Journal
IFOREST-BIOGEOSCIENCES AND FORESTRY
Volume 11, Issue -, Pages 786-793Publisher
SISEF-SOC ITALIANA SELVICOLTURA ECOL FORESTALE
DOI: 10.3832/ifor2825-011
Keywords
Climate; Leaf Fall; Litterfall; Modelling; Plant-soil Interactions; Quercus suber; Seasonality
Categories
Funding
- Ministry of Science and Innovation of Spain
- National Agriculture Research Institute (INIA) [SUM2006-00026-00-00]
- Diputacio de Girona, Spain
- postdoctoral grant - Universidad Complutense in Madrid
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Litterfall plays a key role in the dynamic of forest ecosystems, ultimately determining forest productivity and carbon and nutrient cycling. Increasing our understanding on the role of structural and environmental factors controlling litterfall amount and seasonality is of paramount importance for modelling and estimating soil carbon sequestration and nutrient cycling under climate change scenarios. However, the effect of climatic conditions on litterfall has been scarcely studied, especially in Mediterranean ecosystems. Here, we used nine years of seasonally collected litterfall data in two contrasting Mediterranean cork oak forests to evaluate the effect of climatic variables on leaf fall and litterfall. First, we isolated the litterfall seasonal trend and the between-sites differences in production by using linear mixed models. Then, we evaluated the effect of climatic variables and whether this effect was site-specific. We found a consistent litterfall seasonal pattern, mainly determined by leaf shedding (70% of litterfall). Leaf fall mainly occurs in spring with a second but much smaller peak in autumn some years. Mean temperature, precipitation and mean wind speed strongly influenced litterfall, but this effect was site-specific. In the forest site located at higher latitude and altitude, leaf fall increased linearly with temperature and showed a positive quadratic response to precipitation. In the water-limited site, leaf fall was reduced as temperature increased and did not respond to precipitation. These results have implications for modelling and predicting soil carbon sequestration, nutrient cycling, and the forest ecosystem productivity. Specifically, carbon and nutrient cycling models can be improved by incorporating idiosyncratic forest sites responses to climatic variability.
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