DNA metabarcoding allows the analysis of insect communities faster and more efficiently than ever before. However, metabarcoding can be conducted through several approaches, and the consistency of ...results across methods has rarely been studied. We compare the results obtained by DNA metabarcoding of the same communities using two different markers – COI and 16S – and three different sampling methods: (a) homogenized Malaise trap samples (homogenate), (b) preservative ethanol from the same samples, and (c) soil samples. Our results indicate that COI and 16S offer partly complementary information on Malaise trap samples, with each marker detecting a significant number of species not detected by the other. Different sampling methods offer highly divergent estimates of community composition. The community recovered from preservative ethanol of Malaise trap samples is significantly different from that recovered from homogenate. Small and weakly sclerotized insects tend to be overrepresented in ethanol while strong and large taxa are overrepresented in homogenate. For soil samples, highly degenerate COI primers pick up large amounts of nontarget DNA and only 16S provides adequate analyses of insect diversity. However, even with 16S, very little overlap in molecular operational taxonomic unit (MOTU) content was found between the trap and the soil samples. Our results demonstrate that none of the tested sampling approaches is satisfactory on its own. For instance, DNA extraction from preservative ethanol is not a valid replacement for destructive bulk extraction but a complement. In future metabarcoding studies, both should ideally be used together to achieve comprehensive representation of the target community.
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DNA barcodes are widely used for identification and discovery of species. While such use draws on information at the DNA level, the current amassment of ca. 4.7 million COI barcodes also offers a ...unique resource for exploring functional constraints on DNA evolution. Here, we explore amino acid variation in a crosscut of the entire animal kingdom. Patterns of DNA variation were linked to functional constraints at the level of the amino acid sequence in functionally important parts of the enzyme. Six amino acid sites show variation with possible effects on enzyme function. Overall, patterns of amino acid variation suggest convergent or parallel evolution at the protein level connected to the transition into a parasitic life style. Denser sampling of two diverse insect taxa revealed that the beetles (Coleoptera) show more amino acid variation than the butterflies and moths (Lepidoptera), indicating fundamental difference in patterns of molecular evolution in COI. Several amino acid sites were found to be under notably strong purifying selection in Lepidoptera as compared to Coleoptera. Overall, these findings demonstrate the utility of the global DNA barcode library to extend far beyond identification and taxonomy, and will hopefully be followed by a multitude of work.
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The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only ...pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70-79%), with plant and fungal gene regions providing the clearest distinction between countries. At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.
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Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and ...statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non‐manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data‐driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species‐to‐species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R‐ and Matlab‐packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time‐series data. We illustrate the use of this framework through a series of diverse ecological examples.
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Abstract Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity remain relatively unexplored. In this ...work, we model global shifts in one of the most important marine functional groups—ecosystem-structuring macrophytes—and predict substantial end-of-century change. By modelling the future distribution of 207 brown macroalgae and seagrass species at high temporal and spatial resolution under different climate-change projections, we estimate that by 2100, local macrophyte diversity will decline by 3–4% on average, with 17 to 22% of localities losing at least 10% of their macrophyte species. The current range of macrophytes will be eroded by 5–6%, and highly suitable macrophyte habitat will be substantially reduced globally (78–96%). Global macrophyte habitat will shift among marine regions, with a high potential for expansion in polar regions.
Ecology Letters (2010) 13: 383-393 The extent to which behavioural choices reflect fine-tuned evolutionary adaptation remains an open debate. For herbivorous insects, the preference-performance ...hypothesis (PPH) states that female insects will evolve to oviposit on hosts on which their offspring fare best. In this study, we use meta-analysis to assess the balance of evidence for and against the PPH, and to evaluate the role of individual factors proposed to influence host selection by female insects. We do so in an explicitly bitrophic context (herbivores versus plants). Overall, our analyses offer clear support for the PPH: Offspring survive better on preferred plant types, and females lay more eggs on plant types conducive to offspring performance. We also found evidence for an effect of diet breadth on host choice: female preference for 'good quality plants' was stronger in oligophagous insects than in polyphagous insects. Nonetheless, despite the large numbers of preference-performance studies conducted to date, sample sizes in our meta-analysis are low due to the inconsistent format used by authors to present their results. To improve the situation, we invite authors to contribute to the data base emerging from this work, with the aim of reaching a strengthened synthesis of the subject field.
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Biogeography has traditionally focused on the spatial distribution and abundance of species. Both are driven by the way species interact with one another, but only recently community ecologists ...realized the need to document their spatial and temporal variation. Here, we call for an integrated approach, adopting the view that community structure is best represented as a network of ecological interactions, and show how it translates to biogeography questions. We propose that the ecological niche should encompass the effect of the environment on species distribution (the Grinnellian dimension of the niche) and on the ecological interactions among them (the Eltonian dimension). Starting from this concept, we develop a quantitative theory to explain turnover of interactions in space and time – i.e. a novel approach to interaction distribution modeling. We apply this framework to host–parasite interactions across Europe and find that two aspects of the environment (temperature and precipitation) exert a strong imprint on species co‐occurrence, but not on species interactions. Even where species co‐occur, interaction proves to be stochastic rather than deterministic, adding to variation in realized network structure. We also find that a large majority of host‐parasite pairs are never found together, thus precluding any inferences regarding their probability to interact. This first attempt to explain variation of network structure at large spatial scales opens new perspectives at the interface of species distribution modeling and community ecology.
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Agriculture is one of the largest anthropogenic sources of greenhouse gases (GHGs), with dairy and beef production accounting for nearly two-thirds of emissions. Several recent papers suggest that ...dung beetles may affect fluxes of GHGs from cattle farming. Here, we put these previous findings into context. Using Finland as an example, we assessed GHG emissions at three scales: the dung pat, pasture ecosystem, and whole lifecycle of milk or beef production. At the first two levels, dung beetles reduced GHG emissions by up to 7% and 12% respectively, mainly through large reductions in methane (CH4) emissions. However, at the lifecycle level, dung beetles accounted for only a 0.05-0.13% reduction of overall GHG emissions. This mismatch derives from the fact that in intensive production systems, only a limited fraction of all cow pats end up on pastures, offering limited scope for dung beetle mitigation of GHG fluxes. In contrast, we suggest that the effects of dung beetles may be accentuated in tropical countries, where more manure is left on pastures, and dung beetles remove and aerate dung faster, and that this is thus a key area for future research. These considerations give a new perspective on previous results, corrected and suggest that studies of biotic effects on GHG emissions from dung pats on a global scale are a priority for current research.
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A large array of species distribution model (SDM) approaches has been developed for explaining and predicting the occurrences of individual species or species assemblages. Given the wealth of ...existing models, it is unclear which models perform best for interpolation or extrapolation of existing data sets, particularly when one is concerned with species assemblages. We compared the predictive performance of 33 variants of 15 widely applied and recently emerged SDMs in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDMs that model each species individually combining the predictions afterward. We offer a comprehensive evaluation of these SDM approaches by examining their performance in predicting withheld empirical validation data of different sizes representing five different taxonomic groups, and for prediction tasks related to both interpolation and extrapolation. We measure predictive performance by 12 measures of accuracy, discrimination power, calibration, and precision of predictions, for the biological levels of species occurrence, species richness, and community composition. Our results show large variation among the models in their predictive performance, especially for communities comprising many species that are rare. The results do not reveal any major trade-offs among measures of model performance; the same models performed generally well in terms of accuracy, discrimination, and calibration, and for the biological levels of individual species, species richness, and community composition. In contrast, the models that gave the most precise predictions were not well calibrated, suggesting that poorly performing models can make overconfident predictions. However, none of the models performed well for all prediction tasks. As a general strategy, we therefore propose that researchers fit a small set of models showing complementary performance, and then apply a cross-validation procedure involving separate data to establish which of these models performs best for the goal of the study.
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An increase in species richness with decreasing latitude is a prominent pattern in nature. However, it remains unclear whether there are corresponding latitudinal gradients in the properties of ...ecological interaction networks. We investigated the structure of 216 quantitative antagonistic networks comprising insect hosts and their parasitoids, drawn from 28 studies from the High Arctic to the tropics. Key metrics of network structure were strongly affected by the size of the interaction matrix (i.e. the total number of interactions documented between individuals) and by the taxonomic diversity of the host taxa involved. After controlling for these sampling effects, quantitative networks showed no consistent structural patterns across latitude and host guilds, suggesting that there may be basic rules for how sets of antagonists interact with resource species. Furthermore, the strong association between network size and structure implies that many apparent spatial and temporal variations in network structure may prove to be artefacts.
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