The forests of Amazonia are celebrated for both their exceptional biodiversity and their vital role in the global carbon and water cycles, which contribute towards climate change mitigation. However, our understanding of the spatial organisation of biodiversity and its interaction with ecosystem function at large scales is limited, due primarily to the laborious nature of collecting biodiversity data in Earth’s largest tropical forest. The Carnegie Airborne Observatory (CAO) is a unique research platform, consisting of a custom-built aircraft providing airborne laser-guided spectral profiles of forest canopies at an unprecedented level of spatial and spectral resolution at large spatial scales (e.g. >100 km2). This ‘spectranomic’ approach presents a new paradigm in tropical forest ecology, as spectra reflect the chemical composition of leaves. When combined with careful field calibration, spectranomic techniques can be used to measure specific leaf traits (e.g. leaf N concentration), and potentially map the distribution of individual species at large spatial scales. The goal of E FUNDIA is to integrate state of the art, high fidelity imaging spectroscopy and extensive field plot networks in order to quantify the relationship between biodiversity and ecosystem function in lowland Amazonian tree communities at large spatial scales
The specific objectives of the project are:
1: Map the spatial distribution of >50 common tree species at landscape and regional scales in lowland Amazonia.
2: Determine the extent to which taxonomic diversity drives functional diversity across environmental gradients in lowland Amazonia.
3: Quantify the role of hyperdominant taxa in driving patterns of functional diversity across environmental gradients in lowland Amazonia.
Following the completion of the project the following conclusions have been made:
1. Most hyperdominant tree species in West Amazonian forests cannot be identified from airborne remotely sensed data with a 2m pixel size, this is because their crowns either cannot be seen at all from above, or cannot be isolated from the surrounding forest canopy.
2. Those tree species that dominate the uppermost canopy and emergent strata (i.e. those that are potentially visible in remotely sensed data) are different from those species that dominate lower strata. Moreover these canopy and emergent hyperdominant species are phylogenetically clustered in just a few key plant families.
3. While airborne spectranomic approaches have been used to successfully map variation in community level functional traits, using this data to observe trait data associated with specific tree species presents a major challenge and 2m ground resolution is likely insufficient in most instances.
4. The higher spatial resolution (<10 cm) of UAV data offers greatly enhanced potential for mapping hyperdominant tree species (particularly those with distinctive crown shapes) and potentially for measuring functional trait profiles if UAV-based hyperspectral sensors become more available.
5. More species rich forests do not appear to be necessarily more functionally diverse than more species poor, due to high functional redundancy in diverse Amazonian forests. Functional diversity is increased by including a range of different forest types, regardless of their species richness.
