Evaluation of LandscapeDNDC Model Predictions of CO2 and N2O Fluxes from an Oak Forest in SE England

Shirley M. Cade,Matthew Wilkinson,Rüdiger Grote,Sirwan Yamulki,Saúl Molina-Herrera,Edwin Haas,Kevin C. Clemitshaw,James I. L. Morison

doi:10.3390/f12111517

Shirley M. Cade, Matthew Wilkinson + Show 6 more

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https://doi.org/10.3390/f12111517

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Abstract

Process-based biogeochemical models are valuable tools to evaluate impacts of environmental or management changes on the greenhouse gas (GHG) balance of forest ecosystems. We evaluated LandscapeDNDC, a process-based model developed to simulate carbon (C), nitrogen (N) and water cycling at ecosystem and regional scales, against eddy covariance and soil chamber measurements of CO2 and N2O fluxes in an 80-year-old deciduous oak forest. We compared two LandscapeDNDC vegetation modules: PSIM (Physiological Simulation Model), which includes the understorey explicitly, and PnET (Photosynthesis–Evapotranspiration Model), which does not. Species parameters for both modules were adjusted to match local measurements. LandscapeDNDC was able to reproduce daily micro-climatic conditions, which serve as input for the vegetation modules. The PSIM and PnET modules reproduced mean annual net CO2 uptake to within 1% and 15% of the measured values by balancing gains and losses in seasonal patterns with respect to measurements, although inter-annual variations were not well reproduced. The PSIM module indicated that the understorey contributed up to 21% to CO2 fluxes. Mean annual soil CO2 fluxes were underestimated by 32% using PnET and overestimated by 26% with PSIM; both modules simulated annual soil N2O fluxes within the measured range but with less interannual variation. Including stand structure information improved the model, but further improvements are required for the model to predict forest GHG balances and their inter-annual variability following climatic or management changes.

Highlights

The long-lived greenhouse gas (GHG) that contribute most to global warming with high radiative forcing values are carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) [1]
This study evaluates the LandscapeDNDC model with measured GHG flux data from eddy covariance and soil chamber studies in the Straits Inclosure where N deposition is relatively low at approximately 12 kg N ha−1 year−1 [28]
Simulated daily mean soil temperature data at 10 cm depth from January 2007 to December 2012 were similar to measurement data (Figure 1a, y = 0.8x + 2.1, R2 = 0.90), they do not quite show the same degree of variation and have a 5–6 ◦C lower amplitude range, in earlier years

Summary

Introduction

The long-lived GHGs that contribute most to global warming with high radiative forcing values are carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) [1]. Temperate forests occupy an area of 767 Mha and contribute 0.8 ± 0.1 Pg C year−1 to global C sinks [2]. Soil microbiological processes that result in fluxes of GHGs are reasonably well understood. Many laboratory studies have contributed to the understanding and quantification of these soil processes (e.g., [5,6,7]), and field measurements have helped to understand their spatial and temporal variability, and differences between forest types (e.g., [8,9]). Soil environmental conditions of temperature and moisture and nutrient levels are the primary controls of microbiological processes that lead to GHG fluxes, and are influenced directly and indirectly by secondary factors such as tree shading and density

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