Clara Antón Fernández
Senior Research Scientist
(+47) 482 15 794
clara.anton.fernandez@nibio.no
Place
Ås H8
Visiting address
Høgskoleveien 8, 1433 Ås
Abstract
No abstract has been registered
Authors
Clemens Blattert Mikko Mönkkönen Daniel Burgas Fulvio Di Fulvio Astor Toraño Caicoya Marta Vergarechea Julian Klein Markus Hartikainen Clara Antón Fernández Rasmus Astrup Michael Emmerich Nicklas Forsell Jani Lukkarinen Johanna Lundström Samuli Pitzén Werner Poschenrieder Eeva Primmer Tord Snäll Kyle EyvindsonAbstract
No abstract has been registered
Authors
Iris Hordijk Daniel S. Maynard Simon P. Hart Mo Lidong Hans ter Steege Jingjing Liang Sergio de-Miguel Gert-Jan Nabuurs Peter B. Reich Meinrad Abegg C. Yves Adou Yao Giorgio Alberti Angelica M. Almeyda Zambrano Braulio V. Alvarado Alvarez-Davila Esteban Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernández Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo A. Aymard C Timothy Baker Radomir Bałazy Olaf Banki Jorcely Barroso Meredith L. Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Roel Brienen Eben N. Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo G. César Goran Cesljar Robin Chazdon Han Y. H. Chen Chelsea Chisholm Emil Cienciala Connie J. Clark David B. Clark Gabriel Colletta David Coomes Fernando Cornejo Valverde Jose J. Corral-Rivas Philip Crim Jonathan Cumming Selvadurai Dayanandan André L. de Gasper Mathieu Decuyper Géraldine Derroire Ben DeVries Ilija Djordjevic Amaral Iêda Aurélie Dourdain Engone Obiang Nestor Laurier Brian Enquist Teresa Eyre Adandé Belarmain Fandohan Tom M. Fayle Leandro V. Ferreira Ted R. Feldpausch Leena Finér Markus Fischer Christine Fletcher Lorenzo Frizzera Javier G. P. Gamarra Damiano Gianelle Henry B. Glick David Harris Andrew Hector Andreas Hemp Geerten Hengeveld Bruno Hérault John Herbohn Annika Hillers Eurídice N. Honorio Coronado Cang Hui Hyunkook Cho Thomas Ibanez Il Bin Jung Nobuo Imai Andrzej M. Jagodzinski Bogdan Jaroszewicz Vivian Johanssen Carlos A. Joly Tommaso Jucker Viktor Karminov Kuswata Kartawinata Elizabeth Kearsley David Kenfack Deborah Kennard Sebastian Kepfer-Rojas Gunnar Keppel Mohammed Latif Khan Timothy Killeen Hyun Seok Kim Kanehiro Kitayama Michael Köhl Henn Korjus Florian Kraxner Diana Laarmann Mait Lang Simon Lewis Huicui Lu Natalia Lukina Brian Maitner Yadvinder Malhi Eric Marcon Beatriz Schwantes Marimon Ben Hur Marimon-Junior Andrew Robert Marshall Emanuel Martin Olga Martynenko Jorge A. Meave Omar Melo-Cruz Casimiro Mendoza Cory Merow Miscicki Stanislaw Abel Monteagudo Mendoza Vanessa Moreno Sharif A. Mukul Philip Mundhenk Maria G. Nava-Miranda David Neill Victor Neldner Radovan Nevenic Michael Ngugi Pascal A. Niklaus Jacek Oleksyn Petr Ontikov Edgar Ortiz-Malavasi Yude Pan Alain Paquette Alexander Parada-Gutierrez Elena Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Oliver L. Phillips Nicolas Picard Maria Teresa Piedade Daniel Piotto Nigel C. A. Pitman Irina Polo Lourens Poorter Axel Dalberg Poulsen John R. Poulsen Hans Pretzsch Freddy Ramirez Arevalo Zorayda Restrepo-Correa Mirco Rodeghiero Samir Rolim Anand Roopsind Francesco Rovero Ervan Rutishauser Purabi Saikia Christian Salas-Eljatib Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Eric B. Searle Vladimír Šebeň Josep M. Serra-Diaz Douglas Sheil Anatoly Shvidenko Javier Silva-Espejo Marcos Silveira James Singh Plinio Sist Ferry Slik Bonaventure Sonké Alexandre F. Souza Krzysztof Stereńczak Jens-Christian Svenning Miroslav Svoboda Ben Swanepoel Natalia Targhetta Nadja Tchebakova Raquel Thomas Elena Tikhonova Peter Umunay Vladimir Usoltsev Renato Valencia Fernando Valladares Fons van der Plas Do Van Tran Michael E. Van Nuland Rodolfo Vasquez Martinez Hans Verbeeck Helder Viana Alexander C. Vibrans Simone Vieira Klaus von Gadow Hua-Feng Wang James Watson Gijsbert D. A. Werner Susan K. Wiser Florian Wittmann Verginia Wortel Roderick Zagt Tomasz Zawila-Niedzwiecki Chunyu Zhang Xiuhai Zhao Mo Zhou Zhi-Xin Zhu Irie Casimir Zo-Bi Thomas W. CrowtherAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Camille S. Delavaux Thomas W. Crowther Constantin M. Zohner Niamh M. Robmann Thomas Lauber Johan van den Hoogen Sara Kuebbing Jingjing Liang Sergio de-Miguel Gert-Jan Nabuurs Peter B. Reich Meinrad Abegg Yves C. Adou Yao Giorgio Alberti Angelica M. Almeyda Zambrano Braulio Vilchez Alvarado Esteban Alvarez-Dávila Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernández Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo A. Aymard Timothy R. Baker Radomir Bałazy Olaf Banki Jorcely G. Barroso Meredith L. Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Roel Brienen Eben N. Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo G. César Goran Cesljar Robin Chazdon Han Y. H. Chen Chelsea Chisholm Hyunkook Cho Emil Cienciala Connie Clark David Clark Gabriel D. Colletta David A. Coomes Fernando Cornejo Valverde José J. Corral-Rivas Philip M. Crim Jonathan R. Cumming Selvadurai Dayanandan André L. de Gasper Mathieu Decuyper Géraldine Derroire Ben DeVries Ilija Djordjevic Jiri Dolezal Aurélie Dourdain Nestor Laurier Engone Obiang Brian J. Enquist Teresa J. Eyre Adandé Belarmain Fandohan Tom M. Fayle Ted R. Feldpausch Leandro V. Ferreira Markus Fischer Christine Fletcher Lorenzo Frizzera Javier G. P. Gamarra Damiano Gianelle Henry B. Glick David J. Harris Andrew Hector Andreas Hemp Geerten Hengeveld Bruno Hérault John L. Herbohn Martin Herold Annika Hillers Eurídice N. Honorio Coronado Cang Hui Thomas T. Ibanez Iêda Amaral Nobuo Imai Andrzej M. Jagodziński Bogdan Jaroszewicz Vivian Kvist Johannsen Carlos A. Joly Tommaso Jucker Ilbin Jung Viktor Karminov Kuswata Kartawinata Elizabeth Kearsley David Kenfack Deborah K. Kennard Sebastian Kepfer-Rojas Gunnar Keppel Mohammed Latif Khan Timothy J. Killeen Hyun Seok Kim Kanehiro Kitayama Michael Köhl Henn Korjus Florian Kraxner Diana Laarmann Mait Lang Simon L. Lewis Huicui Lu Natalia V. Lukina Brian S. Maitner Yadvinder Malhi Eric Marcon Beatriz Schwantes Marimon Ben Hur Marimon-Junior Andrew R. Marshall Emanuel H. Martin Olga Martynenko Jorge A. Meave Omar Melo-Cruz Casimiro Mendoza Cory Merow Abel Monteagudo Mendoza Vanessa S. Moreno Sharif A. Mukul Philip Mundhenk María Guadalupe Nava-Miranda David Neill Victor J. Neldner Radovan V. Nevenic Michael R. Ngugi Pascal A. Niklaus Jacek Oleksyn Petr Ontikov Edgar Ortiz-Malavasi Yude Pan Alain Paquette Alexander Parada-Gutierrez Elena I. Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Oliver L. Phillips Nicolas Picard Maria Teresa T. F. Piedade Daniel Piotto Nigel C. A. Pitman Irina Polo Lourens Poorter Axel Dalberg Poulsen Hans Pretzsch Freddy Ramirez Arevalo Zorayda Restrepo-Correa Mirco Rodeghiero Samir G. Rolim Anand Roopsind Francesco Rovero Ervan Rutishauser Purabi Saikia Christian Salas-Eljatib Philippe Saner Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Eric B. Searle Vladimír Seben Josep M. Serra-Diaz Douglas Sheil Anatoly Z. Shvidenko Javier E. Silva-Espejo Marcos Silveira James Singh Plinio Sist Ferry Slik Bonaventure Sonké Alexandre F. Souza Miscicki Stanislaw Krzysztof J. Stereńczak Jens-Christian Svenning Miroslav Svoboda Ben Swanepoel Natalia Targhetta Nadja Tchebakova Hans ter Steege Raquel Thomas Elena Tikhonova Peter M. Umunay Vladimir A. Usoltsev Renato Valencia Fernando Valladares Fons van der Plas Tran Van Do Michael E. van Nuland Rodolfo M. Vasquez Hans Verbeeck Helder Viana Alexander C. Vibrans Simone Vieira Klaus von Gadow Hua-Feng Wang James V. Watson Gijsbert D. A. Werner Susan K. Wiser Florian Wittmann Hannsjoerg Woell Verginia Wortel Roderik Zagt Tomasz Zawiła-Niedźwiecki Chunyu Zhang Xiuhai Zhao Mo Zhou Zhi-Xin Zhu Irie C. Zo-Bi Daniel S. MaynardAbstract
No abstract has been registered
Abstract
Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.
Authors
Jingjing Liang Javier G. P. Gamarra Nicolas Picard Mo Zhou Bryan Pijanowski Douglass F. Jacobs Peter B. Reich Thomas W. Crowther Gert-Jan Nabuurs Sergio de-Miguel Jingyun Fang Christopher W. Woodall Jens-Christian Svenning Tommaso Jucker Jean-Francois Bastin Susan K. Wiser Ferry Slik Bruno Hérault Giorgio Alberti Gunnar Keppel Geerten M. Hengeveld Pierre L. Ibisch Carlos A. Silva Hans ter Steege Pablo L. Peri David A. Coomes Eric B. Searle Klaus von Gadow Bogdan Jaroszewicz Akane O. Abbasi Meinrad Abegg Yves C. Adou Yao Jesús Aguirre-Gutiérrez Angelica M. Almeyda Zambrano Jan Altman Esteban Alvarez-Dávila Juan Gabriel Álvarez-González Luciana F. Alves Bienvenu H. K. Amani Christian A. Amani Christian Ammer Bhely Angoboy Ilondea Clara Antón Fernández Valerio Avitabile Gerardo A. Aymard Akomian F. Azihou Johan A. Baard Timothy R. Baker Radomir Balazy Meredith L. Bastian Rodrigue Batumike Marijn Bauters Hans Beeckman Nithanel Mikael Hendrik Benu Robert Bitariho Pascal Boeckx Jan Bogaert Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Francis Q. Brearley Jaime Briseno-Reyes Eben N. Broadbent Helge Bruelheide Erwin Bulte Ann Christine Catlin Roberto Cazzolla Gatti Ricardo G. César Han Y. H. Chen Chelsea Chisholm Emil Cienciala Gabriel D. Colletta José Javier Corral-Rivas Anibal Cuchietti Aida Cuni-Sanchez Javid A. Dar Selvadurai Dayanandan Thales de Haulleville Mathieu Decuyper Sylvain Delabye Géraldine Derroire Ben DeVries John Diisi Tran Van Do Jiri Dolezal Aurélie Dourdain Graham P. Durrheim Nestor Laurier Engone Obiang Corneille E. N. Ewango Teresa J. Eyre Tom M. Fayle Lethicia Flavine N. Feunang Leena Finér Markus Fischer Jonas Fridman Lorenzo Frizzera André L. de Gasper Damiano Gianelle Henry B. Glick Maria Socorro Gonzalez-Elizondo Lev Gorenstein Richard Habonayo Olivier J. Hardy David J. Harris Andrew Hector Andreas Hemp Martin Herold Annika Hillers Wannes Hubau Thomas Ibanez Nobuo Imai Gerard Imani Andrzej M. Jagodzinski Stepan Janecek Vivian Kvist Johannsen Carlos A. Joly Blaise Jumbam Banoho L. P. R. Kabelong Goytom Abraha Kahsay Viktor Karminov Kuswata Kartawinata Justin N. Kassi Elizabeth Kearsley Deborah K. Kennard Sebastian Kepfer-Rojas Mohammed Latif Khan John N. Kigomo Hyun Seok Kim Carine Klauberg Yannick Klomberg Henn Korjus Subashree Kothandaraman Florian Kraxner Amit Kumar Relawan Kuswandi Mait Lang Michael J. Lawes Rodrigo V. Leite Geoffrey Lentner Simon L. Lewis Moses B. Libalah Janvier Lisingo Pablito Marcelo López-Serrano Huicui Lu Natalia V. Lukina Anne Mette Lykke Vincent Maicher Brian S. Maitner Eric Marcon Andrew R. Marshall Emanuel H. Martin Olga Martynenko Faustin M. Mbayu Musingo T. E. Mbuvi Jorge A. Meave Cory Merow Stanislaw Miscicki Vanessa S. Moreno Albert Morera Sharif A. Mukul Jörg C. Müller Agustinus Murdjoko Maria Guadalupe Nava-Miranda Litonga Elias Ndive Victor J. Neldner Radovan V. Nevenic Louis N. Nforbelie Michael L. Ngoh Anny E. N’Guessan Michael R. Ngugi Alain S. K. Ngute Emile Narcisse N. Njila Melanie C. Nyako Thomas O. Ochuodho Jacek Oleksyn Alain Paquette Elena I. Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Sebastian Pfautsch Oliver L. Phillips Maria T. F. Piedade Daniel Piotto Martina Pollastrini Lourens Poorter John R. Poulsen Axel Dalberg Poulsen Hans Pretzsch Mirco Rodeghiero Samir G. Rolim Francesco Rovero Ervan Rutishauser Khosro Sagheb-Talebi Purabi Saikia Moses Nsanyi Sainge Christian Salas-Eljatib Antonello Salis Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Vladimír Šebeň Giacomo Sellan Federico Selvi Josep M. Serra-Diaz Douglas Sheil Anatoly Z. Shvidenko Plinio Sist Alexandre F. Souza Krzysztof J. Stereńczak Martin J. P. Sullivan Somaiah Sundarapandian Miroslav Svoboda Mike D. Swaine Natalia Targhetta Nadja Tchebakova Liam A. Trethowan Robert Tropek John Tshibamba Mukendi Peter Mbanda Umunay Vladimir A. Usoltsev Gaia Vaglio Laurin Riccardo Valentini Fernando Valladares Fons van der Plas Daniel José Vega-Nieva Hans Verbeeck Helder Viana Alexander C. Vibrans Simone A. Vieira Jason Vleminckx Catherine E. Waite Hua-Feng Wang Eric Katembo Wasingya Chemuku Wekesa Bertil Westerlund Florian Wittmann Verginia Wortel Tomasz Zawiła-Niedźwiecki Chunyu Zhang Xiuhai Zhao Jun Zhu Xiao Zhu Zhi-Xin Zhu Irie C. Zo-Bi Cang HuiAbstract
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.
Abstract
The preservation of the functionality of forest soil is a key aspect in planning mechanized harvesting operations. Therefore, knowledge and information about stand and soil characteristics are vital to the planning process. In this respect, depth-to-water (DTW) maps were reviewed with regard to their potential use as a prediction tool for wheel ruts. To test the applicability of open source DTW maps for prediction of rutting, the ground surface conditions of 20 clear-cut sites were recorded post harvesting, using an unmanned aerial vehicle (UAV). In total, 80 km of machine tracks were categorized by the severity of occurring rut-formations to investigate whether: i) operators intuitively avoid areas with low DTW values, ii) a correlation exists between decreasing DTW values and increasing rut severity, and iii) DTW maps can serve as reliable decision-making tool in minimizing the environmental effects of big machinery deployment. While the machine operators did not have access to these predictions (DTW maps) during the operations, there was no visual evidence that driving through these areas was actively avoided, resulting in a higher density of severe rutting within areas with DTW values <1 m. A logistic regression analysis confirmed that the probability of severe rutting rapidly increases with decreasing DTW values. However, significant differences between sites exist which might be attributed to a series of other factors such as soil type, weather conditions, number of passes and load capacity. Monitoring these factors is hence highly recommended in any further follow-up studies on soil trafficability.
Authors
Marta Vergarechea Rasmus Astrup Carolin Fischer Knut Øistad Clemens Blattert Markus Hartikainen Kyle Eyvindson Fulvio Di Fulvio Nicklas Forsell Daniel Burgas Astor Toraño-Caicoya Mikko Mönkkönen Clara Antón FernándezAbstract
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving mitigation targets and at the same time meet nationally determined targets for other FES. Using data from the Norwegian national forest inventory (NFI) we simulated the development of Norwegian forests under different management regimes and defined different forest policy scenarios, according to the most relevant forest policies in Norway: national forest policy (NFS), biodiversity policy (BIOS), and bioeconomy policy (BIES). Finally, through multi-objective optimization, we identified the combination of management regimes matching best with each policy scenario. The results for all scenarios indicated that Norway will be able to satisfy wood demands of up to 17 million m3 in 2093. However, the policy objectives for FES under each scenario caused substantial differences in terms of the management regimes selected. We observed that BIES and NFS resulted in very similar forest management programs in Norway, with a dominance of extensive management regimes. In BIOS there was an increase of set aside areas and continuous cover forestry, which made it more compatible with biodiversity indicators. We also found multiple synergies and trade-offs between the FES, likely influenced by the definition of the policy targets at the national scale.
Authors
Joyce Machado Nunes Romeiro Tron Haakon Eid Clara Antón Fernández Annika Kangas Erik TrømborgAbstract
It is expected that European Boreal and Temperate forests will be greatly affected by climate change, causing natural disturbances to increase in frequency and severity. To detangle how, through forest management, we can make forests less vulnerable to the impact of natural disturbances, we need to include the risks of such disturbances in our decision-making tools. The present review investigates: i) how the most important forestry-related natural disturbances are linked to climate change, and ii) different modelling approaches that assess the risks of natural disturbances and their applicability for large-scale forest management planning. Global warming will decrease frozen soil periods, which increases root rot, snow, ice and wind damage, cascading into an increment of bark beetle damage. Central Europe will experience a decrease in precipitation and increase in temperature, which lowers tree defenses against bark beetles and increases root rot infestations. Ice and wet snow damages are expected to increase in Northern Boreal forests, and to reduce in Temperate and Southern Boreal forests. However, lack of snow cover may increase cases of frost-damaged seedlings. The increased temperatures and drought periods, together with a fuel increment from other disturbances, likely enhance wildfire risk, especially for Temperate forests. For the review of European modelling approaches, thirty-nine disturbance models were assessed and categorized according to their required input variables and to the models’ outputs. Probability models are usually common for all disturbance model approaches, however, models that predict disturbance effects seem to be scarce.
Abstract
SiTree is a flexible, cross-platform, open-source framework for individual-tree simulators intended to facilitate accurate and flexible analyses of forest growth and yield, or more generally forest dynamics simulations. SiTree provides generic functionality to build customized individual-tree simulators using additional user-written code. In the forestry literature there are a wide variety of individual models that describe the different parts of forest growth and dynamics and new models are continuously developed and published. The aim of SiTree is to provide a broad community of R-users within forestry with an easily adaptable individual-tree simulator framework and an easily accessible tool for testing and combining new and existing models describing parts of forest growth dynamics.
Abstract
Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included.
Abstract
No abstract has been registered
Abstract
Forest harvest residue is a low-competitive biomass feedstock that is usually left to decay on site after forestry operations. Its removal and pyrolytic conversion to biochar is seen as an opportunity to reduce terrestrial CO2 emissions and mitigate climate change. The mitigation effect of biochar is, however, ultimately dependent on the availability of the biomass feedstock, thus CO2 removal of biochar needs to be assessed in relation to the capacity to supply biochar systems with biomass feedstocks over prolonged time scales, relevant for climate mitigation. In the present study we used an assembly of empirical models to forecast the effects of harvest residue removal on soil C storage and the technical capacity of biochar to mitigate national-scale emissions over the century, using Norway as a case study for boreal conditions. We estimate the mitigation potential to vary between 0.41 and 0.78 Tg CO2 equivalents yr−1, of which 79% could be attributed to increased soil C stock, and 21% to the coproduction of bioenergy. These values correspond to 9–17% of the emissions of the Norwegian agricultural sector and to 0.8–1.5% of the total national emission. This illustrates that deployment of biochar from forest harvest residues in countries with a large forestry sector, relative to economy and population size, is likely to have a relatively small contribution to national emission reduction targets but may have a large effect on agricultural emission and commitments. Strategies for biochar deployment need to consider that biochar's mitigation effect is limited by the feedstock supply which needs to be critically assessed.
Abstract
No abstract has been registered
Abstract
Forest structural properties largely govern surface fluxes of moisture, energy, and momentum that strongly affect regional climate and hydrology. Forest structural properties are greatly shaped by forest management activities, especially in the Fennoscandia (Norway, Sweden, and Finland). Insight into transient developments in forest structure in response to management intervention is therefore essential to understanding the role of forest management in mitigating regional climate change. The aim of this study is to present a simple grid-based framework – the Fennoscandic Forest State Simulator (F2S2) -- for predicting time-dependent forest structural trajectories in a manner compatible with land models employed in offline or asynchronously coupled climate and hydrological research. F2S2 enables the prescription of future regional forest structure as a function of: i) exogenously defined scenarios of forest harvest intensity; ii) forest management intensity; iii) climate forcing. We demonstrate its application when applied as a stand-alone tool for forecasting three alternative future forest states in Norway that differ with respect to background climate forcing, forest harvest intensity (linked to two Shared Socio-economic Pathways (SSPs)), and forest management intensity. F2S2 captures impacts of climate forcing and forest management on general trends in forest structural development over time, and while climate is the main driver of longer-term forest structural dynamics, the role of harvests and other management-driven effects cannot be overlooked. To our knowledge this is the first paper presenting a method to map forest structure in space and time in a way that is compatible with land surface or hydrological models employing sub-grid tiling.
Abstract
A new stand-level growth and yield model, consisting of component equations for stand volume, basal area, survival, and dominant stand height, was developed from a dataset of long-term trials for managed thinned and unthinned even-aged Norway spruce (Picea abies (L.) Karst.) forests in Norway. The developed models predict considerably faster growth rates than the existing Norwegian models. Further, it was found that the existing Norwegian stand-level models do not match the data from the thinning trails. The significance of thinning response functions indicated that thinning increases basal area growth while reducing competition related mortality. No significant effects of thinning were found in the dominant stand height growth. Model examination by means of cross-validation indicated that the models were unbiased and performed well within the data range. An application of the developed stand-level model highlights the potential use for these models in comparing different management scenarios.
Abstract
As a carbon dioxide removal measure, the Norwegian government is currently considering a policy of large-scale planting of spruce (Picea abies (L) H. Karst) on lands in various states of natural transition to a forest dominated by deciduous broadleaved tree species. Given the aspiration to bring emissions on balance with removals in the latter half of the 21st century in effort to limit the global mean temperature rise to “well below” 2°C, the effectiveness of such a policy is unclear given relatively low spruce growth rates in the region. Further convoluting the picture is the magnitude and relevance of surface albedo changes linked to such projects, which typically counteract the benefits of an enhanced forest CO2 sink in high-latitude regions. Here, we carry out a rigorous empirically based assessment of the terrestrial carbon dioxide removal (tCDR) potential of large-scale spruce planting in Norway, taking into account transient developments in both terrestrial carbon sinks and surface albedo over the 21st century and beyond. We find that surface albedo changes would likely play a negligible role in counteracting tCDR, yet given low forest growth rates in the region, notable tCDR benefits from such projects would not be realized until the second half of the 21st century, with maximum benefits occurring even later around 2150. We estimate Norway's total accumulated tCDR potential at 2100 and 2150 (including surface albedo changes) to be 447 (±240) and 852 (±295) Mt CO2-eq. at mean net present values of US$ 12 (±3) and US$ 13 (±2) per ton CDR, respectively. For perspective, the accumulated tCDR potential at 2100 represents around 8 years of Norway's total current annual production-based (i.e., territorial) CO2-eq. emissions.
Authors
Constantin M. Zohner Lidong Mo Susanne S. Renner Jens-Christian Svenning Yann Vitasse Blas Manuel Benito De Pando Alejandro Ordonez Frederik Baumgarten Jean-François Bastin Veronica Sebald Peter B. Reich Jingjing Liang Gert-Jan Nabuurs Sergio de-Miguel Giorgio Alberti Clara Antón Fernández Radomir Balazy Urs-Beat Brändli Han Y. H. Chen Chelsea Chisholm Emil Cienciala Selvadurai Dayanandan Tom M. Fayle Lorenzo Frizzera Damiano Gianelle Andrzej M. Jagodzinski Bogdan Jaroszewicz Tommaso Jucker Sebastian Kepfer-Rojas Mohammed Latif Khan Hyun Seok Kim Henn Korjus Vivian Kvist Johannsen Diana Laarmann Mait Lang Tomasz Zawila-Niedzwiecki Pascal A. Niklaus Alain Paquette Hans Pretzsch Purabi Saikia Peter Schall Vladimír Šebeň Miroslav Svoboda Elena Tikhonova Helder Viana Chunyu Zhang Xiuhai Zhao Thomas W. CrowtherAbstract
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.
Authors
Jouni Siipilehto Micky Allen Urban Nilsson Andreas Brunner Saija Huuskonen Soili Haikarainen Narayanan Subramanian Clara Antón Fernández Emma Holmström Kjell Andreassen Jari HynynenAbstract
New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.
Authors
Hanne Kathrine Sjølie Clara Antón Fernández Luiz Goulart Jogeir N. Stokland Gregory S. Latta Birger SolbergAbstract
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Abstract
An understanding of the relationship between volume increment and stand density (basal area, stand density index, etc.) is of utmost importance for properly managing stand density to achieve specific management objectives. There are two main approaches to analyse growth–density relationships. The first relates volume increment to stand density through a basic relationship, which can vary with site productivity, age, and potentially incorporates treatment effects. The second is to relate the volume increment and density of thinned experimental plots relative to that of an unthinned experimental plot on the same site. Using a dataset of 229 thinned and unthinned experimental plots of Norway spruce, a growth model is developed describing the relationship between gross or net volume increment and basal area. The models indicate that gross volume increases with increasing basal area up to 50 m2 and thereafter becomes constant out to the maximum basal area. Alternatively, net volume increment was maximized at a basal area of 43 m2 and decreased with further increases in basal area. However, the models indicated a wide range where net volume increment was essentially constant, varying by less than 1 m3 ha−1 year−1. An analysis of different thinning scenarios indicated that the relative relationship between volume increment and stand density was dynamic and changed over the course of a rotation.
Authors
B.S. Steidinger Thomas W. Crowther Jingjing Liang M. E. Van Nuland G.D.A. Werner Peter B. Reich Gert-Jan Nabuurs Sergio de-Miguel M. Zhou N. Picard Bruno Herault Xiuhai Zhao C. Zhang D. Routh Kabir G Peay Meinrad Abegg C. Yves Adou Yao Giorgio Alberti Angelica Almeyda Zambrano Esteban Alvarez-Davila Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernández Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo Aymard Timothy R. Baker Radomir Bałazy Olaf Bánki Jorcely Barroso Meredith Bastian Jean-François Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Francis Q. Brearley Roel J. W. Brienen Eben Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo Cesar Goran Cesljar Robin L. Chazdon Han Y. H. Chen Chelsea L. Chisholm Emil Cienciala Connie J. Clark David Clark Gabriel Colletta Richard Condit David Coomes Fernando Cornejo Valverde Jose J. Corral-Rivas Philip Crim Jonathan Cumming Selvadurai Dayanandan André L. de Gasper Mathieu Decuyper Géraldine Derroire Ben DeVries Ilija Djordjevic Amaral Iêda Aurélie Dourdain Nestor Laurier Engone Obiang Brian J. Enquist Teresa Eyre Adandé Belarmain Fandohan Tom M. Fayle Ted R. Feldpausch Leena Finér Markus Fischer Christine Fletcher Jonas Fridman Lorenzo Frizzera Javier G. P. Gamarra Damiano Gianelle Henry B. Glick David J. Harris Andy Hector Andreas Hemp Geerten Hengeveld John Herbohn Martin Herold Annika Hillers Eurídice N. Honorio Coronado Markus Huber Cang Hui Hyunkook Cho Thomas Ibanez Ilbin Jung Nobuo Imai Andrzej M. Jagodzinski Bogdan Jaroszewicz Vivian Kvist Johannsen Carlos A. Joly Tommaso Jucker Viktor Karminov Kuswata Kartawinata Elizabeth Kearsley David Kenfack Deborah Kennard Sebastian Kepfer-Rojas Gunnar Keppel Mohammed Latif Khan Timothy Killeen Hyun Seok Kim Kanehiro Kitayama Michael Köhl Henn Korjus Florian Kraxner Diana Laarmann Mait Lang Simon L. Lewis Huicui Lu Natalia Lukina Brian S. Maitner Yadvinder Malhi Eric Marcon Beatriz Schwantes Marimon Ben Hur Marimon-Junior Andrew R. Marshall Emanuel H. Martin Olga Martynenko Jorge A. Meave Omar Melo-Cruz Casimiro Mendoza Cory Merow Abel Monteagudo Mendoza Vanessa Moreno Sharif A. Mukul Philip Mundhenk Maria G. Nava-Miranda David Neill Victor Neldner Radovan Nevenic Michael Ngugi Pascal Niklaus Jacek Oleksyn Petr Ontikov Edgar Ortiz-Malavasi Yude Pan Alain Paquette Alexander Parada-Gutierrez Elena Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Oliver Phillips Maria Teresa Piedade Daniel Piotto Nigel Pitman Irina Polo Lourens Poorter Axel Dalberg Poulsen John R. Poulsen Hans Pretzsch Freddy Ramirez Arevalo Zorayda Restrepo-Correa Mirco Rodeghiero Samir Rolim Anand Roopsind Francesco Rovero Ervan Rutishauser Purabi Saikia Philippe Saner Peter Schall Mart-Jan Schelhaas Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Eric Searle Vladimír Seben Josep M. Serra-Diaz Christian Salas Douglas Sheil Anatoly Shvidenko Javier Silva-Espejo Marcos Silveira James Singh Plinio Sist Ferry Slik Bonaventure Sonké Alexandre F. Souza Krzysztof Stereńczak Jens-Christian Svenning Miroslav Svoboda Natalia Targhetta Nadezhda M. Tchebakova Hans ter Steege Raquel Thomas Elena Tikhonova Peter Umunay Vladimir Usoltsev Fernando Valladares Fons van der Plas Tran Van Do Rodolfo Vasquez Martinez Hans Verbeeck Helder Viana Simone Vieira Klaus von Gadow Hua-Feng Wang James Watson Bertil Westerlund Susan Wiser Florian Wittmann Verginia Wortel Roderick Zagt Tomasz Zawila-Niedzwiecki Zhi-Xin Zhu Irie Casimir Zo-BiAbstract
No abstract has been registered
Authors
B. S. Steidinger T. W. Crowther J. Liang M. E. Van Nuland G. D. A. Werner P. B. Reich G. J. Nabuurs S. de-Miguel M. Zhou N. Picard B. Herault X. Zhao C. Zhang D. Routh Meinrad Abegg C. Yves Adou Yao Giorgio Alberti Angelica Almeyda Zambrano Esteban Alvarez-Davila Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernández Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo Aymard Timothy Baker Radomir Bałazy Olaf Bánki Jorcely Barroso Meredith Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Francis Q. Brearley Roel Brienen Eben Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo Cesar Goran Cesljar Robin Chazdon Han Y. H. Chen Douglas Sheil K. G. PeayAbstract
The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools1,2, sequester carbon3,4 and withstand the effects of climate change5,6. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species7, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species.
Authors
Jari Vauhkonen Ambros Berger Thomas Gschwantner Klemens Schadauer Philippe Lejeune Jérôme Perin Mikhail Pitchugin Radim Adolt Miroslav Zeman Vivian Kvist Johannsen Sebastian Kepfer-Rojas Allan Sims Claire Bastick François Morneau Antoine Colin Susann Bender Pál Kovácsevics György Solti László Kolozs Dóra Nagy Kinga Nagy Mark Twomey John Redmond Patrizia Gasparini M. Notarangelo Maria Rizzo Kristaps Makovskis Andis Lazdins Ainars Lupikis Gintaras Kulbokas Clara Antón Fernández Francisco Castro Rego Leónia Nunes Gheorghe Marin Catalin Calota Damjan Pantić Dragan Borota Joerg Roessiger Michal Bosela Vladimír Šebeň Mitja Skudnik Patricia Adame Iciar Alberdi Isabel Cañellas Torgny Lind Renats Trubins Esther Thürig Golo Stadelmann Ben Ditchburn David Ross Justin Gilbert Lesley Halsall Markus Lier Tuula PackalenAbstract
No abstract has been registered
Authors
Jari Vauhkonen Ambros Berger Thomas Gschwantner Klemens Schadauer Philippe Lejeune Jérôme Perin Mikhail Pitchugin Radim Adolt Miroslav Zeman Vivian Kvist Johannsen Sebastian Kepfer-Rojas Allan Sims Claire Bastick François Morneau Antoine Colin Susann Bender Pál Kovácsevics György Solti László Kolozs Dóra Nagy Kinga Nagy Mark Twomey John Redmond Patrizia Gasparini Monica Notarangelo Maria Rizzo Kristaps Makovskis Andis Lazdins Ainars Lupikis Gintaras Kulbokas Clara Antón Fernández Francisco Castro Rego Leónia Nunes Gheorghe Marin Catalin Calota Damjan Pantić Dragan Borota Joerg Roessiger Michal Bosela Vladimír Šebeň Mitja Skudnik Patricia Adame Iciar Alberdi Isabel Cañellas Torgny Lind Renats Trubins Esther Thürig Golo Stadelmann Ben Ditchburn David Ross Justin Gilbert Lesley Halsall Markus Lier Tuula PackalenAbstract
• Key message A dataset of forest resource projections in 23 European countries to 2040 has been prepared for forest-related policy analysis and decision-making. Due to applying harmonised definitions, while maintaining country-specific forestry practices, the projections should be usable from national to international levels. The dataset can be accessed at https://doi.org/10.5061/dryad.4t880qh . The associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/8f93e0d6-b524-43bd-bdb8-621ad5ae6fa9 .
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Clara Antón FernándezAbstract
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Jonathan Rizzi Clara Antón Fernández Paulo Jorge de Almeida Borges Ryan Bright Rasmus AstrupAbstract
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The present study aims to develop biologically sound and parsimonious site index models for Norway to predict changes in site index (SI) under different climatic conditions. The models are constructed using data from the Norwegian National Forest Inventory and climate data from the Norwegian meteorological institute. Site index was modeled using the potential modifier functional form, with a potential component (POT) depending on site quality classes and two modifier components (MOD): temperature and moisture. Each of these modifiers was based on a portfolio of candidate variables. The best model for spruce-dominated stands included temperature as modifier (R2 = 0.56). In the case of pine- and deciduous-dominated stands, the best models included both modifiers (R2 = 0.40 and 0.54 for temperature and moisture, respectively). We illustrate the use of the models by analyzing the possible shift in SI for year 2100 under one (RCP4.5) of the benchmark scenarios adopted by the Intergovernmental Panel on Climate Change for its fifth assessment report. The models presented can be valuable for evaluating the effect of climate change scenarios in Norwegian forests.
Authors
Lise Dalsgaard Rasmus Astrup Clara Antón Fernández Signe Kynding Borgen Johannes Breidenbach Holger Lange Aleksi Lehtonen Jari LiskiAbstract
Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.
Authors
Susana Barreiro Mart-Jan Schelhaas Gerald Kändler Clara Antón Fernández Antoine Colin Jean-Daniel Bontemps Iciar Alberdi Sonia Condés Marius Dumitru Angel Ferezliev Christoph Fischer Patrizia Gasparini Thomas Gschwantner Georg Kindermann Bjarki Kjartansson Pál Kovácsevics Milos Kucera Anders Lundström Gheorghe Marin Gintautas Mozgeris Thomas Nord-Larsen Tuula Packalen John Redmond Sandro Sacchelli Allan Sims Arnór Snorrason Nickola Stoyanov Esther Thürig Per-Erik WikbergAbstract
Key Message. This analysis of the tools and methods currently in use for reporting woody biomass availability in 21 European countries has shown that most countries use, or are developing, National Forest Inventory-oriented models whereas the others use standwise forest inventory--oriented methods. Context. Knowledge of realistic and sustainable wood availability in Europe is highly relevant to define climate change mitigation strategies at national and European level, to support the development of realistic targets for increased use of renewable energy sources and of industry wood. Future scenarios at European level highlight a deficit of domestic wood supply compared to wood consumption, and some European countries state they are harvesting above the increment. Aims. Several country-level studies on wood availability have been performed for international reporting. However, it remains essential to improve the knowledge on the projection methods used across Europe to better evaluate forecasts. Methods. Analysis was based on descriptions supplied by the national correspondentsinvolved in USEWOOD COST Action (FP1001), and further enriched with additionaldata from international reports that allowedcharacterisation of the forests in these countries for the same base year. Results. Methods currently used for projecting wood availability were described for 21 European countries. Projection systems based on National Forest Inventory (NFI) data prevail over methods based on forest management plans. Only a few countries lack nationwide projection tools, still using tools developed for specific areas. Conclusions. A wide range of NFI-based systems for projecting wood availability exists, being under permanent improvement. The validation of projection forecasts and the inclusion of climate sensitive growth models into these tools are common aims for most countries. Cooperation among countries would result in higher efficiency when developing and improving projection tools and better comparability among them.
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Authors
Ryan Bright Clara Antón Fernández Rasmus Astrup Francesco Cherubini Maria Malene Kvalevåg Anders Hammer StrømmanAbstract
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Lise Dalsgaard Clara Antón Fernández Rasmus Astrup Signe Kynding Borgen Johannes Breidenbach Holger Lange Jogeir N. Stokland Gunnhild SøgaardAbstract
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Authors
Ryan Bright Francesco Cherubini Rasmus Astrup Clara Antón Fernández Anders Hammer Strømman Maria Malene KvalevågAbstract
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Ryan Bright Rasmus Astrup Anders Hammer Strømman Clara Antón Fernández Maria Malene Kvalevåg Francesco CherubiniAbstract
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National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates results not only from selecting a sample of the population but also from uncertainties in the models used to predict the variables of interest. The aim of this study was to quantify the model-related variability of Norway spruce (Picea abies [L.] Karst) biomass stock and change estimates for the Norwegian NFI. The model-related variability of the estimates stems from uncertainty in parameter estimates of biomass models as well as residual variability and was quantified using a Monte Carlo simulation technique. Uncertainties in model parameter estimates, which are often not available for published biomass models, had considerable influence on the model-related variability of biomass stock and change estimates. The assumption that the residual variability is larger than documented for the models and the correlation of within-plot model residuals influenced the model-related variability of biomass stock change estimates much more than estimates of the biomass stock. The larger influence on the stock change resulted from the large influence of harvests on the stock change, although harvests were observed rarely on the NFI sample plots in the 5-year period that was considered. In addition, the temporal correlation between model residuals due to changes in the allometry had considerable influence on the model-related variability of the biomass stock change estimate. The allometry may, however, be assumed to be rather stable over a 5-year period. Because the effects of model-related variability of the biomass stock and change estimates were much smaller than those of the sampling-related variability, efforts to increase the precision of estimates should focus on reducing the sampling variability. If the model-related variability is to be decreased, the focus should be on the tree fractions of living branches as well as stump and roots.
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Harvest activity directly impacts timber supply, forest conditions, and carbon stock. Forecasts of the harvest activity have traditionally relied on the assumption that harvest is carried out according to forest management guidelines or to maximize forest value. However, these rules are, in practice, seldom applied systematically, which may result in large discrepancies between predicted and actual harvest in short-term forecasts. We present empirical harvest models that predict final felling and thinning based on forest attributes such as site index, stand age, volume, slope, and distance to road. The logistic regression models were developed and fit to Norwegian national forest inventory data and predict harvest with high discriminating power. The models were consistent with expected landowners behavior, that is, areas with high timber value and low harvest cost were more likely to be harvested. We illustrate how the harvest models can be used, in combination with a growth model, to develop a national business-as-usual scenario for forest carbon. The business-as-usual scenario shows a slight increase in national harvest levels and a decrease in carbon sequestration in living trees over the next decade.
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