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Background The aim of this contribution is to analyze the forest carbon budget development following the recent historically unprecedented dieback of coniferous stands in the Czech Republic. The drought-induced bark-beetle infestation resulted in record-high sanitary logging, turning the Czech forestry from a long-term carbon sink offsetting about 6% of the country's greenhouse gas (GHG) emissions since 1990 to a significant source of CO2 emissions in recent years (2018–2021). In 2020, the forestry sector accounted for almost 10% of the country's overall GHG emissions. Using the nationally calibrated Carbon Budget Model of the Canadian Forest Sector at a regional spatial resolution, we analyzed the trend and scenarios of forest carbon budget development until 2070. Two critical points arise: the short-term prognosis for reducing current emissions from forestry and the implementation of adaptive forest management focused on tree species change and sustained carbon accumulation. Results This study used four different scenarios to assess the impact of adaptive forest management on the forest carbon budget and CO2 emissions, tree species composition, harvest possibilities, and forest structure in response to the recent calamitous dieback in the Czech Republic. The model analysis indicates that the Czech forestry may stabilize by 2025, or at the latest, by the end of this decade. Subsequently, it may become a sustained sink of about 3 Mt CO2 eq./year (excluding contribution of harvested wood products), while enhancing forest resilience by the gradual implementation of necessary adaptation measures that ensure the provision of all expected forest functions to society. The speed of adaptation is linked to harvest intensity and severity of the current calamity. Under the most severe black scenario, the proportion of unstable spruce stands declines from the current 43% to approximately 25% by 2070, in favor of more suited tree species such as fir and broadleaves. These species would also constitute about 50% of the harvest potential, while maintaining levels generated by the Czech forestry prior to the current calamity. Conclusion The results show progress of stabilizing CO2 emissions, implementing tree species change, and quantifying the expected harvest and mitigation potential in Czech forestry until 2070.

Tree functional strategies play a crucial role regulating the fitness and ability of forests to cope with water stress. However, current understanding on community-level functional strategies of forest ecosystems and how they vary with geographic patterns is still limited. We combined eight functional traits (e.g. leaf nitrogen content, xylem conductivity, leaf area to sapwood area ratio, leaf mass area, xylem water potential at 50% loss of conductivity, slope for the curve between P50-P88, leaf turgor loss point and wood density) with forest inventory data across the USA and Europe (12,332 0.25° gridcells) to identify functional strategies with respect to water stress and to analyse their relationships with climate factors and across functional groups. Principal components analysis suggests that functional strategies at species-level could be captured at community-level. Acquisitive-conservative strategies loaded along the first dimension, while the water storage and isohydricity strategies loaded along the second dimension. Spatial patterns of community-level strategies showed more explanatory power with temperature than aridity. Multiple community-level strategies at a grid cell were observed at water-limited sites, which were broadly captured by broad functional groups based on leaf type and phenology. Our findings promote the understanding of forest adaptation to drought and provide a basis for improving the ability of ecosystem models to predict the patterns of tree mortality and forest biomass accumulation.

Effect of drought during 2017 and 2018 resulted in radial stem increment reduction to 78% and 61%, respectively, of the levels occurring in normal year 2016 in Central Europe. Norway spruce (Picea abies (L.) Karst.) is currently the most threatened commercial tree species in Central Europe. This is due to increased drought stress from advancing climate change as well as the species’ distribution outside its natural range. Tree water status and water movement through a tree are key parameters influencing tree growth and vitality. This study is focused on the growth and stress reaction of spruce to climatic conditions, analysing stem diameter variation along an elevation gradient (381–995 m a.s.l.) in the Czech Republic. Tree water deficit based on the zero-growth concept (TWD), calculated from high-frequency dendrometer records and the temporal dynamics of radial growth, was studied for 3 years (2016–2018). Two of these 3 years were affected by severe drought during the growing season. Contrary to our expectations, the observed TWD showed no clear linear decline with rising elevation. The most severe tree desiccation was observed in experimental sites at middle elevations of about 600 m a.s.l. Here, we show that both the timing and level of tree water deficit had an impact on annual stem radial increment (SRIannual). Severe drought had a substantial negative impact on SRIannual of Norway spruce in both 2017 and 2018. Drought conditions in 2017 and 2018 resulted in reduction of SRIannual relative to measurements for the wetter year in 2016 to 78% and 61%, respectively. We report the evidence that the current climatic conditions in the Central European region are not suitable for growing Norway spruce at lower and middle elevations and that forest management needs to react immediately to this situation.

Forests in Europe have been modified by centuries of intensive land use, substantially influencing forest dynamics and biomass stocks, as well as forest interactions with climate. This makes the accounting for forest management crucial in any large-scale analysis of forest ecosystems, including the estimation of the forest carbon sink dynamics. However, the realistic representation of management in projection models is still hindered by the availability of data. To fill this gap, we analyzed recent forest harvest information in permanent plots of national forest and landscape inventories in several European countries. We used the harvest status information of individual trees between two measurements to characterize probability of different types of harvest events (partial cut vs removal of all trees), harvest intensity and characteristics of harvested trees on a plot level. These results were aggregated to a spatial grid, catching variations on sub-national scale. We then quantified the relationships of harvest events and their properties with potential predictors, including pre-harvest status of the forest (e.g., stand basal area, species and size structure of trees) and climatic, abiotic and socio-economic variables. The results reveal the variation in how forests are currently managed across the continent, with the differences stemming from different climatic and ecological conditions as well as different histories, priorities and goals of forest use and management. For example, the prevalence of even-aged rotation forestry with clear cuts in northern Europe is captured in the results as higher intensities of harvest events and higher probabilities for removing all trees. The results provide a realistic quantification of the current forest harvesting regimes across Europe, providing much needed detail in our understanding of contemporary management practices and a finer spatial resolution compared to existing data sources, such as national-level harvest statistics.

Afforestation has been a popular restoration procedure for spoil heaps in the sites affected by coal open-cast mining in the Czech Republic. Forest replantation is a frequent restoration variant when spoil heaps are recovered, but unreclaimed sites are often left to spontaneous succession. Studies on the dynamics of such restored forests are missing, and the evidence of restored forests with respect to their recreation value is also sporadic. To study the dynamics and management of restored forests—both replanted and recovered by spontaneous succession—on spoil heaps, we used a matrix growth model, which accounts for harvest, artificial and natural regeneration, and recreation value of these forest stands. The model calibration was performed on data from 250 inventory plots distributed across the Velká Podkrušnohorská spoil heap and the Matyáš spoil heap in the Sokolov brown-coal mining area. The growth model was applied on six restored forest types to simulate—over 65 years with a 10-year cutting cycle—the effect of various management regimes of thinning on their recreation value and aboveground biomass (AGB). The results indicate that initial planting density and stand type have an effect on the dynamics of restored forest stands in the short-term horizon. Applying the thinning management resulted in an increase in recreation value for all types of restored stands, while AGB decreased.

Forestry in the Czech Republic is facing a historically unprecedented, mostly drought-induced decline in spruce-dominated stands, accompanied by an extensive bark beetle infestation that has spread across most of the country. As a result, the share of sanitary felling has dramatically increased, driving the total harvest to record-high levels in recent years. As a result, current forest management in the country practically resembles a crisis management dealing dominantly with unplanned disturbances. The Czech case shows clearly the essential, non-separable linkage between forest adaptation and mitigation––a simple recognition that, without adaptation, there is no mitigation. It also demonstrates the importance of tailoring the general climate smart forestry approach to regional circumstances. The current priorities of Czech forestry must be to halt forest decline, restore the lost vegetation cover on clearcut soils, and intensify adaptive management in order to create resilient forest ecosystems than can cope better with changing climate and extreme climate events.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness., Proceedings of the National Academy of Sciences of the United States of America, 119 (6), ISSN:0027-8424, ISSN:1091-6490

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108- 00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)— ‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007– 2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109– 00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/ NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10- 2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/ PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2.

We conducted an extensive screening of forest soils in the whole area of the Czech Republic to determine their degree of acidification and potential degradation. Soils were sampled at 480 forest sites (in a 7 × 7 km grid covering the entire Czech Republic) from the upper 30-cm layer and included both organic and mineral horizons. Based on values of water extractable pH (pHH2O), cation exchange capacity (CEC) and base saturation (BS), soils were divided into three categories by their degree of acidity, i.e., non-or-low-acidic (NLA; pHH2O ≥ 4.2, CEC ≥ 150 meq kg−1, BS ≥ 15%), moderately acidic (MA; at least one parameter is below the limits for the NLA category), and strongly acidic (SA; all three parameters are below the limits for the NLA category). Only 11% of sampled soils were classified in the NLA category, while 58% and 31% belonged to the MA and SA category, respectively. The SA soils had median values of pHH2O, CEC, and BS of 3.9, 102 meq kg−1, and 10.2%, respectively, and their molar ratios between exchangeable concentrations of base cations to aluminum (BCex/Alex) were

Covering large parts of Europe, Norway spruce (Picea abies L Karst.) plays an important role in the adaptation strategy of forest services to future climate change. Although dendroecology can provide valuable information on the past relationships between tree growth and climate, most previous studies were biased towards species-specific distribution limits, where old individuals grow slowly under extreme conditions. In the present study, we investigated the growth variability and climate sensitivity of 2851 Norway spruce trees along longitudinal (E 12–26°), latitudinal (N 45–51°), and elevation (118–1591 m a.s.l.) gradients in central-eastern Europe. We reveal that summer weather significantly affects the radial growth of spruce trees, but the effects strongly vary along biogeographical gradients. Extreme summer heatwaves in 2000 and 2003 reduced the growth rates by 10–35%, most pronounced in the southern Carpathians. In contrast to the population in the Czech Republic, climate warming induced a synchronous decline in the growth rates across biogeographical gradients in the Carpathian arc. By demonstrating the increased vulnerability of Norway spruce under warmer climate conditions, we recommended that the forest services and conservation managers replace or admix monocultures of this species with more drought-resilient mixtures including fir, beech and other broadleaved species.

Tree growth response to recent environmental changes is of key interest for forest ecology. This study addressed the following questions with respect to Norway spruce (Picea abies, L. Karst.) in Central Europe: Has tree growth accelerated during the last five decades? What are the main environmental drivers of the observed tree radial stem growth and how much variability can be explained by them? Using a nationwide dendrochronological sampling of Norway spruce in the Czech Republic (1246 trees, 266 plots), novel regional tree-ring width chronologies for 40(± 10)- and 60(± 10)-year old trees were assembled, averaged across three elevation zones (break points at 500 and 700 m). Correspondingly averaged drivers, including temperature, precipitation, nitrogen (N) deposition and ambient CO2 concentration, were used in a general linear model (GLM) to analyze the contribution of these in explaining tree ring width variability for the period from 1961 to 2013. Spruce tree radial stem growth responded strongly to the changing environment in Central Europe during the period, with a mean tree ring width increase of 24 and 32% for the 40- and 60-year old trees, respectively. The indicative General Linear Model analysis identified CO2, precipitation during the vegetation season, spring air temperature (March–May) and N-deposition as the significant covariates of growth, with the latter including interactions with elevation zones. The regression models explained 57% and 55% of the variability in the two tree ring width chronologies, respectively. Growth response to N-deposition showed the highest variability along the elevation gradient with growth stimulation/limitation at sites below/above 700 m. A strong sensitivity of stem growth to CO2 was also indicated, suggesting that the effect of rising ambient CO2 concentration (direct or indirect by increased water use efficiency) should be considered in analyses of long-term growth together with climatic factors and N-deposition.

The occurrence of major wildfires in countries such as Portugal, Italy and Spain (2017) and Sweden (2018) indicated that wildfires pose a risk across Europe. While Central Europe has not been at the center of such events, observed climate data and climate projections suggest a tendency toward more years with wet and warm winters and dry and hot summers as well as fuel accumulation, leading to more hazardous conditions. Although some existing studies analyzed the differences in wildfire occurrence in this territory based on terrain, soil or vegetation characteristics, the effects of climate change have not been properly appraised. To fill this knowledge gap, we used and tested an ensemble of nine fuel aridity metrics, including three dedicated fire danger rating indices, and evaluated their level of agreement with actual fire occurrence, their ability to explain the interannual variability in wildfire frequency, and their temporal trends. The analysis covered the entire territory of the Czech Republic at 500 m spatial resolution. Two periods were included based on observed (1956–2015) and projected (2020–2100) meteorological data using ensembles of five regional climate models (RCMs) and five global circulation models (GCMs) based on Euro-CORDEX and CMIP5 datasets. For the future, we considered Representative Concentration Pathway (RCP) 4.5. Our results showed that since 1956, most of the Czech territory has exhibited an increasing frequency of fire weather days (i.e., days with highly conducive wildfire conditions) and an increasing area affected by weather conducive to wildfire occurrence, with the trends accelerating after 2000. The annual variation in the fuel aridity levels (derived solely from meteorological data) explained more than 2/3 of the reported wildfire variability during 1991–2015 over the Czech Republic. The future projections based on the RCM or GCM ensembles indicated a significant increase in fuel aridity and an increase in the area under fire-conducive conditions. Recommendations derived from such robust results are provided for stakeholders seeking to implement adaptation measures.

The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas. The objectives are: (1) to test the applicability of UAV visible an near-infrared (VNIR) and geometrical data based on Z values of point dense cloud (PDC) raster to separate forest species and dead trees in the study area; (2) to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling; and (3) to explore the possibility of the qualitative classification of spruce health indicators. Analysis based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir, and for identification of dead tree category. Separation between common beech and fir was distinguished by the object-oriented image analysis. NDVI was able to identify the presence of key indicators of spruce health, such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation, while stem damage by peeling was identified at the significance margin. The results contributed to improving separation of coniferous (spruce and fir) tree species based on VNIR and PDC raster UAV data, and newly demonstrated the potential of NDVI for qualitative classification of spruce trees. The proposed methodology can be applicable for monitoring of spruce health condition in the local forest sites.

This study’s aim was to make a comparative analysis of airborne (ALS) and terrestrial (TLS) laser scanning and field data collection methods in estimating the tree attributes height (H), diameter at breast height (DBH), crown base (CB), and crown diameter (CD). Manual and automatic methods of extracting tree attributes from ALS and TLS data were evaluated for spruce and beech at a study site within the Czech part of the Silesian Beskids. Strong correlation (r) was observed among scanning H and field-measured H for spruce (r = 0.91 for ALS automatic vs. field, r = 0.94 for ALS manual vs. field, r = 0.91 for TLS manual vs. field), and with standard error of the estimates (SEE) from 1.4 m to 2.2 m. DBH estimates from TLS manual method showed r = 0.96 for spruce and beech with average SEE of 2.9 cm. DBH estimates for beech from TLS automatic method were poorer (r = 0.73, SEE = 9.1 cm) than for spruce (r = 0.96, SEE = 2.5 cm). TLS estimates of CB were better both for manual and automatic methods (r = 0.85, SEE = 1.4 m for manual; r = 0.73, SEE = 2.4 for automatic) than ALS estimates (r = 0.67, SEE = 4.0 m for manual; r = 0.61, SEE = 4.2 m for automatic). CD estimates from ALS showed better agreement with field measurements (r = 0.71, SEE = 1.2 m) than did CD estimates from TLS (r = 0.52, SEE = 1.4 m). TLS technology was evaluated as being most time demanding for both manual and automatic modes in comparison with ALS and field technologies. Field technology for in situ measurement was shown to be time effective compared with ALS and/or TLS technologies that used manual methods to extract tree attributes. ALS technology with automatic methods of tree attributes extraction was found to be most efficient, showing that automation is a key process and has strong potential for applications to inventory trees within forests over large areas in Central Europe.

Planted even-aged forests dominated by Norway spruce ( Picea abies ) progressively replaced mixed natural forests in large parts of Central Europe during past centuries due to the productivity-motivated preferences of forest owners. These managed forests have become vulnerable to climate change, specifically to increasingly severe drought. To evaluate the response of trees to warming, we collected samples from a randomized landscape inventory grid of 7 × 7 km to account for spatial gradients in climate/growth interactions in the entire forested part of the Czech Republic. The purely climate-driven forward growth model − Vaganov-Shashkin “Lite” − was calibrated by real (observed) radial growth series to identify a course of climatic limiting factors on an intra-annual scale. Relative proportions of moisture and temperature limited parts of total tree-ring width were determined as well as trends in limiting conditions over the period 1940–2012 and along the elevation gradient. Significant match between modelled and observed growth was shown in 47% of the grid cells. The coherence between modelled and observed site series was significantly improved when individual grid cells were aggregated into elevation belts. In grid cells below 600 m, from 51 to 58% of tree-ring width was formed under moisture-limited conditions, with the proportion of growth under optimal conditions being minimal. The effect of drought stress was outweighed by earlier spring onset of growth, resulting in positive trends in total tree-ring width above 500 m. About 26% of tree-ring growth has occurred under optimal climatic conditions at elevations above 800 m, where, moreover, 45% of total annual growth was temperature limited. Except for one medium-elevation belt, the proportion of growth under moisture-limited conditions significantly increased during the period analysed. Recent warming and increasing frequency of drought events deepened the divergence in growth trends between low-elevation areas and stands at medium and high elevations.

The growth response of trees to changing climate is frequently discussed as increasing temperatures and more severe droughts become major risks for forest ecosystems. However, the ability of trees to cope with the changing climate and the effects of other environmental factors on climate-growth relationships are still poorly understood. There is thus an increasing need to understand the ability of individual trees to cope with changing climate in various environments. To improve the current understanding, a large tree-ring network covering the whole area of the Czech Republic (in 7 × 7 km grids) was utilized to investigate how the climate-growth relationships of Norway spruce are affected by 1) various geographical variables, 2) changing levels of acidic deposition, 3) soil characteristics and 4) age, tree diameter and neighbourhood competition. The period from 1930 to 2013 was divided into four, 21-year long intervals of differing levels of acidic deposition, which peaked in the 1972–1993 period. Our individual-based, spatiotemporal, multivariate analyses revealed that spruce growth was mostly affected by drought and warm summers. Drought plays the most important negative role at lower altitudes, while the positive effect of higher temperature was identified for trees at higher altitudes. Increased levels of acidic deposition, together with geographical variables, were identified as the most important factors affecting climate-growth association. Tree age, tree size and soil characteristics also significantly modulate climate-growth relationships. The importance of all environmental variables on climate-growth relationships was suppressed by acidic deposition during periods when this was at a high level; growth was significantly more enhanced by spring and summer temperatures during these periods. Our results suggest that spruce will undergo significant growth reduction under the predicted climate changes, especially at the lower altitudes which lie outside of its natural range.

Coffee leaf rust (CLR), caused by Hemileia vastarix, is one of the most serious diseases of coffee plantations and cause great losses in coffee production. We aimed to examine coffee varieties, shade, age of coffee plants, coffee plant density and soil properties in relation to CLR infection. To do this, we established a total of 75 plots in three agroforestry coffee plantations in the central Peruvian Amazon. We gathered data there in 2011 (dry season) on the presence/absence of CLR; coffee variety; age and density of coffee plants, and also took hemispherical photographs to determine canopy openness. In 2014 (wet season), we again gathered data on the same variables. In 2012, we collected soil samples from a subset of the plots. At all plantations, coffee variety had a significant effect on CLR incidence, with the Catimor variety infected less frequently than Caturra. Coffee plant age had a significant positive effect on CLR incidence. Increasing coffee density also increased CLR incidence for some of the studied plantations/seasons. Comparing those plots from which data were collected in the dry and wet seasons, we found that CLR presence was significantly higher in the wet season. The effect of shade on CLR incidence was not clear. Catimor and Caturra varieties showed opposite trends of CLR incidence in response to shade quantity in most cases (Caturra variety CLR incidence was decreasing with shading increase and Catimor CLR incidence decreasing with decreasing shading). Finally, the soil properties did not affect CLR incidence.

The study presents three methods for estimation of forest aboveground biomass (AGB) at tree and plot levels using different categories of airborne data. The first method estimates AGB from high spatial resolution hyperspectral (HS) data. The second method estimates AGB from airborne laser scanning data. The third method explores the synergy between hyperspectral and LiDAR data to estimate AGB. The results are compared with AGB estimated from field measurements. The results demonstrate that: 1) The biomass estimation from the HS data showed a good correlation with field biomass values for spruce, beech and mixture of these species at tree and plot levels, but also the highest uncertainties in comparison with the other two methods; 2) The biomass estimation from the LiDAR data had a strong correlation with field biomass values for spruce for tree level and a good correlation for spruce, beech and mixture of these species for plot level; 3) The biomass estimation from fused HS and LiDAR data showed the best results for tree and plot levels for the study sites. This study expands on previous research assessing the applicability of HS, LiDAR and fused datasets for AGB assessment. It proves the efficiency of using fused HS and LiDAR data and suggests the use of HS-based methods for biomass assessment when laser scanning data are not available.

Decline or health deterioration of Norway spruce (Picea abies (L.) Karst.) dominated forest stands has recently been observed mainly in sub-mountainous parts of Central Europe. Forest inventory of 208 randomly distributed circular plots including field observations of spruce tree health and rot symptoms by honey fungus (Armillaria ostoyae) was used for assessing intensity of spruce forest health decline in a managed forest area of 12.7 th. ha located in Beskids Mts., NE Czech Republic. First, principal component analysis was used to separate inventory variables related to environmental stress (reduced apical increment, dry tree top and stem resin exudation due to A. ostoyae infestation) into PC1, and health deterioration symptoms associated with mechanical damage (peeling, crown breaks) into PC2. The first two principal components explained 59% of the total variability in health decline symptoms. Spatial variability of both principal components was explained using spatial lag regression model identified from a set of environmental variables including sulfur and nitrogen deposition, elevation, solar radiation, age of the forest stands and geological properties (geochemical reactivity index). Environmental stress (PC1) was associated with low elevations (sub-optimal for spruce), high level of nitrogen and sulfur deposition (their interaction), low geochemical reactivity and also stand age. On the other hand, mechanical damage (PC2) significantly increased with elevation and stand age. As the forest decline in Beskids Mts. is related to A. ostoyae spreading from local infestation hot spots, both principal components had a significant spatial autocorrelation, partly distorting the signal of environmental conditions. The results indicate that the disturbed forest soils by long-term acid deposition and subsequent nutrient degradation and more pronounced drought stress at low elevations are the most important drivers of the recent spruce health decline in Beskids Mts.

Late-spring frosts (LSFs) affect the performance of plants and animals across the world’s temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees’ adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species’ innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy.

Summary Increasing the amount of carbon stored in harvested wood products (HWPs) is an internationally recognized measure to mitigate climate change. Several approaches and tiers of methods may be used to analyze the contribution of HWP in terms of greenhouse gas emissions and removals at a regional and national level. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on three tiers of methods for estimating annual carbon stock changes in the carbon pool of HWPs. These tiers mostly differ by the availability of input data and the level of HWP aggregation. In this case study for the Czech Republic, we have applied the production approach and alternative tiers of accounting methods, which are described in the IPCC guidelines, including the default method (tier 2) and the most advanced method (tier 3). We used country-specific data and material flow analysis to trace the carbon flow over the entire forest-based sector, including only the domestic harvest and the primary and secondary wood products manufactured within the country. The results of this study show that the carbon stored in the HWP pool could be underestimated if simpler methods and default values nonspecific to the country are applied. At the national level, applying the tier 3 method resulted in a 15.8% higher annual carbon inflow in the pool of HWPs compared to the tier 2 IPCC default method. This means that the advanced method reveals an apparently higher carbon sink in HWPs. A documented increase of carbon storage might bring additional credits to reporting countries, and, more important, it could promote the use of long-life HWPs to mitigate climate change.

The study is aimed to explore the potential of time-series airborne hyperspectral and satellite multispectral data to track the changes in spruce forest decline expressed by a composite spruce decline indicator. Vegetation indices and exergy of solar radiation extracted from remote sensing data are used to predict the development of the composite spruce health indicator. The canopy-level spectral reflectance properties of spruce stands are investigated to identify categories of spruce stand decline: healthy, initial decline, and initial to moderate decline. The sensitivity peaks for initial decline and initial to moderate decline of spruce are shown. The highest potential for the estimation of the composite spruce health indicator is demonstrated by vegetation indices WBI and NDVIred_edge from airborne hyperspectral data, and by PSRI, NDII and exergy of solar radiation from Landsat and Sentinel-2 satellite multispectral data. MODIS data show only a poor correlation between the composite spruce stand health indicator and NDII index. The proposed methodology to obtain the distribution of the composite spruce decline indicator using remote sensing (RS) data promisingly suggests its applicability over a large forest area with potential time and economic benefits, since foliar spectral measurements, canopy chemistry, and laboratory analysis are not required.

We examined the effect of individual environmental factors on the current spruce tree growth assessed from a repeated country-level statistical landscape (incl. forest) survey in the Czech Republic. An extensive set of variables related to tree size, competition, site characteristics including soil texture, chemistry, N deposition and climate was tested within a random-effect model to explain growth in the conditions of dominantly managed forest ecosystems. The current spruce basal area increment was assessed from two consecutive landscape surveys conducted in 2008/2009 and six years later in 2014/2015. Tree size, age and competition within forest stands were found to be the dominant explanatory variables, whereas the expression of site characteristics, environmental and climatic drives was weaker. The significant site variables affecting growth included soil C/N ratio and soil exchangeable acidity (pH KCl; positive response) reflecting soil chemistry, long-term N-deposition (averaged since 1975) in combination with soil texture (clay content) and Standardized Precipitation Index (SPI), a drought index expressing moisture conditions. Sensitivity of growth to N-deposition was positive, although weak. SPI was positively related to and significant in explaining tree growth when expressed for the growth season. Except SPI, no significant relation of growth was determined to altitude-related variables (temperature, growth season length). We identified the current spruce growth optimum at elevations about 800ma.s.l. or higher in the conditions of the country. This suggests that at lower elevations, limitation by a more pronounced water deficit dominates, whereas direct temperature limitation may concern the less frequent higher elevations. The mixed linear model of spruce tree growth explained 55 and 65% of the variability with fixed and random effects included, respectively, and provided new insights on the current spruce tree growth and factors affecting it within the environmental gradients of the country.

We report on the operational use of remotely sensed data by national forest inventory (NFI) programmes in 45 countries representing approximately 65% of the world's forest area. The analysis is based on responses to a questionnaire prepared under the auspices of COST Action FP1001 “Improving Data and Information on the Potential Supply of Wood Resources: A European Approach from Multisource National Forest Inventories (USEWOOD)”. Responses were received from NFI remote sensing experts from both European and non-European countries. Three major conclusions were drawn from the study: (1) remote sensing now plays an essential role in many NFI programmes and provides data that can be used to enhance estimates for the most meaningful and commonly reported forest resource parameters; (2) a wide spectrum of remote sensing methods are currently used by NFI teams; and (3) although substantial effort and attention has been focused on the use of aerial photography and spaceborne sensor data for mapping and enhancing estimation, integration of uncertainly estimation requires additional attention. The operational use of remotely sensed data by NFI programmes is illustrated for three case studies: a case study for Switzerland focuses on digital aerial photography, a case study for Finland focuses on spaceborne sensor data for small area estimation, and a case study for the USA focuses on spaceborne sensor data for increasing the precision of large area estimates. Although use of remotely sensed data by NFI programmes may remain region-specific and some approaches are not readily transferable, generally applicable good practice guidelines were formulated on the basis of the questionnaire responses and the case studies. These guidelines are intended to promote better use of limited financial resources and to increase the accuracy and precision of NFI estimates.

Agroforestry has become an important land use type in Central and South America. It is important to study agroforestry systems because of their ability to sequester carbon. This study investigates plantations that are located in the foothills of the Peruvian Andes, and it evaluates the aboveground and soil carbon storage of agroforestry coffee plantations with different dominant shading trees, including Inga spp., Pinus spp. (both 15 years old) and Eucalyptus spp. (7 years old). These agroforestry systems were also compared to a coffee plantation without shading trees. Biomass and carbon were estimated for trees and coffee shrubs using allometric equations. Soil (within depth of 30 cm) and litter carbon were estimated using field sampling and laboratory analyses. The total carbon stock for the site dominated by Inga spp. was 119.9 ± 19.5 Mg ha−1, while for the sites dominated by Pinus spp. it was 177.5 ± 14.1 Mg ha−1 and for the site dominated by Eucalyptus spp. it was 162.3 ± 18.2 Mg ha−1. In the Sun coffee site the ecosystem carbon stock was 99.7 ± 17.2 Mg ha−1. Most carbon was fixed in the soil compartment (57–99 %), followed by aboveground tree biomass (23–32 %), tree belowground biomass (8–9 %), coffee shrubs (0.2–2 %) and litter (1 %).

Lesy sú na Slovensku obhospodarované podľa programov starostlivosti o lesy. Limity pre objem ťažby sú predpísané na základe pravidiel trvalo udržateľného obhospodarovania lesov. Týmto spôsobom sa produkované drevo stáva obnoviteľnou surovinou s trvalo udržateľnou produkciou. Následné využitie dreva má vplyv na bilanciu uhlíka a produkty z dreva určené na dlhodobé využívanie predstavujú zásobáreň uhlíka, z ktorej sa uhlík uvoľňuje pri rozklade dreva po ukončení životnosti drevného produktu. V práci je prezentovaný metodický postup výpočtu a výsledky bilancie uhlíka v produktoch z dreva na Slovensku. Podľa výsledkov je celkové množstvo uhlíka uloženého v drevných produktoch odhadnuté na 15 Tg a doteraz malo stúpajúci trend. Metodický postup je spracovaný podľa metód a praktických návodov spracovaných v súvislosti s postupmi navrhnutými pre hodnotenie plnenia záväzkov vyplývajúcich z Kjótskeho protokolu.

Cieľom štúdie je zmapovať a analyzovať systémy governancie relevantné pre multifunkčné lesné hospodárstvo vo vybraných horských regiónoch Európy. Tento príspevok vznikol v rámci projektu 7. rámcového programu Zdokonalený multifunkčný manažment lesov v horských regiónoch Európy (ARANGE). Súčasné systémy governancie uplatňované v multifunkčnom obhospodarovaní lesov sme analyzovali v siedmich prípadových štúdiách: Iberské pohorie (Španielsko), Západné Alpy (Francúzsko), Východné Alpy (Rakúsko), Dináre (Slovinsko), Škandinávske vrchy, (Švédsko), Západné Karpaty (Slovensko) a Západné Rodopy (Bulharsko). Použili sme metódy sociologického výskumu. 27 expertov z prípadových štúdií (väčšinou obhospodarovateľov lesov) odpovedalo na 21 pološtruktúrovaných otázok zahŕňajúcich nasledovné prvky governancie: participácia, koordinácia, rozodovanie, zodpovednosť a využitie odborných znalostí. Výsledky poukazujú na skutočnosť, že obhospodarovatelia lesa vo všeobecnosti zdieľajú názor, že multifunkčné obhospodarovanie lesov je zamerané na zachovanie alebo posilnenie viacerých funkcií lesa, vrátane drevoprodukčnej. Uplatňované systémy governancie v zásade podporujú multifunkčné obhospodarovanie horských lesov, ale samotné multifunkčné obhospodarovanie je v jednotlivých prípadoch rozdielne. Tieto rozdiely vychádzajú viac zo špecifických podmienok jednotlivých prípadov, ako z uplatňovaných systémov governancie. Získané výsledky vytvárajú možný základ pre formuláciu a prijatie efektívnych a adekvátnych politických odporúčaní pre multifunkčné obhospodarovanie horských lesov v Európe.

Under the United Nations Framework Convention for Climate Change all Parties have to report on carbon emissions and removals from the forestry sector. Each Party can use its own approach and country specific data for this. Independently, large-scale models exist (e.g. EFISCEN and G4M as used in this study) that assess emissions and removals from this sector by applying a unified approach to each country, still often based on country specific data. Differences exist between the national reported values and the calculations from the large scale models. This study compares these models with national reporting efforts for 24 EU countries for the period 2000–2008, and identifies the most likely causes for differences. There are no directly identifiable single input parameters that could be targeted to fully close the gap between country and model estimates. We found that the method applied by the country (i.e. stock-difference or gain-loss) contributes significantly to differences for EFISCEN and was the best explaining variable for G4M, although for the latter it was not significant. Other variables (biomass expansion factors, harvest volumes and the way harvest losses are treated) were not found to provide a conclusive explanation for the differences between the model estimations and the country submissions in an over-all analysis. However, at the level of individual countries several different causes for differences were identified. This suggests that to really close the gap between country submissions and large scale models, close collaboration between modellers and country experts is needed, calling for openness and willingness to share relevant data and to compare GHG inventories with independent estimates. This would enable to improve the confidence both in historical GHG inventories and in the models which are needed to project the future forest sink for several policy issues., JRC.H.3-Forest Resources and Climate

The aim of this paper is to develop biomass models for commonly multi-stemmed Prosopis juliflora/pallida trees. The data were collected on three of the Cape Verde islands (Maio, Santiago and Santo Antao). The dataset covers 240 trees containing 1,882 stems with stem diameter at breast height over 2 cm; of that 255 individual tree stems were sampled destructively. These calibration data were used to construct stem and tree-level models for estimation of total aboveground biomass and its fine and course fractions with diameter threshold of 5 cm. A set of parameterized biomass models for multi-stemmed Prosopis spp. trees suited for biomass estimation at tree and stem levels using appropriate set of independent variables, commonly available in forest inventory programs, was created. The effect of site (island) on tree allometry was not detected. The two-phase construction of tree biomass models based on destructive sampling limited to individual stems combined with a routine field measurement of entire multi-stemmed tree specimen represents a practicable approach leading to biomass and carbon assessment that may be generally suited for tree species with complex multi-stemmed growth form similar to that of Prosopis spp.

The simulation of forest production until 2100 under different environmental scenarios and current management practices was performed using a process-based model BIOME-BGC previously parameterized for the main Central-European tree species: spruce, pine, beech and oak and adapted to include forest management practices. Climatic scenario HadCM3 used in the simulations was taken from the IPCC database created within the 3rd Assessment Report. It was combined with a scenario of CO 2 concentration development and a scenario of N deposition. The control scenario considered no changes of climatic characteristics, CO 2 concentration and N deposition. Simulation experiment was performed for the test region – South Bohemia – using a 1 km × 1 km grid. The actual data on the regional forest cover were aggregated for each grid cell in such a way that each cell represented an even-aged single-dominant species stand or non-forested area, and a standard management scenario depending on the stand age and species was applied to each cell. The effect of environmental variables was estimated as the difference of simulated carbon pools and fluxes in 2050 under environmental changes and under control scenario. The model simulation for the period to 2050 with only climate change under constant CO 2 concentration and N deposition indicated a small decrease of NPP (median values by species reached −0.9 to −1.7% for different species), NBP (−0.3 to −1.7%) and vegetation carbon (−0.3 to −0.7%), whereas soil C slightly increased. Separate increase of N deposition gave small positive effect on carbon pools (0.8–2.9% for wood C and about 0.5% for soil C) and more expressed effect on carbon fluxes (1.8–4.3% for NPP and 1.0–9.7% for NBP). Separate increase of CO 2 concentration lead to 0.6–2.4% increase of wood C pool and 0.1–0.5% increase of soil C. The positive effects of CO 2 concentration and N deposition were more pronounced for coniferous than for deciduous stands. Replacement of 0.5% of coniferous plantations every year by natural broadleaved stands evoked 10.5% of increase of wood carbon pool due to higher wood density of beech and oak compared to spruce and pine, but slightly decreased soil and litter carbon pools.

The simulation of forest production until 2100 under different environmental scenarios and current management practices was performed using a process-based model BIOME-BGC previously parameterized for the main Central-European tree species, and adapted to include forest management practices. Three climatic scenarios (HadCM3, NCAR-PCM, CSIRO) used were taken from the IPCC database created within the 3 rd Assessment Report. They were combined with a scenario of CO 2 concentration development and a scenario of N deposition. The control scenario considered no changes of climatic characteristics, CO 2 concentration and N deposition. The model simulations showed a decrease of wood carbon pool (from 2 to 6% relative to unchanged conditions) under HadCM3 scenario for all tree species. Under other climatic scenarios wood carbon pool decreased for coniferous and slightly increased for deciduous stands. The decrease of wood carbon pool under HadCM3 scenario was evidently related to decreasing precipitation during the second part of growing season, which increased soil moisture deficit and, consequently, decreased NPP. Under all scenarios a considerable build-up of litter carbon pool was observed (from 7 to 16% at 2100). The changes in soil carbon pool were small (2–3%), positive for deciduous and negative for coniferous stands. Imposing changing climatic conditions only (under constant CO 2 and N deposition) resulted in similar trends of carbon dynamics as under the base scenario, but with smaller magnitude of changes. The combination of CO 2 increase and N decrease under constant climate had a positive effect on C pools for deciduous and a negative effect for coniferous species. The simulation using annual means of climate changes gave considerably smaller carbon changes compared to the simulation with climate change imposed in monthly resolution.

Carbon storage in aboveground tree biomass and soil organic matter (in depth of A layer development i.e., up to 20 cm) was studied in 22–32 year-old post-mining sites in the northwest of the Czech Republic. Four replicated sites afforested with different tree species (spruce, pine, larch, oak, lime or alder) were compared with sites left to natural regeneration which were dominated by aspen, birch and willow. No topsoil was applied at the sites; hence carbon accumulation resulted from in situ soil development on alkaline tertiary clays that were dumped on the heaps. In aboveground tree biomass, carbon storage ranged from 17.0 ± 5.9 (mean ± SEM) to 67.6 ± 5.9 t ha−1 and the rate of C accumulation increased from 0.60 ± 0.09 to 2.31 ± 0.23 t ha−1 year−1 (natural regeneration

This study analyses the effects of thinning on stand transpiration in a typical mixed spruce and pine forest in the southern boreal zone. Studies of transpiration are important for models of water, energy and carbon exchange, and forest management, like thinning, would change those processes. Tree transpiration was measured by the tissue heat-balance sapflow technique, on a reference plot and a thinning plot situated in a 50-year-old stand in central Sweden. Sapflow was measured during one season (1998) on both plots before thinning, to establish reference values. In winter 1998/1999 24% of the basal area was removed from the thinning plot. Thinning was done so as to preserve the initial species composition and the size distribution. The measurements continued after thinning during the growing seasons of 1999 and 2000. The climate showed remarkable differences between the 3 years; 1998 was wet and cool, with frequent rain, and the soil-water content was high throughout the year. In contrast, 1999 was dry and warm, and the soil-water content decreased to very low values, ca. 5-6% by volume. In 2000, the weather was more normal, with variable conditions. Stand transpiration was similar on both plots during the year before thinning; the plot to be thinned transpired 6% more than the reference plot. After thinning, transpiration was initially ca. 40% lower on the thinned plot, but the difference diminished successively. When the following drought was at its worst, the thinned plot transpired up to seven times more than the reference plot. During the second season after thinning, the thinned plot transpired ca. 20% more than the reference plot. The increased transpiration of the thinned plot could not be attributed to environmental variables, but was most probably caused by changes in biological factors, such as a fertilization effect. (Less)

A process-based model BIOME-BGC designed for simulation of biogeochemical element cycling in terrestrial ecosystems was prepared for application to managed forest ecosystems in temperate Europe. New routines were implemented that permit specification of thinning, felling and species change when planting new forest. Other changes were implemented to water cycling routines, specifically to precipitation and evaporation, simulation of industrial nitrogen deposition and fine roots mortality. The major aim of the paper was to conduct a sensitivity analysis of the adapted model. We specifically analysed the effects of site and eco-physiological parameters on the modeled state variables (carbon pools in biomass, litter and soil and net primary production (NPP)). The analysis revealed a high sensitivity of all tested variables to the following site parameters: total precipitation, rooting depth, sand fraction (for sandy soils only), ambient CO2 and parameters of nitrogen input. Similarly, the tested variables were shown to be highly sensitive to the following eco-physiological parameters: leaf and fine root C:N ratio, new stem C to new leaf C ratio, new fine root C to new leaf C ratio, specific leaf area, maximum stomatal conductance, fire mortality and fraction of N in Rubisco (specifically for deciduous species). Additionally, the whole plant mortality had a high effect on carbon pools, but a small effect on NPP.

Forest biomass and its change over time have been measured at both local and large scales, an example for the latter being forest greenhouse gas inventories. Currently used methodologies to obtain stock change estimates for large forest areas are mostly based on forest inventory information as well as various factors, referred to as biomass factors, or biomass equations, which transform diameter, height or volume data into biomass estimates. However, while forest inventories usually apply statistically sound sampling and can provide representative estimates for large forest areas, the biomass factors or equations used are, in most cases, not representative, because they are based on local studies. Moreover, their application is controversial due to the inconsistent or inappropriate use of definitions involved. There is no standardized terminology of the various factors, and the use of terms and definitions is often confusing. The present contribution aims at systematically summarizing the main types of biomass factors (BF) and biomass equations (BE) and providing guidance on how to proceed when selecting, developing and applying proper factors or equations to be used in forest biomass estimation. The contribution builds on the guidance given by the IPCC (Good practice guidance for land use, land-use change and forestry, 2003) and suggests that proper application and reporting of biomass factors and equations and transparent and consistent reporting of forest carbon inventories are needed in both scientific literature and the greenhouse gas inventory reports of countries.