Ostentation and republican civility: Notes from the French face-veiling debates
In: European journal of political theory: EJPT
ISSN: 1474-8851
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In: European journal of political theory: EJPT
ISSN: 1474-8851
In: The British journal of social work, Band 39, Heft 4, S. 710-724
ISSN: 1468-263X
In: Marchionni , V , Guyot , A , Tapper , N , Walker , J P & Daly , E 2019 , ' Water balance and tree water use dynamics in remnant urban reserves ' , Journal of Hydrology , vol. 575 , pp. 343-353 . https://doi.org/10.1016/j.jhydrol.2019.05.022
During the expansion of urban areas, small natural reserves have often been left intact within the built environment as central elements of biodiversity conservation, ecological connectivity, landscape sustainability, and quality of life of urban dwellers. Consequently, the surrounding urbanized landscape may impact the environmental conditions of these reserves (e.g., high temperatures, low moisture conditions), resulting in the need for extensive maintenance. This study presents an estimation of the water balance over two years (2017–2018) in three small urban reserves (between 2 and 30 ha) within the Greater Melbourne metropolitan area in Australia, for the purpose of understanding tree water use. Measurements of micrometeorological variables, soil moisture content profiles, water-table levels, sap flow velocities, and stem diameter variations were used to quantify the water sources of tree transpiration in these reserves. Results revealed that, despite the urban surroundings and the climate variations, these reserves have enough water to sustain tree transpiration. In two of the three reserves, groundwater was pivotal in sustaining transpiration rates; specifically, groundwater was estimated to contribute about 30–40% of the total transpiration amount during the driest periods of the year. Groundwater also played an essential role during nights with temperatures above 25 °C, helping trees to maintain night-time water use from 3 to 16% of the daily water use. In the third reserve, the presence of a shallow layer of heavy clay supplied water to the trees, which were able to maintain relatively constant transpiration rates throughout the year. These results demonstrate the importance of understanding the water regime of each urban reserve in order to support government authorities in preserving these ecosystems.
BASE
Poster ; The acquisition of sub-surface data for agricultural purposes is traditionally achieved by in situ point sampling in the top 2m over limited target areas (farm scale ~ km2) and time periods. This approach is inadequate for integrated regional (water catchment ~ 100 km2) scale management strategies which require an understanding of processes varying over decadal time scales in the transition zone (~ 10's m) from surface to bedrock. With global food demand expected to increase by 100% by 2050, there are worldwide concerns that achievement of production targets will be at the expense of water quality. In order to overcome the limitations of the traditional approach, this research programme will combine airborne and ground geophysics with remote sensing technologies to access hydrogeological and soil structure information on Irish Soils at multiple spatial scales. It will address this problem in the context of providing tools for the sustainable management of agricultural intensification envisioned in Food Harvest 2020 and Food Wise 2025 and considering the EU Habitats and Water Framework Directives (WFD), Clean Air Policy and Soil Thematic Strategies. The work will use existing ground based geophysical and hydrogeological data from Teagasc Agricultural Catchment Programme (ACP) and Heavy Soil sites co-located ground and airborne electromagnetic data. Neural Networks training and Machine learning approaches will supplement traditional geophysical workflows. Work will then focus on upscaling results from ACP to WFD catchment scale. This upscaling will require modification of traditional satellite remote sensing conceptual frameworks to analyse heterogeneous, multi-temporal data streams.
BASE