Critical threshold size for overwintering sandeels (<Emphasis Type="Italic">Ammodytes marinus</Emphasis>)

Several ecologically and commercially important fish species spend the winter in a state of minimum feeding activity and at lower risk of predation. To enable this overwintering behaviour, energetic reserves are generated prior to winter to support winter metabolism. Maintenance metabolism in fish scales with body size and increases with temperature, and the two factors together determine a critical threshold size for passive overwintering below which the organism is unlikely to survive without feeding. This is because the energetic cost of metabolism exceeds maximum energy reserves. In the present study, we estimated the energetic cost of overwintering from a bioenergetic model. The model was parameterised using respirometry-based measurements of standard metabolic rate in buried A. tobianus (a close relative to A. marinus) at temperatures from 5.3 to 18.3°C and validated with two independent long-term overwintering experiments. Maximum attainable energy reserves were estimated from published data on A. marinus in the North Sea. The critical threshold size in terms of length (L _th) for A. marinus in the North Sea was estimated to be 9.5 cm. We then investigated two general predictions: (1) Fish smaller than L _th display winter feeding activity, and (2) size at maturation of iteroparous species is larger than L _th to ensure sufficient energy reserves to accommodate both the metabolic cost of passive overwintering and reproductive investments. Both predictions were found to be consistent with data on size at maturation and total body energy in December and February.     

Modeling fecundity in birds: Conceptual overview, current models, and considerations for future developments

Fecundity is fundamental to the fitness, population dynamics, conservation, and management of birds. For all the efforts made to measure fecundity or its surrogates over the past century of avian research, it is still mismeasured, misrepresented, and misunderstood. Fundamentally, these problems arise because of partial observability of underlying processes such as renesting, multiple brooding, and temporary emigration. Over the last several decades, various analytical approaches have been developed to estimate fecundity from incomplete and biased data. These, include scalar arithmetic formulae, partial differential equations, individual-based simulations, and Markov chain methodology. In this paper, we: (1) identify component processes of avian reproduction; (2) review existing methods for modeling fecundity; (3) place these diverse models under a common conceptual framework; (4) describe the parameterization, validation, and limitations of such models; and (5) point out future considerations and challenges in the application of fecundity models. We hope this synthesis of existing literature will help direct researchers toward the most appropriate methods to assess avian reproductive success for answering questions in evolutionary ecology, natural history, population dynamics, reproductive toxicology, and management.     

Radiocarbon in food: a non-problem of health effects

Recently it has come to our attention that a paper was published in this journal entitled “recycling greenhouse gas fossil fuel emissions into low radiocarbon food products to reduce human genetic damage” (Williams in Environ Chem Lett 5:197–202, 2007). In this article, it is argued that food grown in a greenhouse is healthier for people, when the greenhouse is fertilised with CO₂ prepared from fossil fuels. In this comment, however, we argue that the effect on human health is completely negligible.     

Comparison of the SidePak personal monitor with the Aerosol Particle Sizer (APS)

The aim of this study was to compare the performance of the TSI Aerodynamic Particle Sizer (APS) and the TSI portable photometer SidePak to measure airborne oil mist particulate matter (PM) with aerodynamic diameters below 10 μm, 2.5 μm and 1 μm (PM(10), PM(2.5) and PM(1)). Three SidePaks each fitted with either a PM(10), PM(2.5) or a PM(1) impactor and an APS were run side by side in a controlled chamber. Oil mist from two different mineral oils and two different drilling fluid systems commonly used in offshore drilling technologies were generated using a nebulizer. Compared to the APS, the SidePaks overestimated the concentration of PM(10) and PM(2.5) by one order of magnitude and PM(1) concentrations by two orders of magnitude after exposure to oil mist for 3.3-6.5 min at concentrations ranging from 0.003 to 18.1 mg m(-3) for PM(10), 0.002 to 3.96 mg m(-3) for PM(2.5) and 0.001 to 0.418 mg m(-3) for PM(1) (as measured by the APS). In a second experiment a SidePak monitor previously exposed to oil mist overestimated PM(10) concentrations by 27% compared to measurements from another SidePak never exposed to oil mist. This could be a result of condensation of oil mist droplets in the optical system of the SidePak. The SidePak is a very useful instrument for personal monitoring in occupational hygiene due to its light weight and quiet pump. However, it may not be suitable for the measurement of particle concentrations from oil mist.     

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 3: alternatives to systemic insecticides

Environmental Science and Pollution Research - Over-reliance on pesticides for pest control is inflicting serious damage to the environmental services that underpin agricultural productivity. The...     

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides

Environmental Science and Pollution Research -     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Stages in Dutch regional policy: 1945–1984

This paper discusses the major developments in regional policy in the Netherlands by relating the policy instruments and locations to stages in the socio‐economic and political development of the Netherlands from 1945 onwards. It concludes that, at present, the spatial dimension of economic policy has lost importance, and the support for peripheral regions is restricted.     

Reintroduction of eelgrass ( Zostera marina ) in the Dutch Wadden Sea; Review of research and suggestions for management measures

Eelgras (Zostera marina L.) in the Dutch Wadden Sea historically covered an area varying from 65–150 km² in the eulittoral as well as the sublittoral zones. At present, this area comprises less than 1 km² eulittoral eelgrass stands, with an associated decrease in habitat diversity. The causes for this decline are presumably connected with the ‘wasting disease’ and the closure of the former Zuiderzee in the early 1930s resulting in increased tidal range and increased currents. After a slight recovery of the eelgrass populations on the intertidal flats a definite decline started in the early 1970s, possibly connected to increased turbidity. The present water quality and turbidity do not negatively influence eelgrass growth up to a depth of at least 0.6m below Mean Sea Level. Based on mesocosm experiments and field experiments it is concluded that re-establishment of eelgrass should be possible in sheltered bays and on unexposed tidal falts. The most suitable depths for a reintroduction are those between 0 and 20–40 cm below mean sea level.     

Including adaptation costs and climate change damages in evaluating post-2012 burden-sharing regimes

Many studies have been published to evaluate the consequences of different post-2012 emission allocation regimes on regional mitigation costs. This paper goes one step further and evaluates not only mitigation costs, but also adaptation costs and climate change damages. Three post-2012 emission allocation regimes (Contraction & Convergence, Multistage and Common but differentiated convergence) and two climate targets (2°C and 3°C above the pre-industrial level) are considered. This explorative analysis shows that including these other cost categories could lead to different perspectives on the outcomes of allocation regimes. Up to 2050, the poorest regions have negative mitigation costs under all allocation regimes considered, as they benefit from emission trading. However, these regions also suffer from the most severe climate impacts. As such, the financial flows due to emission trading from developed to developing countries created under these allocation regimes could also be interpreted as compensation of climate change damages and adaptation costs. In the longer run, the sum of climate change damages, adaptation costs and mitigation costs are the highest in the poorest regions of Sub-Saharan Africa and South Asia, for both climate targets and practically all emission allocation regimes.