Nine things to keep in mind about mathematical modelling in ecology and evolution

Joshi, Amitabh

doi:10.1007/s12038-022-00260-z

Cited by 8 publications

(7 citation statements)

References 36 publications

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“…consumption rate) could further be used to understand the role of trait variation. Such empirical validation, either confirming or contradicting our theoretical predictions, would bring in the much needed dialogue between theory and experiment (Haller, 2014;Otto & Rosales, 2020;Joshi, 2022) as well as provide tangible predictions for future studies directly aimed at policy making.…”

Section: Effects Of Eco-evolutionary Dynamicssupporting

confidence: 54%

“…Furthermore, HL can influence evolution of species either directly by differential loss of specific types of habitats and associated changes in selection pressures or indirectly by reducing population sizes and thereby also reducing genetic diversity (McClure et al, 2008). A reduction in genetic diversity can even trigger an extinction vortex if the populations become too small (Nabutanyi & Wittmann, 2021, 2022. HL can also influence evolution, for example, of dispersal distance such that removal of entire patches would select for reduced dispersal, but degradation (reducing carrying capacity) of patches would select for longer dispersal in a multi-patch landscape (North et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale Effects of Habitat Loss and the Role of Trait Variation

Bagawade

Benthem

Wittmann

2023

Preprint

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Habitat loss (HL) is a major cause of species extinctions. Although effects of HL beyond the directly impacted area have been previously observed, they are not very well understood, especially in an eco-evolutionary context. To start filling this gap, we study a two-patch deterministic consumer-resource model, with one of the patches experiencing loss of resources. Our model allows foraging and mating within a patch as well as between patches. We then introduce heritable variation in consumer traits to investigate eco-evolutionary dynamics and compare results with constant or no trait variation scenarios. Our results show that HL indeed reduces consumer densities in the neighboring patch, but when the resources are overexploited, HL in one patch can increase the consumer densities in the neighbouring patch. Yet at the landscape scale, the effect of HL on consumer densities is consistently negative. In presence of HL, patch isolation has positive effects on consumer density in the patch experiencing HL and mostly negative effects on the neighbouring patch. The landscape level pattern depends on which of these effects are dominant at the local scale. Evolution always increased resistance of consumers in the affected patch to HL, with varied effects at the landscape level. Finally, we also show a possibility of landscape level consumer extinction due to HL in a local patch when the cross-patch dependence is high, and foraging and mating preferences are coupled. Eco-evolutionary dynamics can rescue consumers from such extinction in some cases if their death rates are sufficiently small. Our findings show that HL at a local scale can affect the neighbouring patch and the landscape as a whole, and that heritable trait variation can provide some resistance against HL. We thus suggest joint consideration of multiple spatial scales and trait variation when assessing and predicting the impacts of HL.

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Section: Effects Of Eco-evolutionary Dynamicssupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Multi-scale Effects of Habitat Loss and the Role of Trait Variation

Bagawade

Benthem

Wittmann

2023

Preprint

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“…We know from previous work that the dynamics of single-vial populations of Drosophila in an LH food regime are captured reasonably well by the Ricker (1954) model (Sheeba and Joshi 1998). At the same time, there is no reason to believe that the responses of Drosophila population dynamics to various food or selection regimes are limited by the functional form of any simple population growth model (Tung et al 2019, Joshi 2022). Consequently, we examined these attributes in different ways, some taking the Ricker model as the basis, while others were more empirical and model-free.…”

Section: Methodsmentioning

confidence: 99%

Density-dependent selection at low food levels leads to the evolution of population stability in Drosophila melanogaster even without a clear r-K trade-off

Pandey

Joshi

2022

Preprint

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Density-dependent selection, especially together with r-K trade-offs, has been one of the most plausible suggested mechanisms for the evolution of population stability. However, experimental support for this explanation has been both meagre and mixed. One study with Drosophila melanogaster yielded no evidence for populations adapted to chronic larval crowding having also evolved greater population stability. Another study, on D. ananassae, suggested that populations adapted to larval crowding evolved both greater constancy and persistence stability, and the data also suggested an r-K trade-off in those populations, though the evidence for the latter was not conclusive. Moreover, theoretical work suggested that density-dependent selection could result in the evolution of greater population stability, even in the absence of an r-K trade-off. Here, we show that populations of D. melanogaster, selected for adaptation to larval crowding at very low food amounts per vial, evolve enhanced constancy and persistence stability. The enhanced population stability in the crowding-adapted populations seems to have evolved through the increased equlibrium size (K) and reduced sensitivity of realized population growth rates to density (α).There was no clear evidence for reduced intrinsic population growth rate (r) in the more stable crowding-adapted populations. Our study adds to the growing evidence in support of the hypothesis that population stability can evolve in response to density-dependent selection through the evolution of certain life-history traits that are associated with higher K and less negative α. We discuss our results in the light of previous work, and suggest that a model-free framework might be of great heuristic value in understanding the evolution of population stability through changes in the density-sensitivity of life-history traits, whether or not these changes result from density-dependent selection.

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“…Modeling gene regulatory networks is qualitatively different than modeling physical systems like those in celestial mechanics and ecology [25]. While the behavior of the latter is described by equations stemming from physical laws and whose parameters are well defined measurable physical quantities, the models of GRNs describe dynamics on a spatial scales where the first principle models do not apply.…”

Section: Discussionmentioning

confidence: 99%

Assessing biological network dynamics: Comparing numerical simulations with analytical decomposition of parameter space

Hari

Duncan

Ibrahim

et al. 2022

Preprint

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Mathematical modeling of the emergent dynamics of gene regulatory networks (GRN) faces a double challenge of (a) dependence of model dynamics on parameters, and (b) lack of reliable experimentally determined parameters. In this paper we compare two complementary approaches for describing GRN dynamics across unknown parameters: (1) parameter sampling and resulting ensemble statistics used by RACIPE (RAndom CIrcuit PErturbation), and (2) use of rigorous analysis of combinatorial approximation of the ODE models by DSGRN (Dynamic Signatures Generated by Regulatory Networks). We find a very good agreement between RACIPE simulation and DSGRN predictions for four different 2- and 3-node networks typically observed in cellular decision making. This observation is remarkable since the DSGRN approach assumes that the Hill coefficients of the models are very high while RACIPE assumes the values in the range 1 to 6. Thus DSGRN parameter domains, explicitly defined by inequalities between systems parameters, are highly predictive of ODE model dynamics within a biologically reasonable range of parameters.

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Nine things to keep in mind about mathematical modelling in ecology and evolution

Cited by 8 publications

References 36 publications

Multi-scale Effects of Habitat Loss and the Role of Trait Variation

Multi-scale Effects of Habitat Loss and the Role of Trait Variation

Density-dependent selection at low food levels leads to the evolution of population stability in Drosophila melanogaster even without a clear r-K trade-off

Assessing biological network dynamics: Comparing numerical simulations with analytical decomposition of parameter space

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