Rapid phenotypic differentiation in the iconic Japanese knotweed s.l. invading novel habitats

Understanding the mechanisms that underlie plant invasions is critical for management and conservation of biodiversity. At the same time, invasive species also provide a unique opportunity to study rapid adaptation to complex environmental conditions. Using four replicate reciprocal transplant experiments across three habitats, we described patterns of phenotypic response and assessed the degree of local adaptation in knotweed populations. We found plants from beach habitats were generally smaller than plants from marsh and roadside habitats when grown in their home habitat. In the marsh habitat, marsh plants were generally larger than beach plants, but not different from roadside plants. There were no differences among plants grown in the roadside habitat. We found mixed evidence for local adaptation: plants from the marsh habitat had greater biomass in their “home” sites, while plants from beaches and roadsides had greater survival in their “home” sites compared to other plants. In sum, we found phenotypic differentiation and some support for the hypothesis of rapid local adaptation of plants from beach, marsh and roadside habitats. Identifying whether these patterns of differentiation result from genetic or heritable non-genetic mechanisms will require further work.


Trait
Transformation Type of model

Shoot biomass log 2 LMER
Origin type + Garden type + Origin type x Garden type + (Garden site)

Root biomass log 2 LMER
Origin type + Garden type + Origin type x Garden type + (Origin site + Garden site) Supplementary methods: Additional analyses including "Transplant group" as a fixed effect.

Methods
Our design was constrained by the fact that origin site and transplant sites are nested within levels of "Transplant group" 80 .To examine the importance of this design constraint, we also reran the LMER and GLMER models for each trait with the fixed term "Transplant group".To properly test for the effects in this nesting design, we should ideally fit random intercepts for the sites nested within groups, but we did not have enough replication within groups to do so.We assume that fitting the fixed effect of the "Transplant group" also controls for the nonindependence of the origin site and transplant site within groups (Long, 2021).By comparing the modeling with and without the fixed term of Transplant group, we evaluated how these random terms impact the main effects of interest which are the fixed effects of the habitats of the origin and transplant gardens (i.e., "ORIGIN.type"and "GARDEN.type").

Results
When we evaluated the "Transplant group" as a fixed effect, the overall R 2 changed very little (Table S3).On average the models changed by only 0.2%.The largest change in R 2 was in the model for succulence which decreased from 29% in the original model without the effect of transplant group (Table 2) to 26% with the effect (Table S3).On average the Transplant group effect increased the amount of variance explained by fixed effects by 17%.Using commonalityCoefficients, we found that the unique contribution of transplant group was 29-65% of the variance explained by the combined fixed effects.For several traits (e.g., height, succulence, shoot root and total biomass) the majority of the variance explained by fixed effects was due uniquely to the transplant group effect (Table S3).Adding this effect also changed the amount of variance explained by "Origin type" or "Garden type".However, when the transplant group was included, the unique contribution of origin type still explained twice as much of the variance as that of transplant garden type for shoot biomass, but a similar amount of variance as garden type for height, leaf area, succulence and total biomass.In this model, origin type explained half as much of the variance as transplant garden for the number of leaves.Therefore, we considered that the relative importance of our effects of interest ("Origin type" or "Garden type") were not changed by this approach to the analysis.
The model without the effect of transplant group explained approximately 38% of the variance in total biomass and was largely determined by random effects, and particularly the random term "transplant garden site" (43% of the variance attributed to random effects; Table 2).Adding "transplant group" resulted in similar overall variance explained by the model (39.4%) and the largest portion of the random effects (36%) were again explained by transplant site (Table S3).
The fixed effect of origin habitat type explained almost twice as much as that of transplant garden habitat type, but combined they explained only 6% of the variance in biomass (Table 2).When transplant group is included as a fixed effect, the R 2 jumps to 24% explained by combined fixed effects (according to results of r2_nakagawa, Table S3) and the effect of origin habitat type still explains more than that of transplant garden habitat type (19% compared to 13% of the variance due to fixed effects which translates to approximately 4% and 3% of the overall variance in this model).S3.As with table 2 in the main text, we provide tests for components of variance for each trait with random effects of origin site and transplant site, and fixed effects of origin habitat type and transplant garden habitat type as well as the fixed effect of transplant group.The three test of variance provide information about R 2 of the full model versus just fixed effects (r2_nakagawa), R 2 of the two random effects and combined fixed effects (rptR) and the contribution of each fixed effect without accounting for random effects (commonalityCoefficients). See methods for more details.

Supplementary Table
Garden type + Origin type xGarden type + (Garden site)Final heightNone LMEROrigin type + Garden type + Origin type x Garden type + (Origin site + Garden site)