Suchergebnisse

Forest management planning is increasingly relying on airborne laser scanning (ALS) in forest inventory. The area-based method to interpret ALS data requires sample plots measured in the field. The aim of this study was to assess and trace the impacts of the positioning errors of field plots along the entire forest management planning process, from their effect on forest inventory results to the outcome of forest management planning. This research links plot positioning errors with the spatio-temporal allocation of forest treatments and calculates the inoptimality losses arising from plot positioning errors in ALS-based forest inventory. The study area was a forest management unit in Central Spain. Growing stock attributes were predicted for a grid of square-shaped cells. Alternative management schedules were simulated for the grid cells by using growth and yield models. Then, a spatial forest planning problem aiming at maximizing timber production with even-flow cuttings was formulated. Spatial objective variables were used to cluster management prescriptions into dynamic treatment units. We used simulated annealing to conduct spatial optimization. First, the true plot locations were used and then the whole process was repeated with normally distributed random errors with standard deviation equal to 2.5, 5 and 10 m, resulting in an average error of 1.47, 3.06 and 8.34 m, respectively. Increasing the level of positioning errors resulted in higher variability in the estimated growing stock attributes and in the achieved values of management goals. Sub-optimal prescriptions caused by the tested plot positioning errors caused up to 4.62% losses in timber production and up to 3.35% losses in utility. The losses increased with increasing plot positioning error. ; This research was funded by the University of Eastern Finland, School of Forest Sciences and research consortium projects FORBIO (proj. 14970) and ADAPT (proj. 14907), funded by the Academy of Finland and led by Heli Peltola, at the School of Forest Sciences, University of Eastern Finland (UEF). Sergio de-Miguel was funded by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No. 655815)

Purpose of Review: The increased popularity and commercial use of non-timber forest products (NTFPs) calls for the development of models for NTFPs to include their predicted yields in forest management planning and to evaluate the potential of multi-functional forest management. This study assesses and discusses the current state of the art and trends in NTFP yield modelling in Europe and the integration of the models in multi-functional forest management planning at different spatial scales. Recent Findings: Climate-sensitive empirical yield models already exist not only for a variety of NTFPs that are economically important to forest owners (e.g. cork and pine nuts) but also for wild-gathered berries and mushrooms, the harvesting of which cannot be controlled by the forest landowner in all European countries. Several studies on multi-functional forest management planning consider the economic profitability of the joint production of timber and NTFP. Harvesting NTFPs can create significant additional incomes for forest owners, compared with timber production only. However, maximizing the economic returns from the joint production of timber and NTFPs often calls for changes in forest management practices. Summary: Continued efforts in modelling and predicting the yields of NTFPs have enabled forest managers to further expand the analyses of multi-functional forest planning and management in Europe. Climate-sensitive models also allow analyses on the potential effects of climate change on NTFP yields. New models and forest management practices are still needed for tree fruits, birch sap, a wider variety of wild edible mushrooms, specialty mushrooms cultivated on live trees as well as medicinal and edible forest herbs harvested for commercial value in Europe. ; Open access funding provided by Natural Resources Institute Finland (LUKE). Jari Miina and Mikko Kurttila have received part of their salaries from a project that was funded by Natural Resources Institute Finland (Luke). Rafael Calama acknowledges support from PROPINEA agreement CC16-095. Sergio de-Miguel acknowledges support from the project with grant number RTI2018-099315-A-I00, funded by the Spanish Ministry of Science, Innovation and Universities, Government of Spain. Rafael Calama and Sergio de-Miguel acknowledge the project Innovation Networks of Cork, Resins and Edibles in the Mediterranean basin (INCREDIBLE) funded by the European Commission's Horizon 2020 programme under grant agreement N° 774632.

The purpose of this study was to assess the effect of using alternative types of forest inventory units (FIUs) in multi-objective forest planning. The research was carried out in a Mediterranean forest area in central Spain. The study area was divided, alternatively, into pixels (square cells) and segments of two different sizes (small and large), which represented the tested FIU types. Airborne laser scanning data (ALS) and field sample plots were combined using the area-based approach to estimate forest attributes for each FIU. Dynamic treatment units were created using cellular automaton optimization aiming at maximizing timber production during a 60-year plan with periodical even-flow cuttings both with and without the aim of creating aggregated harvest blocks. The hypothesis was that the use of segments would enhance the clustering of harvests, as compared to cells, and provide dynamic treatment units more suitable for forestry practice. The results showed that segment-based planning created compact harvest blocks even without the use of spatial objective variables in optimization. The spatial layout of the solution for large segments was the most efficient in the absence of spatial objective variables. The FIU type that performed the best in maximizing timber production was the small segments. For the three tested FIU types, the inclusion of spatial objective variables further improved the clustering of harvests, especially during the latter half of the 60-year planning period. Segmentation acted as a first-phase clustering that made spatial optimization easier and faster. In the case of square cells, the clustering of harvests was greatly improved by the inclusion of spatial goals. The forest planning system and the spatial optimization method proposed in this study maximize the utility of fine-grained ALS data. ; Open access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital. This research was supported by the University of Eastern Finland, School of Forest Sciences and research consortium projects FORBIO (Proj. 14970) and ADAPT (Proj. 14907), funded by the Academy of Finland and led by Prof. Heli Peltola, at the School of Forest Sciences, University of Eastern Finland (UEF). Sergio de-Miguel was supported by the European Union's Horizon 2020 MultiFUNGtionality Marie Sklodowska-Curie (IF-EF No 655815).

Aim of study: To analyze the influence of harvesting costs on the distribution and type of cuttings when forest management planning is based on the dynamic treatment units (DTUs) approach. Area of study: A Mediterranean pine forest in Central Spain. Materials and methods: Airborne laser scanning data were used in area-based approach to predict stand attributes and delineate segments that were used as calculation units. Predicted stand attributes and existing models for diameter distribution and individual-tree growth were used to simulate alternative management schedules for each segment for a 60-year planning horizon divided into three 20-year periods. Three alternative forest planning problems were formulated. They aimed to maximize or minimize net income, or maximize timber production with a constant flow of harvested timber. Spatial goals were used in all cases to enhance the clustering of treatments. Main results: Maxizing timber production without considering harvesting costs can be costly, even close to the plan that minimized net incomes. Maximizing net incomes led to frequent use of final felling instead of thinnings, placing cuttings near forest roads and creating more compact DTUs than obtained in the plan that maximized timber production. Research highlights: Compared to previous studies on DTUs, this study integrated felling and forwarding costs, which depended on distance to road and stand attributes, in the process of creating DTUs by means of spatial optimization. ; University of Eastern Finland; Academy of Finland (projects FORBIO-14970 and ADAPT-14907); European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No 655815 to SdM).

Fungal fruit-bodies are an important economic resource both for recreational pickers and commercial markets. The broad interest in forest fungi and mushrooms has motivated attempts to develop appropriate silvicultural methods able to preserve and improve mushroom yields. Defining best practices for the sustainability and profitability of forest fungal resources is the main aim of 'mycosilviculture'. However, the difficulty of monitoring and studying such a cryptic kingdom (i.e., fungi) under real forest conditions has led to rather scattered scientific knowledge of the effects of forest management regimes and silvicultural operations on wild mushroom resources. Here, we review the current scientific literature regarding the influence of (i) stand characteristics, i.e. stand age, stand density, canopy cover and tree species composition, (ii) silvicultural practices and (iii) other management-related disturbances affecting the yield of wild epigeous mushrooms, with the aim of systematizing existing scientific knowledge and identifying gaps in knowledge in order to suggest future lines of research. Most of the research in the field of mycosilviculture to date has focused on ectomycorrhizal mushrooms, which include the majority of wild commercial mushrooms. The main findings from the literature indicate that forest management practices, by modifying stand characteristics and microclimatic conditions, can influence wild mushroom occurrence and productivity, both positively and negatively, depending on the specific fungal ecological needs, reproductive strategies, forest type and management regime. Further research efforts relating to all aspects of the interaction between forest management, fungal ecology and mushroom production are needed: in particular, additional research efforts should be devoted to understanding mushroom yield dynamics in unevenaged and mixed forests and evaluating the effects of regeneration methods on fungal communities. ; The review was carried out within the COST Action FP1203 (European Non-Wood Forest Products). Sergio de-Miguel was supported by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No-655815) and José Antonio Bonet benefited from a Serra-Hunter Fellowship provided by the Generalitat of Catalunya. The study was also partially funded by the Spanish research project AGL2015-66001-C3-1-R (MEC Spain) and by the European project StarTree (No. 311919).

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns. ; This study was funded by the Spanish research projects AGL2012-40035-C03-01 and AGL2015-66001-C3-1-R (MEC Spain) and by the European project StarTree (No. 311919). JGA was supported by Juan de la Cierva-fellowship (IJCI-2014-21393) and DYMECO project and SdM by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No. 655815) and JAB benefit from Serra-Hunter Fellow provided by the Generalitat of Catalunya.

Background: The prediction of biogeographical patterns from a large number of driving factors with complex interactions, correlations and non-linear dependences require advanced analytical methods and modeling tools. This study compares different statistical and machine learning-based models for predicting fungal productivity biogeographical patterns as a case study for the thorough assessment of the performance of alternative modeling approaches to provide accurate and ecologically-consistent predictions. Methods: We evaluated and compared the performance of two statistical modeling techniques, namely, generalized linear mixed models and geographically weighted regression, and four techniques based on different machine learning algorithms, namely, random forest, extreme gradient boosting, support vector machine and artificial neural network to predict fungal productivity. Model evaluation was conducted using a systematic methodology combining random, spatial and environmental blocking together with the assessment of the ecological consistency of spatially-explicit model predictions according to scientific knowledge. Results: Fungal productivity predictions were sensitive to the modeling approach and the number of predictors used. Moreover, the importance assigned to different predictors varied between machine learning modeling approaches. Decision tree-based models increased prediction accuracy by more than 10% compared to other machine learning approaches, and by more than 20% compared to statistical models, and resulted in higher ecological consistence of the predicted biogeographical patterns of fungal productivity. Conclusions: Decision tree-based models were the best approach for prediction both in sampling-like environments as well as in extrapolation beyond the spatial and climatic range of the modeling data. In this study, we show that proper variable selection is crucial to create robust models for extrapolation in biophysically differentiated areas. This allows for reducing the dimensions of the ecosystem space described by the predictors of the models, resulting in higher similarity between the modeling data and the environmental conditions over the whole study area. When dealing with spatial-temporal data in the analysis of biogeographical patterns, environmental blocking is postulated as a highly informative technique to be used in cross-validation to assess the prediction error over larger scales. ; This work was supported by the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund. This work was partially supported by the Spanish Ministry of Science, Innovation and Universities (Grant No. RTI2018–099315-A-I00). J.A.B. benefitted from a Serra-Húnter Fellowship provided by the Government of Catalonia.

Fungi are responsible for many of the processes that occur in natural ecosystems and largely determine forest ecosystem dynamics, such as the ability of trees to access limiting nutrients and sequester carbon. Understanding and predicting climate change impacts on fungal dynamics over large scales is key in order to gain further insights into the effects of global change on natural ecosystem functioning and related ecosystem services. In this study, we use predictive models based on machine learning algorithms to estimate, in a spatially explicit way, the historical and future (1976–2100) evolution of mycorrhizal and saprotrophic macrofungal productivity in Mediterranean forest areas under climate change scenarios. The greatest changes in total productivity, as well as mycorrhizal fungi, are predicted to occur in subalpine and montane pine forests, where fungal productivity is estimated to decrease, and will be more pronounced under climate change scenarios with higher expected increase in temperature. In contrast to mycorrhizal species, saprotrophic fungi could benefit from pronounced changes in climate and increase their productivity in supra- and mesomediterranean regions at mid-range elevations. Moreover, we estimated that fungal productivity has also changed historically in some scattered areas where changes in climate over the years may have led to a decrease in productivity. This study contributes to raising awareness on the need for anticipating potential global change impacts on this key element of ecosystem functioning, and for deploying possible management policies oriented toward maintaining the important role of fungal productivity in both climate change mitigation and adaptation. ; We thank the "Agencia Estatal de Meteorología (AEMET)" and "Servei Meteorològic de Catalunya (SMC)" for providing daily weather station data. This work was supported by the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund. This work was ...

Wild mushrooms contribute to a variety of ecosystem services. The expected warmer and drier conditions for the Mediterranean region as a consequence of climate change, are raising concerns about future mushroom productivity due to potential reduction of soil water availability for fungi. The aim of this study was to increase our understanding of the interaction between climate and soil moisture in relation to their impact on mushroom productivity in Mediterranean forests. Mushroom yield data were obtained from 28 permanent mushroom inventory plots intensively monitored in Maritime pine (Pinus pinaster Ait.) stands of northeastern Iberian Peninsula. Annual productivity of total, edible and marketed mushrooms was obtained from measurements conducted every week during the autumn fruiting season for years 2008–2015. Historical weather conditions were obtained through data interpolation from meteorological stations. Soil moisture data were obtained from continuous plot-level measurements. A process-based soil water balance model was used to predict soil moisture under two climate change scenarios, using the predictions of two different regional climate models. Mixed-effects models using either precipitation or soil moisture as predictors, in combination with other weather variables, were fitted to annual mushroom occurrence and yield data. Mushroom yield was primarily dependent on weather and soil moisture conditions during the same month, with the exception of precipitation, whose effects exhibited a one-month delay. High temperatures limited mushroom yield at the beginning of the fruiting season, but tended to enhance it towards the end. The analysis revealed no apparent negative effect of climate change on long-term mushroom productivity, but rather the opposite (i.e., predicted median productivity of marketed mushrooms for 2016–2100 was 23–93% higher compared to the current yield), mainly due to an elongation of the fruiting season arising from the combined effect of increased precipitation at the beginning of the season and warmer temperatures at the end. ; This work benefited from the Erasmus Mundus Master Program MEDFOR (Mediterranean Forestry and Natural Resources Management) which provided a scholarship to the first author. Sergio de Miguel was supported by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie (IF-EF No 655815), Miquel De Cáceres benefited from a Ramon y Cajal fellowship (RYC-2012-11109), and José Antonio Bonet benefited from a Serra-Húnter Fellowship provided by the Generalitat of Catalunya. Additional funding came from the research projects MYCOSYTEMS (AGL2015-66001-C3-1-R − MEC Spain) and FORESTCAST (CGL2014- 59742-C2-2-R), and from the European project StarTree (No. 311919). Special thanks to Mr. Antoine Cabon for his assistance with R software.

Integrating fungal-based ecosystem services into forest management planning and policy-making requires quantitative knowledge of the yields of fungal sporocarps and their environmental drivers. The aim of this study was to predict edible mushroom yield in Pinus pinaster forests of Central Spain, based on a 17-year data series. Two-stage mixed-effects models were used to examine the effect of predictors on mushroom occurrence and yield separately with the aim of providing further insight into the ecological system. Changes in seasonal precipitation represented the main weather-related driver affecting sporocarp emergence and production, since they were both positively influenced by late summer and early autumn precipitation. Soil acidity positively influenced Lactarius yield. Stand age and sandy soils showed a negative influence on mushroom production. The diversity of drivers became more apparent at the fungal species level. The models can be used for predicting the production of edible fungi under different meteorological and site conditions. ; This study was partially funded by the research projects AGL2012-40035-C03-01 and AGL2012-40035-C03-03 (Ministerio de Economía y Competitividad of Spain, Secretaría de Estado de Investigaci on, Desarrollo e Innovaci on), by the Micosylva þ project (Interreg IVB SUDOE SOE3/P2/E533), and by the Mycological Programme of Castilla y Leon (www.micocyl.es). This study also received funding from the European Union's Horizon 2020 research and innovation programme within the framework of the Multi- FUNGtionality Marie Skłodowska-Curie Individual Fellowship (IFEF) under grant agreement No 655815. This work further benefited from the Erasmus Mundus Master Course MEDFOR (Mediterranean Forestry and Natural Resources Management) (520137-1-2011-1- PT-ERA MUNDUS-EMMC), which provided one scholarship to Mr. Zelalem Mengiste Taye. The inventory and monitoring of the sample plots was funded by Junta de Castilla y Leon and ADEMA from 1997 to 2007, and by Junta de Castilla y Leon and CESEFOR from 2007 to 2014.

Fungi provide important forest ecosystem services worldwide. In Mediterranean pine forests, predicted warmer and drier conditions could lead to a decline in mushroom yields. Climate is a key factor regulating both tree growth and fungal yields, particularly in drought-prone Mediterranean ecosystems. However, the responses of forest growth and mushroom production to climate depend on the differences among tree and fungal species and functional groups (e.g., mycorrhizal vs. saprotrophic), forest types, as well as depending on site conditions. Here we investigate how climatic conditions drive seasonal wood formation (earlywood −EW− and latewood −LW− production) and mycorrhizal mushroom production, to disentangle if growth and fungal yields are related. This assessment was done in Mediterranean forests dominated by four pine species in two areas located in Catalonia (NE Spain) representing mesic and xeric conditions and encompassing wide ecological gradients. The data consisted of 7-year to 13-year long inventories of mushroom production. EW production was favoured by cold and wet climate conditions during the previous fall and winter, and during the current spring and summer. LW production was enhanced by warm and humid conditions from spring to early fall. Mushroom yield was improved by wet late-summer and fall conditions, mainly in the most xeric area. This study confirms the ample differences found in tree growth and fungal production along ecological and climatic gradients. Clear relationships between mycorrhizal fungal yields and tree growth were mostly observed in specific sites characterized by severe summer drought. Specifically, latewood production seems to be the tree-ring variable most tightly linked to mycorrhizal fungal yield in drought-prone areas. ; This study was partially funded by the research projects AGL2012-40035-C03-01 and AGL2015-66001-C3-1-R (Ministerio de Economía y Competitividad of Spain, Secretaría de Estado de Investigación, Desarrollo e Innovación), by the European project "StarTree—Multipurpose trees and non-wood forest products: a challenge and opportunity" under grant agreement No. 311919. Irantzu Primicia work was supported by a STSM Grant from the COST Action FP1203 (European Non-Wood Forest Products). Sergio de Miguel's work was supported by the European Union's Horizon 2020 research and innovation programme within the framework of the MultiFUNGtionality Marie Skłodowska-Curie Individual Fellowship (IF-EF) under grant agreement No 655815.

The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation. ; We thank to the volunteers fromthe Catalan Ornithological Institute (ICO) and Dr. Miquel de Cáceres Ainsa for providing data for the analyses presented in this study. Funding was obtained from the Catalan Office for Climate Change (OCCC) through project ForESMap, from EU FORESTERRA program (INFORMED project) and from the Spanish government (CGL2013-46808-R and AGL2015-66001-C3-1-R). JVRD was supported by the Government of Asturias and the FP7-Marie Curie- COFUND program of the European Commission (Grant 'Clarín' ACA17- 02). We also thank the ECOMETAS (CGL2014-53840-REDT) network for support. This study also received funding fromthe European Union's Horizon 2020 research and innovation programme within the framework of the MultiFUNGtionality Marie Skłodowska-Curie Individual Fellowship (IF-EF) under grant agreement No. 655815 and from the Generalitat de Catalunya (Serra-Hunter Fellow grant number UdL-AG-203). We thank Gabriel Borras and Gemma Cantos (OCCC) for useful discussion during the elaboration of this work. We are very grateful to all persons who made the two Spanish Forest Inventories possible and, especially, to their main coordinators, Ramon Villaescusa (IFN2) and Jose Antonio Villanueva (IFN3). We also thank two anonymous reviewers who helped us improve the quality of the manuscript.

Predicted changes in global climate might negatively affect the soil microbiome and associated ecosystem processes in Mediterranean forests. Forest treatments, such as forest thinning, have been suggested to mitigate climate change impacts on vegetation by reducing competition between trees, thus increasing water availability. Studies addressing the combined effects of climate and forest thinning on belowground fungal communities are still scarce, being fundamental to elaborate adaptive strategies to global warming. The aim of this study was to evaluate the tree density reduction effects on soil fungal communities and their response to inter-annual changes in weather conditions. The temporal dynamics of soil fungal communities in relation to these two drivers (i.e., forest management and weather conditions) were studied from 2009 until 2014 in a set of 12 pairs of thinned and un-thinned plots dominated by Pinus pinaster Ait. Thinning (from 30% up to 70% reduction in stand basal area) was conducted in 2009 and soil fungal community composition was studied during 4 years. Here, we used autumn precipitation and temperature to describe the impact of inter-annual weather changes. We used Pacific Biosciences sequencing of fungal ITS2 amplicons to study fungal communities in soil samples. Forest thinning did not significantly affect fungal community composition nor fungal species richness and diversity, indicating that the soil fungal community is resistant to forest thinning regardless of its intensity. However, fungal species composition changed progressively across years, both at the species level and with regards to functional guilds. These changes in community composition were partly driven by inter-annual variation in precipitation and temperature, with free-living fungi increasing in abundance under wetter conditions, and symbiotic fungi being more prominent under drier and colder conditions. The results indicate that mycorrhizal communities in Mediterranean forest ecosystems can resist forest thinning, if enough trees and functional roots from thinned trees are retained. ; This work was supported by the Spanish Ministry of Economy and Competitivity (MINECO) [grant number AGL2015-66001-C3] and by the Collaborative European project ERANET-INFORMED (PCIN-2014-050). Carles Castaño received the support of the Doctorats Industrials program, funded by the European Union and the European Social Fund. Sergio de-Miguel was supported by the European Union's Horizon 2020 MultiFUNGtionality Marie Skłodowska-Curie [Grant number IF-EF No-655815]. Josu G. Alday was supported by Ramon y Cajal fellowship [Grant number RYC-2016-20528] and José Antonio Bonet benefited from a Serra-Húnter Fellowship provided by the Generalitat of Catalunya. The authors are very grateful to the PNIN of Poblet for its considerable help with the process of installing and maintaining the experimental plots. We thank Liu Bing, Daniel Oliach, Francesc Bolaño, Jordi Margalef, Josep Miró and Jewel Yurkewich for their assistance with sampling the plots and processing the samples. The constructive comments and suggestions of two anonymous reviewers were improved substantially this manuscript.

Forest ecosystems provide a wide range of goods and services to society and host high levels of biodiversity. Nevertheless, forest ecosystem services (ES) are often quantified and assessed using simplified methodologies (e.g., proxy methods based exclusively on Land Use Land Cover maps) that introduce substantial uncertainty in the analysis by ignoring, for instance, the species composition and spatial configuration of the ecosystems studied. In this work we defined and calculated a set of 12 indicators of several ES for the forests of the highly populated region of Catalonia (North-eastern Iberian Peninsula). The indicators combined different sources of information such as forest surveys, ecological model predictions and official statistics, but also included additional land cover information. All ES indicators were aggregated at the municipality level to compare their values and distribution patterns. We assessed spatial trade-offs and synergies among ES, as well as their relationships with a set of socioeconomic, climatic and biodiversity variables using correlation analyses and mixed-effects models. The results suggest a clustering of provisioning and regulating ES in mountainous zones towards the North of the study area. These two types of services showed a high degree of spatial similarity and presented high positive correlations. In contrast, cultural ES showed a more scattered pattern, which included lower elevation areas in the South of the study region. Climatic conditions were the main determinants of the spatial variability in the supply of the different ES, with most indicators being positively associated with precipitation and negatively associated with temperature. In addition, biodiversity (particularly woody species richness) showed positive relations with most of these ES, while socioeconomic variables (such as population density and the percentage employment in agriculture) showed negative associations with most of them. The combination of information from different data sources (including primary data) allowed for a detailed analysis of forest ES, likely removing some of the problems derived from approaches based only on proxy methods. In addition, the use of municipalities as study unit makes results directly relevant to management and planning strategies operating at this scale (e.g., forest management and planning). ; Funding was obtained from the Catalan Office for Climate Change (OCCC) through project ForESMap, from EU FORESTERRA program (INFORMED project) and from the Spanish government (CGL2013-46808-R, AGL2015-66001-C3-1-R and CGL2014-59742). We also thank the ECOMETAS (CGL2014-53840-REDT) network for support. This study also received funding from the European Union's Horizon 2020 research and innovation programme within the framework of the MultiFUNGtionality Marie Skłodowska-Curie Individual Fellowship (IF-EF) under grant agreement No655815 and from the Generalitat de Catalunya (Serra-Hunter Fellow). JVRD was supported by the Government of Asturias and the FP7-Marie Curie-COFUND program of the European Commission (Grant 'Clarín' ACA17-02).

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year −1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year −1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year −1 ) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink ; This study was funded by NASA Interdisciplinary Science Program (NNH16ZDA001N-IDS). M.L. and Y. Yang have been supported by the NASA Postdoctoral Program, administered by Universities Space Research Association under contract with NASA.G.-J.N. was supported by the European Union H2020-VERIFY project (776810).