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Institute
Influence of Ozone and Drought on Tree Growth under Field Conditions in a 22 Year Time Series
(2022)
Studying the effect of surface ozone (O3) and water stress on tree growth is important for planning sustainable forest management and forest ecology. In the present study, a 22-year long time series (1998–2019) on basal area increment (BAI) and fructification severity of European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H.Karst.) at five forest sites in Western Germany (Rhineland Palatinate) was investigated to evaluate how it correlates with drought and stomatal O3 fluxes (PODY) with an hourly threshold of uptake (Y) to represent the detoxification capacity of trees (POD1, with Y = 1 nmol O3 m−2 s−1). Between 1998 and 2019, POD1 declined over time by on average 0.31 mmol m−2 year−1. The BAI showed no significant trend at all sites, except in Leisel where a slight decline was observed over time (−0.37 cm2 per year, p < 0.05). A random forest analysis showed that the soil water content and daytime O3 mean concentration were the best predictors of BAI at all sites. The highest mean score of fructification was observed during the dry years, while low level or no fructification was observed in most humid years. Combined effects of drought and O3 pollution mostly influence tree growth decline for European beech and Norway spruce.
Measurements of the atmospheric boundary layer (ABL) structure were performed for three years (October 2017–August 2020) at the Russian observatory “Ice Base Cape Baranova” (79.280° N, 101.620° E) using SODAR (Sound Detection And Ranging). These measurements were part of the YOPP (Year of Polar Prediction) project “Boundary layer measurements in the high Arctic” (CATS_BL) within the scope of a joint German–Russian project. In addition to SODAR-derived vertical profiles of wind speed and direction, a suite of complementary measurements at the observatory was available. ABL measurements were used for verification of the regional climate model COSMO-CLM (CCLM) with a 5 km resolution for 2017–2020. The CCLM was run with nesting in ERA5 data in a forecast mode for the measurement period. SODAR measurements were mostly limited to wind speeds <12 m/s since the signal was often lost for higher winds. The SODAR data showed a topographical channeling effect for the wind field in the lowest 100 m and some low-level jets (LLJs). The verification of the CCLM with near-surface data of the observatory showed good agreement for the wind and a negative bias for the 2 m temperature. The comparison with SODAR data showed a positive bias for the wind speed of about 1 m/s below 100 m, which increased to 1.5 m/s for higher levels. In contrast to the SODAR data, the CCLM data showed the frequent presence of LLJs associated with the topographic channeling in Shokalsky Strait. Although SODAR wind profiles are limited in range and have a lot of gaps, they represent a valuable data set for model verification. However, a full picture of the ABL structure and the climatology of channeling events could be obtained only with the model data. The climatological evaluation showed that the wind field at Cape Baranova was not only influenced by direct topographic channeling under conditions of southerly winds through the Shokalsky Strait but also by channeling through a mountain gap for westerly winds. LLJs were detected in 37% of all profiles and most LLJs were associated with channeling, particularly LLJs with a jet speed ≥ 15 m/s (which were 29% of all LLJs). The analysis of the simulated 10 m wind field showed that the 99%-tile of the wind speed reached 18 m/s and clearly showed a dipole structure of channeled wind at both exits of Shokalsky Strait. The climatology of channeling events showed that this dipole structure was caused by the frequent occurrence of channeling at both exits. Channeling events lasting at least 12 h occurred on about 62 days per year at both exits of Shokalsky Strait.
Anpassung an den Klimawandel stellt eine komplexe gesellschaftliche Herausforderung dar und hat Bezug zu steuerungstheoretischen Fragen um Governance. Klimaanpassung zeichnet sich aus durch die Zusammenarbeit staatlicher und nicht-staatlicher Akteure, netzwerkartige Strukturen, flexible Steuerungsmechanismen sowie formelle und informelle Koordinationsstrukturen. Für die erfolgreiche Gestaltung von Klimaanpassungspolitik müssen vielfältige Akteurs- und Interessenskonstellationen berücksichtigt werden.
Ziel der vorliegenden Studie ist es, das Traben-Trarbacher Akteurs- und Stakeholdernetzwerk aus Perspektive der Klimaanpassung zu analysieren. Ein besonderer Fokus liegt hierbei auf den regionalwirtschaftlich bedeutenden Sektoren Weinbau und Tourismus, die integriert und im Kontext von kommunalen, regionalen und überregionalen Strukturen betrachtet werden. Im Rahmen der Analyse wurden das Beziehungsgeflecht, die Reichweite und Diversität des Netzwerks sowie die Zusammensetzung der Akteurslandschaft dargestellt. Darüber hinaus konnten wichtige Schlüsselakteure, potenzielle Multiplikatoren, Interdependenzen zwischen Weinbau und Tourismus sowie Informations- und Wissensquellen identifiziert werden.
Die Ergebnisse der Stakeholderanalyse geben wichtige Hinweise darauf, welche Akteure in Steuerungsprozesse von Klimaanpassung einbezogen und welche lokalen Gegebenheiten und Beziehungen hierbei berücksichtig werden müssen. Besonders die Zusammensetzung der Akteure hat entscheidenden Einfluss auf den Verlauf und Erfolg der Steuerung von Klimaanpassung. Die vorliegende Stakeholderanalyse schafft also eine wichtige Grundlage zur Etablierung eines Governance-Netzwerks für die Erarbeitung und Erprobung von Klimawandelanpassungsmaßnahmen in Traben-Trarbach und der Moselregion. Damit dient die Analyse der langfristigen Verankerung von Klimaanpassung in der Region und kann auch als Anregung für weitere Kommunen genutzt werden, die vor ähnlichen Herausforderungen stehen wie Traben-Trarbach.
Dieser Maßnahmenkatalog stellt Anpassungsoptionen für den Weinbau an der Mittelmosel vor. Die gemeinsam mit lokalen Akteur*innen erarbeiteten Maßnahmen zielen erstens darauf ab, konkrete Handlungsoptionen zur Anpassung des Weinbaus an den Klimawandel aufzuzeigen. Zweitens sollen durch strukturelle Maßnahmen bestehende regionalspezifische Herausforderungen adressiert und die generellen Anpassungskapazitäten der Akteur*innen an der Mittelmosel gestärkt werden.
Anpassung an den Klimawandel ist eine Zukunftsaufgabe. Auch für den Tourismussektor in der Moselregion.
Der vorliegende Bericht gibt einen Überblick zu den Chancen und Risiken, die im Rahmen des Klimawandels für den Weintourismus an der Mittelmosel entstehen. Mit Hilfe einer SWOT-Analyse wurden am Beispiel der im Projekt Mosel-AdapTiV kooperierenden Kommune Tra-ben-Trarbach exemplarisch die Auswirkungen für eine Vielzahl traditioneller Weinbauorte an der Mittelmosel untersucht.
Als touristische Destination ist die Region Mittelmosel von vielfältigen Auswirkungen des Klimawandels betroffen. Eine Verschiebung der Vegetationsperioden, Extremereignisse wie Starkregen oder Hitzeperioden werden das Leben und Wirtschaften in der Region grundlegend verändern. Diese Klimawirkfolgen treffen mit weiteren regionalökonomischen, soziokulturellen und umweltbezogenen Veränderungen zusammen. Daraus gehen Risiken und zum Teil auch Chancen für den Weintourismus und dessen Vermarktung einher. Wie wir in der Studie zeigen, sind Chancen (beispielsweise durch die Verlängerung der Sommersaison durch veränderte Mitteltemperaturen) aber häufig mit Risiken verbunden (beispielsweise für die identitätsstiftende Weinkulturlandschaft und den beliebten charakteristischen Riesling). Beide Aspekte, die Chancen sowie die Risiken zu untersuchen, ist Gegenstand der SWOT Analyse. Sie hat das Ziel, lokale und regionale Akteure des Tourismus sowie der Stadt- und Regio-nalentwicklung zu sensibilisieren und zu informieren und dazu anzuregen, geeignete Anpas-sungsstrategien zu entwickeln.
Anpassung an die Auswirkungen des Klimawandels bedeutet, sich mit den Folgen zu befassen, Risiken in verschiedenen Sektoren und Handlungsfeldern zu minimieren und sich auf veränderte klimatische Bedingungen in der Zukunft einzustellen. Im Rahmen dessen sollten kon-krete Anpassungsmaßnahmen entwickelt und implementiert werden. Dieser Bericht enthält erste Handlungsempfehlungen. Sie setzen bei der touristischen Vermarktung an, um Chancen wie verlängerte Wärmeperioden oder ein erweitertes Angebotsportfolio nutzen zu können. Zum Minimieren von Risiken empfehlen sich Ansätze wie die Sensibilisierung und Information der Akteur*innen, sowie konkrete Maßnahmen, bspw. zur Reduktion von Hitzestress. Diese Handlungsempfehlungen sollen nicht zuletzt den Akteur*innen vor Ort als Leitfaden zur Kli-mawandelanpassung im Traben-Trarbacher (Wein-)Tourismus dienen. Die Erkenntnisse dieses Berichts dienen als entsprechende Grundlage.
Dieser Bericht basiert auf einer Auswertung relevanter Literatur, der Analyse örtlicher und überregionaler Tourismuskonzepte sowie mehreren qualitativen Interviews mit Akteur*innen vor Ort. Er bildet eine Basis für die weitere Projektarbeit und soll dabei helfen, sektorenübergreifende, langfristige und ganzheitliche Anpassungsstrategien zu entwickeln.
A model-based temperature adjustment scheme for wintertime sea-ice production retrievals from MODIS
(2022)
Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020.
Extension of an Open GEOBIA Framework for Spatially Explicit Forest Stratification with Sentinel-2
(2022)
Spatially explicit information about forest cover is fundamental for operational forest management and forest monitoring. Although open-satellite-based earth observation data in a spatially high resolution (i.e., Sentinel-2, ≤10 m) can cover some information needs, spatially very high-resolution imagery (i.e., aerial imagery, ≤2 m) is needed to generate maps at a scale suitable for regional and local applications. In this study, we present the development, implementation, and evaluation of a Geographic Object-Based Image Analysis (GEOBIA) framework to stratify forests (needleleaved, broadleaved, non-forest) in Luxembourg. The framework is exclusively based on open data and free and open-source geospatial software. Although aerial imagery is used to derive image objects with a 0.05 ha minimum size, Sentinel-2 scenes of 2020 are the basis for random forest classifications in different single-date and multi-temporal feature setups. These setups are compared with each other and used to evaluate the framework against classifications based on features derived from aerial imagery. The highest overall accuracies (89.3%) have been achieved with classification on a Sentinel-2-based vegetation index time series (n = 8). Similar accuracies have been achieved with classification based on two (88.9%) or three (89.1%) Sentinel-2 scenes in the greening phase of broadleaved forests. A classification based on color infrared aerial imagery and derived texture measures only achieved an accuracy of 74.5%. The integration of the texture measures into the Sentinel-2-based classification did not improve its accuracy. Our results indicate that high resolution image objects can successfully be stratified based on lower spatial resolution Sentinel-2 single-date and multi-temporal features, and that those setups outperform classifications based on aerial imagery only. The conceptual framework of spatially high-resolution image objects enriched with features from lower resolution imagery facilitates the delivery of frequent and reliable updates due to higher spectral and temporal resolution. The framework additionally holds the potential to derive additional information layers (i.e., forest disturbance) as derivatives of the features attached to the image objects, thus providing up-to-date information on the state of observed forests.
Soil organic matter (SOM) is an indispensable component of terrestrial ecosystems. Soil organic carbon (SOC) dynamics are influenced by a number of well-known abiotic factors such as clay content, soil pH, or pedogenic oxides. These parameters interact with each other and vary in their influence on SOC depending on local conditions. To investigate the latter, the dependence of SOC accumulation on parameters and parameter combinations was statistically assessed that vary on a local scale depending on parent material, soil texture class, and land use. To this end, topsoils were sampled from arable and grassland sites in south-western Germany in four regions with different soil parent material. Principal component analysis (PCA) revealed a distinct clustering of data according to parent material and soil texture that varied largely between the local sampling regions, while land use explained PCA results only to a small extent. The PCA clusters were differentiated into total clusters that contain the entire dataset or major proportions of it and local clusters representing only a smaller part of the dataset. All clusters were analysed for the relationships between SOC concentrations (SOC %) and mineral-phase parameters in order to assess specific parameter combinations explaining SOC and its labile fractions hot water-extractable C (HWEC) and microbial biomass C (MBC). Analyses were focused on soil parameters that are known as possible predictors for the occurrence and stabilization of SOC (e.g. fine silt plus clay and pedogenic oxides). Regarding the total clusters, we found significant relationships, by bivariate models, between SOC, its labile fractions HWEC and MBC, and the applied predictors. However, partly low explained variances indicated the limited suitability of bivariate models. Hence, mixed-effect models were used to identify specific parameter combinations that significantly explain SOC and its labile fractions of the different clusters. Comparing measured and mixed-effect-model-predicted SOC values revealed acceptable to very good regression coefficients (R2=0.41–0.91) and low to acceptable root mean square error (RMSE = 0.20 %–0.42 %). Thereby, the predictors and predictor combinations clearly differed between models obtained for the whole dataset and the different cluster groups. At a local scale, site-specific combinations of parameters explained the variability of organic carbon notably better, while the application of total models to local clusters resulted in less explained variance and a higher RMSE. Independently of that, the explained variance by marginal fixed effects decreased in the order SOC > HWEC > MBC, showing that labile fractions depend less on soil properties but presumably more on processes such as organic carbon input and turnover in soil.
The process of land degradation needs to be understood at various spatial and temporal scales in order to protect ecosystem services and communities directly dependent on it. This is especially true for regions in sub-Saharan Africa, where socio economic and political factors exacerbate ecological degradation. This study identifies spatially explicit land change dynamics in the Copperbelt province of Zambia in a local context using satellite vegetation index time series derived from the MODIS sensor. Three sets of parameters, namely, monthly series, annual peaking magnitude, and annual mean growing season were developed for the period 2000 to 2019. Trend was estimated by applying harmonic regression on monthly series and linear least square regression on annually aggregated series. Estimated spatial trends were further used as a basis to map endemic land change processes. Our observations were as follows: (a) 15% of the study area dominant in the east showed positive trends, (b) 3% of the study area dominant in the west showed negative trends, (c) natural regeneration in mosaic landscapes (post shifting cultivation) and land management in forest reserves were chiefly responsible for positive trends, and (d) degradation over intact miombo woodland and cultivation areas contributed to negative trends. Additionally, lower productivity over areas with semi-permanent agriculture and shift of new encroachment into woodlands from east to west of Copperbelt was observed. Pivot agriculture was not a main driver in land change. Although overall greening trends prevailed across the study site, the risk of intact woodlands being exposed to various disturbances remains high. The outcome of this study can provide insights about natural and assisted landscape restoration specifically addressing the miombo ecoregion.
Measurements of dust emissions and the modeling of dissipation dynamics and total values are related to great uncertainties. Agricultural activity, especially soil cultivation, may be an essential component to calculate and model local and regional dust dynamics and even connect to the global dust cycle. To budget total dust and to assess the impact of tillage, measurement of mobilized and transported dust is an essential but rare basis. In this study, a simple measurement concept with Modified Wilson and Cook samplers was applied for dust measurements on a small temporal and spatial scale on steep-slope vineyards in the Moselle area. Without mechanical impact, a mean horizontal flux of 0.01 g m2 min−1 was measured, while row tillage produced a mean horizontal flux of 5.92 g m2 min−1 of mobilized material and 4.18 g m2 min−1 emitted dust from site (=soil loss). Compared on this singular-event basis, emissions during tillage operations generated 99.89% of total emitted dust from the site under low mean wind velocities. The results also indicate a differing impact of specific cultivation operations, mulching, and tillage tools as well as the additional influence of environmental conditions, with highest emissions on dry soil and with additional wind impact. The dust source function is strongly associated with cultivation operations, implying highly dynamic but also regular and thus predictable and projectable emission peaks of total suspended particles. Detailed knowledge of the effects of mechanical impulses and reliable quantification of the local dust emission inventory are a basis for analysis of risk potential and choice of adequate management options.