Localized Versus Non-Localized data: its Effect on Maize Nutrient
Removal, Efficiencies and Budgets at a Global Scale.
Abstract
Estimates of cropland nutrient budgets and nutrient use efficiencies at
national to global scales generally rely on average nutrient
concentrations for quantifying nutrients removed in crop yield and
by-products. Given the relevance of crop removal in nutrient budgets, it
is important that more locally relevant coefficients or models are
developed. However, many countries do not have sufficient data from farm
surveys or field experiments. Using maize as an example, we assessed how
much a country’s estimated nutrient removal is affected when using
either global (Tier 1), regional (Tier 2) or national/sub-national (Tier
3) estimates of harvest index and nutrient concentration of crop
products and residues.
Estimates of cropland removal of nitrogen, phosphorus and potassium
varied substantially (up to 52%), depending on which Tier approach was
used. This had a substantial influence on national nutrient budgets and
nutrient use efficiencies. Our study shows the large uncertainty
associated with current nutrient offtake estimates. If national data
(Tier 2) are not available, Tier 3 offers a methodology to overcome such
data limitations through the application of models, trained on localized
but widely available data for countries. We recommend to use Tier 2 or
Tier 3 approaches once they have been evaluated against real on-farm
data. The presented methodology can be applied to other crops and
nutrients to improve cropland nutrient budgets and estimates of crop
nutrient use efficiencies.