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The Ecology of Parasitism
Published in Eric S. Loker, Bruce V. Hofkin, Parasitology, 2023
Eric S. Loker, Bruce V. Hofkin
With respect to density-independent factors, a variety of environmental factors like warming climates, ocean acidification, changing rainfall patterns and widescale pollution have profound, fluctuating and often unpredictable effects on parasite populations. We touch on these topics in several places throughout the book including Section 6.8 below and Chapters 1, 8 and 10. Here we will concentrate more on the operation of density-dependent mechanisms. Density-dependence has the inherent capacity to regulate parasite population sizes, such that the populations are more stable or vary in size in a predictable way. Parasite infrapopulations are a common topic of study and given they are typically aggregated, we would expect density-dependent factors to be triggered earliest and to act most strongly in larger infrapopulations. Aggregation in general is considered to be a factor that would dictate that density-dependent mechanisms come into play. What might such mechanisms be?
Population Dynamics
Published in Jacques Derek Charlwood, The Ecology of Malaria Vectors, 2019
Why populations are what they are at any given moment, in particular population dynamics in space and time, is the domain of ecology. There are a number of factors that will influence the population dynamics of animals in general. As their name implies, density-independent factors, especially meteorological factors, will act on the population irrespective of density, whilst density-dependent factors will have an increasing effect as numbers increase. In the absence of these, populations will grow up to the point that the environment can sustain them, the, so-called, carrying capacity. How much density-dependent factors, such as predators, operate depends on the stability of the environment. Thus, mosquitoes that breed in tree holes (a stable larval habitat) may be affected by density-dependent factors but others, such as A. gambiae s.l., that depend on temporary habitats are more affected by density-independent factors. Typical patterns of population fluctuations, with and without controlling factors, are shown in Figure 5.1.
Precision in the Specification of Ordinary Differential Equations and Parameter Estimation in Modeling Biological Processes
Published in Cliburn Chan, Michael G. Hudgens, Shein-Chung Chow, Quantitative Methods for HIV/AIDS Research, 2017
Assuming constant per capita decay rates, the decline (or growth) of a population is exponential, and depends on the size of the population in a linear way, that is, the decay in the population is proportional (via a constant) to the size of the population, and can be described with linear differential equations. In a density-dependent decay model, this proportionality is variable: the per capita decay rate depends on the size of the population, resulting in a model described by nonlinear differential equations which governs the population dynamics. Population dynamics models of this type are often used in population biology [18] as an alternative to long-term exponential growth or decay: density dependent homeostatic mechanisms are described for lymphocyte populations in mice [19] and humans [12,20,21]; time-dependent decay of a single infected-cell compartment was suggested as a possible alternative explanation for the biphasic decay pattern observed in HIV-1 decline by [8] and [22].
Inference for a discretized stochastic logistic differential equation and its application to biological growth
Published in Journal of Applied Statistics, 2023
F. Delgado-Vences, F. Baltazar-Larios, A. Ornelas Vargas, E. Morales-Bojórquez, V. H. Cruz-Escalona, C. Salomón Aguilar
Since the 1970s, the theory of SDEs has been widely used in the study of population ecology and population dynamics, to establish the bases for estimating parameters (e.g. intrinsic growth rate or value of r) in density-dependent iteroparous populations (see May [37], Braun [5], Golec and Sathananthan [23] and Xiping et al.[51]); further, the MLE method is essential in parameter estimation theory for SLDE applied to population growth (inputs for demographic studies) and somatic growth (biological/fisheries parameters to know the resilience of commercially important species) of bony fishes (Román-Román et al. [45], Shah [47] and Jurado-Molina et al. [31]) and elasmobranchs (Tovar- Ávila et al. [48], Guzmán-Castellanos et al. [24] and Cortés [12]).
Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish
Published in Critical Reviews in Toxicology, 2018
Kate S. Mintram, A. Ross Brown, Samuel K. Maynard, Pernille Thorbek, Charles R. Tyler
Population resilience determines the capacity for a population to withstand and recover from disturbances. The regulation of fish population numbers is primarily determined by compensatory density dependent mechanisms (Beverton and Holt 1957; Ricker 1987), which result in a slowed population growth at high densities, due to predation, disease and/or increased competition for resources, and conversely an increase in population growth at low densities, due to reduced competition, disease and predation (Rose et al. 2001). Life-history processes are considered to be density dependent if their rates change as a result of the density (or number) of individuals in a population, e.g. individual growth, mortality, or reproduction. Population dynamics studies (variation in population numbers over time), indicate that the majority of wildlife populations, including fish, are regulated by density dependent biotic interactions (Brook and Bradshaw 2006). This regulation underlies the management of fish populations (Rose et al. 2001) and is exploited throughout fisheries worldwide to permit sustainable yields.