Summary
1.Under the effects of rapid environmental change, such as climate change and land degradation, assessment of plant species potential distribution is becoming increasingly important for conservation purposes. Moreover, land administrators need reliable predictions of species suitability for planning a wide range of management activities. 2 . In this study, we used the recent Maxent algorithm for modelling the niche of Arnica montana within a Site of Community Importance in the Alps, with the ultimate aim of providing a rigorous evidence base for management of this locally threatened species. We built a final suitability map taking into account (i) the minimization of spatial autocorrelation through the use of a constrained random split of sampled data; (ii) the use of a stepwise selection of predictors in order to obtain a reduced model containing only meaningful variables; (iii) the comparison of the predictive power of three sets of environmental predictors; (iv) the identification of the most suitable areas by overlaying predictions of three competing models; (v) the use of divergence maps as a complement to conventional performance comparison assessments. 3. Maxent improved accuracy both on training and test data sets. Elevation, geomorphology and hosting habitats performed as effective primary predictors. A reduced model based on the outcomes of a preliminary stepwise selection analysis of predictors gave the best accuracy score on test data. Two parts of the study area have been selected for management as a result of areas of agreement between the three competing models. 4. Synthesis and applications . There remain important methodological issues that need to be improved in order to increase confidence in niche modelling and ensure that reintroduction and management activities for threatened or rare plant species are based on reliable distribution models. Modellers can improve predictions of plant distribution by addressing methodological topics that are often overlooked, as demonstrated for A. montana in this study.
Assisted colonization is one way of facilitating range shifts for species that are restricted in their ability to move in response to climate change. Here we conceptualize and apply a new decision framework for modelling assisted colonization of plant species prior to in situ realization. Three questions were examined: a) Is species translocation useful in a certain area? b) where, and c) how long will it be successful in the future? Applying our framework to Carex foetida in Italy at the core of its distribution and its southern edge revealed that assisted colonization could be successful in short-term (2010–2039) climate conditions, partially in medium (2040–2069) but not in long-term (2070–2099) scenarios. We show that, for some species, it is likely that assisted colonization would be successful in some portions of the recipient site under current and short-term climate conditions, but over the mid- and long-term, climate changes will make species translocation unsuccessful. The proposed decision framework can help identify species that will need different conservation actions (seed banks and/or botanical gardens) when assisted colonization is unlikely to be successful. Furthermore it has broad applicability, as it can support planning of assisted migration in mountainous areas in the face of climate change.
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