In our modelling framework for planning assisted colonization of climate-threatened plant species, we first defined an optimized climate profile of the study species in the core area, in the form of a reduced set of meaningful climatic variables. This step was performed in order to avoid statistical pitfalls as much as possible. In fact, as outlined by several authors, the full list of initial candidate variables may be oversized (one or more predictors may have little predictive power) and/or redundant (some predictors may be correlated in a significant manner, hence resulting in multicollinearity)8. This step also met the requirement for parsimony (i.e. with accuracy being approximately equal, the best model is the simplest one). Parsimonious models are more transferable to future conditions9,10. After the removal of unnecessary predictors, the Maxent AUC test helped validate the optimized set of climate variables.

In the second step, in order to preselect potential relocation sites, we applied a dissimilarity measure between the peripheral area and the mean vector of the optimized list of climate variables in the core area. The rationale behind this step is that excessive climate dissimilarities would a priori prevent any kind of assisted colonization. It followed the principle of cautious delimitation for the extent of out-of-range movements of organisms. In fact, accounting for possible differences in the ecological niche between current and recipient sites is necessary in determining whether assisted colonization is likely to incur high risks and should therefore be avoided and other types of conservation measures (seed banks and botanical gardens) promoted6.

In the third step, we calculated species suitability modelling in the peripheral area under current and future climate conditions, using the optimized set of climate variables defined in the first step with the addition of local-scale variables. This proved necessary because, when working on limited areas, local factors such as soil type and geomorphology could assume a non-negligible weight, besides climate factors8,11. As for climate variables, we avoided use of a comprehensive list of topographical variables and focused on two variables (SOIL and TWI) with known contributions to C. foetida potential distribution. The subsequent Maxent AUC test confirmed the fitness of our choice.

Maxent was appropriate for the proposed framework as it can deal with presence-only data and has better performance than other modelling algorithms12. Correlative species distribution models, such as Maxent, assume that species distributions are in equilibrium with the environment, which does not take into account the inability of individuals to reach a suitable habitat and may possibly lead to under-prediction of species current ranges10. In our case study this risk was absent, since the occurrence locations of C. foetida were monitored for many years both in the core area (1991–2014 period) and in the peripheral area (1999–2009). In case monitoring activities at the peripheral area are not feasible, we argue that the climate distance of the peripheral area with respect to the climate profile of the species at the core area may act as cost-effective and reasonable indicator to assess whether species distribution at the peripheral area is in equilibrium with its environment. For instance, in our case study climate similarity (i.e., Mahalanobis distance) indicated that around M. Cusna not any further area can provide a suitable habitat from a climatic viewpoint (Fig. 1), thus confirming the results achieved through field monitoring that the risk of under-prediction of species current ranges was absent.

For the purposes of our study, we opted to use the PRISM dataset instead of the Worldclim dataset13. This was mainly because the study species is climatically characterized by variables that are not present in the Worldclim dataset. In addition, the 1-km resolution of Worldclim climate data cannot capture fine-scale climate variability14.

Our results indicate that even the most promising site for translocation of C. foetida in the Emilia-Romagna region will be suitable only under current and short-term climate conditions. Thus translocation of C. foetida to the five sub-areas delineated here can be expected to be successful for about 25 years, up to the medium term (2040–2069). After this, the five sub-areas will most likely start to decline and are expected to become unsuitable by the beginning of the long-term period studied (2070–2099).

Results raise one main question: are assisted colonization activities worthwhile if they are only expected to be successful in the short or medium term? It is evident that a modelling approach like that proposed here can provide the basis to rigorously examine this question. It has been suggested that the success of assisted colonization activities also involves the population dispersing seeds into the surrounding countryside and producing satellite populations15. Our results indicated that not only is C. foetida likely to disappear from the peripheral area in the future due to climate scenarios, but also that in the N-Apennines mountain system (Emilia-Romagna region) there will be no further suitable sites for this species. In other words, producing satellite populations in surrounding areas is unlikely for C. foetida even under current climate conditions and it will become increasingly improbable as time goes by.

The proposed approach (extra methodological details are presented in the Additional Supporting Information) deals with the spatio-temporal issues of species translocation. Further aspects should be considered when translocating plant species. Invasive alien species are a major threat to global biodiversity and ecosystem services16,17. Numerous plant species have been introduced in the past and many have invaded large areas of natural vegetation and are still spreading. Some species change ecosystems, affecting their capacity to provide services such as water production, soil maintenance and nutrient cycling18. The proposed framework is not intended to replace decision-making tools for planning managing strategies to respond effectively to biological invasions. However, by considering the spatio-temporal feasibility of species translocations, it helps prevent the ill-advised introduction of many plant species as it limits the number of species and potential peripheral areas for which assisted colonization seems a suitable choice. Thus, it also circumscribes the introduction of potentially invasive alien species.

Moreover, we argue that the approach proposed here increases the practicality of the assisted colonization of plant species. In fact, the scale at which thousands of plant species would have to be moved to have any noticeable impact on mitigating climate change cannot be ignored. The costs for doing this work across the world are not negligible. Our approach, by circumscribing the reintroduction areas for which assisted colonization results suitable, provides researchers and conservation managers a tool to thoroughly limit their efforts to a restricted number of sites and to identify species that will need other conservation actions in future when assisted colonization is not likely to be successful, such as storage in seed banks and/or botanical gardens.

We are aware that an eco-evolutionary response may reduce the risk of climate-driven extinction of some plant species. Even in absence of adaptation, phenotypic plasticity may partially counteract the negative effect of climate change. For instance, under moderate climate change, some snowbed species were recently observed to plastically respond to new environmental conditions19. Short and longer-term responses may also differ20,21,22 and extreme climatic events may cause complex responses of plant communities23. However we state that it seems logical and practical to assign higher priority to those plant species whose assisted colonization is more likely to be successful for the longest possible period as a result of the application of spatio-temporal modelling prior to in situ realization. For the remaining plant species, successive field studies might be realized in order to evaluate whether eco-evolutionary response and phenotypic plasticity can make assisted colonization useful despite the unfavorable projections.

Finally, by helping balance the risks and benefits of species translocation, the proposed approach has broad applicability as it can support the planning and assess the feasibility of constrained assisted colonization of any plant species in the face of climate change.