Small-scale area effect on species richness and nesting occupancy of cavity-nesting bees and wasps

Small-scale area effect on species richness and nesting occupancy of cavity-nesting bees and wasps. The research was conducted in an urban forest remnant in southeast Brazil. We tested the predictions of the following hypotheses: (1) larger areas present higher species richness of bees and wasps, (2) solitary bees and wasps occupy more nests in larger areas, (3) rare species occupy more nests in smaller areas. We sampled Aculeate bees and wasps using trap nests from February to November 2004. We placed trap nests in sampling units (SU) with different size (25, 100 and 400 m²) located in 6 ha of secondary mesophytic forest. One hundred and thirty-seven trap nests were occupied by seven species of bees and four species of wasps. We found an increase in wasp, but not bee species richness following increase in SU size. Hymenoptera richness (i.e. bees plus wasps) was also greater in larger SU. Both the number and density of occupied nests increased with SU size. The wasp Trypoxylon lactitarse responded significantly to area size, larger SU having more occupied nests. The same pattern was exhibited by the wasp Auplopus militaris, the Megachile bee species, and the bee Anthodioctes megachiloides. Only Trypoxylon sp. was not affected by SU size. Our results show that cavity-nesting bee and wasps respond differently to the area effects. Such findings must be complemented by information on the frequency and dynamics of area colonization and nest occupancy by species of solitary Hymenoptera.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

Scale decisions can reverse conclusions on community assembly processes.

AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.

Large-scale DNA sequencing in taxonomy and conservation : a case study with the mayfly family Heptageniidae (Ephemeroptera) in the Alps and Madagascar

Les larves aquatiques d'éphémères (Ephemeroptera) colonisent toutes les eaux douces du monde et sont couramment utilisées comme bio-indicateurs de la qualité de l'eau. Le genre Rhithrogena (Heptageniidae) est le deuxième plus diversifié chez les éphémères, et plusieurs espèces européennes ont une distribution restreinte dans des environnements alpins sensibles. Les espèces de Rhithrogena ont été classées en "groupes d'espèces" faciles à identifier. Cependant, malgré leur importance écologique et en terme de conservation, beaucoup d'espèces présentent des différences morphologiques ambiguës, suggérant que lataxonomie actuelle ne refléterait pas correctement leur diversité évolutive. De plus, aucune information sur leurs relations, leur origine, le taux de spéciation ou les mécanismes ayant provoqué leur remarquable diversification dans les Alpes n'est disponible. Nous avons d'abord examiné le statut spécifique d'environ 50% des espèces européennes de Rhithrogena en utilisant un large échantillonnage de populations alpines incluant 22 localités typiques, ainsi qu'une analyse basée sur le modèle général mixte de Yule et de coalescence (GMYC) appliqué à un gène mitochondrial standard (coxl) et à un gène nucléaire développé spécifiquement pour cette étude. Nous avons observé un regroupement significatif des séquences coxl en 31 espèces potentielles, et nos résultats ont fortement suggéré la présence d'espèces cryptiques et de fractionnements taxonomiques excessifs chez les Rhithrogena. Nos analyses phylogénétiques ont démontré la monophylie de quatre des six groupes d'espèces reconnus présents dans notre échantillonnage. La taxonomie ADN développée dans cette étude pose les bases d'une future révision de ce genre important mais cryptique en Europe. Puis nous avons mené une étude phylogénétique multi-gènes entre les espèces européennes de Rhithrogena. Les données provenant de trois gènes nucléaires et de deux gènes mitochondriaux ont été largement concordantes, et les relations entre les espèces bien résolues au sein de la plupart des groupes d'espèces dans une analyse combinant tous les gènes. En l'absence de points de calibration extérieurs tels que des fossiles, nous avons appliqué à nos données mitochondriales une horloge moléculaire standard pour les insectes, suggérant une origine des Rhithrogena alpins à la limite Oligocène / Miocène. Nos résultats ont montré le rôle prépondérant qu'ont joué les glaciations du quaternaire dans leur diversification, favorisant la spéciation d'au moins la moitié des espèces actuelle dans les Alpes. La biodiversité et le taux d'endémisme à Madagascar, notamment au niveau de la faune des eaux douces, sont parmi les plus extraordinaires et les plus menacés au monde. On pense que beaucoup d'espèces d'éphémères sont restreintes à un seul bassin versant (microendémisme) dans les zones forestières, ce qui les rendrait particulièrement sensibles à la réduction et à la dégradation de leur habitat. Mis à part deux espèces décrites, Afronurus matitensis et Compsoneuria josettae, les Heptageniidae sont pratiquement inconnus à Madagascar. Les deux genres ont une distribution discontinue en Afrique, à Madagascar et en Asie du Sud-Est, et leur taxonomie complexe est régulièrement révisée. L'approche standard pour comprendre leur diversité, leur endémisme et leur origine requerrait un échantillonnage étendu sur plusieurs continents et des années de travaux taxonomiques. Pour accélérer le processus, nous avons utilisé des collections de musées ainsi que des individus fraîchement collectés, et appliqué une approche combinant taxonomie ADN et phylogénie. L'analyses GMYC du gène coxl a délimité 14 espèces potentielles à Madagascar, dont 70% vraisemblablement microendémiques. Une analyse phylogénique incluant des espèces africaines et asiatiques portant sur deux gènes mitochondriaux et quatre gènes nucléaires a montré que les Heptageniidae malgaches sont monophylétiques et groupe frère des Compsoneuria africains. L'existence de cette lignée unique, ainsi qu'un taux élevé de microendémisme, mettent en évidence leur importance en terme de conservation. Nos résultats soulignent également le rôle important que peuvent jouer les collections de musées dans les études moléculaires et en conservation. - Aquatic nymphs of mayflies (Ephemeroptera) colonize all types of freshwaters throughout the world and are extensively used as bio-indicators of water quality. Rhithrogena (Heptageniidae) is the second most species-rich genus of mayflies, and several European species have restricted distributions in sensitive Alpine environments and therefore are of conservation interest. The European Rhithrogena species are arranged into "species groups" that are easily identifiable. However, despite their ecological and conservation importance, ambiguous morphological differences among many species suggest that the current taxonomy may not accurately reflect their evolutionary diversity. Moreover, no information about their relationships, origin, timing of speciation and mechanisms promoting their successful diversification in the Alps is available. We first examined the species status of ca. 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule- coalescent (GMYC) model analysis of one standard mitochondrial (coxl) and one newly developed nuclear marker. We observed significant clustering of coxl into 31 GMYC species, and our results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Phylogenetic analyses recovered four of the six recognized species groups in our samples as monophyletic. The DNA taxonomy developed here lays the groundwork for a future revision of this important but cryptic genus in Europe. Then we conducted a species-level, multiple-gene phylogenetic study of European Rhithrogena. Data from three nuclear and two mitochondrial loci were broadly congruent, and species-level relationships were well resolved within most species groups in a combined analysis. In the absence of external calibration points like fossils, we applied a standard insect molecular clock hypothesis to our mitochondrial data, suggesting an origin of Alpine Rhithrogena in the Oligocene / Miocene boundary. Our results highlighted the preponderant role that quaternary glaciations played in their diversification, promoting speciation of at least half of the current diversity in the Alps. Madagascar's biodiversity and endemism are among the most extraordinary and endangered in the world. This includes the island's freshwater biodiversity, although detailed knowledge of the diversity, endemism, and biogeographic origin of freshwater invertebrates is lacking. Many mayfly species are thought to be restricted to single river basins (microendemic species) in forested areas, making them particularly sensitive to habitat reduction and degradation. The Heptageniidae are practically unknown in Madagascar except for two described species, Afronurus matitensis and Compsoneuria josettae. Both genera have a disjunct distribution in Africa, Madagascar and Southeast Asia, and a complex taxonomic status still in flux. The standard approach to understanding their diversity, endemism, and origin would require extensive field sampling on several continents and years of taxonomic work. Here we circumvent this using museum collections and freshly collected individuals in a combined approach of DNA taxonomy and phylogeny. The cox/-based GMYC analysis revealed 14 putative species on Madagascar, 70% of which potentially microendemics. A phylogenetic analysis that included African and Asian species and data from two mitochondrial and four nuclear loci indicated the Malagasy Heptageniidae are monophyletic and sister to African Compsoneuria. The observed monophyly and high microendemism highlight their conservation importance. Our results also underline the important role that museum collections can play in molecular studies, especially in critically endangered biodiversity hotspots like Madagascar.

A matter of scale: apparent niche differentiation of diploid and tetraploid plants may depend on extent and grain of analysis

Aim: Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. Location: European Alps. Methods: We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100x100m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2x2m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations. Results: All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole-range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine-grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse-grained data. Main conclusions: Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse-grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.

Improving sampling, optimization and feature extraction in Boltzmann machines

L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inférence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.

A study of the large-scale structure of the wind of WR 134

Diverses méthodes ont été utilisées pour étudier les étoiles Wolf-Rayet (WR) dans le but de comprendre les phénomènes physiques variés qui prennent place dans leur vent dense. Pour étudier la variabilité qui n'est pas strictement périodique et ayant des caractéristiques différentes d'une époque à l'autre, il faut observer pendant des périodes de temps suffisamment longues en adopter un échantillonnage temporel élevé pour être en mesure d'identifier les phénomènes physiques sous-jacents. À l'été 2013, des astronomes professionnels et amateurs du monde entier ont contribué à une campagne d'observation de 4 mois, principalement en spectroscopie, mais aussi en photométrie, polarimétrie et en interférométrie, pour observer les 3 premières étoiles Wolf-Rayet découvertes: WR 134 (WN6b), WR 135 (WC8) et WR 137 (WC7pd + O9). Chacune de ces étoiles est intéressante à sa manière, chacune présentant une variété différente de structures dans son vent. Les données spectroscopiques de cette campagne ont été réduites et analysées pour l'étoile présumée simple WR 134 pour mieux comprendre le comportement de sa variabilité périodique à long terme dans le cadre d'une étude des régions d'interactions en corotation (CIRs) qui se retrouvent dans son vent. Les résultats de cette étude sont présentés dans ce mémoire.

Short-eared Owl (Asio flammeus) surveys in the North American Intermountain West: utilizing citizen scientists to conduct monitoring across a broad geographic scale

The Short-eared Owl (Asio flammeus) is an open-country species breeding in the northern United States and Canada, and has likely experienced a long-term, range-wide, and substantial decline. However, the cause and magnitude of the decline is not well understood. We set forth to address the first two of six previously proposed conservation priorities to be addressed for this species: (1) better define habitat use and (2) improve population monitoring. We recruited 131 volunteers to survey over 6.2 million ha within the state of Idaho for Short-eared Owls during the 2015 breeding season. We surveyed 75 transects, 71 of which were surveyed twice, and detected Short-eared Owls on 27 transects. We performed multiscale occupancy modeling to identify habitat associations, and performed multiscale abundance modeling to generate a state-wide population estimate. Our results suggest that within the state of Idaho, Short-eared Owls are more often found in areas with marshland or riparian habitat or areas with greater amounts of sagebrush habitat at the 1750 ha transect scale. At the 50 ha point scale, Short-eared Owls tend to associate positively with fallow and bare dirt agricultural land and negatively with grassland. Cropland was not chosen at the broader transect scale suggesting that Short-eared Owls may prefer more heterogeneous landscapes. On the surface our results may seem contradictory to the presumed land use by a “grassland” species; however, the grasslands of the Intermountain West, consisting largely of invasive cheatgrass (Bromus tectorum), lack the complex structure shown to be preferred by these owls. We suggest the local adaptation to agriculture represents the next best habitat to their historical native habitat preferences. Regardless, we have confirmed regional differences that should be considered in conservation planning for this species. Last, our results demonstrate the feasibility, efficiency, and effectiveness of utilizing public participation in scientific research to achieve a robust sampling methodology across the broad geography of the Intermountain West.

The Representative Soil Sampling Scheme of England and Wales: the spatial variation of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme (RSSS) has monitored the soil of agricultural land in England and Wales since 1969. Here we describe the first spatial analysis of the data from these surveys using geostatistics. Four years of data (1971, 1981, 1991 and 2001) were chosen to examine the nutrient (available K, Mg and P) and pH status of the soil. At each farm, four fields were sampled; however, for the earlier years, coordinates were available for the farm only and not for each field. The averaged data for each farm were used for spatial analysis and the variograms showed spatial structure even with the smaller sample size. These variograms provide a reasonable summary of the larger scale of variation identified from the data of the more intensively sampled National Soil Inventory. Maps of kriged predictions of K generally show larger values in the central and southeastern areas (above 200 mg L-1) and an increase in values in the west over time, whereas Mg is fairly stable over time. The kriged predictions of P show a decline over time, particularly in the east, and those of pH show an increase in the east over time. Disjunctive kriging was used to examine temporal changes in available P using probabilities less than given thresholds of this element. The RSSS was not designed for spatial analysis, but the results show that the data from these surveys are suitable for this purpose. The results of the spatial analysis, together with those of the statistical analyses, provide a comprehensive view of the RSSS database as a basis for monitoring the soil. These data should be taken into account when future national soil monitoring schemes are designed.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

Boundary layer structure and decoupling from synoptic scale flow during NAMBLEX

This paper presents an overview of the meteorology and planetary boundary layer structure observed during the NAMBLEX field campaign to aid interpretation of the chemical and aerosol measurements. The campaign has been separated into five periods corresponding to the prevailing synoptic condition. Comparisons between meteorological measurements ( UHF wind profiler, Doppler sodar, sonic aneometers mounted on a tower at varying heights and a standard anemometer) and the ECMWF analysis at 10 m and 1100 m identified days when the internal boundary layer was decoupled from the synoptic flow aloft. Generally the agreement was remarkably good apart from during period one and on a few days during period four when the diurnal swing in wind direction implies a sea/land breeze circulation near the surface. During these periods the origin of air sampled at Mace Head would not be accurately represented by back trajectories following the winds resolved in ECMWF analyses. The wind profiler observations give a detailed record of boundary layer structure including an indication of its depth, average wind speed and direction. Turbulence statistics have been used to assess the height to which the developing internal boundary layer, caused by the increased surface drag at the coast, reaches the sampling location under a wide range of marine conditions. Sampling conducted below 10 m will be impacted by emission sources at the shoreline in all wind directions and tidal conditions, whereas sampling above 15 m is unlikely to be affected in any of the wind directions and tidal heights sampled during the experiment.

Evaluating the efficiency of sampling methods in assessing soil macrofauna communities in arable systems

The soil fauna is often a neglected group in many large-scale studies of farmland biodiversity due to difficulties in extracting organisms efficiently from the soil. This study assesses the relative efficiency of the simple and cheap sampling method of handsorting against Berlese-Tullgren funnel and Winkler apparatus extraction. Soil cores were taken from grassy arable field margins and wheat fields in Cambridgeshire, UK, and the efficiencies of the three methods in assessing the abundances and species densities of soil macroinver-tebrates were compared. Handsorting in most cases was as efficient at extracting the majority of the soil macrofauna as the Berlese-Tullgren funnel and Winkler bag methods, although it underestimated the species densities of the woodlice and adult beetles. There were no obvious biases among the three methods for the particular vegetation types sampled and no significant differences in the size distributions of the earthworms and beetles. Proportionally fewer damaged earthworms were recorded in larger (25 x 25 cm) soil cores when compared with smaller ones (15 x 15 cm). Handsorting has many benefits, including targeted extraction, minimum disturbance to the habitat and shorter sampling periods and may be the most appropriate method for studies of farmland biodiversity when a high number of soil cores need to be sampled. (C) 2008 Elsevier Masson SAS. All rights reserved.