• Energy Research

La biomasse aérienne (AGB) est considérée comme une variable climatique essentielle qui sous-tend nos connaissances et nos informations sur le rôle des forêts dans l'atténuation du changement climatique. La disponibilité des produits AGB et AGB change (ΔAGB) par satellite a augmenté ces dernières années. Ici, nous avons évalué le ΔAGB net de la dernière décennie dérivé de quatre cartes AGB multi-dates mondiales récentes : cartes ESA-CCI, modèle WRI-Flux, séries temporelles JPL et séries temporelles SMOS-LVOD. Nos évaluations explorent et utilisent différentes sources de données de référence avec des réévaluations de la biomasse au cours de la dernière décennie. Les données de référence comprennent les données des placettes de l'Inventaire forestier national (INF), les cartes ΔAGB locales du LiDAR aéroporté et certaines données de pays de l'Évaluation des ressources forestières provenant de pays dotés de capacités de suivi bien développées. Des comparaisons entre la carte et les données de référence ont été effectuées à des niveaux allant de 100 m à 25 km d'échelle spatiale. Les comparaisons ont révélé que les données LiDAR se comparaient le plus raisonnablement aux cartes, tandis que les comparaisons utilisant NFI ne montraient que quelques accords à des niveaux d'agrégation <10 km. Quel que soit le niveau d'agrégation, les pertes et les gains d'AGB selon les comparaisons cartographiques étaient systématiquement inférieurs aux données de référence. Les comparaisons de cartes à 25 km ont mis en évidence que les cartes capturaient systématiquement les pertes d'AGB dans les points chauds de déforestation connus. Les comparaisons ont également identifié plusieurs régions de puits de carbone systématiquement détectées par toutes les cartes. Cependant, les désaccords entre les cartes sont encore importants dans les régions forestières clés telles que le bassin amazonien. La corrélation croisée globale des cartes ΔAGB entre les cartes variait entre 0,11 et 0,29 (r). Les magnitudes ΔAGB déclarées étaient les plus grandes dans les ensembles de données à haute résolution, y compris les méthodes de différentiation de carte CCI (variation de stock) et de modèle de flux (gain-perte), tandis qu'elles étaient les plus petites selon les produits de séries chronologiques LVOD et JPL à résolution plus grossière, en particulier pour les gains AGB. Nos résultats suggèrent que le ΔAGB évalué à partir des cartes actuelles peut être biaisé et toute utilisation des estimations devrait en tenir compte. Actuellement, les données de référence ΔAGB sont rares, en particulier sous les tropiques, mais ce déficit peut être atténué par les réseaux de données LiDAR à venir dans le contexte des Supersites et des GEO-Trees. La biomasa sobre el suelo (AGB) se considera una variable climática esencial que sustenta nuestro conocimiento e información sobre el papel de los bosques en la mitigación del cambio climático. La disponibilidad de productos AGB y AGB change (ΔAGB) basados en satélites ha aumentado en los últimos años. Aquí evaluamos la ΔAGB neta de la última década derivada de cuatro mapas AGB globales de múltiples fechas recientes: mapas ESA-CCI, modelo WRI-Flux, series de tiempo JPL y series de tiempo SMOS-LVOD. Nuestras evaluaciones exploran y utilizan diferentes fuentes de datos de referencia con nuevas mediciones de biomasa en la última década. Los datos de referencia comprenden datos de parcelas del Inventario Forestal Nacional (NFI), mapas locales ΔAGB de LiDAR aerotransportado y datos de países seleccionados de Evaluación de Recursos Forestales de países con capacidades de monitoreo bien desarrolladas. Las comparaciones del mapa con los datos de referencia se realizaron a niveles que van desde una escala espacial de 100 m a 25 km. Las comparaciones revelaron que los datos LiDAR se compararon más razonablemente con los mapas, mientras que las comparaciones utilizando NFI solo mostraron algunos acuerdos a niveles de agregación <10 km. Independientemente del nivel de agregación, las pérdidas y ganancias de AGB de acuerdo con las comparaciones del mapa fueron consistentemente menores que los datos de referencia. Las comparaciones mapa-mapa a 25 km destacaron que los mapas capturaron consistentemente las pérdidas de AGB en puntos críticos de deforestación conocidos. Las comparaciones también identificaron varias regiones sumideras de carbono detectadas consistentemente por todos los mapas. Sin embargo, el desacuerdo entre los mapas sigue siendo grande en regiones forestales clave como la cuenca del Amazonas. La correlación cruzada general del mapa ΔAGB entre los mapas varió en el rango de 0.11-0.29 (r). Las magnitudes ΔAGB informadas fueron las más grandes en los conjuntos de datos de alta resolución, incluidos los métodos de diferenciación de mapas CCI (cambio de stock) y modelo de flujo (ganancia-pérdida), mientras que fueron las más pequeñas de acuerdo con los productos de series de tiempo LVOD y JPL de resolución más gruesa, especialmente para las ganancias AGB. Nuestros resultados sugieren que la ΔAGB evaluada a partir de los mapas actuales puede estar sesgada y cualquier uso de las estimaciones debe tenerlo en cuenta. Actualmente, los datos de referencia de ΔAGB son escasos, especialmente en los trópicos, pero ese déficit puede aliviarse con las próximas redes de datos LiDAR en el contexto de los supersitios y los árboles GEO. Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees. تعتبر الكتلة الحيوية فوق الأرض (AGB) متغيرًا مناخيًا أساسيًا يدعم معرفتنا ومعلوماتنا حول دور الغابات في التخفيف من تغير المناخ. زاد توافر منتجات تغيير AGB و AGB المستندة إلى الأقمار الصناعية (ΔAGB) في السنوات الأخيرة. هنا قمنا بتقييم صافي ΔAGB للعقد الماضي المستمد من أربع خرائط AGB عالمية حديثة متعددة التواريخ: خرائط ESA - CCI، ونموذج WRI - Flowx، والسلاسل الزمنية JPL، والسلاسل الزمنية SMOS - LVOD. تستكشف تقييماتنا وتستخدم مصادر بيانات مرجعية مختلفة مع إعادة قياس الكتلة الحيوية خلال العقد الماضي. تشمل البيانات المرجعية بيانات قطع الأراضي الوطنية للغابات (NFI)، وخرائط ΔAGB المحلية من LiDAR المحمولة جواً، وبيانات قطرية مختارة لتقييم الموارد الحرجية من البلدان ذات قدرات الرصد المتطورة. تم إجراء مقارنات بين الخريطة والبيانات المرجعية على مستويات تتراوح من 100 متر إلى 25 كم على نطاق مكاني. كشفت المقارنات أن بيانات ليدار قارنت بشكل معقول مع الخرائط، في حين أن المقارنات باستخدام المواد غير الغذائية أظهرت فقط بعض الاتفاقات عند مستويات التجميع <10 كم. بغض النظر عن مستوى التجميع، كانت خسائر ومكاسب AGB وفقًا لمقارنات الخريطة أصغر باستمرار من البيانات المرجعية. سلطت مقارنات الخرائط على بعد 25 كم الضوء على أن الخرائط سجلت باستمرار خسائر AGB في النقاط الساخنة المعروفة لإزالة الغابات. كما حددت المقارنات العديد من مناطق بالوعة الكربون التي تم اكتشافها باستمرار من قبل جميع الخرائط. ومع ذلك، لا يزال الخلاف بين الخرائط كبيرًا في مناطق الغابات الرئيسية مثل حوض الأمازون. اختلف الارتباط التبادلي العام لخريطة ΔAGB بين الخرائط في النطاق 0.11–0.29 (r). كانت مقادير ΔAGB المبلغ عنها هي الأكبر في مجموعات البيانات عالية الدقة بما في ذلك اختلافات خريطة CCI (تغيير الأسهم) وطرق نموذج Flux (الربح والخسارة)، في حين كانت أصغر وفقًا لمنتجات السلاسل الزمنية LVOD و JPL ذات الدقة الخشنة، خاصة بالنسبة لمكاسب AGB. تشير نتائجنا إلى أن ΔAGB المقيّمة من الخرائط الحالية يمكن أن تكون متحيزة وأي استخدام للتقديرات يجب أن يأخذ ذلك في الاعتبار. في الوقت الحالي، البيانات المرجعية ΔAGB متناثرة خاصة في المناطق الاستوائية ولكن يمكن تخفيف هذا العجز من خلال شبكات بيانات ليدار القادمة في سياق المواقع الفائقة والأشجار الجغرافية.

The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a significant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difficult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simplifications, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reflection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty - which is imperative for decision making - without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support.

Background: Over the last decades, many forest simulators have been developed for the forests of individual European countries. The underlying growth models are usually based on national datasets of varying size, obtained from National Forest Inventories or from long-term research plots. Many of these models include country- and location-specific predictors, such as site quality indices that may aggregate climate, soil properties and topography effects. Consequently, it is not sensible to compare such models among countries, and it is often impossible to apply models outside the region or country they were developed for. However, there is a clear need for more generically applicable but still locally accurate and climate sensitive simulators at the European scale, which requires the development of models that are applicable across the European continent. The purpose of this study is to develop tree diameter increment models that are applicable at the European scale, but still locally accurate. We compiled and used a dataset of diameter increment observations of over 2.3 million trees from 10 National Forest Inventories in Europe and a set of 99 potential explanatory variables covering forest structure, weather, climate, soiland nutrient deposition. Results: Diameter increment models are presented for 20 species/species groups. Selection of explanatory variables was done using a combination of forward and backward selection methods. The explained variance ranged from 10% to 53% depending on the species. Variables related to forest structure (basal area of the stand and relative size of the tree) contributed most to the explained variance, but environmental variables were important to account for spatial patterns. The type of environmental variables included differed greatly among species. Conclusions: The presented diameter increment models are the first of their kind that are applicable at the European scale. This is an important step towards the development of a new generation of forest development simulators that can be applied at the European scale, but that are sensitive to variations in growing conditions and applicable to a wider range of management systems than before. This allows European scale but detailed analyses concerning topics like CO2 sequestration, wood mobilisation, long term impact of management, etc.

Outbreaks of tree-killing bark beetles have reached unprecedented levels in conifer forests in the northern hemisphere and are expected to further intensify due to climate change. In parts of Europe, bark beetle outbreaks and efforts to manage them have even triggered social unrests and political instability. These events have increasingly challenged traditional responses to outbreaks, and highlight the need for a more comprehensive management framework. Several synthesis papers on different aspects of bark beetle ecology and management exist. However, our understanding of outbreak drivers and impacts, principles of ecosystem management, governance, and the role of climate change in the dynamics of ecological and social systems has rapidly advanced in recent years. These advances are suggesting a reconsideration of previous management strategies. We synthesize the state of knowledge on drivers and impacts of bark beetle outbreaks in Europe and propose a comprehensive context-dependent framework for their management. We illustrate our ideas for two contrasting societal objectives that represent the end-members of a continuum of forest management goals: wood and biomass production and the conservation of biodiversity and natural processes. For production forests, we propose a management approach addressing economic, social, ecological, infrastructural, and legislative aspects of bark beetle disturbances. In conservation forests, where non-intervention is the default option, we elaborate under which circumstances an active intervention is necessary, and whether such an intervention is in conflict with the objective to conserve biodiversity. Our approach revises the current management response to bark beetles in Europe and promotes an interdisciplinary social-ecological approach to dealing with disturbances.

Large-scale forest scenario models are widely used to simulate the development of forests and to compare the carbon balance estimates of different countries. However, as site variability in the application area often exceeds the variability in the calibration area, model validation is important. The aim of this study was to evaluate the European Forest Information Scenario model (EFISCEN). As Switzerland exhibits high spatial and climatic diversity, it was taken as a case study. The model output was compared to measured data in terms of initialization, estimation of growing stock, stand age, increment, management, and natural mortality. Comparisons were done at the country level, but also for regions and site classes. The results showed that the initialization procedure of EFISCEN works well for Switzerland. Moreover, EFISCEN accurately estimated the observed growing stock at the country level. On a regional level, major differences occurred. In particular, distribution of the harvesting amounts, mortality, and age-class distribution deviated considerably from empirical values. For future model applications, we therefore propose to define the required harvesting level not per country, but to specify it for smaller regions. Moreover, the EFISCEN simulations should be improved by refining the mortality function and by incorporating more flexibility in forest management practices.