Canada＇s　terrestrial　ecostratification　framework　provides　nested　spatial　units　for　organizing　national　data　related　to　soils,　landforms　and　land　use.　In　the　agricultural　domain,　the　lack　of　national,　uniform　crop　yield　data　on　the　ecostratification　framework　severely　hinders　our　ability　to　evaluate　the　biophysical　data　with　respect　to　economic　and　climatic　conditions.　We　developed　a　national　crop　yield　database　at　the　regional　(ecodistrict)　level　by　aggregating　individual　records　of　an　existing　but　very　broad-level　sample-derived　yield　database　according　to　the　ecostratification　hierarchy.　Issues　related　to　the　different　sampling　frameworks　and　the　need　for　confidentiality　of　individual　records　were　resolved　in　order　to　generate　an　ecostratified　crop　yield　dataset　at　a　reasonably　detailed　spatial　scale.　Sixty　crops　were　first　statistically　arranged　into　37　agronomically　similar　crop　groups　in　order　to　increase　class　size,　and　these　crop　groups　were　aggregated　into　increasingly　large　spatial　units　until　confidentiality　was　assured.　The　methodology　maintained　data　quality　and　confidentiality　while　producing　crop　yield　estimates　at　the　ecodistrict　level.　Comparison　to　independent　crop　insurance　data　confirmed　that　the　resulting　crop　yield　data　are　valid　where　estimates　were　derived　from　data　released　at　the　level　of　an　ecodistrict　or　an　ecoregion,　but　not　at　the　ecoprovince　level.　Our　crop　yield　estimates　offer　a　reasonably　high　level　of　spatial　precision　while　remaining　within　standard　confidentiality　constraints.