Integrative analysis of relative abundance data and presence-absence data of the microbiome using the LDM

We previously developed LDM for testing hypotheses about the microbiome that performs the test at both the community level and the individual taxon level. LDM can be applied to relative abundance data and presence-absence data separately, which work well when associated taxa are abundant and rare, respectively. Here we propose an omnibus test based on LDM that allows simultaneous consideration of data at different scales, thus offering optimal power across scenarios with different association mechanisms. The omnibus test is available for the wide range of data types and analyses that are supported by LDM. The omnibus test has been added to the R package LDM, which is available on GitHub at https://github.com/yijuanhu/LDM .

Salinity Tolerance of Four Hardy Ferns from the Genus Dryopteris Adans. Grown under Different Light Conditions

Hardy ferns form a group of attractive garden perennials with an unknown response to abiotic stresses. The aim of this study was to evaluate the tolerance of three species of ferns of Dryopteris genus (D. affinis, D. atrata and D. filix-mas) and one cultivar (D. filix-mas cv. “Linearis-Polydactylon”) to salinity and light stress. The plants were grown in full sun and shade and watered with 50 and 100 mM dm−3 NaCl solution. All taxa treated with 100 mM NaCl responded with reduced height, leaf greenness index and fresh weight of the above-ground part. In D. affinis and D. atrata salinity caused leaf damage manifested by necrotic spots, which was not observed in the other two taxa. The effect of NaCl depended on light treatments and individual taxon. D. affinis and D. atrata were more tolerant to salinity when growing under shade. Contrary to that, D. filix-mas cv. “Linearis-Polydactylon” seemed to show significantly greater tolerance to this stress under full sun. Salt-treated D. filix-mas cv. “Linearis-Polydactylon” plants accumulated enhanced amounts of K+ in the leaves, which might be associated with the taxon’s tolerance to salinity. Among the investigated genotypes, D. filix-mas cv. “Linearis-Polydactylon” seemed the most and D. affinis and D. atrata the least tolerant to salinity and light stress.

A Rarefaction-Based Extension of the LDM for Testing Presence-Absence Associations in the Microbiome

BackgroundMany methods for testing association between the microbiome and covariates of interest (e.g., clinical outcomes, environmental factors) assume that these associations are driven by changes in the relative abundance of taxa. However, these associations may also result from changes in which taxa are present and which are absent. Analyses of such presence-absence associations face a unique challenge: confounding by library size (total sample read count), which occurs when library size is associated with covariates in the analysis. It is known that rarefaction (subsampling to a common library size) controls this bias, but at the potential cost of information loss as well as the introduction of a stochastic component into the analysis. Currently, there is a need for robust and efficient methods for testing presence-absence associations in the presence of such confounding, both at the community level and at the individual-taxon level, that avoid the drawbacks of rarefaction.MethodsWe have previously developed the linear decomposition model (LDM) that unifies the community-level and taxon-level tests into one framework. Here we present an extension of the LDM for testing presence-absence associations. The extended LDM is a non-stochastic approach that repeatedly applies the LDM to all rarefied taxa count tables, averages the residual sum-of-squares (RSS) terms over the rarefaction replicates, and then forms an F-statistic based on these average RSS terms. We show that this approach compares favorably to averaging the F-statistic from R rarefaction replicates, which can only be calculated stochastically. The flexible nature of the LDM allows discrete or continuous traits or interactions to be tested while allowing confounding covariates to be adjusted for.ResultsOur simulations indicate that our proposed method is robust to any systematic differences in library size and has better power than alternative approaches. We illustrate our method using an analysis of data on inflammatory bowel disease (IBD) in which case samples have systematically smaller library sizes than controls.ConclusionsThe rarefaction-based extension of the LDM performs well for testing presenceabsence associations and should be adopted even when there is no obvious systematic variation in library size.

Climatic Reconstruction in Europe for 18,000 YR B.P. from Pollen Data

An improved concept of the best analogs method is used to reconstruct the climate of the last glacial maximum from pollen data in Europe. In order to deal with the lack of perfect analogs of fossil assemblages and therefore to obtain a more accurate climate reconstruction, we used a combination of pollen types grouped according to plant phenology and present climate constraints rather than pollen percentages for each individual taxon. The distribution of pollen taxa into plant functional types (PFTs) is aimed to reflect the vegetation in terms of biomes which have a wider distribution than a species. The climatic variables are then calibrated on these PFTs using an artificial neural network technique. The use of PFTs allowed us to deal with situations where pollen assemblages have only partial modern analogs. The method is applied to the glacial steppic vegetation in Europe, using 15 pollen records. North of the Pyrenees–Alps line, the reconstructed temperatures were lower than today: −30 ± 10°C for the temperature of the coldest month ( Tc) and −12 ± 3°C for the annual mean ( Tann). South of that line, Tc and Tann anomalies were respectively, −15 ± 5°C and −10 ± 5°C. The available moisture index and annual precipitation were also lower than present: −60 ± 20% north of Mediterranean Sea, (−800 ± 100 mm for precipitation). In Italy and Greece, the available moisture was 20% lower, with a precipitation anomaly of ca. −600 ± 200 mm. Southward, the moisture index was close to that at present (±20%), and precipitation was lower (−300 ± 300 mm).

Rock-wallaby Conservation: Essential Data and Management Priorities. Proceedings of the 1994 National Rock-Wallaby Symposium Workshops.

Workshops held at the 1994 National Rock- wallaby Symposium aimed to identify the gaps in knowledge that hinder the effective management and conservation of rock-wallabies. They also sought to identify research and management priorities for rock- wallabies at both the generic and individual taxon level. The requirements and difficulties of ensuring the implementation of research results and management strategies were also discussed.

The macrobenthic infauna off Sellafield (north-eastern irish sea) with special reference to bioturbation

Between 1983 and 1989,66 stations in the north-eastern Irish Sea offshore from Sellafield, Cumbria, were sampled by Reineck box corer to assess the abundance and distribution of the benthic macro-infauna. A total of 40 taxa was identified, of which the predominant group was polychaetes. Cluster analysis of the abundance data showed a division into three station clusters. Simple discriminant analysis showed that the three clusters were correlated (P<0.01) with sand, silty sand and sandy silt sediments. However, the three station groups did not show any clear pattern of characterizing taxa with sediment classification. The bioturbating potential of each taxon is reviewed. A method of weighting abundance data by a factor representing an estimate of individual taxon bioturbating potential is also suggested. This technique is illustrated and discussed by using the weighted data in a further cluster analysis to identify probable areas of high inf aunal bioturbation off Sellafield.