{'fraction_non_alphanumeric': 0.024508111839834312, 'fraction_numerical': 0.027959958577839145, 'mean_word_length': 5.419497784342688, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Restoring local climate refugia to enhance the capacity for dispersal-limited species to track climate change

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors which buffer against variability in time. However, climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population’s capacity to track increasing temperatures over time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species’ dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher local heterogeneity and lower environmental stochasticity. When simulating a management action that increased the local heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species’ persistence under climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.


30
Many species are tracking climate change by shifting their ranges to higher latitudes and 31 elevations (Parmesan et al. 1999, Chen et al. 2011. Species that are adapted to a narrow range of 32 climate conditions that cannot shift to analogous climates quickly enough could be at risk of 33 extinction (Pearson 2006, Urban 2015. Traits that could limit a species' ability to track climate 34 change include short dispersal, narrow climate tolerance, or low fecundity (Pearson 2006, Urban 35 2015). The ability to track climate change also depends on characteristics of the environment, as 36 variation in spatial heterogeneity and topography mean that local climate will change at different . 55 Climate-vulnerable species that do not currently live near or within climate refugia might then 56 require alternative conservation strategies (Roberts & Hamann 2016), such as restoring the 57 environmental conditions that might have previously supported refugia. 58 One potential source of climate refugia that could be impacted by anthropogenic  of connected patches on a one-dimensional temperature gradient (e.g., latitudinal or elevational 100 gradient). To represent spatio-temporal heterogeneity in temperature, each patch contains several 101 subpatches with unique temperatures that change stochastically over time at a designated level of 102 variability. During each time step, the population cycles through reproduction, dispersal, and 103 density-dependent survival. Species differ by dispersal ( ), thermal tolerance breadth ( ), and 104 fecundity ( ). Each environment is defined by the standard deviation in interannual 105 environmental stochasticity ( ) and the standard deviation in local climate heterogeneity ( ). We 106 randomized these five parameters for each simulation to explore how each influences species' 107 persistence and population size. We then implemented changing spatial heterogeneity or 108 environmental stochasticity to simulate management actions that restore refugia. (1) We represent temperature variation over time with the environmental stochasticity parameter, (Fig. 1d). Each time step, all patches change in temperature by an average value of  (Table 1). We 178 generated species by drawing the mean dispersal distance ( ) from a log-uniform distribution 179 and the thermal tolerance breadth ( ) and fecundity ( ) from uniform distributions (Table 1).

180
In the first set of simulations, we evaluated which types of species and environments limitations (e.g., species with both short dispersal and narrow thermal tolerance) were less likely 217 to persist through climate change (Fig. 3, S3).

218
On average, restoring heterogeneity along the temperature gradient (by doubling ) 219 improved a species' likelihood of persisting through 4°C of temperature increase over 100 years 220 more often than it decreased a species' likelihood of persisting (Fig. 3, Fig. 4a,c,e). Restoring 221 heterogeneity also generally increased a species' population size relative to no action. However, 222 when the temperature increased by only 2°C over 100 years, restoring local heterogeneity was 223 more likely to decrease a species' population size, and the species that were more likely to 224 benefit were those that were already likely to persist (Fig. S4, S5). In simulations with 4°C of 225 temperature increase, species with shorter average dispersal particularly benefited from increased 226 heterogeneity (Fig. 3). Though many of the species with the shortest dispersal ranges went 227 extinct regardless of management, increasing the local heterogeneity was more likely to prevent extinction and increase the final population size and rarely decreased population size or caused 229 extinction (Fig. 4a). Species with longer dispersal ranges were less likely to go extinct without 230 management, and increasing heterogeneity was less likely to benefit and more likely to decrease 231 the population size or cause the extinction of these species. Species with narrow thermal 232 tolerance or low fecundity were also unlikely to persist without heterogeneity restoration, but 233 these species did not benefit as strongly and were more likely to experience negative effects from 234 increased heterogeneity when compared with species with shorter dispersal ranges (Fig. 4c,e).

235
Decreasing the environmental stochasticity along the temperature gradient (by halving 236 the value of ) typically increased the persistence likelihood and population size (relative to no 237 action) of species throughout our simulations under both the 2°C and 4°C increase scenarios 238 (Fig. 4b,d,f, S5). Decreasing the stochasticity did not strongly benefit species with very short 239 dispersal, narrow thermal tolerance, or low fecundity, as many of these species were likely to go 240 extinct regardless of management action. Species with longer dispersal, narrower thermal 241 tolerance, and higher fecundity were more likely to benefit from decreased stochasticity.

242
Comparing both restoration strategies in the 4°C increase scenario, we found that 243 restoring heterogeneity was particularly beneficial to species with low dispersal (below the 25% 244 quantile) but with high values in one or both of the other two traits (above the 75% quantile) 245 (Fig. 3). For these combinations, restoring heterogeneity either prevented the species from going      The standard deviation of the temperature among subpatches within a patch depends on the local 535 temperature heterogeneity . Between the beginning and end of climate change, analogous temperatures 536 are closer with higher rather than lower local temperature heterogeneity. represent the proportion of species that benefit from either increasing heterogeneity or decreasing 553 stochasticity (final population size of the species more than 105% relative to simulations without 554 management action) and the proportion that are negatively affected in parentheses (final population size 555 less than 95% relative to simulations without management action). Darker colors in the final three 556 columns represent higher values. indicates simulations where a species goes extinct with no action but persists with management. Hues 564 from yellow to red indicate simulations where management increases a species' population size relative to 565 no action. Gray indicates simulations where a species persists, and management has little effect on the 566 final population size. Hues from cyan to blue indicate simulations where management decreases a 567 species' population size relative to no action. Dark blue indicates that management caused the species to 568 go extinct. 569