Data from: Seed masting causes fluctuations in optimum litter size and lag load in a seed predator
Data files
Apr 26, 2022 version files 409.18 KB
-
Cones_data_README.docx
13.46 KB
-
Cones_data.csv
20.31 KB
-
Fall_Numbers_README.docx
13.13 KB
-
Fall_Numbers.csv
589 B
-
Juvenile_data_README.docx
13.27 KB
-
Juvenile_data.csv
152.79 KB
-
Litter_data_README.docx
13.59 KB
-
Litter_data.csv
164.24 KB
-
Spring_Numbers_README.docx
13.25 KB
-
Spring_Numbers.csv
4.54 KB
Abstract
The episodic production of large seed crops by some perennial plants (masting) is known to increase seed escape by alternately starving and swamping seed predators. These pulses of resources might also act as an agent of selection on the life histories of seed predators, which could indirectly enhance seed escape by inducing an evolutionary load on seed predator populations. We measured natural selection on litter size of female North American red squirrels (Tamiasciurus hudsonicus) across 28 years and five white spruce (Picea glauca) masting events. Observed litter sizes were similar to optimum litter sizes during non-mast years but were well below optimum litter sizes during mast years. Mast events, therefore, caused selection for larger litters (’ = 0.25) and a lag load (L = 0.25) on red squirrels during mast years. Reduced juvenile recruitment associated with this lag load increased the number of spruce cones escaping squirrel predation. Although, offspring and
parents often experienced opposite environments with respect to the mast, we found no effect of environmental mismatches across generations on either offspring survival or population growth. Instead, squirrels plastically increased litter sizes in anticipation of mast events, which partially, although not completely, reduced the lag load resulting from this change in food availability. These results, therefore, suggest that in addition to ecological and behavioural effects on seed predators, mast seed production can further enhance seed escape by inducing maladaptation in seed predators through fluctuations in optimal trait values.