In the face of unprecedented global changes and biodiversity loss, understanding how biodiversity change affects the functioning of Earth’s ecosystems across all scales, from local to global, is critical. However, assessing biodiversity–ecosystem function relationships across large spatial scales with traditional field-based approaches is close to intractable, even for a single point in time. Moreover, moving beyond phenomenological descriptions of biodiversity–ecosystem function relationships is needed to predict the consequences of biodiversity change under novel conditions—yet, direct evidence of underlying mechanisms is rare. Here we ask whether and how emerging remote sensing technologies—which are becoming increasingly accessible—can be leveraged to meet these challenges. We combined airborne imaging-spectroscopy data (AVIRIS-NG) with field-collected data across a tree-diversity experiment (IDENT-Cloquet, MN, USA) composed of 192 young stands of monocultures and different mixtures of two and six species. Using spectroscopic imaging, we estimated stand productivity, mapped canopy nitrogen and identified the species composition of stands. We also quantified the spectral differences among stands, introducing the concept of the 'spectral net biodiversity effect' which can be partitioned into components that reveal distinct underlying ecological mechanisms.
Results/Conclusions
Differences between the spectral reflectance of monocultures and mixed-species stands enabled us to quantify spectral net biodiversity effects on productivity and on canopy nitrogen, both of which were associated with diversity effects on productivity as quantified on the ground. We then partitioned spectral net biodiversity effects into components attributable to shifts in species' relative abundances within the canopy (spectral dominance effect) and to within-species shifts in spectral reflectance (spectral plasticity effect), revealing how these processes contribute to diversity-induced differences in stand-level spectra, chemistry and productivity. Consistent with physiological understanding, diversity-enhanced productivity across stands was best explained by the dominance of species with greater canopy nitrogen. Our results demonstrate that in the investigated experimental forest stands diversity effects on productivity can be remotely detected by spectrally identifying both the species composition and productivity of stands.
Spectral data lend a new perspective for viewing communities, potentially opening new avenues of ecological questioning and insight. Our spectral approach to quantifying biodiversity effects in young forests at small scales provides insight into underlying ecological drivers and, in theory, could be applied at large spatial scales. Overall, this work highlights the promise of remote sensing to address challenges in documenting and understanding biodiversity–ecosystem function relationships across scales.