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Humans require multiple services from ecosystems, but it is largely unknown whether trade‐offs between ecosystem functions prevent the realisation of high ecosystem multifunctionality across spatial scales. Here, we combined a comprehensive dataset (28 ecosystem functions measured on 209 forest plots) with a forest inventory dataset (105,316 plots) to extrapolate and map relationships between various ecosystem multifunctionality measures across Europe. These multifunctionality measures reflected different management objectives, related to timber production, climate regulation and biodiversity conservation/recreation. We found that trade‐offs among them were rare across Europe, at both local and continental scales. This suggests a high potential for ‘win‐win’ forest management strategies, where overall multifunctionality is maximised. However, across sites, multifunctionality was on average 45.8‐49.8% below maximum levels and not necessarily highest in protected areas. Therefore, using one of the most comprehensive assessments so far, our study suggests a high but largely unrealised potential for management to promote multifunctional forests.

In view of the economic, social and ecological importance of Canada's forest ecosystems, there is a growing interest in studying the response of these ecosystems to climate change. Accurate knowledge regarding growth trajectories is needed for both policy makers and forest managers to ensure sustainability of the forest resource. However, results of previous analyses regarding the sign and magnitude of trends have often diverged. The main objective of this paper was to analyse the current state of scientific knowledge on growth and productivity trends in Canada's forests and provide some explanatory elements for contrasting observations. The three methods that are commonly used for assessments of tree growth and forest productivity (i.e. forest inventory data, tree-ring records, and satellite observations) have different underlying physiological assumptions and operate on different spatiotemporal scales, which complicates direct comparisons of trend values between studies. Within our systematic review of 44 peer-reviewed studies, half identified increasing trends for tree growth or forest productivity, while the other half showed negative trends. Biases and uncertainties associated with the three methods may explain some of the observed discrepancies. Given the complexity of interactions and feedbacks between ecosystem processes at different scales, researchers should consider the different approaches as complementary, rather than contradictory. Here, we propose the integration of these different approaches into a single framework that capitalizes on their respective advantages while limiting associated biases. Harmonization of sampling protocols and improvement of data processing and analyses would allow for more consistent trend estimations, thereby providing greater insight into climate-change related trends in forest growth and productivity. Similarly, a more open data-sharing culture should speed-up progress in this field of research.

The importance of biodiversity in supporting ecosystem functioning is generally well accepted. However, most evidence comes from small-scale studies, and scaling-up patterns of biodiversity-ecosystem functioning (B-EF) remains challenging, in part because the importance of environmental factors in shaping B-EF relations is poorly understood. Using a forest research platform in which 26 ecosystem functions were measured along gradients of tree species richness in six regions across Europe, we investigated the extent and the potential drivers of context dependency of B-EF relations. Despite considerable variation in species richness effects across the continent, we found a tendency for stronger B-EF relations in drier climates as well as in areas with longer growing seasons and more functionally diverse tree species. The importance of water availability in driving context dependency suggests that as water limitation increases under climate change, biodiversity may become even more important to support high levels of functioning in European forests.

The importance of biodiversity in supporting ecosystem functioning is generally well accepted. However, most evidence comes from small‐scale studies, and scaling‐up patterns of biodiversity–ecosystem functioning (B‐EF) remains challenging, in part because the importance of environmental factors in shaping B‐EF relations is poorly understood. Using a forest research platform in which 26 ecosystem functions were measured along gradients of tree species richness in six regions across Europe, we investigated the extent and the potential drivers of context dependency of B‐EF relations. Despite considerable variation in species richness effects across the continent, we found a tendency for stronger B‐EF relations in drier climates as well as in areas with longer growing seasons and more functionally diverse tree species. The importance of water availability in driving context dependency suggests that as water limitation increases under climate change, biodiversity may become even more important to support high levels of functioning in European forests.

Fine roots (diameter ≤ 2 mm) contribute significantly to the forest carbon cycle and are essential for resource acquisition from the soil. We conducted a study to assess the relationships between tree and ground vegetation fine root biomass and tree species diversity (monocultures compared to 2–5 species mixtures), conifer proportion and other site factors (stand basal area, soil carbon stocks and C:N ratio) in the six major European forest types, boreal forest in Finland, temperate forests in Poland, Germany and Romania, thermophilous deciduous forests in Italy, and Mediterranean forests in Spain. We sampled the fine roots of trees and ground vegetation to the depth of 20 cm in the mineral soil and allocated the fine root biomass to individual tree species using near-infrared reflectance spectroscopy (NIRS). We did not find any general positive effects of tree species diversity on the fine root biomass of trees or ground vegetation across the forest types and tree species combinations. However, our results suggest that tree fine root biomass increases with tree species diversity in pure broadleaf forests, but not in pure conifer forests. Species diversity explained 7% of the variation in tree fine root biomass in the broadleaf stands. The narrow tree species diversity gradient (1–2 species) in the conifer forests compared to the broadleaf forests (1−4) may have decreased the probability of conifer species combinations with below-ground functional traits conducive to over-yielding. Some evidence of diversity-mediated changes in the vertical rooting patterns of broadleaf trees and ground vegetation were found within the entire organic and 0–20 cm mineral soil layer although the weighted mean depth of fine root biomass was not affected. Negative diversity effects were found in the organic layer and positive diversity effects in the 0–10 cm mineral soil layer for broadleaf tree fine root biomass. Diversity effects were negative for ground vegetation fine root biomass i

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.

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.

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.

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. and 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., SCOPUS: ar.j, iiTSE, info:eu-repo/semantics/published

info:eu-repo/semantics/inPress