Bridging Big and Small: How Remote Sensing and Microbial Data Are Transforming Ecosystem Science

Understanding how the tiniest of organisms influence the largest ecosystems in the world is what will shed light on the environmental problems facing us in modern-day ecological science. Microbes are generally invisible to the naked eye, yet they play major environmental roles, driving processes ranging from nutrient cycling to disease outbreaks.

However, studying these tiny organisms in large landscapes has always been challenging. That is where the cutting-edge technology of remote sensing when integrated with omics-based microbial research, may potentially fundamentally change how we perceive and understand ecosystems.

In a recent paper, The Future Is Big—and Small: Remote Sensing Enables Cross-Scale Comparisons of Microbiome Dynamics and Ecological Consequences, Deanna S. Beatty and co-authors from the University of California and Cornell University outline an exciting way forward: combining remote sensing technologies with microbial omics data to understand relationships of microbes and their environments at large spatial scales.

What is Remote Sensing?

Remote sensing is the collection of information regarding an environment from a distance. Most often, this means using a satellite or an unmanned aerial vehicle (UAV). These tools collect detailed images and environmental measurements across large spatial extents in such a way that becomes appropriate for monitoring changes in ecosystems. Very exciting is that the newest ways to use these technologies can give scientists insights with one incredibly fine spatial resolution—as fine as one centimetre when using UAVs!

Think of being able to monitor how a microscopic community of bacteria in the ocean influences massive phenomena like coral bleaching or harmful algal blooms. That is the real power of using remote sensing combined with microbial research.

Microbial Dynamics: Small Organisms, Big Effect

Microbes are tiny bacteria, fungi, and other microorganisms that have huge roles in ecosystems. Take, for example, Prochlorococcus, the most abundant photosynthetic organism on Earth. It creates a large amount of oxygen produced by the planet and participates in global carbon cycling. Forecasting large-scale environmental change through understanding the biotic interaction of these organisms within the environment is the paramount task.

English: Microbiome dynamics in time and scale

    a) Temporal dynamics of the microbiome are characterized by considering both the transient state of the microbiome as a response to

 environmental perturbations, such as, for example, seasonal or circadian rhythms, and the resident state that contains rather constant core microbiota.

  b) Spatial dynamics of the microbiome are characterized by variations in the microbial composition between similar habitats separated in

space. The separation may be between the organisms (e.g., the same plant species grown in two different locations), between the parts of one

 organism (e.g., plant roots and the whole plant), or even within an organ (e.g., comparing microbiomes of various intestinal segments)

Attribution: Gabriele Berg, Daria Rybakova and 33 others, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, via Wikimedia Commons

The Beatty et al. paper discusses how omics-based approaches are revealing microbial interactions; such a way of studying it is through metagenomics—studying the collective genetic material of microbial communities. But why stop there? By combining this powerful data with remote sensing tools, researchers can now see how these microbes influence whole ecosystems across time and space.

Case Studies: Algal Blooms to Seagrass Health

Below we present two of the most important case studies in which remote sensing linked to microbial data is already making history within the realm of scientific research:

Phytoplankton Blooms: 

Harmful algal blooms have recently come out as a problem in fresh and marine waters due to their potential to harm human and wildlife health. UAVs, along with satellite data, allow scientists to follow these blooms' development; at the same time, they have a chance to monitor microbial dynamics that could influence this development and persistence. This makes it easier to predict or manage such dangerous events.

Attribution: Contains modified Copernicus Sentinel data 2019, CC BY-SA 3.0 IGO <https://creativecommons.org/licenses/by-sa/3.0/igo/deed.en>, via Wikimedia Commons

Seagrass Disease:

Seagrasses are paramount in maintaining marine biodiversity, but they are under constant threat from diseases such as wasting disease of seagrass. Using UAVs in the monitoring of seagrass meadows, the change in the presence of pathogens and environmental stressors, weakening these ecosystems, may be detected. The fusion of remote sensing and microbial data can help scientists predict outbreaks and even develop targeted restoration efforts.

Attribution: Frédéric Ducarme, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, via Wikimedia Commons

Why Cross-Disciplinary Research is Essential

The interdisciplinary approach is a great promise. It conjoins experts in microbiology, ecology, remote sensing, and data science to yield new insights into the ecosystems. Machine learning algorithms digest the huge data collected by satellites and UAVs, and spatial statistics are a tool for scientists to link microbial activities with environmental changes.

This type of collaboration is important for us to understand and address the complex environmental challenges that lie ahead, such as climate change, habitat degradation, and species loss.

Looking Ahead: Ecosystem Prediction and Management

One of the most exciting opportunities for predictive ecological modelling is the coupling of microbial and remote sensing data. By linking such information, a scientist could create models that predict ecosystem changes before these are manifest. Imagine predicting exactly where the next harmful algal bloom will form, or how a warming ocean will impact coral reef ecosystems. Such knowledge would inform and guide conservation efforts, resource management, and even policy-making.

As Beatty and her team suggest, the future of ecological research lies in these big and small connections. Integration of microbial data and remote sensing is in its infancy but holds great promise. These tools are going to help make sense of the vast networks of life that drive our planet's ecosystems—and help ensure we're better equipped to protect them in the years ahead.

Conclusion

The integration of microbial research and remote sensing technologies dramatically changes our insight into and control over ecosystems. This cross-disciplinary approach opens new frontiers in environmental science from tracking the tiniest microbial interactions to the prediction of large-scale ecological consequences. As climate change and other global challenges ramp up, big and small data will be our best hope for preserving the ecosystems that sustain life on Earth. In these ways, science is crossing the divide between the very small and the very large, giving us a better view of Earth's future as Beatty and her team fittingly call it—both big and small.

Citation:

Beatty, D. S., Aoki, L. R., Graham, O. J., & Yang, B. (2021). The future is big—and small: Remote sensing enables cross-scale comparisons of microbiome dynamics and ecological consequences. mSystems, 6(6), e01106-21. https://doi.org/10.1128/mSystems.01106-21