DOI: 10.5061/dryad.g7641
title: Data from: Fitness declines toward range limits and local adaptation to climate affect dispersal evolution during climate-induced range shifts

description: Dispersal ability will largely determine whether species track their
 climatic niches during climate change, a process especially important for
 populations at contracting (low-latitude/low-elevation) range limits that
 otherwise risk extinction. We investigate whether dispersal evolution at
 contracting range limits is facilitated by two processes that potentially
 enable edge populations to experience and adjust to the effects of climate
 deterioration before they cause extinction: (i) climate-induced fitness
 declines towards range limits and (ii) local adaptation to a shifting
 climate gradient. We simulate a species distributed continuously along a
 temperature gradient using a spatially explicit, individual-based model.
 We compare range-wide dispersal evolution during climate stability vs.
 directional climate change, with uniform fitness vs. fitness that declines
 towards range limits (RLs), and for a single climate genotype vs. multiple
 genotypes locally adapted to temperature. During climate stability,
 dispersal decreased towards RLs when fitness was uniform, but increased
 when fitness declined towards RLs, due to highly dispersive genotypes
 maintaining sink populations at RLs, increased kin selection in smaller
 populations, and an emergent fitness asymmetry that favoured dispersal in
 low-quality habitat. However, this initial dispersal advantage at
 low-fitness RLs did not facilitate climate tracking, as it was outweighed
 by an increased probability of extinction. Locally adapted genotypes
 benefited from staying close to their climate optima; this selected
 against dispersal under stable climates but for increased dispersal
 throughout shifting ranges, compared to cases without local adaptation.
 Dispersal increased at expanding RLs in most scenarios, but only increased
 at the range centre and contracting RLs given local adaptation to climate.
description: Fig 2 (heatmap) data
 files and R codeData and R code needed
 to create Fig 2 in Hargreaves et al (2015) J Evol Biol. One data file for
 each of the 6 figure panels. Each file contains evolved D across the range
 in each of 500 generations of stable climate followed by 1000 generations
 of climate change.Fig 2
 (heatmap).zipFig 3 (D lines) data and
 R codeData and R code needed
 to create Fig 3 in Hargreaves et al (2015) J Evol Biol. One data file for
 each of the 6 models shown. Each file contains evolved D across the range
 after 500 generations of stable climate and after 1000 generations of
 climate change, averaged across 10 runs per cost per
 model.Fig 3
 (D lines).zipFig 4 (delta.D) data and
 R codeData and R code needed
 to create Fig 4 in Hargreaves et al (2015) J Evol Biol. One data file for
 each of the 4 models (ie figure rows) shown. Each file contains evolved D
 across the range after 500 generations of stable climate and after 1000
 generations of climate change for 30 runs per model.Fig 4
 (delta.D).zipFig 6 (D vs density)
 data and R codeData and R code needed
 to create Fig 6 in Hargreaves et al (2015) J Evol Biol. Two data files
 (one for evolved D and one for density) for each of 2 model runs, one with
 dispersal (dispersal distance =1 as normal) and one run without dispersal
 (dispersal distance =0).Fig 6 (D vs
 density).zipAppendix S1 data and R
 code for each figureData and R code needed
 to create figures in Appendix S1 in Hargreaves et al (2015) J Evol Biol.
 All figures remake Fig 3 while varying one parameter. Fig S1.1 shows
 murate = .005; Fig S1.2 shows avshift = .01, .05, .2; Fig. S1.3 shows
 K=10; Fig. S1.4 shows effect of eliminating kin selection by randomizing
 individuals within columns before each dispersal event. For each figure
 there is 1 data file per model. Each data file contains evolved D across
 the range after 500 generations of stable climate and after 1000
 generations of climate change, for 10 runs per cost.Appendix
 S1.zipModel code Matlab
 fileCode to run the model
 simulations.rangeshift (for
 dryad).mFig 5 (extinction
 threshold) Matlab codeMatlab code to run the
 simulations necessary to determine the relationship between the speed of
 climate change (avshift) and probability of extinction.rangeshift_thresh (for
 dryad).m