Demographics and landscape features determine intrariver population structure in Atlantic salmon (Salmo salar L.): the case of the River Moy in Ireland

Contemporary genetic structure of Atlantic salmon (Salmo salar L.) in the River Moy in Ireland is shown here to be strongly related to landscape features and population demographics, with populations being defined largely by their degree of physical isolation and their size. Samples of juvenile salmon were collected from the 17 major spawning areas on the river Moy and from one spawning area in each of five smaller nearby rivers. No temporal allele frequency differences were observed within locations for 12 microsatellite loci, whereas nearly all spatial samples differed significantly, suggesting that each was a separate population. Bayesian clustering and landscape genetic analyses suggest that these populations can be combined hierarchically into five genetically informative larger groupings. Lakes were found to be the single most important determinant of the observed population structure. Spawning area size was also an important factor. The salmon population of the closest nearby river resembled genetically the largest Moy population grouping. In addition, we showed that anthropogenic influences on spawning habitats, in this case arterial drainage, can affect relationships between populations. Our results show that Atlantic salmon biodiversity can be largely defined by geography, and thus, knowledge of landscape features (for example, as characterized within Geographical Information Systems) has the potential to predict population structure in other rivers without an intensive genetic survey, or at least to help direct sampling. This approach of combining genetics and geography, for sampling and in subsequent statistical analyses, has wider application to the investigation of population structure in other freshwater/anadromous fish species and possibly in marine fish and other organisms.

A PRELIMINARY ASSESSMENT OF THE DISTRIBUTION OF THE SEA LAMPREY (PETROMYZON MARINUS L.), RIVER LAMPREY (LAMPETRA FLUVIATILIS (L.)) AND BROOK LAMPREY (LAMPETRA PLANERI (BLOCH)) IN NORTHERN IRELAND

Lampreys are endangered in Europe, and European states are legally required to take measures to ensure their protection. However, there is currently little information on the distribution of the three species present in Northern Ireland. Anecdotal records of adult lampreys were collated from anglers and other sources, and a systematic electrofishing survey was undertaken to establish the distribution of lamprey ammocoetes. Lampreys were found in seven of the nine Northern Irish river catchments. Brook lampreys (Lampetra planeri (Bloch)) were widely distributed, but the two anadromous species, sea lamprey (Petromyzon marinus L.) and river lamprey (Lampetra fluviatilis (L.)), were more limited in their distribution, possibly due to barriers restricting migration.

River definitions in Roman technical literature

Definitions of rivers and their use by Roman land surveyors and lawyers.

Technical Note: Assessing a 24/7 solution for monitoring water quality loads in small river catchments

Quantifying nutrient and sediment loads in catchments is dif?cult owing to diffuse controls related to storm hydrology. Coarse sampling and interpolation methods are prone to very high uncertainties due to under-representation of high discharge, short duration events. Additionally, important low-?ow processes such as diurnal signals linked to point source impacts are missed. Here we demonstrate a solution based on a time-integrated approach to sampling with a standard 24 bottle autosampler con?gured to take a sample every 7 h over a week according to a Plynlimon design. This is evaluated with a number of other sampling strategies using a two-year dataset of sub-hourly discharge and phosphorus concentration data. The 24/7 solution is shown to be among the least uncertain in estimating load (inter-quartile range: 96% to 110% of actual load in year 1 and 97% to 104% in year 2) due to the increased frequency raising the probability of sampling storm events and point source signals. The 24/7 solution would appear to be most parsimonious in terms of data coverage and certainty, process signal representation, potential laboratory commitment, technology requirements and the ability to be widely deployed in complex catchments.