Data from: A review and meta-analysis of intraspecific differences in phenotypic plasticity: implications to forecast plant responses to climate change
Matesanz, Silvia; Ramírez-Valiente, José Alberto (2019), Data from: A review and meta-analysis of intraspecific differences in phenotypic plasticity: implications to forecast plant responses to climate change, Dryad, Dataset, https://doi.org/10.5061/dryad.nn96ps3
Aim: Many studies use differences among plant populations to infer future plant responses, but these predictions will only provide meaningful insights if plasticity patterns among populations are similar (i.e. in the absence of Population-by-Environment interaction, P × E). In this study, we test whether P × E is considered in climate change studies. We evaluated whether population differentiation varies across environments and is determined by aspects of the study system and experimental design.
Methods: We conducted a literature search in the Web of Science database to identify studies assessing population differentiation in a climate change context. We quantified P × E and performed a meta-analysis to calculate the percentage of traits showing P × E in the study cases.
Results: We identified 309 study cases (from 237 articles) assessing population differentiation in 172 plant species, of which 64 % included more than one test environment and tested P × E. In 77% of these, P × E was significant for at least one functional trait. The overall proportion of traits showing P × E was 33.4% (CI 27.7-39.3). These results were generally consistent across life forms, ecoregions and type of experiment. Furthermore, population differentiation varied across test environments in 76% of cases. The overall proportion of traits showing environment-dependent population differentiation was 53.7 % (CI 37.9-69.3).
Conclusions: Our findings revealed that differences in phenotypic plasticity among populations are common, but are usually neglected to forecast population responses to climate change. Future studies should assess population differentiation in multiple test environments that realistically reflect future environmental conditions, assessing climate change drivers that are rarely considered (e.g. multifactor experiments). Our review also revealed the predominant focus of population studies on trees from temperate climates, identifying underexplored life forms, phylogenetic groups and ecoregions that should receive more future attention.