The ecological niche of Daphnia magna characterized using population growth rate

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.

The use of image analysis to estimate population growth rate in Daphnia magna

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.

Population growth rate and carrying capacity for springtails Folsomia candida exposed to ivermectin

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).

Joint effects of density and a growth inhibitor on the life history and population growth rate of the midge Chironomus riparius

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.

Estimation of population growth or decline in genetically monitored populations

This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.

The joint effects of larval density and C-14-cypermethrin on the life history and population growth rate of the midge Chironomus riparius

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.

The influence of larval density, food availability and habitat longevity on the life history and population growth rate of the midge Chironomus riparius

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).

The determinants of local population growth: a study of Oxfordshire in the nineteenth century

This paper presents a new econometric model for analysing population growth at the village and town level. It develops and applies a theory of the equilibrium distribution of population over space. The theory emphasises geographical fundamentals, such as rivers as transport corridors, and soil types that govern agricultural specialisation; also institutional factors such as town government, market charters and the concentration of land ownership. Nineteenth century Oxfordshire is used as a case study, but the method can also be applied at a multi-county and national level. The results show that the development of railways in nineteenth-century Oxfordshire accelerated a long-term shake-out in the market system, whereby rural markets disappeared and urban markets grew. This shake-out had significant implications for population growth at the local level.

Survival, reproduction and population growth of the bee pollinator, Osmia rufa (Hymenoptera: Megachilidae), along gradients of heavy metal pollution

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.

Managing threatened species – the ecological toolbox, evolutionary theory and the declining-population paradigm

1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviourbased models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley’s declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

The effects of spatial and temporal heterogeneity on the population dynamics of four animal species in a Danish landscape

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.

The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation

The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.