Biological correlates of description date in carnivores and primates
被引:76
作者:
Collen, B
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机构:Univ London Imperial Coll Sci Technol & Med, Dept Biol Sci, Ascot SL5 7PY, Berks, England
Collen, B
Purvis, A
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机构:Univ London Imperial Coll Sci Technol & Med, Dept Biol Sci, Ascot SL5 7PY, Berks, England
Purvis, A
Gittleman, JL
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机构:Univ London Imperial Coll Sci Technol & Med, Dept Biol Sci, Ascot SL5 7PY, Berks, England
Gittleman, JL
机构:
[1] Univ London Imperial Coll Sci Technol & Med, Dept Biol Sci, Ascot SL5 7PY, Berks, England
[2] Zool Soc London, Inst Zool, London NW1 4RY, England
[3] Univ Virginia, Dept Biol, Charlottesville, VA 22904 USA
来源:
GLOBAL ECOLOGY AND BIOGEOGRAPHY
|
2004年
/
13卷
/
05期
关键词:
Body size;
conservation;
geographical range;
hotspots;
independent contrasts;
mammal;
D O I:
10.1111/j.1466-822X.2004.00121.x
中图分类号:
Q14 [生态学(生物生态学)];
学科分类号:
071012 ;
0713 ;
摘要:
Aim To examine which aspects of primates and carnivore biology can be used to predict attributes of species yet to be discovered. Location Global. Methods Multiple regressions of phylogenetically independent contrasts and non-phylogenetic species date of description, on multiple biological predictor variables, formed from previous hypotheses tested in the literature. Results Orders differ, but both carnivore and primate species with a large geographical range tend to have been discovered earlier. When geographical range is controlled for, body mass is also significantly correlated with description date in carnivores, but remains a poor predictor in primates. No multiple-predictor model is apparent in the primates, but diurnal species are on average more likely to be described first. Carnivores not endemic to the tropics are more likely to be discovered earlier, reflecting a northern bias in description patterns. Main conclusions Geographical range is by far the most important predictor variable. The study may have ramifications for conservation hotspot selection: species possessing a small geographical range are least likely to have been described, yet are most heavily weighted in some hotspot selection algorithms.