Planning for assisted colonization of plants in a warming world

Abstract

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.

Translocations, conservation, and climate change: use of restoration sites as protorefuges and protorefugia

“…Diverse communities, with a diverse genetic mix within species, are desirable to build in resilience and enable systems to persist into new states. Building resilience to threats through translocation has long been accepted as a method to help conserve species-providing them with the space and habitat required to survive (Richardson et al 2009;Ferrarini et al 2016). This may be of significant long-term benefit, as long as best practice is applied and associated dangers of translocations are minimized by the following appropriate codes (e.g.…”

The future of cold‐adapted plants in changing climates: Micranthes (Saxifragaceae) as a case study

“…However, predictions from ENMs have many downfalls, including errors introduced from misidentified specimens and inaccurate georeferencing, lack of incorporation of eco‐evolutionary process. Furthermore, ENMs do not model microclimates generated by habitat heterogeneity (Cotto et al., ; Ferrarini et al., ; Kearney & Porter, ; Lozier, Aniello, & Hickerson, ). Despite, these limitations, ENMs provide a basis for directing conservation concerns (Ferrarini et al., ).…”

“…Furthermore, ENMs do not model microclimates generated by habitat heterogeneity (Cotto et al., ; Ferrarini et al., ; Kearney & Porter, ; Lozier, Aniello, & Hickerson, ). Despite, these limitations, ENMs provide a basis for directing conservation concerns (Ferrarini et al., ). There have been many studies employing ENMs at regional scales (i.e., political boundaries), and these include many species with vastly different evolutionary histories, climatic tolerances, and dispersal abilities (Loarie et al., ; Randin et al., ; Warren, Wright, Seifert, & Shaffer, ).…”

“…Despite, these limitations, ENMs provide a basis for directing conservation concerns (Ferrarini et al, 2016). There have been many studies employing ENMs at regional scales (i.e., political boundaries), and these include many species with vastly different evolutionary histories, climatic tolerances, and dispersal abilities (Loarie et al, 2008;Randin et al, 2009;Warren, Wright, Seifert, & Shaffer, 2014 We examine these questions in an evolutionary context, and by investigating within the Micranthes clade, rather than between clades, we take into account that many of the factors influencing adaptation and dispersal are likely to share an evolutionary history.…”

High‐resolution distribution modeling of a threatened short‐range endemic plant informed by edaphic factors

“…Even at the known populations, the modeling suggests that not all suitable habitat is filled (Figure 4). Correlative modeling approaches such as MaxEnt are often used to guide these enterprises (Ferrarini et al, 2016;Regan et al, 2012). Correlative modeling approaches such as MaxEnt are often used to guide these enterprises (Ferrarini et al, 2016;Regan et al, 2012).…”