Search

Europe has a history rich in examples of successful and less successful introductions of non-native trees (NNT) - trees with an evolutionary origin outside of Europe. NNT have been introduced for various reasons such as ornamental purposes, food production, land reclamation/amelioration and timber production. The use of NNT also causes controversies due to potential negative impacts on natural ecosystems of NNT that become invasive. Many international legal frameworks responded to the presence and use of NNT, such as international treaties and conventions ; and also the European Union deals with the issue of invasive alien species in Regulation (EU) No. 1143/2014. However, especially the national and regional responses to NNT affect current and future management decisions in the forest sector and furthermore shape forest landscapes of Europe. In this comprehensive study of the legal landscape concerning NNT we identified all relevant legislations, the different legal approaches and the regulatory intensity in every European country (except microstates). Hard and relevant soft law items at the national and sub-national (regional) level for 40 European countries were collected and proofed using a targeted questionnaire sent to country experts across Europe mainly coming from the forestry and nature conservation sector. In addition, international and national legislation information systems and databases were consulted to complete the information. Legislations included updates until June/July 2019. In total, 320 national and regional law items were identified to be relevant for the regulation of NNT in the investigated 116 legislative units (countries, and regions with own legislation) in Europe. Countries and regions were empirically categorised according to ad hoc created legislation indicators dealing with the general ban of introduction of non-native species, the generally allowed and prohibited NNT, approval mechanisms, e.g. mandatory forest management plans, and areas and cases where NNT are restricted or completely prohibited. Our study revealed a very diverse legal landscape in Europe, with a large variety of approaches being pursued to regulate NNT, and the intensity of regulation ranging from very little restrictions on the species choice and plantation surface area to a complete ban of NNT in forests.

Purpose of Review Non-native tree species (NNT) raise a range of different associations and emotions—to many citizens they are just an exotic curiosity in parks, to many conservationists they are an evil to native ecosystems that should be eradicated, to a rising group of foresters they are part of the solution to climate change and an increasing timber demand, and to others they are already daily forestry business. In this review, where we also summarise the findings of the recent COST Action FP1403 (NNEXT) ‘Non-native tree species for European forests: experiences, risks and opportunities’, we highlight opportunities and challenges in the light of climate change, ecological risks and legislative limits of growing non-native tree species in Europe. Recent Findings Few NNT in Europe show invasive behaviour and are listed as prohibited species or as species to be monitored. A larger number of NNT is utilised in productive forestry and forest restoration due to their superior growth, valuable timber properties and good performance under harsh growing conditions. Current species distribution, experiences with success and failures and environmental concerns differ profoundly across Europe, with Western Europe overall revealing higher shares in NNT and showing a stronger interest of forestry related stakeholder groups to continue planting NNT. Summary Many more NNT are already used in forestry than previously thought, but relatively few species have major importance in terms of area, mainly in western European countries. Diversification, mixing and avoidance of invasion in relation to NNT are necessities that are relatively new on the agenda. In contrast, provenance research of major NNT has been going on for many decades and now provides important information for climate change adaptation. Despite the limitations to the use of NNT either through legal restrictions or forest certification that differ considerably across Europe, the careful integration of a range of tested NNT also into future forest management planning shows a high potential for climate change adaptation and mitigation.

Ailanthus altissima is a common tree species of the European non-native flora. In Eastern Austria, Ailanthus has both a long tradition, dating back to the late 18th century, and a high frequency of occurrence. Here, we apply molecular markers from the nuclear and chloroplast DNA in order to study the origin, as well as the clonal and genetic structure of the species in forest stands of this region. Our results indicate a single area of origin for all our study populations from the north-eastern part of the native range, in agreement with historical reports. Within populations, vegetative reproduction has resulted in extensive clonal structures at some sites. Long presence and repeated vegetative recruitment might have led to expansion of clones in areas of early introduction. In addition, limited mate availability may also have promoted vegetative reproduction. Tests for recent bottlenecks were significant in almost all stands, possibly reflecting founder effects since the introduction of Ailanthus in our study area. Among populations, we found a very pronounced and significant genetic structure, which did not follow a spatial pattern. We argue that founder effects due to population establishment with a low number of propagules – whether naturally or artificially – have caused genetic drift and a structured gene pool. The lack of spatial pattern or isolation-by-distance suggests that seed transfer by humans might have been a major factor shaping the genetic variation of Ailanthus in Eastern Austria.

The structure of a forest dictates its function, vulnerability to mortality, and ecosystem services it provides. Many aspects of the environment and management determine forest structures, such as canopy height, stand density, carbon content, etc. Environmental factors, such as climate, limit the extent to which management can maximize structures of a forest. By understanding how climate limits forest structures over large landscapes we can better quantify the potential upper limit that a forest structure can achieve independent of management. Further, by quantifying how climate limits forest structures we can deepen our understanding of the impact climate change has had and will have on our forest resources and services. This type of information goes beyond quantifying how climate will impact the pools and fluxes of a forest, which is typically done for climate change studies over large landscapes. Estimating how climate change will impact structures will allow us to quantify how climate change will impact resources and services unquantifiable by pools and fluxes alone – such as biodiversity, habitat suitability, and market values. We quantified how maximum and minimum temperatures, and precipitation limit 3 forest structures, diameter at breast height, height, and basal area across the European continent. We found that climate zones exist that maximize each forest structure. Further, we estimated how climate change since the 1950’s has influenced the potential structures of European forests by assessing eight individual forests throughout Europe and then Europe as a whole. All three forest structures are limited in different ways depending on their location in Europe. Though some individual forests have seen a benefit from climate change, European forests on average have lost 5.0%, 1.7% and 6.5% of potential forest diameter, height and basal area respectively. Further, the extremes of the climate values in our study, which may support endemic life, have already begun to vanish from the entire continent.

Litterfall is a major, yet poorly studied, process within forest ecosystems globally. It is important for carbon dynamics, edaphic communities, and maintaining site fertility. Reliable information on the carbon and nutrient input from litterfall, provided by litter traps, is relevant to a wide audience including policymakers and soil scientists. We used litterfall observations of 320 plots from the pan-European forest monitoring network of the “International Co-operative Programme on Assessment and Monitoring of AirPollution Effects on Forests” to quantify litterfallfluxes. Eight litterfall models were evaluated (four using climate information and four using biomass abundance). We scaled up our results to the total European forestarea and quantified the contribution of litterfall to the forest carbon cycle using net primary production aggregated by bioregions (north, central, and south) and by forest types (conifers and broadleaves). The 1,604 analyzed annual litterfall observations indicated an average carbon input of 224 g C · m2· year 1 (annual nutrient inputs 4.49 g N, 0.32 g P, and 1.05 g K · m2), representing a substantial percentage of net primary production from 36% in north Europe to 32% in central Europe. The annual turnover of carbon and nutrient in broadleaf canopies was larger than for conifers. The evaluated models provide large-scale litterfall predictions with a bias less than 10%. Each year litterfall in European forests transfers 351 Tg C, 8.2 Tg N,0.6 Tg P, and 1.9 Tg K to the forestfloor. The performance of litterfall models may be improved by including foliage biomass and proxies for forest management.

National and international carbon reporting systems require information on forest carbon stocks. This information can be derived from national forest inventory data and remote sensing. Here we present the conceptual challenges in assessing forest resources across Europe by combining MODIS satellite versus terrestrial driven NPP estimates calculated from 13 national forest inventory (NFI) data covering 200.000 sampling plots. The results suggest that MODIS NPP predictions using local daily climate data and addressing stand desnsity effects, provide realistic forest productivity estimates. Ignoring these effects leads to an overestimation in the estimated carbon storage of European forests derived from satellite data.

Due to its productivity and potential to adapt to the expected climate change, the Douglas-fir is one of the most important commercial non-native forest tree species in Europe. Currently, seeds from both non-native European and native American seed stands are used for plantations. In this study, we investigate European seed lots for their native origin (variety and potential geographic origin in America) and assess the adaptability, growth and survival potential of European versus American Douglas-fir seed lots. We compare the genetic diversity, morphological characteristics such as height (h), root collar diameter (rcd) and the ratio of h/rcd, and the timing of bud burst. We investigate 852 1-year-old seedlings from 10 different US and European seed lots representing 5 provenance regions which are sold in Germany and Austria. Seedlings are genotyped for 13 nuclear SSRs and analysed together with reference data set and standard genetic structuring and assignment methods. Adaptive traits of morphological characteristics and timing of bud burst of the seedlings are recorded and statistically analysed. The results show that the investigated European seedlings originate from recommended American native seed sources and represent both varieties and inter-varietal admixed individuals. European seedlings have a lower genetic diversity versus the American seedlings and native populations. They show significant differences in the adaptive traits such as morphological characteristics and timing of bud burst. According to the genetic diversity indices, certified North American Douglas-fir seed sources should be preferred for planting in Central Europe.

Tree mortality is an important process in forest ecosystems, frequently hypothesized to be highly climate sensitive. Yet, tree death remains one of the least understood processes of forest dynamics. Recently, changes in tree mortality have been observed in forests around the globe, which could profoundly affect ecosystem functioning and services provisioning to society. We describe continental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe. Analyzing 925,462 annual observations of 235,895 trees between 2000 and 2012, we determine the influence of climate variability and tree age on interannual variation in tree mortality using Cox proportional hazard models. Warm summers as well as high seasonal variability in precipitation increased the likelihood of tree death. However, our data also suggest that reduced cold-induced mortality could compensate increased mortality related to peak temperatures in a warming climate. Besides climate variability, age was an important driver of tree mortality, with individual mortality probability decreasing with age over the first century of a trees life. A considerable portion of the observed variation in tree mortality could be explained by satellite-derived net primary productivity, suggesting that widely available remote sensing products can be used as an early warning indicator of widespread tree mortality. Our findings advance the understanding of patterns of large-scale tree mortality by demonstrating the influence of seasonal and diurnal climate variation, and highlight the potential of state-of-the-art remote sensing to anticipate an increased likelihood of tree mortality in space and time.

Pan-European gridded datasets derived from a single methodology to inform researchers, policy makers and conservationists on the state of forest structures would improve our ability to study forests independent of political boundaries and along various gradients. Although National Forest Inventory (NFI) data provide information on the characteristics of forests, including carbon content, volume, height, and age, such spatial data is not available across Europe. Before this study, remotely sensed data covering all of Europe had not been utilized to produce multiple European-focused forest structure datasets over the entire continent that are methodologically consistent and comparable. We used existing European data to develop a pan-European dataset covering tons of live tree carbon and volume per hectare, mean tree height and mean tree age by integrating remotely sensed and harmonized NFI data from 13 different European countries. We produced a pan-European map for each of the four key variables on a 0.133° grid representing the time period 2000–2010.

Moses (MOdelling Stand rESponse) is a distance and potential-dependent single-tree growth simulator. It consists of a diameter and height increment model, a dynamic crown model and models that calculate mortality and regeneration. It was originally calibrated for spruce, beech and pine forests in Austria and has been recalibrated several times throughout the years. In this study, we recalibrated and validated the increment models and the mortality model within MOSES using the latest large and holistic dataset based on monitoring and permanent inventory plots for seven of the most common tree species in Europe (five for the mortality model). These plots were mainly from Austria and Switzerland, as well as Germany. In addition, we calibrated sets of coefficients for the “species groups” (i) other broadleaf and (ii) other conifer trees. The total dataset comprises 278,979 repeated tree measurements, 56,312 of them were used for calibration and 222,667 for validation. The validation of the newly parameterized growth and mortality models exhibit consistent and unbiased estimates for tree growth in central European forests using the MOSES simulator.

© 2019 The Authors FORMIT-M is a widely applicable, open-access, simple and flexible, climate-sensitive forest management simulator requiring only standard forest inventory data as input. It combines a process-based carbon balance approach with a strong inventory-based empirical component. The model has been linked to the global forest sector model EFI-GTM to secure consistency between timber cutting and demand, although prescribed harvest scenarios can also be used. Here we introduce the structure of the model and demonstrate its use with example simulations until the end of the 21st century in Europe, comparing different management scenarios in different regions under climate change. The model was consistent with country-level statistics of growing stock volumes (R 2 = 0.938) and its projections of climate impact on growth agreed with other studies. The management changes had a greater impact on growing stocks, harvest potential and carbon balance than projected climate change, at least in the absence of increased disturbance rates. ispartof: Environmental Modelling and Software vol:115 pages:128-143 status: published

Many spatial vegetative physiological and environmental impact studies demand consistent as well as fine resolution daily meteorological data, which is often unavailable. This problem is evident when studies and applications focus at the regional and local scale. Meteorological stations cannot provide the needed data due to their irregular locations and several associated shortcomings such as missing data. Climate data from global sources like the National Centers for Environmental Prediction (NCEP) and WorldClim are provided at a coarse resolution which makes them inappropriate to use directly at regional and local scales. In order to circumvent this problem, we downscaled daily WorldClim and NCEP global climate grids to produce weather data sets using a delta method to 0.0083‾ (approximately 1 × 1 km) spatial resolution for the Amhara region of northwestern Ethiopia. The downscaled data set includes daily precipitation, and minimum and maximum temperature from 1979 to 2010. The drizzle effect in the downscaled data set was first eliminated by using a rain threshold that removed values of

Forests provide critical ecosystem services that ensure the sustainability of the environment and society. To manage forests on large scales, spatially explicit gridded data that describes the characteristics of these forests over the entire study area are required. There have been multiple efforts to create such data on regional and global scales. This type of gridded spatially explicit data on forest characteristics are typically done by integrating terrestrial forest inventory (NFI) and satellite-based remotely sensed data. Many studies that incorporate remotely sensed data and forest inventory data often directly compare pixels to inventory plots. The standard resolution of 0.0083° is typically used to integrate these two types of data sets. There is an assumption that, when producing gridded data sets incorporating forest inventory data, the finer the resolution the better the information. This assumption may seem intuitive, however at this resolution, in Europe, each 0.0083° cell has on average 1 NFI plot, which results in a sample with 0 degrees of freedom that represents 0.02% of the cell area. In this study, we challenge this assumption and we quantify the optimal resolution with which to compare and combine remotely sensed and NFI data from the largest collated and harmonized NFI data set in Europe including 196,434 plots. We determined that aggregating data with an original resolution of 0.0083° to between 0.0664° and 0.266° (or × 8 to × 32) produces the best agreement between these two forest inventory and remotely sensed data sets, and the lowest standard error in NFI data, and maintains the majority of the local-level spatial heterogeneity.

We assessed the impact of anthropogenic activities such as selective felling and resource extraction on plant diversity and forest structure in the broad-leaved forests of Bhutan. The forest area was grouped into three zones according to human influence: settlement-agriculture, semi-disturbed, and natural forest. A total of 140 plant species were identified. Maximum species richness of trees (8 species/plot) was recorded in natural forests and least in the settlement-agriculture zone (3 species/plot). Shannon (1.73 ± 0.62) and Simpson diversity (5.49 ± 2.97) indices were highest for the natural forest zone as compared to the semi-disturbed (0.92 ± 0.74, 2.70 ± 2.05) and settlement-agriculture zones (0.74 ± 0.74, 2.24 ± 2.13). The density and basal area of trees decreased from 373 N ha−1 and 37.9 m2 ha−1 in the natural forest zone to 114 N ha−1 and 5.7 m2 ha−1 in the settlement-agriculture zone. The diameter distribution revealed a lack of commercial tree species in the higher dbh classes from the ...

Little is known about sustainable forest management and tree growth in the Amazon forest. Reliable growth data from trees are very important in the context of forest management. Tree-characteristics such as architecture and competition are associated with diameter growth. Previous studies analyzing tree growth have indicated that these variables can describe these effects for temperate and boreal forests. However, the role of these effects for the growth of tropical trees needs to be enhanced for forest management practices. Here, we reconstructed the periodic annual basal area increment ( BAI i cm 2 yr −1 ) of four long-lived timber species from the Amazon forest of Brazil: (i) Cedrela odorata, (ii) Amburana cearensis, (iii) Copaifera pauper and (iv) Swietenia macrophylla to investigate the growth development. The study focuses on (i) drivers important for individual tree growth, (ii) calibration of an individual tree basal area increment model for each of the four species, and (iii) assessing the practical implementation of our findings for enhancing sustainable forest management of these four tree species in the Amazon rainforest. The results exhibit a significant relationship between increasing basal area increment versus increasing crown length and decreasing competition expressed by Hegyi’s index. Trees sampled in densities greater than 25 m 2 ha −1 had their BAI % significantly reduced. For Cedrela an additional negative impact on basal area increment from liana load is evident. Our findings reinforce the importance of release trees to obtain better crown exposure.

Forests are a key player within the global carbon cycle and reforestation is an important climate change mitigation mechanism. In this study, we identify potentially suitable areas for reforestation to assess the carbon sequestration potential in the highly deforested and degraded Amhara region of Ethiopia. We apply biogeochemical mechanistic ecosystem modelling to predict the amount of carbon that can be potentially sequestered within different time horizons. Since human intervention plays a key role within the Amhara region, three different forest management scenarios and five different rotation periods following reforestation are tested: (i) unthinned, (ii) removal of 5% of the stem carbon every 20 years (thinning 1), and (iii) removal of 10% stem carbon every 20 years (thinning 2), as well as a rotation period of 10, 30, 50, 100, and 150 years. Sustainable management of reforested land is addressed by implementing the so called ‘Normal-forest’ system (equal representation of every age class). This ensures the long term sequestration effect of reforested areas. The study shows that 3.4 Mha (Mha = Million hectare) of land, including bare land (0.7 Mha), grass land (1.2 Mha), and shrub land (1.5 Mha) can be considered as ecologically potentially suitable for reforestation. Assuming a 100 year rotation period in a ‘Normal-forest’ system, this shows that a total net carbon sequestration potential of 177 Tg C (10.8 Tg C in the soil and 165.9 Tg C aboveground, Teragram = 1012 g) is possible, if all 3.4 Mha are replanted. The highest total net carbon sequestration (soil and aboveground) was evident for the Highland-wet agro-ecological zone, whereas the lowest values are typically in the Midland-dry zone. The highest net aboveground carbon sequestration was predicted for reforestations on current grass land and shrub land versus bare land, whereas the highest net soil carbon sequestration was predicted on current bare land, followed by grass land and shrub land.

Since the nineteenth century, Douglas-fir seed sources have been widely used for establishment of forest stands outside its natural distribution range. In Europe, some of these old Douglas-fir stands are registered as seed stands and provide seed sources for nurseries, although it is unclear from which region in North America they originate. In recent years, the interest in planting Douglas-fir has increased substantially because the species is seen as a potential adaptation option to climate change. This makes the assignment of European Douglas-fir stands of unknown seed origin to their geographic origin in North America increasingly important, because the genetic quality of these plantations must be guaranteed. In this study, we use 13 nuSSR loci to investigate the origin of 67 Austrian and German Douglas-fir stands of unknown origin. We performed a hierarchical Bayesian cluster analysis using 38 native Douglas-fir populations. The resulting clusters are used as reference populations to assign the 67 Central European Douglas-fir stands from Austria and Germany planted more than 80 years ago. Our results suggest that the majority of our investigated Douglas-fir stands come from central Washington (USA), the recommended seed zones for Central Europe. Some stands were located outside the suggested area, e.g. central Oregon and Santa Fe (New Mexico). The accuracy assessment of our approach revealed the best performance for the highest hierarchical level, e.g. assigning populations either to the coastal or the Rocky Mountain variety. As expected, the uncertainty increases with decreasing hierarchical level. The final assessment, if an admixture of seed sources within the European Douglas-fir stands is evident suggests that 23 of the Douglas-fir stands show an admixture which was not detected in our Douglas-fir reference populations growing in the natural distribution range.

E-OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia. However, for studying regional or local climatic effects, a finer resolution would be more appropriate. A continental data set with resolution would allow research that is large in scale and still locally relevant. Until now, a climate data set with high spatial and temporal resolution has not existed for Europe. To fulfil this need, we produced a downscaled version of E-OBS, applying the delta method, which uses WorldClim climate surfaces to obtain a 0.008° (about 1 × 1 km) resolution climate data set on a daily time step covering the European Union. The new downscaled data set includes minimum and maximum temperature and precipitation for the years 1951–2012. It is analysed against weather station data from six countries: Norway, Germany, France, Italy, Austria, and Spain. Our analysis of the downscaled data set shows a reduction in the mean bias error of 3 °C for mean daily minimum temperature and of 4 °C for mean daily maximum temperature. Daily precipitation improved by 0.15 mm on average for all weather stations in the validation. The entire data set is freely and publically available at ftp://palantir.boku.ac.at/Public/ClimateData.

Sustainable forest management requires a continuous assessment of the forest conditions covering the species distribution, standing tree volume as well as volume increment rates. Forest inventories are designed to record this information. They, in combination with ecosystem models, are the conceptual framework for sustainable forest management. While such management systems are common in many countries, no forest inventory system and/or modeling tools for deriving forest growth information are available in Ethiopia. This study assesses, for the first time, timber volume, carbon, and Net Primary Production (NPP) of forested areas in the Amhara region of northwestern Ethiopia by combining (i) terrestrial inventory data, and (ii) land cover classification information. The inventory data were collected from five sites across the Amhara region (Ambober, Gelawdiwos, Katassi, Mahiberesilasse and Taragedam) covering three forest types: (i) forests, (ii) shrublands (exclosures) and (ii) woodlands. The data were recorded on 198 sample plots and cover diameter at breast height, tree height, and increment information. In order to extrapolate the local terrestrial inventory data to the whole Amhara region, a digital land cover map from the Amhara’s Bureau of Agriculture was simplified into (i) forest, (ii) shrubland, and (iii) woodland. In addition, the forest area is further stratified in five elevation classes. Our results suggest that the forest area in the Amhara region covers 2% of the total land area with an average volume stock of 65.7 m3·ha−1; the shrubland covers 27% and a volume stock of 3.7 m3·ha−1; and the woodland covers 6% and an average volume stock of 27.6 m3·ha−1. The corresponding annual volume increment rates are 3.0 m3·ha−1, for the forest area; 1.0 m3·ha−1, for the shrubland; and 1.2 m3·ha−1, for the woodland. The estimated current total volume stock in the Amhara region is 59 million m3.

The ecological impact of continental scale land-use policies that influence forest management is often difficult to quantify. European forest conservation began in 1909 with a marked increase in designated areas with the inception of Natura 2000 in the early 1990s. It has been shown that increases in European forest mortality may be linked to climate variability. Measuring productivity response to climate variability may be a valid proxy indicating a forest&rsquo, s ability to bear this disturbance. Net Primary Production (NPP) response to climate variability has also been linked to functional diversity within forests. Using a European specific annual MODIS NPP estimates, we assess the NPP response to climate variability differences between actively managed forests, which experience human interventions and conserved, Protected Area (PA) forests with minimal to no human impact. We found, on the continental scale, little to no differences in NPP response between managed and conserved forests. However, on the regional scale, differences emerge that are driven by the historic forest management practices and the potential speciation of the area. Northern PA forests show the same NPP response to climate variability as their actively managed counter parts. PA forests tend to have less NPP response to climate variability in the South and in older conserved forests. As the time a forest has been designated, as a PA, extends past its typically actively managed rotation length, greater differences begin to emerge between the two management types.

Scaling is widely recognized as a central issue in ecology. The associated cross-scale interactions and process transmutations make scaling (i.e. a change in spatial or temporal grain and extent) an important issue in understanding ecosystem structure and functioning. Moreover, current concepts of ecosystem stewardship, such as sustainability and resilience, are inherently scale-dependent. The importance of scale and scaling in the context of forest management is likely to further increase in the future because of the growing relevance of ecosystem services beyond timber production. As a result, a consideration of processes both below (e.g. leaf-level carbon uptake in the context of climate change mitigation) and above (e.g. managing for biodiversity conservation at the landscape scale) the traditional focus on the stand level is required in forest ecosystem management. Furthermore, climate change will affect a variety of ecosystem processes across scales, ranging from photosynthesis (tree organs) to disturbance regimes (landscape scale). Assessing potential climate change impacts on ecosystem services thus requires a multi-scale perspective. However, scaling issues have received comparatively little attention in the forest management community to date. Our objectives here are thus first, to synthesize scaling issues relevant to forest management and second, to elucidate ways of dealing with complex scaling problems by highlighting examples of how they can be addressed with ecosystem models. We have focused on three current management issues of particular importance in European forestry: (1) climate change mitigation through carbon sequestration, (2) multi-functional stand management for biodiversity and non-timber goods and services and (3) improving the resilience to natural disturbances. We conclude that taking into account the full spatiotemporal heterogeneity and dynamics of forest ecosystems in management decision-making is likely to make management more robust to increasing environmental and societal pressures. Models can aid this process through explicitly accounting for system dynamics and changing conditions, operationally addressing the complexity of cross-scale interactions and emerging properties. Our synthesis indicates that increased attention to scaling issues can help forest managers to integrate traditional management objectives with emerging concerns for ecosystem services and therefore deserves more attention in forestry.

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp//palantir.boku.ac.at/Public/MODIS_EURO. © 2016 by the authors.

National and international carbon reporting systems require information on carbon stocks of forests. For this purpose, terrestrial assessment systems such as forest inventory data in combination with carbon estimation methods are often used. In this study we analyze and compare terrestrial carbon estimation methods from 12 European countries. The country-specific methods are applied to five European tree species (Fagus sylvatica L.;Quercus robur L.;Betula pendula Roth, Picea abies (L.) Karst.;Pinus sylvestris L.), using a standardized theoretically-generated tree dataset. We avoid any bias due to data collection and/or sample design by using this approach. We are then able to demonstrate the conceptual differences in the resulting carbon estimates with regard to the applied country-specific method. In our study we analyze (i) allometric biomass functions, (ii) biomass expansion factors in combination with volume functions and (iii) a combination of both. The results of the analysis show discrepancies in the resulting estimates for total tree carbon and for single tree compartments across the countries analyzed of up to 140. t. carbon/ha. After grouping the country-specific approaches by European Forest regions, the deviation within the results in each region is smaller but still remains. This indicates that part of the observed differences can be attributed to varying growing conditions and tree properties throughout Europe. However, the large remaining error is caused by differences in the conceptual approach, different tree allometry, the sample material used for developing the biomass estimation models and the definition of the tree compartments. These issues are currently not addressed and require consideration for reliable and consistent carbon estimates throughout Europe. © 2015 Elsevier B.V.

First Online: 07 June 2016; International audience; AbstractKey messageA daily 1-km Pan-European weather dataset can drive the BIOME-BGC model for the estimation of current and future beech gross primary production (GPP). Annual beech GPP is affected primarily by spring temperature and more irregularly by summer water stress.ContextThe spread of beech forests in Europe enhances the importance of modelling and monitoring their growth in view of ongoing climate changes.AimsThe current paper assesses the capability of a biogeochemical model to simulate beech gross primary production (GPP) using a Pan-European 1-km weather dataset.MethodsThe model BIOME-BGC is applied in four European forest ecosystems having different climatic conditions where the eddy covariance technique is used to measure water and carbon fluxes. The experiment is in three main steps. First, the accuracy of BIOME-BGC GPP simulations is assessed through comparison with flux observations. Second, the influence of two major meteorological drivers (spring minimum temperature and growing season dryness) on observed and simulated inter-annual GPP variations is analysed. Lastly, the impacts of two climate change scenarios on beech GPP are evaluated through statistical analyses of the ground data and model simulations.ResultsThe weather dataset can drive BIOME-BGC to simulate most of the beech GPP evolution in all four test areas. Both observed and simulated inter-annual GPP variations are mainly dependent on minimum temperature around the beginning of the growing season, while spring/summer dryness exerts a secondary role. BIOME-BGC can also reasonably predict the impacts of the examined climate change scenarios.ConclusionThe proposed modelling approach is capable of approximately reproducing spatial and temporal beech GPP variations and impacts of expected climate changes in the examined European sites.

Forest degradation due to land use change is a severe problem in Ethiopian Afromontane Forests. We investigated such degradation effects by comparing degraded agricultural land (previously covered with forest) with neighboring natural forests, 40 to 50 years after conversion. We selected four different study areas to cover the eco-climatic conditions of the Amhara region in Northwestern Ethiopia. For a paired-stand comparison we collected soil data on both land use types. We calculated forest biomass to evaluate the biogeochemical-mechanistic ecosystem model Biome-BGC, which is used as a diagnostic tool to assess the site and management impacts on productivity as well as ecosystem carbon and nitrogen accumulation. We applied Biome-BGC to assess rehabilitation options on such degraded land. Afromontane forests in the highlands of Ethiopia showed high soil C stocks, resulting from long lasting biomass accumulation. Removing the tree cover and converting forest areas to crop- or grassland, has led to a loss of 40–85% of the soil C stocks and thus a loss in soil fertility within only 40 to 50 years. Rehabilitation efforts by replanting trees will improve soil fertility, but may require over a thousand years to achieve a similar level in biomass and soil fertility versus the situation prior to the land use change.

The aim of this paper is to determine whether a detectable impact of climate change is apparent in Austrian forests. In regions of complex terrain such as most of Austria, climatic trends over the past 50 years show marked geographic variability. As climate is one of the key drivers of forest growth, a comparison of growth characteristics between regions with different trends in temperature and precipitation can give insights into the impact of climatic change on forests. This study uses data from several hundred climate recording stations, interpolated to measurement sites of the Austrian National Forest Inventory (NFI). Austria as a whole shows a warming trend over the past 50 years and little overall change in precipitation. The warming trends, however, vary considerably across certain regions and regional precipitation trends vary widely in both directions, which cancel out on the national scale These differences allow the delineation of 'climatic change zones' with internally consistent climatic trends that differ from other zones. This study applies the species-specific adaptation of the biogeochemical model BIOME-BGC to Norway spruce (Picea abies (L.) Karst) across a range of Austrian climatic change zones, using input data from a number of national databases. The relative influence of extant climate change on forest growth is quantified, and compared with the far greater impact of non-climatic factors. At the national scale, climate change is found to have negligible effect on Norway spruce productivity, due in part to opposing effects at the regional level. The magnitudes of the modeled non-climatic influences on aboveground woody biomass increment increases are consistent with previously reported values of 20-40emsp14;kg of added stem carbon sequestration per kilogram of additional nitrogen deposition, while climate responses are of a magnitude difficult to detect in NFI data.