General information of the tracked individuals.

<p>General information of the tracked individuals.</p

Skull metric dataset from LaPoint et al. RSOpenScience 2017 Growth overshoot and seasonal size changes in the skulls of two weasel species

This .csv contains the individuals used within our analyses and 18 attributes that were recorded or measured by the lead author. These attributes are listed below with definitions: species (2 levels: Mustela erminea, Mustela nivalis), institution (14 levels: BRUS Muséum d‘Histoire Naturelle Brussels, CUMV Cornell University, HELS Finnish Museum of Natural History Helsinki , MFN Museum für Naturkunde Berlin, MNHG Muséum d‘Histoire Naturelle Geneva, MRI Mammal Research Institute Białowieża , MSU Michigan State University Museum, MVZ Museum of Vertebrate Zoology Berkeley, NCMNS North Carolina Museum of Natural Sciences Raleigh, NCSU North Carolina State University, NYSM New York State Museum Albany, ROM Royal Ontario Museum Toronto, UMMZ University of Michigan Museum of Zoology, USNM National Museum of Natural History Washington), catalog (unique values, for referencing to actual specimens in natural history collections, but not used for analyses), age (3 levels: A, adult, J, juvenile, S, subadult, see methods for definitions), condylobasal length (numeric, measured in mm), height of braincase with auditory bullae (numeric, measured in mm), braincase depth (numeric, measured in mm, excludes auditory bullae), braincase width (numeric, measured in mm), B2CBL (numeric, relative value of braincase depth to condylobasal length), MDY (date, month/day/year), doy (numeric, day of year), sex (2 levels: F, female, M, male), country (24 levels, Austria, Belarus, Belgium, Canada, China, Czech Republic, Egypt, Finland, France, Germany, Italy, Korea, Morocco, Netherlands, Norway, Poland, Romania, Russia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States), state (119 levels, state/region/province), location (549 levels, town/village when provided, otherwise see methods), origin (8 levels, broad geographic regions that were created to bin specimens into spatially similar regions, see Methods for details, all origins were included in analyses that present 'global' results), latitude (decimal degrees, WGS84), longitude (decimal degrees, WGS84)

Tracks of the individuals included in this study.

<p>Tracks of the individuals included in this study.</p

Skull measurements for measurement error

Repeated skull measurements from X-ray images on 10 individuals used to calculate the technical measurement erro

Skull measurements from X-ray images in common shrews

Measurements in absolute values (mm) of braincase height, skull length, braincase width and tooth row and corrected by tooth row (cor) from individual (id) shrews captured/recaptured at different times (date) along their lifespan

Table S3. from Growth overshoot and seasonal size changes in the skulls of two weasel species

We bootstrapped t-tests (5000 iterations, with replacement) between age categories for each sex and species combination to produce a normally distributed random sample from the observed non-normally distributed measurement data and compared the likelihood (p-value) of calculating the number of possible t-values (i.e., tb; mean t-value from bootstrapped simulations) that was greater than or equal to the observed absolute t-value (i.e., to). Significant p-values (<0.05) indicate “true” differences in observed means that are not artifacts of the observed data distribution. These bootstrapped t-tests suggest braincase depth growth overshoots across sexes and species in juveniles, as these braincases are significantly taller than all other age categories, yet similar to or significantly shorter in CBL to all other age categories (see metric means in Table 1). The results presented here suggest these significant differences persist despite the non-normal distribution of the data. Bold to values indicate significant differences between groups via t-tests on observed data directly

Per marten, top: the utilization distribution of marten highway crossing locations within 200 m from the highway (UD_cross).

<p>Bottom: the observed probability of crossing the highway at each road segment (UD_cross at highway location; solid line). Grey areas represent the 5–95% percentile envelope of reference from the simulated datasets. White (black) arrows indicate highway segments with higher (lower) use than expected. Points indicate road passage location. For each marten, the highway segment in the upper-half of the figure is projected in the X axis from the bottom picture.</p

A: Highway A6 in southern Portugal and its crossing structures (squares - culverts, circles - under/over passages), land covers, and marten home range areas (white lines).

<p>B: Duration (2008–2009) of tracking nights for each marten (each bar is one night) with “LC” indicating loss of contact and “WVC” indicating a confirmed WVC (corpse recovered). Apparent home range overlap of F1 with M1 and M4, and F5 with F7 correspond to distinct periods.</p

Summary data for each marten considered in the present study.

<p>Summary data for each marten considered in the present study.</p

Maximum likelihood estimates of parameters for the ‘responsive’ model: μ - mean angle (in absolute values, ranging from 0 to |π| radians); θ₁ – strength of concentration parameter when marten is at distance zero from the highway; θ₂ – rate (exponential) of decay of the concentration parameter as the animal moves farther the highway.

<p>Maximum likelihood estimates of parameters for the ‘responsive’ model: μ - mean angle (in absolute values, ranging from 0 to |π| radians); θ₁ – strength of concentration parameter when marten is at distance zero from the highway; θ₂ – rate (exponential) of decay of the concentration parameter as the animal moves farther the highway.</p