Relative contributions of fixed and dynamic heterogeneity to variation in lifetime reproductive success in kestrels (<scp><i>Falco tinnunculus</i></scp>)

Broekman, Maarten J. E.; Jongejans, Eelke; Tuljapurkar, Shripad

doi:10.1002/1438-390x.12063

Cited by 11 publications

(14 citation statements)

References 43 publications

(118 reference statements)

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“…Paine 1992), we can identify potential candidates by comparing a species’ impact on the population growth of other species to it’s own density (Libralato et al 2006). It is important to note that because our framework allows for asymmetrical interactions, we are able to differentiate a species’ impact on other species from it’s response or sensitivity to neighbours (Broekman et al 2020). Figure 3.B highlights two native species in green which may be potential keystone species due to having strongly competitive effects on the rest of the community overall, despite low densities: Trachymene ornata (TROR) and Gilberta tenuifolia (GITE).…”

Section: Resultsmentioning

confidence: 99%

“…Firtly, the variable chosen to measure the performance of focal species p may not directly translate into a measure of performance which is relevant to system dynamics, due to inherent practical constraints with collecting empirical data. For example, the life-history reproductive strategies of certain species may lead to measures of high fecundity (or performance) in the field which do not account for low survival rates post-observation (Broekman et al 2020). In these cases, population dynamics models can be used to account for species-specific demographic rates into estimates of interaction effects.…”

Section: Methodsmentioning

confidence: 99%

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Estimating interaction matrices from performance data for diverse systems

Bimler

Mayfield

Martyn

et al. 2022

Preprint

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Network theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases non-linearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. We present a novel modelling framework which estimates the strength of pairwise interactions in diverse horizontal systems, using measures of species performance in the presence of varying densities of their potential interaction partners. Our method allows us to directly estimate pairwise effects when they are statistically identifiable and approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and are non-symmetrical. The advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Estimating interaction matrices from performance data for diverse systems

Bimler

Mayfield

Martyn

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Paine, 1992) and the inclusion of multiple trophic levels, we can identify potential candidates by comparing a species' impact on the population growth of other species to its own density (Libralato et al, 2006). It is important to note that because our framework allows for asymmetrical interactions, we are able to differentiate a species' impact on other species from its response or sensitivity to neighbours (Broekman et al, 2020). Figure 3b highlights a native species in green, Gilberta tenuifolia (GITE), which may be a potential keystone species due to having strongly competitive effects on the rest of the community overall, despite low density.…”

Section: Resultsmentioning

confidence: 99%

Estimating interaction strengths for diverse horizontal systems using performance data

et al. 2023

View full text Add to dashboard Cite

Network theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases nonlinearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. We present a novel modelling framework which uses measures of species performance in the presence of varying densities of their potential interaction partners to estimate the strength of pairwise interactions in diverse horizontal systems. Our method allows us to directly estimate pairwise effects when they are statistically identifiable and to approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and allows for non‐symmetrical interactions. We show how to link the parameters inferred by our framework to a population dynamics model to make inferences about the effect of interactions on community dynamics and diversity. The advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology.

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“…Arnold and Wade (1984) partitioned reproductive success and Crow’s Opportunity for Selection into sequential episodes of selection and showed that the components are additive only if one includes a residual factor that accounts for all the covariance terms. More recently, several authors interested in distinguishing ‘pluck’ from ‘luck’ (Snyder and Elner 2018) have focused on parsing out the component of LRS that can be attributed to random demographic stochasticity in survival and reproduction (van Daalen and Caswell 2017; Tuljapurkar et al 2020; Broekman et al 2020; Lee et al 2020). All of these approaches can provide useful insights, depending on one’s objectives and the kinds of data that are available.…”

Section: Discussionmentioning

confidence: 99%

“…In their analysis of empirical data for a water-strider, Ferguson and Fairbairn (2001) focused on a similar partitioning: pre-adult survival, adult lifespan, and daily fecundity. Arnold and Wade (1984) Tuljapurkar et al 2020;Broekman et al 2020;Lee et al 2020). All of these approaches can provide useful insights, depending on one's objectives and the kinds of data that are available.…”

Section: Other Ways To Partition Variation In Reproductive Successmentioning

confidence: 99%

Partitioning variance in reproductive success, within years and across lifetimes

Waples

2022

Preprint

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Variance in reproductive success (Vk, with k = number of offspring)is the stuff of evolution. Evolution by natural selection requires variation in offspring number, and the ratio ratio phi = Vk/kbar is the primary factor that reduces effective size (Ne) compared to census size (N). To date, no attempts to parse factors that contribute to Vk have focused on age-specific values of phi, which indicate the degree to which reproductive skew is overdispersed among individuals of the same age and sex. Here, an ANOVA framework is used to partition Vk into between-age and within-age components and, for lifetime reproductive success, a component due to variation in longevity. The between-age effect depends on mean age-specific fecundity (bx), but few empirical data are available on the within-age effect, which depends on phi. Analytical results show how to quantify the expected contribution of random demographic stochasticity to these variance components. Analyses of empirical and simulated data illustrate the new methods and show that the largely-neglected within-age effect a) typically represents a substantial component of overall variance in offspring number (even under a null model of random reproductive success), and b) can dominate the overall variance when phi >1.

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Relative contributions of fixed and dynamic heterogeneity to variation in lifetime reproductive success in kestrels (Falco tinnunculus)

Cited by 11 publications

References 43 publications

Estimating interaction matrices from performance data for diverse systems

Estimating interaction matrices from performance data for diverse systems

Estimating interaction strengths for diverse horizontal systems using performance data

Partitioning variance in reproductive success, within years and across lifetimes

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