Sentence examples for models with species from inspiring English sources

In hierarchical models with species identity as a random effect, we found no evidence of a demographic advantage to resident species.

We analyzed data using Multimodel Inference and Model Averaging on Generalized Linear Mixed Models, with species presence/absence as the response variable, sampling area as a random factor and forest covariates as fixed factors.

Our assumption of relatively similar bird detectability within pools was supported, and models with species as a covariate were the least likely compared to models with a vegetation type covariate, an observer covariate and no covariate for all three species pools (Table S4).

Temporal patterns in hydrolysate preference were examined by comparing preference scores on the first and second days of the HC and GE series using Repeated Measures (RM) ANOVA models with species as the between-subjects factor and day as the within-subjects factor.

Doing this, we found that only five models with species absent from any reactive organization remained: BIOMD044, BIOMD093, BIOMD094, BIOMD143 and BIOMD151 (Table 1).

Statistics: We re-analyzed all data using mixed models with "species ID" included as a subject grouping factor and random intercepts for each species.

To this end, we suggested a framework that includes the modeling of species distributions and corresponding environmentally associated intraspecific variation using population-level genetic and phenotypic variation and the subsequent integration of the resulting models with species-level information and socio-economic data to finalize prioritization (Thomassen et al. 2010).

Using large observational study in Northeast China, Temesgen et al. (2014) used a nonlinear mixed effect model with species indicators to make tree height predictions compatible and precise for 23 tree species found in multi-layered forests in NE China.

Good agreement of the CFD predictions with the experimental data was obtained by the k ɛ model with species transport, where dependence of the CFD predictions on the turbulent Schmidt number (i.e. Sct) was discussed in detail.

The limitation of the BO PVT model in violating the species material balance principal could lead to significant errors when pairing the BO PVT model with species material balance-based techniques such as Walsh Towler algorithm (Walsh and Towler 1995; Walsh and Lake 2003).

Some populations adapt to these changes, but the overall contribution of evolution to species' persistence decreases in models with high species richness.