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Integrating evolutionary, demographic and ecophysiological processes to predict the adaptive dynamics of forest tree populations under global change

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Abstract

Three types of process-based models (PBMs) are traditionally used to predict the response of forest tree populations to global change (GC): (i) ecophysiological models, which simulate carbon and water fluxes in forest ecosystems by explicitly integrating the effects of climate and CO2; (ii) forest dynamics models which simulate forest successions by explicitly linking mortality, growth and regeneration processes; and (iii) evolutionary dynamics models, which simulate the variation and evolution of adaptive traits by explicitly accounting for selection, mutation, gene flow and inheritance rules. The ongoing context of rapid GC, however, questions the boundaries between these types of models. Here, we review different strategies of model integration: (i) physio-demographic PBMs, integrating physiological and demographic processes; (ii) demo-genetic PBMs, integrating demographic and evolutionary processes; and (iii) physio-demo-genetic PBMs, which attempt to integrate these three types of processes. We show that these integrative models allow a better understanding of how different functional traits influence demographic rates (the phenotype-demography map), how the variation in demographic rates influences fitness (the demography-fitness map) and how individual variations of fitness may in turn influence the genetic composition of a population. Our review highlights that accounting for inter-individual variation in ecological processes is increasingly recognized as crucial for modelling the ecosystem response to environmental change. We argue that the effort of integrating these different processes is valuable, both for a basic understanding of their interactive effects on the responses of forests to GC and for applied horizon scanning to support adaptive strategies.

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Notes

  1. Terms in italic with an asterisk (*) are defined in the glossary.

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Acknowledgments

We are grateful to numerous URFM colleagues (A. Amm, M. Alleaume-Benharira, A. Bontemps, M. Cailleret, C. Pichot, I. Scotti) for the discussions and comments on a previous version of this manuscript.

Funding

This study was partly funded by the European Union’s Horizon 2020 research and innovation programme, under Grant Agreement No. 676876 (GenTree) and No. 773383 (B4EST).

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Authors and Affiliations

  1. INRAE, UR 629 Ecologie des Forêts Méditerranéennes, URFM, 84000, Avignon, France

    Sylvie Oddou-Muratorio, Hendrik Davi & François Lefèvre

Authors
  1. Sylvie Oddou-Muratorio
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  2. Hendrik Davi
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  3. François Lefèvre
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Contributions

FL searched the literature for models integrating demographic and evolutionary processes, HD for models integrating demographic and physiological processes and SOM for models integrating physiological, demographic and evolutionary processes. All the authors drafted the manuscript and SOM coordinated the assembly.

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Correspondence to Sylvie Oddou-Muratorio.

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Communicated by S.C. González-Martínez

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Glossary

Adaptive or evolutionary dynamics

: the regime of change in the genetic composition of a population across generations.

Demographic (or vital) rates

: refer to how fast demographic statistics (e.g. the number of death and births) change in a population. At population level, they are usually expressed as number (of deaths, or birth) scaled by population size and expressed per unit of time. They can also be expressed at cohort or individual level, as individual probabilities per unit of time (e.g. age-specific survival probability or expected fecundity). Demographic rates are the outcomes of the interaction between traits (e.g. size) and environment.

Fitness

: the number of offspring produced by a given phenotype or genotype over its lifetime that reach maturity.

Genetic adaptation

: genetic response of a population to selection through changes in DNA sequence between generations, resulting in phenotypic change and increasing fitness.

Life-history trait

: an individual characteristic contributing to life-history strategy (i.e. a change in that trait creates the most significant difference in fitness). Major life-history traits are size at birth, growth rate, age and size at maturity, number and size of offspring, age- and size-specific reproductive investments.

Functional trait

: any observable characteristic of an individual, including morphological, physiological or phenological characteristics, which influences the demographic and reproductive performances or ecological functions of this plant.

Performance

: an individual characteristic recognized as good proxy of the survival or reproductive components of fitness. In trees, growth is often used as a predictor of survival, while characteristics such as seed output and seed mass are usually considered as good proxies of fecundity. Population ecologists often consider these plant performances as demographic/vital rates, while evolutionary ecologists consider them as life-history traits.

Phenotypic plasticity

: the phenomenon of the same genotype producing different phenotypes in response to different environmental stimuli.

Population dynamics

: the regime of change in demographic composition (size, age structure) through time.

Process-based (or mechanistic) model

: models that characterize the dynamics of a system (through the description of its internal mechanisms) as explicit functions of component parts and their associated actions and interactions.

Resistance

: capacity of a population or an individual to remain stable and limit the negative impact of an external pressure.

Resilience

: in a strict sense, it is the capacity of a population or an individual to persist to an external pressure despite response changes (persistent unstable system); in a broad sense, it also includes resistance.

The genotype-phenotype-fitness map

: is a composite framework proposed by Coulson et al. (2006) that maps different levels of biological diversity onto one another. Each individual map is environment-dependent, and the integrative PBMs integrate the fact that part of the environment dynamically evolves with the demographic structure (Fig. 2). It includes three components:

•The genotype-phenotype map

: specifies the link between alleles, the proteins they code for and phenotypic traits. The genotype-phenotype map potentially includes epistatic interactions among several genes on a single trait or pleiotropic effect of a single gene on several traits (pleiotropy can result dynamically from the model).

•The phenotype-demography map

: describes the changes in the values of demographic rates resulting from changes in the values of the traits. Its aim is to identify the association between the value of a phenotypic trait and the probability of an individual expressing that trait value surviving, reproducing or dispersing. It accounts for phenotype-by-environment interactions. The associations between all traits and all demographic rates ultimately describes population growth (the mean demography). The phenotype-demography map may include functional effects comparable to genetic epistasis (interaction effects of several traits on a single demographic rate) or pleiotropy (multiple effects of a single trait on several demographic rates).

•The demography-fitness map

: describes the way that trait variation contributes to individual variation in fitness via demography and hence provides opportunity for selection. The original formulation by Coulson et al. (2006) relates to mean fitness, i.e. population growth rate in the matrix populations models’ framework.

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Oddou-Muratorio, S., Davi, H. & Lefèvre, F. Integrating evolutionary, demographic and ecophysiological processes to predict the adaptive dynamics of forest tree populations under global change. Tree Genetics & Genomes 16, 67 (2020). https://doi.org/10.1007/s11295-020-01451-1

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