Is the Current Modelling of Litter Decomposition Rates Reliable under Limiting Environmental Conditions Induced by Ongoing Climate Change?

• DOI: 10.3390/soilsystems6040081
• Publication Date: 2022-10-26T11:17:48Z
• Authors: Maddalena Ranucci; Martina Perez; Danilo Lombardi; Marcello Vitale
• Keywords: Physical geography; decomposition; 04 agricultural and veterinary sciences; 15. Life on land; GB3-5030; Chemistry; climate change; 13. Climate action; 0401 agriculture, forestry, and fisheries; Mediterranean forest; QD1-999; decomposition; Mediterranean forest; climate change; climatic decomposition index; climatic decomposition index

Plant litter decomposition is a key process in the biogeochemical cycles of terrestrial ecosystems. The main goal of this work is to determine the impact of current climate change on the decomposition process of the litter of Palo Laziale Wood (Rome, Italy), one of the last remnants of the Tyrrhenian lowland forest. A time-dependent simulation of leaf litter decay was previously performed on a dynamic semi-empirical model based on Olson’s model (1963). It was also assumed that microbial activity depended on optimal temperature and moisture conditions simulated by Climatic Decomposition Index (CDI). The comparison between the observed and simulated leaf litter biomass reduction over time (t = −0.127, p = 0.901) highlighted the adequacy of CDI in reproducing biomass trends under limiting climatic conditions (high temperature and low precipitation). However, the decomposition model used here was not able to simulate the reduction of recalcitrant compounds (lignin) in strongly limiting conditions of water availability in the Palo Laziale Wood. These climatic conditions were attributable to climate change, which made the year 2020 representative of future years increasingly characterized by limiting climatic conditions. Therefore, it is necessary to carefully calibrate the CDI in order to consider the current and future changes in temperature and water availability in the Mediterranean area, and to, therefore, perform a better model-based foreseeing for leaf litter decomposition.