The structure of mutualistic networks is likely to result from the simultaneous influence of neutrality and the constraints imposed by complementarity in species phenotypes, phenologies, spatial ...distributions, phylogenetic relationships, and sampling artifacts. We develop a conceptual and methodological framework to evaluate the relative contributions of these potential determinants. Applying this approach to the analysis of a plant-pollinator network, we show that information on relative abundance and phenology suffices to predict several aggregate network properties (connectance, nestedness, interaction evenness, and interaction asymmetry). However, such information falls short of predicting the detailed network structure (the frequency of pairwise interactions), leaving a large amount of variation unexplained. Taken together, our results suggest that both relative species abundance and complementarity in spatiotemporal distribution contribute substantially to generate observed network patters, but that this information is by no means sufficient to predict the occurrence and frequency of pairwise interactions. Future studies could use our methodological framework to evaluate the generality of our findings in a representative sample of study systems with contrasting ecological conditions.
Morphology and phenology influence plant–pollinator network structure, but whether they generate more stable pairwise interactions with higher pollination success remains unknown. Here we evaluate ...the importance of morphological trait matching, phenological overlap and specialisation for the spatio‐temporal stability (measured as variability) of plant–pollinator interactions and for pollination success, while controlling for species' abundance. To this end, we combined a 6‐year plant–pollinator interaction dataset, with information on species traits, phenologies, specialisation, abundance and pollination success, into structural equation models. Interactions among abundant plants and pollinators with well‐matched traits and phenologies formed the stable and functional backbone of the pollination network, whereas poorly matched interactions were variable in time and had lower pollination success. We conclude that phenological overlap could be more useful for predicting changes in species interactions than species abundances, and that non‐random extinction of species with well‐matched traits could decrease the stability of interactions within communities and reduce their functioning.
Morphology and phenology influence plant‐pollinator network structure, but whether they generate more stable pairwise interactions with higher pollination success is unknown. We show that interactions among abundant plants and pollinators with well‐matched traits and phenologies formed the stable and functional backbone of the pollination network, whereas poorly‐matched interactions were variable in time and had lower pollination success.
BACKGROUND: Ecologists and evolutionary biologists are becoming increasingly interested in networks as a framework to study plant-animal mutualisms within their ecological context. Although such ...focus on networks has brought about important insights into the structure of these interactions, relatively little is still known about the mechanisms behind these patterns. SCOPE: The aim in this paper is to offer an overview of the mechanisms influencing the structure of plant-animal mutualistic networks. A brief summary is presented of the salient network patterns, the potential mechanisms are discussed and the studies that have evaluated them are reviewed. This review shows that researchers of plant-animal mutualisms have made substantial progress in the understanding of the processes behind the patterns observed in mutualistic networks. At the same time, we are still far from a thorough, integrative mechanistic understanding. We close with specific suggestions for directions of future research, which include developing methods to evaluate the relative importance of mechanisms influencing network patterns and focusing research efforts on selected representative study systems throughout the world.
Ecological interactions are highly dynamic in time and space. Previous studies of plant–animal mutualistic networks have shown that the occurrence of interactions varies substantially across years. ...We analyzed interannual variation of a quantitative mutualistic network, in which links are weighted by interaction frequency. The network was sampled over six consecutive years, representing one of the longest time series for a community-wide mutualistic network. We estimated the interannual similarity in interactions and assessed the determinants of their persistence. The occurrence of interactions varied greatly among years, with most interactions seen in only one year (64%) and few (20%) in more than two years. This variation was associated with the frequency and position of interactions relative to the network core, so that the network consisted of a persistent core of frequent interactions and many peripheral, infrequent interactions. Null model analyses suggest that species abundances play a substantial role in generating these patterns. Our study represents an important step in the study of ecological networks, furthering our mechanistic understanding of the ecological processes driving the temporal persistence of interactions.
Understanding how bees use resources at a landscape scale is essential for developing meaningful management plans that sustain populations and the pollination services they provide. Bumblebees are ...important pollinators for many wild and cultivated plants, and have experienced steep population declines worldwide. Bee foraging behavior can be influenced by resource availability and bees' lifecycle stage. To better understand these relationships, we studied the habitat selection of Bombus pauloensis by tracking 17 queen bumblebees with radio telemetry in blueberry fields in Entre R#237;os province, Argentina. To evaluate land use and floral resources used by bumblebees, we tracked bees before and after nest establishment and estimated home ranges using minimum convex polygons and kernel density methods. We also classified the pollen on their bodies to identify the floral resources they used from the floral species available at that time. We characterized land use for each bee as the relative proportion of GPS points inside of each land use. Bumblebees differed markedly in their movement behavior in relation to pre and post nest establishment. Bees moved over larger areas, and mostly within blueberry fields, before nest establishment. In contrast, after establishing the nest, the bees preferred the edges near forest plantations and they changed the nutritional resources to prefer wild floral species. Our study is the first to track queen bumblebee movements in an agricultural setting and relate movement changes across time and space with pollen resource availability. This study provides insight into the way bumblebee queens use different habitat elements at crucial periods in their lifecycle, showing the importance of mass flowering crops like blueberry in the first stages of queen's lifecycle, and how diversified landscapes help support bee populations as their needs changes during different phases of their lifecycle.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Generalist species are the linchpins of networks, as they are important for maintaining network structure and function. Previous studies have shown that interactions between generalists tend to occur ...consistently across years and sites. However, the link between temporal and spatial interaction persistence across scales remains unclear. To address this gap, we collected data on plant–pollinator interactions throughout the flowering period for 5 yr across six plots in a subalpine meadow in the Rocky Mountains. We found that interactions between generalists tended to persist more in time and space such that interactions near the network core were more frequently recorded across years, within seasons, and among plots. We posit that species’ tolerance of environmental variation across time and space plays a key role in generalization by regulating spatiotemporal overlap with interaction partners. Our results imply a role of spatiotemporal environmental variation in organizing species interactions, marrying niche concepts that emphasize species environmental constraints and their community role.
1. Over the last decade, there has been much concern about the decline in pollinator abundance and diversity caused by different types of anthropogenic disturbances, including deforestation and ...habitat fragmentation. However, little empirical information exists documenting this decline and its consequences for cultivated flowering crops. We tested the hypothesis that remnants of natural habitats act as a source of flower-visiting insects for neighbourhood crops. 2. Over 3 consecutive years we evaluated flower-visiting insect diversity, visitation frequency and composition in four grapefruit Citrus paradisi Macf. plantations at increasing distances (edge, 10, 100, 500 and 1000 m) from remnants of subtropical premontane forest in NW Argentina. 3. The frequency of visits to grapefruit flowers decreased by more than twofold as distance to the forest increased and the flower-visiting fauna became more depaupurate. Even the feral africanized honeybee Apis mellifera, the dominant flower visitor to grapefruit flowers, showed a decline at distances > 500 m from the forest edge. However, the greatest relative declines occurred among stingless and solitary bees as well as other native flower visitors, which were rarely seen a few hundred metres inside the plantations. In addition, flower-visiting insect faunas among plantations became more homogeneous as distance from the edge increased. 4. These trends were consistent over years and among plantations up to 50 km apart. Thus, we can conclude that negative forest edge effects on flower-visiting insects inside grapefruit plantations are widespread in the increasingly deforested landscape of NW Argentina. 5. Synthesis and applications. This study provides empirical evidence for considering remnants of natural habitats as a source of both native and alien flower-visiting insects that can be potential pollinators for agriculture. Increasing edge density in agricultural lands, through preservation and restoration of natural habitats, can foster stocks of diverse and abundant insect pollinators.
Ecology Letters (2011) 14: 1062–1072
Sustainable agricultural landscapes by definition provide high magnitude and stability of ecosystem services, biodiversity and crop productivity. However, few ...studies have considered landscape effects on the stability of ecosystem services. We tested whether isolation from florally diverse natural and semi‐natural areas reduces the spatial and temporal stability of flower‐visitor richness and pollination services in crop fields. We synthesised data from 29 studies with contrasting biomes, crop species and pollinator communities. Stability of flower‐visitor richness, visitation rate (all insects except honey bees) and fruit set all decreased with distance from natural areas. At 1 km from adjacent natural areas, spatial stability decreased by 25, 16 and 9% for richness, visitation and fruit set, respectively, while temporal stability decreased by 39% for richness and 13% for visitation. Mean richness, visitation and fruit set also decreased with isolation, by 34, 27 and 16% at 1 km respectively. In contrast, honey bee visitation did not change with isolation and represented > 25% of crop visits in 21 studies. Therefore, wild pollinators are relevant for crop productivity and stability even when honey bees are abundant. Policies to preserve and restore natural areas in agricultural landscapes should enhance levels and reliability of pollination services.
1. The study of plant-pollinator interactions in a network context is receiving increasing attention. This approach has helped to identify several emerging network patterns such as nestedness and ...modularity. However, most studies are based only on qualitative information, and some ecosystems, such as deserts and tropical forests, are underrepresented in these data sets. 2. We present an exhaustive analysis of the structure of a 4-year plant-pollinator network from the Monte desert in Argentina using qualitative and quantitative tools. We describe the structure of this network and evaluate sampling completeness using asymptotic species richness estimators. Our goal is to assess the extent to which the realized sampling effort allows for an accurate description of species interactions and to estimate the minimum number of additional censuses required to detect 90% of the interactions. We evaluated completeness of detection of the community-wide pollinator fauna, of the pollinator fauna associated with each plant species and of the plant-pollinator interactions. We also evaluated whether sampling completeness was influenced by plant characteristics, such as flower abundance, flower life span, number of interspecific links (degree) and selectiveness in the identity of their flower visitors, as well as sampling effort. 3. We found that this desert plant-pollinator network has a nested structure and that it exhibits modularity and high network-level generalization. 4. In spite of our high sampling effort, and although we sampled 80% of the pollinator fauna, we recorded only 55% of the interactions. Furthermore, although a 64% increase in sampling effort would suffice to detect 90% of the pollinator species, a fivefold increase in sampling effort would be necessary to detect 90% of the interactions. 5. Detection of interactions was incomplete for most plant species, particularly specialists with a long flowering season and high flower abundance, or generalists with short flowering span and scant flowers. Our results suggest that sampling of a network with the same effort for all plant species is inadequate to sample interactions. 6. Sampling the diversity of interactions is labour intensive, and most plant-pollinator networks published to date are likely to be undersampled. Our analysis allowed estimating the completeness of our sampling, the additional effort needed to detect most interactions and the plant traits that influence the detection of their interactions.
The study of mutualistic interaction networks has led to valuable insights into ecological and evolutionary processes. However, our understanding of network structure may depend upon the temporal ...scale at which we sample and analyze network data. To date, we lack a comprehensive assessment of the temporal scale‐dependence of network structure across a wide range of temporal scales and geographic locations. If network structure is temporally scale‐dependent, networks constructed over different temporal scales may provide very different perspectives on the structure and composition of species interactions. Furthermore, it remains unclear how various factors – including species richness, species turnover, link rewiring and sampling effort – act in concert to shape network structure across different temporal scales. To address these issues, we used a large database of temporally‐resolved plant–pollinator networks to investigate how temporal aggregation from the scale of one day to multiple years influences network structure. In addition, we used structural equation modeling to explore the direct and indirect effects of temporal scale, species richness, species turnover, link rewiring and sampling effort on network structural properties. We find that plant–pollinator network structure is strongly temporally‐scale dependent. This general pattern arises because the temporal scale determines the degree to which temporal dynamics (i.e. phenological turnover of species and links) are included in the network, in addition to how much sampling effort is put into constructing the network. Ultimately, the temporal scale‐dependence of our plant–pollinator networks appears to be mostly driven by species richness, which increases with sampling effort, and species turnover, which increases with temporal extent. In other words, after accounting for variation in species richness, network structure is increasingly shaped by its underlying temporal dynamics. Our results suggest that considering multiple temporal scales may be necessary to fully appreciate the causes and consequences of interaction network structure.
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