What the study found
Eddy covariance tower sites are not evenly distributed across global soils and climate conditions. The study found that the network overlaps with soils that are, on average, more fertile than soils across the terrestrial surface.
Why the authors say this matters
The authors conclude that global syntheses of eddy covariance towers should recognize this bias toward more fertile soils. They also suggest that building collaborations and investing in underrepresented regions would be a logical way to improve global representativeness.
What the researchers tested
The researchers examined 1,233 global eddy covariance towers. They compared tower locations with global soil database pixels and also looked at distances between towers to assess how often sites had nearby neighbors for possible paired tower studies.
What worked and what didn't
Half of the towers had a nearest neighbor within 10 km. Soil pixels with towers had nearly 20% more silt and 8% less sand than the global soil texture distribution, along with more soil nitrogen, organic carbon, and about 10% greater cation exchange capacity in upper layers than pixels without towers.
What to keep in mind
The abstract does not describe detailed study limitations beyond the unequal representation it reports. The findings are limited to the global tower network and the soil and spacing comparisons described in the abstract.
Key points
- The study examined 1,233 global eddy covariance towers.
- Half of the towers had a nearest neighbor within 10 km.
- Tower locations were associated with soils that had more silt, less sand, more nitrogen, more organic carbon, and higher cation exchange capacity than comparison pixels without towers.
- The authors say global syntheses should account for this bias toward more fertile soils.
- The authors suggest collaborations and investment in underrepresented regions to improve representativeness.
Disclosure
- Research title:
- Global eddy covariance towers cluster on more fertile soils
- Authors:
- Paul Stoy, Housen Chu, Emma Dahl, Daniela Cala, Victoria Shveytser, Susanne Wiesner, Ankur R. Desai, Kimberly A. Novick
- Institutions:
- University of Wisconsin System, University of Wisconsin–Madison, Lawrence Berkeley National Laboratory, Indiana University Bloomington, Technical University of Denmark
- Publication date:
- 2026-03-30
- OpenAlex record:
- View
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