Abstract
Plant biodiversity supports life on Earth and provides a range of important ecosystem services, but is under severe pressure by global change. Structural diversity plays a crucial role for carbon, water and energy cycles and animal habitats. However, it is very difficult to map and monitor over large areas, limiting our ability to assess the status of biodiversity and predict change. NASA’s Global Ecosystem Dynamics Investigation (GEDI) provides a new opportunity to measure 3D plant canopy structure of the world’s temperate, Mediterranean and tropical ecosystems, but its potential to map structural diversity is not yet tested. Here, we use wall-to-wall airborne laser scanning (ALS) to simulate GEDI data (GEDIsim) over 7380 km2 in the southern Sierra Nevada mountains in California and evaluate how well GEDI’s sampling scheme captures patterns of structural diversity. We evaluate functional richness and functional beta diversity in a biodiversity hot spot. GEDIsim performed well for trait retrievals (r2 = 0.68) and functional richness mapping (r2 = 0.75) compared to ALS retrievals, despite lower correlations in complex terrain with steep slopes. Functional richness patterns were strongly associated with soil organic carbon stocks and density as well as variables related to water availability and could be appropriately mapped by GEDIsim with and without cloud cover. Functional beta diversity was more strongly related to local changes in topography and more challenging to map, especially with decreasing sampling density. The reduced number of GEDIsim shots when simulating cloud cover lead to a strong overestimation of beta diversity and a reduction of r2 from 0.64 to 0.40 compared to ALS. The ability to map functional richness has been demonstrated with potential application at continental scales that could be transformative for our understanding of large-scale patterns of plant canopy structure, diversity and potential links to animal diversity, movement and habitats.
Highlights
Ac temperate and tropical forests at 1 km spatial resolution, Global Ecosystem Dynamics Investigation (GEDI) provides a range of products that characterize 3D2019)
It has proven successful in characterizing vegetation canopy structure and structural diversity for a range of traits, such as canopy height (Næsset & Økland, 2002), plant area index (PAI, Schneider et al, 2014), foliage height diversity (FHD, MacArthur & MacArthur, 1961), the vertical distribution of plant material in the canopy (either through PAI profiles (Marselis et al, 2018), or relative height (RH) of lidar energy (Drake et al, 2002; Dubayah et al, 2010)), and combinations thereof (Schneider et al, 2017)
We investigate the following four research questions: (1) How do waveform-based structural traits of GEDIsim compare to discrete return airborne laser scanning (ALS) traits?, (2) Do trait to trait relationships hold between ALS and GEDIsim ?, (3) How does GEDIsim capture functional richness and beta diversity with and without the simulation of cloud cover?, and (4) What is the relationship between functional richness and beta diversity to the environment? We observe this over a heterogeneous mountain landscape, which provides a hot spot for plant biodiversity in the temperate and Mediterranean biomes comprising over 50% of California’s plant diversity with more than 3500 native species (CWWR, 1996)
Summary
Ac temperate and tropical forests at 1 km spatial resolution, GEDI provides a range of products that characterize 3D2019). Since GEDI is a sampling instrument sending laser pulses that reach 25 m diameter on the ground, spaced at 60 m along track and 600 m across track, it is not yet tested to what degree GEDI can capture large-scale diversity patterns and how GEDI observed structural traits relate to established measurements from airborne laser scanning (ALS) acquisitions. It has proven successful in characterizing vegetation canopy structure and structural diversity for a range of traits, such as canopy height (Næsset & Økland, 2002), plant area index (PAI, Schneider et al, 2014), foliage height diversity (FHD, MacArthur & MacArthur, 1961), the vertical distribution of plant material in the canopy (either through PAI profiles (Marselis et al, 2018), or relative height (RH) of lidar energy (Drake et al., 2002; Dubayah et al, 2010)), and combinations thereof (Schneider et al, 2017). The study of structural diversity, in particular of forests, has gained increasing interest due to its importance for the carbon cycle, ecosystem services, plant and animal diversity, and habitat characterization (Bohn & Huth, 2017; Vierling et al, 2008; Davies & Asner, 2014)
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