A substantial proportion of the global land surface is used for agricultural production. Agricultural land serves multiple societal purposes; it provides food, fuel and fibre and also acts as habitat for organisms and supports the services they provide. Biodiversity conservation and food production need to be balanced: production needs to be sustainable, while conservation cannot be totally at the expense of crop yield. To identify the benefits (in terms of biodiversity conservation) and costs (in terms of reduction in yields) of agricultural management, we examined the relationship between crop yield and abundance and species density of important taxa in winter cereal fields on both organic and conventional farms in lowland England. Of eight species groups examined, five (farmland plants, bumblebees, butterflies, solitary bees and epigeal arthropods) were negatively associated with crop yield, but the shape of this relationship varied between taxa. It was linear for the abundance of bumblebees and species density of butterflies, concave up for the abundance of epigeal arthropods and butterflies and concave down for species density of plants and bumblebees. Grain production per unit area was 54% lower in organic compared with conventional fields. When controlling for yield, diversity of bumblebees, butterflies, hoverflies and epigeal arthropods did not differ between farming systems, indicating that observed differences in biodiversity between organic and conventional fields are explained by lower yields in organic fields and not by different management practices per se. Only percentage cover and species density of plants were increased by organic field management after controlling for yield. The abundance of solitary wild bees and hoverflies was increased in landscapes with high amount of organic land. Synthesis and applications. Our results indicate that considerable gains in biodiversity require roughly proportionate reductions in yield in highly productive agricultural systems. They suggest that conservation efforts may be more cost effective in low-productivity agricultural systems or on non-agricultural land. In less productive agricultural landscapes, biodiversity benefit can be gained by concentrating organic farms into hotspots without a commensurate reduction in yield.© 2013 British Ecological Society.
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Aim: As the global climate is changing rapidly, there is a need to make conservation decisions to facilitate species' persistence under climate change. Models employed to make predictions regarding the impacts of climate change on species' distributions, and ultimately persistence, typically assume that interannual variability in environmental conditions is independent between years. However, the colour of environmental noise has been shown to affect extinction risk in populations occupying spatially static environments, and should therefore affect persistence during climate change. This study aims to investigate the importance of noise colour for extinction risk during climate-induced range shifts. Methods: We use a spatially explicit coupled map lattice with a latitudinal gradient in climatic suitability, together with time series of environmental noise, to simulate periods of directional climate change and investigate the effects of noise colour on extinction risk and range size. Results: Extinction risk increases with reddening of the environmental noise, and this effect is particularly pronounced over short time frames when climate change is rapid. Main conclusions: Given that management decisions are typically made over such short time frames, and the rapid rates of climate change currently being experienced, we highlight the importance of incorporating realistic time series of environmental noise into models used for conservation planning under climate change.© 2013 Blackwell Publishing Ltd.
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Including predictors in species distribution models at inappropriate spatial scales can decrease the variance explained, add residual spatial autocorrelation (RSA) and lead to the wrong conclusions. Some studies have measured predictors within different buffer sizes (scales) around sample locations, regressed each predictor against the response at each scale and selected the scale with the best model fit as the appropriate scale for this predictor. However, a predictor can influence a species at several scales or show several scales with good model fit due to a bias caused by RSA. This makes the evaluation of all scales with good model fit necessary. With potentially several scales per predictor and multiple predictors to evaluate, the number of predictors can be large relative to the number of data points, potentially impeding variable selection with traditional statistical techniques, such as logistic regression. We trialled a variable selection process using the random forest algorithm, which allows the simultaneous evaluation of several scales of multiple predictors. Using simulated responses, we compared the performance of models resulting from this approach with models using the known predictors at arbitrary and at the known spatial scales. We also apply the proposed approach to a real data set of curlew (Numenius arquata). AIC, AUC and Naglekerke's pseudo R of the models resulting from the proposed variable selection were often very similar to the models with the known predictors at known spatial scales. Only two of nine models required the addition of spatial eigenvectors to account for RSA. Arbitrary scale models always required the addition of spatial eigenvectors. 75% (50-100%) of the known predictors were selected at scales similar to the known scale (within 3 km). In the curlew model, predictors at large, medium and small spatial scales were selected, suggesting that for appropriate landscape-scale models multiple scales need to be evaluated. The proposed approach selected several of the correct predictors at appropriate spatial scales out of 544 possible predictors. Thus, it facilitates the evaluation of multiple spatial scales of multiple predictors against each other in landscape-scale models.© 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.
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Residential landscapes with private gardens are major land covers in cities and their sustainable management is paramount for achieving a resilient urban future. Here we focus on the value of residential ecosystems for biodiversity conservation and explore the social and ecological factors that influence wildlife-friendly garden management. Using a stratified sampling design across the UK city of Leeds, this interdisciplinary study develops and applies a mixed method approach, including questionnaires, interviews and ecological surveys across multiple spatial scales. We quantify wildlife-friendly gardening using two measures: (i) the number of wildlife-friendly features within gardens (the wildlife resources index, WRI); and (ii) the frequency of winter bird feeding. Wildlife-friendly gardening is influenced by a combination of garden characteristics and management intensity, householder demographics, wider environmental activity and landscape context. Residents reveal a range of motivations for wildlife-friendly gardening, notably personal well-being and a moral responsibility to nature. Respondents expressed a duty to maintain neighbourhood standards, revealing that social norms are a considerable barrier to uptake of wildlife-friendly activities, but also provide an opportunity where neighbour mimicry results in diffusion of wildlife-friendly practices. Community-driven initiatives that engage, educate and empower residents are better placed to encourage wildlife-friendly gardening than top-down financial incentives.© 2012 Elsevier B.V.
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The world is experiencing significant, largely anthropogenically induced, environmental change. This will impact on the biological world and we need to be able to forecast its effects. In order to produce such forecasts, ecology needs to become more predictive-to develop the ability to understand how ecological systems will behave in future, changed, conditions. Further development of process-based models is required to allow such predictions to be made. Critical to the development of such models will be achieving a balance between the brute-force approach that naively attempts to include everything, and over simplification that throws out important heterogeneities at various levels. Central to this will be the recognition that individuals are the elementary particles of all ecological systems. As such it will be necessary to understand the effect of evolution on ecological systems, particularly when exposed to environmental change. However, insights from evolutionary biology will help the development of models even when data may be sparse. Process-based models are more common, and are used for forecasting, in other disciplines, e.g. climatology and molecular systems biology. Tools and techniques developed in these endeavours can be appropriated into ecological modelling, but it will also be necessary to develop the science of ecoinformatics along with approaches specific to ecological problems. The impetus for this effort should come from the demand coming from society to understand the effects of environmental change on the world and what might be performed to mitigate or adapt to them.© 2011 The Royal Society.
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In this paper we present a multi-disciplinary analysis of the potential impacts of undertaking similar environmental actions on multiple farms in a small geographic area, using organic farming as a proxy for a co-ordinated approach. Recent papers have called for more co-ordinated efforts between farmers in terms of their environmental actions, but there has been limited applied research demonstrating the environmental benefits or the economic and social implications to farmers of this approach. Comparative analysis of biodiversity, soil and water, and farm profitability were undertaken in England on 32 matched farms in areas of low and high organic farming concentration; qualitative interviews were also conducted with 48 farmers living in two of the eight areas. Findings demonstrate higher overall levels of biodiversity on organic farms (particularly in " hotspot" areas) but this was not universal across the species groups investigated. Higher water infiltration rates were found in organic grasslands, which could prove to be a useful measure to combat flooding. In terms of the technical efficiency of producing these environmental gains, conventional and organic farms in hotspot areas demonstrated equivalent efficiency from a financial perspective. Socio-cultural research identified the different amounts of trust farmers have in their neighbours, based in part on their performance as 'good farmers'. We discuss the neighbourhood effect with a multi-disciplinary approach and conclude that encouraging local farmer co-ordination can have clear environmental benefits without high economic cost, but must be undertaken with caution - specifically regarding the trade-offs between benefits, local geophysical and social characteristics, and assumptions made about inter-farmer trust.© 2011 Elsevier Ltd.
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Capsule The body condition of nestling Yellowhammers was negatively correlated with the amount of cereal grain in the diet. This supports the hypothesis that cereal grain is an inferior nestling food relative to invertebrates. Cereal grain is frequently provisioned to nestlings in a range of bunting species breeding on farmland, suggesting that invertebrates may be limiting in these habitats.© 2012 Copyright British Trust for Ornithology.
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Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro-organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade-offs, they give rise to covariation between dispersal and other life-history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life-history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.© 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.
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Environmental change continually perturbs populations from a stable state, leading to transient dynamics that can last multiple generations. Several long-term studies have reported changes in trait distributions along with demographic response to environmental change. Here we conducted an experimental study on soil mites and investigated the interaction between demography and an individual trait over a period of nonstationary dynamics. By following individual fates and body sizes at each life-history stage, we investigated how body size and population density influenced demographic rates. By comparing the ability of two alternative approaches, a matrix projection model and an integral projection model, we investigated whether consideration of trait-based demography enhances our ability to predict transient dynamics. By utilizing a prospective perturbation analysis, we addressed which stage-specific demographic or trait-transition rate had the greatest influence on population dynamics. Both body size and population density had important effects on most rates; however, these effects differed substantially among life-history stages. Considering the observed trait-demography relationships resulted in better predictions of a population's response to perturbations, which highlights the role of phenotypic plasticity in transient dynamics. Although the perturbation analyses provided comparable predictions of stage-specific elasticities between the matrix and integral projection models, the order of importance of the life-history stages differed between the two analyses. In conclusion, we demonstrate how a trait-based demographic approach provides further insight into transient population dynamics.© 2012 by The University of Chicago.
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The geographic distribution of life on Earth supports a general pattern of increase in biodiversity with increasing temperature. However, some previous analyses of the 540-million-year Phanerozoic fossil record found a contrary relationship, with paleodiversity declining when the planet warms. These contradictory findings are hard to reconcile theoretically.We analyze marine invertebrate biodiversity patterns for the Phanerozoic Eon while controlling for sampling effort. This control appears to reverse the temporal association between temperature and biodiversity, such that taxonomic richness increases, not decreases, with temperature. Increasing temperatures also predict extinction and origination rates, alongside other abiotic and biotic predictor variables. These results undermine previous reports of a negative biodiversity-temperature relationship through time, which we attribute to paleontological sampling biases. Our findings suggest a convergence of global scale macroevolutionary and macroecological patterns for the biodiversity-temperature relationship.
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Residential landscapes with private gardens are major land covers in cities and their sustainable management is paramount for achieving a resilient urban future. Here we focus on the value of residential ecosystems for biodiversity conservation and explore the social and ecological factors that influence wildlife-friendly garden management. Using a stratified sampling design across the UK city of Leeds, this interdisciplinary study develops and applies a mixed method approach, including questionnaires, interviews and ecological surveys across multiple spatial scales. We quantify wildlife-friendly gardening using two measures: (i) the number of wildlife-friendly features within gardens (the wildlife resources index, WRI); and (ii) the frequency of winter bird feeding. Wildlife-friendly gardening is influenced by a combination of garden characteristics and management intensity, householder demographics, wider environmental activity and landscape context. Residents reveal a range of motivations for wildlife-friendly gardening, notably personal well-being and a moral responsibility to nature. Respondents expressed a duty to maintain neighbourhood standards, revealing that social norms are a considerable barrier to uptake of wildlife-friendly activities, but also provide an opportunity where neighbour mimicry results in diffusion of wildlife-friendly practices. Community-driven initiatives that engage, educate and empower residents are better placed to encourage wildlife-friendly gardening than top-down financial incentives.© 2012 Elsevier B.V. All rights reserved.
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We investigate neutral evolution during range shifts in a strategic model of a metapopulation occupying a climate gradient. Using heritable, neutral markers, we track the spatio-temporal fate of lineages. Owing to iterated founder effects ('mutation surfing'), survival of lineages derived from the leading range limit is enhanced. At trailing limits, where habitat suitability decreases, survival is reduced (mutations 'wipe out'). These processes alter (i) the spatial spread of mutations, (ii) origins of persisting mutations and (iii) the generation of diversity. We show that large changes in neutral evolution can be a direct consequence of range shifting.© 2009 The Royal Society.
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Population dynamics result from the interplay of density-independent and density-dependent processes. Understanding this interplay is important, especially for being able to predict near-term population trajectories for management. In recent years, the study of model systems - experimental, observational and theoretical-has shed considerable light on the way that the both density-dependent and -independent aspects of the environment affect population dynamics via impacting on the organism's life history and therefore demography. These model-based approaches suggest that (i) individuals in different states differ in their demographic performance, (ii) these differences generate structure that can fluctuate independently of current total population size and so can influence the dynamics in important ways, (iii) individuals are strongly affected by both current and past environments, even when the past environments may be in previous generations and (iv) dynamics are typically complex and transient due to environmental noise perturbing complex population structures. For understanding population dynamics of any given system, we suggest that 'the devil is in the detail'. Experimental dissection of empirical systems is providing important insights into the details of the drivers of demographic responses and therefore dynamics and should also stimulate theory that incorporates relevant biological mechanism.© 2006 The Royal Society.
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The well studied trade-off between offspring size and offspring number assumes that offspring fitness increases with increasing per-offspring investment. Where mothers differ genetically or exhibit plastic variation in reproductive effort, there can be variation in per capita investment in offspring, and via this trade-off, variation in fecundity. Variation in per capita investment will affect juvenile performance directly - a classical maternal effect - while variation in fecundity will also affect offspring performance by altering the offsprings' competitive environment. The importance of this trade-off, while a focus of evolutionary research, is not often considered in discussions about population dynamics. Here, we use a factorial experiment to determine what proportion of variation in offspring performance can be ascribed to maternal effects and what proportion to the competitive environment linked to the size-number trade-off. Our results suggest that classical maternal effects are significant, but that in our system, the competitive environment, which is linked to maternal environments by fecundity, can be a far more substantial influence.© 2005 The Royal Society.
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Knowledge of the ecological and evolutionary causes of dispersal can be crucial in understanding the behaviour of spatially structured populations, and predicting how species respond to environmental change. Despite the focus of much theoretical research, simplistic assumptions regarding the dispersal process are still made. Dispersal is usually regarded as an unconditional process although in many cases fitness gains of dispersal are dependent on environmental factors and individual state. Condition-dependent dispersal strategies will often be superior to unconditional, fixed strategies. In addition, dispersal is often collapsed into a single parameter, despite it being a process composed of three interdependent stages: emigration, inter-patch movement and immigration, each of which may display different condition dependencies. Empirical studies have investigated correlates of these stages, emigration in particular, providing evidence for the prevalence of conditional dispersal strategies. Ill-defined use of the term 'dispersal', for movement across many different spatial scales, further hinders making general conclusions and relating movement correlates to consequences at the population level. Logistical difficulties preclude a detailed study of dispersal for many species, however incorporating unrealistic dispersal assumptions in spatial population models may yield inaccurate and costly predictions. Further studies are necessary to explore the importance of incorporating specific condition-dependent dispersal strategies for evolutionary and population dynamic predictions.
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A major challenge in ecology is to explain why so many species show oscillatory population dynamics and why the oscillations commonly occur with particular periods. The background environment, through noise or seasonality, is one possible driver of these oscillations, as are the components of the trophic web with which the species interacts. However, the oscillation may also be intrinsic, generated by density-dependent effects on the life history. Models of structured single-species systems indicate that a much broader range of oscillatory behavior than that seen in nature is theoretically possible. We test the hypothesis that it is selection that acts to constrain the range of periods. We analyze a nonlinear single-species matrix model with density dependence affecting reproduction and with trade-offs between reproduction and survival. We show that the evolutionarily stable state is oscillatory and has a period roughly twice the time to maturation, in line with observed patterns of periodicity. The robustness of this result to variations in trade-off function and density dependence is tested.
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Managing populations - whether pests, rare species or economically important ones - is ever more important. Effective management requires an understanding of how populations will respond to changes in their environment. Studying how the environment changes individual behaviour, life-history and population dynamics in soil mites indicates that this process is surprisingly complex.
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The sheep tick Ixodes ricinus (L.) (Acari: Ixodidae) is an ectoparasite of major economic and pathogenic importance in Scotland. Its distribution in the Scottish uplands is assumed to be governed by the abundance and distribution of its definitive hosts (deer and sheep) and climatic variables such as temperature and rainfall. As the numbers of its major host in Scotland, red deer, have increased dramatically and climatic conditions have become more favourable, the level of parasitism could have been expected to rise. We use data gathered from tick counts on over 4000 red grouse chicks Lagopus lagopus scoticus Latham (Galliformes: Tetraonidae) in various experiments over the past 19 years to ascertain whether the intensity and prevalence of parasitism has been increasing. From 1985 to 2003 the average tick burden of a parasitized red grouse chick has grown from 2.60+/-1.12 ticks per chick to 12.71+/-1.44. Over this period the percentage of chicks of a given brood parasitized has also increased from 4+/-2% to 92+/-3%. The possible implications of this increase in parasitism for red grouse production are discussed.
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In most organisms, transitions between different life-history stages occur later and at smaller sizes as growth conditions deteriorate. Day and Rowe recently proposed that this pattern could be explained by the existence of developmental thresholds (minimum sizes or levels of condition below which transitions are unable to proceed). The developmental-threshold model predicts that the reaction norm of age and size at maturity will rotate in an anticlockwise manner from positive to a shallow negative slope if: (i) initial body size or condition is reduced; and/or (ii) some individuals encounter poor growth conditions at increasingly early developmental stages. We tested these predictions by rearing replicated populations of soil mites Sancassania berlesei (Michael) under different growth conditions. High-food environments produced a vertical relationship between age and size at maturity. The slope became increasingly shallow as food was reduced. By contrast, high food in the maternal environment reduced the slope of the reaction norm of age and size at maturity, whereas low food increased it. Overall, the reaction norm of age and size at maturity in S. berlesei was significantly nonlinear and differed for males and females. We describe how growth conditions, mother's environment and sex determine age and size at maturity in S. berlesei.
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1. Mathematical models are frequently used to make predictions of the response of a population to management interventions or environmental perturbations, but it is rarely possible to make controlled or replicated tests of the accuracy of these predictions. 2. We report results from replicated laboratory experiments on populations of a soil mite, Sancassania berlesei, living in 'constant' or 'variable' environments. We experimentally perturbed vital rates, via selective harvesting, and examined the population-level responses. The response depends on the stage manipulated and whether there is environmental variability. Increased mortality usually decreased population size and increased population variability. However, egg mortality in a variable environment increased total population size. 3. We used time-series analysis to construct a stage-based population model of this system, incorporating the responses to both density and variation in food supply. 4. The time-series model qualitatively captures the population dynamics, but does not predict well the way the populations will respond to the change in mortality. Elasticity analysis, conducted on the model's output, therefore did not lead to accurate predictions. 5. The presence of indirect positive population effects of a negative perturbation, but only in a variable environment, suggests that predicting the population response will require the incorporation of density dependence and environmental stochasticity. That the considerable biological complexity of our time-series model did not allow accurate predictions suggests that accurate prediction requires modelling processes within a stage class rather than trying to make do with simple functions of total density.
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The coexistence of periodic and point attractors has been confirmed for a range of stage-structured discrete time models. The periodic attractor cycles have large amplitude, with the populations cycling between extremely low and surprisingly high values when compared to the equilibrium level. In this situation a stable state can be shocked by noise of sufficient strength into a state of high volatility. We found that the source of these large amplitude cycles are Arnol'd tongues, special regions of parameter space where the system exhibits periodic behaviour. Most of these tongues lie entirely in that part of parameter space where the system is unstable, but there are exceptions and these exceptions are the tongues that lead to attractor coexistence. Similarity in the geometry of Arnol'd tongues over the range of models considered might suggest that this is a common feature of stage-structured models but in the absence of proof this can only be a useful working hypothesis. The analysis shows that although large amplitude cycles might exist mathematically they might not be accessible biologically if biological constraints, such as non-negativity of population densities and vital rates, are imposed. Accessibility is found to be highly sensitive to model structure even though the mathematical structure is not. This highlights the danger of drawing biological conclusions from particular models. Having a comprehensive view of the different mechanisms by which periodic states can arise in families of discrete time models is important in the debate on whether the causes of periodicity in particular ecological systems are intrinsic, environmental or trophic. This paper is a contribution to that continuing debate.
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In variable environments, it is probable that environmental conditions in the past can influence demographic performance now. Cohort effects occur when these delayed life-history effects are synchronized among groups of individuals in a population. Here we show how plasticity in density-dependent demographic traits throughout the life cycle can lead to cohort effects and that there can be substantial population dynamic consequences of these effects. We show experimentally that density and food conditions early in development can influence subsequent juvenile life-history traits. We also show that conditions early in development can interact with conditions at maturity to shape future adult performance. In fact, conditions such as food availability and density at maturity, like conditions early in development, can generate cohort effects in mature stages. Based on these data, and on current theory about the effects of plasticity generated by historical environments, we make predictions about the consequences of such changes on density-dependent demography and on mite population dynamics. We use a stochastic cohort effects model to generate a range of population dynamics. In accordance with the theory, we find the predicted changes in the strength of density dependence and associated changes in population dynamics and population variability.
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1. Elasticity and sensitivity analyses are used widely in evolutionary biology, ecology and population management. However, almost all applications ignore density dependence, despite the widespread assumption that density dependence is ubiquitous. We assess whether this matters by comparing density-dependent and density-independent elasticity analyses for the LPA model of Tribolium. 2. Density-independent elasticities of lambda are a poor indicator of the effects of changes in demographic parameters on population size, even for populations at stable equilibrium. With non-equilibrium dynamics, the divergence can be particularly large. In the extreme, a change in a demographic parameter with a positive effect on individual fitness can reduce mean population size, so even the sign of a density-independent elasticity may be wrong. Elasticities of larval, pupal and adult numbers are not proportional to each other, neither are they proportional to elasticities of total population size. 3. A full density-dependent analysis is therefore vital when concerned with effects on population numbers, as in population management, pest control and prediction of population effects of toxins. 4. When examining the consequences for individual fitness of changes in demographic parameters, density-independent elasticities provide a more useful approximation to the density-dependent values. However, they fail to detect cases where non-equilibrium dynamics means that particular life histories gain an advantage by exploiting predictable periods when density dependence is relaxed. 5. This phenomenon can produce a marked change in the pattern of elasticities as a bifurcation is crossed. The corresponding changes in selection pressures may act to stabilize dynamics in some circumstances and destabilize them in others. There is no single answer to the question of whether selection should favour equilibrium or non-equilibrium dynamics.
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How much do we understand about the ecology of extinction? A review of recent literature, and a recent conference in Helsinki gives a snapshot of the "state of the art"*. This "snapshot" is important as it highlights what we currently know, the tools available for studying the process of extinction, its ecological correlates, and the theory concerning extinction thresholds. It also highlights that insight into the ecology of extinction can come from areas as diverse as the study of culture, the fossil record and epidemiology. Furthermore, it indicates where the gaps in knowledge and understanding exist. Of particular note is the need either to generate experimental data, or to make use of existing empirical data-perhaps through meta-analyses, to test general theory and guide its future development.
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While the concept of population growth rate has been of central importance in the development of the theory of population dynamics, few empirical studies consider the intrinsic growth rate in detail, let alone how it may vary within and between populations of the same species. In an attempt to link theory with data we take two approaches. First, we address the question 'what growth rate patterns does theory predict we should see in time-series?' The models make a number of predictions, which in general are supported by a comparative study between time-series of harvesting data from 352 red grouse populations. Variations in growth rate between grouse populations were associated with factors that reflected the quality and availability of the main food plant of the grouse. However, while these results support predictions from theory, they provide no clear insight into the mechanisms influencing reductions in population growth rate and regulation. In the second part of the paper, we consider the results of experiments, first at the individual level and then at the population level, to identify the important mechanisms influencing changes in individual productivity and population growth rate. The parasitic nematode Trichostrongylus tenuis is found to have an important influence on productivity, and when incorporated into models with their patterns of distribution between individuals has a destabilizing effect and generates negative growth rates. The hypothesis that negative growth rates at the population level were caused by parasites was demonstrated by a replicated population level experiment. With a sound and tested model framework we then explore the interaction with other natural enemies and show that in general they tend to stabilize variations in growth rate. Interestingly, the models show selective predators that remove heavily infected individuals can release the grouse from parasite-induced regulation and allow equilibrium populations to rise. By contrast, a tick-borne virus that killed chicks simply leads to a reduction in the equilibrium. When humans take grouse they do not appear to stabilize populations and this may be because many of the infective stages are available for infection before harvesting commences. In our opinion, an understanding of growth rates and population dynamics is best achieved through a mechanistic approach that includes a sound experimental approach with the development of models. Models can be tested further to explore how the community of predators and others interact with their prey.
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Environmental variation is ubiquitous, but its effects on nonlinear population dynamics are poorly understood. Using simple (unstructured) nonlinear models we investigate the effects of correlated noise on the dynamics of two otherwise independent populations (the Moran effect), i.e, we focus on noise rather than dispersion or trophic interaction as the cause of population synchrony. We find that below the bifurcation threshold for periodic behaviour (1) synchrony between populations is strongly dependent on the shape of the noise distribution but largely insensitive to which model is studied, (2) there is, in general, a loss of synchrony as the noise is filtered by the model, (3) for specially structured noise distributions this loss can be effectively eliminated over a restricted range of distribution parameter values even though the model might be nonlinear, (4) for unstructured models there is no evidence of correlation enhancement, a mechanism suggested by Moran, but above the bifurcation threshold enhancement is possible for weak noise through phase-locking, (5) rapid desynchronisation occurs as the chaotic regime is approached. To carry out the investigation the stochastic models are (a) reformulated in terms of their joint asymptotic probability distributions and (b) simulated to analyse temporal patterns.
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BACKGROUND: Students tend to rate university courses more positively if they do well. Greenwald and Gillmore (1997a) suggested that it is not students' absolute grades that are important but rather how these grades compare to their expectations. However, this hypothesis is difficult to evaluate because few studies have measured grade expectations at the beginning of courses. AIM: By measuring students' grade expectations and enjoyment at several stages during a course, we hoped to evaluate the extent to which expectations modulate the impact of grades on course enjoyment. SAMPLE: Participants were 242 students in a university course in psychology. METHOD: Students were asked what grades they expected, and how much they were enjoying the course, at four stages. The effect of grades and grade expectations on enjoyment were analysed using restricted maximum likelihood (REML) and regression analyses. RESULTS: The best predictor of course enjoyment varied somewhat at different stages, but in general it was the extent to which students' grades surpassed their expectations. Students' expectations at the beginning of the course proved particularly influential. CONCLUSIONS: Grade expectations do influence how students react to course grades, but the prominent role of pre-course expectations suggests that it may be important to distinguish between grade aspirations and grade expectations. It appears to be students' aspirations--the grades they hope to achieve--that most strongly shape their emotional reactions, rather than the more realistic expectations they may form later in a course.
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As part of a study of the effects of food quality on macrodecomposers, a new method for estimating rates of leaf-titter production by dicotyledonous plants has been developed and tested for three grassland sites. The method is based on estimations of i) rates of leaf abscission by monitoring increases in the number of leaf-scars on shoots, ii) the mean weight of leaves, iii) the proportion of leaves removed by herbivores, and iv) the density of shoots, to give monthly estimates of leaf-litter production. Litter production by 20 species was monitored for seven months. The three sites differed in both the pattern and amount of dicotyledonous leaf-litter production which was strongly influenced by the extent of vertebrate and invertebrate herbivory. By combining the detailed litter production estimates for one year, in which all the parameters were monitored throughout the season, with more approximate estimates of standing crop of dicotyledonous plants in other years, more approximate estimates of annual litter production were obtained over a 20-year period. The highest rates of dicotyledonous leaf-litter production were on the site subjected to the highest levels of vertebrate grazing, which prompted a greater diversity and abundance of forbs relative to grasses. Production rates on this site declined when grazing pressure became very intense.
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In a constant environment, the rate of convergence of a density-independent Leslie matrix model to stable age distribution is determined by the damping ratio (the ratio of the absolute magnitudes of the first and second eigenvalues of the projection matrix). In a stochastic environment, the difference between the first two Lyapunov exponents is known to be analogous to the logarithm of the damping ratio, but there has been no systematic investigation of the consequences of enviromnental variation on convergence rates. In this study, the Lyapunov spectrum has been calculated for a wide variety of density-independent projection matrices subject to random variations in vital rates. This allows the impact of these random variations on convergence rates to be assessed. For rapidly convergent life histories, stochastic variation leads to a decrease in convergence rate. For life histories which are slow to converge, stochastic variation speeds up convergence. These effects are, however, relatively minor, and the value of the damping ratio for the mean matrix is a good predictor of the damping ratio in a stochastic environment. Consequently, when only an approximate indication of convergence rates is needed, the damping ratio for the mean projection matrix gives a very good guide. Detailed calculations of the Lyapunov spectrum would only be necessary to make comparisons between similar life histories or if very precise information on convergence rates were needed.
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Most life-history theory assumes the environment is invariant. For the first time, analytical and numerical techniques were employed to investigate the impact of environmental variability on selection pressures (elasticities = proportional sensitivities) on a range of life histories. We find that the impact of variability is influenced significantly by the amount of variability an organism experiences (more variability affects selection pressures more), the correlations between variations among the vital rates (negative correlations are more likely to relax selection on fecundities and increase it on survival rates), and the life history in question (shorter life histories are more affected). In addition, the impact of a variable environment on the elastici-ties of life histories is sensitive to the sampling distribution used to generate the variability, and it is particularly sensitive to extreme values, such as those caused by occasional catastrophic events. The elasticities of life histories in highly variable environments may bear little relationship to those in a constant environment. In detailed optimality or evolutionarily stable strategy (ESS) modeling, variability in vital rates as small as a standard deviation being 10%-15% of the mean may appreciably alter the conclusions. Thus, it may be very important to consider the possible impact of environmental stochasticity and not to assume that it has no effect.
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Before the mating season males become vagrant to search for females. On encountering a pregnant female or one with young, in her "burrow', the male may mate-guard her until her period of maternal care ends and she becomes receptive to him. Large males have a higher mating success than small males. Two instars of adult males exist in this population of scorpions: large 7th instars and small 6th instars. -from Author
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