• Energy Research

La biomasse forestière est un indicateur essentiel pour la surveillance des écosystèmes et du climat de la Terre. Il s'agit d'une contribution essentielle à la comptabilisation des gaz à effet de serre, à l'estimation des pertes de carbone et de la dégradation des forêts, à l'évaluation du potentiel des énergies renouvelables et à l'élaboration de politiques d'atténuation du changement climatique telles que REDD+, entre autres. La cartographie mur à mur de la biomasse aérienne (AGB) est maintenant possible avec la télédétection par satellite (RS). Cependant, les méthodes RS nécessitent des données in situ existantes, à jour, fiables, représentatives et comparables pour l'étalonnage et la validation. Nous présentons ici l'initiative Forest Observation System (Fos), une coopération internationale visant à établir et à maintenir une base de données mondiale sur la biomasse forestière in situ. Les estimations de la hauteur de l'AGB et de la canopée avec leurs incertitudes associées sont dérivées à une échelle de 0,25 ha à partir de mesures sur le terrain effectuées dans des parcelles de recherche permanentes à travers les forêts du monde. Toutes les estimations des placettes sont géolocalisées et ont une taille qui permet une comparaison directe avec de nombreuses mesures RS. Le Fos offre le potentiel d'améliorer la précision des produits de la biomasse à base de RS tout en développant de nouvelles synergies entre la RS et les communautés de recherche sur les écosystèmes terrestres. La biomasa forestal es un indicador esencial para monitorear los ecosistemas y el clima de la Tierra. Es un insumo crítico para la contabilidad de gases de efecto invernadero, la estimación de las pérdidas de carbono y la degradación forestal, la evaluación del potencial de energía renovable y para el desarrollo de políticas de mitigación del cambio climático como REDD+, entre otras. El mapeo de pared a pared de la biomasa sobre el suelo (AGB) ahora es posible con la teledetección satelital (RS). Sin embargo, los métodos de RS requieren datos in situ existentes, actualizados, confiables, representativos y comparables para la calibración y validación. Aquí, presentamos la iniciativa del Sistema de Observación Forestal (FOS), una cooperación internacional para establecer y mantener una base de datos global de biomasa forestal in situ. Las estimaciones de altura de AGB y dosel con sus incertidumbres asociadas se derivan a una escala de 0,25 ha a partir de mediciones de campo realizadas en parcelas de investigación permanentes en los bosques del mundo. Todas las estimaciones de parcelas están geolocalizadas y tienen un tamaño que permite la comparación directa con muchas mediciones de RS. El FOS ofrece el potencial de mejorar la precisión de los productos de biomasa basados en RS al tiempo que desarrolla nuevas sinergias entre las comunidades de investigación de ecosistemas basados en RS y en tierra. Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities. الكتلة الحيوية للغابات هي مؤشر أساسي لرصد النظم الإيكولوجية للأرض ومناخها. وهو مدخل حاسم في المحاسبة المتعلقة بغازات الدفيئة، وتقدير خسائر الكربون وتدهور الغابات، وتقييم إمكانات الطاقة المتجددة، ووضع سياسات للتخفيف من آثار تغير المناخ مثل المبادرة المعززة لخفض الانبعاثات الناجمة عن إزالة الغاباتوتدهورها، من بين أمور أخرى. أصبح من الممكن الآن رسم خرائط من الجدار إلى الجدار للكتلة الحيوية فوق الأرض (AGB) باستخدام الاستشعار عن بعد عبر الأقمار الصناعية (RS). ومع ذلك، تتطلب طرق RS بيانات موجودة وحديثة وموثوقة وتمثيلية وقابلة للمقارنة في الموقع للمعايرة والتحقق من الصحة. نقدم هنا مبادرة نظام مراقبة الغابات، وهو تعاون دولي لإنشاء وصيانة قاعدة بيانات عالمية للكتلة الحيوية للغابات في الموقع. يتم اشتقاق تقديرات ارتفاع AGB والمظلة مع أوجه عدم اليقين المرتبطة بها على مقياس 0.25 هكتار من القياسات الميدانية التي تم إجراؤها في قطع البحث الدائمة عبر غابات العالم. جميع تقديرات المخطط محددة جغرافيًا ولها حجم يسمح بالمقارنة المباشرة مع العديد من قياسات RS. يوفر نظام التشغيل الحر إمكانية تحسين دقة منتجات الكتلة الحيوية القائمة على RS مع تطوير أوجه تآزر جديدة بين RS ومجتمعات أبحاث النظام الإيكولوجي الأرضية.

Abstract For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.

AbstractTropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, $$\varPsi $$ Ψ 50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3–5, little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters $$\varPsi $$ Ψ 50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both $$\varPsi $$ Ψ 50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink.

Abstract. The Moderate Resolution Imaging Spectroradiometer vegetation continuous fields (MODIS VCF) Earth observation product is widely used to estimate forest cover changes, parameterise vegetation and Earth System models, and as a reference for validation or calibration where field data is limited. However, although limited independent validations of MODIS VCF have shown that MODIS VCF's accuracy decreases when estimating tree cover in sparsely-vegetated areas, such as in tropical savannas, no study has yet assessed the impact this may have on the VCF based tree cover distributions used by many in their research. Using tropical forest and savanna inventory data collected by the TROpical Biomes In Transition (TROBIT) project, we produce a series of corrections that take into account (i) the spatial disparity between the in-situ plot size and the MODIS VCF pixel, and (ii) the trees' spatial distribution within in-situ plots. We then applied our corrections to areas identified as forest or savanna in the International Geosphere-Biosphere Programme (IGBP) land cover mapping product. All IGBP classes identified as savanna show substantial increases in cover after correction, indicating that the most recent version of MODIS VCF consistently underestimates woody cover in tropical savannas. We estimate that MODIS VCF could be underestimating tropical tree cover by between 9–15 %. Models that use VCF as their benchmark could be underestimating the carbon uptake in forest-savanna areas and misrepresenting forest-savanna dynamics. While more detailed in-situ field data is necessary to produce more accurate and reliable corrections, we recommend caution when using MODIS VCF in tropical savannas.