion , and ants; ii high-dispersal plants, including species dispersed by vertebrates, wind and water. We evaluated how plant interaction patterns varied among plants differing in their dependence on pollinators and dispersal ability. In our analysis, plant generalization, contribution to nestedness and mean generalization of pollinators were the response variables, and dependence on pollinators and dispersal ability the explanatory factors.
Patterns Of Interaction Pdf
Since residuals of linear models were not normally distributed but variances among groups were homogeneous, we chose to use the distance-based non-parametric analysis of variance introduced by Anderson [ 40 , 41 ]. We performed these permutation analyses using the Adonis function included in the Vegan package on R [ 42 ]. Particularities of each assemblage such as species richness and connectance i.
Thus, permutations were performed among species within networks.
To determine a posteriori pair-wise differences between levels of factors that influenced the response variables, we performed separated permutation tests following [ 40 ]. Data on plants occurring in more than one network 6 species were included only once in the analyses by randomly choosing one of these networks.
Including or not these 6 species in the analyses did not change the results. We evaluated how plant sensitivity to pollinator loss might influence network robustness by simulating plant extinctions.
Among these 10 networks, species without information on a given trait were randomly assigned with equal probability to one category of the trait at the beginning of each simulation of extinction events. We evaluated network robustness under different simulated scenarios of plant extinctions. We used a fully factorial design leading to eight simulated scenarios in which each plant trait i. Plant sensitivity depending on species generalization represented the ability of plants to cope with fluctuations on the abundances of pollinators or even pollinator loss, associated with pollinator redundancy e.
Thus, plants interacting with multiple pollinators were considered to be less sensitive to pollinator loss than those interacting with a few species. In the case of plant dependence on pollinators and dispersal ability, plant sensitivity represented the ability of plants to cope with pollinator decline with alternative strategies, e.
Simulated scenarios also included a random scenario under which no plant trait affected plant sensitivity. This random scenario represented a null model to compare the effects of the other scenarios on assemblage robustness [ 11 , 13 , 44 ].
To perform extinction sequences, we assigned probabilities of extinction to each plant species according to plant generalization, dependence on pollinators and dispersal ability as follows. For scenarios only considering one of these traits, we first ranked all the species according to a decreasing order of sensitivity to pollinator loss, as explained above.
Thus, in the case of plant dependence on pollinators, strongly dependent species were considered the most sensitive whereas slightly dependent species were the least sensitive.
In relation to dispersal ability, low-dispersal plants were considered the most sensitive whereas high-dispersal species were the least sensitive. In the case of plant generalization on pollinators, higher generalization was associated with lower sensitivity to pollinator loss. Secondly, for the N species within each category of each trait we sampled N extinction probabilities from a truncated exponential distribution, where the lambda parameter was randomly chosen among values ranging from 10 to Thus, species belonging to more sensitive categories were first ranked and received higher extinction probabilities.
Then, we computed the mean extinction probability of the sampled values for each trait category and assigned this mean value to all plants within the category.
Finally, we normalized the probability values across all species i.
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In scenarios taking into account any combination of traits, we assigned extinction probabilities according to each trait as explained above, and we multiplied the set of probabilities for each species.
Then, we normalized these probability values across species in order to obtain the final probability of extinction for each species.
We performed sequences of plant extinction for each scenario. Each sequence included the sequential removal of all plant species.
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A pollinator species died out if all their interacting plants were extinct. After the removal of each plant species, we computed the percentage of surviving pollinator species. Then, we assessed the robustness of the networks following each sequence of extinction by computing the area under the curve describing the proportion of remaining pollinator species against the proportion of plants that went extinct [ 45 , 46 ].
Areas that are close to one represent networks that are robust to plant extinction, since large percentages of extinctions are needed until significant secondary extinctions of pollinators are observed. On the other hand, areas that are close to zero correspond to very fragile networks, in which extinction of a small proportion of plant species leads to the extinction of a high proportion of pollinator species [ 45 ]. We obtained mean values of robustness for each scenario and then we compared the differences between means of a-priori planned pair-wise comparisons see S5 — S12 Tables.
Thus, species with low dispersal ability and slight dependence on pollinators showed the highest contribution to nestedness Fig.
McDougal Littell World History - Patterns .pdf
Species with strong dependence on pollinators and high dispersal ability showed intermediate mean values of contribution to nestedness Fig. By contrast, low-dispersal plants with strong dependence on pollinators were among those that showed the lowest contributions to nestedness Fig. Black lines within boxes represent median values. Upper and lower limits of boxes represent 1 st and 3 rd quartiles, respectively. Boxes were drawn with widths proportional to the number of observations in each group.
The probability of obtaining a difference higher than that observed among groups is also shown.