Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the latter being used to build plant tissues and synthesize non-structural and ...secondary compounds. Waring et al. (1998; Net primary production of forests: a constant fraction of gross primary production? Tree Physiol 18:129-134) suggested that a NPP:GPP ratio of 0.47 ± 0.04 (SD) is universal across biomes, tree species and stand ages. Representing NPP in models as a fixed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since the Waring et al. paper. Research has confirmed the existence of pervasive acclimation mechanisms that tend to stabilize the NPP:GPP ratio and indicates that Ra should not be modelled independently of GPP. Nonetheless, studies indicate that the value of this ratio is influenced by environmental factors, stand age and management. The average NPP:GPP ratio in over 200 studies, representing different biomes, species and forest stand ages, was found to be 0.46, consistent with the central value that Waring et al. proposed but with a much larger standard deviation (±0.12) and a total range (0.22-0.79) that is too large to be disregarded.
Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or-more generally-for the production of organic ...matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings-FPE declining with age-are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
Scientific community and policy-makers share the common interest in identifying and evaluating potential impacts of climate change on ecosystems, relying mainly on probabilistic methods of exploring ...the risks. In this perspective, the concept of ensemble forecasting makes possible to handle uncertainties associated with climate risk analysis by focusing on a range of potential or probable impact scenarios rather than actualizing a single case. In this paper, an ensemble of simulations based on the Lund-Potsdam-Jena (LPJ) model was used to investigate the uncertainty upon predictions of the future Euro-Mediterranean vegetation distribution, carbon dynamics, and water budget. Twenty simulations from past to future were based on the combination of different climate inputs, vegetation model parameterizations, and configurations. The evaluation of results combined the separate deterministic future projections from the LPJ model into a single probabilistic projection, associating a likelihood degree in accordance with the most recent Intergovernmental Panel on Climate Change terminology. Results projected a general critical situation in terms of water availability, made more serious if considering that also the occurrence of extreme-related events, e.g., fires, is expected to become more frequent as favored by more recurrent drought episodes. Although more uncomfortable climate conditions were projected for vegetation, net primary production (NPP) was predicted to increase due to the potential enrichment of CO
2
in atmosphere and its fertilization effects on vegetation. The combination of rising NPP and fire frequency may shape the carbon cycle components, as the carbon losses by fire also were projected to increase.
Mast seeding is one of the most intriguing reproductive traits in nature. Despite its potential drawbacks in terms of fitness, the widespread existence of this phenomenon suggests that it should have ...evolutionary advantages under certain circumstances. Using a global dataset of seed production time series for 219 plant species from all of the continents, we tested whether masting behaviour appears predominantly in species with low foliar nitrogen and phosphorus concentrations when controlling for local climate and productivity. Here, we show that masting intensity is higher in species with low foliar N and P concentrations, and especially in those with imbalanced N/P ratios, and that the evolutionary history of masting behaviour has been linked to that of nutrient economy. Our results support the hypothesis that masting is stronger in species growing under limiting conditions and suggest that this reproductive behaviour might have evolved as an adaptation to nutrient limitations and imbalances.
ABSTRACTProcess-based Forest Models (PBFMs) offer the possibility to capture important spatial and temporal patterns of carbon fluxes and stocks in forests. Yet, their predictive capacity should be ...demonstrated not only at the stand-level but also in the context of broad spatial and temporal heterogeneity. We apply a stand scale PBFM (3D-CMCC-FEM) in a spatially explicit manner at 1 km resolution in southern Italy. We developed a methodology to initialize the model that includes information derived from the integration of Remote Sensing (RS) and the National Forest Inventory (NFI) data and regional forest maps to characterize structural features of the main forest species. Gross primary production (GPP) is simulated over 2005–2019 period and the model predictive capability of the model in simulating GPP is evaluated both aggregated as at species-level through multiple independent data sources based on different nature RS-based products. We show that the model is able to reproduce most of the spatial (~2800 km2) and temporal (32 years in total) patterns of the observed GPP at both seasonal, annual and interannual time scales, even at the species-level. These promising results open the possibility of confindently applying the 3D-CMCC-FEM to investigate the forests’ behaviour under climate and environmental variability over large areas across highly variable ecological and bio-geographical heterogeneity of the Mediterranean region.
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 ...FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration schemes, was implemented in this new daily version. Model ability in reproducing timing and magnitude of daily and monthly GPP fluctuations is validated at intra-annual and inter-annual scale, including extreme anomalous seasons. With the purpose to test the 3D-CMCC FEM applicability over Europe without a site-related calibration, the model has been deliberately parametrized with a single set of species-specific parametrizations for each forest ecosystem. The model consistently reproduces both in timing and in magnitude daily and monthly GPP variability across all sites, with the exception of the two Mediterranean sites. We find that 3D-CMCC FEM tends to better simulate the timing of inter-annual anomalies than their magnitude within measurements' uncertainty. In six of eight sites where data are available, the model well reproduces the 2003 summer drought event. Finally, for three sites we evaluate whether a more accurate representation of forest structural characteristics (i.e. cohorts, forest layers) and species composition can improve model results. In two of the three sites results reveal that model slightly increases its performances although, statistically speaking, not in a relevant way.
Vegetation phenology and its variability have substantial influence on land‐atmosphere interaction, and changes in growing season length are additional indicators of climate change impacts on ...ecosystems. For these reasons, global land surface models are routinely evaluated in order to assess their ability to reproduce the observed phenological variability. In this work, we present a new approach that integrates a wider spectrum of growing season modes, in order to better describe the observed variability in vegetation growing season onset and offset, as well as assess the ability of state‐of‐the‐art land surface models to capture this variability at the global scale. The method is applied to the Community Land Model version 4.5 (CLM4.5) simulations and LAI3g satellite observation. The comparison between data and model outputs shows that CLM4.5 is capable of reproducing the growing season features in the Northern Hemisphere midlatitude and high latitude, but also displays its limitations in areas where water availability acts as the main driver of vegetation phenological activity. Besides, the new approach allows evaluating land surface models in capturing multigrowing‐season phenology. In this regard, CLM4.5 proves its ability in reproducing the two‐growing‐season cycles in the Horn of Africa. In general, the new methodology expands the area of analysis from northern midlatitude and high latitude to the global continental areas and allows to assess the vegetation response to the ongoing climate change in a larger variety of ecosystems, ranging from semiarid regions to rain forests, passing through temperate deciduous and boreal evergreen forests.
Key Points
A new phenology analysis method able to validate land surface model at global scale is presented
Satellite observation is used as a benchmark for the evaluation of Community Land Model version 4.5
The Mediterranean basin is one of the most varied areas worldwide in terms of biodiversity and species richness due to its climatic and geomorphological features, and it is characterized by ...multi-faceted habitats where forests play a crucial role. Nowadays, the geographic distribution of forest species is well known and multiple geographic datasets are available with different spatial details. However, protection and conservation strategies need more specific information to identify areas with high conservation priority or more vulnerable to the ongoing environmental change (“hot spots”). To this purpose, tree species distribution data were investigated through hot spot analysis using Geographic Information Systems. The analysis was carried out on presence data of ten relevant forest tree species/classes across Mediterranean Europe. By combining spatial analysis and spatial statistics, we identified high and very high hot spot areas for the selected species/classes, which were validated by assessing their biological significance. Given the sub-continental extent of the study, a multiple scale approach was applied ranging from regional, sub-regional to local scale, coherently with the potential multi-level and multi-sector users of similar data and tools. Our results confirm the feasibility of the approach used to increase the quality and quantity of information achievable from available forest distribution datasets. The hot spot maps obtained are a useful support for further spatial evaluations, and may help environmental decision makers to identify priority areas for forest protection and conservation.
This review is a follow-up to the first meeting of the Forest modeling working group (FMWG) of the Italian Society of Silviculture and Forest Ecology (SISEF), held in December 2009. 18 talks were ...delivered to an audience of 40 researchers. We review the state of the art of forest ecosystem modeling in Italy, highlight findings from Italian research groups, and summarize relevant issues. Developing on the discussion session of the meeting, we indicate current research gaps and future challenges for modelers, forest ecologists and foresters alike, with a special emphasis on model validation, data availability, and communication between researchers and managers.
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