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Global warming and drying trends, as well as the increase in frequency and intensity of droughts, may have unprecedented impacts on various forest ecosystems. We assessed the role of internal water storage (WS) in drought resistance of mature pine trees in the semi-arid Yatir Forest. Transpiration (T), soil moisture and sap flow (SF) were measured continuously, accompanied by periodical measurements of leaf and branch water potential (Ψleaf) and water content (WC). The data were used to parameterize a tree hydraulics model to examine the impact of WS capacitance on the tree water relations. The results of the continuous measurements showed a 5-h time lag between T and SF in the dry season, which peaked in the early morning and early afternoon, respectively. A good fit between model results and observations was only obtained when the empirically estimated WS capacitance was included in the model. Without WS during the dry season, Ψleaf would drop below a threshold known to cause hydraulic failure and cessation of gas exchange in the studied tree species. Our results indicate that tree WS capacitance is a key drought resistance trait that could enhance tree survival in a drying climate, contributing up to 45% of the total daily transpiration during the dry season.

Soil respiration studies in paludified forests of the European part of Russia are quite rare in comparison with those of open peat bogs, which make long-term observations in this region highly relevant. In this study, soil CO2 emissions were measured by the close chamber method in different microlandscapes of paludified forests. For four summer seasons with different environments, soil respiration ranged from 1078 to 248 mg CO2 m−2 h−1 in a paludified spruce forest site with coarse woody debris to 659–820 mg CO2 m−2 h−1 in a paludified boggy pine forest. The most intensive soil respiration was observed during the hot summer of 2013 and the lowest in the hot and humid summer of 2016. Annual total soil CO2 emissions in paludified forests in 2015–2016 were approximately 2000–3000 g CO2 m−2. During the year, the lowest CO2 emission values were observed from November to April (14–84 mg CO2 m−2 h−1) and the maximum were in July and August (522–1205 mg CO2 m−2 h−1). The contributions of CO2 emissions in the cold November–April period were 6–8.5%. The impacts of temperature on soil respiration were higher (r2 = 0.45–0.57) than those of groundwater levels (r2 = 0.17–0.49). Soil respiration in the paludified spruce forest and in the pine bog generally were higher than emissions from ecosystems with similar hydrothermal conditions in the boreal zone.

Efficiency and energetics of the turbulent transport in the canopy sublayer of a semi-arid pine forest and the atmospheric surface layer of a sparse desert-like shrubland are investigated from ultrasonic anemometer measurements during the summer dry season. The results show that an increased sensible heat flux over the forest canopy is generated by more energetic turbulence at small and large scales, but the transport process itself is equally efficient compared to the neighbouring shrubland. In contrast, the turbulent momentum flux over the forest canopy is caused by more efficient and energetic momentum transport at large scales. The more energetic turbulence appears to reduce the aerodynamic resistance to heat transfer of the semi-arid forest, which enables the increased sensible heat flux at a lower surface temperature. The results help explain the observed differences in diurnal variation of statistical moments of turbulent quantities that are caused by the interaction between radiative forcing, the background wind and the different turbulence production regimes of the forest and the shrubland. Lastly, the results also explain the observed cooler nighttime temperatures and quicker formation of a residual layer at the forest site.

Climate change will have a considerable impact on forest productivity worldwide. Forecasting the magnitude of such impact, with multiple environmental stressors changing simultaneously, is only possible with the help of process-based models. In order to assess their performance, such models require careful evaluation against measurements. However, direct comparison of model outputs against observational data is often not reliable, as models may provide the right answers due to the wrong reasons. This would severely hinder forecasting abilities under unprecedented climate conditions. Here, we present a methodology for model assessment, which supplements the traditional output-to-observation model validation. It evaluates model performance through its ability to reproduce observed seasonal changes of the most limiting environmental driver (MLED) for a given process, here daily gross primary productivity (GPP). We analyzed seasonal changes of the MLED for GPP in two contrasting pine forests, the Mediterranean Pinus halepensis Mill. Yatir (Israel) and the boreal Pinus sylvestris L. Hyytiälä (Finland) from three years of eddy-covariance flux data. Then, we simulated the same period with a state-of-the-art process-based simulation model (LandscapeDNDC). Finally, we assessed if the model was able to reproduce both GPP observations and MLED seasonality. We found that the model reproduced the seasonality of GPP in both stands, but it was slightly overestimated without site-specific fine-tuning. Interestingly, although LandscapeDNDC properly captured the main MLED in Hyytiälä (temperature) and in Yatir (soil water availability), it failed to reproduce high-temperature and high-vapor pressure limitations of GPP in Yatir during spring and summer. We deduced that the most likely reason for this divergence is an incomplete description of stomatal behavior. In summary, this study validates the MLED approach as a model evaluation tool, and opens up new possibilities for model improvement.

Remote sensing (RS) techniques have great potentials for earth surface monitoring. Nevertheless, for most low to moderate resolution satellites, the problem of mixed pixels with information from the vegetation of interest and the background surfaces can cause large biases in signals and also in their interpretations. This is especially so in low-density forests and semi-arid ecosystems. Ground-level multispectral instruments reduce these effects by measuring at close range to the canopy. However, little work has been published on partitioning the contributions from vegetation and the background elements for both approaches.This work was motivated by the observed mismatch between data for the same ecosystem from Landsat 8 satellite and Skye radiometer installed on a flux tower in a low-density semi-arid pine forest from 2013-2019. Data from both sources showed similar seasonal patterns in NDVI, but large differences in the reflectance bands. This was most prominent in the NIR reflectance, which showed an opposite seasonal cycle in the two sensors. Thus, similar changes in NDVI were produced by different signals. We hypothesized that the different contributions of the surface components (canopy, shaded areas, and exposed soil) in the footprint areas of the two sensors can explain, and can help correct, these differences. Multispectral images with a spatial resolution of 5 cm were captured monthly using an Unmanned Aerial Vehicle (UAV) from April 2018 to November 2019. Reflectance-based algorithms were developed to identify and estimate the fraction and reflectance from the canopy, shaded areas, and open soil. This information was, in turn, applied in the equivalent nadir-viewing satellite pixel. For the tower-based Skye footprint, the same quantities were calculated from its 90° angle of view and the 3D canopy data.The results showed a canopy fraction of 45% and 95% in the Landsat 8 and Skye footprints. The remaining soil fraction showed a similar seasonal cycle in NDVI as the canopy, but different in the NIR reflectance. The partition between exposed and shaded soil was related to the sun angle, with the exposed soil having a NIR seasonal cycle opposite to that of the vegetation (correlating with soil moisture), and shaded soil having a weak NIR signal variably diluting the overall pixel NIR signal. Differences in the red reflectance were smaller with less effects on the seasonal NDVI cycles.The results demonstrated firstly, that accounting for the fractional contributions of the surface components can reconcile differences between satellite and ground-based RS. Secondly, vegetation indices such as NDVI obtained by satellite RS in low-density forests can provide misleading information, despite its apparent correlation with certain vegetation variables.

Dry forests are expected to heat up considerably more than adjacent shrubland areas due to lower albedo and reduced latent heat flux. Paradoxically, the forest surface at our research site was observed to be cooler than the non-forested neighbouring areas during drought. This reflected the control over canopy temperature through the sensible heat flux, i.e. a 'convector effect'. Our objective was to examine how the efficient non-evaporative energy management, critical to protect the biological functioning of dryland ecosystems, develops at the small, leaf scale. We developed a novel system to continuously measure the energy balance and heat dissipation mechanisms on a leaf scale under field conditions. It allows the measurement of emitted leaf and background longwave radiation, and estimating the incoming, absorbed and reflected shortwave radiation using PAR measurements and full spectrum models. Latent heat exchange and photosynthetic activity were measured with branch chambers. The system was deployed during the long summer drought (>8 months) in drought-exposed and irrigated plots in our semi-arid research Aleppo Pine forest site in southern Israel (mean daytime temperature of >30°C).Preliminary results showed that in spite of a x10 higher transpiration rate in the irrigated plot compared with the control plots, leaf temperature remains within 1-2°C of air temperature on average in both plots during direct exposure to sunlight at midday. These results suggest an effective leaf to air heat transfer which prevents overheating independent of the latent heat flux. Under the high radiation load, the midday summer value of incoming shortwave radiation was >800 W·m-2 (mostly absorbed by the low albedo leaves), and background longwave radiation was >500 W·m-2. In turn, the energy dissipation in the drought-exposed trees was dominated by sensible heat flux of >500 W·m-2, while the long-wave radiation balance was near neutral (~50 W m-2), and the residual latent heat flux was -2. We demonstrated a system that provided new insights to leaf and canopy energy management under drought, which is a basis for the evolution of the convector effect.

International audience; Short-term, intense heat waves (hamsins) are common in the eastern Mediterranean region and provide an opportunity to study the resilience of forests to such events that are predicted to increase in frequency and intensity. * The response of a 50-yr-old Aleppo pine (Pinus halepensis) forest to hamsin events lasting 1–7 d was studied using 10 yr of eddy covariance and sap flow measurements. * The highest frequency of heat waves was c. four per month, coinciding with the peak productivity period (March–April). During these events, net ecosystem carbon exchange (NEE) and canopy conductance (gc) decreased by c. 60%, but evapotranspiration (ET) showed little change. Fast recovery was also observed with fluxes reaching pre-stress values within a day following the event. NEE and gc showed a strong response to vapor pressure deficit that weakened as soil moisture decreased, while sap flow was primarily responding to changes in soil moisture. On an annual scale, heat waves reduced NEE and gross primary productivity by c. 15% and 4%, respectively. * Forest resilience to short-term extreme events such as heat waves is probably a key to its survival and must be accounted for to better predict the increasing impact on productivity and survival of such events in future climates.

Afforestation is an important approach to mitigate global warming. Its complex interactions with the climate system, however, makes it controversial. Afforestation is expected to be effective in the tropics where biogeochemical and biogeophysical effects act in concert; however, its potential in the large semi-arid regions remains insufficiently explored. Here, we use a Global Climate Model to provide a process-based demonstration that implementing measured characteristics of a successful semi-arid afforestation system (2000 ha, ~300 mm mean annual precipitation) over large areas (~200 million ha) of similar precipitation levels in the Sahel and North Australia leads to the weakening and shifting of regional low-level jets, enhancing moisture penetration and precipitation (+0.8 ± 0.1 mm d−1 over the Sahel and +0.4 ± 0.1 mm d−1 over North Australia), influencing areas larger than the original afforestation. These effects are associated with increasing root depth and surface roughness and with decreasing albedo. This results in enhanced evapotranspiration, surface cooling and the modification of the latitudinal temperature gradient. It is estimated that the carbon sequestration potential of such large-scale semi-arid afforestation can be on the order of ~10% of the global carbon sink of the land biosphere and would overwhelm any biogeophysical warming effects within ~6 years.

The project “Volgaforest” was focused on a study of the water budget of the forested Upper Volga catchment in Russia in order to describe: • the terrestrial water balance of the Upper Volga catchment as a function of external factors, such as climate and land-use, and • the response of forest ecosystems to these external factors. Future changes of water budget of the Upper Volga catchment area were estimated from: past and present dynamics of the atmospheric, water and forest conditions, different climatic scenarios and SVAT (Soil–Vegetation–Atmosphere Transfer) and hydrological models. Analysis of past climatological and hydrological data showed a large atmospheric and hydrological variability of the Upper Volga catchment. During the last 50–60 years the mean annual air temperature increased by 1.2 °C, and annual precipitation increased by 140 mm. However, no significant trend of annual runoff during the last 20 years could be found. Air temperature and precipitation changes were significant during winter and spring but very small in summer. Coniferous and mixed coniferous-broadleaf forests cover at present about 72% of the catchment area. During the last 30 years the area of natural coniferous forests (spruce, pine) decreased from 8.4% to 7% and the area of mixed forests increased from 52% to 59% of the total land area. Results of field measurements at a forest site showed a large variability of energy and water fluxes during the entire year. Transpiration of the boreal forest ecosystem measured using a sap flow method during the dry summer 1999 was limited by very dry soil water conditions, especially for spruce trees, and during the rainy summer 2000 probably by lack of oxygen in the rooting zone. Transpiration was about 10–20% larger for broadleaf trees (birch, aspen) than for spruce trees. Model estimations of possible changes in the hydrological regime of the Upper Volga catchment area for climatic scenarios suggest changes of evapotranspiration, surface runoff and soil moisture storage. Reduced snow accumulation, earlier melting, increased runoff reaction on precipitation in autumn and winter and drier soils in summer are the principal impacts on water resources of predicted future climatic changes. Surface runoff during the spring will be higher but summer and autumn runoff can be slightly suppressed by higher transpiration of deciduous tree species. Decreased summer precipitation and increased transpiration will result in decreasing ground water discharge, and lowering water levels of Volga river and of the Upper Volga lakes.

La variation journaliere et saisonniere du rayon du tronc du chene pedoncule (Quercus robur L.) a ete etudiee en dependance des facteurs environnementaux dans une foret marecageuse en Moravie du sud d'avril a octobre, plusieurs annees apres le fin des inondations naturelles regulieres. Les deux principaux processus generaux qui controlent le rayon du tronc ont ete etudies separement : la croissance des tissus de l'arbre et leur hydratation (contraction et gonflement). Differents types de dynamique journaliere de variation de dimension du rayon du tronc ont ete obtenus, y compris la croissance avec et sans contraction, la croissance nocturne et la contraction diurne et vice versa. Un modele physiologique simple a ete utilise pour decrire la dynamique du rayon du tronc. Des donnees concernant le flux transpiratoire, le rayonnement global et la temperature de l'air ont ete utilisees comme donnees d'entree. La croissance a ete simulee a partir de la photosynthese et de la respiration calculees pour les conditions meteorologiques reelles et l'hydratation des tissus a ete deduite de la difference entre la transpiration potentielle et reelle (flux transpiratoire). La simulation a partir du modele a demontre une bonne aproximation de la dynamique saisonniere de variation dimensionnelle du tronc en conditions climatiques moderees et humidite non limitante.

Soil, tree stems, and ecosystem carbon dioxide fluxes were measured by chambers and eddy covariance methods in a paludified shallow-peat spruce forest in the southern taiga of European Russia (Tver region, 56 N 33 E) during the growing seasons of 2002‐2012. The site was established in 1998 as part of the EUROSIBERIAN CARBONFLUX project, an international field experiment examining atmosphere‐biosphere interaction in Siberia and European Russia. In all years the observed annual cumulative net ecosystem flux was positive (the forest was a source of carbon to the atmosphere). Soil and tree stem respiration was a significant part of the total ecosystem respiration (ER) in this paludified shallow-peat spruce forest. On average, 49% of the ER came from soil respiration. We found that the soil fluxes exhibited high seasonal variability, ranging from 0.7 to 10 mol m 2 s 1 . Generally, the soil respiration depended on the soil temperature and ground water level. In drought conditions, the soil respiration was low and did not depend on temperature. The stem respiration of spruces grew intensively in May, had permanently high values from June to the end of September, and in October it dramatically decreased. The tree stem respiration in midsummer was about 3‐5 mol m 2 s 1 for dominant trees and about 1‐2 mol m 2 s 1 for subdominant trees. The respiration of living tree stems was about 10‐20% of the ER.

A process-based model (Forest-DNDC) was applied to describe the possible impacts of climate change on carbon dioxide (CO2) fluxes from a peat bog in European Russia. In the first step, Forest-DNDC was tested against CO2 fluxes measured by the eddy covariance method on an oligotrophic bog in a representative region of the southern taiga (56 ◦ N3 3 ◦ E). The results of model validations show that Forest-DNDC is capable of quantifying the CO2 fluxes from the bog ecosystem. In the second step, the validated model was used to estimate how the expected future changes of the air temperature and water table depth could affect the C dynamics in the bogs. It was shown that a decrease in the water table and an increase in temperature influence significantly the CO2 exchange between our bog ecosystem and the atmosphere. Under elevated temperature and deepened water table the bog ecosystems could become a significant source of atmospheric CO2.

Nation wide estimates of the changes in forest biomass are needed for the greenhouse gas (GHG) reporting under the Climate Convention. The bases for national GHG reporting concerning forest sector are the national forest inventory (NFI) programmes. Since these programmes were mostly established for monitoring of timber resources, one of the current challenges for the NFIs is the development of methodology, such as biomass expansion factors (BEFs). The methodology for carbon stock change estimation should be transparent and verifiable, but this demand is not currently met due to the fact that the source data and uncertainty in the applied BEFs are not known. Here we developed BEFs with uncertainty estimation applicable to stand wise inventory of Norway spruce forests in the Czech Republic. BEFs were constructed, based on tree wise data from permanent research plots, by applying biomass and volume models to tree-level data. These BEFs were age-dependent and their uncertainty was sensitive to the dependencies among errors. Most of the uncertainty in the BEFs was due to uncertainty in the biomass and volume models applied. biomass expansion factor / Monte Carlo simulation / greenhouse gas inventory / national forest inventory

In KUREX‐88 and KUREX‐91 the measurements of absorbed Photosynthetically active radiation (APAR), stomatal resistance (R st), transpiration (E) and net photosynthesis (P) were made for three agricultural crops: spring wheat, buckwheat and corn. Most of the variations in the R st, E and P were found to be dominated by PAR and difference in temperature between leaf and the atmosphere (T l — Ta ). Parametrizations describing the R st, E and P responses to environmental factors were developed. The PAR, (Tl — T a), leaf temperature, humidity of the air and Rst were associated with 60–95% of variations in transpiration coefficient characterizing the efficiency of the water utilization in the dry matter production. Scaling up of energy and mass exchange processes from a leaf to a canopy was studied. Shelter factor (P s) for the corn crop was estimated as P s = 0.464 LAI ‐ 0.25. Theoretical and empirical relationships between vegetation indices and APAR, and canopy photosynthesis (P c) were developed. The simple ...