Adaptation of a modelling strategy to predict the NPP of even-aged forest stands

Abstract

The assessment of net forest production is important for both scientific and practical purposes. The current paper presents the application of a recently developed strategy to estimate the net primary productivity of an even-aged Mediterranean pine forest (Natural Park of San Rossore, Central Italy). The strategy is based on the use of two models, C-Fix and BIOME-BGC, whose outputs are combined with forest volume data in order to describe the actual status of the ecosystems examined. The accuracy of the simulation is tested against measurements of current annual increment (CAI) derived from a recent forest inventory of the Park. The results of this test indicate that the methodology must be modified to account for the evenaged nature of the study stands. The modification is performed by the analysis of dendrochronological and tree density data, which characterize the temporal volume and CAI evolution of representative forest stands. The modified methodology is capable of taking into account the effect of stand ageing and yielding nearly unbiased estimates of forest CAI.

Use of Remote Sensing and Biogeochemical Modelling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

“…A similar capability has been proven for the calibrated BIOME-BGC versions to simulate all forest processes in the same region. Further investigations have supported the efficiency of the model combination for predicting the actual processes of forest ecosystems in different development phases [22]. In particular, the independent estimation of the three C pools which regulate photosynthesis, autotrophic and heterotrophic respirations permits an efficient simulation of the processes of ecosystems far from equilibrium conditions [20].…”

Assessing most relevant factors to simulate current annual increments of beech forests in Italy

“…CAI is particularly overestimated for Val Cervara (7.79 vs. 1.41 m 3 ha -1 ), which is the less dense and oldest stand (see Tab. 2). This leads to a relatively high overall RMSE (2.57 m 3 ha Both curves are relative to BIOME-BGC CAI modeling at equilibrium conditions and are derived from Maselli et al (2009a) and Chiesi et al (2012), respectively; in the latter case a stem volume lower than the potential maximum is considered (see text for details). ).…”

“…As fully explained by Chiesi et al (2012), applying the above equation leads to modify the relationship between photosynthesis and autotrophic respiration in an age-dependent way. Consequently, for a certain woody biomass, tree aging has an inhibiting effect on the predicted CAI.…”

“…4 (see Chiesi et al 2012 for details). In the first case, a general growth curve was calibrated by statistically reproducing the average of all available reference CAIs derived from dendrochronological measurements with the exclusion of the last 5 years; this allowed an approximate independence of the calibration and validation phases.…”

Optimized Application of Biome‐BGC for Modeling the Daily GPP of Natural Vegetation Over Peninsular Spain

“…Several applications of optimized PEMs have been carried out locally and regionally in Mediterranean areas (Gilabert et al, 2015Maselli, Chiesi, et al, 2009;Sanchez-Ruiz et al, 2017) reporting improvements in the estimation accuracy of gross primary production (GPP) with respect to global PEMs such as MOD17 (Heinsch et al, 2006;Running & Zhao, 2015) or C-Fix (Veroustraete et al, 2002). On the other hand, ecosystem process models, such as Biome-BGC (Running & Hunt, 1993;White et al, 2000), are able to simulate the main vegetation processes and have been successfully applied in Mediterranean areas (Chiesi et al, 2007(Chiesi et al, , 2012Maselli, Papale, et al, 2009). However, they need a rather high amount of inputs that can be divided into drivers (meteorological time series and site data) and parameters (referring to ecophysiological data).…”