Capturing juvenile tree dynamics from count data using Approximate Bayesian Computation

Abstract

The juvenile life stage is a crucial determinant of forest dynamics and a first indicator of changes to species' ranges under climate change. However, paucity of detailed re‐measurement data of seedlings, saplings and small trees means that their demography is not well understood at large scales, and rarely represented in forest models in detail. In this study we quantify the effects of climate and density dependence on recruitment and juvenile growth and mortality rates of thirteen species measured in the Spanish Forest Inventory. Single‐census sapling count data is used to constrain demographic parameters of a simple forest juvenile dynamics model based on the perfect plasticity approximation model (PPA) within a likelihood‐free parameterisation method, Approximate Bayesian Computation. Our results highlight marked differences between species, and the important role of climate and stand structure, in controlling juvenile dynamics. Recruitment had a hump‐shaped relationship with conspecific density, and for most species conspecific competition had a stronger negative effect than heterospecific competition. Mediterranean species showed on average higher mortality and lower growth rates than temperate species, and in low density stands recruitment and mortality rates were positively correlated. Under climate change our model predicted declines in recruitment rates for almost all species. Reliable predictive models of forest dynamics should include realistic representation of critical early life‐stage processes and our approach demonstrates that existing coarse count data can be used to parameterise such models. Approximate Bayesian Computation may have wide application in many fields of ecology to unlock information about past processes from single survey observations.

Tree recruitment is determined by stand structure and shade tolerance with uncertain role of climate and water relations

“…However, for the smallest size class and especially for modeling tree recruitment and regeneration over larger scales, our study showed that many processes are most likely dominated by complex relationships with feedback between stand structure and climate that cannot be formulated in GLMMs. Thus, for further large‐scale studies on tree recruitment‐environment interactions, we strongly recommend the use of alternatives to GLMMs, such as process‐based Bayesian approaches (Clark, 2003 ; Lines et al., 2020 ). The advantage of process‐based models is that they treat complex processes with feedbacks within the stand more explicitly.…”

Demographic performance of European tree species at their hot and cold climatic edges

“…However, we cannot rule out the possibility that the regeneration phase has a disproportional importance for the dynamics at the edge, as several studies have shown that this phase is extremely sensitive to climate (Canham & Murphy, 2016; Clark et al., 2014; Defossez et al., 2016). Integrating fecundity and juvenile life stages in tree IPMs is challenging because we have much less data on them (Needham et al., 2018; Ruiz‐Benito et al., 2020; but see Lines et al., 2019).…”

A new framework to understand context dependence of two-species population dynamics: A case study of rocky intertidal sessile assembly

“…Here, the strength of intraspecific density dependence decreased as the intrinsic growth rate of the focal species increased, which is contrary to the results of many previous studies in which the strength of intraspecific density dependence increased as the intrinsic growth rate increased (Lillegård et al 2008;Zehnder & Hunter 2008;Pasinelli et al 2011;Roy et al 2016;Gamelon et al 2019;Koetke et al 2020). On the other hand, a few studies have shown a negative relationship between environmental suitability and the strength of density dependence (Agrawal et al 2004;Lines et al 2020). Thus, the strength of intraspecific density dependence has various responses to environmental changes among different species and habitats.…”

“…First, this framework cannot be applied to situations in which invasion has failed in order to evaluate the causes, because it requires that both target species can be continuously observed. Second, the relationship between the strengths of intra-and interspecific density dependence and the intrinsic growth rates indicates pattern but not processes, because differences in intrinsic growth rates among localities will be multicausal phenomena, as suggested by the inconsistent relationship between strength of intraspecific density dependence and intrinsic growth rate in various studies (e.g., Agrawal et al 2004;Lillegård et al 2008;Zehnder & Hunter 2008;Pasinelli et al 2011;Roy et al 2016;Gamelon et al 2019;Koetke et al 2020;Lines et al 2020). Compared with the framework proposed here, future work should focus on the integration of this framework with the environmental gradient approach, which could be helpful for interpreting the mechanism underlying the pattern between strength of intraspecific density dependence and intrinsic growth rate through decomposing the effect of each environmental component.…”