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Low-level jets (LLJs) are climatological features in polar regions. It is well known that katabatic winds over the slopes of the Antarctic ice sheet are associated with strong LLJs. Barrier winds occurring, e.g., along the Antarctic Peninsula may also show LLJ structures. A few observational studies show that LLJs occur over sea ice regions. We present a model-based climatology of the wind field, of low-level inversions and of LLJs in the Weddell Sea region of the Antarctic for the period 2002–2016. The sensitivity of the LLJ detection on the selection of the wind speed maximum is investigated. The common criterion of an anomaly of at least 2 m/s is extended to a relative criterion of wind speed decrease above and below the LLJ. The frequencies of LLJs are sensitive to the choice of the relative criterion, i.e., if the value for the relative decrease exceeds 15%. The LLJs are evaluated with respect to the frequency distributions of height, speed, directional shear and stability for different regions. LLJs are most frequent in the katabatic wind regime over the ice sheet and in barrier wind regions. During winter, katabatic LLJs occur with frequencies of more than 70% in many areas. Katabatic LLJs show a narrow range of heights (mostly below 200 m) and speeds (typically 10–20 m/s), while LLJs over the sea ice cover a broad range of speeds and heights. LLJs are associated with surface inversions or low-level lifted inversions. LLJs in the katabatic wind and barrier wind regions can last several days during winter. The duration of LLJs is sensitive to the LLJ definition criteria. We propose to use only the absolute criterion for model studies.
Digital technologies have become central to social interaction and accessing goods and services. Development strategies and approaches to governance have increasingly deployed self-labelled ‘smart’ technologies and systems at various spatial scales, often promoted as rectifying social and geographic inequalities and increasing economic and environmental efficiencies. These have also been accompanied with similarly digitalized commercial and non-profit offers, particularly within the sharing economy. Concern has grown, however, over possible inequalities linked to their introduction. In this paper we critically analyse the role of sharing economies’ contribution to more inclusive, socially equitable
and spatially just transitions. Conceptually, this paper brings together literature on sharing economies, smart urbanism
and just transitions. Drawing on an explorative database of sharing initiatives within the cross-border region of Luxembourg and Germany, we discuss aspects of sustainability as they relate to distributive justice through spatial accessibility, intended benefits, and their operationalization. The regional analysis shows the diversity of sharing models, how they are appropriated in different ways and how intent and operationalization matter in terms of potential benefits.
Results emphasize the need for more fine-grained, qualitative research revealing who is, and is not, participating and
benefitting from sharing economies.
Amphibian diversity in the Amazonian floating meadows: a Hanski core-satellite species system
(2021)
The Amazon catchment is the largest river basin on earth, and up to 30% of its waters flow across floodplains. In its open waters, floating plants known as floating meadows abound. They can act as vectors of dispersal for their associated fauna and, therefore, can be important for the spatial structure of communities. Here, we focus on amphibian diversity in the Amazonian floating meadows over large spatial scales. We recorded 50 amphibian species over 57 sites, covering around 7000 km along river courses. Using multi-site generalised dissimilarity modelling of zeta diversity, we tested Hanski's core-satellite hypothesis and identified the existence of two functional groups of species operating under different ecological processes in the floating meadows. ‘Core' species are associated with floating meadows, while ‘satellite' species are associated with adjacent environments, being only occasional or accidental occupants of the floating vegetation. At large scales, amphibian diversity in floating meadows is mostly determined by stochastic (i.e. random/neutral) processes, whereas at regional scales, climate and deterministic (i.e. niche-based) processes are central drivers. Compared with the turnover of ‘core' species, the turnover of ‘satellite' species increases much faster with distances and is also controlled by a wider range of climatic features. Distance is not a limiting factor for ‘core' species, suggesting that they have a stronger dispersal ability even over large distances. This is probably related to the existence of passive long-distance dispersal of individuals along rivers via vegetation rafts. In this sense, Amazonian rivers can facilitate dispersal, and this effect should be stronger for species associated with riverine habitats such as floating meadows.
Background
The morphology of anuran larvae is suggested to differ between species with tadpoles living in standing (lentic) and running (lotic) waters. To explore which character combinations within the general tadpole morphospace are associated with these habitats, we studied categorical and metric larval data of 123 (one third of which from lotic environments) Madagascan anurans.
Results
Using univariate and multivariate statistics, we found that certain combinations of fin height, body musculature and eye size prevail either in larvae from lentic or lotic environments.
Conclusion
Evidence for adaptation to lotic conditions in larvae of Madagascan anurans is presented. While lentic tadpoles typically show narrow to moderate oral discs, small to medium sized eyes, convex or moderately low fins and non-robust tail muscles, tadpoles from lotic environments typically show moderate to broad oral discs, medium to big sized eyes, low fins and a robust tail muscle.
With the ongoing trend towards deep learning in the remote sensing community, classical pixel based algorithms are often outperformed by convolution based image segmentation algorithms. This performance was mostly validated spatially, by splitting training and validation pixels for a given year. Though generalizing models temporally is potentially more difficult, it has been a recent trend to transfer models from one year to another, and therefore to validate temporally. The study argues that it is always important to check both, in order to generate models that are useful beyond the scope of the training data. It shows that convolutional neural networks have potential to generalize better than pixel based models, since they do not rely on phenological development alone, but can also consider object geometry and texture. The UNET classifier was able to achieve the highest F1 scores, averaging 0.61 in temporal validation samples, and 0.77 in spatial validation samples. The theoretical potential for overfitting geometry and just memorizing the shape of fields that are maize has been shown to be insignificant in practical applications. In conclusion, kernel based convolutions can offer a large contribution in making agricultural classification models more transferable, both to other regions and to other years.
Energy transition strategies in Germany have led to an expansion of energy crop cultivation in landscape, with silage maize as most valuable feedstock. The changes in the traditional cropping systems, with increasing shares of maize, raised concerns about the sustainability of agricultural feedstock production regarding threats to soil health. However, spatially explicit data about silage maize cultivation are missing; thus, implications for soil cannot be estimated in a precise way. With this study, we firstly aimed to track the fields cultivated with maize based on remote sensing data. Secondly, available soil data were target-specifically processed to determine the site-specific vulnerability of the soils for erosion and compaction. The generated, spatially-explicit data served as basis for a differentiated analysis of the development of the agricultural biogas sector, associated maize cultivation and its implications for soil health. In the study area, located in a low mountain range region in Western Germany, the number and capacity of biogas producing units increased by 25 installations and 10,163 kW from 2009 to 2016. The remote sensing-based classification approach showed that the maize cultivation area was expanded by 16% from 7305 to 8447 hectares. Thus, maize cultivation accounted for about 20% of the arable land use; however, with distinct local differences. Significant shares of about 30% of the maize cultivation was done on fields that show at least high potentials for soil erosion exceeding 25 t soil ha−1 a−1. Furthermore, about 10% of the maize cultivation was done on fields that pedogenetically show an elevated risk for soil compaction. In order to reach more sustainable cultivation systems of feedstock for anaerobic digestion, changes in cultivated crops and management strategies are urgently required, particularly against first signs of climate change. The presented approach can regionally be modified in order to develop site-adapted, sustainable bioenergy cropping systems.
The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.