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

[摘要] Historically, ecosystem models have treated rainfall asthe primary moisture source driving litter decomposition. In many arid andsemi-arid lands, however, non-rainfall moisture (fog, dew, and water vapor)plays a more important role in supporting microbial activity and carbonturnover. To date though, we lack a robust approach for modeling the role ofnon-rainfall moisture in litter decomposition. We developed a series ofsimple litter decay models with different moisture sensitivity andtemperature sensitivity functions to explicitly represent the role ofnon-rainfall moisture in the litter decay process. To evaluate modelperformance, we conducted a 30-month litter decomposition study at 6 sitesalong a fog and dew gradient in the Namib desert, spanning almost an eightfolddifference in non-rainfall moisture frequency. Litter decay rates in thefield correlated with fog and dew frequencies but not with rainfall. Includingeither temperature or non-rainfall moisture sensitivity functions improvedmodel performance, but the combination of temperature and moisturesensitivity together provided more realistic estimates of litterdecomposition than relying on either alone. Model performance was similarregardless of whether we used continuous moisture sensitivity functionsbased on relative humidity or a simple binary function based on the presenceof moisture, although a Gaussian temperature sensitivity outperformed amonotonically increasing Q 10 temperature function. We demonstrate thatexplicitly modeling non-rainfall moisture and temperature together isnecessary to accurately capture litter decay dynamics in a fog-affecteddryland system and provide suggestions for how to incorporate non-rainfallmoisture into existing Earth system models.

[学科分类] 大气科学