<jupyter_start><jupyter_text>Estimating the total biomass on EarthTo estimate the total biomass on Earth, we sum all of the contributions from each of the taxa. Here are our estimate of the total biomass of each taxon:<jupyter_code>results = pd.read_excel('results.xlsx','Table1 & Fig1', index_col=[0,1])
results
best_estimate = results['Biomass [Gt C]'].sum()
print('Our best estimate for the global biomass on Earth is ≈%.d Gt C' %round(best_estimate,-1))<jupyter_output>Our best estimate for the global biomass on Earth is ≈550 Gt C<jupyter_text>Uncertainty analysisTo project the uncertainty associated with our estimate of the total biomass on Earth, we sum the biomass of the different kingdoms of life and take into account the uncertainty in our estimates of their biomass:<jupyter_code>kingdoms = results.groupby(level=0).apply(sum).drop('Total biomass')

mul_CI = CI_sum_prop(estimates=kingdoms['Biomass [Gt C]'], mul_CIs=kingdoms['Total uncertainty'])
print('Our best projection for the uncertainty associated with our estimate of the total biomass on Earth is ≈%.1f-fold' %mul_CI)
update_results(path='results.xlsx', sheet='Table1 & Fig1',row = ('Total biomass','Total biomass'), col='Total uncertainty', values=mul_CI)<jupyter_output><empty_output>
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