Genetic evidence of human mediated, historical seed transfer from the Tyrolean Alps to the Romanian Carpathians in Larix decidua (Mill.) forests

International audienceKey messageHistoric transfer of larch from Alpine sources to Southern and Eastern Carpathians has been verified by means of nuclear genetic markers. Tyrolean populations can be differentiated into a north-western and south-eastern group, while Romanian populations are separated according to the Southern and Eastern Carpathians. Low-level introgression from Alpine sources is found in autochthonous Carpathian populations.ContextLarge scale human mediated transfer of forest reproductive material may have strongly modified the gene pool of European forests. Particularly in European larch, large quantities of seeds from Central Europe were used for plantations in Southern and Eastern Europe starting in the mid nineteenth century.AimsOur main objective was to provide DNA marker based evidence for the anthropogenic transfer of Alpine larch reproductive material to native Carpathian populations.MethodsWe studied and compared 12 populations (N = 771) of Larix decidua in the Alps (Austria, Italy) and in the Southern and Eastern Carpathians (Romania) using 13 microsatellites.ResultsHigh genetic diversity (He = 0.752; RS = 9.4) and a moderate genetic differentiation (FST = 0.13; G′ST = 0.28) among populations were found; Alpine and Carpathian populations were clearly separated by clustering methods. A Tyrolean origin of plant material was evident for one out of four adult Romanian populations. In the transferred population, a genetic influence from Carpathian sources was found neither in adults nor in juveniles, while the natural regeneration of two Romanian populations was genetically affected by Alpine sources to a minor degree (2.2 and 2.9% allochthonous individuals according to GeneClass and Structure, respectively). ConclusionTracing back of plant transfer by means of genetic tools is straightforward, and we propose further studies to investigate gene flow between natural and transferred populations

Conservation priorities for Prunus africana defined with the aid of spatial analysis of genetic data and climatic variables

Conservation priorities for Prunus africana, a tree species found across Afromontane regions, which is of great commercial interest internationally and of local value for rural communities, were defined with the aid of spatial analyses applied to a set of georeferenced molecular marker data (chloroplast and nuclear microsatellites) from 32 populations in 9 African countries. Two approaches for the selection of priority populations for conservation were used differing in the way they optimize representation of intra-specific diversity of P. africana across a minimum number of populations. The first method (Si) was aimed at maximizing genetic diversity of the conservation units and their distinctiveness with regard to climatic conditions, the second method (S2) at optimizing representativeness of the genetic diversity found throughout the species' range. Populations in East African countries (especially Kenya and Tanzania) were found to be of great conservation value, as suggested by previous findings. These populations are complemented by those in Madagascar and Cameroon. The combination of the two methods for prioritization led to the identification of a set of 6 priority populations. The potential distribution of P. africana was then modeled based on a dataset of 1,500 georeferenced observations. This enabled an assessment of whether the priority populations identified are exposed to threats from agricultural expansion and climate change, and whether they are located within the boundaries of protected areas. The range of the species has been affected by past climate change and the modeled distribution of P. africana indicates that the species is likely to be negatively affected in future, with an expected decrease in distribution by 2050. Based on these insights, further research at the regional and national scale is recommended, in order to strengthen P. africana conservation efforts

Relevance of dietary protein concentration and quality as risk factors for the formation of calcium oxalate stones in cats

The role of dietary protein for the development of feline calcium oxalate (CaOx) uroliths has not been conclusively clarified. The present study evaluated the effects of a varying dietary protein concentration and quality on critical indices for the formation of CaOx uroliths. Three diets with a high protein quality (10–11 % greaves meal/diet) and a varying crude protein (CP) concentration (35, 44 and 57 % in DM) were compared. Additionally, the 57 % CP diet was compared with a fourth diet that had a similar CP concentration (55 % in DM), but a lower protein quality (34 % greaves meal/diet). The Ca and oxalate (Ox) concentrations were similar in all diets. A group of eight cats received the same diet at the same time. Each feeding period was divided into a 21 d adaptation period and a 7 d sampling period to collect urine. There were increases in urinary volume, urinary Ca concentrations, renal Ca and Ox excretion and urinary relative supersaturation (RSS) with CaOx with increasing dietary protein concentrations. Urinary pH ranged between 6·34 and 6·66 among all groups, with no unidirectional effect of dietary protein. Lower renal Ca excretion was observed when feeding the diet with the lower protein quality, however, the underlying mechanism needs further evaluation. In conclusion, although the observed higher urinary volume is beneficial, the increase in urinary Ca concentrations, renal Ca and Ox excretion and urinary RSS CaOx associated with a high-protein diet may be critical for the development of CaOx uroliths in cats

Height Change Feature Based Free Space Detection

In the context of autonomous forklifts, ensuring non-collision during travel, pick, and place operations is crucial. To accomplish this, the forklift must be able to detect and locate areas of free space and potential obstacles in its environment. However, this is particularly challenging in highly dynamic environments, such as factory sites and production halls, due to numerous industrial trucks and workers moving throughout the area. In this paper, we present a novel method for free space detection, which consists of the following steps. We introduce a novel technique for surface normal estimation relying on spherical projected LiDAR data. Subsequently, we employ the estimated surface normals to detect free space. The presented method is a heuristic approach that does not require labeling and can ensure real-time application due to high processing speed. The effectiveness of the proposed method is demonstrated through its application to a real-world dataset obtained on a factory site both indoors and outdoors, and its evaluation on the Semantic KITTI dataset [2]. We achieved a mean Intersection over Union (mIoU) score of 50.90 % on the benchmark dataset, with a processing speed of 105 Hz. In addition, we evaluated our approach on our factory site dataset. Our method achieved a mIoU score of 63.30 % at 54 H

Poster: How to Raise a Robot - Beyond Access Control Constraints in Assistive Humanoid Robots

Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore incorporating privacy and security constraints (Activity-Centric Access Control and Deep Learning Based Access Control) with robot task planning approaches (classical symbolic planning and end-to-end learning-based planning). We report preliminary results on their respective trade-offs and conclude that a hybrid approach will most likely be the method of choice

How to Raise a Robot - A Case for Neuro-Symbolic AI in Constrained Task Planning for Humanoid Assistive Robots

Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore the novel field of incorporating privacy, security, and access control constraints with robot task planning approaches. We report preliminary results on the classical symbolic approach, deep-learned neural networks, and modern ideas using large language models as knowledge base. From analyzing their trade-offs, we conclude that a hybrid approach is necessary, and thereby present a new use case for the emerging field of neuro-symbolic artificial intelligence

Developing Effective Measures for Reduction of the Urban Heat Island based on Urban Climate Model Simulations and Stakeholder Cooperation

The climate change projections for the Austrian cities indicate that the observed warming trend, including frequent occurrences of extreme heat events, is expected to continue in the coming decades. Due to the Urban Heat Island (UHI) effect, caused by modification of energy balance in the built-up environment, the cities are warmer than their rural surroundings and therefore more exposed to negative impacts of climate change. During prolonged heat wave events, the excess in heat combined with reduced night-time cooling, decreased ventilation and possible air pollution can cause severe health impacts on the urban population. Developing measures for reduction of the UHI effect is important in the context of sustainable urban development and climate sensitive urban planning. Number of counteracting measures such as increase in vegetation, green open spaces, green roofs, unsealing of paved surfaces, decreasing absorption of solar radiation by increasing the reflectiveness of buildings and paved surfaces, are considered in the scope of climate change adaptation strategies. Nevertheless, the effectiveness of these measures, as well as their applicability in the existing urban structure, especially in the densely-built environments is not well known. Moreover, the expected cooling effects need to be quantified and the possible application should be communicated and appropriately planned with the relevant stakeholders in order to anticipate a large-scale implementation. This study investigates the effective methods for application of climate adaptation measures to reduce the UHI effect in a densely built-up environment on an example of the residential and business district of Jakomini in the city of Graz/Styria. The current local climate conditions are simulated with the urban climate model MUKLIMO_3 of the German Weather Service (DWD) using meteorological, geomorphological and land use data from the city of Graz. The simulations with altered land use characteristics corresponding to application of different UHI counteracting measures are calculated and compared to the reference simulation. The gradual increase in green areas, existing potential for green roofs implementation, modification in reflectivity of roofs and façades as well as unsealing of paved surfaces is considered. The resulting difference in heat load is evaluated as the potential cooling effect for the area of the Jakomini district and its surroundings. Based on the model results, a set of measures with optimal climatic impact is identified in close cooperation with the city’s planning department and in accordance with already existing concepts, plans and projects. This information is communicated with the relevant stakeholder groups both from private and public sectors to get their commitment to definitely undertake measures in the test-district. Considering the respective interests and role of action of different stakeholder groups a set of target measures is selected for further technical, financial and administrative planning of implementation. The study is supported by the Austrian Research Promotion Agency (FFG) and the Climate and Energy Fund (KLIEN) within the Smart Cities project “JACKY_cool_check” (Project Nr. 855554)

Joint inversion estimate of regional glacial isostatic adjustment in Antarctica considering a lateral varying Earth structure (ESA STSE Project REGINA)

A major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry, and to a lesser extent satellite altimetry, is the poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA). Although much progress has been made in consistently modelling the ice-sheet evolution throughout the last glacial cycle, as well as the induced bedrock deformation caused by these load changes, forward models of GIA remain ambiguous due to the lack of observational constraints on the ice sheet's past extent and thickness and mantle rheology beneath the continent. As an alternative to forward modelling GIA, we estimate GIA from multiple space-geodetic observations: GRACE, Envisat/ICESat and GPS. Making use of the different sensitivities of the respective satellite observations to current and past surface mass (ice mass) change and solid Earth processes, we estimate GIA based on viscoelastic response functions to disc load forcing. We calculate and distribute the viscoelastic response functions according to estimates of the variability of lithosphere thickness and mantle viscosity in Antarctica. We compare our GIA estimate with published GIA corrections and evaluate its impact in determining the ice mass balance in Antarctica from GRACE and satellite altimetry. Particular focus is applied to the Amundsen Sea Sector in West Antarctica, where uplift rates of several cm/yr have been measured by GPS. We show that most of this uplift is caused by the rapid viscoelastic response to recent ice-load changes, enabled by the presence of a low-viscosity upper mantle in West Antarctica. This paper presents the second and final contribution summarizing the work carried out within a European Space Agency funded study, REGINA, (www.regina-science.eu)

Acceleration of dynamic ice loss in Antarctica from satellite gravimetry

The dynamic stability of the Antarctic Ice Sheet is one of the largest uncertainties in projections of future global sea-level rise. Essential for improving projections of the ice sheet evolution is the understanding of the ongoing trends and accelerations of mass loss in the context of ice dynamics. Here, we examine accelerations of mass change of the Antarctic Ice Sheet from 2002 to 2020 using data from the GRACE (Gravity Recovery and Climate Experiment; 2002–2017) and its follow-on GRACE-FO (2018-present) satellite missions. By subtracting estimates of net snow accumulation provided by re-analysis data and regional climate models from GRACE/GRACE-FO mass changes, we isolate variations in ice-dynamic discharge and compare them to direct measurements based on the remote sensing of the surface-ice velocity (2002–2017). We show that variations in the GRACE/GRACE-FO time series are modulated by variations in regional snow accumulation caused by large-scale atmospheric circulation. We show for the first time that, after removal of these surface effects, accelerations of ice-dynamic discharge from GRACE/GRACE-FO agree well with those independently derived from surface-ice velocities. For 2002–2020, we recover a discharge acceleration of -5.3 ± 2.2 Gt yr−2 for the entire ice sheet; these increasing losses originate mainly in the Amundsen and Bellingshausen Sea Embayment regions (68%), with additional significant contributions from Dronning Maud Land (18%) and the Filchner-Ronne Ice Shelf region (13%). Under the assumption that the recovered rates and accelerations of mass loss persisted independent of any external forcing, Antarctica would contribute 7.6 ± 2.9 cm to global mean sea-level rise by the year 2100, more than two times the amount of 2.9 ± 0.6 cm obtained by linear extrapolation of current GRACE/GRACE-FO mass loss trends

Quantifying the Potential of Photonic Cooling to Improve Urban Microclimate

The observed warming trend in regional climate is expected to continue in the future, aggravating urban heat load as extreme temperatures are amplified in cities due to the urban heat island (UHI) effect. Beside causing negative health effects and reducing human comfort, this development results in an increase in urban air conditioning (AC) usage, again negatively influencing the outdoor urban microclimate due to AC waste heat emission. As cities are continiously growing (the population of e.g. Vienna increased more than 10% over the past 10 years), more and more people are affected by this additional anthropogenic heating of the urban canyon. The Viennese trend away from individual motorized traffic such as cars and towards the use of public transport, walking and cycling further leaves increased numbers of inhabitants directly exposed to excessive heat loads, highlighting the need for innovative solutions to counteract this problem. The exploratory project ‘Photonic Cooling’, funded by the Austrian Research Promotion Agency through the ‘City of the Future’ program, aims at evaluating the potential of practical and cost-effective photonic cooling techniques for the cooling of buildings. The use of the photonic cooling technology instead of conventional AC systems minimizes anthropogenic heat emissions resulting from building cooling, hence minimizing the UHI development due to AC heat release and improving the quality of life of the urban population as a result. This paper focusses on the quantification of the potential of photonic cooling to improve the urban microclimate using Vienna as a case study. To estimate the future development of the UHI, the resulting changes in cooling demand and its effect on urban temperatures, a modelling approach is used. Simulations with the MUKLIMO_3 urban climate model are performed for the city of Vienna to determine changes in urban temperature for the 2021-2050 period relative to the 1971-2000 period. These results are then used as input for an empirical model to determine future cooling demand in terms of AC electricity use in buildings. Based on existing studies for other cities a relation between AC heat release and city temperature increase is established. Combining this with the modelled future cooling demand quantifies the influence from conventional AC systems on the urban microclimate, illustrating the benefit of using passive photonic cooling techniques to cover cooling demands instead