Habitat specificity of a threatened and endemic cliff-dwelling halophyte

Research ArticleCoastal areas and other saline environments are major contributors to regional and global biodiversity patterns. In these environments, rapidly changing gradients require highly specialized plants like halophytes. In European coastal cliff-tops, rocky and sandy seashores, and saltmarshes, typical halophytes from the genus Limonium are commonly found. Among them, the aneuploid tetraploid (2n ¼ 4x ¼ 35, 36, 37) Limonium multiflorum, endemic to the west coast of Portugal, is an interesting case study for investigating the ecology and conservation of a halophyte agamospermic species. Although it is listed in the IUCN red list of threatened species, information on its population size or rarity, as well as its ecology, in some respects is still unknown. Field surveys in the largest known population were performed (Raso cape, Portugal) in order to determine habitat requirements and conservation status. A total of 88 quadrats were monitored, 43 of which contained at least one L. multiflorum individual. For each sampled quadrat, four abiotic and four biotic variables as well as two spatially derived variables were recorded. Principal component analysis and cluster analysis showed narrow habitat specificity for this species which appeared to be intolerant to competition with invasive alien plants. We conclude that in situ conservation in a local ‘hotspot’ of this rare and vulnerable species emerges as a priority in order to ensure that biodiversity is not los

Derivation of a national fuzzy phosporous export model using 84 Irish catchments

Implementation of appropriate management strategies to mitigate diffuse phosphorus (P) pollution at the catchment scale is vitally important for the sustainable development of water resources in Ireland. An important element in the process of implementing such strategies is the prediction of their impacts on P concentrations in a catchment using a reliable mathematical model. In this study, a state-of-the-art adaptive neuro-fuzzy inference system (ANFIS) has been used to develop a new national P model capable of estimating average annual ortho-P concentrations at un-gauged catchments. Data from 84 catchments dominated by diffuse P pollution were used in developing and testing the model. Six different split-sample scenarios were used to partition the total number of the catchments into two sets, one to calibrate and the other to validate the model. The k-means clustering algorithm was used to partition the sets into clusters of catchments with similar features. Then for each scenario and for each cluster case, 11 different models, each of which consists of a linear regression sub-model for each cluster, were formulated by using different input variables selected from among six spatially distributed variables including phosphorus desorption index (PDI), runoff risk index (RRI), geology (GEO), groundwater (GW), land use (LU), and soil (SO). The success of the new approach over the conventional lumped, empirical, modelling approach was evident from the improved results obtained for most of the cases. In addition the results highlighted the importance of using information on PDI and RRI as explanatory input variables to simulate the average annual ortho-P concentrations.For repositories (i) School of Civil Structural and Environmental Engineering and (ii) Centre for Water Resources ResearchAM

Potential impacts of climate change on veterinary medicinal residues in livestock produce: An island of Ireland perspective

Residues of veterinary medicines are a food safety issue regulated by European legislation. The occurrence of animal diseases necessitating application of veterinary medicines is significantly affected by global and local climate changes. This review assesses potential impacts of climate change on residues in food produced on the island of Ireland. Use of various classes of veterinary drugs in light of predicted local climate change is reviewed with particular emphasis on anthelmintic drugs and consideration is given to residues accumulating in the environment. Veterinary medicine use is predicted to increase as disease burdens increase due to varied climate effects. Locally relevant mitigation and adaptation strategies are suggested to ensure climate change does not adversely affect food safety via increasing drug residues