Preprints
https://doi.org/10.5194/bg-2022-16
https://doi.org/10.5194/bg-2022-16
 
14 Feb 2022
14 Feb 2022
Status: this preprint was under review for the journal BG. A revision for further review has not been submitted.

Accounting for non-rainfall moisture and temperature improves litter decay model performance in a fog-dominated dryland system

J. Robert Logan1,2, Kathe E. Todd-Brown3, Kathryn M. Jacobson4, Peter J. Jacobson4, Roland Vogt5, and Sarah E. Evans1,2 J. Robert Logan et al.
  • 1W. K. Kellogg Biological Station, Hickory Corners, MI, USA
  • 2Department of Integrative Biology, Michigan State University, East Lansing, MI, USA
  • 3Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL, USA
  • 4Department of Biology, Grinnell College, Grinnell, IA, USA
  • 5Institute of Meteorology, Climatology and Remote Sensing, University of Basel, Basel, Switzerland

Abstract. Historically, ecosystem models have treated rainfall as the primary moisture source driving litter decomposition. In many arid and semi-arid lands however, non-rainfall moisture (fog, dew, and water vapor) plays a more important role in supporting microbial activity and carbon turnover. To date though, we lack a robust approach for modeling the role of non-rainfall moisture in litter decomposition. We developed a series of simple litter decay models with different moisture sensitivity and temperature sensitivity functions to explicitly represent the role of non-rainfall moisture in the litter decay process. To evaluate model performance, we conducted a 30-month litter decomposition study at six sites along a fog/dew gradient in the Namib Desert, spanning almost an eight-fold difference in non-rainfall moisture frequency. Litter decay rates in the field correlated with fog and dew frequency but not with rainfall. Including either temperature or non-rainfall moisture sensitivity functions improved model performance, but the combination of temperature and moisture sensitivity together provided more realistic estimates of litter decomposition than relying on either alone. Model performance was similar regardless of whether we used continuous moisture sensitivity functions based on relative humidity or a simple binary function based on the presence of moisture, though a Gaussian temperature sensitivity outperformed a monotonically increasing Q10 temperature function. We demonstrate that explicitly modeling non-rainfall moisture and temperature together is necessary to accurately capture litter decay dynamics in a fog-affected dryland system and provide suggestions for how to incorporate non-rainfall moisture into existing Earth system models.

J. Robert Logan et al.

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-16', Anonymous Referee #1, 24 Mar 2022
    • AC2: 'Reply on RC1', J. Robert Logan, 23 Apr 2022
  • RC2: 'Comment on bg-2022-16', Anonymous Referee #2, 31 Mar 2022
    • AC1: 'Reply on RC2', J. Robert Logan, 23 Apr 2022

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-16', Anonymous Referee #1, 24 Mar 2022
    • AC2: 'Reply on RC1', J. Robert Logan, 23 Apr 2022
  • RC2: 'Comment on bg-2022-16', Anonymous Referee #2, 31 Mar 2022
    • AC1: 'Reply on RC2', J. Robert Logan, 23 Apr 2022

J. Robert Logan et al.

J. Robert Logan et al.

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Short summary
Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but in deserts, it’s a different story. We performed a 2.5-year study in one of the driest places on Earth (the Namib Desert in southern Africa) and found that fog and dew, not rainfall, closely controlled how quickly plants decompose. We also created a model to help predict decomposition in drylands with lots of fog/dew.
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