Topic
Threshold population
About: Threshold population is a research topic. Over the lifetime, 17 publications have been published within this topic receiving 395 citations.
Papers
TL;DR: For a large class of population dynamics, the optimal strategy is to harvest all individuals above a threshold population size, with no harvest below the threshold as discussed by the authors, regardless of the form of expected dynamics or the magnitude of stochasticity.
Abstract: Commercially important species often are overexploited, and many endan- gered mammals and birds are threatened by hunting and international trade. To sustain biological resources requires harvesting strategies that maximize yield while accounting for stochastic dynamics, uncertainty, and risk of resource collapse or extinction. For a large class of population dynamics, the optimal strategy is to harvest all individuals above a threshold population size, with no harvest below the threshold. Maximizing the expected cumulative harvest before extinction puts the optimal threshold at carrying capacity, re- gardless of the form of expected dynamics or the magnitude of stochasticity. Maximizing the mean annual yield lowers the optimal threshold, which then depends on the form of expected dynamics and the magnitude of stochasticity. Uncertainty in estimated population sizes increases the threshold, and with large uncertainty, the optimal strategy is proportional threshold harvesting, involving harvest of only a fraction of the excess in estimated pop- ulation above the threshold. The theoretical justification for the common strategy of a constant harvest rate is extremely weak in comparison to that for optimal threshold strat- egies. Thresholds are a necessary feature of any harvesting strategy with the objective of minimizing risks of resource depletion or extinction, while optimizing yields.
207 citations
TL;DR: Based on theories about the influences of urban economic structure on intensive land use, this article analyzed the impacts of two main types of urban economy structure in China (specialized economy and diversified economy) on intensive urban land use using spatial panel techniques and large-scale urban panel data.
80 citations
TL;DR: It is shown that ecological parameters that may be unimportant in conventional models that do not account for the endogeneity of the host-density threshold are potentially important when host density threshold is recognized as endogenous.
Abstract: . We investigate wildlife disease management, in a bioeconomic framework, when the wildlife host is valuable and disease transmission is density-dependent. Disease prevalence is reduced in density-dependent models whenever the population is harvested below a host-density threshold a threshold population density below which disease prevalence declines and above which a disease becomes epidemic. In conventional models, the threshold is an exogenous function of disease parameters. We consider this case and find a steady state with positive disease prevalence to be optimal. Next, we consider a case in which disease dynamics are affected by both population controls and changes in human-environmental interactions. The host-density threshold is endogenous in this case. That is, the manager does not simply manage the population relative to the threshold, but rather manages both the population and the threshold. The optimal threshold depends on the economic and ecological trade-offs arising from the jointly-determined system. Accounting for this endogene-ity can lead to reduced disease prevalence rates and higher population levels. Additionally, we show that ecological parameters that may be unimportant in conventional models that do not account for the endogeneity of the host-density threshold are potentially important when host density threshold is recognized as endogenous.
48 citations
TL;DR: The cause of threshold behaviour is explained, and a phenomenological approach for estimating the threshold population size is presented, which is found to be linearly proportional to the inverse of the square of the system's signal-to-noise ratio.
Abstract: We study the performance of the maximum likelihood (ML) method in population decoding as a function of the population size. Assuming uncorrelated noise in neural responses, the ML performance, quantified by the expected square difference between the estimated and the actual quantity, follows closely the optimal Cramer-Rao bound, provided that the population size is sufficiently large. However, when the population size decreases below a certain threshold, the performance of the ML method undergoes a rapid deterioration, experiencing a large deviation from the optimal bound. We explain the cause of such threshold behaviour, and present a phenomenological approach for estimating the threshold population size, which is found to be linearly proportional to the inverse of the square of the system's signal-to-noise ratio. If the ML method is used by neural systems, we expect the number of neurons involved in population coding to be above this threshold.
32 citations
TL;DR: A model of discrete-generations population dynamics originally due to M. H. Williamson is analyzed, and protected polymorphism is possible in an asexual or haploid population, but only if the genotype which would be lost if there were no K-selection has the greater population fluctuation when present alone.
Abstract: A model of discrete-generations population dynamics originally due to M. H. Williamson is analyzed. In this model, the negative effect of population density acts suddenly and completely as the population size passes a threshold. The model almost always yields chaotic fluctuation of population size. When it does, this chaos ensues whatever the initial population size. The average population cycle length is found, as well as the distribution of population sizes over time. One can readily analyze r- and K-selection in this model. Natural selection will favor cycles with more time spent above the threshold population size, and will favor increase of the threshold. When r- and K-selection oppose each other, protected polymorphism is possible in an asexual or haploid population, but only if the genotype which would be lost if there were no K-selection has the greater population fluctuation when present alone. Conditions for protected polymorphism in a two-allele diploid population are also given.
27 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2020 | 2 |
| 2019 | 1 |
| 2017 | 1 |
| 2013 | 1 |
| 2010 | 1 |
| 2009 | 1 |