We analyze the properties of model food webs and of fifteen community food webs from a variety of environments -including freshwater, marine-freshwater interfaces and terrestrial environments. We first perform a theoretical analysis of a recently proposed model for food webs-the niche model of Williams and Martinez (2000). We derive analytical expressions for the distributions of species' number of prey, number of predators, and total number of trophic links and find that they follow universal functional forms. We also derive expressions for a number of other biologically relevant parameters which depend on these distributions. These include the fraction of top, intermediate, basal, and cannibal species, the standard deviations of generality and vulnerability, the correlation coefficient between species' number of prey and number of predators, and assortativity. We show that our findings are robust under rather general conditions; a result which could not have been demonstrated without treating the problem analytically. We then use our analytical predictions as a guide to the analysis of fifteen of the most complete empirical food webs available. We uncover quantitative unifying patterns that describe the properties of the model food webs and most of the trophic webs considered. Our results support a strong new hypothesis that the empirical distributions of number of prey and number of predators follow universal functional forms that, without free parameters, match our analytical predictions. Further, we find that the empirically observed correlation coefficient, assortativity, and fraction of cannibal species are consistent with our analytical expressions and simulations of the niche model. Finally, we show that two quantities typically used to characterize complex networks, the average distance between nodes and the average clustering coefficient of the nodes, show a high degree of regularity for both the empirical data and simulations of the niche model. Our findings suggest that statistical physics concepts such as scaling and universality may be useful in the description of natural ecosystems.

Working paper Community ecology is tasked with the considerable challenge of predicting the structure, and properties, of emerging ecosystems. It requires the ability to understand how and why species interact, as this will allow the development of mechanism-based predictive models, and as such to better characterize how ecological mechanisms act locally on the existence of inter-specific interactions. Here we argue that the current conceptualization of species interaction networks is illsuited for this task. Instead, we propose that future research must start to account for the intrinsic variability of interaction networks. This can be accompslihed simply by recognizing that there exists intra-specific variability, in traits or properties related to the establishment of species interactions. By shifting the scale towards population-based processes, we show that this new approach will improve our predictive ability and mechanistic understanding of how species interact over biogeographical scales.

Abstract:The increased availability of both open ecological data, and software to interact with it, allows the 22 fast collection and integration of information at all spatial and taxonomic scales. This offers the opportunity 23 to address macroecological questions in a cost-effective way. In this contribution, we illustrate this approach 24 by forecasting the structure of a stream food web at the global scale. In so doing, we highlight the most salient 25 issues needing to be addressed before this approach can be used with a high degree of confidence. Existing datasets can, to an increasing extent, be used to build new datasets (henceforth synthetic 44 datasets, since they represent the synthesis of several types of data). There are several parallel 45 advances that make this approach possible. First, the volume of data on ecological systems that 46 are available openly increases on a daily basis. This includes point-occurrence data (as in GBIF or 47 BISON), but also taxonomic knowledge (through ITIS, NCBI or EOL) or trait and interactions data. 48In fact, there is a vast (and arguably under-exploited) amount of ecological information, that is now 49 available without having to contact and secure authorization from every contributor individually. 50Second, these data are often available in a programmatic way; as opposed to manually visiting data 51 repositories, and downloading or copy-and-pasting datasets, several software packages offer the 52 opportunity to query these databases automatically, considerably speeding up the data collection 53 process. As opposed to manual collection, identification, and maintenance of datasets, most of 54 these services implement web APIs (Application Programming Interface, i.e. services that allow 55 users to query and/or upload data in a standard format). These services can be queried, either once 56 2 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/021402 doi: bioRxiv preprint first posted online Jun. 23, 2015; or on a regular basis, to retrieve records with the desired properties. This ensures that the process 57 is repeatable, testable, transparent, and (as long as the code is properly written) nearly error proof. 58Finally, most of the heavy lifting for these tasks can be done through a burgeoning ecosystem of 59 packages and software that handles query formatting, data retrieval, and associated tasks, all the 60 while exposing simple interfaces to researchers. None of these are new data, in the sense that these 61 collections represent the aggregation of thousands of ecological studies; the originality lies in the 62 ability to query, aggregate, curate, and use these data consistently and in a new way using open 63 solutions. 64Hypothesis testing for large-scale systems is inherently limited by the availability of suitable datasets 65-most data collection results in small scale, local data, and it is not always clear how these can be ...

Niche packing is one of the prevailing mechanisms underlying the increase in the number of co-occurring species and the extraordinary diversity of tropical ecosystems. However, it is not yet understood whether niche packing is facilitated by higher specialization and reduced niche overlap or, rather, by diffuse competition and increased niche overlap. We combined highly resolved bird-plant interaction networks, bird phylogenies, and plant functional traits to compare dietary niche overlap and foraging frequencies among frugivorous birds at seven sites in the tropical Andes. We quantified niche overlap on the basis of the traits of the plants used by each bird and related it to the degree of niche packing at the different sites. Niche complementarity decreased with increasing niche packing, suggesting that increasingly dense niche packing is facilitated by increased niche overlap. Pairwise niche overlap was mediated by shifts in foraging frequencies away from shared resources, and it decreased with decreasing phylogenetic relatedness and increasing dependence on fruit as resource. Our findings suggest that foraging choices are a key axis of diversification in frugivorous birds and that differences in resource use frequencies are already sufficient to reduce potential competition between ecologically similar species and facilitate niche packing, especially if species differ in their dependence on particular resources.

Pollinator foraging behavior determines floral visitation rates, an important proxy to the strength of mutual- istic interactions. Although there is evidence that pollinators modify their behavior in the presence of other foragers, there are equivocal findings regarding whether or not pollinators interfere with one another. We employ a functional-response framework to analyse experimental data of times between floral visits made by a focal pollinator and to estimate pollinator interference by conspecifics and three other species. Additionally we develop and compare models that allow different levels of resource availability and the sub-lethal exposure to a neonicotinoid pesticide to modify how pollinators forage alone and with co-foragers. We found that all co-foragers interfere with a focal pollinator under at least one set of abiotic conditions; for most species, interference was strongest at higher levels of resource availability and with pesticide exposure. Overall our results highlight that density-dependent responses are often context dependent themselves.