Species' functional traits set the blueprint for pair-wise interactions in ecological networks. Yet, it is unknown to what extent the functional diversity of plant and animal communities controls network assembly along environmental gradients in real-world ecosystems. Here we address this question with a unique dataset of mutualistic bird-fruit, bird-flower and insect-flower interaction networks and associated functional traits of 200 plant and 282 animal species sampled along broad climate and land-use gradients on Mt. Kilimanjaro. We show that plant functional diversity is mainly limited by precipitation, while animal functional diversity is primarily limited by temperature. Furthermore, shifts in plant and animal functional diversity along the elevational gradient control the niche breadth and partitioning of the respective other trophic level. These findings reveal that climatic constraints on the functional diversity of either plants or animals determine the relative importance of bottom-up and top-down control in plant-animal interaction networks.

Most studies of plant-animal mutualisms involve a small number of species. There is almost no information on the structural organization of species-rich mutualistic networks despite its potential importance for the maintenance of diversity. Here we analyze 52 mutualistic networks and show that they are highly nested; that is, the more specialist species interact only with proper subsets of those species interacting with the more generalists. This assembly pattern generates highly asymmetrical interactions and organizes the community cohesively around a central core of interactions. Thus, mutualistic networks are neither randomly assembled nor organized in compartments arising from tight, parallel specialization. Furthermore, nestedness increases with the complexity (number of interactions) of the network: for a given number of species, communities with more interactions are significantly more nested. Our results indicate a nonrandom pattern of community organization that may be relevant for our understanding of the organization and persistence of biodiversity.

The structure of ecological interaction networks is often interpreted as a product of meaningful ecological and evolutionary mechanisms that shape the degree of specialization in community associations. However, here we show that both unweighted network metrics (connectance, nestedness, and degree distribution) and weighted network metrics (interaction evenness, interaction strength asymmetry) are strongly constrained and biased by the number of observations. Rarely observed species are inevitably regarded as "specialists," irrespective of their actual associations, leading to biased estimates of specialization. Consequently, a skewed distribution of species observation records (such as the lognormal), combined with a relatively low sampling density typical for ecological data, already generates a "nested" and poorly "connected" network with "asymmetric interaction strengths" when interactions are neutral. This is confirmed by null model simulations of bipartite networks, assuming that partners associate randomly in the absence of any specialization and any variation in the correspondence of biological traits between associated species (trait matching). Variation in the skewness of the frequency distribution fundamentally changes the outcome of network metrics. Therefore, interpretation of network metrics in terms of fundamental specialization and trait matching requires an appropriate control for such severe constraints imposed by information deficits. When using an alternative approach that controls for these effects, most natural networks of mutualistic or antagonistic systems show a significantly higher degree of reciprocal specialization (exclusiveness) than expected under neutral conditions. A higher exclusiveness is coherent with a tighter coevolution and suggests a lower ecological redundancy than implied by nested networks.

Using historic data sets, we quantified the degree to which global change over 120 years disrupted plant-pollinator interactions in a temperate forest understory community in Illinois, USA. We found degradation of interaction network structure and function and extirpation of 50% of bee species. Network changes can be attributed to shifts in forb and bee phenologies resulting in temporal mismatches, nonrandom species extinctions, and loss of spatial co-occurrences between extant species in modified landscapes. Quantity and quality of pollination services have declined through time. The historic network showed flexibility in response to disturbance; however, our data suggest that networks will be less resilient to future changes.

Positive indirect effects of consumers on their resources can stabilize food webs by preventing overexploitation, but the coupling of trophic and non-trophic interactions remains poorly integrated into our understanding of community dynamics. Elephants engineer African savanna ecosystems by toppling trees and breaking branches, and although their negative effects on trees are well documented, their effects on small-statured plants remain poorly understood. Using data on 117 understory plant taxa collected over 7 yr within 36 1-ha experimental plots in a semi-arid Kenyan savanna, we measured the strength and direction of elephant impacts on understory vegetation. We found that elephants had neutral effects on most (83-89%) species, with a similar frequency of positive and negative responses among the remainder. Overall, estimated understory biomass was 5-14% greater in the presence of elephants across a range of rainfall levels. Whereas direct consumption likely accounts for the negative effects, positive effects are presumably indirect. We hypothesized that elephants create associational refuges for understory plants by damaging tree canopies in ways that physically inhibit feeding by other large herbivores. As predicted, understory biomass and species richness beneath elephant-damaged trees were 55% and 21% greater, respectively, than under undamaged trees. Experimentally simulated elephant damage increased understory biomass by 37% and species richness by 49% after 1 yr. Conversely, experimentally removing elephant damaged branches decreased understory biomass by 39% and richness by 30% relative to sham-manipulated trees. Camera-trap surveys revealed that elephant damage reduced the frequency of herbivory by 71%, whereas we detected no significant effect of damage on temperature, light, or soil moisture. We conclude that elephants locally facilitate understory plants by creating refuges from herbivory, which countervails the direct negative effects of consumption and enhances larger-scale biomass and diversity by promoting the persistence of rare and palatable species. Our results offer a counterpoint to concerns about the deleterious impacts of elephant "overpopulation" that should be considered in debates over wildlife management in African protected areas: understory species comprise the bulk of savanna plant biodiversity, and their responses to elephants are buffered by the interplay of opposing consumptive and non-consumptive interactions.© 2016 by the Ecological Society of America.

Mutualistic interactions involving pollination and ant-plant mutualistic networks typically feature tightly linked species grouped in modules. However, such modularity is infrequent in seed dispersal networks, presumably because research on those networks predominantly includes a single taxonomic animal group (e.g. birds). Herein, for the first time, we examine the pattern of interaction in a network that includes multiple taxonomic groups of seed dispersers, and the mechanisms underlying modularity. We found that the network was nested and modular, with five distinguishable modules. Our examination of the mechanisms underlying such modularity showed that plant and animal trait values were associated with specific modules but phylogenetic effect was limited. Thus, the pattern of interaction in this network is only partially explained by shared evolutionary history. We conclude that the observed modularity emerged by a combination of phylogenetic history and trait convergence of phylogenetically unrelated species, shaped by interactions with particular types of dispersal agents.© 2011 Blackwell Publishing Ltd/CNRS.

1. Co-existing plants and flower-visiting animals often form complex interaction networks. A long-standing question in ecology and evolutionary biology is how to detect nonrandom subsets (compartments, blocks, modules) of strongly interacting species within such networks. Here we use a network analytical approach to (i) detect modularity in pollination networks, (ii) investigate species composition of modules, and (iii) assess the stability of modules across sites. 2. Interactions between entomophilous plants and their flower-visitors were recorded throughout the flowering season at three heathland sites in Denmark, separated by >or= 10 km. Among sites, plant communities were similar, but composition of flower-visiting insect faunas differed. Visitation frequencies of visitor species were recorded as a measure of insect abundance. 3. Qualitative (presence-absence) interaction networks were tested for modularity. Modules were identified, and species classified into topological roles (peripherals, connectors, or hubs) using 'functional cartography by simulated annealing', a method recently developed by Guimerà & Amaral (2005a). 4. All networks were significantly modular. Each module consisted of 1-6 plant species and 18-54 insect species. Interactions aggregated around one or two hub plant species, which were largely identical at the three study sites. 5. Insect species were categorized in taxonomic groups, mostly at the level of orders. When weighted by visitation frequency, each module was dominated by one or few insect groups. This pattern was consistent across sites. 6. Our study adds support to the conclusion that certain plant species and flower-visitor groups are nonrandomly and repeatedly associated. Within a network, these strongly interacting subgroups of species may exert reciprocal selection pressures on each other. Thus, modules may be candidates for the long-sought key units of co-evolution.

How many dimensions (trait-axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small ( < 10), with model selection favouring less than five. Using 18 high-quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large-scale community structure.© 2013 Blackwell Publishing Ltd/CNRS.

In the past years, there have been many advances-but also many debates- around mutualistic communities, whose structural features appear to facilitate mutually beneficial interactions and increase biodiversity, under some given population dynamics. However, most approaches neglect the structure of inter-species competition by adopting a mean-field perspective that does not deal with competitive interactions properly. Here, we build up a multilayer network that naturally accounts for mutualism and competition and show, through a dynamical population model and numerical simulations, that there is an intricate relation between competition and mutualism. Specifically, the multilayer structure is coupled to a dynamical model in which the intra-guild competitive terms are weighted by the abundance of shared mutualistic relations. We find that mutualism does not have the same consequences on the evolution of specialist and generalist species, and that there is a non-trivial profile of biodiversity in the parameter space of competition and mutualism. Our findings emphasize how the simultaneous consideration of positive and negative interactions derived from the real networks is key to understand the delicate trade-off between topology and biodiversity in ecosystems and call for the need to incorporate more realistic interaction patterns when modeling the structural and dynamical stability of mutualistic systems.

In network ecology, landscape-scale processes are often overlooked, yet there is increasing evidence that species and interactions spill over between habitats, calling for further study of interhabitat dependencies. Here, we investigate how species connect a mosaic of habitats based on the spatial variation of their mutualistic and antagonistic interactions using two multilayer networks, combining pollination, herbivory and parasitism in the UK and New Zealand. Developing novel methods of network analysis for landscape-scale ecological networks, we discovered that few plant and pollinator species acted as connectors or hubs, both within and among habitats, whereas herbivores and parasitoids typically have more peripheral network roles. Insect species' roles depend on factors other than just the abundance of taxa in the lower trophic level, exemplified by larger Hymenoptera connecting networks of different habitats and insects relying on different resources across different habitats. Our findings provide a broader perspective for landscape-scale management and ecological community conservation.© 2019 John Wiley & Sons Ltd/CNRS.

Gradients in elevation are increasingly used to investigate how species respond to changes in local climatic conditions. Whilst many studies have shown elevational patterns in species richness and turnover, little is known about how food web structure is affected by elevation. Contrasting responses of predator and prey species to elevation may lead to changes in food web structure. We investigated how the quantitative structure of a herbivore-parasitoid food web changes with elevation in an Australian subtropical rain forest. On four occasions, spread over 1 year, we hand-collected leaf miners at twelve sites, along three elevational gradients (between 493 m and 1159 m a.s.l). A total of 5030 insects, including 603 parasitoids, were reared, and summary food webs were created for each site. We also carried out a replicated manipulative experiment by translocating an abundant leaf-mining weevil Platynotocis sp., which largely escaped parasitism at high elevations (≥ 900 m a.s.l.), to lower, warmer elevations, to test if it would experience higher parasitism pressure. We found strong evidence that the environmental change that occurs with increasing elevation affects food web structure. Quantitative measures of generality, vulnerability and interaction evenness decreased significantly with increasing elevation (and decreasing temperature), whilst elevation did not have a significant effect on connectance. Mined plant composition also had a significant effect on generality and vulnerability, but not on interaction evenness. Several relatively abundant species of leaf miner appeared to escape parasitism at higher elevations, but contrary to our prediction, Platynotocis sp. did not experience greater levels of parasitism when translocated to lower elevations. Our study indicates that leaf-mining herbivores and their parasitoids respond differently to environmental conditions imposed by elevation, thus producing structural changes in their food webs. Increasing temperatures and changes in vegetation communities that are likely to result from climate change may have a restructuring effect on host-parasitoid food webs. Our translocation experiment, however, indicated that leaf miners currently escaping parasitism at high elevations may not automatically experience higher parasitism under warmer conditions and future changes in food web structure may depend on the ability of parasitoids to adapt to novel hosts.© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Forest loss threatens biodiversity, but its potential effects on multitrophic ecological interactions are poorly understood. Insect herbivory depends on complex bottom-up (e.g., resource availability and plant antiherbivore defenses) and top-down forces (e.g., abundance of predators and herbivorous), but its determinants in human-altered tropical landscapes are largely unknown. Using structural equation models, we assessed the direct and indirect effects of forest loss on insect herbivory in 40 landscapes (115 ha each) from two regions with contrasting land-use change trajectories in the Brazilian Atlantic rainforest. We considered landscape forest cover as an exogenous predictor and (1) forest structure, (2) abundance of predators (birds and arthropods), and (3) abundance of herbivorous arthropods as endogenous predictors of insect leaf damage. From 12 predicted pathways, 11 were significant and showed that (1) leaf damage increases with forest loss (direct effect); (2) leaf damage increases with forest loss through the simplification of vegetation structure and its associated dominance of herbivorous insects (indirect effect); and further demonstrate (3) a lack of top-down control of herbivores by predators (birds and arthropods). We conclude that forest loss favors insect herbivory by undermining the bottom-up control (presumably reduced plant antiherbivore defense mechanisms) in forests dominated by fast-growing pioneer plant species, and by improving the conditions required for herbivores proliferation.© 2016 by the Ecological Society of America.

In natural communities, species and their interactions are often organized as nonrandom networks, showing distinct and repeated complex patterns. A prevalent, but poorly explored pattern is ecological modularity, with weakly interlinked subsets of species (modules), which, however, internally consist of strongly connected species. The importance of modularity has been discussed for a long time, but no consensus on its prevalence in ecological networks has yet been reached. Progress is hampered by inadequate methods and a lack of large datasets. We analyzed 51 pollination networks including almost 10,000 species and 20,000 links and tested for modularity by using a recently developed simulated annealing algorithm. All networks with >150 plant and pollinator species were modular, whereas networks with <50 species were never modular. Both module number and size increased with species number. Each module includes one or a few species groups with convergent trait sets that may be considered as coevolutionary units. Species played different roles with respect to modularity. However, only 15% of all species were structurally important to their network. They were either hubs (i.e., highly linked species within their own module), connectors linking different modules, or both. If these key species go extinct, modules and networks may break apart and initiate cascades of extinction. Thus, species serving as hubs and connectors should receive high conservation priorities.

Humans are altering the global distributional ranges of plants, while their co-evolved herbivores are frequently left behind. Native herbivores often colonise non-native plants, potentially reducing invasion success or causing economic loss to introduced agricultural crops. We developed a predictive model to forecast novel interactions and verified it with a data set containing hundreds of observed novel plant-insect interactions. Using a food network of 900 native European butterfly and moth species and 1944 native plants, we built an herbivore host-use model. By extrapolating host use from the native herbivore-plant food network, we accurately forecasted the observed novel use of 459 non-native plant species by native herbivores. Patterns that governed herbivore host breadth on co-evolved native plants were equally important in determining non-native hosts. Our results make the forecasting of novel herbivore communities feasible in order to better understand the fate and impact of introduced plants. © 2013 John Wiley & Sons Ltd/CNRS.

Food webs are a powerful way to represent the diversity, structure, and function of ecological systems. However, the accurate description of food webs requires significant effort in time and resources, limiting their widespread use in ecological studies. Newly published methods allow for the inference of feeding interactions using proxy variables. Here, we compare the accuracy of two recently described methods, as well as describe a composite model of the two, for the inference of feeding interactions using a large, well-described dataset. Both niche and neutral processes are involved in determining whether or not two species will form a feeding link in communities. Three different models for determining niche constraints of feeding interactions are compared, and all three models are extended by incorporating neutral processes, based on relative abundances. The three models compared here infer niche processes through (a) phylogenetic relationships, (b) local species trait distributions (e.g., body size), and (c) a composite of phylogeny and local traits. We show that all three methods perform well at predicting individual species interactions, and that these individual predictions scale up to the network level, resulting in food web structure of inferred networks being similar to their empirical counterparts. Our results indicate that inferring food web structure using phylogenies can be an efficient way of getting summary webs with minimal data, and offers a conservative test of changes in food web structure, particularly when there is low species turnover between sites. Inferences made using traits require more data, but allows for greater understanding of the mechanisms underlying trophic interactions. A composite model of the two methods provides a framework for investigating the importance of how phylogeny, trait distributions, and relative abundances, affect species interactions, and network structure.

A long-standing question in community ecology is whether food webs are organized in compartments, where species within the same compartment interact frequently among themselves, but show fewer interactions with species from other compartments. Finding evidence for this community organization is important since compartmentalization may strongly affect food web robustness to perturbation. However, few studies have found unequivocal evidence of compartments, and none has quantified the suite of mechanisms generating such a structure. Here, we combine computational tools from the physics of complex networks with phylogenetic statistical methods to show that a large marine food web is organized in compartments, and that body size, phylogeny, and spatial structure are jointly associated with such a compartmentalized structure. Sharks account for the majority of predatory interactions within their compartments. Phylogenetically closely related shark species tend to occupy different compartments and have divergent trophic levels, suggesting that competition may play an important role structuring some of these compartments. Current overfishing of sharks has the potential to change the structural properties, which might eventually affect the stability of the food web.

Mechanisms that enable declining networks to avert structural collapse and performance degradation are not well understood. This knowledge gap reflects a shortage of data on declining networks and an emphasis on models of network growth. Analyzing >700,000 transactions between firms in the New York garment industry over 19 years, we tracked this network's decline and measured how its topology and global performance evolved. We find that favoring asymmetric (disassortative) links is key to preserving the topology and functionality of the declining network. Based on our findings, we tested a model of network decline that combines an asymmetric disassembly process for contraction with a preferential attachment process for regrowth. Our simulation results indicate that the model can explain robustness under decline even if the total population of nodes contracts by more than an order of magnitude, in line with our observations for the empirical network. These findings suggest that disassembly mechanisms are not simply assembly mechanisms in reverse and that our model is relevant to understanding the process of decline and collapse in a broad range of biological, technological, and financial networks.

A major challenge in evolutionary ecology is to understand how co-evolutionary processes shape patterns of interactions between species at community level. Pollination of flowers with long corolla tubes by long-tongued hawkmoths has been invoked as a showcase model of co-evolution. Recently, optimal foraging models have predicted that there might be a close association between mouthparts' length and the corolla depth of the visited flowers, thus favouring trait convergence and specialization at community level. Here, we assessed whether hawkmoths more frequently pollinate plants with floral tube lengths similar to their proboscis lengths (morphological match hypothesis) against abundance-based processes (neutral hypothesis) and ecological trait mismatches constraints (forbidden links hypothesis), and how these processes structure hawkmoth-plant mutualistic networks from five communities in four biogeographical regions of South America. We found convergence in morphological traits across the five communities and that the distribution of morphological differences between hawkmoths and plants is consistent with expectations under the morphological match hypothesis in three of the five communities. In the two remaining communities, which are ecotones between two distinct biogeographical areas, interactions are better predicted by the neutral hypothesis. Our findings are consistent with the idea that diffuse co-evolution drives the evolution of extremely long proboscises and flower tubes, and highlight the importance of morphological traits, beyond the forbidden links hypothesis, in structuring interactions between mutualistic partners, revealing that the role of niche-based processes can be much more complex than previously known.© 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

The degree of interdependence and potential for shared coevolutionary history of frugivorous animals and fleshy-fruited plants are contentious topics. Recently, network analyses revealed that mutualistic relationships between fleshy-fruited plants and frugivores are mostly built upon generalized associations. However, little is known about the determinants of network structure, especially from tropical forests where plants' dependence on animal seed dispersal is particularly high. Here, we present an in-depth analysis of specialization and interaction strength in a plant-frugivore network from a Kenyan rain forest. We recorded fruit removal from 33 plant species in different forest strata (canopy, midstory, understory) and habitats (primary and secondary forest) with a standardized sampling design (3447 interactions in 924 observation hours). We classified the 88 frugivore species into guilds according to dietary specialization (14 obligate, 28 partial, 46 opportunistic frugivores) and forest dependence (50 forest species, 38 visitors). Overall, complementary specialization was similar to that in other plant-frugivore networks. However, the plant-frugivore interactions in the canopy stratum were less specialized than in the mid- and understory, whereas primary and secondary forest did not differ. Plant specialization on frugivores decreased with plant height, and obligate and partial frugivores were less specialized than opportunistic frugivores. The overall impact of a frugivore increased with the number of visits and the specialization on specific plants. Moreover, interaction strength of frugivores differed among forest strata. Obligate frugivores foraged in the canopy where fruit resources were abundant, whereas partial and opportunistic frugivores were more common on mid- and understory plants, respectively. We conclude that the vertical stratification of the frugivore community into obligate and opportunistic feeding guilds structures this plant-frugivore network. The canopy stratum comprises stronger links and generalized associations, whereas the lower strata are composed of weaker links and more specialized interactions. Our results suggest that seed-dispersal relationships of plants in lower forest strata are more prone to disruption than those of canopy trees.

Modularity is a recurrent and important property of bipartite ecological networks. Although well-resolved ecological networks describe interaction frequencies between species pairs, modularity of bipartite networks has been analysed only on the basis of binary presence-absence data. We employ a new algorithm to detect modularity in weighted bipartite networks in a global analysis of avian seed-dispersal networks. We define roles of species, such as connector values, for weighted and binary networks and associate them with avian species traits and phylogeny. The weighted, but not binary, analysis identified a positive relationship between climatic seasonality and modularity, whereas past climate stability and phylogenetic signal were only weakly related to modularity. Connector values were associated with foraging behaviour and were phylogenetically conserved. The weighted modularity analysis demonstrates the dominating impact of ecological factors on the structure of seed-dispersal networks, but also underscores the relevance of evolutionary history in shaping species roles in ecological communities. © 2014 John Wiley & Sons Ltd/CNRS.

Food web structure plays an important role when determining robustness to cascading secondary extinctions. However, existing food web models do not take into account likely changes in trophic interactions ('rewiring') following species loss. We investigated structural dynamics in 12 empirically documented food webs by simulating primary species loss using three realistic removal criteria, and measured robustness in terms of subsequent secondary extinctions. In our model, novel trophic interactions can be established between predators and food items not previously consumed following the loss of competing predator species. By considering the increase in robustness conferred through rewiring, we identify a new category of species--overlap species--which promote robustness as shown by comparing simulations incorporating structural dynamics to those with static topologies. The fraction of overlap species in a food web is highly correlated with this increase in robustness; whereas species richness and connectance are uncorrelated with increased robustness. Our findings underline the importance of compensatory mechanisms that may buffer ecosystems against environmental change, and highlight the likely role of particular species that are expected to facilitate this buffering.

Research on the relationship between the architecture of ecological networks and community stability has mainly focused on one type of interaction at a time, making difficult any comparison between different network types. We used a theoretical approach to show that the network architecture favoring stability fundamentally differs between trophic and mutualistic networks. A highly connected and nested architecture promotes community stability in mutualistic networks, whereas the stability of trophic networks is enhanced in compartmented and weakly connected architectures. These theoretical predictions are supported by a meta-analysis on the architecture of a large series of real pollination (mutualistic) and herbivory (trophic) networks. We conclude that strong variations in the stability of architectural patterns constrain ecological networks toward different architectures, depending on the type of interaction.

Plant diversity and niche complementarity had progressively stronger effects on ecosystem functioning during a 7-year experiment, with 16-species plots attaining 2.7 times greater biomass than monocultures. Diversity effects were neither transients nor explained solely by a few productive or unviable species. Rather, many higher-diversity plots outperformed the best monoculture. These results help resolve debate over biodiversity and ecosystem functioning, show effects at higher than expected diversity levels, and demonstrate, for these ecosystems, that even the best-chosen monocultures cannot achieve greater productivity or carbon stores than higher-diversity sites.

Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

Much research debates whether properties of ecological networks such as nestedness and connectance stabilise biological communities while ignoring key behavioural aspects of organisms within these networks. Here, we computationally assess how adaptive foraging (AF) behaviour interacts with network architecture to determine the stability of plant-pollinator networks. We find that AF reverses negative effects of nestedness and positive effects of connectance on the stability of the networks by partitioning the niches among species within guilds. This behaviour enables generalist pollinators to preferentially forage on the most specialised of their plant partners which increases the pollination services to specialist plants and cedes the resources of generalist plants to specialist pollinators. We corroborate these behavioural preferences with intensive field observations of bee foraging. Our results show that incorporating key organismal behaviours with well-known biological mechanisms such as consumer-resource interactions into the analysis of ecological networks may greatly improve our understanding of complex ecosystems.© 2016 John Wiley & Sons Ltd/CNRS.

Species distribution, catalogues, phylogeny, and life history traits are the data basis of biodiversity studies, playing critical roles in understanding species origins, evolution, and conservation biodiversity. Recently, a large number of scientific data-sharing platforms have been created, greatly contributing to the development of biodiversity informatics. However, it is difficult for most researchers to deal with big data with high complexity and heterogeneity. Determining how to select and utilize these data accurately and effectively becomes a huge challenge for ecologists and conservation biologists. To better deal with existing problems related to scattered distributed data, we classify biodiversity data resources into four groups (species distribution, catalogues, phylogeny and life history traits), and select representative databases (e.g. Global Biodiversity Information Facility, The Plant List, Open Tree of Life, and The Plant Trait Database (TRY) for demonstration. For each database, data type, and sampling design, geographic coverage and data availability are reported, and selected publications using these datasets are briefly introduced. Meanwhile, we describe recent achievements on the construction of China’s biodiversity digital platforms in each section. Overall, we hope that this paper provides a starting point for researchers to be familiar with these databases and use them correctly, and could have the potential to stimulate the development of related fields in research and conservation of biodiversity under the efforts of researchers and the public.

High-quality biodiversity data are the scientific basis for understanding the origin and maintenance of biodiversity and dealing with its extinction risk. Currently, we identify at least seven knowledge shortfalls or gaps in biodiversity science, including the lack of knowledge on species descriptions, species geographic distributions, species abundance and population dynamics, evolutional history, functional traits, interactions between species and the abiotic environment, and biotic interactions. The arrival of the current era of big data offers a potential solution to address these shortfalls. Big data mining and its applications have recently become the frontier of biodiversity science and macroecology. It is a challenge for ecologists to utilize and effectively analyze the ever-growing quantity of biodiversity data. In this paper, I review several biodiversity-related studies over global, continental, and regional scales, and demonstrate how big data approaches are used to address biodiversity questions. These examples include forest cover changes, conservation ecology, biodiversity and ecosystem functioning, and the effect of climate change on biodiversity. Furthermore, I summarize the current challenges facing biodiversity data collection, data processing and data analysis, and discuss potential applications of big data approaches in the fields of biodiversity science and macroecology.

高质量的生物多样性数据是认知生物多样性的起源和维持机制及应对其丧失风险的科学基础。当前, 在新物种发现、已知物种的地理分布、种群数量与时空动态、物种进化史、功能性状、物种与环境之间以及物种与物种之间的相互作用等7个方面都存在着知识上的空缺。大数据时代的到来为弥补这些知识空缺提供了可能,大数据的挖掘及其应用最近已成为国际生物多样性与宏生态学研究的前沿内容。如何有效地利用和分析不断增长的生物多样性大数据是生物多样性研究面临的一个极大挑战。本文通过全球、大陆和区域尺度上的研究案例展示了大数据在生物多样性研究中应用的新进展, 内容涉及森林覆盖变化、保护生态学、生物多样性与生态系统功能、气候变化对生物多样性的影响等。最后, 对大数据在生物多样性研究中存在的数据采集、处理和分析等方面的问题进行了总结, 并对其潜在应用前景进行了探讨。