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In the mid-latitudes, climate change is characterized by a shift towards more persistent precipitation regimes, i.e. longer periods of both drought and precipitation. The effect of such a shift on a grass-legume grassland was simulated in a 480-day field mesocosm experiment. Treatments of the gradient design differed in the length of alternating dry/wet periods of 1, 3, 6, 10, 15, 20, 30, and 60 days, either starting with a dry or a wet period, resulting in 16 different treatments. All treatments received the same total amount of water, i.e., all dry periods were alternated with wet periods of equivalent duration and all treatments finished having received an even number of periods. Each mesocosm was planted with 12 common grassland species varying in traits (grasses/forbs/legumes). Plant survival, diversity and aboveground biomass production were monitored regularly throughout the experiment. Microbial diversity was investigated after 60 and 120 days of experiment. Soil samples from the beginning and the end of the experiment were analyzed for root biomass, organic carbon, nitrogen, bulk density, soil water retention, pore size distribution, microbial biomass, basal respiration, nematodes, mesofauna and macrofauna. Hydrophobicity and infiltration was measured at the end of the experiment. We hypothesized that with more persistent weather, plant and soil biodiversity and functioning would become exponentially impaired and that this would occur at different tipping points for different ecosystem components.Plant diversity decreased as expected with increased weather persistence, mostly due to loss of forbs and N-fixers, with a tipping point around a blocking duration of 20 days after the end of the first growing season (120 days). These initial diversity losses could be traced to the timing and intensity of the preceding dry periods. By the end of the experiment (480 days), species richness showed a more linear response pattern, suggesting disappearance of the initial timing & tipping point effects, yet this may in part be attributed to preclusion of non-native colonization throughout the experiment. Plant productivity first followed a similar but less steep decline, possibly because reduced water availability was partly compensated by greater nutrient supply rate observed after longer droughts. Later, productivity overall decreased especially in grasses and evened out possibly reflecting the cumulative nutrient depletion associated with previous harvests, nutrient leaching and/or microbial/plant immobilization or higher plant density. However, the negative response of the N-fixer/grass production ratio to weather persistence became even more pronounced. After 120 days, microbial biomass was affected negatively by the 60-day treatment with a tendency of fungal biomass and F:B ratio to peak under intermediate weather persistence. Bacterial alpha diversity reacted negatively to persistent weather after 60 days within dry start treatments with tipping point around 10 days, but the trend was opposite after 120 days in both wet and dry treatments. Fungal beta diversity (community dissimilarity) was also positively influenced by more persistent weather.Furthermore we found that with longer drought, studied soils became increasingly hydrophobic and this reduced initial infiltration rates. We discuss how this effect could exacerbate drought stress as well as increase erosion risk in sloping grasslands.

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups’ biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils., This article is based upon work from COST Actions FP1305 (BioLink) and ES1406 (KEYSOM), supported by COST (European Cooperation in Science and Technology), and their Short Term Scientific Mission (STSM) programs. Omar Flores’ work was funded by FPU PhD grant program of the Spanish Ministry of Science, Innovation and Universities. Jorge Curiel Yuste received funding from the Spanish Ministry of Economy and Competitiveness (MINECO) under projects IBERYCA (CGL2017-84723-P) and the BC3 María de Maeztu excellence accreditation (MDM-2017-0714). Jorge Curiel Yuste also received funding from the Basque Government through the BERC 2018-2021 program., We also acknowledge institutional support from the Unit of Information Resources for Research at the Unit of Information Resources for Research at the "Consejo Superior de Investigaciones Científicas" (CSIC) for the article-processing charges contribution.

Quantifying the output uncertainty and tracking down its origins is key to interpreting the results of modelling studies. We performed such an uncertainty analysis on the predictions of forest growth and yield under climate change. We specifically focused on the effect of the interannual climate variability. For that, the climate years in the model input (daily resolution) were randomly shuffled within each 5-year period. In total, 540 simulations (10 parameter sets, nine climate shuffles, three global climate models, and two mitigation scenarios) were made for one growing cycle (80 years) of a Scots pine (Pinus sylvestris L.) forest growing in Peitz, Germany. Our results show that, besides the important effect of the parameter set, the random order of climate years can significantly change results such as basal area and produced volume, as well as the response of these to climate change. We stress that the effect of weather variability should be included in the design of impact model ensembles and in the accompanying uncertainty analysis. We further suggest presenting model results as likelihoods to allow risk assessment. For example, in our study, the likelihood of a decrease in basal area of >10% with no mitigation was 20.4%, whereas the likelihood of an increase >10% was 34.4%.

Altres ajuts: COST Actions BIOLINK (FP1305) and KEYSOM (ES 1406). Jorge Curiel Yuste received funding by the Basque Government through the BERC 2018-2021 program. The relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale.

Many studies have shown the importance of ectomycorrhizal fungi (EM) in forests both for nutrient availability and for carbon (C) and nutrient cycling in the soil. Yet so far they are not incorporated in forest ecosystem growth and yield models. Recent research suggests phosphorus (P) shortage could be a major constraints to forest productivity in the future. For a realistic simulation of future forest ecosystem functioning, inclusion of detailed soil P cycling and the trees-EM interaction is necessary. We developed a full ecosystem P model that simulates P uptake by roots and EM, allocation within trees, physiological deficiency effects on C assimilation and allocation, release through litter decomposition, coupled with water, C and nitrogen (N) fluxes accounted for in the mechanistic forest stand model ANAFORE. Our results confirm the importance of incorporating EM in forest ecosystem models and suggest that the lack of incorporation of P in models may result in an under- or overestimation of forest growth. This new model has the potential of being used to assess the response of trees and/or stands to nutrient availability under different climate and management scenarios. With the current parameterization it is functional as a scientific research tool to investigate hypotheses.

For a sustainable future, we must sustainably manage not only the human/industrial system but also ecosystems. To achieve the latter goal, we need to predict the responses of ecosystems and their provided services to management practices under changing environmental conditions via ecosystem models and use tools to compare the estimated provided services between the different scenarios. However, scientific articles have covered a limited amount of estimated ecosystem services and have used tools to aggregate services that contain a significant amount of subjective aspects and that represent the final result in a non-tangible unit such as 'points'. To resolve these matters, this study quantifies the environmental impact (on human health, natural systems and natural resources) in physical units and uses an ecosystem service valuation based on monetary values (including ecosystem disservices with associated negative monetary values). More specifically, the paper also focuses on the assessment of ecosystem services related to pollutant removal/generation flows, accounting for the inflow of eutrophying nitrogen (N) when assessing the effect of N leached to groundwater. Regarding water use/provisioning, evapotranspiration is alternatively considered a disservice because it implies a loss of (potential) groundwater. These approaches and improvements, relevant to all ecosystems, are demonstrated using a Scots pine stand from 2010 to 2089 for a combination of three environmental change and three management scenarios. The environmental change scenarios considered interannual climate variability trends and included alterations in temperature, precipitation, nitrogen deposition, wind speed, Particulate matter (PM) concentration and CO2 concentration. The addressed flows/ecosystem services, including disservices, are as follows: particulate matter removal, freshwater loss, CO2 sequestration, wood production, NOx emissions, NH3 uptake and nitrogen pollution/removal. The monetary ecosystem service valuation yields a total average estimate of 361-1242 euro ha(-1) yr(-1). PM2.5 (

Understanding the drivers of net ecosystem exchange of carbon (NEE) between forests and the atmosphere is crucial for the prediction of future global carbon dynamics. We therefore analyzed the long-term (1999–2014) ecosystem carbon fluxes of a mixed coniferous/deciduous forest (Brasschaat forest) in the Campine ecoregion of Belgium. The carbon uptake of this forest increased over the 16-year study period. By consecutively performing time series decomposition and the statistical technique of random forests, the correlative strength between multiple meteorological drivers, tropospheric pollutants and biotic indices with NEE was quantified at different time scales: i.e., long-term, seasonal and weekly, and separately for day- and nighttime NEE fluxes. The drivers that were most correlated with the trend in carbon sink capacity were the increasing atmospheric CO2 level and soil recovery from acidification. The radiation-saturated carbon uptake increased remarkably and explained much of the long-term variability of daytime NEE. When the long-term and seasonal variation were extracted the remaining weekly variation in daytime NEE was most strongly correlated with variation in the incoming radiation and cloudiness, and to a lesser extent by variation in vapor pressure deficit. In contrast to daytime NEE, nighttime NEE did not show a steady trend over time, but fluctuated, peaking in 1999 and in 2011. The long-term variability in nighttime NEE was most strongly correlated with the groundwater table depth. Air temperature was highly correlated to the seasonal as well as to the remaining weekly variation, i.e., after removal of the long-term and seasonal variability, in nighttime NEE. Biotic drivers (e.g., quantum yield and radiation-saturated carbon uptake) explained less of the variation in NEE on a seasonal and short-term scale, but were more important at the long term.

Although ectomycorrhizal fungi play an important role in forest ecosystem functioning, they are usually not included in forest growth or ecosystem models. Simulation is hampered by two main issues: a lack of understanding of the ecological functioning of the ectomycorrhizal fungi and a lack of adequate basic data for parameterization and validation. Concerning these issues, much progress has been made during the past few years, but this information has not found its way into the forest and soil models. In this paper, state-of-the-art insight into ectomycorrhizal functioning and basic values are described in a manner transparent to nonspecialists and modelers, together with the existing models and model strategies. As such, this paper can be the starting point and the motivator to include ectomycorrhizal fungi into existing soil and forest ecosystem models.

This study reports on 3.5 years (2008-2011) of actual evapotranspiration (ET) measurements of two short-rotation poplar coppice (SRC) plantations in comparison with two reference grass covers (clipped turf grass and permanent grassland) in a rain-fed area of the Czech-Moravian Highlands in the Czech Republic. The Bowen ratio/energy balance method (BREB) was used to measure the ET of all the four investigated covers. Although the ET of the SRCs sometimes exceeded that of grass vegetation or the reference evapotranspiration (ET0) on an hourly, daily or monthly time scale, it was always lower over an entire annual cycle. The cumulative annual ET of the SRCs ranged from 344 to 549 mm year(-1), whereas that of the turf grass ranged from 561 to 573 mm year(-1), and the ET of the grassland reached up to 619 mm year(-1). The wide range of the annual ET totals for the SRCs was determined mainly by the different rotation periods and ages of the stands, along with the leaf area index (LAI), the state of the canopy closure, and tree heights. The lowest annual ET (344 mm) was observed during the 1st year of the 2nd rotation (following the winter harvest) in 2010. During that year, the SRC regrowth started only after mid-June, and the maximum LAI of the canopy, which was approximately 2 m in height and was not completely closed, reached 3.7. In contrast, in the case of a mature stand approximately 12 m in height in 2009, i.e., the 8th year of the 1st rotation, the maximum canopy LAI reached 7.5, and the annual ET reached its highest observed value (549 mm). The leaf area duration of the SRCs was always lower than that of the grass covers, and this seemed to be the main reason for the significantly lower annual ET totals of the SRCs. The absolute maximum daily ET of 6.3 mm day(-1) was achieved by the SRC in July 2011 when the stand was in the 2nd year of the 2nd rotation cycle. The highest daily ET of the grass covers (5.9 mm day(-1)) was reached by turf grass in June 2011. The maximum monthly ET occurred in July 2009 when the weather was wet and relatively warm; the ET was identical for the SRCs and the turf grass, reaching 107 mm month(-1), just slightly lower than the ET0 (109 mm month(-1)). These results are in the middle range of ET values from 21 recent studies on poplar and willow cultures. The results of this study indicate that conversion of arable land into poplar SRCs instead of grasslands does not result in significant differences in ET of the agricultural landscape. (C) 2013 Elsevier B.V. All rights reserved.

The purpose of this study was to find the ecological factors that most affect height growth of Norway spruce (Picea abies Karst.) over the Western Carpathians. The specific aim was to find climate and soil parameters which are influenced by climate change and can thus be used to make a forest growth model more sensitive to climate. From the results, a regression model was built which can predict top height growth of Norway spruce from ecological parameters. Data collected on 201 plots established within National Forest Inventory of Slovakia were used. The plots selected for the study were distributed almost over the whole Western Carpathians. Mean height of the 20 % largest spruce trees was used as dependent variable. From all investigated ecological factors, the growing season length explained as the number of days with temperature over 5 A degrees C, the carbon-to-nitrogen ratio and soil acidity were shown to have the major impact on top height growth of Norway spruce. Finally, 76 % of total variability in top height was explained by the mentioned site variables. To obtain a user-friendly output, a probability matrix was developed showing the likelihood of a discrete site index to occur on different combinations of site factors. Moreover, raster maps showing the site index of spruce and its probability distribution were developed.

Forest management requires prediction of forest growth, but there is no general agreement about which models best predict growth, how to quantify model parameters, and how to assess the uncertainty of model predictions. In this paper, we show how Bayesian calibration (BC), Bayesian model comparison (BMC) and Bayesian model averaging (BMA) can help address these issues. We used six models, ranging from simple parameter-sparse models to complex process-based models: 3PG, 4C, ANAFORE, BASFOR, BRIDGING and FORMIND. For each model, the initial degree of uncertainty about parameter values was expressed in a prior probability distribution. Inventory data for Scots pine on tree height and diameter, with estimates of measurement uncertainty, were assembled for twelve sites, from four countries: Austria, Belgium, Estonia and Finland. From each country, we used data from two sites of the National Forest Inventories (NFIs), and one Permanent Sample Plot (PSP). The models were calibrated using the NFI-data and tested against the PSP-data. Calibration was done both per country and for all countries simultaneously, thus yielding country-specific and generic parameter distributions. We assessed model performance by sampling from prior and posterior distributions and comparing the growth predictions of these samples to the observations at the PSPs. We found that BC reduced uncertainties strongly in all but the most complex model. Surprisingly, country-specific BC did not lead to clearly better within-country predictions than generic BC. BMC identified the BRIDGING model, which is of intermediate complexity, as the most plausible model before calibration, with 4C taking its place after calibration. In this BMC, model plausibility was quantified as the relative probability of a model being correct given the information in the PSP-data. We discuss how the method of model initialisation affects model performance. Finally, we show how BMA affords a robust way of predicting forest growth that accounts for both parametric and model structural uncertainty. (C) 2012 Elsevier B.V. All rights reserved.

The contribution of selected sources of uncertainty to the total variance of model simulation results of stem biomass increment calculated from annual stem biomass predictions of European beech (Fagus sylvatica L.) was quantified. Sources of uncertainty were defined as the selected variables that influence the total variance of the model results. Simulations were made: (i) for ten regional climate models (RCMs) based on the IPCC scenario A1B and providing an ensemble of climate projections up to 2100; (ii) with two forest model types (FMTYPEs); (iii) for four forest management intensities (MANFORs); and (iv) for three time windows (TIMEWINDs), each spanning 15 years, starting in 2019, in 2049 and in 2079. Both models, the empirical SIBYLA model and the process-based ANAFORE model, were calibrated using experimental tree growth data from four plots in central Slovakia between 1989 and 2003. Three of these plots, representing the four MANFORs, were subject to different prior intensities of thinning while one was left untouched as a control. The FMTYPE explained most of the total variance in the simulation results (39.9%), followed by MANFOR (i.e. thinning intensity; 22.2%) and TIMEWIND (12.0%), while the effect of RCMs on model uncertainty was limited (

• Increasing atmospheric concentrations of phytotoxic ozone (O(3) ) can constrain growth and carbon sink strength of forest trees, potentially exacerbating global radiative forcing. Despite progress in the conceptual understanding of the impact of O(3) on plants, it is still difficult to detect response patterns at the leaf level. • Here, we employed principal component analysis (PCA) to analyse a database containing physiological leaf-level parameters of 60-yr-old Fagus sylvatica (European beech) trees. Data were collected over two climatically contrasting years under ambient and twice-ambient O(3) regimes in a free-air forest environment. • The first principal component (PC1) of the PCA was consistently responsive to O(3) and crown position within the trees over both years. Only a few of the original parameters showed an O(3) effect. PC1 was related to parameters indicative of oxidative stress signalling and changes in carbohydrate metabolism. PC1 correlated with cumulative O(3) uptake over preceding days. • PC1 represents an O(3) -responsive multivariate pattern detectable in the absence of consistently measurable O(3) effects on individual leaf-level parameters. An underlying effect of O(3) on physiological processes is indicated, providing experimental confirmation of theoretical O(3) response patterns suggested previously.

Six photosynthesis-dependent stomatal models were tested and compared against twig cuvette gas exchange data for adult common beech ( Fagus sylvatica L.). The models differed in the use of (1) either leaf surface CO 2 concentration ( C s ) or leaf intercellular CO 2 concentration ( C i ), and of (2) either measured environmental humidity variables or a crudely calculated leaf water potential to simulate the effect of drought stress on stomatal conductance. The models applying C s performed slightly better than the models applying C i . The models based on environmental humidity variables performed distinctly better than the models applying a calculated leaf water potential. Several explanations for the observed performance differences between models applying C s or C i were brought forward and discussed.

A stand-scale forest model has been developed that dynamically simulates, besides carbon (C) and water (H2O) fluxes, wood tissue development from physiological principles. The forest stand is described as consisting of trees of different size cohorts (for example, dominant, co-dominant and suppressed trees), either of the same or of different species (deciduous or coniferous). Half-hourly C and H2O fluxes are modeled at the leaf, tree and stand level. In addition to total growth and yield, the model simulates the daily evolution of tracheid or vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition and density are calculated. Simulation of the labile C stored in the living tissues allows for simulation of trans-seasonal and trans-yearly effects, and improved simulations of long-term effects of environmental stresses on growth. A sensitivity analysis was performed to indicate the main parameters influencing simulated stem growth and wood quality at the tree and stand level. Case studies were performed for a temperate pine forest to illustrate the main model functioning and, more in particular, the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for simultaneous analyses of wood quality development and forest ecosystem functioning.

We present a mechanistic model of wood tissue development in response to changes in competition, management and climate. The model is based on a refinement of the pipe theory, where the constant ratio between sapwood and leaf area (pipe theory) is replaced by a ratio between pipe conductivity and leaf area. Simulated pipe conductivity changes with age, stand density and climate in response to changes in allocation or pipe radius, or both. The central equation of the model, which calculates the ratio of carbon (C) allocated to leaves and pipes, can be parameterized to describe the contrasting stem conductivity behavior of different tree species: from constant stem conductivity (functional homeostasis hypothesis) to height-related reduction in stem conductivity with age (hydraulic limitation hypothesis). The model simulates the daily growth of pipes (vessels or tracheids), fibers and parenchyma as well as vessel size and simulates the wood density profile and the earlywood to latewood ratio from these data. Initial runs indicate the model yields realistic seasonal changes in pipe radius (decreasing pipe radius from spring to autumn) and wood density, as well as realistic differences associated with the competitive status of trees (denser wood in suppressed trees).

To compare the benefits for carbon (C) sequestration of afforestation with a multifunctional oak–beech forest vs. a poplar short-rotation coppice (SRC), model simulations were run through a serial linkage of a mechanistic model and an accounting model. The process model SECRETS (Stand to Ecosystem CaRbon and EvapoTranspiration Simulator) was used to predict growth, C allocation and soil C. The output from SECRETS was used as an input for the C accounting model GORCAM (Graz Oak Ridge Carbon Accounting Model) yielding data on C sequestration in wood products, substitution of wood fuel for fossil fuel and total CO2 emission reduction. Such C accounting based on a process model enables a more realistic calculation of forest growth, litter decomposition and soil processes. Moreover, it allows simulating the influence of climate change on the C budget. Net primary production of an oak–beech forest is low, a stable 2.5 t C ha−1 yr−1 after 150 years, compared to 6.2 t C ha−1 yr−1 for a SRC plantation. But while the yield from the SRC poplar is used as fuel and thus returns quickly to the atmosphere, the yield from the oak-beech forest is used in long-lasting wood products. The total C pool in the mixed forest (living biomass, wood products and soil) after 150 years amounts to 324 t C ha−1 compared to 162 in the poplar coppice. However, when account is taken of the energy substitution, coppice culture reduces emissions with 24.3–29.3 t CO2 ha−1 yr−1 while the mixed forest reduces only 6.2–7.1 t CO2 ha−1 yr−1. These results demonstrate the added value of combining detailed process models with C-accounting models to improve the predictive capacity of model simulations.

Airborne fine particulate matter (PM) is responsible for the most severe health effects induced by air pollution in Europe. Vegetation, and forests in particular, can play a role in mitigating this pollution since they have a large surface area to filter PM out of the air. Many studies have solely focused on dry deposition of PM onto the tree surface, but deposited PM can be resuspended to the air or may be washed off by precipitation dripping from the plants to the soil. It is only the latter process that represents a net-removal from the atmosphere. To quantify this removal all these processes should be accounted for, which is the case in our modeling framework. Practically, a multilayered PM removal model for forest canopies is developed. In addition, the framework has been integrated into an existing forest growth model in order to account for changes in PM removal efficiency during forest growth. A case study was performed on a Scots pine stand in Belgium (Europe), resulting for 2010 in a dry deposition of 31 kg PM2.5 (PM < 2.5 ?m) ha(-1) yr(-1) from which 76% was resuspended and 24% washed off. For different future emission reduction scenarios from 2010 to 2030, with altering PM2.5 air concentration, the avoided health costs due to PM2.5 removal was estimated to range from 915 to 1075 euro ha(-1) yr(-1). The presented model could even be used to predict nutrient input via particulate matter though further research is needed to improve and better validate the model.

Recent temperature increases have elicited strong phenological shifts in temperate tree species, with subsequent effects on photosynthesis. Here, we assess the impact of advanced leaf flushing in a winter warming experiment on the current year's senescence and next year's leaf flushing dates in two common tree species: Quercus robur L. and Fagus sylvatica L. Results suggest that earlier leaf flushing translated into earlier senescence, thereby partially offsetting the lengthening of the growing season. Moreover, saplings that were warmed in winter-spring 2009-2010 still exhibited earlier leaf flushing in 2011, even though the saplings had been exposed to similar ambient conditions for almost 1 y. Interestingly, for both species similar trends were found in mature trees using a long-term series of phenological records gathered from various locations in Europe. We hypothesize that this long-term legacy effect is related to an advancement of the endormancy phase (chilling phase) in response to the earlier autumnal senescence. Given the importance of phenology in plant and ecosystem functioning, and the prediction of more frequent extremely warm winters, our observations and postulated underlying mechanisms should be tested in other species.

A greenhouse experiment was conducted to investigate whether small differences in UV-B irradiance would lead to changes in competition between cocksfoot (Dactylis glomerata L. cv. Athos) and white clover (Trifolium repens L. cv. Mervi). Plants were grown in greenhouses covered with different thicknesses of UV-transmittant plexi (3 and 5 mm) resulting in 82 % and 88 % of ambient UV-B radiation. Aboveground biomass was harvested at 4-week intervals and the vertical distribution of biomass, leaf thickness and specific leaf area were determined. Tillering, stubble and root biomass and crop height were also measured. There was only one significant effect: at 88 % of ambient UV-B radiation a larger fraction of the biomass was present in the lower layers and a smaller fraction was present in the upper layers.

The effects of changes in solar UV-B on the growth and pigmentation of six grass species from cold-temperate grasslands (Lolium perenne, Lolium multiflorum, Festuca arundinacea, Festuca rubra, Phleum pratense and Dactylis glomerata) in spring and summer were studied. The grasses were grown in greenhouses with different foils, resulting in three treatments: no UV-B, 80% of ambient and 90% of ambient UV-BBE.(biologically effective UV-B). The results indicated important effects of ambient UV-B levels on grass, but the different species reacted in very different ways. Both morphology and biomass production were influenced by UV-B in some species. However, changes in biomass production did not necessarily occur within the same species as changes in morphology. The grasses were more sensitive in summer. Overall, only F. rubra was positively influenced by UV-B under all circumstances. The biomass of D. glomerata and L. perenne was reduced by UV-B in spring and summer. Morphological changes included reduced height and increased tillering. The sensitivity of the different species was partially explained by their ability to reduce their specific leaf area in response to UV-B. Only the more sensitive species showed increased production of protective pigments. Overall, there were important differences between the effect of a low level of UV-B, and the further increase in UV-B, indicating that several mechanisms are operating at different light levels.

The penetration of natural and artificial UV-BBE (Biologically Effective UV-B, Caldwell 1971) and PAR (400–700 nm) in a grass canopy with increasing LAI was followed during 2 months. Overall, the transmission of UV-BBE sunlight is significantly higher than of PAR sunlight. This is mainly due to the higher proportion of diffuse light in the UV-B. Under cloudy conditions no difference between UV-BBE and PAR could be found. Sun angle and intensity of the radiation were less important in determining the penetration of light. Artificial light penetrates much more through the canopy, resulting in higher irradiation levels in the lower part of the canopy, but a lower UV-BBE/PAR ratio (since UV-B transmittance of the leaves is lower). The UV-BBE/PAR ratio reaching the leaves was influenced by LAI, sun angle, percent diffuse light and leaf angle. The large differences in UV-BBE/PAR ratio per unit leaf area under natural and artificial light conditions are important in understanding the influence of UV-B on plants.

To evaluate the effect of different naturally occurring irradiation conditions on the sensitivity of rye (Secale cereale L.) to increased UV-B levels, plants were grown under eight different light treatments. In the control series (at ambient levels of UV-B), UV-B and visible light were decreased in parallel, resulting in four different total irradiation treatments with the same UV-B/photosynthetically active radiation (PAR) ratios. A second series with a 30% increase in UV-B irradiation at each PAR level was used to investigate the effect of UV-B under the varying total irradiance levels. The different total irradiance levels resulted in significant differences in total dry weight, specific leaf weight, photosynthesis-light response and pigment concentrations. A 30% increase in UV-B resulted in equal reductions in total dry weight (from 20.0 to 28.6%) and effective photosynthesis for all light levels. The accumulation of protective pigments in the leaves was stimulated by PAR and even more by UV-B, except at the highest UV-B irradiation, where a small decrease was noted. These results indicate that rye plants are able to adapt to changes in the natural light environment as long as the ratio UV-B/PAR is constant.

Habitat destruction is a key determinant of species extinction. Its principle components, habitat fragmentation and habitat loss, affect species persistence in landscapes, but few models have investigated how dispersal type and intraspecific competition (crowding effect) modulate this. If dispersal type or crowding changes extinction thresholds, then fragmentation and habitat loss might act differently on different species. Here we generate fragmented landscapes by varying the orthogonal neighbouring correlation between suitable and unsuitable habitat. We show that local dispersers undergo a strong negative impact of habitat fragmentation (lower occupancy of suitable sites), but only under severe habitat loss. In contrast, global dispersal eliminated fragmentation effects through random establishment. Both fragmentation and crowding effects enhanced the extinction risk of species that spread their seeds at close range, while long-range dispersers were not influenced. However, fragmentation improved the persistence of global dispersers that are highly sensitive to crowding, probably through reduced intraspecific competition. With respect to species conservation, our results suggest that random habitat destruction is a more serious threat to species persistence than clustered habitat destruction. Moreover, as species responses to habitat fragmentation depend on dispersal type and sensitivity to crowding, fragmented landscapes with different properties may accommodate different species.

Phenological events are sensitive to climate change, and a clear advancement of spring leaf phenology has been well documented. However, the observed phenological trends cannot be directly used to forecast future changes because the underlying mechanisms are still unclear. We conducted a two-year experimental warming experiment using one-meter-high saplings of birch (Betula pendula L), oak (Quercus robur L) and beech (Fagus sylvatica L.). The main objective of this study was to quantify the temperature sensitivity of leaf unfolding to six different warming levels. The results suggested that leaf unfolding dates were significantly advanced with warming for all species in both experimental years. However, different warming treatments elicited different leaf unfolding responses. At low and moderate warming (

Budburst phenology is a key driver of ecosystem structure and functioning, and it is sensitive to global change. Both cold winter temperatures (chilling) and spring warming (forcing) are important for budburst. Future climate warming is expected to have a contrasting effect on chilling and forcing, and subsequently to have a non-linear effect on budburst timing. To clarify the different effects of warming during chilling and forcing phases of budburst phenology in deciduous trees, (i) we conducted a temperature manipulation experiment, with separate winter and spring warming treatments on well irrigated and fertilized saplings of beech, birch and oak, and (ii) we analyzed the observations with five temperature-based budburst models (Thermal Time model, Parallel model, Sequential model, Alternating model, and Unified model). The results show that both winter warming and spring warming significantly advanced budburst date, with the combination of winter plus spring warming accelerating budburst most. As expected, all three species were more sensitive to spring warming than to winter warming. Although the different chilling requirement, the warming sensitivity was not significantly different among the studied species. Model evaluation showed that both one- and two- phase models (without and with chilling, respectively) are able to accurately predict budburst. For beech, the Sequential model reproduced budburst dates best. For oak and birch, both Sequential model and the Thermal Time model yielded good fit with the data but the latter was slightly better in case of high parameter uncertainty. However, for late-flushing species, the Sequential model is likely be the most appropriate to predict budburst data in a future warmer climate.

Phenology models are tools to analyze changes in the timing and duration of the growing season. During the past three decades different budburst models have been developed, but, so far, no consensus model has been found to accurately predict budburst date across different tree species. The aim of this study was to estimate the performance of six different temperature-driven models of leaf budburst (thermal time, thermal period fixed, sequential, parallel, alternating, unified) for four temperate tree species in Belgium (birch, chestnut, oak, beech). The models were parameterized using a Bayesian approach. The performance of these models was compared using Bayesian model comparison (BMC) and root mean square error (RMSE). Model comparison showed that the two models that do not include a calculation of chilling requirement were the best for the studied four tree species. The Sequential model (SM) was the third most plausible model for predicting budburst, having a higher probability to be correct than the other two-phase models combining a chilling phase with a forcing phase. This suggested that in our budburst observation dataset, the chilling requirement was probably always fulfilled, making the date of budburst controlled by forcing temperature. We cannot rule out that in warmer regions or future warmer conditions, chilling may become insufficient and a sequential pattern of chilling and forcing may become most appropriate to simulate budburst date. Parameter analysis showed that the last month prior to budburst had the greatest impact on determining the date of bud opening in the case of birch and chestnut, whereas the last 3 months were the main determinants for oak and beech, the two later flushing species. Validation showed that the models that fitted the parameterization data well had much poorer performance when tested with independent data. This indicates that other factors (e.g. photoperiod) might affect the budburst process and/or model parameterization (determining the sensitivity of budburst to temperature) substantially change between different localities. (C) 2012 Elsevier BM. All rights reserved.

Numerous phenology models developed to predict the budburst date of trees have been merged into one Unified model (Chuine, 2000, J. Theor. Biol. 207, 337347). In this study, we tested a simplified version of the Unified model (Unichill model) on six woody species. Budburst and temperature data were available for five sites across Belgium from 1957 to 1995. We calibrated the Unichill model using a Bayesian calibration procedure, which reduced the uncertainty of the parameter coefficients and quantified the prediction uncertainty. The model performance differed among species. For two species (chestnut and black locust), the model showed good performance when tested against independent data not used for calibration. For the four other species (beech, oak, birch, ash), the model performed poorly. Model performance improved substantially for most species when using site-specific parameter coefficients instead of across-site parameter coefficients. This suggested that budburst is influenced by local environment and/or genetic differences among populations. Chestnut, black locust and birch were found to be temperature-driven species, and we therefore analyzed the sensitivity of budburst date to forcing temperature in those three species. Model results showed that budburst advanced with increasing temperature for 13 days °C−1, which agreed with the observed trends. In synthesis, our results suggest that the Unichill model can be successfully applied to chestnut and black locust (with both across-site and site-specific calibration) and to birch (with site-specific calibration). For other species, temperature is not the only determinant of budburst and additional influencing factors will need to be included in the model.

Ground-level ozone (O3) has gained awareness as an agent of climate change. In this respect, key results are comprehended from a unique 8-year free-air O3-fumigation experiment, conducted on adult beech (Fagus sylvatica) at Kranzberg Forest (Germany). A novel canopy O3 exposure methodology was employed that allowed whole-tree assessment in situ under twice-ambient O3 levels. Elevated O3 significantly weakened the C sink strength of the treesoil system as evidenced by lowered photosynthesis and 44% reduction in whole-stem growth, but increased soil respiration. Associated effects in leaves and roots at the gene, cell and organ level varied from year to year, with drought being a crucial determinant of O3 responsiveness. Regarding adult individuals of a late-successional tree species, empirical proof is provided first time in relation to recent modelling predictions that enhanced ground-level O3 can substantially mitigate the C sequestration of forests in view of climate change. Empirical proof corroborates substantial mitigation of carbon sequestration in the treesoil system of a forest site under enhanced O3 impact for adult beech.

The purpose of this study was to expand an existing semi-mechanistic forest model, ANAFORE (ANAlysing Forest Ecosystems), to allow for the prediction of log quality and the accompanying uncertainty as influenced by climate and management. The forest stand is described as consisting of trees of different cohorts, either of the same or of different species (deciduous or coniferous). In addition to photosynthesis, transpiration, total growth and yield, the model simulates the daily evolution in vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition, knot formation and density are calculated. The new version presented here, includes the description of log quality, including red heart formation of beeches. A Bayesian optimisation routine for the species parameters was added to the stand model. From a given range of input parameters (prior), the model calculates an optimised range for the parameters (posterior) based on given output data, as well as an uncertainty on the predicted values. A case study was performed for Slovenian beech forests to illustrate the main model functioning and more in particular the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for analyzing wood quality development and forest ecosystem functioning in response to management, climate and stand characteristics. However, the Bayesian optimization showed that the remaining uncertainty on the input parameters for the chosen stand was very large, due to the large number of input parameters in comparison to the limited stand data.

There is a gap between the increased scientific understanding of carbon pools and fluxes at individual trees/stand and that of forested landscape with complex structures (i.e. variety of species, age classes, site characteristic and management practices). The question about how results generated from a simulated physiologically distinct individual(s)/stands grown at a particular location (scale) can be extrapolated (scaling) across a diverse population in time and space with diverse environments, has been troubling scientists for many years. Scale and scaling present three problems in common: (a) spatial heterogeneity, (b) non-linearity in response and (c) disturbance regimes. Scale, in particular, presents other three problems: (d) threshold scale for processes, (e) dominant processes with scales and (f) emerging properties of the system. Scaling presents problems with (g) feedbacks between plants and environment and (h) plant interactions. The present study proposes a modeling framework linking a process-based model SECRETS - to overcome some of the scale and scaling problems (a, b, c, d and g) - to a C accounting model GORCAM - to integrate the effects of C stock in wood products and from fossil fuel substitution. The capabilities of the modeling framework are tested against three theoretical complex forested landscapes that combine some of the five following scenarios: existing multifunctional forest under (1) actual and (2) changing environmental conditions, and afforestation of an agricultural area with (3) a new multifunctional forest or with (4) a short rotation coppice (poplar) or with (5) an agricultural crop (miscanthus) for bioenergy production. Forest reserves calculations are included for completeness of the landscape C balance and as reference. Results, on the one hand, suggest that the framework is able to simulate C sequestration and stock in ecosystem pools, wood products and fossil fuel substitution of the scenarios under actual environmental conditions. However, comparison of results under changing environmental conditions, against specific plant literature suggest SECRETS formulation must be improved with recent development in photosynthesis, stomatal conductance and N balances. On the other hand, results also suggest that under actual environmental conditions, the optimum landscape scenario to sequester C and avoid fossil emissions to the atmosphere is composed by existing multifunctional forest, reserves and afforestation with short rotation coppice for bioenergy production. © 2007 Springer Science+Business Media B.V.

Ozone affects adult trees significantly, but effects on stem growth are hard to prove and difficult to correlate with the primary sites of ozone damage at the leaf level. To simulate ozone effects in a mechanistic way, at a level relevant to forest stand growth, we developed a simple ozone damage and repair model (CASIROZ model) that can be implemented into mechanistic photosynthesis and growth models. The model needs to be parameterized with cuvette measurements on net photosynthesis and dark respiration. As the CASIROZ ozone sub-model calculates effects of the ozone flux, a reliable representation of stomatal conductance and therefore ozone uptake is necessary to allow implementation of the ozone sub-model. In this case study the ozone sub-model was used in the ANAFORE forest model to simulate gas exchange, growth, and allocation. A preliminary run for adult beech (Fagus sylvatica) under different ozone regimes at the Kranzberg forest site (Germany) was performed. The results indicate that the model is able to represent the measured effects of ozone adequately, and to distinguish between immediate and cumulative ozone effects. The results further help to understand ozone effects by distinguishing defence from damage and repair. Finally, the model can be used to extrapolate from the short-term results of the field study to long-term effects on tree growth. The preliminary simulations for the Kranzberg beech site show that, although ozone effects on yearly growth are variable and therefore insignificant when measured in the field, they could become significant at longer timescales (above 5 years, 5 % reduction in growth). The model offers a possible explanation for the discrepancy between the significant effects on photosynthesis (10 to 30 % reductions simulated), and the minor effects on growth. This appears to be the result of the strong competition and slow growth of the Kranzberg forest, and the importance of stored carbon for the adult beeches (by buffering effects on carbon gain). We finally conclude that inclusion of ozone effects into current forest growth and yield models can be an important improvement into their overall performance, especially when simulating younger and less dense forests.

Currently, the most important source of uncertainty in stomatal ozone flux (FO3) modelling is the stomatal conductance (g(st)) factor. Hence FO3 model accuracy will strongly depend on the g,t model being implemented. In this study the recently developed semi-empirical g(st) model of Dewar was coupled to the widely known biochemical photosynthesis (A(n)) model of Farquhar. The g(st) performance of this model combination was evaluated with a 4-month time series of beech (Fagus sylvatica L.) measurements. The g(st) model was hereto optimized in two steps to a 4-day and a 8-day period. A comparison between the modelled and measured g(st) to O-3 (g(stO3)) revealed a rather good overall performance (R-2 = 0.77). Errors between the model combination and the measurements are thought to be largely caused by a moderate performance of the A(n) model, due to poor parameterization. Two 2-day periods with distinctly differing soil and meteorological conditions were chosen to give a picture of the daily g, performance. Although instant relative differences between modelled and measured g(stO3) are sometimes high, the model combination is able to simulate the rough daily courses of g(stO3) and hence FO3 reasonably well. Further improvement on full parameterization of the g, model and a well-parameterized A, model to be linked to are needed to draw founded conclusions about its performance. Future efforts hereto are certainly justified since the model's mechanistic nature makes it a tool able to model g(st) variation in space and time, O-3 effects on g(st), and effective FO3.

A three-step methodology to assess the carbon sequestration and the environmental impact of afforestation projects in the framework of the Flexible Mechanisms of the Kyoto Protocol (Joint Implementation and Clean Development Mechanism) was developed and tested using a dataset collected from the Jonkershoek forest plantation, Western Cape, South Africa, which was established with Pinus radiata in former native fynbos vegetation and indigenous forest. The impact of a change in land use was evaluated for a multifunctional, a production and a non-conversion scenario. First, the carbon balance was modelled with GORCAM and was expressed as (1) C sequestration in tC ha−1 year−1 in soil, litter, and living biomass according to the rules of the first commitment period of the Kyoto Protocol, and (2) CO2 emission reductions in tC ha−1 year−1, which includes carbon sequestered in the above-mentioned pools and additionally in wood products, as well as emission reductions due to fossil fuel substitution. To estimate forest growth, three data sources were used: (1) inventory data, (2) growth simulation with a process-based model, and (3) yield tables. Second, the effects of land use change were assessed for different project scenarios using a method related to Life Cycle Assessment (LCA). The method uses 17 quantitative indicators to describe the impact of project activities on water, soil, vegetation cover and biodiversity. Indicator scores were calculated by comparing indicator values with reference values, estimated for the climax vegetation. The climax vegetation is the site-specific ecosystem phase with the highest exergy content and the highest exergy flow dissipation capacity. Third, the land use impact per functional unit of 1 tC sequestered was calculated by combining the results of step 1 and step 2. The average baselines to obtain carbon additionality are 476 tC ha−1 for indigenous forest and 32 tC ha−1 for fynbos. Results show that the influence of the growth assessment method on the magnitude of C sequestration and hence on the environmental impact per functional unit is large. When growth rate is assessed with the mechanistic model and with the yield table, it is overestimated in the early years and underestimated in the long term. The main conclusion of the scenario analysis is that the production forest scenario causes higher impacts per functional unit than the multifunctional scenario, but with the latter being less efficient in avoiding CO2 emissions. The proposed method to assess impacts on diverse components of the ecosystem is able to estimate the general tendency of the adverse and positive effects of each scenario. However, some indicators, more specifically about biodiversity and water balance, could be improved or reinterpreted in light of specific local data about threat to biodiversity and water status.

Land use, land use change and forestry (LULUCF) offer domestic and international opportunities to accomplish the targets set by the Kyoto Protocol. Design and selection of successful forestry projects are complex decision processes based on information of the carbon dioxide mitigation potential, the environmental impacts and the cost efficiency of selected scenarios. In this paper, a decision support framework to evaluate forestry scenarios for greenhouse gas emission reduction is presented and tested on five scenarios (existing and new multifunctional forest in Flanders, Belgium, bioenergy crop with short rotation poplar and with elephant grass in Flanders, Belgium, plantation forestry in the subtropics, and, conservation of tropical rainforest). The framework is organized as a serial connection of a carbon accounting module, an environmental impact module and an economic module. Modules include a combination of models and quantitative assessment procedures. In order to make scenarios comparable, the environmental and economic modules calculate their outputs on a functional unit basis of 1 t CO2 emission reduction. The framework is universally applicable and straightforward, transparent and quantitative. The level of data requirement is medium, but the application is fairly complex due to the interdisciplinary character of the tool. Further developments would require automated data flows between models and a user interface. Results of the test application showed that the only attractive domestic option is the establishment of new multifunctional forests. This scenario even yields a net benefit because it replaces the generally loss-making agriculture and, in addition, it provides other environmental and recreational benefits. The establishment of bioenergy plantations is a very efficient way of reducing CO2 emissions as far as land occupation and environmental impacts per functional unit are concerned. However, it also turns out to be a very expensive option. Plantation forestry in the tropics is advantageous when evaluated over longer periods of time. Conservation of tropical forest is not eligible as a clean development mechanism (CDM) project, although it would be economically attractive for Flanders since the cost per tonne CO2 emission reduction is close to the expected world market price. This option is thus promising for the voluntary market and for future commitment periods of the Kyoto Protocol.

The process model SECRETS was adapted to simulate coppice growth of poplar. The effects of soil type, irrigation, nitrogen fertilization and rotation cycle on growth and yield were studied. Simulated average production on an agricultural soil was 12.4 t ha −1 year −1 . Poplar growth was strongly reduced on sandy soils ( 6 t ha −1 year −1 ). Irrigation increased yield on all soil types by 25% while fertilization increased yield by 26%. The highest yield was simulated for the combined irrigation/fertilization ( 22.45 t ha −1 year −1 ). Length of rotation cycle greatly influenced yield; optimal rotation cycle in terms of yield was 3 or 4 years. The results clearly indicate a useful role for process models in predicting effects of management strategies on poplar yield in short rotation coppice.

For the implementation of the Kyoto Protocol, governments of annex I countries need to develop strategies and policies for greenhouse gas reduction. Land use, land use change and forestry (LULUCF) offer CO2 emission reduction opportunities both home and abroad. Selection of effective forestry opportunities is a complex decision process based on multiple information concerning the greenhouse gas emission reduction potential, the environmental impacts and the cost efficiency of potential scenarios. In this paper, a decision support framework to evaluate forestry scenarios for greenhouse gas emission reduction was presented and tested on five different scenarios (existing and new multifunctional forest in Flanders, Belgium, energy crop with short rotation poplar, energy crop with annually harvested Miscanthus, forest plantation in the subtropics, and conservation of tropical rainforest). The framework is organized as a serial connection of a carbon accounting module, an environmental module and an economic module. Modules include a combination of models and quantitative assessments procedures. In order to make scenarios comparable, the environmental and economic modules calculate their outputs on a functional unit basis of 1 ton CO2 emission reduction. The framework is universally applicable, straightforward, transparent and quantitative. Data requirements are medium, but applicability is fairly complex due to the interdisciplinary character of the tool. Further developments would require automated data flows between models and a user interface. As to the results of the scenario analysis, the only attractive possibility for sinks in Flanders is the establishment of new multifunctional forests. This even yields a net benefit because it replaces the generally loss-making agriculture and, in addition, yields other environmental and recreational benefits. The establishment of bioenergy plantations is a very efficient way of reducing CO2 as far as land occupation and environmental impacts are concerned. However, it also turns out to be a very expensive option. Plantation forestry in the tropics is advantageous when evaluated over longer periods of time. Conservation of tropical forest does not come into consideration as a CDM project, but is nevertheless economically attractive for Flanders since the cost per ton CO2 emission reduction is in the neighborhood of the world market price.

Needle length and width at midpoint are often used to make estimates of needle surface area for conifers. For these estimates, Scots pine (Pinus sylvestris L.) fascicles are assumed to be cylindrical; thus, for a two-needle pine, the cross section of a needle within the fascicle is assumed to be hemicylindrical. The objectives of this study were to determine whether these assumptions lead to a good estimate of the actual surface area and how needles vary with tree age and crown position. We used a digital scanning microscope to measure needle width, thickness, and perimeter at 11 positions along 28 needles from different crown positions in different-aged trees and found that they varied with position within the individual needle as well as with tree age and crown position. Needle shape was relatively constant: needle width and perimeter both increased from the base to the needle midpoint and then decreased slightly to the needle tip, but needles were not hemicylindrical and actual perimeters were nearly 12% larger than predicted perimeters. The predicted surface areas based on measurements of width at the needle midpoint and length need to be reduced by 9% to account for the fact that needles taper and are not cylindrical. Furthermore, tree age and crown position must be considered when crown-level estimates are made.Key words: digital image analyzer, light microscope, needle width, needle thickness, needle perimeter, Pinus sylvestris.

The interaction between reduced UV-B radiation and elevated CO 2 on the growth, allocation and physiology of white clover ( Trifolium repens ) was studied in greenhouses of different UV-B transmittance (82 and 88% of ambient) with either ambient (371 ppm) or elevated (521 μmol mol −1 ) CO 2 concentration. The 88% UV-B levels in increased growth and flowering, indicating an important role for ambient UV-B levels in plant functioning and growth. High CO 2 increased growth significantly only under the 88% UV-B level. The interaction between UV-B and CO 2 effects on total biomass was significant. Allocation was affected significantly by both UV-B (increased root growth, increased flowering) and CO 2 (increased flowering, reduced stem weight). The results clearly indicate the importance of using UV-B transmittant greenhouse or open-top chamber when conducting CO 2 studies, or at least stating the reduction in UV-B within greenhouses.

The purpose of this study was to investigate whether differences in canopy architecture due to the investigated species (planophile versus erectophile, single versus mixed canopies) or to UV-B effects on plant morphology, lead to differences in UV-B and UV-B/PAR doses within canopies.

There are several very accurate methods to determine leaf angles in closed canopies. However, these are generally very time-consuming or require special equipment. Average canopy leaf angles were derived from simple height and blade length measurements. An exponential relationship between the height/length ratio and the average blade leaf angle was used. The method was tested for two grass species, Dactylis glomerata and Festuca arundinacea, grown under different UV-B levels. The results clearly show that the method is reasonably accurate and able to identify UV-B induced changes in leaf angle. To get these results only 50 measurements of leaf blade height and length were necessary to calculate the allometric relationship, after which 10 length and height measurements from a canopy were used to calculate the average canopy leaf angle.

The interactive effects of N-deficiency and enhanced UV-B radiation on growth, photosynthesis and pigmentation of rye were studied. The plants were grown for 5 weeks in growth chambers with high (700 μmolm-2 s-2) irradiance levels. A 30% difference in UV-B at plant level was achieved by using different thicknesses of UV-B transparent Plexiglass. One half of the plants received optimal N nutrition, while the other received half of this dose. Both enhanced UV-B and N deficiency strongly decreased production (from 24–33%). The combined effect was additive (no interaction) on most parameters, including total dry weight production which was 52% lower than in the control series. Significant interaction was found on the root/shoot ratio. While reduced N supply induced an increase in the ratio at normal UV-B irradiation, under the increased UV-B, N deficiency had no effect on the root/shoot ratio. The reduced biomass due to UV-B was clearly correlated to a reduction in photosynthesis. At optimal N supply the plants increased the production of protective pigments in response to UV-B, but at reduced N supply this response was lacking. The increased N content of the high UV-B/high N plants could be a result of increased flavonoid production as well as changes in light penetration in the canopy.

We estimated daily use of stored water by Scots pine (Pinus sylvestris L.) trees growing in a temperate climate with the ANAFORE model (ANAlysis of FORest Ecosystems) and compared the simulation results with sap flow measurements. The original model was expanded with a dynamic water flow and storage model that simulates sap flow dynamics in an individual tree. ANAFORE was able to accurately simulate diurnal patterns of measured sap flow under microclimatic conditions that differ from those of the calibration period. Strong relationships were found between stored water use and several tree characteristics (diameter at breast height, sapwood area, leaf area), but not with tree height. Relative to transpiration, stored water use varied over time (between < 1% and 44% of daily transpiration). On days when transpiration was high, trees were more dependent on stored water, indicating that the contribution of internal water to transpiration is not a constant in the water budget of trees.

Soil organic matter (SOM) is key to soil fertility, climate change mitigation, combatting land degradation, and the conservation of above- and below-ground biodiversity and associated ecosystem services like decomposition, nutrient cycling, carbon sequestration, detoxification and maintenance of soil physico-chemical properties. SOM dynamics represent the balance between the input of plant material (residues, root-derived materials) and the output through decomposition (OM mineralization) by organisms, erosion and leaching. Approximately 20% of global CO2 emissions, one third of global CH4 emissions and two thirds of N2O emissions originate from soils. In many soils, most of the macro-aggregate structure is formed by the activities of soil invertebrates and roots, with important consequences for soil organic matter dynamics, carbon sequestration and water infiltration at several spatial and temporal scales. Current models of SOM dynamics are defined in terms of plant residues input and microbial decomposition, overlooking the important contribution of soil fauna. The composition and activity of soil fauna greatly vary with respect to climate and land use. SOM modelling has thus far largely ignored soil fauna due to various reasons: i) hardly existing communication between [C flow centered] biogeochemistry and [organism-centered] soil ecology, ii) lack of [awareness of] data on soil animals (both in the field and from laboratory experiments) and, iii) two different visions by soil ecologists: foodweb vs. self-organization. An international interdisciplinary approach (COST Action ES1406) is the proper platform for both experimentalists and modellers to discuss and provide solutions. This Action has fostered networking and collaboration for improved SOM models by implementing the role of the soil fauna as a basis for sustainable soil management. Key challenges in SOM management, soil fauna and modelling will be addressed and how far have we got thus far to meet the objectives of this Action.

The raw material properties of wood develop as the tree grows, laying down wood cells with specific properties, and forming the stem structure that is focal for timber quality. This development is influenced by genetic and environmental factors and forest management practices. It is desirable in growth and yield models intended for the economic assessment of management practices to include some indication of wood quality and how it is affected by genetics, environmental factors and silvicultural measures. This paper reviews approaches and models that allow us to consider the development of wood quality in combination with tree growth, and thus to include wood quality in the assessment of the value of the yield. We present such models as classified into three categories based on their complexity and information needs: quality indicators, static quality models, and dynamic quality models. We illustrate three advanced dynamic quality models and their applications with example case studies. These include empirical, hybrid, and mechanistic models applied to predictions of both sawn timber and fibre properties. Finally, we consider the current challenges for wood quality modelling in connection with growth models. Las propiedades de la madera se desarrollan cuando crece el arbol, estableciendose las células de la madera con propiedades específicas, y formandose la estructura del tronco que es central para la calidad de la madera. Esta desarrollo se ve influido por factores genéticos y ambientales y por las prácticas de gestión forestal. Es deseable incluir en los modelos de crecimiento y producción destinados a la evaluación económica de las prácticas de gestión una indicación de la calidad de la madera y cómo se ve afectada por factores genéticos y ambientales y por las medidas silvícolas. En el sector forestal, la comprensión del desarrollo y la variación de la calidad de la madera es importante en distintos programas de gestión y planificación que se pueden clasificar en (1) la gestión de las operaciones de cosecha, y (2) la planificación silvícola a largo plazo. Este artículo discute los principales enfoques y modelos que nos permiten estudiar estos dos problemas en términos cuantitativos. Comenzamos la revisión discutiendo el concepto de «modelo de calidad de madera», y luego clasificamos los enfoques sobre la base de su complejidad, el principio subyacente y el uso previsto. Mostramos tres modelos dinámicos avanzados de calidad y sus aplicaciones con estudios de casos. Estos incluyen modelos empíricos, híbridos y mecánicistas aplicadaos a las predicciones tanto de la madera aserrada como a las propiedades de la fibra. Por último, consideramos los retos actuales para el modelado de la calidad de la madera en relación con la gestión forestal.