Abstract
Agroforestry combines perennial woody elements (e.g. trees) with an agricultural understory (e.g. wheat, pasture) which can also potentially be used by a livestock component. In recent decades, modern agroforestry systems have been proposed at European level as land use alternatives for conventional agricultural systems. The potential range of benefits that modern agroforestry systems can provide includes farm product diversification (food and timber), soil and biodiversity conservation and carbon sequestration, both in woody biomass and the soil. Whilst typically these include benefits such as food and timber provision, potentially, there are benefits in the form of carbon sequestration, both in woody biomass and in the soil. Quantifying the effect of agroforestry systems on soil carbon is important because it is one means by which atmospheric carbon can be sequestered in order to reduce global warming. However, experimental systems that can combine the different alternative features of agroforestry systems are difficult to implement and long-term. For this reason, models are needed to explore these alternatives, in order to determine what benefits different combinations of trees and understory might provide in agroforestry systems. This paper describes the integration of the widely used soil carbon model RothC, a model simulating soil organic carbon turnover, into Yield-SAFE, a parameter sparse model to estimate aboveground biomass in agroforestry systems. The improvement of the Yield-SAFE model focused on the estimation of input plant material into soil (i.e. leaf fall and root mortality) while maintaining the original aspiration for a simple conceptualization of agroforestry modeling, but allowing to feed inputs to a soil carbon module based on RothC. Validation simulations show that the combined model gives predictions consistent with observed data for both SOC dynamics and tree leaf fall. Two case study systems are examined: a cork oak system in South Portugal and a poplar system in the UK, in current and future climate.
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Notes
DPM/RPM ratios are proposed in Coleman and Jenkinson (2014) for Agricultural crops and improved grasslands (1.44; 59% DPM and 41% is RPM), Unimproved grasslands and scrub (0.67; 40% DPM and 60% RPM); Deciduous or tropical woodland (0.25; 20% DPM and 80% RPM) and Farmyard manure (1; DPM 49%, RPM 49% and HUM 2%). When day of tree harvest occurs, the ratio between DMP and RPM is considered 0.25.
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Funding
European Commission through the AGFORWARD FP7 research Project (contract 613520), Forest Research Center strategic Project (PEst OE/AGR/UI0239/2014), the Portuguese Foundation for Science and Technology (FCT) fellowships SFRH/BD/52691/2014 and SFRH/BPD/96475/2013, XUNTA DE GALICIA, Consellería de Cultura, Educación e Ordenación Universitaria (“Programa de axudas á etapa posdoutoral”) (contract ED481B 2016/071-0)
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Palma, J.H.N., Crous-Duran, J., Graves, A.R. et al. Integrating belowground carbon dynamics into Yield-SAFE, a parameter sparse agroforestry model. Agroforest Syst 92, 1047–1057 (2018). https://doi.org/10.1007/s10457-017-0123-4
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DOI: https://doi.org/10.1007/s10457-017-0123-4