Consistent crown phenology, not functional traits, predicts whether tropical trees can be mapped from imaging spectroscopy

Phenological regularity is the strongest correlate of spectrally separable tropical tree species in moist forests of French Guiana, surviving multivariate analyses across species, pairs, and crowns.

• Why it matters: Species-level mapping from airborne imaging spectroscopy is possible in hyperdiverse tropical forests, but accuracy varies greatly, and the ecological drivers of spectral separability are unclear.
• What they did: In French Guiana, learning curves were fitted for 169 species using labelled crowns, then six hypothesised determinants were tested on 45 species rarefied to ten crowns at species, species-pair, and crown scales.
• The result: Dispersed sampling and larger crowns increased accuracy, while liana infestation more than halved correct identification odds; leaf and bark traits did not predict separability, implying mapping depends on signal consistency and contamination control.