Regionalization of the site water balance in forests using fuzzy inference systems

Relief-dependent variations in micro-climatic parameters control evaporation and soil water conditions of forests. Therefore, mapping of soil water conditions in mountainous terrain requires that model computations have a high spatial resolution. Unfortunately, highly sophisticated, physically based modeling in combination with a large number of model runs leads to demanding computation costs. To overcome these shortcomings, a physically and physiologically based water balance model was combined with fuzzy inference systems. Grid-point-specific factors representing the systematic alteration of the station data due to the topography are the basis for the parameterization of the antecedent side of the fuzzy system. Model outputs of the water balance model BROOK 90 were used directly as parameters of the consequents of the fuzzy rules. Thus, the parameterization of the fuzzy inference system is model-based and objective, and parameter training is not required. The validation of the method shows only small differences between fuzzy system outputs and BROOK 90 results.Um bei der flächenhaften Modellierung des Wasserhaushaltes aus dem Relief resultierende Variabilitäten der meteorologischen Eingangsgrößen zu berücksichtigen, ist eine hohe räumliche Auflösung erforderlich. Das führt zu hohen Rechenzeiten. Die Kombination physikalisch und physiologisch begründeter Modellierung mit Fuzzy-Inference-Systemen (FIS) zeigt einen Weg aus diesem Dilemma. Rasterpunktspezifische Korrekturfaktoren widerspiegeln das Verhältnis zwischen den meteorologischen Bedingungen am Standort zu den Messwerten an der Klimastation. Diese Korrekturfaktoren werden direkt zur Parametrisierung der Bedingungen der Fuzzy-regeln verwendet. Als Parameter der Folgerung werden direkt Modellergebnisse des forsthydrologischen Modells BROOK 90 eingesetzt. Damit erfolgt eine objektive modellgestützte Parametrisierung des FIS. Ein Training wird nicht ausgeführt. Die Validierung der Methode zeigt nur geringe Abweichungen zwischen den Modellergebnissen und den FIS-Outputs

Impact of soil and stand properties on soil water conditions

As an objective water balance classification is lacking for forest sites, efforts were made to develop a model-based site classification system taking into account the effects of relief, soil and stand type on soil water conditions. As a first step, this paper displays the results of a BROOK 90 application evaluating the influence of these three factors on soil water balance with a strong emphasis on drought conditions. Model runs have been carried out for four different soil types, four stand types and a meteorological input covering the range of typical forest sites in the Tharandt Forest as a testing area. Concepts of drought stress quantification help to point out the effects of stress on the sites. In drought years, deciduous trees and soils with limited water retention properties show the effects of drought stress more strongly. The effects of both soil and stand properties were of the same magnitude as the influence of the conventionally considered relief-based meteorological variation at the site.Die forstliche Standortklassifikation ist bundesweit uneinheitlich und bezüglich der Bewertung des Gesamtwasserhaushalts meist subjektiv. Um eine Vereinheitlichung zu erreichen, wird eine modellbasierte, objektive Klassifikation angestrebt, die neben der reliefbasierten meteorologischen Variabilität auch Bodenform und Bestockung einbezieht. In diesem Artikel werden die Ergebnisse vergleichender BROOK 90-Simulationen, die den Effekt unterschiedlicher Böden, Baumarten und Ausrichtungen im Gelände untersuchen, dargestellt und diskutiert. Der Schwerpunkt liegt dabei auf der Betrachtung von Wasserverfügbarkeit. Es wurden Parametrisierungen für vier verschiedene Bodenformen mit den Bestockungen Buche, Eiche, Fichte und Kiefer verwendet. Die reliefbedingten meteorologischen Standortcharakteristiken richten sich nach den lokalen Gegebenheiten des Testgebiets Tharandter Wald. Für das Konzept der Darstellung von Unterschieden hinsichtlich des Standortswasserhaushaltes wurden hierfür im Modell implementierte Stressindikatoren verwendet. Es zeigt sich, daß in Trockenjahren die Laubbäume höhere Stressindikatoren erreichen. Gleichfalls treten bei Böden mit geringerer Wasserretention erwartungsgemäß mehr Stress-tage auf. Bestockung und Bodeneigenschaften haben einen Einfluß auf Wasserknappheit in der Größenordnung wie die zur forstlichen Standortklassifikation verwendeten morphologischen Geländeeigenschaften

Spatially differentiated modeling and evaluation of soil water conditions in forest sites of low mountain ranges

The forest hydrological model BROOK 90 was integrated into a GIS framework to calculate and evaluate soil water conditions in forest sites based on climate, topography, soil, and tree species. Model results are visualized in a novel forest site map using indicators for soil drought, soil water excess, and transpiration constraints. Based on knowledge of the number of days in which thresholds of these indicators were exceeded, an evaluation framework for soil water conditions was developed. The model was tested at the Tharandt Forest for an area with varying soil conditions and different tree species. Results can be used to derive and test new forest management strategies. For instance, recommendations for achieving optimum growth based on tree species or stand structure choices can be derived. Further research should focus on relating soil water indices with growth indices.Auf der Basis des forsthydrologischen Modells BROOK 90 wurde ein Modellsystem zur Berechnung und Beurteilung des Standortswasserhaushaltes in Abhängigkeit von Klima, Relief, Boden und Bestockung entwickelt. Implementierte Indikatoren zur Ausschöpfung des Bodenwasservorrates, der Einschränkung der Transpiration und des Auftretens von Staunässe erlauben eine Visualisierung der Modellergebnisse in Form neuartiger Standortskarten. Basierend auf der Kenntnis der Unterschreitungshäufigkeiten von Schwellenwerten dieser Indikatoren wurde ein fünfstufiger Bewertungsrahmen für den Wasserhaushalt aufgestellt. Das Modell wurde im Tharandter Wald für ein Gebiet mit variierenden Böden und unterschiedlicher Bestockung (Buche, Eiche, Fichte und Kiefer) getestet. Die Ergebnisse zeigen, dass diese Vorgehensweise eine differenzierte Informationsgrundlage für die forstliche Planung liefert. Beispielsweise können Entscheidungen zu Baumartenwahl und Bestandesstruktur abgeleitet werden. Forschungsbedarf besteht vor allem in der Verknüpfung der im Modell implementierten Indikatoren des Wasserhaushaltes mit Wachstumsparametern und physiologisch definierten Schwellenwerten

Klimatische Stabilität von Mittelgebirgsmooren

Inwieweit bisherige und prognostizierte Klimaänderungen Mittelgebirgsmoore beeinflussen, wurde am Beispiel der Mothhäuser Haide im Mittleren Erzgebirge untersucht. Mit den angewandten moorkundlichen Methoden und dem Vergleich von drei Landnutzungsszenarien (IST, pnV, Paläovegetation) mit drei Klimaszenarien (Messdaten 1981 - 2000, WEREX IV 2041-60, Paläoklima) lassen sich die Ökotopveränderungen der Moorfläche ableiten. Im Ergebnis wird ein Rückgang an nässeren Ökotopen prognostiziert, wobei der Charakter eines Moores aber erhalten bleibt. Anthropogene Einflüsse wie Straßenbau, Entwässerung und Torfabbau haben größere Veränderungen bewirkt als durch den Klimawandel zu erwarten sind. Die Wiederherstellung der hydrologischen Durchgängigkeit des Moores, d.h. die Beseitigung von Gräben und Barrieren, kann die negativen Folgen eines zukünftig wärmeren Klimas abpuffern. Hinweise des Herausgebers (Stand: 4. April 2011): Zu Seite 18, Abbildung 4: Die Temperaturreihe vom Hohenpeißenberg und die Temperaturrekonstruktionen nach Glaser (2001), welche diese Reihe mit berücksichtigt hat, weisen in der verwendeten Form Inhomogenitäten auf. Nach einer Homogenisierung durch den DWD wird deutlich, dass das mittlere Temperaturniveau um 1780 eher dem von 1970 entspricht. Die Folgejahre sind von einem Anstieg um ca. 1 °C gekennzeichnet (Glaser 2008). Zu Seite 20, Abschnitt 4.3.2: Die genannten Datenfehler wurden inzwischen behoben. Weil vergleichbare Unplausibilitäten nie ganz ausgeschlossen werden können, sind Qualitätsprüfungen von Beobachtungs- und Projektionsdaten vor jeder Datenanwendung durchzuführen. Zu Seite 20, Abschnitt 4.3.3: Das Regionalisierungsverfahren WEREX simuliert im Betrachtungszeitraum 10 Realisierungen. Statistische Kenngrößen sollten aus allen 10 Realisierungen für vorzugsweise 30-jährige Zeiträume abgeleitet werden. Abweichungen der statistischen Kenngrößen in Modelldaten von denen des beobachteten Datenkollektives sind modellimmanent und deshalb zu erwarten. Die dargestellten Ergebnisse ermöglichen keine abschließende Bewertung der statistischen Eigenschaften der Projektionsdaten. Klimaprojektionen liefern generell nur Annahmen einer möglichen Klimazukunft. Neben der Plausibilitätsprüfung sollte die Bewertung der Aussagen eines Modells möglichst immer in die Bandbreite der Ergebnisse vieler Modelle erfolgen

Genome-wide meta-analysis of phytosterols reveals five novel loci and a detrimental effect on coronary atherosclerosis

Correction: Volume13, Issue1 Article Number1122 DOI 10.1038/s41467-022-28863-y Published FEB 25 2022Phytosterol serum concentrations are under tight genetic control. The relationship between phytosterols and coronary artery disease (CAD) is controversially discussed. We perform a genome-wide meta-analysis of 32 phytosterol traits reflecting resorption, cholesterol synthesis and esterification in six studies with up to 9758 subjects and detect ten independent genomewide significant SNPs at seven genomic loci. We confirm previously established associations at ABCG5/8 and ABO and demonstrate an extended locus heterogeneity at ABCG5/8 with different functional mechanisms. New loci comprise HMGCR, NPC1L1, PNLIPRP2, SCARB1 and APOE. Based on these results, we perform Mendelian Randomization analyses (MR) revealing a risk-increasing causal relationship of sitosterol serum concentrations and CAD, which is partly mediated by cholesterol. Here we report that phytosterols are polygenic traits. MR add evidence of both, direct and indirect causal effects of sitosterol on CAD.Peer reviewe

The consolidated European synthesis of CO2emissions and removals for the European Union and United Kingdom : 1990-2018

Acknowledgements FAOSTAT statistics are produced and disseminated with the support of its member countries to the FAO regular budget. Philippe Ciais acknowledges the support of the European Research Council Synergy project SyG-2013-610028 IMBALANCE-P and from the ANR CLAND Convergence Institute. We acknowledge the work of the entire EDGAR group (Marilena Muntean, Diego Guizzardi, Edwin Schaaf and Jos Olivier). We acknowledge Stephen Sitch and the authors of the DGVMs TRENDY v7 ensemble models for providing us with the data. Financial support This research has been supported by the H2020 European Research Council (grant no. 776810).Peer reviewedPublisher PD

The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom : 1990-2017

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 C UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 TgCH(4) yr (-1) (EDGAR v5.0) and 19.0 TgCH(4) yr(-1) (GAINS), consistent with the NGHGI estimates of 18.9 +/- 1.7 TgCH(4) yr(-1). The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 TgCH(4) yr(-1). Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 TgCH(4) yr(-1)) and surface network (24.4 TgCH(4) yr (-1)). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 TgCH(4) yr(-1). For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 TgN(2)Oyr(-1), respectively, agreeing with the NGHGI data (0.9 0.6 TgN(2)Oyr(-1)). Over the same period, the average of the three total TD global and regional inversions was 1.3 +/- 0.4 and 1.3 +/- 0.1 TgN(2)Oyr(-1), respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU CUK scale and at the national scale.Peer reviewe

The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom:1990-2020

Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990-2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926g±g13gTggCgyr-1, while eight other BU sources report a mean value of 948 [937,961]gTggCgyr-1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875gTggC in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for -91g±g32gTggCgyr-1, while six other BU approaches reported a mean sink of -62 [-117,-49]gTggCgyr-1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5]gTggCgyr-1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73gTggCgyr-1 has a slightly smaller spread (0th-100th percentiles of [-135,+45]gTggCgyr-1), and it was calculated after removing net land-atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (-0.61)gTggCgyr-2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000gTggCgyr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at 10.5281/zenodo.8148461 (McGrath et al., 2023).</p