63 resultados para Cladocerans. Cyanobacteria. Cyanotoxins. Population growth rate. Reproductive parameters. Paralysis of movements. Chronic toxicity bioassays

em CentAUR: Central Archive University of Reading - UK


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1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

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The concept of an organism's niche is central to ecological theory, but an operational definition is needed that allows both its experimental delineation and interpretation of field distributions of the species. Here we use population growth rate (hereafter, pgr) to de. ne the niche as the set of points in niche space where pgr. 0. If there are just two axes to the niche space, their relationship to pgr can be pictured as a contour map in which pgr varies along the axes in the same way that the height of land above sea level varies with latitude and longitude. In laboratory experiments we measured the pgr of Daphnia magna over a grid of values of pH and Ca2+, and so defined its "laboratory niche'' in pH-Ca2+ space. The position of the laboratory niche boundary suggests that population persistence is only possible above 0.5 mg Ca2+/L and between pH 5.75 and pH 9, though more Ca2+ is needed at lower pH values. To see how well the measured niche predicts the field distribution of D. magna, we examined relevant field data from 422 sites in England and Wales. Of the 58 colonized water bodies, 56 lay within the laboratory niche. Very few of the sites near the niche boundary were colonized, probably because pgr there is so low that populations are vulnerable to extinction by other factors. Our study shows how the niche can be quantified and used to predict field distributions successfully.

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Forecasting the effects of stressors on the dynamics of natural populations requires assessment of the joint effects of a stressor and population density on the population response. The effects can be depicted as a contour map in which the population response, here assessed by Population growth rate, varies with stress and density in the same way that the height of land above sea level varies with latitude and longitude. We present the first complete map of this type using as our model Folsomia candida exposed to five different concentrations of the widespread anthelmintic veterinary medicine ivermectin in replicated microcosm experiments lasting 49 days. The concentrations of ivermectin in yeast were 0.0, 6.8 28.83 66.4 and 210.0 mg/L wet weight. Increasing density and chemical concentration both significantly reduced the population growth rate of Folsomia candida, in part through effects on food consumption and fecundity. The interaction between density and ivermectin concentration was "less-than-additive," implying that at high density populations were able to compensate for the effects of the chemical. This result demonstrates that regulatory protocols carried out at low density (as in most past experiments) may seriously overestimate effects in the field, where densities are locally high and populations are resource limited (e.g., in feces of livestock treated with ivermectin).

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Results of previous laboratory studies suggest that high population density often buffers the effects of chemical stressors that predominately increase mortality. Mortality stressors act to release more resources for the survivors and, therefore, produce less-than-additive effects. By contrast, growth stressors are expected to have opposite results or more-than-additive effects. We investigated the effects of a growth inhibitor (lufenuron) on larval growth and survival of Chironomus riparius and examined its joint effects with density on population growth rate (PGR). Exposure to 60 mu g/kg sediment or greater inhibited larval growth, and exposure to 88 mu g/kg or greater often resulted in mortality before reaching emergence. The effects of lufenuron, however, differed with population density. At 88 mu g/kg, mortalities and, to a lesser extent, reduced fecundity resulted in a reduction in PGR at low density. Conversely, when populations were initiated at high density, PGR was similar to that of controls, because the few survivors reached maturity sooner and started producing offspring earlier. The effect of density as a growth stressor therefore was stronger than the effect of lufenuron, which had effects similar to those of a mortality stressor and produced less-than-additive effects. Longterm studies under field conditions, however, are needed before less-than-additive effects are considered to be the norm.

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1. Chemical effects on organisms are typically assessed using individual-level endpoints or sometimes population growth rate (PGR), but such measurements are generally made at low population densities. In contrast most natural populations are subject to density dependence and fluctuate around the environmental carrying capacity as a result of individual competition for resources. As ecotoxicology aims to make reliable population projections of chemical impacts in the field, an understanding of how high-density or resource-limited populations respond to environmental chemicals is essential. 2. Our objective was to determine the joint effects of population density and chemical stress on the life history and PGR of an important ecotoxicological indicator species, Chironomus riparius, under controlled laboratory conditions. Populations were fed the same ration but initiated at different densities and exposed to a solvent control and three concentrations of C-14-cypermethrin in a sediment-water test system for 67 days at 20 +/- 1 degreesC. 3. Density had a negative effect on all the measured life-history traits, and PGR declined with increasing density in the controls. Exposure to C-14-cypermethrin had a direct negative effect on juvenile survival, presumably within the first 24 h because the chemical rapidly dissipated from the water column. Reductions in the initial larval densities resulted in an increase in the available resources for the survivors. Subsequently, exposed populations emerged sooner and started producing offspring earlier than the controls. C-14-cypermethrin had no effect on estimated fecundity and adult body weight but interacted with density to reduce the time to first emergence and first reproduction. As a result, PGR increased with cypermethrin concentration when populations were initiated at high densities. 4. Synthesis and applications. The results showed that the effects of C-14-cypermethrin were buffered at high density, so that the joint effects of density and chemical stress on PGR were less than additive. Low levels of chemical stressors may increase carrying capacity by reducing juvenile competition for resources. More and perhaps fitter adults may be produced, similar to the effects of predators and culling; however, toxicant exposure may result in survivors that are less tolerant to changing conditions. If less than additive effects are typical in the field, standard regulatory tests carried out at low density may overestimate the effects of environmental chemicals. Further studies over a wide range of chemical stressors and organisms with contrasting life histories are needed to make general recommendations.

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Despite long-standing interest in the forms and mechanisms of density dependence, these are still imperfectly understood. However, in a constant environment an increase in density must reduce per capita resource availability, which in turn leads to reduced survival, fecundity and somatic growth rate. Here we report two population experiments examining the density dependent responses under controlled conditions of an important indicator species, Chironomus riparius. The first experiment was run for 35 weeks and was started at low density with replicate populations being fed three different rations. Increased ration reduced generation time and increased population growth rate (pgr) but had no effect on survival, fecundity and female body weight in the first generation. In the second generation there was a six-fold increase in generation time, presumably due to the greatly reduced per capita resource availability as the estimated initial densities of the second generation were 300 times greater than the first. Juvenile survival to emergence, fecundity, adult body weight and pgr declined by 90%, 75%, 35% and 99%, respectively. These large between-generation effects may have obscured the effects of the threefold variation in ration, as only survival to emergence significantly increased with ration in the second generation. These results suggest that some chironomid larvae survive a reduction in resource availability by growing more slowly. In the ephemeral habitats sometimes occupied by C. riparius, the effects of population density may depend crucially on the longevity of the environment. A second experiment was therefore performed to measure pgr from six different starting densities over an eight-week period. The relationship between pgr and density was concave, viewed from above. At densities above 16 larvae per cm(2), less than 1% of the population emerged and no offspring were produced. Under the conditions of experiment 2 - an 8-week habitat lifespan carrying capacity was estimated as 8 larvae per cm(2).

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Erythrina variegata grown from seeds showed a great deal of variation with respect to height, diameter, density of wood and dry matter production. Statistical analysis showed that the density of wood produced by any plant was not related to its growth rate, but dry matter production was associated with plant growth rate (height and diameter) that could lead to overall increased dry matter or biomass production.

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The present study investigates the growth of error in baroclinic waves. It is found that stable or neutral waves are particularly sensitive to errors in the initial condition. Short stable waves are mainly sensitive to phase errors and the ultra long waves to amplitude errors. Analysis simulation experiments have indicated that the amplitudes of the very long waves become usually too small in the free atmosphere, due to the sparse and very irregular distribution of upper air observations. This also applies to the four-dimensional data assimilation experiments, since the amplitudes of the very long waves are usually underpredicted. The numerical experiments reported here show that if the very long waves have these kinds of amplitude errors in the upper troposphere or lower stratosphere the error is rapidly propagated (within a day or two) to the surface and to the lower troposphere.

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In a recent paper of Feng and Sidorov they show that for β∈(1,(1+5√)/2) the set of β-expansions grows exponentially for every x∈(0,1/(β−1)). In this paper we study this growth rate further. We also consider the set of β-expansions from a dimension theory perspective.

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1. Bees are one of the most important groups of pollinators in the temperate zone. Although heavy metal pollution is recognised to be a problem affecting large parts of the European Union, we currently lack insights into the effects of heavy metals on wild bee survival and reproduction. 2. We investigated the impact of heavy metal pollution on the wild bee Osmia rufa (Hymenoptera: Megachilidae) by comparing their survival, reproduction and population dynamics along two independent gradients of heavy metal pollution, one in Poland and the other in the United Kingdom. We used trap nests to evaluate the response of fitness and survival parameters of O. rufa. To quantify the levels of pollution, we directly measured the heavy metal concentration in provisions collected by O. rufa. 3. We found that with increasing heavy metal concentration, there was a steady decrease in number of brood cells constructed by females and an increase in the proportion of dead offspring. In the most polluted site, there were typically 3–4 cells per female with 50–60% dead offspring, whereas in unpolluted sites there were 8 to 10 cells per female and only 10–30% dead offspring. Moreover, the bee population growth rate (R0) decreased along the heavy metal pollution gradients. In unpolluted sites, R0 was above 1, whereas in contaminated sites, the values tended to be below 1. 4. Our findings reveal a negative relationship between heavy metal pollution and several fitness parameters of the wild bee O. rufa, and highlight a mechanism whereby the detrimental effects of heavy metal pollution may severely impact wild bee communities.

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The non-steroidal anti-inflammatory drug (NSAID) ibuprofen (IB) is a widely used pharmaceutical that can be found in several freshwater ecosystems. Acute toxicity studies with Daphnia magna suggest that the 48 h EC50 (immobilisation) is 10-100 mg IB l(-1). However, there are currently no chronic IB toxicity dataon arthropod populations, and the aquatic life impacts of such analgesic drugs are still undefined. We performed a 14-day exposure of D. magna to IB as a model compound (concentration range: 0, 20, 40 and 80 mg IB l(-1)) measuring chronic effects on life history traits and population performance. Population growth rate was significantly reduced at all IB concentrations, although survival was only affected at 80 mg IB l(-1). Reproduction, however, was affected at lower concentrations of IB (14-day EC50 of 13.4 mg IB l(-1)), and was completely inhibited at the highest test concentration. The results from this study indicate that the long-term crustacean population consequences of a chronic IB exposure at environmentally realistic concentrations (ng l(-1) to mu g l(-1)) would most likely be of minor importance. We discuss our results in relation to recent genomic studies, which suggest that the potential mechanism of toxicity in Daphnia is similar to the mode of action in mammals, where IB inhibits eicosanoid biosynthesis. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

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It is generally acknowledged that population-level assessments provide,I better measure of response to toxicants than assessments of individual-level effects. population-level assessments generally require the use of models to integrate potentially complex data about the effects of toxicants on life-history traits, and to provide a relevant measure of ecological impact. Building on excellent earlier reviews we here briefly outline the modelling options in population-level risk assessment. Modelling is used to calculate population endpoints from available data, which is often about Individual life histories, the ways that individuals interact with each other, the environment and other species, and the ways individuals are affected by pesticides. As population endpoints, we recommend the use of population abundance, population growth rate, and the chance of population persistence. We recommend two types of model: simple life-history models distinguishing two life-history stages, juveniles and adults; and spatially-explicit individual-based landscape models. Life-history models are very quick to set up and run, and they provide a great deal or insight. At the other extreme, individual-based landscape models provide the greatest verisimilitude, albeit at the cost of greatly increased complexity. We conclude with a discussion of the cations of the severe problems of parameterising models.

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Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

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The potential reproductive value of arbuscular mycorrhizal fungi (Gloinus intraradices and Glomus invermaium), root pathogenic fungi (Rhizoctonia solani and Fusarium culmorum) and saprotrophic fungi (Penicillium hordei and Trichoderma harzianum) were examined for the collembolans Folsomia candida Willem and Folsomia fimetaria L. Dried baker's yeast (Saccharomyces cerevisiae) was used as a reference standard food in laboratory cultures. Collembolan performance was determined as final size, fecundity and population growth rate after when fed the fungal food sources for 31 days. The mycorrhizal fungi gave the least growth and fecundity compared with the other fungi, but G. intraradices gave good fecundity for F. candida. In terms of growth, Baker's yeast was a high-quality food for both adults and juveniles of both species, but it was a poorer food in terms of fecundity of F. candida. Preference of the fungi in all possible pairwise combinations showed that although F. fimetaria did not perform well on Glomus spp. and F. candida did not grow well on Glomus spp. their preference for these fungi did not reflect this. The highest fecundity was seen with the root pathogen F. culmorum. Different quality indicators such as the C:N ratio of the fungal food sources as well as other biological parameters are discussed in relation to their reproductive value and Collembola preferential feeding. (c) 2007 Elsevier Ltd. All rights reserved.

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Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.