23 resultados para POPULATION-DYNAMICS

em Helda - Digital Repository of University of Helsinki


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Europe was declared malaria free in 1975. The disappearance of malaria has traditionally been attributed to numerous deliberate actions like vector control, the screening of houses, more efficient medication etc. Malaria, however, disappeared from many countries like Finland before any counter measures had even started. The aim of this thesis is to study the population ecology of P. vivax and its interaction with the human host and the vector. By finding the factors that attributed to the extinction of vivax malaria it might be possible to improve the modern strategy against P. vivax. The parasite was studied with data from Finland, which provides the longest time series (1749-2008) of malaria statistics in the world. The malaria vectors, Anopheles messeae and A. beklemishevi are still common species in the country. The eradication of vivax malaria is difficult because the parasite has a dormant stage that can cause a relapse long after a primary infection. It was now shown that P. vivax is able to detect the presence of a potential vector. A dormant stage is triggered even from a bite of an uninfected Anopheles mosquito. This optimizes the chances for the Plasmodium to reach a mosquito vector for sexual reproduction. The longevity of the dormant stage could be shown to be at least nine years. The parasite spends several years in its human host and the behaviour of the human carrier had a profound impact on the decline of the disease in Finland. Malaria spring epidemics could be explained by a previous warm summer. Neither annual nor summer mean temperature had any impact on the long term malaria trend. Malaria disappeared slowly from Finland without mosquito control. The sociological change from extended families to nuclear families led to decreased household size. The decreased household size correlated strongly with the decline of malaria. That led to an increased isolation of the subpopulations of P. vivax. Their habitat consisted of the bedrooms in which human carriers slept together with the overwintering vectors. The isolation of the parasite ultimately led to the extinction of vivax malaria. Metapopulation models adapted to local conditions should therefore be implemented as a tool for settlement planning and socio-economic development and become an integrated part of the fight against malaria.

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Spatial and temporal variation in the abundance of species can often be ascribed to spatial and temporal variation in the surrounding environment. Knowledge of how biotic and abiotic factors operate over different spatial and temporal scales in determining distribution, abundance, and structure of populations lies at the heart of ecology. The major part of the current ecological theory stems from studies carried out in central parts of the distributional range of species, whereas knowledge of how marginal populations function is inadequate. Understanding how marginal populations, living at the edge of their range, function is however in a key position to advance ecology and evolutionary biology as scientific disciplines. My thesis focuses on the factors affecting dynamics of marginal populations of blue mussels (Mytilus edulis) living close to their tolerance limits with regard to salinity. The thesis aims to highlight the dynamics at the edge of the range and contrast these with dynamics in more central parts of the range in order to understand the potential interplay between the central and the marginal part in the focal system. The objectives of the thesis are approached by studies on: (1) factors affecting regional patterns of the species, (2) long-term temporal dynamics of the focal species spaced along a regional salinity gradient, (3) selective predation by increasing populations of roach (Rutilus rutilus) when feeding on their main food item, the blue mussel, (4) the primary and secondary effects of local wave exposure gradients and (5) the role of small-scale habitat heterogeneity as determinants of large-scale pattern. The thesis shows that populations of blue mussels are largely determined by large scale changes in sea water salinity, affecting mainly recruitment success and longevity of local populations. In opposite to the traditional view, the thesis strongly indicate that vertebrate predators strongly affect abundance and size structure of blue mussel populations, and that the role of these predators increases towards the margin where populations are increasingly top-down controlled. The thesis also indicates that the positive role of biogenic habitat modifiers increases towards the marginal areas, where populations of blue mussels are largely recruitment limited. Finally, the thesis shows that local blue mussel populations are strongly dependent on high water turbulence, and therefore, dense populations are constrained to offshore habitats. Finally, the thesis suggests that ongoing sedimentation of rocky shores is detrimental for the species, affecting recruitment success and post-recruit survival, pushing stable mussel beds towards offshore areas. Ongoing large scale changes in the Baltic Sea, especially dilution processes with attendant effects, are predicted to substantially contract the distributional range of the mussel, but also affect more central populations. The thesis shows that in order to understand the functioning of marginal populations, research should (1) strive for multi-scale approaches in order to link ecosystem patterns with ecosystem processes, and (2) challenge the prevailing tenets that origin from research carried out in central areas that may not be valid at the edge.

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Population dynamics are generally viewed as the result of intrinsic (purely density dependent) and extrinsic (environmental) processes. Both components, and potential interactions between those two, have to be modelled in order to understand and predict dynamics of natural populations; a topic that is of great importance in population management and conservation. This thesis focuses on modelling environmental effects in population dynamics and how effects of potentially relevant environmental variables can be statistically identified and quantified from time series data. Chapter I presents some useful models of multiplicative environmental effects for unstructured density dependent populations. The presented models can be written as standard multiple regression models that are easy to fit to data. Chapters II IV constitute empirical studies that statistically model environmental effects on population dynamics of several migratory bird species with different life history characteristics and migration strategies. In Chapter II, spruce cone crops are found to have a strong positive effect on the population growth of the great spotted woodpecker (Dendrocopos major), while cone crops of pine another important food resource for the species do not effectively explain population growth. The study compares rate- and ratio-dependent effects of cone availability, using state-space models that distinguish between process and observation error in the time series data. Chapter III shows how drought, in combination with settling behaviour during migration, produces asymmetric spatially synchronous patterns of population dynamics in North American ducks (genus Anas). Chapter IV investigates the dynamics of a Finnish population of skylark (Alauda arvensis), and point out effects of rainfall and habitat quality on population growth. Because the skylark time series and some of the environmental variables included show strong positive autocorrelation, the statistical significances are calculated using a Monte Carlo method, where random autocorrelated time series are generated. Chapter V is a simulation-based study, showing that ignoring observation error in analyses of population time series data can bias the estimated effects and measures of uncertainty, if the environmental variables are autocorrelated. It is concluded that the use of state-space models is an effective way to reach more accurate results. In summary, there are several biological assumptions and methodological issues that can affect the inferential outcome when estimating environmental effects from time series data, and that therefore need special attention. The functional form of the environmental effects and potential interactions between environment and population density are important to deal with. Other issues that should be considered are assumptions about density dependent regulation, modelling potential observation error, and when needed, accounting for spatial and/or temporal autocorrelation.

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Large carnivore populations are currently recovering from past extirpation efforts and expanding back into their original habitats. At the same time human activities have resulted in very few wilderness areas left with suitable habitats and size large enough to maintain populations of large carnivores without human contact. Consequently the long-term future of large carnivores depends on their successful integration into landscapes where humans live. Thus, understanding their behaviour and interaction with surrounding habitats is of utmost importance in the development of management strategies for large carnivores. This applies also to brown bears (Ursus arctos) that were almost exterminated from Scandinavia and Finland at the turn of the century, but are now expanding their range with the current population estimates being approximately 2600 bears in Scandinavia and 840 in Finland. This thesis focuses on the large-scale habitat use and population dynamics of brown bears in Scandinavia with the objective to develop modelling approaches that support the management of bear populations. Habitat analysis shows that bear home ranges occur mainly in forested areas with a low level of human influence relative to surrounding areas. Habitat modelling based on these findings allows identification and quantification of the potentially suitable areas for bears in Scandinavia. Additionally, this thesis presents novel improvements to home range estimation that enable realistic estimates of the effective area required for the bears to establish a home range. This is achieved through fitting to the radio-tracking data to establish the amount of temporal autocorrelation and the proportion of time spent in different habitat types. Together these form a basis for the landscape-level management of the expanding population. Successful management of bears requires also assessment of the consequences of harvest on the population viability. An individual-based simulation model, accounting for the sexually selected infanticide, was used to investigate the possibility of increasing the harvest using different hunting strategies, such as trophy harvest of males. The results indicated that the population can sustain twice the current harvest rate. However, harvest should be changed gradually while carefully monitoring the population growth as some effects of increased harvest may manifest themselves only after a time-delay. The results and methodological improvements in this thesis can be applied to the Finnish bear population and to other large carnivores. They provide grounds for the further development of spatially-realistic management-oriented models of brow bear dynamics that can make projections of the future distribution of bears while accounting for the development of human activities.

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Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

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Natural selection generally operates at the level of the individual, or more specifically at the level of the gene. As a result, individual selection does not always favour traits which benefit the population or species as a whole. The spread of an individual gene may even act to the detriment of the organism in which it finds. Thus selection at the level of the individual can affect processes at the level of the organism, group or even at the level of the species. As most behaviours ultimately affect births, deaths and the distribution of individuals, it seems inevitable that behavioural decisions will have an impact on population dynamics and population densities. Behavioural decisions can often involve costs through allocation of energy into behavioural strategies, such as the investment into armaments involved in fighting over resources or increased mortality due to injury or increased predation risk. Similarly, behaviour may act o to benefit the population, in terms of higher survival and increased fecundity. Examples include increased investment through parental care, choosing a mate based on the nuptial gifts they may supply and choosing territories in the face of competition. Investigating the impact of behaviour on population ecology may seem like a trivial task, but it is likely to have important consequences at different levels. For example, antagonistic behaviour may occasionally become so extreme that it increases the risk of extinction, and such extinction risk may have important implications for conservation. As a corollary, any such behaviour may also act as a macroevolutionary force, weeding out populations with traits which, whilst beneficial to the individuals in the short term, ultimately result in population extinction. In this thesis, I examine how behaviours, specifically conflict and competition over a resource and aspects of behaviour involved in sexual selection, can affect population densities, and what the implications are for the evolution and ecology of the populations in question. It is found that both behaviours related to individual conflict and mating strategies can have an effect at the level of the population, but that various factors, such as a feedback between selection and population densities or macroevolution caused by species extinctions, may act to limit the intensity of conflicts that we observe in nature.

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Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

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Productivity is predicted to drive the ecological and evolutionary dynamics of predator-prey interaction through changes in resource allocation between different traits. However, resources are seldom constantly available and thus temporal variation in productivity could have considerable effect on the species' potential to evolve. To study this, three long-term microbial laboratory experiments were established where Serratia marcescens prey bacteria was exposed to predation of protist Tetrahymena thermophila in different prey resource environments. The consequences of prey resource availability for the ecological properties of the predator-prey system, such as trophic dynamics, stability, and virulence, were determined. The evolutionary changes in species traits and prey genetic diversity were measured. The prey defence evolved stronger in high productivity environment. Increased allocation to defence incurred cost in terms of reduced prey resource use ability, which probably constrained prey evolution by increasing the effect of resource competition. However, the magnitude of this trade-off diminished when measured in high resource concentrations. Predation selected for white, non-pigmented, highly defensive prey clones that produced predation resistant biofilm. The biofilm defence was also potentially accompanied with cytotoxicity for predators and could have been traded off with high motility. Evidence for the evolution of predators was also found in one experiment suggesting that co-evolutionary dynamics could affect the evolution and ecology of predator-prey interaction. Temporal variation in resource availability increased variation in predator densities leading to temporally fluctuating selection for prey defences and resource use ability. Temporal variation in resource availability was also able to constrain prey evolution when the allocation to defence incurred high cost. However, when the magnitude of prey trade-off was small and the resource turnover was periodically high, temporal variation facilitated the formation of predator resistant biofilm. The evolution of prey defence constrained the transfer of energy from basal to higher trophic levels, decreasing the strength of top-down regulation on prey community. Predation and temporal variation in productivity decreased the stability of populations and prey traits in general. However, predation-induced destabilization was less pronounced in the high productivity environment where the evolution of prey defence was stronger. In addition, evolution of prey defence weakened the environmental variation induced destabilization of predator population dynamics. Moreover, protozoan predation decreased the S. marcescens virulence in the insect host moth (Parasemia plantaginis) suggesting that species interactions outside the context of host-pathogen relationship could be important indirect drivers for the evolution of pathogenesis. This thesis demonstrates that rapid evolution can affect various ecological properties of predator-prey interaction. The effect of evolution on the ecological dynamics depended on the productivity of the environment, being most evident in the constant environments with high productivity.

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In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.

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Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

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The knowledge about the optimal rearing conditions, such as water temperature and quality, photoperiod and density, with the understanding of animal nutritional requirements forms the basis of economically stable aquaculture for freshwater crayfish. However, the shift from a natural environment to effective culture conditions induces several changes, not only at the population level, but also at the individual level. The social contacts between conspecifics increase with increasing animal density. The competition for limited resources (e.g. food, shelter, mates) is more severe with the presence of agonistic behaviour and may lead to unequal distribution of these. The objectives of this study were to: 1) study the distribution of a common food resource between communally reared signal crayfish (Pacifastacus leniusculus) and to assign potential feeding hierarchy on the basis of individual food intake measurements, 2) explore the possibilities of size distribution manipulations to affect population dynamics and food intake to improve growth and survival in culture and 3) study the effect of food ration and spatial distribution on food intake and to explore the effect of temperature and food ration on growth and body composition of freshwater crayfish. The feeding ranks between animals were assigned with a new method for individual food intake measurement of communally reared crayfish. This technique has a high feasibility and a great potential to be applied in crayfish aquaculture studies. In this study, signal crayfish showed high size-related variability in food consumption both among individuals within a group (inter-individual) and within individual day-to-day variation (intra-individual). Increased competition for food led to an unequal distribution of this resource and this may be a reason for large growth differences between animals. The consumption was significantly higher when reared individually in comparison with communal housing. These results suggest that communally housed crayfish form a feeding hierarchy and that the animal size is the major factor controlling the position in this hierarchy. The optimisation of the social environment ( social conditions ) was evaluated in this study as a new approach to crayfish aquaculture. The results showed that the absence of conspecifics (individual rearing vs. communal housing) affects growth rate, food intake and the proportion of injured animals, whereas size variation between animals influences the number and duration of agonistic encounters. In addition, animal size had a strong influence on the fighting success of signal crayfish reared in a social milieu with a wide size variation of conspecifics. Larger individuals initiated and won most of the competitions, which suggests size-based social hierarchy of P. leniusculus. This is further supported by the fact that the length and weight gain of smaller animals increased after size grading, maybe because of a better access to the food resource due to diminished social pressure. However, the high dominance index was not based on size under conditions of limited size variation, e.g. those characteristic of restocked natural populations and aquaculture, indicating the important role of behaviour on social hierarchy.