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This paper evaluates the out-of-distribution performance of the Prithvi-EO-2.0 geospatial foundation model for crop classification across 37 events in 12 countries on three continents, finding accuracy declines driven largely by phenological misalignment rather than pure spatial transfer, and proposes no-retraining adjustments like class consolidation and observation-window compression to recover operational reliability.