Evaluating the potential of full‐waveform lidar for mapping pan‐tropical tree species richness

Abstract

Aim Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full‐waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness. Location Tropics. Time period Present. Major taxa studied Trees. Methods First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large‐footprint full‐waveform lidar data (22 m diameter) and related these findings to in‐situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan‐tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression. Results The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R2 ranging from .44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan‐tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R2 = .39 and RMSD% = 43%, 0.25‐ha resolution). Main conclusions Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics.

Large trees in tropical rain forests require big plots

“…As the price of remote sensing continues to drop and the technology matures the need for accurately located and identified tree plots will increase. Marselis et al., (2020), for example, call for more coincident lidar and field data to improve models.…”

Carbon Stocks, Species Diversity and Their Spatial Relationships in the Yucatán Peninsula, Mexico

“…These maps used mainly field data obtained from national forest inventories (NFI), which provide a more representative number of sampling plots as well as detailed information of vegetation structure used to estimate biomass [16]. In contrast, despite the current alarming loss of biodiversity, there is a lack of plant diversity maps with high spatial resolution at regional scales [17]. In this work, we created one of the first regional maps of tree species diversity with high spatial resolution (25 m) using the TDF of the Yucatan Peninsula as a model.…”

“…Species diversity also increases with forest structure [17], but has been found to be strongly and positively associated with environmental or habitat heterogeneity [29], which is in turn associated with higher availability of niches [30]. There are different ways to measure environmental heterogeneity from remotely sensed data, from using variance of spectral data to more complex methods such as texture metrics, which reflect spatial variation within a moving window in an image [31].…”

The Rapid Rise of Next-Generation Natural History

“…For the last 50 years, satellite remote sensing has documented landscape-level modifications due to human encroachment (Harper et al, 2007), spread of invasive species (Pengra et al, 2007), plant and animal diseases (Colwell, 1996;Liu et al, 2006;Bruno et al, 2007), and fire (Nepstad et al, 1999). The recent availability of satellite based lidar data from the Global Ecosystem Dynamics Investigation mission now opens a new window of opportunity to understand fine scale vegetation structure at a global scale, including predictions of tropical forest tree species richness (e.g., Marselis et al, 2020). These data collected at the global scale can then be used as explanatory variables to model resource selection and identify suitable habitat for target species (Jarvis et al, 2005).…”