Time, transients and elasticity

Haridas, C. V.; Tuljapurkar, Shripad

doi:10.1111/j.1461-0248.2007.01108.x

Cited by 43 publications

(72 citation statements)

References 16 publications

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“…I calculated the average transient growth rate

r (t_{1}, t_{2})

by projecting the population over 10 years using eqn ():

r false(t_{1}, t_{2} false) = \frac{1}{t_{2} - t_{1}} log \frac{N (t_{2})}{N (t_{1})},

with initial population vector n (0) equal to the average observed population structure over the 4‐year study. Transient dynamics are sensitive to initial population structure (Haridas & Tuljapurkar ; Stott, Townley & Hodgson ; Stott, Hodgson & Townley ). One could use different n (0) (dominated by adults, or by seedlings, or stable stage distribution) to test how initial conditions may change transient dynamics.…”

Section: Methodsmentioning

confidence: 99%

“…; Miller & Tenhumberg ; Stott, Hodgson & Townley ; Tremblay, Raventos & Ackerman ). Transient elasticities can be temporally dynamic (Haridas & Tuljapurkar ; Yearsley ). For example, Maron, Horvitz & Williams () showed that the relative importance of fertility for transient growth of the invasive Cynoglossum officinale varies over time and between native and invasive ranges, oscillating in one environment and phasing each other in another.…”

Section: Introductionmentioning

confidence: 99%

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Transient dynamics reveal the importance of early life survival to the response of a tropical tree to harvest

Gaoue

2015

Journal of Applied Ecology

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Summary1. Exploitation of non-timber forest products can contribute to the alleviation of poverty. However, overexploitation can also lead to species decline. Studies on the sustainability of harvest often use stationary population growth rates to assess harvesting effects. For such frequently harvested systems, transient analysis can provide new insights into the response of populations to harvest. 2. To test the prediction that the effect of harvest differs between transient and asymptotic phases, I used four years of demographic data to compare the impact of harvesting bark and foliage on the short-and long-term dynamics of African dry zone Mahogany Khaya senegalensis in West Africa. 3. The effect of harvest was stronger in the short term than in the long term, particularly in the moist region. Patterns of transient elasticities also differed from the elasticities of longterm growth rates to perturbation of vital rates. Survival at early life stages was more important for short-term dynamics than for long-term population dynamics. 4. Synthesis and applications. This study illustrates that using the asymptotic growth rates to assess the impact of harvest may underestimate the short-term effects of harvest. Short-term management plans based on the elasticity analysis of long-term growth rates will be suboptimal given the relative importance of the survival of non-reproductive stages for population dynamics in the near term. Managers should use results from elasticity analysis of both longterm and short-term population dynamics to develop more realistic management plans.

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“…I calculated the average transient growth rate

r (t_{1}, t_{2})

by projecting the population over 10 years using eqn ():

r false(t_{1}, t_{2} false) = \frac{1}{t_{2} - t_{1}} log \frac{N (t_{2})}{N (t_{1})},

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transient dynamics reveal the importance of early life survival to the response of a tropical tree to harvest

Gaoue

2015

Journal of Applied Ecology

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“…In some scenarios, earlier life stages disproportionally contributed to the population growth rate of long‐lived species over the short‐term (e.g. 10 years), relative to later life stages (Haridas & Tuljapurkar ; McMahon & Metcalf ; Ezard et al . ; Haridas & Gerber ; Gaoue ).…”

Section: Discussionmentioning

confidence: 99%

“…To identify the relative importance of life stages on the short‐term population growth rate, we conducted stochastic transient elasticity analyses with respect to small changes in matrix elements to unperturbed stage structure, e 1, i , j (Haridas & Tuljapurkar ; Haridas & Gerber ). The e 1, i , j distribution for each scenario ( A , B , C , and D ) was iteratively calculated by simulation, using 1000 iterations.…”

Section: Methodsmentioning

confidence: 99%

Microhabitat heterogeneity and a non‐native avian frugivore drive the population dynamics of an island endemic shrub, Cyrtandra dentata

Bialic‐Murphy

Gaoue

Kawelo³

2017

Journal of Applied Ecology

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Summary Understanding the role of environmental change in the decline of endangered species is critical for designing scale‐appropriate restoration plans. For locally endemic rare plants on the brink of extinction, frugivory can drastically reduce local recruitment by dispersing seeds away from geographically isolated populations. Dispersal of seeds away from isolated populations can ultimately lead to population decline. For localized endemic plants, fine‐scale changes in microhabitat can further limit population persistence. Evaluating the individual and combined impact of frugivores and microhabitat heterogeneity on the short‐term (i.e. transient) and long‐term (i.e. asymptotic) dynamics of plants will provide insight into the drivers of species rarity. In this study, we used 4 years of demographic data to develop matrix projection models for a long‐lived shrub, Cyrtandra dentata (H. St. John & Storey) (Gesneriaceae), which is endemic to the island of O'ahu in Hawai'i. Furthermore, we evaluated the individual and combined influence of a non‐native frugivorous bird, Leiothrix lutea, and microhabitat heterogeneity on the short‐term and long‐term C. dentata population dynamics. Frugivory by L. lutea decreased the short‐term and long‐term population growth rates. However, under the current level of frugivory at the field site the C. dentata population was projected to persist over time. Conversely, the removal of optimum microhabitat for seedling establishment (i.e. rocky gulch walls and boulders in the gulch bottom) reduced the short‐term and long‐term population growth rates from growing to declining. Survival of mature C. dentata plants had the greatest influence on long‐term population dynamics, followed by the growth of seedlings and immature plants. The importance of mature plant survival was even greater when we simulated the combined effect of frugivory and the loss of optimal microhabitat, relative to population dynamics based on field conditions. In the short‐term (10 years), however, earlier life stages had the greatest influence on population growth rate. Synthesis and applications. This study emphasizes how important it is to decouple rare plant management strategies in the short vs. long‐term in order to prioritize restoration actions, particularly when faced with multiple stressors not all of which can be feasibly managed. From an applied conservation perspective, our findings also illustrate that the life stage that, if improved by management, would have the greatest influence on population dynamics is dependent on the timeframe of interest and initial conditions of the population.

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“…Short-term behavior, however, can be different from its long-term behavior because, unlike asymptotic rates, transient growth rates can be strongly influenced by the population current age or size distribution (Caswell and Werner 1978;Caswell 1989;Burgman et al 1993;Caswell 2007). Haridas and Tuljapurkar (2007) showed that it is possible to have only properties of the unperturbed vital rates and stage structure of a population to predict short-term responses to perturbations, and should therefore be useful in several management contexts.…”

Section: Introductionmentioning

confidence: 99%

Prediction vs. reality: Can a PVA model predict population persistence 13 years later?

2009

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The challenge of conservation biology is to make models that predict population dynamics and have a high probability of accurately tracking population change (increase, decrease, constancy). In this study we tested whether the transition model is accurate enough to predict population persistence and size 13 years down and whether after 13 years populations had achieved a stable stage distribution. We modeled 6 small populations of an epiphytic orchid using a Lefkovitch type analysis to predict population growth pattern based on monthly surveys for approximately 1.5 years. In addition, sensitivity and elasticity analyses were used to identify life stages with high sensitivity or elasticity that have the largest influence on population growth rate. We re-censused the populations 13 years after the first study and compared the structure of the populations to predictions based on the earlier census data. Effective population growth rates were similar to those expected except for one where the population went extinct. The prediction slightly (but not significantly) overestimated the actual population growth rates of some populations. Elasticity analysis revealed that the adult stage is critical in the life cycle. The observed stage distributions of the populations were not stable at the beginning of the survey and neither were they after 13 years. We suggest that this might be caused by external perturbations that result in unequal mortality between life stages and stochastic recruitment events. The ability of the matrices to predict population size approximately eight generations in the future is encouraging and warrants the continued use of these approaches for PVA.

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Time, transients and elasticity

Cited by 43 publications

References 16 publications

Transient dynamics reveal the importance of early life survival to the response of a tropical tree to harvest

Transient dynamics reveal the importance of early life survival to the response of a tropical tree to harvest

Microhabitat heterogeneity and a non‐native avian frugivore drive the population dynamics of an island endemic shrub, Cyrtandra dentata

Prediction vs. reality: Can a PVA model predict population persistence 13 years later?

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