Ecosystem Characterization and Functioning

What is this about?

Ecosystem characterization and functioning refer to the scientific study and understanding of ecosystems, including their structure, components, interactions, and the processes that govern their stability and dynamics. Ecosystems are complex and interconnected systems comprising living organisms, such as plants, animals, and microorganisms, along with their physical environment, such as soil, water, and climate.
Ecosystem characterization involves identifying and describing the various components of an ecosystem, including its biotic (living) and abiotic (non-living) factors.

Main research areas

Ecosystem characterization

By combing field data, sensing technology, and machine learning we define new techniques and approaches to improve our understanding of the various components and interactions within an ecosystem. An ecosystem is a complex, interconnected system comprising living organisms (biotic components) and their physical environment (abiotic components), which interact and influence each other. Ecosystem characterization involves studying the ecological relationships, patterns, processes, and functions that define a particular ecosystem. This information helps scientists, researchers, and policymakers gain insights into how ecosystems work and how they might be managed or conserved.

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EcoImaging: Subsurface to above surface integration

Subsurface to above-surface integration in EcoImaging refers to a scientific approach that combines imaging techniques and data from both below-ground (subsurface) and above-ground (surface) environments to study and understand ecological processes and interactions within ecosystems. EcoImaging is an interdisciplinary field that integrates various imaging technologies, remote sensing, and ecological research to gain insights into the complex dynamics of ecosystems. This integration allows researchers to explore the relationships between the above-ground vegetation, soil properties, and the underlying subsurface features, such as root systems, soil moisture, and geology. By capturing data from both perspectives, EcoImaging provides a more comprehensive understanding of the functioning and health of ecosystems and how they respond to environmental changes.

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Forest decline

Forest’s decline due to pulse and press disturbances including bark beetles, temperature increase, earlier snowmelt, exceptional droughts, and wildfire have been observed in mountainous ecosystems, affecting species diversity and composition, associated functional traits, productivity and mortality. To better understand how forested regions of watersheds will respond to future perturbations, it is critical to quantify and characterize such ecosystem changes. Using time-series satellite imaging (Landsat, Sentinel, Planet) we compute and analyze variations in health, productivity, and functional traits.

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Scaling ecosystem fluxes with remote sensing

Creating models that forecast carbon exchange, which represents the equilibrium between the intake of carbon dioxide through photosynthesis and its release through respiration by autotrophs and heterotrophs, plays a pivotal role in the terrestrial carbon cycle. Alpine meadows stand as ecosystems characterized by their carbon-rich soils and exhibit abrupt shifts in ecosystem structure due to extreme climatic conditions, such as snowmelt timing, temperature fluctuations, and the duration of the growth season, which significantly impact the resident biota. The world of alpine plant communities is intricately tied to a diverse range of microclimatic conditions and topographic variations, yet the implications of this diversity on ecosystem processes remain unclear. Thus, it becomes imperative to pinpoint indicators of shifts in vegetation within alpine meadows, as doing so is essential for comprehending how alterations in the community impact the rates at which carbon circulates. We use spectroscopic techniques and machine learning to build models to predict carbon fluxes.

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Selected publications

  • Enguehard, L., Falco, N., Schmutz, M., Newcomer, M. E., Ladau, J., Brown, J. B., Bourgeau-Chavez, L., & Wainwright, H. M. (2022). Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie. Remote Sensing, 14(14), 3285. Link
  • Uhlemann, S., Dafflon, B., Wainwright, H. M., Williams, K. H., Minsley, B., Zamudio, K., Carr, B., Falco, N., Ulrich, C., & Hubbard, S. (2022). Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics. Science Advances, 8(12), eabj2479. Link
  • Wainwright, H. M., Uhlemann, S., Franklin, M., Falco, N., Bouskill, N. J., Newcomer, M. E., Dafflon, B., Siirila-Woodburn, E. R., Minsley, B. J., Williams, K. H., & Hubbard, S. S. (2022). Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions. Hydrology and Earth System Sciences, 26(2), 429–444. Link
  • Chadwick, K. D., Brodrick, P. G., Grant, K., Goulden, T., Henderson, A., Falco, N., Wainwright, H., Williams, K. H., Bill, M., Breckheimer, I., Brodie, E. L., Steltzer, H., Rick Williams, C. F., Blonder, B., Chen, J., Dafflon, B., Damerow, J., Hancher, M., Khurram, A., … Maher, K. (2020). Integrating airborne remote sensing and field campaigns for ecology and Earth system science. Methods in Ecology and Evolution. Link
  • Devadoss, J., Falco, N., Dafflon, B., Wu, Y., Franklin, M., Hermes, A., Hinckley, E.-L. S., & Wainwright, H. (2020). Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem. Remote Sensing, 12(17), 2733. Link
  • Hermes, A. L., Wainwright, H. M., Wigmore, O., Falco, N., Molotch, N. P., & Hinckley, E.-L. S. (2020). From Patch to Catchment: A Statistical Framework to Identify and Map Soil Moisture Patterns Across Complex Alpine Terrain. Frontiers in Water, 2. Link
  • Falco, N., Wainwright, H., Dafflon, B., Léger, E., Peterson, J., Steltzer, H., Wilmer, C., Rowland, J. C., Williams, K. H., & Hubbard, S. S. (2019). Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High‐Resolution Remote Sensing and Surface Geophysical Data. Journal of Geophysical Research: Biogeosciences. Link
  • Hubbard, S. S., Williams, K. H., Agarwal, D., Banfield, J., Beller, H., Nicholas Bouskill, Brodie, E., Carroll, R., Dafflon, B., Dwivedi, D., Falco, N., Faybishenko, B., Maxwell, R., Nico, P., Steefel, C., Steltzer, H., Tokunaga, T., Tran, P. A., Wainwright, H., & Charuleka Varadharajan. (2018). The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics. Vadose Zone Journal, 17(1), 0. Link
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