Risk-sensitive maternal investment: an evaluation of parent–offspring conflict over nest site choice in the wild

Delaney, David M.; Janzen, Fredric J.

doi:10.1016/j.anbehav.2020.03.004

Cited by 9 publications

(9 citation statements)

References 99 publications

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“…Specifically, females increased canopy cover, distance to water, nest depth and the frequency of gravel in nests with age and size. Such nest‐site variation with maternal age has been found in smaller subsets of data from our site (canopy cover—Warner et al, 2016; distance to water—Harms, Paitz, Bowden, & Janzen, 2005; Delaney & Janzen, 2020; nest depth—Morjan, 2003b). But why might nesting behaviour change predictably with age?…”

Section: Discussionsupporting

confidence: 65%

“…But why might nesting behaviour change predictably with age? Young females likely nest close to shore to reduce their own risk of predation by terrestrial predators (Delaney & Janzen, 2020; Harms et al, 2005; Tucker, Filoramo, & Janzen, 1999; but see Refsnider, Reedy, Warner, & Janzen, 2015). However, nests laid closer to shore tend to experience elevated predation rates because nest predators (such as raccoons) tend to forage along shorelines and other environmental edges (Kolbe & Janzen, 2002; Spencer, 2002; Strickland, Colbert, & Janzen, 2010).…”

Section: Discussionmentioning

confidence: 99%

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Becoming creatures of habit: Among‐ and within‐individual variation in nesting behaviour shift with age

Delaney

Hoekstra

Janzen

2020

J of Evolutionary Biology

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The quantification of repeatability has enabled behavioural and evolutionary ecologists to assess the heritable potential of traits. For behavioural traits that vary across life, age‐related variation should be accounted for to prevent biasing the microevolutionary estimate of interest. Moreover, to gain a mechanistic understanding of ontogenetic variation in behaviour, among‐ and within‐individual variance should be quantified across life. We leveraged a 30‐year study of painted turtles (Chrysemys picta) to assess how age contributes to variation in the repeatability of nesting behaviours. We found that four components of nesting behaviour were repeatable and that accounting for age increased the repeatability estimate for maternal choice of canopy cover over nests. We detected canalization (diminished within‐individual variance with age) of canopy cover choice in a reduced data set despite no shift in repeatability. Additionally, random regression analysis revealed that females became more divergent from each other in their choice of canopy cover with age. Thus, properly modelling age‐related variance should more precisely estimate heritable potential, and assessing among‐ and within‐individual variance components in addition to repeatability will offer a more mechanistic understanding of behavioural variation across age.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Becoming creatures of habit: Among‐ and within‐individual variation in nesting behaviour shift with age

Delaney

Hoekstra

Janzen

2020

J of Evolutionary Biology

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“…Finally, startups emphasize innovation and are the extension of innovative enterprises. China’s GEB is the financing market for SMEs, high-tech enterprises, and startups to be listed on the main-board market, so many enterprises choose to be listed on the GEB ( Delaney and Janzen, 2020 ; Wulandari, 2021 ). The factors of the enterprises’ innovation behaviors can be divided into external factors and internal factors: external factors include industry, region, political, cultural and legal environment, enterprise ownership, and the enterprise’s international environment; the internal factors include the size of the enterprise, the enterprise strategies, the internal governance system, the profitability of the enterprise, the capital structure, the characteristics of senior managers, and the participation of institutions.…”

Section: Related Concepts Of Venture Capitalmentioning

confidence: 99%

The Impact of Foreign Venture Capital Intervention on Venture Capital Innovation of Startup Entrepreneurs Using Propensity Score Matching Model

Han

2021

Front. Psychol.

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The research expects to give full play to the role of venture capital in corporate innovation and enhance the development capability of enterprises. Based on Propensity Score Matching (PSM) model, the characteristics of venture capital and startup enterprises are analyzed, and the innovation of venture capital is discussed. Next, the PSM model is used to analyze the innovation of venture capital intervention in enterprises from risk probability intervention, probability evaluation, matching equilibrium validity test, matching results analysis, different venture capital, and different background risks. The results show that the difference of standardized mean is close to 0, which accords with the equilibrium test. The significant impact of venture capital intervention on the Number of Invention Patent Applications (NIPA) and Number of Utility Model Patent Applications (NUMPA) is 0.1 and 0.01, respectively. Venture capital intervention has a significantly positive impact on NIPA and NUMPA but has no significant positive impact on Number of Design Patent Applications (NDPA). The impact of joint venture capital intervention on the NIPA, NUMPA, and NDPA is 0.0874, 0.0635, and 0.1213, respectively. Hence, the intervention of joint venture capital can greatly promote the increase of Number of Patent Applications (NPA), especially, NIPA, and NUMPA. Compared with private venture capital, joint venture capital plays a greater role in promoting the growth of NPA and NIPA. Compared with private venture capital and foreign venture capital, national venture capital has a stronger innovation orientation and a longer investment cycle, which can greatly improve innovation performance, such as NIPA, while private venture capital and foreign venture capital have a less significant impact on enterprise innovation performance. The results demonstrate that the foreign capital sharing assessment based on the PSM model can be a good predictor of the performance of startups. It is hoped that the research results can provide a reference for the development of startups.

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“…Researchers often assume that young animals have the highest RRV because their potential for future reproduction is greater than older animals that are closer to the terminal age of reproduction. Researchers have thus intuitively used age as a proxy for RRV (e.g., Cameron et al 2000;Dammhahn 2012;Heinze and Schrempf 2012;Takata et al 2016;Delaney and Janzen 2020) and often imply that age and RRV are inverses of each other (fig. 1A).…”

Section: Introductionmentioning

confidence: 99%

“…We then compared them among each other and with age to test which better predicts how far female C. picta construct nests from water. Nest distance to water is an important investment measure because maternal risk should increase the farther females travel from the safety of water (discussed in Delaney et al 2017;Delaney and Janzen 2020). In contrast, embryos in nests constructed farther from water experience lower predation rates because nest predators tend to forage along the shore (e.g., Kolbe and Janzen 2002;Spencer 2002;Strickland et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Age Predicts Risky Investment Better Than Residual Reproductive Value

Delaney

Hoekstra

Janzen

2021

The American Naturalist

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Life-history theory predicts that investment in reproduction should increase as future reproductive potential (i.e., residual reproductive value [RRV]) decreases. Researchers have thus intuitively used age as a proxy for RRV and assume that RRV decreases with age when interpreting age-specific investment. Yet age is an imperfect proxy for RRV and may even be a poor correlate in some systems. We used a 31-year study of the nesting ecology of painted turtles (Chrysemys picta) to assess how age and RRV compare in explaining variation in a risky investment behavior. We predicted that RRV would be a better predictor of risky investment than age because RRV accounts for variation in future reproductive potential across life. We found that RRV was high in early life, slowly decreased until midlife, and then steadily decreased to terminal reproduction. However, age predicted risky behavior better than RRV. This finding suggests that stronger correlates of age (e.g., size) may be more responsible for this behavior in turtles. This study highlights that researchers should not assume that age-specific investment is driven by RRV and that future work should quantify RRV to more directly test this key element of life-history theory.

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Risk-sensitive maternal investment: an evaluation of parent–offspring conflict over nest site choice in the wild

Cited by 9 publications

References 99 publications

Becoming creatures of habit: Among‐ and within‐individual variation in nesting behaviour shift with age

Becoming creatures of habit: Among‐ and within‐individual variation in nesting behaviour shift with age

The Impact of Foreign Venture Capital Intervention on Venture Capital Innovation of Startup Entrepreneurs Using Propensity Score Matching Model

Age Predicts Risky Investment Better Than Residual Reproductive Value

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