The ecology of the song thrush, Turdus philomelos Br., in Ireland

Over the last 30 years, western European Song Thrush populations have declined with the steepest decline recorded on British farmland. Changes in agricultural practices have been implicated in these population declines. Ireland is an agriculturally dominated landscape but changes in agriculture here have occurred on a relatively slower rate and scale. Little is known about the ecology of the Song Thrush in Ireland, even though it is not classified as a species of conservation concern here. Some decline is thought to have occurred but the current breeding population appears to be stable and widespread. In light of these facts, this study investigated various aspects of Song Thrush ecology in relation to the Irish landscape from 2001-2003. The breeding season extended from mid March to late June, where mean clutch size was 4.1 and number of fledglings was 3.7. There were very few third broods. Daily nest survival rates were calculated for egg stage 0.9362, incubation stage 0.9505 and nestling stage 0.6909. Most nest failures were due to avian predation at both egg and chick stages. Most nests were located 1.3 -2.4m from the ground at trees, bushes or hedgerow. Clutch size was significantly higher on farmland than garden & parkland and woodland, and the number of fledglings was significantly lower in nests in trees than hedgerow and bush sites. Daily nest fail rates were significantly higher at tree sites and partly concealed nests. Nesting areas had significantly denser vertical vegetation than non-nesting areas. Mercury and the organochlorine HEOD were the most common contaminants in Song Thrush eggs and livers. However concentrations and occurrence were low and of no apparent biological or ecological concern. The presence of breeding Song Thrushes was influenced by mixed surrounding farmland, the absence of grass surrounding farmland, ditches especially wet ones, tall dense vegetation and trimmed boundaries. Song Thrush winter densities were predicted by ditches, with wet or dry, low thin vegetation and untrimmed boundaries. Winter densities were almost double that of the breeding season, probably due to the arrival and passage of migrating Song Thrushes through the country, especially in November. Changes in Irish agriculture did not differ significantly in areas of Song Thrush breeding population stability and apparent decline during 1970 1990. Even though the current breeding population heavily uses farmland, woodland, human and scrub habitats are more preferred. Nevertheless no farmland habitat was avoided, highlighting a positive relationship between breeding Song Thrushes and Irish agriculture. This appears to be in contrast with findings between breeding Song Thrushes and British agriculture. Theses findings are compared with other studies and possible influences by agricultural intensification, climate, latitude and insular syndrome are discussed. Implications for conservation measures are considered, especially for areas of decline. Even though Song Thrushes are currently widespread and stable here, future environmental consequences of longer-term changes in Irish agriculture and perhaps climate change remain to be seen.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Air sensitivity of MoS2, MoSe2, MoTe2, HfS2 and HfSe2

A surface sensitivity study was performed on different transition-metal dichalcogenides (TMDs) under ambient conditions in order to understand which material is the most suitable for future device applications. Initially, Atomic Force Microscopy and Scanning Electron Microscopy studies were carried out over a period of 27 days on mechanically exfoliated flakes of 5 different TMDs, namely, MoS2, MoSe2, MoTe2, HfS2, and HfSe2. The most reactive were MoTe2 and HfSe2. HfSe2, in particular, showed surface protrusions after ambient exposure, reaching a height and width of approximately 60 nm after a single day. This study was later supplemented by Transmission Electron Microscopy (TEM) cross-sectional analysis, which showed hemispherical-shaped surface blisters that are amorphous in nature, approximately 180–240 nm tall and 420–540 nm wide, after 5 months of air exposure, as well as surface deformation in regions between these structures, related to surface oxidation. An X-ray photoelectron spectroscopy study of atmosphere exposed HfSe2 was conducted over various time scales, which indicated that the Hf undergoes a preferential reaction with oxygen as compared to the Se. Energy-Dispersive X-Ray Spectroscopy showed that the blisters are Se-rich; thus, it is theorised that HfO2 forms when the HfSe2 reacts in ambient, which in turn causes the Se atoms to be aggregated at the surface in the form of blisters. Overall, it is evident that air contact drastically affects the structural properties of TMD materials. This issue poses one of the biggest challenges for future TMD-based devices and technologies.

Design, modelling and preliminary characterisation of microneedle-based electrodes for tissue electroporation in vivo

We analysed the use of microneedle-based electrodes to enhance electroporation of mouse testis with DNA vectors for production of transgenic mice. Different microneedle formats were developed and tested, and we ultimately used electrodes based on arrays of 500 μm tall microneedles. In a series of experiments involving injection of a DNA vector expressing Green Fluorescent Protein (GFP) and electroporation using microneedle electrodes and a commercially available voltage supply, we compared the performance of flat and microneedle electrodes by measuring GFP expression at various timepoints after electroporation. Our main finding, supported by both experimental and simulated data, is that needles significantly enhanced electroporation of testis.