meth_6.1.1 Microbial Niche Indices

Contributor(s): Mark Brown: https://orcid.org/0000-0002-6591-2989 ; Martin Ostrwoski: https://orcid.org/0000-0002-4357-3023

Citation: Brown, M.V., Ostrowski, M., Messer, L.F. et al. A marine heatwave drives significant shifts in pelagic microbiology. Commun Biol 7, 125 (2024). https://doi.org/10.1038/s42003-023-05702-4

AM Project ID:

Calculation of species optima and range parameters

RCode for calculation of microbial species and community indices from 3 column species x abundance x environmental variable is available on the Australian Microbiome Github (https://github.com/AusMicrobiome/microbial_ocean_atlas).

 

For each ASV we calculate the optima and range of its relationship with available environmental parameters including temperature, salinity, nitrate/nitrite, phosphate, silicate, oxygen and chlorophyll.

Relative abundance data along with associated environmental variables were fit to a Kernel Density Estimation (KDE) function using the density() function in the stats package. This is a non-parametric smoothing technique used to estimate the probability density function of a random variable. The value of the environmental variable at the maximum point of the Kernel Density curve (point of maximal estimated abundance), is then defined as the species optima. Species ranges were calculated as the difference between the minimum and maximum of the environmental parameter where kernel density = ¼ peak height. We allowed the normal distribution of the kernel density model to continue 3 ℃ each side of the minimum and maximum temperature in each instance to allow for potentially negatively or positively skewed range dynamics (e.g. organisms with temperature optima close to or at the minimum or maximum range). To further ensure the kernel density approach was not inaccurately identifying optima we also calculated temperature optima based on the mean temperature of the samples in which each organism displayed its four highest relative abundances. There was some evidence that this mean approach led to marginally higher bacterial and archaeal STI at upper temperature ranges, but the effect did nothing to alter the observed latitudinal trends in temperature bias, and indeed in eukaryotes the effect was marginally increased.

 

For each index we report the mean and standard deviation based on 100 repeat KDE calculations. To remove sampling bias, for each of the 100 iterations, samples were selected randomly with replacement from bins along the variable gradient, based on the number of samples in the smallest sized bin. Each ASV was required to be present in at least 100 samples in the subset for the calculation to be performed.

 

In all we calculated 7 indices and associated measures, which are illustrated by the example of Temperature below.

 

Species Temperature Index (STI) is a measure of the optimal temperature of the realised thermal niche of an organisms’ (represented by an ASV) for a given environmental variable. It was calculated as 1) the value corresponding to the peak of the abundance weighted kernel density plot or 2) using the mean of the value of the variable for samples containing the top 4 relative abundances.

 

Species thermal range (STR) is the temperature range for a defined species (ASVs) abundance, here calculated as the difference between the minimum and maximum temperatures where kernel density = ¼ peak height.

 

 

Species thermal bias (T-bias) is the difference between STI and environmental sea temperature at the time and depth of sampling (ST) and thus is not a static factor for any given species. Thermal bias can also be calculated using the species maximum temperature (Tmax; maximum temperatures where kernel density = ¼ peak height) rather than optimum (STI), providing an indication of periods where environmental temperatures approach or exceed the upper limits of a species known thermal distribution.

 

Community temperature/thermal index (CTI) is the average thermal affinity of the entire assemblage. Calculated as the realised thermal niche of each organism present (STI) weighted by their relative abundance.

 

 

Thermal bias (T_bias) CTI – ST difference between CTI and environmental sea temperature (ST). Thermal bias is positive for assemblages that are composed of taxa displaying temperature affinities higher than the local temperature. Theoretically these assemblages may be preconditioned to higher temperatures and thus display reduced sensitivity to warming. Conversely, thermal bias is negative for assemblages dominated by taxa with a cooler thermal affinity than the local temperature, implying increased sensitivity to warming.

 

Community thermal range (CTR) is the abundance weighted average width of thermal ranges of all species in the assemblage. This index provides an indication of whether the predominant STRs of the species in the assemblage are broad or narrow.

 

 

Community thermal diversity (CTDiv) is the variability of thermal affinities among species in the assemblage, calculated as the abundance weighted standard deviation of all STIs. Low values of CTDiv correspond to assemblages that are composed of taxa with similar STIs, while higher values of CTDiv reflect an assemblage structure with a wider range of STIs, that is, composed of both warm and cold-water taxa.