Sentence examples for data species from inspiring English sources

ENMs (Peterson et al. 1999; Kozak et al. 2008) use the association between distribution data (species occurrences) and environmental variables (e.g., temperature, precipitation) to predict the range within which a species could occur.

The proposed mechanism has been validated against a large number of experimental data including pyrolysis histories, ignition delay time data, species profile versus time and temperature and flame speed measurements over a wide range of initial combustion conditions and various experimental devices including shock tubes, flow reactors, jet-stirred reactors and spherical combustion bombs.

With the age 2 15 year data, species comparisons were conducted using a mixed-effect model for split-plot experiment design with repeated measurements, for average DBH, average height, average live crown length and crown ratio, cronartium infection, survival, stand density index, stand basal area and total volume.

As for the read import step, missing data (species, chromosome, etc).

To analyse whether the diversity of the biogas-producing microbial community is sufficiently covered by the sequence data, species richness, diversity and rarefaction calculations were conducted.

Alternatively, the issues in the molecular data (species polyphyly), at least within the context of this analysis, seem to be more a problem of both precision and accuracy.

Methodologies used by researchers for biomass/carbon stock estimation are destructive, nondestructive, tree inventories data, species-specific biomass estimation, and remote sensing.

Various methods are employed for measuring biomass/carbon include destructive (total harvesting of sample), nondestructive (measurable parameters like basal area, height, tree density), tree inventories data, species-specific biomass estimation, and remote sensing methods (Brown et al. 1989, 1999; Lu 2006; Murali et al. 2005).

The following categories were used for analysis of multi-species data: negative, one species, mixed species (ie >1 species).

Here we analyze the state of knowledge of Caribbean marine biodiversity using georeferenced species-record data and species lists for localities within that region.

We explored the effect of varying pseudo-absence data in species distribution modelling using empirical data for four real species and simulated data for two imaginary species.