Search

The Groningen gas field in the Netherlands is experiencing induced seismicity as a result of ongoing depletion. The physical mechanisms that control seismicity have been studied through rock mechanical experiments and combined physical-statistical models to support development of a framework to forecast induced-seismicity risks. To investigate whether machine learning techniques such as Random Forests and Support Vector Machines bring new insights into forecasts of induced seismicity rates in space and time, a pipeline is designed that extends time-series analysis methods to a spatiotemporal framework with a factorial setup, which allows probing a large parameter space of plausible modelling assumptions, followed by a statistical meta-analysis to account for the intrinsic uncertainties in subsurface data and to ensure statistical significance and robustness of results. The pipeline includes model validation using e.g. likelihood ratio tests against average depletion thickness and strain thickness baselines to establish whether the models have statistically significant forecasting power. The methodology is applied to forecast seismicity for two distinctly different gas production scenarios. Results show that seismicity forecasts generated using Support Vector Machines significantly outperform beforementioned baselines. Forecasts from the method hint at decreasing seismicity rates within the next 5 years, in a conservative production scenario, and no such decrease in a higher depletion scenario, although due to the small effective sample size no statistically solid statement of this kind can be made. The presented approach can be used to make forecasts beyond the investigated 5-years period, although this requires addition of limited physics-based constraints to avoid unphysical forecasts.

Advancing production from the Groningen gas field to full depletion generates substantial, field-scale deformation, and surface subsidence. Quantifying associated risk requires understanding physical processes in the subsurface, in particular those related to deformation of the Permian sandstone reservoir. Here, we report the results of a large experimental study, using fresh core material taken from the center of the field. By subjecting the material to depletion and slight unloading, complemented with a range of rock property measurements, we determine what rock physical properties control production-induced compaction in the material. Our results show that, although a large part of the deformation can be explained by classical linear poroelasticity, the contribution of inelastic (permanent) deformation is also significant. In fact, it increases with progressing pressure depletion, i.e. with increasing production. Utilizing univariate and multivariate statistical methods, we explain the additional inelastic deformation by direct effects of porosity, packing, and mineral composition. These proxies are in turn related to the depositional setting of the Permian reservoir. Our findings suggest that field-scale subsidence may not only be related to the often-used rock porosity, but also to packing, and composition, hence the local depositional environment. This motivates alternative assessments of human-induced mechanical effects in sedimentary systems.

Concern exists about the potential effects of pile-driving sounds on fish, but evidence is limited, especially for fish larvae. A device was developed to expose larvae to accurately reproduced pile-driving sounds. Controlled exposure experiments were carried out to examine the lethal effects in common sole larvae. No significant effects were observed at zero-to-peak pressure levels up to 210 dB re 1 μPa 2 and cumulative sound exposure levels up to 206 dB re 1 μPa 2 ·s, which is well above the US interim criteria for nonauditory tissue damage in fish. Experiments are presently being carried out for European sea bass and herring larvae. © Springer Science+Business Media New York 2016.

Uhlmann, S. S., Bierman, S. M., and van Helmond, A. T. M. 2011. A method of detecting patterns in mean lengths of samples of discarded fish, applied to the self-sampling programme of the Dutch bottom-trawl fishery. – ICES Journal of Marine Science, 68: 1712–1718. In 2009, a self-sampling programme was organized in the Netherlands, fishers sampling ca. 80 kg of discards from randomly selected bottom trawls in the North Sea. A statistical procedure is proposed to highlight samples, trips (with multiple samples), or vessels (which may have multiple trips within a year) where extreme mean lengths of discarded fish were observed. Randomization methods were used to test for evidence of non-randomness in patterns of highlighted discard samples, e.g. repeated observations of extreme mean lengths for consecutive discard samples across trips from the same vessel. European plaice (Pleuronectes platessa), common dab (Limanda limanda), grey gurnard (Eutrigla gurnardus), and whiting (Merlangius merlangus) were considered because these were the most abundant species in most of the discard samples. A linear mixed model was used to estimate random-sample effects on the estimated mean lengths by species. These random effects were incorporated into uni- and bivariate procedures to identify extreme samples that were summed for each vessel, and the probability of observing such numbers was estimated. Excluding these samples from the dataset had marginal effects on estimated size distributions of fish.

Variation in plant functional traits has been related to variation in environmental conditions. In particular, the relationship between leaf traits and climate has received much attention. This paper presents a functional-trait-centred approach to identify potential impacts of climate and land use change on plant species assemblages. Using species atlas data, we modelled the relative frequencies of species with different leaf anatomies (LARF) as a function of observed climate and land use data on a regular spatial grid across Germany. Subsequently, we projected the geographical distribution of LARF with simulated climate and land use data for the late 21st century under two future scenarios. We used a conditional autoregressive regression model to account for spatially structured variation in LARF that remained unexplained by the environmental factors considered. We found a clear relationship between the climatic gradient of water availability and shifts in LARF: increasing water deficit was associated with a decreasing proportion of species with hygromorphic leaves in the composition and increasing proportions of species with scleromorphic and mesomorphic leaves. The variation in LARF due to land use was only small. Under future environmental scenarios the proportion of species with hygromorphic leaves was projected to decrease in all parts of Germany, whereas the proportions of species with sclero- and mesomorphic leaves were projected to increase on average. In particular, Germany's south-western and north-eastern areas were projected to experience functional change in LARF. Our study highlights the relationship between functional traits and plant species vulnerability to climate change. Our results suggest that the functional-trait-centred approach can provide a powerful additional modelling tool to estimate potential impacts of climate change on plant species assemblages.

The threshold concentration for NH 3 in rearing water of African catfish ( Clarias gariepinus ) was assessed. African catfish with an initial mean (SD) weight of 141.0 (24) g were exposed to five different T amm [sum of NH 3 and NH 4 + ] concentrations: 0.37 (Control), 1.06, 2.12, 5.16 and 19.7 mM, which concurs with NH 3 concentrations of 4 (Control), 14, 38, 176 and 1084 μM. Plasma concentrations of NH 4 + , cortisol, glucose and lactate, plasma osmolality, gill morphology, branchial Na + /K + -ATPase activity, feed intake and specific growth rate were monitored. No effect of water NH 3 on plasma NH 4 + concentrations was detected. Feed intake and specific growth rate were severely affected at exposure to water NH 3 concentrations above 90 μM (calculated EC 10 values: 89 and 122 μM). No major disturbances in physiological blood parameters were observed at these NH 3 concentrations, but gill morphology (a remarkably sensitive stress indicator) deteriorated significantly. Based on the lower limit of the 95% confidence interval for EC 10 , we advise for African catfish not to exceed a water NH 3 concentration of 24 μM (0.34 mg NH 3 -N/L). This finding is relevant for design and management of African catfish production systems.

Effects of regular treatments with the fungicides carbendazim and prochloraz applied to whole plots divided into subplots with different initial population mixtures of carbendazim-sensitive or carbendazim-resistant Tapesia yallundae or T. acuformis were studied in successive crops of winter wheat from 1984/85 to 1999/2000. In unsprayed and carbendazim-sprayed whole plots, a stable coexistence of about 50% each of T. yallundae and T. acuformis developed within five seasons, but in whole plots sprayed with prochloraz or prochloraz plus carbendazim, the proportion of T. acuformis increased to > 80%. A discrete time difference equation model was derived from knowledge of the biology of eyespot and competition theory to describe the population changes. The model was fitted to the data from treatments where coexistence occurred [subplots in unsprayed (1985–92) and carbendazim-sprayed (1985–89) whole plots], using nonlinear least squares regression. The optimized value of the resource overlap coefficient was small, suggesting niche differences between the two species. Populations were nearly 100% carbendazim-resistant in carbendazim-sprayed whole plots by July 1985 (one season) and in whole plots sprayed with prochloraz plus carbendazim by July 1986 (two seasons). In prochloraz-sprayed whole plots, the proportion of carbendazim-resistant isolates decreased more rapidly than in unsprayed whole plots in the 1980s, but by July 1992 a shift in populations in unsprayed and prochloraz-sprayed whole plots towards predominantly carbendazim-resistant strains had occurred.

The ammonia (NH 3 ) and nitrate (NO 3 − ) threshold concentrations in rearing water of juvenile pikeperch ( Sander lucioperca ) were assessed. Pikeperch with an initial mean (SD) weight of 17.7 (4.2) g were exposed to 0.9 (control), 3.6, 5.2, 7.1, 11.2 and 18.9 μM NH 3 in the water for 42 days. Plasma NH 4 + concentrations stayed at control levels (~ 650 μM) up to 11.2 μM NH 3 in the water. At the highest water NH 3 concentration tested, plasma NH 4 + had more than doubled to 1400 μM. Based on the specific growth rate, the EC 10 value for NH 3 was 5.7 μM. When pikeperch (initial mean (SD) weight of 27.0 (4.9) g) were exposed to 0.1 (control), 1.5, 2.3, 3.7, 6.1, 10.2, 15.8 and 25.6 mM NO 3 − for 42 days, mean (SD) plasma NO 3 − concentrations increased linearly from 88 (47) to 5993 (899) μM at the highest ambient NO 3 − level. Feed intake, specific growth rate and feed conversion ratio were not affected. Neither NH 3 nor NO 3 − exposure significantly affected haematocrit, plasma concentrations of cortisol, glucose, lactate, osmolality, gill morphology or branchial Na + /K + -ATPase activity in pikeperch. For juvenile pikeperch we advise not to exceed a water NH 3 concentration of 3.4 μM (0.05 mg NH 3 –N/L), the lower limit of the 95% confidence interval of the EC 10 value for SGR, to ensure proper physiology and growth. For NO 3 − we advise not to exceed 25 mM (350 mg NO 3 − –N/L). This criterion is based on the highest NO 3 − concentration tested (25.6 mM). As no negative effects were detected at the highest concentration tested, the actual NO 3 − threshold probably exceeds 25.6 mM.

Dover sole (Solea solea) is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea) and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole.

In view of the rapid extension of offshore wind farms, there is an urgent need to improve our knowledge on possible adverse effects of underwater sound generated by pile-driving. Mortality and injuries have been observed in fish exposed to loud impulse sounds, but knowledge on the sound levels at which (sub-)lethal effects occur is limited for juvenile and adult fish, and virtually non-existent for fish eggs and larvae. A device was developed in which fish larvae can be exposed to underwater sound. It consists of a rigid-walled cylindrical chamber driven by an electro-dynamical sound projector. Samples of up to 100 larvae can be exposed simultaneously to a homogeneously distributed sound pressure and particle velocity field. Recorded pile-driving sounds could be reproduced accurately in the frequency range between 50 and 1000 Hz, at zero to peak pressure levels up to 210 dB re 1µPa(2) (zero to peak pressures up to 32 kPa) and single pulse sound exposure levels up to 186 dB re 1µPa(2)s. The device was used to examine lethal effects of sound exposure in common sole (Solea solea) larvae. Different developmental stages were exposed to various levels and durations of pile-driving sound. The highest cumulative sound exposure level applied was 206 dB re 1µPa(2)s, which corresponds to 100 strikes at a distance of 100 m from a typical North Sea pile-driving site. The results showed no statistically significant differences in mortality between exposure and control groups at sound exposure levels which were well above the US interim criteria for non-auditory tissue damage in fish. Although our findings cannot be extrapolated to fish larvae in general, as interspecific differences in vulnerability to sound exposure may occur, they do indicate that previous assumptions and criteria may need to be revised.

Biological atlases are, for many species, the only source of information on their distribution over large geographical areas, and are widely used to inform models of the environmental distribution of species. Such data are not collected using standardized survey techniques, however, and spatial variations in coverage (the relative extent or completeness of records) may lead to variations in the probability that the species will be recorded at locations where it is present (the ‘‘recording probability’’). If spatial patterns in recording probabilities are correlated with key environmental variables, then biased estimates of the relationships between environmental variables and species distributions may be obtained. We outline a general statistical framework for modelling the environmental distribution of species using, known as Bayesian Image Restoration (BIR). BIR can be used in combination with any species distribution model, but in addition allows us to account for spatial heterogeneity in recording probabilities by utilizing expert knowledge on spatial patterns in coverage. We illustrate the methodology by applying it to maps of the recorded distribution of two plant species in Germany, taken from the German atlas of vascular plants. We find that estimated spatial patterns in recording probabilities for both species are correlated with key environmental variables. Consequently, different relationships between the probability of presence of a species and environmental variables were obtained when the species distribution models were parameterised within a BIR framework. Care must be taken in the application of BIR, since the resulting inferences can depend strongly upon the modelling assumptions that are adopted. Nevertheless, we conclude that BIR has the potential to make better use of uncertain information on species distributions than conventional methods, and can be used to formally investigate the robustness of inferences on the environmental distribution of species to assumptions concerning spatial patterns in recording probabilities.

Bierman, S. M., Dickey-Collas, M., van Damme, C. J. G., van Overzee, H. M. J., Pennock-Vos, M. G., Tribuhl, S. V., and Clausen, L. A. W. 2010. Between-year variability in the mixing of North Sea herring spawning components leads to pronounced variation in the composition of the catch. – ICES Journal of Marine Science, 67: 885–896. North Sea herring (Clupea harengus) are managed as a single stock, but maintaining a diversity of spawning components is considered important. However, the total catch from each of these components cannot be estimated easily because the components mix during the summer feeding season. The spawning origin of herring is determined from patterns in the microstructure of the otolith core, from samples taken in the central and northern North Sea during summer of 2004–2007. The annual catch composition of Dutch vessels is determined within a statistical framework that takes account of the spatial patterns in mixing of spawning components and the classification success of the method. Mixing of components varied between years, with steep latitudinal gradients in compositions in some years, resulting in pronounced between-year differences in estimated catch compositions. Differences in lengths-at-age between spawning components, in particular of the 2000 year class, may have caused the observed between-year changes in mixing of components. Our results indicate that estimates of compositions change when assumptions of perfect spatial mixing and perfect classification are relaxed, and can be uncertain in particular as a result of misclassifications, and that it may not be appropriate to assume that ratios between components are constant through time.

Summary • The relative frequencies of functional traits of plant species show notable spatial variation, which is often related to environmental factors. Pollination type (insect-, wind- or self-pollination) is a critical trait for plant reproduction and provision of ecosystem services. • Here, we mapped the distribution of pollination types across Germany by combining databases on plant distribution and plant pollination types. Applying a new method, we modelled the composition of pollination types using a set of 12 environmental variables as predictors within a Bayesian framework which allows for the analysis of compositional data in the presence of spatial autocorrelation. • A clear biogeographical pattern in the distribution of pollination types was revealed which was adequately captured by our model. The most striking relationship was a relative increase in insect-pollination and a corresponding decrease of selfing with increasing altitude. Further important factors were wind speed, geology and land use. • We present a powerful tool to analyse the distribution patterns of plant functional types such as pollination types and their relationship with environmental parameters in a spatially explicit framework.

Given the poor status of the European eel (Anguilla anguilla) population, good assessments are essential to optimise recovery measures. Quantifying eel stock size is challenging given the fractal nature of the distribution of eels, particularly in The Netherlands with its dense interconnected network of drainage ditches, rivers and lakes. Dynamic demographic models as used by others are inappropriate in this delta with a demand for regional information on stock size. We therefore estimated the standing eel stock biomass for all freshwater water bodies, using fish monitoring data collected under the Water Framework Directive and a static GIS approach. Density data were extrapolated to total biomass estimates using GIS data concerning water type, surface area and bank length, and biological parameters obtained from biological data. The analysis yielded density and biomass estimates of the total eel and silver eel stock, with most silver eel biomass being confined to a few coastal regions. The main conclusion is that over half of the Dutch eel biomass is found in the small, regionally managed waters, revealing a crude underestimation of the eel biomass in the 2009 Dutch Eel Management Plan. The silver eel biomass estimate presented here is two to three times higher than previous estimates. Providing spatial information on eel biomass will aid in prioritising management measures to reduce anthropogenic mortality.