The world's ecosystems are losing biodiversity fast. A satellite mission designed to track changes in plant functional diversity around the globe could deepen our understanding of the pace and consequences of this change, and how to manage it.

The ability to view Earth's vegetation from space is a hallmark of the Space Age. Yet decades of satellite measurements have provided relatively little insight into the immense diversity of form and function in the plant kingdom over space and time. Humans are rapidly impacting biodiversity around the globe1,2, leading to the loss of ecosystem function3 as well as the goods and services they provide4,5. Recognizing the gravity of this threat, the international community has committed to urgent action to halt biodiversity loss6,​7,​8,​9.

Ecosystem processes10,​11,​12 are often directly linked to the functional biodiversity of plants, that is, to a wide range of plant chemical, physiological and structural properties that are related to the uptake, use and allocation of resources. The functional biodiversity of plants varies in space and time and across scales of biological organization. Capturing and understanding this variation is vitally important for tracking the status and resilience of Earth's ecosystems, and for predicting how our ecological life support systems will function in the future.

We currently lack consistent, repeated, high-resolution global-scale data on the functional biodiversity of the Earth's vegetation2,10,​11,​12. However, the technological tools, informatics infrastructure, theoretical basis and analytical capability now exist to produce this essential data. Here we suggest that this capability should be used in a satellite mission supporting a ‘global biodiversity observatory’ that tracks temporal changes in plant functional traits around the globe to fill critical knowledge gaps, aid in the assessment of global environmental change, and improve predictions of future change. The continuous, global coverage in space and time that such a mission would provide has the potential to transform basic and applied science on diversity and function, and to pave the way to a more mechanistically detailed representation of the terrestrial biosphere in Earth system models.

The data and knowledge gap

Plant functional biodiversity encompasses the vast variation in the chemical, physiological and morphological properties of plants, such as the concentration of metabolites and non-structural carbohydrates in leaves and the ratio of leaf mass to leaf area. These attributes are related functionally to the uptake, allocation and use of resources such as carbon and nutrients within the plant, and to the defence against pests and environmental stresses.

Functional properties vary within and among individuals (for instance, as determined by the position of a leaf on a plant, or a tree in a forest), populations, species and communities, and may be measured at any of these levels of biological organization. With increasing spatial scale (and thus decreasing spatial resolution of measurements), the capture of functional properties may increasingly represent the aggregate properties of many individuals and species, reflecting the functional biodiversity of whole communities. Aggregate ‘functional diversity’ metrics that characterize the breadth of functional properties of a group of organisms are known to be strongly associated with taxonomic13 and phylogenetic14 measures of biodiversity and their potential decrease under habitat loss15. Plant functional biodiversity is also closely linked to ecosystem processes such as carbon, water and energy exchange, which enables a direct integration with Earth system models16,17. Global information on the functional composition and diversity of plant communities thus provides a necessary foundation for monitoring, understanding and predicting the productivity of ecosystems, and for relating productivity and carbon uptake to other critical ecosystem services.

Available global data on plant functional biodiversity are grossly incomplete and non-representative taxonomically, geographically, environmentally, temporally and functionally. Although datasets of traits and their connection to function continue to grow18,19, local observations of plant functional traits are limited along multiple dimensions. On average, only around 2% of currently known vascular plant species have any trait measurements available at the regional scale (here defined as a 110 × 110 km grid cell, n = 11,626); in the species-rich tropical regions, this figure is even smaller (Fig. 1). Data on other biodiversity attributes such as species occurrence, abundance and biomass hold similar biases20,21. These spatial and environmental data gaps and biases are exacerbated by even scarcer information on temporal variation in plant functional biodiversity. Even in areas for which current data are relatively complete, widespread biodiversity change driven by anthropogenic pressures is rapidly outpacing incremental gains in our knowledge of the Earth's biodiversity afforded by in situ biodiversity sampling22. Furthermore, existing ‘global’ datasets have not been collected consistently or systematically, but instead compiled post hoc from thousands of disparate research activities, often not designed to address long-term trends or large-scale patterns23. These severe sampling inhomogeneities and resulting biases cannot be readily overcome statistically, and continue to impose severe limits on inference and application in global biodiversity science21,24,25. An integrated system for rapidly and consistently monitoring plant functional diversity globally is thus urgently needed.

Figure 1: The data gap in regional species trait measurements.
Figure 1

The graph shows the latitudinal variation in the number of vascular plant species for which at least one trait has been measured regionally (open boxes; left axis) in relation to all species expected for that region (filled boxes; right axis). Regions are here defined as 110 × 110 km grid cells (n = 11,626); data on their expected richness is from ref. 25, and region trait data comes from the TRY database (version June 2015)18. Regions are analysed at the grid cell level and their variation is summarized in latitudinal bands of 5° width. On average, only about 2% of species have any such regional measurements, and the data gap is largest in the tropics. This limits understanding of both biodiversity and ecosystem function and services.

Filling the gap

Remote sensing has already proved to be a pivotal technology for addressing the global biodiversity data gap. Data on plant productivity, phenology, land cover and other environmental parameters from MODIS (moderate resolution imaging spectroradiometer) and Landsat satellites currently serve as reasonably effective covariates for spatiotemporal biodiversity models based on in situ data12,20,26. However, the coarse spectral resolution of current satellite-borne sensors has prevented a more direct capture of biodiversity, and correlative models are limited by the above-mentioned data gaps.

In contrast, imaging spectroscopy is a well-established, continuously advancing technology capable of monitoring terrestrial plant functional biodiversity in a way that is vastly richer and more sensitive than other remote sensing techniques22,27,28. It captures environmental information at extremely fine spectral resolution by simultaneously mapping the reflectance and emission of light from the Earth's surface in hundreds of narrow spectral bands, producing essentially continuous spectra from the visible to infrared wavelengths29. Distinctive features are imprinted in these spectra as light interacts with the chemical bonds and structural composition of plants. Spectra are thus an aggregate signal of the chemical and structural composition of vegetation, and can be directly related to a number of leaf biochemical and morphological functional traits (Table 1)30,​31,​32. Air- or satellite-borne spectrometers are able to measure the aggregate functional traits of plant communities represented in the top layers of vegetation, and even the attributes of single species directly, depending on community spatial and spectral characteristics33. This capability has been successfully demonstrated using airborne spectrometers for many traits at regional scales across multiple biomes34,35. There are similar techniques (that are at various stages of development) for characterizing freshwater36 and tidal ecosystems37, marine phytoplankton38,39 and coral reefs40. Satellite technology is now poised to provide global coverage at spatial resolutions sufficiently fine (30 to 60 m pixel size) to support biodiversity inference and applications.

Table 1: Key functional plant traits that are remotely observable from space.

Linking data across scales

A global biodiversity observatory would integrate remotely sensed information on functional traits together with other remotely sensed information and in situ observations of phylogenetic relationships, functional traits and species distributions (Fig. 2). Developing such an observatory would not be without challenges, however. Cloud cover, especially in the tropics, poses constraints for any optical remote-sensing method aiming to be spatially and temporally representative (but see ref. 41 for some encouraging evidence regarding space-based spectrometry). Further, direct measurements of plant traits by imaging spectroscopy are currently limited to only those traits with a clear spectral signature expressed in the canopy layer (Table 1), rendering root and stem traits hard to capture. Finally, the vast quantity of data generated will constrain the spatial resolution that a global mission can support, at least initially: envisioned spatial grains of around 30 m will limit the direct capture of individuals or stands of single species to only a few select cases.

Figure 2: The envisioned global biodiversity observatory.
Figure 2

Top: space-based imaging spectrometer sensors capture global spatial data on key functional attributes in time, including leaf mass per area (LMA), nitrogen concentration (N) and non-structural carbohydrates (NSC), among others (see Table 1). Other sensors (such as LiDAR) may also contribute measurements. An informatics infrastructure and appropriate modelling techniques connect this information with trait, evolutionary and spatial biodiversity information20 collected worldwide in situ at different spatial scales and levels of biological organization (bottom).

The convergence of imaging spectroscopy with other remote-sensing advances, together with prominent developments in plant biology and biogeography, can pave the way to a more integrated global assessment of plant functional biodiversity. Specifically, spectroscopic trait measurements combined with LiDAR (light detection and ranging) data on ecosystem vertical structure at similar spatial resolutions may dramatically enhance the ecological interpretation of the spectral imagery and help overcome its current limitation to surface signals only42,43. Although significant gaps remain (Fig. 1), select trait data has now been collected in situ for more than 100,000 vascular plant species, providing a means to both directly and indirectly connect, through models, spectral observations from the top layer of vegetation to a variety of plant traits18. And the global phylogeny (‘tree of life’) for plants is becoming ever more complete44, enabling researchers to trace the evolutionary history of plant traits within lineages45. Although for some traits and functions convergent evolution has pulled disparate (and often geographically distant) lineages into functional similarity46,​47,​48,​49, traits and associated functions are in many cases conserved to relatively deep phylogenetic levels50,​51,​52. In combination, this provides several relevant opportunities. For example, advances in macroevolutionary models and data-gap-filling techniques53,​54,​55, when coupled with increasingly complete phylogenies, can allow for the prediction of traits for species lacking observations. Further, the strong phylogenetic signal in the individual traits that make up overall functional biodiversity means that spectral observations of aggregate species may in some cases still be meaningfully connected to specific functional properties or clades, and interpreted or monitored as a unit56.

The increasing volume of online species occurrence data is a fourth synergistic development that supports the predictive modelling and mapping of species' and plant community distributions57. Combined with trait and phylogenetic data, and potentially other ecological information (such as typical stand density), hierarchical statistical models and downscaling techniques58,59 may, with some uncertainty, allow the pinpointing of particular species and the make-up of communities. We hypothesize that such predictions will generally be much more effective at coarser levels of biological organization, such as higher-level clades or other well-characterized species groups that can be associated with the aggregate functions of the spectral signal of a pixel.

The envisioned imaging spectroscopy mission will naturally provide only some of the data required for global biodiversity monitoring and modelling. Nevertheless, the model-based integration of detailed and global spectral information with other remote sensing data and rapidly growing in situ biological information points to an array of transformative new opportunities for monitoring plant functional biodiversity through space and time.

A global biodiversity observatory

Scaling up processes from fine-grained local studies to larger regions (and ultimately the entire globe) is an urgent challenge for all of the Earth sciences. Environmental understanding at larger scales requires observations that capture dimensions of the entire system to place the microscale measurements in context. Plant functional biodiversity observations from space have the potential to provide a global context for biodiversity science, and to link the evolutionary and functional diversity of plants at local scales to ecosystem function around the globe. Such information would link key dimensions of diversity to ecosystem processes including the carbon cycle, the water cycle and the provisioning of ecosystem services. And it would revolutionize large-scale research on the stability and resilience of ecosystems to shocks such as drought, fire and pathogen outbreaks. Several space missions planned for launch within this decade60 — such as EnMAP (German Spaceborne Imaging Spectrometer Mission)61 and HISUI (Japan Aerospace Exploration Agency, JAXA)62 — will have some capability for mapping plant functional diversity over limited geographic areas. However, none of these will provide the spatial coverage, repeat frequency or mission duration needed to monitor ecosystem-relevant changes in global plant functional biodiversity through time. Satellites technology such as that proposed for HyspIRI63, a mission that was called for in the 2007 National Research Council (NRC) Decadal Survey64, would be able to serve the initial remote sensing capabilities of the envisioned global biodiversity observatory, but no satellite development process or launch date has yet been determined.

Predicting how ecosystems and the services they provide will respond to accelerating environmental change requires more comprehensive, globally consistent and repeated data on the patterns and dynamics of functional biodiversity. Advanced observing technology (which is available but not yet deployed at scale) integrated with in situ measurements65 could transform this situation. The envisioned global biodiversity observatory offers vastly more biologically relevant and spatially and temporally highly resolved information about vegetation than any existing or otherwise planned global sampling or observation scheme. Rates of change today are so high that the longer a global spectroscopic mission is delayed, the more biological information is irretrievably lost22. The earliest possible launch of a mission able to spectroscopically monitor key plant functional traits globally is an urgent priority for understanding and managing our changing biosphere.


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This study is an output of the ‘Biodiversity from Space’ Working Group of the National Center for Ecological Analysis and Synthesis (NCEAS) and was produced with support from the National Aeronautics and Space Administration (NASA) grant no. NNX14AN31G to NCEAS, University of California, Santa Barbara. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. The work also benefited from National Science Foundation (NSF) grant nos GEO-1408965 (or “Support for the Future Earth Interim Director and Implementation”) and DBI-1262600; NASA grant no. NNX11AP72G to W.J. and R.G.; NSF–NASA Dimensions of Biodiversity grant no. DEB-1342872 to J.C.B.; and the University of Zurich Research Priority Program on ‘Global Change and Biodiversity’ to M.E.S. and F.D.S.

Author information


  1. Yale University, 165 Prospect Street, New Haven, Connecticut 06520, USA.

    • Walter Jetz
  2. Department of Ecology, Evolution and Behavior, University of Minnesota, 1987 Upper Buford Circle, St Paul, Minnesota 55108, USA.

    • Jeannine Cavender-Bares
  3. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, California 91109, USA.

    • Ryan Pavlick
    •  & David Schimel
  4. National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, 735 State Street, Suite 300, Santa Barbara, California 93101, USA.

    • Frank W. Davis
    •  & Mark P. Schildhauer
  5. Department of Global Ecology, Carnegie Institution of Washington, 260 Panama Street, Stanford, California 94305, USA.

    • Gregory P. Asner
  6. Florida Museum of Natural History, University of Florida, Gainesville, Florida 32611, USA.

    • Robert Guralnick
  7. Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745 Jena, Germany.

    • Jens Kattge
    •  & Ulrike Stahl
  8. Department of Plant Sciences, University of California, Davis, 139 Veihmeyer Hall, Davis, California 95616, USA.

    • Andrew M. Latimer
  9. Harvard University, 26 Oxford Street, HMNH, Suite 43, Cambridge, Massachusetts 02138, USA.

    • Paul Moorcroft
  10. University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.

    • Michael E. Schaepman
    •  & Fabian D. Schneider
  11. School of Geography, University of Brighton, 9 Old Court Close, Brighton BN1 8HF, UK.

    • Franziska Schrodt
  12. Center for Spatial Technologies and Remote Sensing, University of California, Davis, 139 Veihmeyer Hall, Davis, California 95616, USA.

    • Susan L. Ustin


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W.J. and J.C.-B. contributed equally to this work.

Corresponding authors

Correspondence to Walter Jetz or Jeannine Cavender-Bares.

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