Evaluating the importance of demographic connectivity in a marine metapopulation

Recently researchers have gone to great lengths to measure marine metapopulation connectivity via tagging, genetic, and trace-elemental fingerprinting studies. These empirical estimates of larval dispersal are key to assessing the significance of metapopulation connectivity within a demographic context, but the life-history data required to do this are rarely available. To evaluate the demographic consequences of connectivity we constructed seasonal, size-structured metapopulation matrix models for two species of mytilid mussel in San Diego County, California, USA. The self-recruitment and larval exchange terms were produced from a time series of realized connectivities derived from trace-elemental fingerprinting of larval shells during spring and fall from 2003 to 2008. Both species exhibited a strong seasonal pattern of southward movement of recruits in spring and northward movement in fall. Growth and mortality terms were estimated using mark-recapture data from representative sites for each species and subpopulation, and literature estimates of juvenile mortality. Fecundity terms were estimated using county-wide settlement data from 2006-2008; these data reveal peak reproduction and recruitment in fall for Mytilus californianus, and spring for M. galloprovincialis. Elasticity and life-stage simulation analyses were employed to identify the season- and subpopulation-specific vital rates and connectivity terms to which the metapopulation growth rate (lambda) was most sensitive. For both species, metapopulation growth was most sensitive to proportional changes in adult fecundity, survival and growth of juvenile stages, and population connectivity, in order of importance, but relatively insensitive to adult growth or survival. The metapopulation concept was deemed appropriate for both Mytilus species as exchange between the subpopulations was necessary for subpopulation persistence. However, highest metapopulation growth occurred in years when a greater proportion of recruits was retained within the predominant source subpopulation. Despite differences in habitat and planktonic duration, both species exhibited similar overall metapopulation dynamics with respect to key life stages and processes. However, different peak reproductive periods in an environment of seasonal current reversals led to different regional (subpopulation) contributions to metapopulation maintenance; this result emphasizes the importance of connectivity analysis for spatial management of coastal resources.     

Fiscal spending and the environment: Theory and empirics

During economic crises, governments often increase fiscal spending to stimulate the economy. While the fiscal spending surge may be temporary, spending composition is often altered in favor of expenditures on social programs and other public goods which may persist over time. We model and measure the impact of fiscal spending patterns on the environment. The model predicts that a reallocation of government spending composition towards social and public goods reduces pollution. However, increasing total government spending without altering its composition does not reduce pollution. We empirically test these predictions for air and water pollutants showing that they are fully supported.     

Intra- and interannual variability in the larval fish assemblage off Gran Canaria (Canary Islands) over 2005–2007

The present study provides the longest and most intensive plankton and larval fish seasonal variability analysis in the Canary Islands and forms a basis for understanding life cycle scheduling and interactions among species, as well as the potential variability in transport processes of early life stages. Larval fish assemblages were studied weekly at Gran Canaria Island, Canary Islands, from January 2005 to June 2007, which represented two contrasting hydrological and biological periods. The former year was characterized by lower temperature and salinity that increased through 2006 and 2007. In contrast, chlorophyll concentration and mesozooplankton biomass decreased through the same period, especially when only the late winter bloom period was evaluated. However, ichthyoplankton abundance did not exhibit any clear pattern, as larger values were observed during 2006. The larval fish community of this oceanic island, located near the NW African upwelling, was composed of both neritic and oceanic taxa. Two families accounted for almost half of the collected larvae: Clupeidae (21.9%) and Myctophidae (20.5%). Although total larval concentration did not exhibit any seasonal peak linked to changes in zooplankton, the ichthyoplankton composition gradually changed during the year due to the high diversity and extended spawning periods of the fish species represented in samples. “Winter” and “summer” larval assemblages were identified, corresponding to the mixing and stratification periods of the water column, respectively. These assemblages were characterized by changes in the contribution of the most abundant annual taxa (Sardinella aurita, Cyclothone braueri, Ceratoscopelus spp. and Gobids) and by the presence of larvae of winter (Pagellus bogaraveo, Pomacentridae sp1) or summer spawners (Pomacentridae sp2, Trachinus draco, Arnoglossus thori, Tetraodontidae sp1). Upwelling filaments shed from the NW African coast reached the sampling area three times during this study, but changes in the local larval community were only detected in August 2005.     

Information-theoretic approaches to statistical analysis in behavioural ecology: an introduction

Scientific thinking may require the consideration of multiple hypotheses, which often call for complex statistical models at the level of data analysis. The aim of this introduction is to provide a brief overview on how competing hypotheses are evaluated statistically in behavioural ecological studies and to offer potentially fruitful avenues for future methodological developments. Complex models have traditionally been treated by model selection approaches using threshold-based removal of terms, i.e. stepwise selection. A recently introduced method for model selection applies an information-theoretic (IT) approach, which simultaneously evaluates hypotheses by balancing between model complexity and goodness of fit. The IT method has been increasingly propagated in the field of ecology, while a literature survey shows that its spread in behavioural ecology has been much slower, and model simplification using stepwise selection is still more widespread than IT-based model selection. Why has the use of IT methods in behavioural ecology lagged behind other disciplines? This special issue examines the suitability of the IT method for analysing data with multiple predictors, which researchers encounter in our field. The volume brings together different viewpoints to aid behavioural ecologists in understanding the method, with the hope of enhancing the statistical integration of our discipline.     

Leaf ontogeny interacts with Bt modification to affect innate resistance in GM aspens

Bioassays with a non-target slug (Deroceras spp.) and chemical analyses were conducted using leaf tissue from already existing genetically modified insect-resistant aspen trees to examine whether genetic modifications to produce Bacillus thuringiensis (Bt) toxins could affect plant phytochemistry, which in turn might influence plant–herbivore interactions. Three major patterns emerged. First, two independent modifications for Bt resistance affected the phytochemical profiles of leaves such that both were different from the isogenic wild-type (Wt) control leaves, but also different from each other. Among the contributors to these differences are substances with a presumed involvement in resistance, such as salicortin and soluble condensed tannins. Second, bioassays with one Bt line suggest that the modification somehow affected innate resistance (“Innate” is used here in opposition to the “acquired” Bt resistance) in ways such that slugs preferred Bt over Wt leaves. Third, the preference test suggests that the innate resistance in Bt relative to Wt plants may not be uniformly expressed throughout the whole plant and that leaf ontogeny interacts with the modification to affect resistance. This was manifested through an ontogenetic determined increase in leaf consumption that was more than four times higher in Bt compared to Wt leaves. Our result are of principal importance, as these indicate that genetic modifications can affect innate resistance and thus non-target herbivores in ways that may have commercial and/or environmental consequences. The finding of a modification–ontogeny interaction effect on innate resistance may be especially important in assessments of GM plants with a long lifespan such as trees.     

Element determination in environmental samples using Z-GFAAS with variable magnetic field

Electrothermal atomic absorption spectrometry methods with Zeeman effect background correction (Z-GFAAS) for determination of As, Sb, Se, Ag, Cd, Pb, Cu, Fe, Zn, Cr, and Ni in water and sludge samples were developed. The measurements using Z-GFAAS and variable magnetic field at the three-field dynamic mode permit the sensitivity adaptation for higher analytical concentrations. Calibration ranges were expanded over two orders of magnitude within one measurement run by the applying three-field dynamic mode of this correction system. There are presented calibration data, furnace programs, modifiers, and microwave digestion programs of the obviously monitored elements in the environmental samples. Very low detection limits (3σ criterion) were obtained. Quality assurance was checked by the suitable CRM. The study brings simultaneous determination of the samples with different element concentration range and different sample matrixes, as an important application information for an analyst working in the area of the eco-analytical research.     

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10?cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.     

The development of probabilistic models to estimate accident risk (due to runway overrun and landing undershoot) applicable to the design and construction of runway safety areas

The risks of landing overrun (LDOR – LanDing OverRun), Take-off Overrun (TOOR – Take-Off OverRun) and landing undershoot (LDUS – LanDing UnderShoot) are dependent on multiple factors related to operating conditions. These include wind, runway surface conditions, landing or take-off distances required, the presence of obstacles, runway distance available, the existence and dimensions of runway safety areas.In this paper we propose risk models for runway overrun and landing undershoot, using a probabilistic approach. These models are supported by historical data on accidents in the area around the runway and will enable us to determine if the risk level is acceptable or whether action must be taken to mitigate such risks at a given airport. Furthermore, these models permit comparison of the results of different risk mitigation actions in terms of operational risk and safety.The principal advantage of this method is the high quality results obtained for a limited investment in terms of time, computing power and data. As such the method is extremely practical and easy to apply in aerodrome planning, development and operation.