The application of a multiple-recapture technique for the study of some aspects of dynamics of large fish populations

The multiple-recapture technique can be used to study some aspects of the dynamics of large fish populations, if a part of the fishing fleet is considered as experimental fishing boats by appointing obserers to release tagged fish which are captured, while untagged fish captured are retained. The tagged and untagged populations are assumed to have different properties such as catchability and survival rates. The fish are sampled during a number of sampling surveys with equal duration and no intervening time intervals between them. It is assumed that fish suffer from mortalities during sampling surveys. The parameters of untagged populations can be estimated with the help of the readily estimated parameters of tagged fish (Rafail, 1972), the relationship between the parameters of tagged and untagged populations, and the numbers of untagged fish captured during the sampling surveys. The estimates are free from Types A and B tagging errors.     

Migration effects in a stochastic multipopulation model for African bee population dynamics

The rate of northern migration of the Africanized honey bee (AHB) in the United States has recently slowed dramatically. This paper investigates the impact of migration on the equilibrium size distributions of a particular stochastic multipopulation model, namely a coupled logistic power law model. The bivariate equilibrium size distribution of the model is derived and illustrated with parameter values used to describe AHB population dynamics. In the model, the difference between the equilibrium sizes of the two populations is a measure of the effect of migration. The distribution of this difference may be approximated by a normal distribution. The mean and variance parameters for the normal are predicted accurately by a second-order regression model based on the migration rate and the maximum size of the first population. The methodology is general, and should be useful in studying the migration effect in many other applications with one-way migration.     

A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study

The models used for ecosystems modeling are generally based on differential equations. However, in recent years new computational models based on biological processes, or bioinspired models, have arisen, among which are P systems. These are inspired by the functions of cells and present important advantages with respect to traditional models, such as a high computational efficiency, modularity and their ability to work in parallel. They are simple, individual-based models that use biological parameters that can be obtained experimentally. In this work, we present the framework for a model based on P systems applied to the study of an ecosystem in which three avian scavengers (predators) interact with 10 wild and domestic ungulates (preys). The computation time for 100 repetitions, corresponding to 14 simulation years each, with an initial population composed of 385,422 individuals, was 30 min. Our results suggest that the model presented, based on P systems, correctly simulates the population dynamics in the period of time analyzed. We discuss the usefulness of this tool in simulating complex ecosystems dynamics to aid managers, conservationists and policy-makers in making appropriate decisions for the improvement of management and conservation programs.     

The pattern of species turnover resulting from stochastic population dynamics: The model and field data

The model of random population dynamics in a sampling site returns geometric distribution of longevities of continuous presence (=persistence) and Poisson distribution of the presence–absence transitions. This discrete-time stochastic process describes the presence–absence pattern observed in the beetles surveyed 6 years on Mount Carmel, Israel. Homogeneous pools of species mostly on the Families rank, exhibit the predicted by the model patterns. Conformity to an ergodic hypothesis is the criterion of ecological homogeneity. This criterion assumes the equivalence of short-term behavior of entire pool and long-term behavior of any species from this pool. The pool of all 801 species of Order Coleoptera does not match the model. Thus a taxon of an arbitrary rank may not be considered a priory as a unit of ecological study. Determined from field data parameters of the model are biased and magnitude of the bias depends on longevity of the survey. Parameter of distribution depends also on species tolerance, which is the level adaptation of given species to given environment in given time interval. Random process of species turnover may be considered as a game of species to gain their presence against deteriorative fluctuations of environmental conditions.     

Selecting parameters for calibration via sensitivity analysis: An individual-based model of mosquitofish population dynamics

A stochastic individual-based model (IBM) of mosquitofish population dynamics in experimental ponds was constructed in order to increase, virtually, the number of replicates of control populations in an ecotoxicology trial, and thus to increase the statistical power of the experiments. In this context, great importance had to be paid to model calibration as this conditions the use of the model as a reference for statistical comparisons. Accordingly, model calibration required that both mean behaviour and variability behaviour of the model were in accordance with real data. Currently, identifying parameter values from observed data is still an open issue for IBMs, especially when the parameter space is large. Our model included 41 parameters: 30 driving the model expectancy and 11 driving the model variability. Under these conditions, the use of “Latin hypercube” sampling would most probably have “missed” some important combinations of parameter values. Therefore, complete factorial design was preferred. Unfortunately, due to the constraints of the computational capacity, cost-acceptable “complete designs” were limited to no more than nine parameters, the calibration question becoming a parameter selection question. In this study, successive “complete designs” were conducted with different sets of parameters and different parameter values, in order to progressively narrow the parameter space. For each “complete design”, the selection of a maximum of nine parameters and their respective n values was carefully guided by sensitivity analysis. Sensitivity analysis was decisive in selecting parameters that were both influential and likely to have strong interactions. According to this strategy, the model of mosquitofish population dynamics was calibrated on real data from two different years of experiments, and validated on real data from another independent year. This model includes two categories of agents; fish and their living environment. Fish agents have four main processes: growth, survival, puberty and reproduction. The outputs of the model are the length frequency distribution of the population and the 16 scalar variables describing the fish populations. In this study, the length frequency distribution was parameterized by 10 scalars in order to be able to perform calibration. The recently suggested notion of “probabilistic distribution of the distributions” was also applied to our case study, and was shown to be very promising for comparing length frequency distributions (as such).     

Development and validation of an individual based Daphnia magna population model: The influence of crowding on population dynamics

An individual-based model was developed to predict the population dynamics of Daphnia magna at laboratory conditions from individual life-history traits observed in experiments with different feeding conditions. Within the model, each daphnid passes its individual life cycle including feeding on algae, aging, growing, developing and – when maturity is reached – reproducing. The modelled life cycle is driven by the amount of ingested algae and the density of the Daphnia population. At low algae densities the population dynamics is mainly driven by food supply, when the densities of algae are high, the limiting factor is “crowding” (a density-dependent mechanism due to chemical substances released by the organisms or physical contact, but independent of food competition).     

Local population dynamics of an invasive tree species with a complex life-history cycle: A stochastic matrix model

Biological invasions are widely accepted as having a major impact on ecosystem functioning worldwide, giving urgency to a better understanding of the factors that control their spread. Modelling tools have been developed for this purpose but are often discrete-space, discrete-time spatial-mechanistic models that adopt a computer simulation approach and resist mathematical analysis. We constructed a simple demographic matrix model to explore the local population dynamics of an invasive species with a complex life history and whose invasive success depends on resource availability, which occurs stochastically. As a case study we focused on the American black cherry (Prunus serotina Ehrh.), a gap-dependent tree able both to constitute a long-living seedling bank under unfavourable light conditions and to resprout vigorously once cut-down, which is invading European temperate forests. The model used was a stage-classified matrix population model (i.e., Lefkovitch matrix), integrating environmental stochasticity. Stochastic matrix projection analysis was combined with elasticity analysis and stochastic simulations to search for the species’ ‘Achille heel’. As expected, the population growth rate (i.e., Lyapunov exponent), which measures the risk of P. serotina invasion at the stand scale, increased with light frequency. There was a critical value above which the population of P. serotina explodes and below which it locally goes extinct. The resprouting capacity usually speed up the invasion but appeared to play a minor role. The mean duration of stand invasion was measured and important life stage transitions that mostly contribute to the local stochastic growth rate were identified. Some relevant management implications are discussed and the interest of such models for the understanding of demographic characteristics of invasive species is stressed.     

Microclimate influence in a physiological model of cattle-fever tick (Boophilus spp.) population dynamics

Since their official eradication from the US in 1943, the cattle-tick species Boophilus microplus and Boophilus annulatus, vectors of bovine babesiosis, frequently have penetrated a quarantine zone established along the Texas–Mexico border designed to exclude them. Inspection and quarantine procedures have eradicated reinfestations successfully within the US, but increasing acaricide resistance in Mexican B. microplus populations poses a threat to future eradication efforts. Better understanding of interrelationships among Boophilus populations, their hosts, and vegetation communities in south Texas could improve prediction of the behavior of reintroduced Boophilus populations and increase management options. To this end, we constructed a simulation model to evaluate how microclimate, habitat (i.e. vegetation) heterogeneity, and within-pasture cattle movement may influence dynamics of Boophilus ticks in south Texas. Unlike previous Boophilus tick models, this model simulates dynamics at an hourly time-step, calculates all off-host dynamics as functions of temperature and relative humidity, and runs with ground-level microclimate data collected bi-hourly in three different habitat types. Sensitivity analysis of the model showed that temperatures and relative humidities created by habitat type, as well as engorged female mass, influenced tick population dynamics most strongly. Host habitat selection, initial number of larvae per cow, and the number of cells into which the simulated pasture was divided also had a strong influence. Population dynamics appeared moderately sensitive to the proportion of Bos indicus in cattle genotypes and the larval attachment rate, while appearing relatively insensitive to factors such as mortality rate of engorged females. When used to simulate laboratory experiments from the literature, the model predicted most observed life-history characteristics fairly well; however, it tended to underestimate oviposition duration, incubation duration, and egg mortality and overestimate larval longevity, especially at low temperatures and high humidities. Use of the model to predict Boophilus population dynamics in hypothetical south Texas pastures showed that it reasonably generated qualitative patterns of stage-wise abundances but tended to overestimate on-host tick burdens. Collection and incorporation of data that appear not to exist for Boophilus ticks, such as larval lipid content and lipid-use rates, may improve model accuracy. Though this model needs refinements such as a smaller spatial resolution, it provides insight into responses of B. microplus or B. annulatus populations to specific weather patterns, habitat heterogeneity, and host movement.     

Mathematical model and computer simulation of the population dynamics of zooplankton in lake and estuary ecosystems

A mathematical model is developed for the population dynamics and survival probabilities of zooplankton in lake and estuarine. Basic digital computer simulation methodology is used for systematic application of the mathematical model for analysis of the population dynamics of zooplankton. In the analysis of this theoretical modelling, attention is focused on the production and destruction processes of the animal. Both processes are assumed stationary. The birth (production) rate is constant and life-span distribution is independent of time. It is also assumed that the different zooplankton species are independent and share a common aquatic ecosystem, and what happens to one of them does not influence the fate of any other in this system.     

Spatiotemporal variation in survival rates: implications for population dynamics of yellow-bellied marmots

Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.     

The role of intraguild predation in the population dynamics of small pelagic fish

In this paper, we argue that understanding marine ecosystem functioning requires a thorough appreciation of the role of intraguild predation to system dynamics. The theoretical predictions of intraguild predation models might explain some of the community features observed in marine ecosystems such as low diversity in upwelling and productive systems and species alternation in response to moderate external forcing. Finally, we argue that an ecosystem approach to fisheries requires that the size–structure of fish populations should be taken into account and that it is extremely important to account for the predators of early stages (eggs and larvae) to gain a thorough understanding of the key interactions between species.     

A system dynamics model for evaluating collaborative forest management: a case study in Indonesia

This article presents a system dynamics (SD) method to examine the problem of forest degradation. The model developed takes a system-oriented view of forest management, embracing both social and biophysical factors affecting deforestation. Social factors examined are socio-economic variables or elements that influence behaviour and decision-making choices at the household level. Biophysical factors are four sub-components that are considered major land uses namely, the paddy field component, rattan plantations, coffee plantations and forest stands. The model was applied in a case study located in Pasir District of East Kalimantan, Indonesia. The site covers an area that includes a protected forest and a privately allocated timber license concession. Three village communities are examined in the case study. The SD model developed was applied to the case study focusing on three management policies or scenarios, which are based on access rights to the forest resources within the study area. Specifically, the property arrangements examined in each scenario are: Policy 1 – status quo (i.e. continue present property rights arrangements); Policy 2 – local communities manage the forest exclusively; and Policy 3 – collaborative management involving both local communities and a private company. Results from the model show that the third policy is the most viable option, and also lead to a win–win solution.     

Invasion dynamics of the varnish clam (Nuttallia obscurata): a matrix demographic modeling approach

Marine invaders have become a significant threat to native biodiversity and ecosystem function. In this study, the invasion of the varnish clam (Nuttallia obscurata) in British Columbia, Canada, is investigated using a matrix modeling approach to identify the life history characteristics most crucial for population growth and to investigate population differences. Mark-recapture analyses and field collections from 2003 to 2004 were used to determine individual growth, survival rates, and fecundity for two sites. A multi-state matrix model was used to determine population growth rates and to conduct sensitivity and elasticity analyses. A life table response experiment was also used to determine what life history stage contributed most to observed differences in population growth rates. Population survey data were used in conjunction with the matrix model to determine plausible recruitment levels and to investigate recruitment scenarios. Both populations are currently declining but are likely sustainable because of the pulsed nature of large recruitment events. Survival of larger clams (>40 mm) is the most important for population growth based on elasticity and sensitivity analyses. Adult survival also had the largest influence on observed differences between site-specific population growth rates. The two populations studied differed in recruitment dynamics; one experiencing annual recruitment with higher post-settlement mortality and the other, episodic recruitment and lower post-settlement mortality. The most influential factor for the successful invasion of the varnish clam appears to be survival of the larger size classes. Therefore, any process that decreases adult survival (e.g., predation, commercial harvest) will have the greatest impact on population growth.     

Economic aspects of global change impacts and response strategies in the coastal zone of The Netherlands

Economic aspects of possible land use strategies and protection measures in coastal zones as a response to global environmental change are examined. First, some key elements are mentioned that are of critical importance for water and land management in coastal zones. Next, various socio-economic repercussions are discussed. In this context, research needs will be addressed. Subsequently, these issues are considered for the case of The Netherlands. It is concluded that integrated modelling and analysis is just starting and needs to receive more attention in order to study long run economic costs, benefits and changes in coastal zones.     

The triple helix of Plantago lanceolata: genetics and the environment interact to determine population dynamics

The theory of evolution via natural selection predicts that the genetic composition of wild populations changes over time in response to the environment. Different genotypes should exhibit different demographic patterns, but genetic variation in demography is often impossible to separate from environmental variation. Here, we asked if genetic variation is important in determining demographic patterns. We answer this question using a long-term field experiment combined with general linear modeling of deterministic population growth rates (lambda), deterministic life table response experiment (LTRE) analysis, and stochastic simulation of demography by paternal lineage in a short-lived perennial plant, Plantago lanceolata, in which we replicated genotypes across four cohorts using a standard breeding design. General linear modeling showed that growth rate varied significantly with year, spatial block, and sire. In LTRE analysis of all cohorts, the strongest influences on growth rate were from year x spatial block, and cohort x year x spatial block interactions. In analysis of genetics vs. temporal environmental variation, the strongest impacts on growth rate were from year and year x sire. Finally, stochastic simulation suggested different genetic composition among cohorts after 100 years, and different population growth rates when genetic differences were accounted for than when they were not. We argue that genetic variation, genotype x environment interactions, natural selection, and cohort effects should be better integrated into population ecological studies, as these processes should result in deviations from projected deterministic and stochastic population parameters.     

Nonlinear effects of climate and density in the dynamics of a fluctuating population of reindeer

Nonlinear and irregular population dynamics may arise as a result of phase dependence and coexistence of multiple attractors. Here we explore effects of climate and density in the dynamics of a highly fluctuating population of wild reindeer (Rangifer tarandus platyrhynchus) on Svalbard observed over a period of 29 years. Time series analyses revealed that density dependence and the effects of local climate (measured as the degree of ablation [melting] of snow during winter) on numbers were both highly nonlinear: direct negative density dependence was found when the population was growing (Rt > 0) and during phases of the North Atlantic Oscillation (NAO) characterized by winters with generally high (1979-1995) and low (1996-2007) indices, respectively. A growth-phase-dependent model explained the dynamics of the population best and revealed the influence of density-independent processes on numbers that a linear autoregressive model missed altogether. In particular, the abundance of reindeer was enhanced by ablation during phases of growth (Rt > 0), an observation that contrasts with the view that periods of mild weather in winter are normally deleterious for reindeer owing to icing of the snowpack. Analyses of vital rates corroborated the nonlinearity described in the population time series and showed that both starvation mortality in winter and fecundity were nonlinearly related to fluctuations in density and the level of ablation. The erratic pattern of growth of the population of reindeer in Adventdalen seems, therefore, to result from a combination of the effects of nonlinear density dependence, strong density-dependent mortality, and variable density independence related to ablation in winter.     

Calanoid resting eggs in the Baltic Sea: implications for the population dynamics of Acartia bifilosa (Copepoda)

Resting eggs of Acartia spp. (presumably A. bifilosa Giesbr.) at densities between 65 and 125 eggs cm^-2 were found in sediment off the southern coast of Finland and represent the first observations of dormant calanoid eggs in the Baltic Sea. The highest egg densities were found at sediment depths between 4 and 8 cm. The hatching percentage varied between 0 and 90% in the different sediment layers and at different experimental temperatures (13, 16 and 19°C). Some nauplii emerged from the eggs extracted from sediment layers 9 to 10 cm beneath the surface layer and other nauplii emerged from eggs after 82 d of dark storage at 3°C. Light was not needed to trigger hatching; the nauplii were able to hatch in darkness when the eggs were resuspended in filtered seawater. Indirect evidence suggests that the marked spring peak of Acartia spp. nauplii seen in a monitoring data from the years 1973 to 1984 was derived from benthic eggs and not from spawning. The possible mechanisms for induction of hatching and the adaptive benefits of resting egg production for A. bifilosa are discussed.     

Life history strategy of a southern European population of brown shrimp (Crangon crangon L.): evidence for latitudinal changes in growth phenology and population dynamics

This study provides a comprehensive examination of the life cycle dynamics of the brown shrimp (Crangon crangon L.) in the Mondego estuary, Portugal, a habitat located near the southern edge of the range of this species in European waters. The phenology of all life stages was documented (from the occurrence of ovigerous females, developing embryos, planktonic larvae and benthic post-larvae), and migration patterns of larvae into and out of the estuary were examined. Temperature-dependent functions of egg and larval development were combined with data on field abundance to predict the timing and magnitude of occurrence of larvae and recruits. Compared to brown shrimp at higher latitudes, southern conspecifics grow slower, mature earlier and have smaller brood sizes, and larvae have a more protracted settlement period. The Mondego estuary, besides acting as nursery area, is a dynamic platform for C. crangon to use in different stages, sizes and seasons.     

Light regime in an Arctic fjord: a study related to stratospheric ozone depletion as a basis for determination of UV effects on algal growth

Solar radiation as a primary abiotic factor affecting productivity of seaweeds was monitored in the Arctic Kongsfjord on Spitsbergen from 1996 to 1998. The radiation was measured in air and underwater, with special emphasis on the UV-B (ultraviolet B, 280–320 nm) radiation, which may increase under conditions of stratospheric ozone depletion. The recorded irradiances were related to ozone concentrations measured concurrently in the atmosphere above the Kongsfjord with a balloon-carried ozone probe and by TOMS satellite. For comparison, an ozone index (a spectroradiometrically determined irradiance of a wavelength dependent on ozone concentration, standardized to a non-affected wavelength) was used to indicate the total ozone concentration present in the atmosphere. Weather conditions and, hence, solar irradiance measured at ground level were seldom stable throughout the study. UV-B irradiation was clearly dependent on the actual ozone concentration in the atmosphere with a maximal fluence rate of downward irradiance of 0.27 W m⁻² on the ground and a maximal daily fluence (radiation exposure) of 23.3 kJ m⁻². To characterize the water body, the light transmittance, temperature and salinity were monitored at two different locations: (1) at a sheltered shallow-water bay and (2) at a wave-exposed, deep-water location within the Kongsfjord. During the clearest water conditions in spring, the vertical attenuation coefficient (K _d) for photosynthetically active radiation (PAR) was 0.12 m⁻¹ and for UV-B 0.34 m⁻¹. In spring, coinciding with low temperatures and clear water conditions, the harmful UV radiation penetrated deeply into the water column and the threshold irradiance negatively affecting primary plant productivity was still found at about 5–6 m depth. The water body in spring was characterized as a Jerlov coastal water type 1. With increasing temperature in summer, snow layers and glacier ice melted, resulting in a high discharge of turbid fresh water into the fjord. This caused a stratification in the optical features, the salinity and temperature of the water body. During melt-water input, a turbid freshwater layer was formed above the more dense sea water. Under these conditions, light attenuation was stronger than defined for a Jerlov coastal water type 9. Solar radiation was strongly attenuated in the first few metres of the water column. Consequently, organisms in deeper water are protected against harmful UV-B radiation. In the surface water, turbidity decreased when rising tide caused an advection of clearer oceanic water. In the course of the summer season, salinity continuously decreased and water temperature increased particularly in shallow water regions. The impact of global climate change on the radiation conditions under water and its effects on primary production of seaweeds are discussed, since organisms in the eulittoral and upper sublittoral zones are affected by UV radiation throughout the polar day. In clearer water conditions during spring, this may also apply to organisms inhabiting greater depths. Received: 20 June 2000 / Accepted: 17 October 2000