Dataset Information

Phenotypic variation explains food web structural patterns.

ABSTRACT: Food webs (i.e., networks of species and their feeding interactions) share multiple structural features across ecosystems. The factors explaining such similarities are still debated, and the role played by most organismal traits and their intraspecific variation is unknown. Here, we assess how variation in traits controlling predator-prey interactions (e.g., body size) affects food web structure. We show that larger phenotypic variation increases connectivity among predators and their prey as well as total food intake rate. For predators able to eat only a few species (i.e., specialists), low phenotypic variation maximizes intake rates, while the opposite is true for consumers with broader diets (i.e., generalists). We also show that variation sets predator trophic level by determining interaction strengths with prey at different trophic levels. Merging these results, we make two general predictions about the structure of food webs: (i) trophic level should increase with predator connectivity, and (ii) interaction strengths should decrease with prey trophic level. We confirm these predictions empirically using a global dataset of well-resolved food webs. Our results provide understanding of the processes structuring food webs that include functional traits and their naturally occurring variation.

SUBMITTER: Gibert JP

PROVIDER: S-EPMC5651739 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Phenotypic variation explains food web structural patterns.

Gibert Jean P JP DeLong John P JP

Proceedings of the National Academy of Sciences of the United States of America 20171002 42

Food webs (i.e., networks of species and their feeding interactions) share multiple structural features across ecosystems. The factors explaining such similarities are still debated, and the role played by most organismal traits and their intraspecific variation is unknown. Here, we assess how variation in traits controlling predator-prey interactions (e.g., body size) affects food web structure. We show that larger phenotypic variation increases connectivity among predators and their prey as we ...[more]

PMID: 28973955

Similar Datasets

Project description:Soil food webs are important drivers for key ecological functions in terrestrial systems such as carbon and nutrient cycling. However, soil food web models generally lack quantitative data, mainly due to the shortage in high-throughput methods to describe energy flows. In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. A premise for the application of such models to soil systems is to acquire the fatty acid pattern of a broad range of resources and to reveal potential overlap in their signatures. We present a comprehensive comparison of lipid pattern across widespread taxa of plants (leaves and roots, n = 48), algae (n = 59), fungi (n = 60), and bacteria (n = 62) as basal food web resources. Lipid profiles from microorganisms and algae were assessed from laboratory cultures, whereas plant tissue was derived from an arable field. A lipid library was constructed and multivariate data analyses (hierarchical clustering, nMDS) was used to assess the extent of separation in lipid pattern by species or resource type. The performance of the lipid library was tested by leave-one-prey-out (LOPO) analysis, giving the distinctiveness of the resource (prey) groups. Fungi and plant leaves were correctly assigned based on their lipid pattern with more than 98%, while plant roots and bacteria achieved 88 and 85%, respectively. However, algae were only correctly classified by 60%, pointing to a bias in the herbivore food chain. Fatty acids most important for separation of algae and plant leaves were of the omega 3 type, i.e. 16:3ω3 and 18:3ω3. In plant roots 18:1ω9 was most important, whereas bacteria were distinguished predominantly by methyl-branched fatty acids. Overall, the lipid pattern of major soil food web resources are sufficiently differentiated to allow for qualitative (biomarker) analyses as well as quantitative modelling, yet with precaution in the case of algae.

Project description:RationaleMinority drug-resistant Mycobacterium tuberculosis subpopulations can be associated with phenotypic resistance but are poorly detected by Sanger sequencing or commercial molecular diagnostic assays.ObjectivesTo determine the role of targeted next-generation sequencing in resolving these minor variant subpopulations.MethodsWe used single molecule overlapping reads (SMOR), a targeted next-generation sequencing approach that dramatically reduces sequencing error, to analyze primary cultured isolates phenotypically resistant to rifampin, fluoroquinolones, or aminoglycosides, but for which Sanger sequencing found no resistance-associated variants (RAVs) within respective resistance-determining regions (study group). Isolates also underwent single-colony selection on antibiotic-containing agar, blinded to sequencing results. As a positive control, isolates with multiple colocalizing chromatogram peaks were also analyzed (control group).Measurements and main resultsAmong 61 primary culture isolates (25 study group and 36 control group), SMOR described 66 (49%) and 45 (33%) of 135 total heteroresistant RAVs at frequencies less than 5% and less than 1% of the total mycobacterial population, respectively. In the study group, SMOR detected minor resistant variant subpopulations in 80% (n = 20/25) of isolates with no Sanger-identified RAVs (median subpopulation size, 1.0%; interquartile range, 0.2-3.9%). Single-colony selection on drug-containing media corroborated SMOR results for 90% (n = 18/20) of RAV-containing specimens, and the absence of RAVs in 60% (n = 3/5) of isolates. Overall, Sanger sequencing was concordant with SMOR for 77% (n = 53/69) of macroheteroresistant (5-95% total population), but only 5% of microheteroresistant (<5%) subpopulations (n = 3/66) across both groups.ConclusionsCryptic minor variant mycobacterial subpopulations exist below the resolving capability of current drug susceptibility testing methodologies, and may explain an important proportion of false-negative resistance determinations.

Project description:BackgroundThe harlequin ladybird Harmonia axyridis (Coleoptera: Coccinellidae), native to Asia, has been introduced to other major continents where it has caused serious negative impacts on local biodiversity. Though notable advances to understand its invasion success have been made during the past decade, especially with then newer molecular tools, the conclusions reached remain to be confirmed with more advanced genomic analyses and especially using more samples from larger geographical regions across the native range. Furthermore, although H. axyridis is one of the best studied invasive insect species with respect to life history traits (often comparing invasive and native populations), the traits responsible for its colonization success in non-native areas warrant more research.ResultsOur analyses of genome-wide nuclear population structure indicated that an eastern Chinese population could be the source of all non-native populations and revealed several putatively adaptive candidate genomic loci involved in body color variation, visual perception, and hemolymph synthesis. Our estimates of evolutionary history indicate (1) asymmetric migration with varying population sizes across its native and non-native range, (2) a recent admixture between eastern Chinese and American populations in Europe, (3) signatures of a large progressive, historical bottleneck in the common ancestors of both populations and smaller effective sizes of the non-native population, and (4) the southwest origin and subsequent dispersal routes within its native range in China. In addition, we found that while two mitochondrial haplotypes-Hap1 and Hap2 were dominant in the native range, Hap1 was the only dominant haplotype in the non-native range. Our laboratory observations in both China and USA found statistical yet slight differences between Hap1 and Hap2 in some of life history traits.ConclusionsOur study on H. axyridis provides new insights into its invasion processes into other major continents from its native Asian range, reconstructs a geographic range evolution across its native region China, and tentatively suggests that its invasiveness may differ between mitochondrial haplotypes.

Dataset Information

Phenotypic variation explains food web structural patterns.

Publications

Phenotypic variation explains food web structural patterns.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets