SpecNet

Toward a better understanding of global carbon and water vapor flux patterns across the world

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SpecNet (Spectral Network) is an international network of cooperating investigators and sites linking optical measurements with flux sampling for the purpose of improving our understanding of the controls on these fluxes.

Themes

SpecNet research focuses on the following themes:

Enhanced optical sensing methods

  • Linked optical-flux (carbon &/or water) sampling, particularly at the ecosystem scale.
  • Novel optical sampling methods, processing methods, indices, etcetera, particularly those relevant to fluxes.
  • Factors controlling carbon- and water vapor fluxes, particularly as they can be detected with optical sampling.
  • Studies applying optical or thermal methods to understanding component fluxes (e.g. separate respiratory and photosynthetic components of carbon flux).

Remote sensing of biodiversity

  • Assessing the contrasting roles of individual plants, species, functional types, and whole-ecosystem behavior, particularly as they can be detected optically
  • Multi-scale analyses of optical signals or optical-flux relationships
  • Experimental (i.e. comparative) studies of optical signals/remote sensing (comparison of multiple spatial, temporal or spectral scales, contrasting ecosystem treatments, different instruments, contrasting methods, various models, et cetera), particularly as they affect interpretation of ecosystem fluxes.

Developing and assessing vegetation indices

  • Comparative analyses of optical-flux relationships across ecosystems, etc.
  • Evaluation of light-use efficiency models or their component terms (Efficiency, APAR…).
  • Development of the chlorophyll/carotenoid index (CCI), a reflectance index sensitive to seasonally changing chlorophyll/carotenoid pigment ratios, particularly in evergreen conifers.
Welcome

Biospheric Carbon

SpecNet data can be used to monitor phenologic and biospheric carbon fluxes, which, at present, are not well represented in carbon markets. SpecNet measurements provide a link between fluxes and remote sensing, which is needed if we are to "scale" from local fluxes (e.g. chamber or eddy covariance measurements) to regional and global understanding (e.g. satellite maps). These measurements can also be used to validate aircraft and satellite imagery used in the calculation of carbon fluxes and stocks.

Image (right): Mead irrigated maize soybean rotation site, Mead, NE, University of Nebraska-Lincoln field site

SpecNet

Grants

Data Grants

SpecNet offers small, short-term grants to encourage contributors to share data, protocols, and related software tools. Awards can be up to (US) $5000 for up to a period of up to 3 months. At the end of the period, successful applicants are expected to provide a report and deliver data or tools in a form compatible with SpecNet’s open-access policies. Students and early-career scientists are particularly encouraged to apply.

Travel Grants

SpecNet offers small, short-term grants to encourage contributors to share data, protocols, and related software tools. This grant covers travel costs for participation in SpecNet activities.

 

Image (left): Radiation and spectral monitoring booms at Fontainebleau-Barbeau fieldsite, France.

Join us!

We are a data sharing consortium dedicated to maximizing the usefulness of data, knowledge, and expertise in order to advance our understanding of ecosystem function. By clicking on the link below, you agree to follow the Fair Use Policy:

--Kindly inform the appropriate Principal Investigators of how you are using site data and of any publication plans. If the Principal Investigators feel that they should be acknowledged or offered participation as authors, they will let you know and we assume that an agreement on such matters will be reached prior to publishing and/or use of the data for publication. If your work directly competes with the Principal Investigator's analysis they may ask that they have the opportunity to submit a manuscript before you submit the one that uses their data. In addition, when publishing, please acknowledge the agency that supported the research.--