Biodiversity trends are stronger in marine than terrestrial assemblagesShane Blowes, Sarah Supp, Laura Antao, Amanda Bates, Helge Bruelheide, Jonathan Chase, Faye Moyes, Anne Magurran, Brian McGill, Isla Myers-Smith, Marten Winter, Anne Bjorkman, Diana Bowler, Jarrett EK Byrnes, Andrew Gonzalez, Jes Hines, Forest Isbell, Holly Jones, Laetitia Navarro, Patrick Thompson, Mark Vellend, Conor Waldock, Maria DornelasbioRxiv, October 30th, 2018doi: https://doi.org/10.1101/457424Overview and take-home messages:Blowes et al. tackle an impressive and large undertaking in this paper by attempting to disentangle global biodiversity trends through a meta-analysis of data from 358 studies. By dividing the available data by biome and taxa, the authors were able to detect different biodiversity trends in marine and terrestrial biomes. Tropical marine biomes, particularly the Caribbean, have a more negative deviation from the mean trend in species richness and more positive deviations from the overall trend in species turnover--species are turning over more quickly in marine biomes. The analyses demonstrate that mean local species richness is not decreasing, but many individual regions deviate significantly from the overall mean. The results have important implications for how we discuss changes in biodiversity in the anthropocene, but it is important to make clear that locally static species richness does not equate to globally static species richness, and species are going extinct at an alarming rate. Overall, this paper presents careful analyses and is clearly written, however, there are a few issues that, if addressed, we feel could improve future versions of the manuscript.
Disentangling unspecific and specific transgenerational immune priming components in host-parasite interactionsFrida Ben-Ami, Christian Orlic, Roland R. Regoes doi: https://doi.org/10.1101/429498bioRxiv, 9/27/2018Overview and take-home messages:In this study, the authors tackle the topic of transgenerational immune priming in invertebrates. The authors designed a large experiment taking advantage of clonal Daphnia to test whether infecting parental generations with different parasite strains improves the offspring's resistance to that parasite overall and if yes, if they resist that specific strain more effectively than other strains. This experiment essentially tests the specificity of immune priming at a very fine "strain" scale. The results did not support parental infection strain differentially affecting offspring resistance to different strains, suggesting that immune priming is not specific to the strain level in this system. However, a mathematical model the authors developed for that study fits the data exceptionally well, which means this model could potentially be used in a predictive manner for this or similar systems. Additionally, the unexpected result that one strain actually facilitates specific infection in the offspring is surprising and opens the door to additional inquiry and future experimentation. Overall this study is very interesting and well-presented, but there are a few concerns that could be addressed and improved in the next version of the manuscript.
filtering is not defined as a reduction of species, selection of best-suited species (historical term , but confusing in context)use consistent vocabularymat & methodsthe values measured were much more than listed in the mats and meths (only mention seeds and fitness, but measured root length, leaf area, dry biomas, etc)sentence about pollinators and soil microbes is a little awkward ... Yuka likes figure 1 but typo - below the dashed line should be (-) exponents error bars? each point is a species, but there were replicates ... right?but the highlight? why? pie charts are 200%? -> make 2 (one for green, one for yellow) what about effect of density? within species competition? competitors = intra and interrelative abundance here?change yellow/green to yellow/blueFigure 1c? - I think it would be better to make the the difference between biotic and abiotic effects (or traits) clearer. (Or, a clearer explanation of what they mean by “environment” should be given.) Although authors are using terms in this field correctly, the difference may not be clear. Still, I would appreciate it if they could give more context of coexistence theory and filtering concept.- Is the moisture level a good environmental parameter for these particular plant species? (Any chance that the effect of environmental filtering caused by the wet/dry condition is not strong enough to be compared with the inter/intra-specific interactions used here?)-- is the dry, dry enough?- If authors imply measures of stabilising and equalising mechanisms by fitness difference and niche difference, I think they should state or relate them.
Frequency of disturbance alters diversity, function, and underlying assembly mechanisms of complex bacterial communitiesEzequiel Santillan, Hari Seshan, Florentin Constancias, Daniela I. Drautz-Moses, Stefan Wuertz, May 4th 2018, bioRxiv[doi: https://doi.org/10.1101/313585] Understanding the effects of disturbance on ecosystem function and diversity has many potential applications in microbial ecology and human disease biology. In this paper, the authors tackled the long-standing question of how different disturbance frequencies affect bacterial community diversity and function. To do so, activated-sludge communities within laboratory-scale microcosms were exposed to toxic 3-chloroaniline (3-CA) at varying frequencies. Ecosystem function and community diversity were measured weekly by measuring biomass and organic carbon, ammonia, and toxin removal as proxies for ecosystem function and T-RFLP 16S rRNA gene fingerprinting and shotgun metagenomics were performed to examine variation in bacterial diversity and community composition. This work is an excellent example of integrating genomic and functional analysis, thereby providing a more thorough understanding of the effects of disturbance frequency on microbial community diversity and function. Interestingly, both genetic methods yielded similar results, suggesting that the less expensive gene fingerprinting method could be sufficient when sequencing resources are limited. We particularly commend the use of multiple alpha-diversity measurements and the inclusion of abundance-related indices, which are less method dependent and allow results to be compared between studies. Ultimately, the authors propose the "Intermediate Stochasticity Hypothesis,” which suggests that stochastic processes produce higher diversity assemblages at intermediate disturbance frequencies while deterministic processes produce lower diversity assemblages at low and high disturbance frequencies. Overall, this paper is a fascinating and substantial contribution to microbial ecology. There are, however, a few issues that we feel could be improved in future versions of the manuscript. Major concerns:This comment is unique to the preprint. The manuscript references multiple figures available in the supplementary materials, but these materials were not made available as part of the preprint. This hindered our ability to understand the fine points of the experiments. We encourage the authors to upload the supplementary materials to bioRxiv. 1. Figure 2 is an integral figure to the manuscript because it showcases the effects of 3-CA disturbance frequencies on community performance, namely organic carbon and toxin removal (plots A, C) and nitrification products (plots B, D). In the Materials and Methods section (lines 353-356), the authors state that these parameters were measure weekly, which leads to the assumption that data is available for days 7, 15, 21, and 35, even though only the data from days 7 and 35 are included in the figure (is there T0 data?). The results section refers to supplementary figures S2 and S3 in addition to Figure 2, so these supplementals may portray the data of interest. However, since these data are so important to the overall conclusions, we believe it should be available in the main text. One way to accomplish this could be to have one plot per variable with time on the x-axis and different colors for each disturbance frequency. The number of plots could be reduced by not including Volatile Suspended Solids (VSS) results in the main text. In Figure 2A, the COD removal and 3-CA removal is not monotonously decreasing relative to the disturbance frequency (specifically, level 2 and 4). We figured that this was due to the number of days since the disturbance being different for each disturbance frequency at measurement time on day 7. We encourage the authors to mention and explain this in the text, as this was a puzzling feature of the results for us for some time. It also calls into question the appropriateness of the weekly measurements, especially given that some disturbance level will be highly correlated to this rhythm of measurement (level 1 disturbance will always happen on the same day of the measurements, while level 2 and others will drift). 2. Along with disturbance frequency, varied intensity and duration of disturbance and differing sampling frequencies (e.g- data collection every two days or bi-weekly, larger spread of intermediate disturbance levels) might produce a different pattern of microbial community diversity and function. Questions we can ask are: would the system reach the observed IDH pattern at an early stage? Would the intermediate levels still follow the IDH model? We would be very interested in the authors opinions on these topics, perhaps in the discussion section.
Recent demographic histories and genetic diversity across pinnipeds are shaped by anthropogenic interactions and mediated by ecology and life-history Martin Adam Stoffel, Emily Humble, Karina Acevedo-Whitehouse, Barbara L. Chilvers, Bobette Dickerson, Fillipo Galimberti, Neil Gemmell, Simon D. Goldsworthy, Hazel J. Nichols, Oliver Krueger, Sandra Negro, Amy Osborne, Anneke J. Paijmans, Teresa Pastor, Bruce C. Robertson, Simona Sanvito, Jennifer Schultz, Aaron B.A. Shafer, Jochen B.W. Wolf, Joseph I. Hoffman, April 12, 2018, version 1, bioRxiv doi: https://doi.org/10.1101/293894Firstly, we thank the authors for their work and for posting it as a preprint on bioRxiv. This work endeavored to evaluate the occurrence and intensity of population bottlenecks in a large number of pinniped species that have been differentially affected by human exploitation. Population bottlenecks can decrease genetic diversity and adversely affect the ability of a species to adapt to modern habitat loss and climate change. Because historical data is sparse and unreliable, the authors applied population genetics methods to a large, multi-species dataset to detect and evaluate past population bottlenecks and then compared the results to life-history traits and current conservation status for each species. The results indicate that 11 of the species included in the analysis experienced a population bottleneck and that land-breeding pinnipeds are more likely to have experienced a bottleneck than ice-breeding pinnipeds. While there was not an overall relationship between IUCN status and past bottleneck events, bottleneck events were detected for 4 of the 6 endangered species included in the study. The breadth of this study is especially important, as it represents a first effort to apply these methods across 30 species in a single analysis. Our overall impression is that this was a large project using an extensive amount of data from multiple sources, which then had to be standardized in order to be analyzed in a novel way. This paper highlights the benefits of open science and open data, as data from multiple studies was reused and analyzed in a far broader context than any single study on a single population or species.This manuscript is exceptionally well-written and uses clear language, making it both easy and enthralling to read. However, there are a few small mistakes that caused some confusion. Particularly, the caption of Figure 4 switches the descriptions for Panels A and B. Additionally, the figures in the main text are numbered 1:4, 6; it appears that Figure 5 may have been moved to the supplemental materials, but the main figure numbering was not adjusted accordingly. All of the figures in the manuscript are very attractive and make good use of consistent coloring. Figure 1 nicely summarizes many of the main findings of the paper. This figure would be even better if Panel A utilized a 2-color scale like Panels B and C. Additionally since Pbot and Pneut are complementary, we suggest that only Pbot needs to be included in Panel C, which will reduce the size of the figure and make it easier to interpret. Figure 2 is very clear and intuitive and nicely illustrates the intensity of population bottlenecks for different species. Additionally, the pinniped drawings are beautiful and the use of original artwork in the paper is commendable. We feel that Figure 4, which displays the expected correlation between global abundance and allelic richness does not necessarily need to be included in the main text. Conversely, we feel that Supplementary Table 1, which contains the sample size, number of microsatellite loci, and citation for each species' dataset, is important for readers to have available in the main text. Overall, the authors did an outstanding job applying population genetics techniques appropriately. In particular, the authors made very good use of the program STRUCTURE. This program was used to detect population substructure and if detected, the largest genetic cluster was selected for inclusion in ensuing analyses. This important step prevents false detection of bottlenecks, which can be a common mistake. It is also appreciated that the authors chose to examine allelic richness rather than allelic frequency. We were left with a few lingering questions about the methods, however. First, we are curious if the authors acquired raw electropherograms or pre-interpreted genotypes for the published datasets used and if there were any measures taken to control for observer bias in interpreting microsatellite genotypes, such as preparing and running samples from other labs and assessing whether similar conclusions were reached. We were also curious about the justification for grouping IUCN categories into "concern" ('near threatened,' 'vulnerable,' and 'endangered') and "least concern" ('least concern'), especially since the IUCN Red List Categories and Criteria groups 'near threatened' with 'least concern' and explicitly distinguishes 'vulnerable,' 'endangered,' and 'critically endangered' as the "threatened" categories. We wonder how the results presented in Figure 6 would be affected by moving the species designated as 'near threatened' out of the "concern" category.Lastly, we would have appreciated a more extensive discussion. For example, the authors describe ice-breeding species as experiencing less historical exploitation than the land-breeding species, but ice-breeding species are likely more susceptible to negative impacts from climate change in the recent past and into the future. The implications of the findings of the study combined with change in anthropogenic disturbance patterns and continuing disturbance in these habitats into the future could be addressed in the discussion. We are also very interested in what the authors perceive as weaknesses in the approaches used, if there may be alternative interpretations of the results, and especially what future studies they would suggest based on their results and conclusions. Again, it was a great pleasure reading this impressive work. We hope that our comments are useful to the authors and we look forward to reading the final version when it is published. Thank you!The OIST Ecology and Evolution Preprint Journal Club