Final Report Summary - TRECC (Tree Range Evolution under Climate Change)
Climate change will modify species’ distribution ranges (e.g. Thuiller et al. 2005; Intergovernmental Panel on Climate Change 2007; Hickler et al. 2012). Whether species, and especially temperate trees, will be able to track favourable climates, is currently unknown (Jump & Penuelas 2005). This depends on each species’ ability to disperse towards favourable habitats (Kremer et al. 2012; Meier et al. 2012). Aside from migration, tree species may respond to changing climates by genetic and/or by plastic changes in key traits (such as winter chilling requirements; Chuine 2010). The pace of trait evolution depends on population size, on the strength of selective pressures, on the genetic variance available for these traits, and on genetic trade-offs and multivariate selective pressures acting jointly on them (e.g. Pease et al. 1989; Kirkpatrick & Barton 1997; Hoffmann et al. 2003; Kirkpatrick 2009; Polechová et al. 2009; Walsh & Blows 2009).
This two-year project aimed at (1) determining how genetic correlations between traits and joint selective pressures affected a species’ distribution ranges in the context of changing environments; (2) assessing whether genetic evolution could dampen the pessimistic forecasts of future forest trees’ ranges in Europe, as provided by a process-based species distribution model.
For this second part, the fellow intended to consider pedunculate oak (Quercus robur) as a biological model, and to assess its present and future distribution using an already existing process-based tree distribution model (PHENOFIT, Chuine & Beaubien 2001; Morin & Chuine 2005), whose realism would be improved through its combination with a model of trait evolution (as developed in (1)). To this aim, it was first necessary to (a) allow the process-based model to account for local adaptation; (b) determine the strength of selective pressures; (c) check whether it produced accurate projections of current species distribution ranges (before proceeding to forecasts).
Objective 1 was validated; so were objectives (2-a-c). Objectives (2-a) and (2-c) raised general issues,
which were tackled prior to completing the initial Objective 2:
- objective (2-a) raised the question of the extent to which phenotypic plasticity contributes to enlarging the geographic range (or ecological niche) of a species (new objective (2-g)).
- objective (2-c) raised the question of the existence of reliable atlas data for species presence/absence. Indeed, different reference atlases exist in the literature. Model accuracy depends on the map used as a reference. More importantly, for correlative species distribution models, the choice of a reference map modifies the factors recognised as driving a species’ distribution, and strongly impacts its forecast. (new objective (2-f))
- objective (2-c) raised the issue of building consensual forecasts or species distributions, taking into account what we know of the strengths and weaknesses of each model (new objective (2-e).
The fellow considered these issues were important, and tackled them before completed objective 2. As a result, objective 2 is not achieved, but more general and necessary prerequisite questions have been answered instead.
The overall schedule of the project was expanded by 16 weeks, given that the fellow’s contract was interrupted for that duration during year 1, for a maternity leave.
This two-year project aimed at (1) determining how genetic correlations between traits and joint selective pressures affected a species’ distribution ranges in the context of changing environments; (2) assessing whether genetic evolution could dampen the pessimistic forecasts of future forest trees’ ranges in Europe, as provided by a process-based species distribution model.
For this second part, the fellow intended to consider pedunculate oak (Quercus robur) as a biological model, and to assess its present and future distribution using an already existing process-based tree distribution model (PHENOFIT, Chuine & Beaubien 2001; Morin & Chuine 2005), whose realism would be improved through its combination with a model of trait evolution (as developed in (1)). To this aim, it was first necessary to (a) allow the process-based model to account for local adaptation; (b) determine the strength of selective pressures; (c) check whether it produced accurate projections of current species distribution ranges (before proceeding to forecasts).
Objective 1 was validated; so were objectives (2-a-c). Objectives (2-a) and (2-c) raised general issues,
which were tackled prior to completing the initial Objective 2:
- objective (2-a) raised the question of the extent to which phenotypic plasticity contributes to enlarging the geographic range (or ecological niche) of a species (new objective (2-g)).
- objective (2-c) raised the question of the existence of reliable atlas data for species presence/absence. Indeed, different reference atlases exist in the literature. Model accuracy depends on the map used as a reference. More importantly, for correlative species distribution models, the choice of a reference map modifies the factors recognised as driving a species’ distribution, and strongly impacts its forecast. (new objective (2-f))
- objective (2-c) raised the issue of building consensual forecasts or species distributions, taking into account what we know of the strengths and weaknesses of each model (new objective (2-e).
The fellow considered these issues were important, and tackled them before completed objective 2. As a result, objective 2 is not achieved, but more general and necessary prerequisite questions have been answered instead.
The overall schedule of the project was expanded by 16 weeks, given that the fellow’s contract was interrupted for that duration during year 1, for a maternity leave.
