Abstract

Assessing functional diversity and its abiotic controls at continuous spatial scales are crucial to understanding changes in ecosystem processes and services. Semi-arid ecosystems cover large portions of the global terrestrial surface and provide carbon cycling, habitat, and biodiversity, among other important ecosystem processes and services. Yet, the spatial trends and patterns of functional diversity in semi-arid ecosystems and their abiotic controls are unclear. The objectives of this study are two-fold. We evaluated the spatial pattern of functional diversity as estimated from small footprint airborne lidar (ALS) with respect to abiotic controls and fire in a semi-arid ecosystem. Secondly, we used our results to understand the capabilities of large footprint spaceborne lidar (GEDI) for future applications to semi-arid ecosystems. Overall, our findings revealed that functional diversity in this ecosystem is mainly governed by elevation, soil, and water availability. In burned areas, the ALS data show a trend of functional recovery with time since fire. With 16 months of data (April 2019-August 2020), GEDI predicted functional traits showed a moderate correlation (r = 41–61%) with the ALS predicted traits except for the plant area index (PAI) (r = 11%) of low height vegetation (<5 m). We found that the number of GEDI footprints relative to the size of the fire-disturbed areas (=< 2 km2) limited the ability to estimate the full effects of fire disturbance. However, the consistency of diversity trends between ALS and GEDI across our study area demonstrates GEDI’s potential of capturing functional diversity in similar semi-arid ecosystems. The capability of spaceborne lidar to map trends and patterns of functional diversity in this semi-arid ecosystem demonstrates its exciting potential to identify critical biophysical and ecological shifts. Furthermore, opportunities to fuse GEDI with complementary spaceborne data such as ICESat-2 or the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR), and fine scale airborne data will allow us to fill gaps across space and time. For the first time, we have the potential to monitor carbon cycle dynamics, habitats and biodiversity across the globe in semi-arid ecosystems at fine vertical scales.

Highlights

  • Understanding the drivers of ecosystem processes and services at regional and global scales provide pivotal knowledge to assess ecosystem responses under changing conditions (Díaz et al, 2007; Isbell et al, 2015)

  • Our objectives were to 1) evaluate the spatial pattern of functional diversity estimated from small footprint airborne lidar (ALS) with respect to abiotic controls and fire in a semi-arid ecosystem; and 2) assess Global Ecosystem Dynamics Investigation (GEDI)’s potential of capturing the semi-arid ecosystem diversity at regional scales using GEDI data from 16 months (April 2019–August 2020) over the same study area

  • We describe functional diversity as a 3-D trait space where the axes are represented by the three functional traits

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Summary

Introduction

Understanding the drivers of ecosystem processes and services at regional and global scales provide pivotal knowledge to assess ecosystem responses under changing conditions (Díaz et al, 2007; Isbell et al, 2015). In addition to climate factors, other influences including human intervention and pathogens can alter functional traits and their spatial distribution (Oliva et al, 2020). The distribution of functional traits within and between species of an ecosystem represent the demography, resilience, and response strategies to disturbance (Díaz et al, 2004; Poorter and Markesteijn, 2008; Serbin et al, 2019). A wealth of research uses functional trait-based approaches to assess ecosystem processes and services including productivity, nutrient cycling and biodiversity (Hooper et al, 2002; Bardgett and van der Putten, 2014; Violle et al, 2014; Wieczynski et al, 2019). Functional traits have been utilized in assessing community assembly processes across a variety of traits (e.g., Pakeman and Stockan, 2014; Medeiros et al, 2019)

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