Levels of Arsenic and Other Trace Elements in Southern Libyan Agricultural Irrigated Soil and Non-irrigated Soil Projects

The levels of As and various other trace elements found in the irrigated agricultural soil (Tsoil) of southern Libya were compared with non-irrigated soil (Csoil) from the same sampling campaign collected between April and May 2008. The soil samples represented agronomic practice in the southern Libyan regions of Maknwessa (MAK), Aril (ARL) and Taswaa (TAS), and were analyzed by Inductively coupled plasma mass spectrometry (ICP-MS) for Co, Ni, Cu, Se, Mo, Zn, As, Pb, Cd and P. Concentrations of P and As in TAS and MAK were found to be higher in Tsoil compared to Csoil, while the opposite was true for ARL. In general, As concentrations in these areas were 2-3 times lower than the global average. In ARL, the average P concentrations of the Csoil samples were significantly higher than those of Tsoil samples: this site is composed mainly of pasture for animal production, where phosphate fertilizers are used regularly. Distance from the source of irrigation was found to be of an important influence on the heavy metal concentration of the soil, with greater concentrations found closer to the irrigation source. It can be concluded from the results that irrigation water contains elevated levels of As, which finds its way into the soil profile and can lead to accumulation of As in the soil over time.

Efficacy of sod removal in regenerating fen vegetation for the conservation of the marsh fritillary butterfly Euphydryas aurinia, Montiaghs Moss Nature Reserve, County Antrim, Northern Ireland.

The efficacy of ‘sod removal’ as a fenland restoration technique was tested using an experimental approach at Montiaghs Moss Nature Reserve, Northern Ireland, from 2006 to 2008. The site suffered from rank growth of purple moor-grass Molinia caerulea which was out-competing herbaceous species. Soil was removed up to a depth of 15 cm completely denuding vegetation in the experimental plot exposing bare peat. By July 2007, 15.2% of sod-removal areas were revegetated; by October 2008 cover had risen to 64.6%. Of this cover, purple moor-grass accounted for only 9-11% compared to 78- 79% on control plots. Cover of other rank-forming grass species was also significantly reduced. Sod removal significantly increased the cover of species characteristic of fenlands including sedges Carex spp., rushes Juncus spp., marsh pennywort Hydrocotyle vulgaris and lesser spearwort Ranunculus flammula. It seems likely that sod removal, which lowered the surface of the peat, restored minerotrophic conditions and exposed the historical seed bank stimulating regeneration of some fenland specialists and pioneer species; this resulted in significantly higher species richness on sod removal plots than control plots two years after treatment. There was no demonstrable effect of sod removal on abundance of devil’s-bit scabious Succisa pratensis, the larval food plant of the Annex II listed marsh fritillary butterfly Euphydryas aurinia. We recommend that consideration should be given to artificially seeding devil’s-bit scabious soon after sod removal treatment to promote early recolonisation and to increase plant abundance on the site.

Applying species distribution modelling to identify areas of high conservation value for endangered species: A case study using Margaritifera margaritifera (L.)

The development and implementation of a population supplementation and restoration plan for any endangered species should involve an understanding of the species’ habitat requirements prior to the release of any captive bred individuals. The freshwater pearl mussel, Margaritifera margaritifera, has undergone dramatic declines over the last century and is now globally endangered. In Northern Ireland, the release of captive bred individuals is being used to support wild populations and repatriate the species in areas where it once existed. We employed a combination of maximum entropy modelling (MAXENT) and Generalized Linear Mixed Models (GLMM) to identify ecological parameters necessary to support wild populations using GIS-based landscape scale and ground-truthed habitat scale environmental parameters. The GIS-based landscape scale model suggested that mussel occurrence was associated with altitude and soil characteristics including the carbon, clay, sand, and silt content. Notably, mussels were associated with a relatively narrow band of variance indicating that M. margaritifera has a highly specific landscape niche. The ground-truthed habitat scale model suggested that mussel occurrence was associated with stable consolidated substrates, the extent of bankside trees, presence of indicative macrophyte species and fast flowing water. We propose a three phase conservation strategy for M. margaritifera identifying suitable areas within rivers that (i) have a high conservation value yet needing habitat restoration at a local level, (ii) sites for population supplementation of existing populations and (iii) sites for species reintroduction to rivers where the mussel historically occurred but is now locally extinct. A combined analytical approach including GIS-based landscape scale and ground-truthed habitat scale models provides a robust method by which suitable release sites can be identified for the population supplementation and restoration of an endangered species. Our results will be highly influential in the future management of M. margaritifera in Northern Ireland.

Spatial and Temporal Changes in Soil Organic Carbon Assessment using an Integrated Geostatistical and Compositional Data Analysis Approach

The Irish and UK governments, along with other countries, have made a commitment to limit the concentrations of greenhouse gases in the atmosphere by reducing emissions from the burning of fossil fuels. This can be achieved (in part) through increasing the sequestration of CO2 from the atmosphere including monitoring the amount stored in vegetation and soils. A large proportion of soil carbon is held within peat due to the relatively high carbon density of peat and organic-rich soils. This is particularly important for a country such as Ireland, where some 16% of the land surface is covered by peat. For Northern Ireland, it has been estimated that the total amount of carbon stored in vegetation is 4.4Mt compared to 386Mt stored within peat and soils. As a result it has become increasingly important to measure and monitor changes in stores of carbon in soils. The conservation and restoration of peat covered areas, although ongoing for many years, has become increasingly important. This is summed up in current EU policy outlined by the European Commission (2012) which seeks to assess the relative contributions of the different inputs and outputs of organic carbon and organic matter to and from soil. Results are presented from the EU-funded Tellus Border Soil Carbon Project (2011 to 2013) which aimed to improve current estimates of carbon in soil and peat across Northern Ireland and the bordering counties of the Republic of Ireland.
Historical reports and previous surveys provide baseline data. To monitor change in peat depth and soil organic carbon, these historical data are integrated with more recently acquired airborne geophysical (radiometric) data and ground-based geochemical data generated by two surveys, the Tellus Project (2004-2007: covering Northern Ireland) and the EU-funded Tellus Border project (2011-2013) covering the six bordering counties of the Republic of Ireland, Donegal, Sligo, Leitrim, Cavan, Monaghan and Louth. The concept being applied is that saturated organic-rich soil and peat attenuate gamma-radiation from underlying soils and rocks. This research uses the degree of spatial correlation (coregionalization) between peat depth, soil organic carbon (SOC) and the attenuation of the radiometric signal to update a limited sampling regime of ground-based measurements with remotely acquired data. To comply with the compositional nature of the SOC data (perturbations of loss on ignition [LOI] data), a compositional data analysis approach is investigated. Contemporaneous ground-based measurements allow corroboration for the updated mapped outputs. This provides a methodology that can be used to improve estimates of soil carbon with minimal impact to sensitive habitats (like peat bogs), but with maximum output of data and knowledge.