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ZENODO
Dataset . 2015
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2015
License: CC 0
Data sources: Datacite
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Data from: Empirical tests of harvest-induced body-size evolution along a geographic gradient in Australian macropods

Authors: Prowse, Thomas A. A.; Correll, Rachel A.; Johnson, Christopher N.; Prideaux, Gavin J.; Brook, Barry W.;

Data from: Empirical tests of harvest-induced body-size evolution along a geographic gradient in Australian macropods

Abstract

1. Life-history theory predicts the progressive dwarfing of animal populations that are subjected to chronic mortality stress but the evolutionary impact of harvesting terrestrial herbivores has seldom been tested. In Australia, marsupials of the genus Macropus (kangaroos and wallabies) are subjected to size-selective commercial harvesting. Mathematical modelling suggests that harvest quotas (ca. 10–20 % of population estimates annually) could be driving body-size evolution in these species. 2. We tested this hypothesis for three harvested macropod species with continental-scale distributions. To do so, we measured more than 2 000 macropod skulls sourced from wildlife collections spanning the last 130 years. We analysed these data using spatial Bayesian models that controlled for the age and sex of specimens as well as environmental drivers and island effects. 3. We found no evidence for the hypothesized decline in body size for any species; rather, models that fit trend terms supported minor body size increases over time. This apparently counterintuitive result is consistent with reduced mortality due to a depauperate predator guild and increased primary productivity of grassland vegetation following European settlement in Australia. 4. Spatial patterns in macropod body size supported the heat dissipation limit and productivity hypotheses proposed to explain geographic body-size variation (i.e., skull size increased with decreasing summer maximum temperature and increasing rainfall, respectively). 5. There is no empirical evidence that size-selective harvesting has driven the evolution of smaller body size in Australian macropods. Bayesian models are appropriate for investigating the long-term impact of human harvesting because they can impute missing data, fit non-linear growth models and account for non-random spatial sampling inherent in wildlife collections.

Macropod specimen details and extracted spatial covariate valuesThis file provides the following information for macropod skulls of three Macropus species sourced from nine wildlife collections: Species, Longitude (as recorded on the specimen tag), Latitude (as recorded on the specimen tag), gridLongitude (the central longitude of the grid cell from which covariates were extracted for the specimen), gridLatitude (the central latitude of the grid cell from which covariates were extracted for the specimen), Sex, Island, Year (the year of collection as recorded on the specimen tag), MI (molar index), CL (condylobasal length), WinterMinTemp (mean minimum temperature over the winter months), SummerMaxTemp (mean maximum temperature over the summer months), SummerWetBulbTemp (mean wet bulb temperature over the summer months), AnnualRain (mean annual rainfall), AnnualNDVI (mean annual Normalised Difference Vegetation Index), GrowSeasRain (mean rainfall during the growing season), GrowSeasNDVI (mean Normalised Difference Vegetation Index during the growing season), MinSeasRain (mean rainfall of the driest season), MinSeasNDVI (mean Normalised Difference Vegetation Index for the season with the lowest mean NDVI).ProwseEtAl_MacropodData.csv

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Keywords

Bergmann's rule, Macropus fuliginosus, Macropus giganteus, Holocene, Bergmann’s rule, human-induced evolution, Macropus rufogriseus, conditional autoregressive model, harvesting, Bayesian hierarchical model

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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