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Hinrichsen, R. A.

Publications and source records attributed to Hinrichsen, R. A..

2 recordsLinked to original sources

From theory to application: Elasticity-consistent aggregation of Leslie matrix population models for comparative demography

O_LIEcology has entered the big data era. This influx of data has now enabled ecologists to address questions about life history and demographic patterns across the tree of life. Supporting this momentum, the COMADRE and COMPADRE databases represent a boon to comparative demography. However, these initiatives also present challenges due to the complexities of the life cycles that they describe. Matrix population models can vary in sampling frequency, life cycle stage width, life cycle complexity, and census type (e.g. pre- or post-reproduction). Complicating this picture is the fact that there are myriad matrix model representations of the same population, and model representation influences key demographic parameters. Thus, a key challenge in exploiting large demographic datasets is fair comparison of models constructed with different projection intervals and complexities. C_LIO_LIOne way to compare models of different complexity is to reduce ( aggregate) the larger models to the dimensionality of the smaller models. The commonly used aggregator (i.e. the standard aggregator), although it yields stable growth rate and stable stage distribution consistent with the original demographic model, does not provide consistent reproductive values and elasticities. To address this limitation, we extend and validate an existing elasticity-consistent aggregator, overcoming several of its methodological and biological limitations. Specifically, we derive the aggregator using balancing and interstage flows, which removes the requirement of matrix primitivity, and we restrict aggregation to Leslie-to-Leslie models, thereby preventing biologically infeasible survival probabilities exceeding one. We further introduce explicit metrics of aggregation effectiveness and apply the approach to 12 Leslie matrix population models representing animal populations from diverse taxonomic classes. C_LIO_LIThe elasticity-consistent aggregator returns a Leslie matrix that preserves key properties of the original matrix, including irreducibility and primitivity, and yields consistent estimates of population growth rate, stable age distribution, and reproductive values. Moreover, across all aggregated models from the 12 examined animal populations, the elasticity-consistent aggregator produced more accurate estimates than the standard aggregator for 86% of generation times, 60% of Demetrius entropies, and 76% of net reproductive rates. C_LIO_LIBy preserving key properties of the original model, the elasticity-consistent aggregator provides a useful framework for comparing matrix population models of varying complexity in comparative demography. Such a method helps seize the promise of big data in ecology and discover principles across the tree of life, from microbes to fungi, plants, and animals. C_LI

ecology↗

Solving three core challenges in transient dynamics analysis of matrix population models

O_LIPopulations are at the mercy of random disturbances large and small and rarely, if ever, converge on predicted long-term behaviours. Therefore, when using matrix population models, ecologists study the dynamics of populations that depart from stable distributions. Necessary for such studies are indices that gauge transient dynamics, which are short-term population fluctuations away from asymptotic trajectories. Conventional indices of transient dynamics present three core challenges: they are distorted by abundant stages of low value (usually immature stages), they are scale dependent, and they conflate transient and asymptotic responses. C_LIO_LII develop a new analytical framework for transient dynamics that overcomes these challenges. To solve distortion and scale dependence, I balance a population projection matrix (PPM) by its reproductive values ( Fisher balancing) or, alternatively, its stable stage distribution ( Demetrius balancing). To disentangle transient and asymptotic dynamics, I strip a PPM of its output in the direction of its stable stage distribution, resulting in a transient PPM. I develop indices of transient dynamics that gauge the size of a transient PPM using reactivities defined by matrix norms. Among these indices is a new coefficient of transient response (COTR) that represents the fraction of the sum of squares of the total response that is explained by the transient response. In addition to the indices of transient dynamics that apply directly to PPMs, the framework also includes case-specific indices of transient dynamics that arise from a specified initial stage vector. C_LIO_LIUsing a dataset of 6,332 PPMs retrieved from the COMPADRE Plant Matrix Database, I compared the new analytical framework with the conventional framework without balancing, focusing mainly on transient responses estimated by COTR. The new framework dramatically changed the rankings of PPMs from the least to the greatest transient dynamics. Spearman correlation between COTR of standardised PPMs and that of balanced PPMs was weak ([≤] 0.25). This change in rankings led to new inferences about which taxonomic orders were least or most prone to transient dynamics. C_LIO_LIBy solving three core challenges, the new framework produces a clearer and more robust portrait of transient dynamics. C_LI

ecology↗