Initial Population Size Research Articles

Evolutionary game analysis of factors influencing green innovation in Enterprises under environmental governance constraints

The key to controlling environmental pollution is to promote green innovation in relevant enterprises and achieve a healthy development of the environmental governance system. This paper constructs a tripartite evolutionary game model of environmental protection enterprises, polluting enterprises, and governments, and conducts in-depth research on the influencing factors that promote green innovation in two types of enterprises. MATLAB software is used to analyze the impact of different degrees of influencing variables on system evolution. It has found that (1) increasing the intensity of environmental governance and the level of innovation subsidies by the government can effectively promote green innovation in both types of enterprises. (2) The varying degrees of innovation compensation from polluting enterprises to environmental protection enterprises have a significant impact on system evolution. (3) The initial intention and population size of two types of enterprise entities will have a significant impact on system evolution. In the initial state, subjects with more green innovation are less willing to change their strategies during the evolution process, while the willingness of the other party to green innovation will be suppressed.

What is the risk of overcollecting for translocation? An opportunistic assessment of a wingless grasshopper

AbstractTranslocation is an increasingly used tool in conservation management, but there is a risk that source populations are overcollected. The risk depends critically on the detection probability and the source population size. We quantified this risk for a wingless grasshopper population in a patch of remnant habitat in suburban Melbourne that was condemned to be cleared for housing development. We collected ∼2000 grasshoppers in five samples spread over 1 month and used the results to estimate the initial population size (∼3400) with high confidence. Despite our perception of substantially depleting the population, we removed only an estimated 60%, and this relatively high fecundity (∼50 eggs per lifetime) annual species had recovered by the following year to near its original density. Wild‐to‐wild translocation is likely to be a low‐cost and effective strategy in the conservation of many invertebrates, and our findings highlight the feasibility of using natural source populations.

Controlling smoking: A smoking epidemic model with different smoking degrees in deterministic and stochastic environments

Engaging in smoking not only leads to substantial health risks but also imposes considerable financial burdens. To deepen our understanding of the mechanisms behind smoking transmission and to address the tobacco epidemic, we examined a five-dimensional smoking epidemic model that accounts for different degrees of smoking under both deterministic and stochastic conditions. In the deterministic case, we determine the basic reproduction number, analyze the stability of equilibria with and without smoking, and investigate the existence of saddle–node bifurcation. Our analysis reveals that the basic reproduction number cannot completely determine the existence of smoking, and the model possesses bistability, indicating its dynamic is susceptible to interference from environmental noises. In the stochastic case, we establish sufficient conditions for the ergodic stationary distribution and the elimination of smokers by constructing appropriate Lyapunov functions. Numerical simulations suggest that the effects of inevitable random fluctuations in the natural environment on controlling the smoking epidemic may be beneficial, harmful, or negligible, which are closely related to the noise intensities, initial smoking population sizes, and the effective exposure rate of smoking transmission (β). Given the uncontrollable nature of environmental random effects, effective smoking control strategies can be achieved by: (1) accurate monitoring of initial smoking population sizes, and (2) implementing effective measures to reduce β. Therefore, it is both effective and feasible to implement a complete set of strong MPOWER measures to control smoking prevalence.

Optimal allocation system of urban land use types under multi-objective constraints

Abstract This paper arranges suitable land use types according to the quality characteristics of land parcel units, obtains the objective function of optimal land use allocation, and constructs a multi-objective constraint system in the process of land use planning. The integer vector is used to encode the land use types and represent the spatial distribution of land use, combined with the particle swarm algorithm to calculate its adaptability, speed and position update based on the initial population size and construct the land use optimization allocation model based on the constraint system. The particle swarm algorithm is used to explore the geographic environment and climate resources, the economy of the natural economy of the study area, and Landsat TM remote sensing image technology is used to obtain the initial data on the land use of the study area and empirical analysis is carried out on the optimization of the allocation of urban land use in the study area. The results show that the algorithm converges faster and achieves global convergence when the parameter is set to the fourth state, and the comprehensive suitability evaluation function achieves global convergence at generation 73, with a value of 1.64E+08, which is faster than the convergence of parameter settings 1 and 2 as well as 3. The land types that increase in area include garden land, forest land, transportation land, and water and water conservancy facilities land, which increase by 0.8%, 2.84%, 0.14%, and 0.8%, respectively, which protects the arable land and restricts the expansion of the construction land in terms of the quantitative structure. This study enriches the content and methods of optimizing land use space allocation, which helps to rationalize the use of land resources.

Research on the Cultivation Mechanism of Innovation and Entrepreneurship Ability of Excellent Engineers

Abstract In this paper, after using PSO algorithm to encode the information on innovation and entrepreneurship education resources in universities, N particle is randomly generated to form the initial population, and it is also necessary to continuously update the particles to carry out the adjustment of the initial population size. The mathematical model of hard constraints of all courses of innovation and entrepreneurship teaching is obtained through the fitness function, on the basis of which, according to the objective function of innovation and entrepreneurship education resources in universities, each kind of resource is effectively allocated to the most adapted aspects, so as to realize the optimal allocation of innovation and entrepreneurship education resources in universities. Based on the current situation of innovation and entrepreneurship education at the Polytechnic Institute of Zhejiang University, the research hypothesis and research design are proposed, and the utilization efficiency and allocation efficiency of innovation and entrepreneurship education resources are confirmed and analyzed. The results show that before the experiment, there was a large difference in resource allocation efficiency between groups; the minimum value was 0.123, and the maximum value was 0.187. After optimization, the allocation efficiency is 0.188, with an average growth rate of 19.55%. That is, the PSO algorithm can achieve the optimization of innovation and entrepreneurship education resource allocation at the Polytechnic Institute of Zhejiang University. The four dimensions of innovation and entrepreneurship education: theoretical education, practical education, teacher quality, educational support and initiative personality of the three dimensions, motivation, change and resilience are in the presence of each other in the middle of the work, and the correlation coefficient is concentrated in the role of 0.5 on average. This study further stimulates the students passion for innovation and entrepreneurship, which is of great significance to the cultivation of students innovation and entrepreneurship abilities.

Accelerated Organic Crystal Structure Prediction with Genetic Algorithms and Machine Learning.

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based only on its molecular composition. Our tool uses neural network potentials to allow for efficient screening and structural relaxation of generated crystal candidates. Our pipeline consists of two distinct stages: random search, whereby crystal candidates are randomly generated and screened, and optimization, where a genetic algorithm (GA) optimizes this screened population. We assess the performance of each stage of our pipeline on 21 molecules taken from the Cambridge Crystallographic Data Centre's CSP blind tests. We show that random search alone yields matches for ≈50% of targets. We then validate the potential of our full pipeline, making use of the GA to optimize the root-mean-square deviation between crystal candidates and the experimentally derived structure. With this approach, we are able to find matches for ≈80% of candidates with 10-100 times smaller initial population sizes than when using random search. Lastly, we run our full pipeline with an ANI model that is trained on a small data set of molecules extracted from crystal structures in the Cambridge Structural Database, generating ≈60% of targets. By leveraging machine learning models trained to predict energies at the density functional theory level, our pipeline has the potential to approach the accuracy of ab initio methods and the efficiency of empirical force fields.

Bistability in modified Holling II response model with harvesting and Allee effect: Exploring transitions in a noisy environment

Here, we explore the complex dynamics of a predator–prey system with a modified Holling type II functional response and the Allee effect that accounts for a reduced hunting efficiency due to intra-predator interactions. Besides the growth due to focal prey, the predator population follows a Beverton–Holt-like reproduction due to the alternative food sources. The model also considers the impact of harvesting on the predator population, reflecting economic interests in biological resource exploitation. We systematically investigate key aspects, including solution’s positivity, system’s equilibria, stability analysis, and various type of bifurcation. The model is extended to its stochastic version; conditions for the extinction as well as persistence of species are derived. All the theoretical findings are validated with numerical examples. In the deterministic scenario, the Allee effect, harvesting intensity, and the growth in predators due to external food sources exhibit intricate dynamics, such as Hopf, saddle–node (LP) and transcritical bifurcations; we also observe bistable behavior of the system. Notably, less growth in predators due to the other food sources results in extinction, while low intensity of Allee effect leads to bistability, where initial population size matters. A higher Allee effect reduces the region of stability generated by the harvesting effort and the predators’ growth due to additional foods. The stochastic system uncovers diverse transitions in scenarios with high noise intensity, affecting bistability occurred for lower noise intensity. Overall, this study provides valuable insights into predator–prey dynamics, with practical implications for the ecological conservation and resource management.

The possible impact of escaped captive American mink (Neogale vison) on the population of feral mink in Denmark.

The Danish feral mink (Neogale vison) population can be divided into wild-born and captive-born mink newly escaped from a farm. The impact of the captive-born mink on the population of feral population is unknown. Captive-born mink has lately been estimated to make up 25-30% of the feral mink population. In December 2020 Danish mink farms were decommissioned until January 2023. The aim of this study was to: 1) Examine whether a supplementation of farmed mink into the feral mink population influence the population growth and extinction rate of the feral mink, 2) Investigate which parameters affect the viability in feral mink populations the most. The age and mortality of 351 mink and the reproduction of 85 adult females culled by hunters from 2019-2022 were determined in three distinct geographic areas of Denmark (Jutland, Zealand, and Bornholm). VORTEX simulations were used to model the population viability and to simulate the impact of a supplementation of captive-born mink into the wild population. Simulations show that changes by 30% in the parameters: fecundity, percentages of breeding females and mortality influenced population size influenced the final population size significantly. The initial population size and inbreeding did not affect the population growth significantly. The simulations showed that the mink population in the regions of Jutland and Zealand could go extinct within 15 to 30 years without any supplementation of captive-born mink to the feral population. The population on Bornholm will however remain stable with current levels of mortality and reproduction even without supplementation of captive mink.

Trouble in the trawls: Is bycatch in trawl fisheries preventing the recovery of sawfish? A case study using the US population of smalltooth sawfish, Pristis pectinata

All five species of sawfish (Family Pristidae), are among the most threatened families of elasmobranchs, and face significant threats from fishing, in particular trawl fisheries, and habitat loss. Unfortunately, there is little data on the level of sawfish taken in trawl fisheries outside Australia and the United States and case studies from these areas can provide a “risk analysis” for populations elsewhere. In the United States, bycatch risk for smalltooth sawfish is significantly higher for the southeast shrimp trawl fishery than all other fisheries assessed. Using new estimates of life history and population size, an updated population viability model was developed and trajectories using different scenarios of initial population sizes, fishery catches and post-release mortality were projected for 100 years. The simulated population trajectories for the assumed initial population sizes and fishing mortality ranged between population extinction, quasi-extinction, to a slight reduction in population size and in some cases the population continuing to recover. The most pessimistic scenarios were when the initial population was lowest and post-release mortality in the shrimp trawl fishery was highest. Quasi-extinction for some scenarios was between 6.9 and 22.8 years. While some scenarios suggest that smalltooth sawfish still can recover despite the potential for shrimp trawl fishing mortality, key input variables for these optimistic scenarios is the initial population size and the true level of fishing mortality. This uncertainty highlights the importance of improving our understanding of sawfish life history, captures in fisheries and their associated post-release mortality.

Population viability analysis informs Western Grasswren translocation: Multi-population sourcing of 112 founder individuals needed to meet success criteria

Abstract Conservation translocations have become an increasingly popular method to restore or secure vulnerable populations. However, translocations greatly vary in success. The use of population viability analysis (PVA) may increase the likelihood of meeting translocation goals. However, the quality of PVAs to inform translocations is dependent on the availability of ecological data and clear translocation objectives to guide them. Here, we used PVAs to inform the planned conservation translocation of the Western Grasswren (Amytornis textilis textilis) from mainland Shark Bay onto Dirk Hartog Island, Western Australia. A range of translocation scenarios were modelled and scored against success criteria as determined by translocation objectives. Simulations of 20-yr outcomes found that a minimum founder population of 112 individuals meet all success criteria. PVA supported sourcing individuals from 2 subpopulations to maximize genetic diversity. No impact to source populations was detected for the proposed harvest quantities despite conservative estimates of initial source population sizes. Here we demonstrate that creating clear, measurable objectives alongside a PVA lessens ambiguity about which translocation scenarios could be viable. In doing so, we have identified the minimum translocation sizes needed to maintain genetic diversity and population growth, thus increasing the likelihood of translocation success without impacting the source population.

Competitive interactions facilitate resistance development against antimicrobials.

While the evolution of antimicrobial resistance is well studied in free-living bacteria, information on resistance development in dense and diverse biofilm communities is largely lacking. Therefore, we explored how the social interactions in a duo-species biofilm composed of the brewery isolates Pseudomonas rhodesiae and Raoultella terrigena influence the adaptation to the broad-spectrum antimicrobial sulfathiazole. Previously, we showed that the competition between these brewery isolates enhances the antimicrobial tolerance of P. rhodesiae. Here, we found that this enhanced tolerance in duo-species biofilms is associated with a strongly increased antimicrobial resistance development in P. rhodesiae. Whereas P. rhodesiae was not able to evolve resistance against sulfathiazole in monospecies conditions, it rapidly evolved resistance in the majority of the duo-species communities. Although the initial presence of R. terrigena was thus required for P. rhodesiae to acquire resistance, the resistance mechanisms did not depend on the presence of R. terrigena. Whole genome sequencing of resistant P. rhodesiae clones showed no clear mutational hot spots. This indicates that the acquired resistance phenotype depends on complex interactions between low-frequency mutations in the genetic background of the strains. We hypothesize that the increased tolerance in duo-species conditions promotes resistance by enhancing the selection of partially resistant mutants and opening up novel evolutionary trajectories that enable such genetic interactions. This hypothesis is reinforced by experimentally excluding potential effects of increased initial population size, enhanced mutation rate, and horizontal gene transfer. Altogether, our observations suggest that the community mode of life and the social interactions therein strongly affect the accessible evolutionary pathways toward antimicrobial resistance.IMPORTANCEAntimicrobial resistance is one of the most studied bacterial properties due to its enormous clinical and industrial relevance; however, most research focuses on resistance development of a single species in isolation. In the present study, we showed that resistance evolution of brewery isolates can differ greatly between single- and mixed-species conditions. Specifically, we observed that the development of antimicrobial resistance in certain species can be significantly enhanced in co-culture as compared to the single-species conditions. Overall, the current study emphasizes the need of considering the within bacterial interactions in microbial communities when evaluating antimicrobial treatments and resistance evolution.

Treatment of infected predators under the influence of fear-induced refuge

In this research, we delve into the dynamics of an infected predator–prey system in the presence of fear and refuge, presenting a novel inclusion of treatment for infected individuals in this type of model. Through our analytical efforts, we establish a significant reproduction number that holds a pivotal role in determining disease extinction or persistence within the system. A noteworthy threshold value for this reproduction number delineates a boundary below which the infected population cannot endure in the system. It’s important to note that a range of reproduction numbers leads to both disease-free and endemic scenarios, yet the stability of these situations is contingent upon the initial population sizes. Furthermore, our investigation extends to the exploration of various types of bifurcation-namely, Backward, Saddle-node, and Hopf bifurcations. These findings unravel the intricate and diverse dynamics of the system. Of particular significance is the derivation of an optimal control policy for treatment, augmenting the practical utility of our work. The robustness of our analytical findings is fortified through meticulous verification via numerical simulations. These simulations not only bolster the credibility of our analytical results but also enhance their accessibility. Our study unveils that fear, refuge, and treatment possess individual capabilities to eradicate the disease from the system. Notably, increasing levels of fear and refuge exert a passive influence on the elimination of the infected population, whereas treatment wields an active influence-a crucial insight that bolsters the foundation of our model. Furthermore, our investigation uncovers a spectrum of system dynamics including bistability, one-period, two-period, and multi-period/chaotic behavior. These discoveries contribute to a profound enrichment of the system’s dynamic landscape.

Avoiding bias in estimates of population size for translocation management.

Mark-recapture surveys are commonly used to monitor translocated populations globally. Data gathered are then used to estimate demographic parameters, such as abundance and survival, using Jolly-Seber (JS) models. However, in translocated populations initial population size is known and failure to account for this may bias parameter estimates, which are important for informing conservation decisions during population establishment. Here, we provide methods to account for known initial population size in JS models by incorporating a separate component likelihood for translocated individuals, using a maximum-likelihood estimation, with models that can be fitted using either R or MATLAB. We use simulated data and a case study of a threatened lizard species with low capture probability to demonstrate that unconstrained JS models may overestimate the size of translocated populations, especially in the early stages of post-release monitoring. Our approach corrects this bias; we use our simulations to demonstrate that overestimates of population size between 78% and 130% can occur in the unconstrained JS models when the detection probability is below 0.3 compared to 1%-8.9% for our constrained model. Our case study did not show an overestimate; however accounting for the initial population size greatly reduced error in all parameter estimates and prevented boundary estimates. Adopting the corrected JS model for translocations will help managers to obtain more robust estimates of the population sizes of translocated animals, better informing future management including reinforcement decisions, and ultimately improving translocation success.

Northern Europe’s suitability for offshore European flat oyster (Ostrea edulis) habitat restoration based on population dynamics

IntroductionEuropean and member state legislation encourage the sustainable development of offshore environments, with the restoration or creation of flat oyster (Ostrea edulis) habitats offering potential solutions to enhance biodiversity and provide ecosystem services. The site selection and identification of suitable habitats for flat oyster habitat restoration projects remains a significant knowledge gap.MethodsBy combining seabed substrate information with a coupled population (Dynamic Energy Budget - Individual-Based Models) and particle tracking model (for larvae dispersal), critical insights can be gained into the spatial distribution of suitability indicators such as population growth, fitness, reproduction, and self-recruitment. By applying this model to the English Channel and the North Sea over a ten-year period, suitable locations for flat oyster habitat restoration, restorative aquaculture, or oyster-related nature-inclusive designs can be identified. Comparing historical oyster bed locations with model outputs offers insights into why these locations were suitable for oyster bed development and allows for validation of the proposed approach.Results and discussionCoastal and nearshore environments are generally more suitable for flat oyster habitat restoration, and populations will grow more quickly in these areas. Offshore restoration in the North Sea presents challenges if it relies solely on self-recruitment. Besides site selection purposes, the model can be used to evaluate the effect of management strategies (e.g., initial population size) or environmental pressures (e.g., climate change, pollution) on restorations success.

Efficient Evaluation of Incident Power Density by Millimeter-Wave MIMO User Equipment Using Vectorized Field Superposition and Stochastic Population Optimizers

In this work, stochastic population optimizers are applied with vectorized field values to determine the peak exposure of user equipment (UE) installed with a multiple-input multiple-output (MIMO) antenna operating at 28 GHz. This problem presents a significant challenge due to the difficulty in evaluating all possible configurations of the input values. By aids of optimization on initial population size as well as the sampling spacing, two optimizers incorporating variable population size exhibit good robustness and efficiency, i.e., an error of 1% compared to the results by Monte Carlo (MC) simulation of 1 000 000 times. A reduction in the simulation time of 90% compared to MC simulation of 10 000 times. The proposed method demonstrates its performance in evaluating exposure at both planar and nonplanar surface according to the standards. Besides, the method can be applied in postprocessing of the numerical simulation and the measured data for maximized spatial-average power density. The study provides a new and easy to implement method for efficiently characterizing the maximum exposure from millimeter wave MIMO UE.

Influence of silvicultural practices in northern hardwood forests on a long-lived perennial herb, Trillium cernuum L.

Contemporary and predicted declines in tree species diversity and forest resilience have prompted renewed interest in even-aged systems and/or site preparation to overcome bottlenecks to tree recruitment or facilitate range expansion of future-adapted species. The impact of this intensification on the herbaceous layer in forests traditionally managed with uneven-aged systems, however, is unclear, especially for uncommon dispersal limited species with heterogenous distributions. We leveraged a large-scale experiment (the Northern Hardwood Silvicultural Experiment to Enhance Diversity) to investigate the response of Trillium cernuum L., a somewhat uncommon and heterogeneously distributed non-clonal herb in our study system, to a gradient of canopy removal and soil disturbance. We monitored 16 small populations from 2015 (the year prior to treatment) to 2019 (3-years post treatment). Our results suggest that initial population size and stage structure were inextricably coupled with T. cernuum response. Independent of treatment, T. cernuum abundance and flowering generally increased over time commensurate with initial population size. Moreover, our study highlights the confounding effect of deer herbivory, which increased significantly following treatment. Collectively, our findings suggest that T. cernuum populations were resilient to canopy disturbance associated with single-tree selection and shelterwood harvests and the levels of scarification applied as part of our study. Higher levels of site impact or other site preparation methods such as herbicides will likely have greater impacts and warrant further investigation. Our results also suggest that directly monitoring populations of interest may be necessary to quantify treatment effects for uncommon and/or heterogenous species that are missed with common plot-based sampling designs or of conservation concern.

Modeling population growth of a proto-city: A new urban accretion growth hypothesis and its P-CPAG model

The population growth of a proto-city (P–C, the initial stage of city-forming) is fundamental for shaping the subsequent pattern of population growth in city evolution. This study proposed a mathematical model, the P–C Population Accretion Growth (P-CPAG) model, to simulate key processes of population growth over a P–C period, based on the Urban Accretion Growth hypothesis (the UAG hypothesis). In the P-CPAG model, several parameters, e.g., natural increase rate of population(k), accretion rate (ρ), accretion radius(r), and initial population size (Pt0o), are vital for population growth. In the model examination, we determined the potential value for all parameters by the universal laws and the collected literature about the worldwide ancient cities. Based on observation and evaluation of 64 simulation scenarios, a promising plan of optimal parameters was suggested, that is, k = 0.008, ρ = 0.01, kρ = 0.003, Pt0o = 2000, Pt0i = 3.6, r = 5, N = 200000, Ni = 300. The proposed P-CPAG model sheds new light on population simulation in the critical but limited-mentioned P–C stage and has the potential to simulate population growth in other periods of city evolution. The unique perspectives on urban accretion growth and the P-CPAG model are meaningful for understanding the complicated and mysterious history of cities' evolution back about 5000 years ago.

Population Rescue through an Increase in the Selfing Rate under Pollen Limitation: Plasticity versus Evolution.

AbstractIncreased rates of self-fertilization offer reproductive assurance when plant populations experience pollen limitation, but self-fertilization may reduce fitness by exposing deleterious mutations. If an environmental change responsible for pollen limitation also induces plastic mating system shifts toward self-pollination, the reproductive assurance benefit and inbreeding depression cost of increased self-fertilization occur immediately, while the benefit and cost happen more gradually when increased self-fertilization occur through evolution. I built eco-evolutionary models to explore the demographic and genetic conditions in which higher self-fertilization by plasticity and/or evolution rescues populations, following deficits due to a sudden onset of pollen limitation. Rescue is most likely under an intermediate level of selfing rate increase, either through plasticity or evolution, and this critical level of selfing rate increase is higher under stronger pollen limitation. Generally, rescue is more likely through plasticity than through evolution. Under weak pollen limitation, rescue by enhanced self-fertilization may mainly occur through purging of deleterious mutations rather than reproductive assurance. The selfing rate increase conferring the highest rescue probability is lower when the initial population size is smaller. This article shows the importance of plasticity during plant population rescue and offers insights for future studies of the evolution of mating system plasticity.

Transient population dynamics drive the spread of invasive wild pigs and reveal impacts of management in North America

Invasion of nonindigenous species is considered one of the most urgent problems affecting native ecosystems and agricultural systems. Mechanistic models that account for short-term population dynamics can improve prediction because they incorporate differing demographic processes that link the environmental conditions of a spatial location explicitly with the invasion process. Yet short-term population dynamics are rarely accounted for in spatial models of invasive species spread.Accounting for transient (short-term) population dynamics that arise from the interaction of age structure and vital rates, we predict the stochastic population growth rate and establishment probability of wild pigs following introduction into any location in North America. Established ecological theory suggests that the rate of spatial spread is proportional to population growth rate. Using observed geographic distribution data for wild pigs we calculated geographic spread rates (watersheds/year) from 1982 to 2021. We investigated if observed spread rates increased in watersheds with higher stochastic population growth rates. Stochastic population growth rate and establishment probability of wild pigs increased with increasing initial population (propagule) size and length of establishment time. Areas along the Mississippi, Ohio, and lower portions of the Missouri river drainages had the highest probability of wild pig establishment with many regions having probabilities close to 1. Spread rates demonstrated strong spatial heterogeneity with the greatest rates of spread (5.8 watersheds/year) occurring from 2008 to 2013 prior to the establishment of a National wild pig control program in 2013. Spread rates declined 82% (0.57 watersheds/year) in the period from 2013 to 2021 compared to the period from 1982 to 2013. We found significant positive associations among stochastic population growth rate and observed geographic rates of spread. Stochastic population growth rate explained a large amount of variation (79.3–92.1%) in annual rate of watershed spread of wild pigs. Our predicted probabilities of establishment and population growth can be used to inform surveillance and control efforts to reduce the potential for establishment and spread of wild pigs.

Theoretical investigation of the dependence of population parameters on initial population size

In a series of experiments with yeast, classical dynamical models were fitted to populations that differed only in their initial population size (Pylvänäinen 2005). The results revealed a surprising dependence between estimated growth rate and initial population size. Perceived as an artefact, this undesired relationship was tentatively removed by an ad-hoc procedure. This strategy reflects the usual approach of population models in which parameters are not considered to depend on initial conditions. However, our analysis reveals that the observed relationship between estimated growth rate and initial population size is unavoidable when the dimension of a system is reduced. For the present case, the two-dimensional food-yeast system was reduced to a model for yeast only. The consequence of system reduction questions our conception of one-dimensional population models.