Network analysis of phenological units to detect important species in plant-pollinator communities: can it inform conservation strategies? (original) (raw)
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Community Ecology, 2017
Conservation of species is often focused either only on those that are endangered, or on maximising the number recorded on species lists. However, species share space and time with others, thus interacting and building frameworks of relationships that can be unravelled by community-level network analysis. It is these relationships that ultimately drive ecosystem function via the transfer of energy and nutrients. However interactions are rarely considered in conservation planning. Network analysis can be used to detect key species ("hubs") that play an important role in cohesiveness of networks. We applied this approach to plant-pollinator communities on two montane Northern Apennine grasslands, paying special attention to the modules and the identity of hubs. We performed season-wide sampling and then focused the network analyses on time units consistent with plant phenology. After testing for significance of modules, only some modules were found to be significantly segregated from others. Thus, networks were organized around a structured core of modules with a set of companion species that were not organized into compartments. Using a network approach we obtained a list of important plant and pollinator species, including three Network Hubs of utmost importance, and other hubs of particular biogeographical interest. By having a lot of links and high partner diversity, hubs should convey stability to networks. Due to their role in the networks, taking into account such key species when considering the management of sites could help to preserve the greatest number of interactions and thus support many other species.
Acta Oecologica
The decline of pollinators may alter the complex system of interactions that they establish with flowering plants, with potential negative consequences on both partners. Within this context, network analysis may be a useful tool to study ecological properties of plant-pollinator interactions and to evaluate the outcomes of conservation actions. Three conservation measures were implemented within the European LIFE+ PP-ICON project to support the local pollinator community of a population of the rare plant Dictamnus albus in a protected area near Bologna, Italy. Artificial nesting sites were installed to support solitary bees, populations of native plants were reinforced to increase foraging resources for pollinators, and colonies of bumblebees reared from wild queens were released in the study area. In this work we evaluate the effects of these conservation actions on plant-pollinator networks over a period of four years, comparing a pre-(2011-2012) and a post-conservation (2013-2014) action period. The overall network generalisation increased after the implementation of conservation measures and interactions were more evenly distributed. Module composition significantly changed between the two periods, showing a marked rewiring of interactions. D. albus was a module hub both before and after conservation actions, thus emerging as an important node within its own module. In addition, some plant and pollinator species directly targeted by conservation measures became module connectors, highlighting their increased importance in linking different modules. Finally, the reinforcement of plant and pollinator populations led to increased flower visitation. These results indicate that conservation actions affected species both directly and indirectly and that the network of interactions has potentially increased its robustness and resilience towards possible species loss. This study highlights ways in which network analysis can be used to measure changes in plant-pollinator interactions in response to conservation actions.
Effects of sampling completeness on the structure of plant-pollinator networks
Ecology, 2012
Plant-animal interaction networks provide important information on community organization. One of the most critical assumptions of network analysis is that the observed interaction patterns constitute an adequate sample of the set of interactions present in plant-animal communities. In spite of its importance, few studies have evaluated this assumption and in consequence there is no consensus on the sensitivity of network metrics to sampling methodological shortcomings. In this study we examine how variation in sampling completeness influences the estimation of six network metrics frequently used in the literature (connectance, nestedness, modularity, robustness to species loss, path length, and centralization). We analyze data of 186 flowering plants and 336 pollinator species in ten networks from a forest fragmented system in central Chile. Using species-based accumulation curves we estimated the deviation of network metrics in undersampled communities with respect to exhaustively sampled communities and the effect of network size and sampling evenness on network metrics. Our results indicate that: 1) most metrics were affected by sampling completeness, but they differ in their sensitivity to sampling effort, 2) nestedness, modularity, and robustness to species loss were less influenced by insufficient sampling than connectance, path length, and centralization, 3) robustness was mildly influenced by sampling evenness. These results caution studies that summarize information from databases with high, or unknown, heterogeneity in sampling effort per species, and stimulate researchers to report sampling intensity to standardize its effects in the search for broad patterns in plant-pollinator networks.
How to monitor ecological communities cost-efficiently: The example of plant–pollinator networks
Biological Conservation, 2010
Conservation practitioners often lack tools to monitor functioning of communities because time and monetary constraints create a gap between the optimal monitoring methods and the practical needs in conservation. Interaction networks provide a framework that has proven useful in ecological research. However, they are considered time consuming and too expensive for conservation purposes. We investigate whether it is possible to sample interaction networks cost-efficiently and whether a compromise exists between data quality and amount of resources required to sample the data by using a highly resolved mutualistic plant-pollinator network sampled over two years in Norway. The dataset was resampled with decreasing sampling intensity to simulate decreasing monitoring costs and we investigated the cost-efficiency of these monitoring regimes. The success in monitoring community structure varied largely with sampling intensity and the descriptor investigated. One major result was that a large proportion of the functionally most important species in the community, both plants and insects, could be identified with relatively little sampling. For example, monitoring only in ''peak-season", which costs ca. 20% relative to full monitoring, resulted in recording of 70% (in 2003) or 85% (in 2004) of the top 20 most functionally important pollinator species. Also, peak-season monitoring resulted in relatively precise estimates of several network descriptors. We present a first estimation of the full cost (travel time, sampling time and taxonomic services) of constructing pollination networks with different sampling effort. We recommend monitoring plant-pollinator networks in temperate regions during peak-season to cost-efficiently collect data for practical habitat management of ecosystem functioning.
Abstract. Plant–animal interaction networks provide important information on community organization. One of the most critical assumptions of network analysis is that the observed interaction patterns constitute an adequate sample of the set of interactions present in plant–animal communities. In spite of its importance, few studies have evaluated this assumption and, in consequence, there is no consensus on the sensitivity of network metrics to sampling methodological shortcomings. In this study we examined how variation in sampling completeness influences the estimation of six network metrics frequently used in the literature (connectance, nestedness, modularity, robustness to species loss, path length, and centralization). We analyzed data of 186 flowering plants and 336 pollinator species in 10 networks from a forest-fragmented system in central Chile. Using species-based accumulation curves, we estimated the deviation of network metrics in undersampled communities with respect to exhaustively sampled communities and the effect of network size and sampling evenness on network metrics. Our results indicate that: (1) most metrics were affected by sampling completeness, but differed in their sensitivity to sampling effort; (2) nestedness, modularity, and robustness to species loss were less influenced by insufficient sampling than connectance, path length, and centralization; (3) robustness was mildly influenced by sampling evenness. These results caution studies that summarize information from databases with high, or unknown, heterogeneity in sampling effort per species, and stimulate researchers to report sampling intensity to standardize its effects in the search for broad patterns in plant–pollinator networks. Key words: accumulation curves; Clench model; ecological networks; Los Ruiles National Reserve, Chile; network size; plant–pollinator network metrics; sampling completeness; sampling effort; sampling evenness.
Interaction networks are widely used as tools to understand plant–pollinator communities, and to examine potential threats to plant diversity and food security if the ecosystem service provided by pollinating animals declines. However, most networks to date are based on recording visits to flowers, rather than recording clearly defined effective pollination events. Here we provide the first networks that explicitly incorporate measures of pollinator effectiveness (PE) from pollen deposition on stigmas per visit, and pollinator importance (PI) as the product of PE and visit frequency. These more informative networks, here produced for a low diversity heathland habitat, reveal that plant–pollinator interactions are more specialized than shown in most previous studies. At the studied site, the specialization index Embedded Image was lower for the visitation network than the PE network, which was in turn lower than Embedded Image for the PI network. Our study shows that collecting PE data is feasible for community-level studies in low diversity communities and that including information about PE can change the structure of interaction networks. This could have important consequences for our understanding of threats to pollination systems.
Contrasting Response of Mountain Plant-Pollinator Network to Fragmented Semi-Natural Grasslands
Land
The majority of the world’s plants rely on animal pollinators for reproduction, making pollination a key ecosystem service for the maintenance of natural and cultivated plant communities. Mutual interactions between plants and pollinators, also called “plant-pollinator networks”, are becoming increasingly vulnerable due to the intensification of anthropogenic land use and climate change. Thus, due to the rapid decline of semi-natural grasslands in the Northern Apennines (Italy), we aimed at understanding how the fragmentation of these habitats, the spatial distribution, and the amount of semi- and natural areas surrounding them, could affect species diversity and plant-pollinator networks. Specifically, in the Northern Apennines, we monitored semi-natural grasslands belonging to the EU habitat type 6510 to evaluate the effect of fragmentation on plant and pollinator richness and on the plant-pollinator network. We carried out generalized linear models considering three taxonomical a...
A method for under-sampled ecological network data analysis: plant-pollination as case study
In this paper, we develop a method, termed the Interaction Distribution (ID) method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi,j: the probability for a visit made by the i’th p...
Phenological shifts drive biodiversity loss in plant--pollinator networks
2020
Plant-pollinator interactions are key for ecosystem maintenance and world crop production, and their occurrence depends on the synchronization of life-cycle events among interacting species. Phenological shifts observed for plant and pollinator species increase the risk of phenological mismatches, threatening community stability. However, the magnitudes and directions of phenological shifts present a high variability, both among communities and among species of the same community. Community-wide consequences of these different responses have not been explored. Additionally, variability in phenological and topological traits of species can affect their persistence probability under phenological changes. We explored the consequences of several scenarios of plant-pollinator phenological mismatches for community stability. We also assessed whether species attributes can predict species persistence under phenological mismatch. To this end, we used a dynamic model for plant-pollinator networks. The model incorporates active and latent life-cycle states of species and phenological dynamics regulating life-cycle transitions. Interaction structure and species phenologies were extracted from eight empirical plant-pollinator networks sampled at three locations during different periods. We found that for all networks and all scenarios, species persistence decreased with increasing magnitude of the phenological shift, for both advancements and delays in flowering phenologies. Changes in persistence depended on the scenario and the network being tested. However, all networks exhibited the lowest species persistence when the mean of the expected shift was equivalent to its standard deviation and this shift was greater than two weeks. Conversely, the highest species persistences occurred when earlier-flowering plants exhibited stronger shifts. Phenophase duration was the most important attribute as a driver of plant persistence. For pollinator persistence, species degree was the most important attribute, followed by phenophase duration. Our findings highlight the importance of phenologies on the stability and robustness of mutualistic networks.
Plant–pollinator networks: adding the pollinator’s perspective
Ecology Letters, 2009
Pollination network studies are based on pollinator surveys conducted on focal plants. This plant‐centred approach provides insufficient information on flower visitation habits of rare pollinator species, which are the majority in pollinator communities. As a result, pollination networks contain very high proportions of pollinator species linked to a single plant species (extreme specialists), a pattern that contrasts with the widely accepted view that plant–pollinator interactions are mostly generalized. In this study of a Mediterranean scrubland community in NE Spain we supplement data from an intensive field survey with the analysis of pollen loads carried by pollinators. We observed 4265 contacts corresponding to 19 plant and 122 pollinator species. The addition of pollen data unveiled a very significant number of interactions, resulting in important network structural changes. Connectance increased 1.43‐fold, mean plant connectivity went from 18.5 to 26.4, and mean pollinator c...