Sentence examples for abundance studies from inspiring English sources

The presence of dust implies that planetary nebulae are even richer in heavy elements than gas-phase abundance studies suggest.

Animals with the highest and lowest SF values (six animals each) were then selected for protein abundance studies.

Spatially explicit conservation efforts to identify, designate, and prioritize protected areas or biologically significant areas require analyses beyond basic species distribution and abundance studies, including assessments of migration patterns, habitat use, and ecological drivers of behavior.

On the other hand, it is possible that insect life-history studies detect effects of plant species loss at an earlier stage than richness or abundance studies.

In a review of 100 reef fish abundance studies over the last 10 years, 54% used tape-based belt transects, indicating that this is clearly the dominant UVC technique (see Figure S1 and Text S1).

Although the poor consistency between genome-wide protein abundance studies is likely to arise from many different sources, these observations suggest that varying extraction efficiencies could be one factor contributing to high data variance.

Variations in the abundance pattern of CAZy families among the green and dry roughage groups of the three treatments reveal the modulating microbial diversity with respect to feed as also observed from the abundance study on organisms involved in encoding these CAZymes.

The plant materials tomato (S. lycopersicum) genotypes PtoR and prf3 used for this study were the same as those used for the global protein abundance study, except that the prf3 24 hai samples were not included due to the limitation of six-plexes of the cysTMT.

Using both synthetic data and data from published gene-expression and protein-abundance studies, the authors report that the out-of-bag estimator is similar in performance to the leave-one-out estimator, the performance of other estimators is consistent with what has been observed in the previous studies using single classifiers, and bolstered error estimators showed the best performance.

For protein and transcript abundance, these studies report partially overlapping results sets.

Despite an abundance of studies that predict wildfire occurrence, many of these studies have employed traditional generalized linear models (GLMs), whose prediction accuracy is relatively low.