chainplan: an R package for climate-smart selection of conservation areas with retention refugia and dispersal chains

Conservation areas chosen for present species distributions can lose these species as the climate changes. Spatiotemporal complementarity addresses the problem by choosing places where species can persist through time (retention refugia), together with sequences of places through which species can follow shifting climates (dispersal chains). The approach has lacked an open, general implementation. I present chainplan 1, an R package that implements the procedure as documented and tested functions: planning units, protected areas, anchors and targets per region; retention refugia; independent dispersal chains built period by period, by minimum-cost network flow or one at a time; greedy complementarity selection with lock-in and goal-essential units; exact selection by integer programming, either the cheapest network that meets the targets or the most that a fixed share of the land can secure; and candidate boundaries drawn with density-based clustering, concave hulls and least-cost merging. Projections enter as presence and absence or as probabilities of occurrence. With probabilities, each refugium or chain is valued by a probability of persistence, by default its least suitable period or, under a rule of occupancy with recolonisation, its probability of being occupied at the end of the horizon; independent units combine as 1 − Π(1 − π), targets are probabilities, and a target can ask for several independent routes to persistence, which is what a larger budget buys once every species has one. An audit register records why each planning unit was chosen and which species depend on it. In the Azores case study (1,060 planning units, 167 species), greedy and exact solutions each took under one second and differed by at most 4.5%; in a case study of 292 Iberian vertebrates on 5,899 planning units, greedy networks cost 10–76% more than exact minimum-cost networks found in seconds. chainplan is free software under the GPL-3 licence.

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Published
2026-10-26
DOI
https://doi.org/10.22541/authorea.15011053/v1
Primary Topic
Species Distribution and Climate Change
Type
preprint
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chainplan: an R package for climate-smart selection of conservation areas with retention refugia and dispersal chains

Miguel B. Araújo
Species Distribution and Climate Change
preprint

chainplan: an R package for climate-smart selection of conservation areas with retention refugia and dispersal chains

Miguel B. Araújo
preprint en

Abstract

Conservation areas chosen for present species distributions can lose these species as the climate changes. Spatiotemporal complementarity addresses the problem by choosing places where species can persist through time (retention refugia), together with sequences of places through which species can follow shifting climates (dispersal chains). The approach has lacked an open, general implementation. I present chainplan 1, an R package that implements the procedure as documented and tested functions: planning units, protected areas, anchors and targets per region; retention refugia; independent dispersal chains built period by period, by minimum-cost network flow or one at a time; greedy complementarity selection with lock-in and goal-essential units; exact selection by integer programming, either the cheapest network that meets the targets or the most that a fixed share of the land can secure; and candidate boundaries drawn with density-based clustering, concave hulls and least-cost merging. Projections enter as presence and absence or as probabilities of occurrence. With probabilities, each refugium or chain is valued by a probability of persistence, by default its least suitable period or, under a rule of occupancy with recolonisation, its probability of being occupied at the end of the horizon; independent units combine as 1 − Π(1 − π), targets are probabilities, and a target can ask for several independent routes to persistence, which is what a larger budget buys once every species has one. An audit register records why each planning unit was chosen and which species depend on it. In the Azores case study (1,060 planning units, 167 species), greedy and exact solutions each took under one second and differed by at most 4.5%; in a case study of 292 Iberian vertebrates on 5,899 planning units, greedy networks cost 10–76% more than exact minimum-cost networks found in seconds. chainplan is free software under the GPL-3 licence.

Consejo Superior de Investigaciones Científicas (ES)
Species Distribution and Climate Change
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