Measuring biodiversity from microbes to insects and plants to what we can see from space.

Biodiversity sustains life on Earth and is rapidly changing under the sixth mass extinction. While conservation focuses on species- specific management, there is a need for bioindicators to study, monitor, and assess our success at curbing biodiversity loss globally. The "Essential Biodiversity Variables (EBV)" are intended to help measure biodiversity conservation efforts, however they span different measurement techniques, and little is know about how these techniques relate to one another. 

Pereira et al. (2013), Science, 339:6117 p 277-278. DOI: 10.1126/science.1229931

Remote sensing can make consistent measurements globally, but work is needed to relate it to the scales of biodiversity that are managed (taxon and phylogenies). Imaging spectroscopy and thermal imaging can map key ecosystem functions that relate to species habitat. As such, the 2017-2027 Earth Science Decadal Survey recognized mapping biodiversity as a “very important” observational need using imaging spectroscopy and thermal imaging. Thus, we critically need an objective method for calibrating and validating our algorithms from one location to another.

Current research has correlated remote sensing to field survey observations of keystone species as indicators representing broader diversity across kingdoms. These observations, however, are limited in the taxonomic breadth they can efficiently capture, are labor intensive, and have certain observer biases.

In contrast, environmental DNA (eDNA) can be collected by citizen scientists and provides a unified bioinventory across organismal scales (bacteria, fungi, plants, invertebrates and vertebrates) that can explain point-to-watershed scale biodiversity patterns. The challenge with eDNA is that it is still a relatively new methodology and little is known about how transient the signal is and how it correlates with observations from above (i.e., remote sensing and traditional field metrics).

Because NASA will be launching a global imaging spectrometer and thermal imager as part of the Surface Biology and Geology (SBG) mission (expected launch in the late 2020s), there is a pressing need to understand how relatively affordable, and consistent observations of biodiversity like that of eDNA, relate to such remote sensing measurements.

Specifically, there is a need to understand how taxonomic, phylogenetic, and functional diversity relate (See Definitions below). We ask: how do eDNA, traditional field, and remote sensing observations of biodiversity relate across spatial scales within the Berg and Eerste River watersheds?

We test three hypotheses on:

  1. the relationships between phylogenetic, taxonomic, and functional biodiversity;
  2. how biodiversity organizes in a watershed; and
  3. how signals relate to hydrometeorological processes.

We will explore relationships between phylogenetic (eDNA), taxonomic (eDNA, vegetation), and functional (AVIRIS-ng and HyTES) biodiversity and create maps. Our cross-disciplinary, international team will collect eDNA, invertebrate, and vegetation surveys in the dry season in conjunction with NASA AVIRIS-ng and HyTES (precursors to SBG) and after rain (no flights). We aim to observe phylogenetic, taxonomic, and functional biodiversity across ecoregions connected along the Berg and Eerste Rivers, freshwater to marine watersheds in South Africa’s Greater Cape Floristic Region (GCFR).

Outcomes from this research can have significant implications for global biodiversity mapping by testing applicability of joint eDNA-remote sensing while also advancing our understanding of the organizational units of biodiversity across scales.

Figure 2A credit to M. Newcomer and D. Swantek (LBNL) as part of collaborations for similar work in the California Russian River watershed. LBNLFigure EESA19-011.

Figure 2 shows that we focus on watersheds (A) to test if the organizational units of hydrogeomorphic change at variable scales (B) vary with ecological units of biodiversity (C) in the Berg River Watershed using eDNA to inventory all kingdoms and using traditional vegetation surveys, with SBG-precursor airborne remote sensing data: AVIRIS-ng and HyTES. 



Common Terms

Functional Traits - describe biogeochemical traits that represent ecosystem function, as they represent key chemical processes (e.g., metabolism) that facilitate many of the cellular functions necessary to sustain life. Each of these traits (e.g., %C, %N, Phosphorus) are characterized by chemical compounds with variable structures that absorb and scatter the electromagnetic spectrum from the visible to thermal infrared.

Functional Diversity - describes the diversity of functional traits over an area. For any given area, there can be many pixels. The distance between these pixels in a multi-dimensional space with functional traits as the axes can describe the richness (volume), evenness and divergence of their distribution within this space (Schneider et al., 2017).

Phylogenetic Diversity - describes the evolutionary relationships among taxa where distance is calculated from differences in molecular or morphological characters that separate clades and contribute to branch lengths of phylogenetic trees. On these clades, we can calculate how redundant (regular) communities are in clades, clade richness, divergence, and extinction/loss.

Taxonomic Diversity - describes the diversity of taxa within an evolving hierarchical nomenclature constructed by taxonomists that have historically grouped organisms based on morphology, ecological or economic function, or genetic similarity. Grouping species relies on taxonomic classification when a species has not been evaluated in a phylogenetic analysis.

Project Team

Project Lead

Matthew Rossi

Matthew Rossi is a geomorphologist who recently joined the Earth Lab team as a Post-Doctoral Research Scholar in the research area of Erosion. He received his B.S. in Geology from the College of William and Mary (2003) and his Ph.D. in Geological Sciences from Arizona State University (2014).

Madeline Slimp

University of California Santa Cruz

Rachel Meyer

University of California Santa Cruz