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Bridging the gaps between field-based ecology and remote sensing to estimate plant functional diversity: a systematic review

19 Feb 2026 · 10.64898/2026.02.19.706857

Abstract

Understanding plant functional diversity across scales requires integrating field-based ecology and remote sensing, yet these disciplines differ in how traits are studied. We evaluated the conceptual and methodological convergence between these disciplines. Our results reveal that field-based ecology has undergone longer conceptual development and covers a broader range of traits, while remote sensing has experienced rapid growth driven by technological advances. Both disciplines are increasingly converging on similar concepts. However, major gaps in empirical coverage persist across biomes in both disciplines. Although plant-dominated ecosystems have been extensively studied, extreme ecosystems remain undersampled. While there is considerable diversity in the definition “functional traits”, both disciplines converge on using a similar set of traits, reflecting their central role in plant strategies and spectral detectability. Our synthesis underscores the potential for methodological synergy. Harmonizing trait definitions, scaling assumptions, and computational steps involved in estimating plant functional diversity are crucial for building a unified, multiscale framework for biodiversity monitoring in ecosystems undergoing biodiversity loss and climate change. Teaser A synthesis of how field ecology and remote sensing can be aligned to monitor plant functional diversity across scales.

Plant phenotyping relevance

植物機能形質・機能多様性をリモートセンシングで推定する方法論の系統的レビューであり、形質定義、スケーリング、計算手順の統合が中心である。

titleBridging the gaps between field-based ecology and remote sensing to estimate plant functional diversity: a systematic review
abstractHarmonizing trait definitions, scaling assumptions, and computational steps involved in estimating plant functional diversity are crucial for building a unified, multiscale framework for biodiversity monitoring

Code and data availability

The supplied blocks contain no data or code availability statements, no public phenotype/trait datasets, images, sensor inputs, author analysis code, or trained models specific to this systematic review. The paper is a bibliometric/systematic review; only generic references to trait databases and remote sensing data (e

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