The role of transient dynamics in stochastic population growth for nine perennial plants

Ellis, Martha M.; Crone, Elizabeth E.

doi:10.1890/13-0028.1

Cited by 35 publications

(58 citation statements)

References 37 publications

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“…S1) highlights a role for stochastic fluctuations in size structure as a potentially important component of demographic variability, as has been recently emphasized (Ellis andCrone 2013, McDonald et al 2016). This finding agrees with two recent comparative studies based on matrix population models, which found that the variance in realized growth rates (λ t ) caused by fluctuations in size structure was often larger than the variance caused by fluctuations in vital rates (Ellis andCrone 2013, McDonald et al 2016). However, the constant fluctuations in size structure that are characteristic of populations in stochastic environments may cause realized growth rates (λ t ) to deviate from expectations based solely on vital rates (λ 1,t ).…”

Section: Discussionmentioning

confidence: 65%

“…Importantly, this LTRE method approximates only the variance of the asymptotic population growth rate associated with each year (i.e., the leading eigenvalue of each year-specific kernel or matrix, λ 1,t ). We present the LTRE decomposition of Var(λ 1,t ) in Appendix S5 (including additional methods) as a complement to our simulation results, because this captures the influence of demographic correlations in isolation from stochastic fluctuations in population structure, which can be a substantial source of variability in population growth (Ellis andCrone 2013, McDonald et al 2016). The variance of λ 1,t is a relevant but incomplete measure of stochastic population dynamics because at each time step λ t = λ 1,t × reactivity t (Ellis andCrone 2013, McDonald et al 2016).…”

Section: Effects Of Vital Rate Correlations On the Variance Of Populamentioning

confidence: 99%

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The effect of demographic correlations on the stochastic population dynamics of perennial plants

Compagnoni

Bibian

Ochocki

et al. 2016

Ecological Monographs

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Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-toyear variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (λ s )? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from −1% to +22%. However, vital rate correlations caused virtually no change in the estimates of λ s (mean effects ranging from −0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that, in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data intensive and technically challenging.

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Section: Discussionmentioning

confidence: 65%

Section: Effects Of Vital Rate Correlations On the Variance Of Populamentioning

confidence: 99%

The effect of demographic correlations on the stochastic population dynamics of perennial plants

Compagnoni

Bibian

Ochocki

et al. 2016

Ecological Monographs

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“…Furthermore, these alternative measures were not always highly correlated with measures of maximum population decline (Appendix S2) which is consistent with other studies of transient demography that found measures of short‐term population decline are weakly correlated with measures of short‐term population gain (Stott et al . ,b; Ellis & Crone ). Our results therefore demonstrate a rich diversity of patterns among species in the rate, magnitude and ability to recover from declines in density following introductions of seeds.…”

Section: Discussionmentioning

confidence: 99%

“…; Crone et al . ; Ellis & Crone ). Thus, invading populations could potentially experience significant extinction risks due to stochastic events if transient growth rates reduce invading populations to (or maintain populations at) low density, despite a high asymptotic growth rate.…”

Section: Introductionmentioning

confidence: 99%

Linking transient dynamics and life history to biological invasion success

et al. 2015

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1. Upon arriving in a novel environment, invading populations are likely to be small and far from a stable stage structure. This unstable stage structure can cause transient (short-term) population dynamics to differ greatly from asymptotic (long-term) dynamics. Because the persistence of small populations depends heavily on population growth rate, short-term dynamics may strongly influence the viability of invading populations. 2. We used published matrix population models to study the dynamics of small 'invading' populations for 105 plant species spanning a range of life histories, including species classified as both invasive and non-invasive. We simulated the matrix population models to estimate the effect of transient dynamics on population viability (i.e. potential invasiveness) after a hypothetical seed dispersal event into a novel environment. We then evaluated the predictive power of transient and long-term population growth rates to explain variation in population viability and identified the life-history correlates of population dynamics that best explained establishment success. 3. Transient and long-term population growth rates were positively but independently correlated with population viability across species. Minimum transient density (minimum population density attained en route to a stable stage structure) was the best transient predictor of population viability. This suggests that avoidance of severe short-term population declines is more important during establishment than either the rate of decline or transient ability to increase in density following a decline. 4. Despite a negative correlation between transient density and fecundity, species with high fecundity had disproportionately favourable transient dynamics and higher long-term population growth rates, resulting in higher population viability. Together, these results suggest that highly fecund species are better equipped to overcome the early effects of demographic stochasticity in the establishment phase than less fecund species and help explain the common empirical finding that species invasiveness is correlated with fecundity. 5. Synthesis. Transient and long-term population dynamics are independent predictors of demographic performance that influence the viability of invading (i.e. small, unstable) populations subjected to strong effects of demographic stochasticity. Greater long-term population growth rates and disproportionately favourable transient dynamics may account for the commonly observed invasiveness of highly fecund species. Given the strong dependence of population viability on population growth and the wide range of transient responses among species, transient analysis may provide critical insights into the demographic correlates of biological invasion potential.

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“…Environmental perturbations or long-term climatic changes can affect several demographic parameters, and integrating these complex interactions to assess the viability of a population can be challenging (Katzner et al 2006, Nadeem andLele 2012). Matrix population models, the standard tool for the study of population dynamics (Morris et al 2002), may not offer reliable population projections if environmental conditions in the future deviate from the conditions during which data were collected , or if unobservable demographic processes such as transience and immigration affect population dynamics (Ellis and Crone 2013). Incorporating the environmental drivers of demographic parameters and demographic processes such as immigration into population projections may therefore improve forecasts and strengthen the practical relevance of population viability assessments.…”

Section: Introductionmentioning

confidence: 99%

Assessing population viability while accounting for demographic and environmental uncertainty

Oppel

Hilton

Ratcliffe

et al. 2014

Ecology

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Abstract. Predicting the future trend and viability of populations is an essential task in ecology. Because many populations respond to changing environments, uncertainty surrounding environmental responses must be incorporated into population assessments. However, understanding the effects of environmental variation on population dynamics requires information on several important demographic parameters that are often difficult to estimate. Integrated population models facilitate the integration of time series data on population size and all existing demographic information from a species, allowing the estimation of demographic parameters for which limited or no empirical data exist. Although these models are ideal for assessments of population viability, they have so far not included environmental uncertainty. We incorporated environmental variation in an integrated population model to account for both demographic and environmental uncertainty in an assessment of population viability. In addition, we used this model to estimate true juvenile survival, an important demographic parameter for population dynamics that is difficult to estimate empirically. We applied this model to assess the past and future population trend of a rare island endemic songbird, the Montserrat Oriole Icterus oberi, which is threatened by volcanic activity. Montserrat Orioles experienced lower survival in years with volcanic ashfall, causing periodic population declines that were compensated by higher seasonal fecundity in years with high pre-breeding season rainfall. Due to the inclusion of both demographic and environmental uncertainty in the model, the estimated population growth rate in the immediate future was highly imprecise (95% credible interval 0.844-1.105), and the probability of extinction after three generations (in the year 2028) was low (2.1%). This projection demonstrates that accounting for both demographic and environmental sources of uncertainty provides a more realistic assessment of the viability of populations under unknown future environmental conditions.

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The role of transient dynamics in stochastic population growth for nine perennial plants

Cited by 35 publications

References 37 publications

The effect of demographic correlations on the stochastic population dynamics of perennial plants

The effect of demographic correlations on the stochastic population dynamics of perennial plants

Linking transient dynamics and life history to biological invasion success

Assessing population viability while accounting for demographic and environmental uncertainty

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