• Energy Research
• 2016-2025close

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.

AbstractA generic regression model for above-ground biomass of forest stands was constructed based on published data (R2= 0.88,RSE= 32.8 t/ha). The model was used 1) to verify two allometric regression models of trees from Scandinavia applied to repeated measurements of 275 sample plots from database of Estonian Network of Forest Research (FGN) in Estonia, 2) to analyse impact of between-tree competition on biomass, and 3) compare biomass estimates made with different European biomass models applied on standardized forest structures. The model was verified with biomass measurements from hemiboreal and tropical forests. The analysis of two Scandinavian models showed that older allometric regression models may give biased estimates due to changed growth conditions. More biomass can be stored in forest stands where competition between trees is stronger. The tree biomass calculation methods used in different countries have also substantial influence on the estimates at stand-level. A common database of forest biomass measurements from Europe in similar to pan-tropical tree measurement data may be helpful to harmonise carbon accounting methods.

L'une des questions les plus fondamentales en écologie est de savoir combien d'espèces habitent la Terre. Cependant, en raison des défis logistiques et financiers massifs et des difficultés taxonomiques liées à la définition du concept d'espèce, le nombre global d'espèces, y compris celles des formes de vie importantes et bien étudiées telles que les arbres, reste encore largement inconnu. Ici, sur la base de données mondiales provenant de sources terrestres, nous estimons la richesse totale des espèces d'arbres aux niveaux mondial, continental et du biome. Nos résultats indiquent qu'il y a environ73 000 espèces d'arbres dans le monde, parmi lesquelles environ9 000 espèces d'arbres n'ont pas encore été découvertes. Environ 40 % des espèces d'arbres non découvertes se trouvent en Amérique du Sud. En outre, près d'un tiers de toutes les espèces d'arbres à découvrir peuvent être rares, avec des populations très faibles et une répartition spatiale limitée (probablement dans les basses terres tropicales et les montagnes éloignées). Ces résultats mettent en évidence la vulnérabilité de la biodiversité forestière mondiale aux changements anthropiques dans l'utilisation des terres et le climat, qui menacent de manière disproportionnée les espèces rares et donc la richesse mondiale en arbres. Una de las preguntas más fundamentales en ecología es cuántas especies habitan la Tierra. Sin embargo, debido a los enormes desafíos logísticos y financieros y a las dificultades taxonómicas relacionadas con la definición del concepto de especie, el número global de especies, incluidas las de formas de vida importantes y bien estudiadas, como los árboles, sigue siendo en gran medida desconocido. Aquí, con base en datos globales de fuentes terrestres, estimamos la riqueza total de especies de árboles a nivel global, continental y de biomas. Nuestros resultados indican que hay ~73,000 especies de árboles a nivel mundial, entre las cuales ~9,000 especies de árboles aún no se han descubierto. Aproximadamente el 40% de las especies de árboles no descubiertas se encuentran en América del Sur. Además, casi un tercio de todas las especies de árboles por descubrir pueden ser raras, con poblaciones muy bajas y una distribución espacial limitada (probablemente en tierras bajas y montañas tropicales remotas). Estos hallazgos ponen de relieve la vulnerabilidad de la biodiversidad forestal mundial a los cambios antropogénicos en el uso de la tierra y el clima, que amenazan desproporcionadamente a las especies raras y, por lo tanto, a la riqueza arbórea mundial. 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. أحد أهم الأسئلة الأساسية في علم البيئة هو عدد الأنواع التي تعيش على الأرض. ومع ذلك، نظرًا للتحديات اللوجستية والمالية الهائلة والصعوبات التصنيفية المرتبطة بتعريف مفهوم الأنواع، لا تزال الأعداد العالمية للأنواع، بما في ذلك أشكال الحياة المهمة والمدروسة جيدًا مثل الأشجار، غير معروفة إلى حد كبير. هنا، استنادًا إلى البيانات العالمية من مصادر أرضية، نقدر إجمالي ثراء أنواع الأشجار على المستويات العالمية والقارية والبيولوجية. تشير نتائجنا إلى أن هناك 73000 نوع من الأشجار على مستوى العالم، من بينها 9000 نوع من الأشجار لم يتم اكتشافها بعد. يوجد ما يقرب من 40 ٪ من أنواع الأشجار غير المكتشفة في أمريكا الجنوبية. علاوة على ذلك، قد يكون ما يقرب من ثلث جميع أنواع الأشجار التي سيتم اكتشافها نادرًا، مع أعداد قليلة جدًا وتوزيع مكاني محدود (على الأرجح في الأراضي المنخفضة والجبال الاستوائية النائية). تسلط هذه النتائج الضوء على ضعف التنوع البيولوجي العالمي للغابات أمام التغيرات البشرية المنشأ في استخدام الأراضي والمناخ، والتي تهدد بشكل غير متناسب الأنواع النادرة وبالتالي ثراء الأشجار العالمي.

National and international carbon reporting systems require information on carbon stocks of forests. For this purpose, terrestrial assessment systems such as forest inventory data in combination with carbon estimation methods are often used. In this study we analyze and compare terrestrial carbon estimation methods from 12 European countries. The country-specific methods are applied to five European tree species (Fagus sylvatica L., Quercus robur L., Betula pendula Roth, Picea abies (L.) Karst. and Pinus sylvestris L.), using a standardized theoretically-generated tree dataset. We avoid any bias due to data collection and/or sample design by using this approach. We are then able to demonstrate the conceptual differences in the resulting carbon estimates with regard to the applied country-specific method. In our study we analyze (i) allometric biomass functions, (ii) biomass expansion factors in combination with volume functions and (iii) a combination of both. The results of the analysis show discrepancies in the resulting estimates for total tree carbon and for single tree compartments across the countries analyzed of up to 140 t carbon/ha. After grouping the country-specific approaches by European Forest regions, the deviation within the results in each region is smaller but still remains. This indicates that part of the observed differences can be attributed to varying growing conditions and tree properties throughout Europe. However, the large remaining error is caused by differences in the conceptual approach, different tree allometry, the sample material used for developing the biomass estimation models and the definition of the tree compartments. These issues are currently not addressed and require consideration for reliable and consistent carbon estimates throughout Europe.