Karen S. Richardson
McGill University
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Publication
Featured researches published by Karen S. Richardson.
Proceedings of The Royal Society of London Series B-biological Sciences | 2001
Craig Moritz; Karen S. Richardson; Simon Ferrier; Geoffrey B. Monteith; John Stanisic; Stephen E. Williams; Trevor Whiffin
Prioritizing areas for conservation requires the use of surrogates for assessing overall patterns of biodiversity. Effective surrogates will reflect general biogeographical patterns and the evolutionary processes that have given rise to these and their efficiency is likely to be influenced by several factors, including the spatial scale of species turnover and the overall congruence of the biogeographical history. We examine patterns of surrogacy for insects, snails, one family of plants and vertebrates from rainforests of northeast Queensland, an area characterized by high endemicity and an underlying history of climate–induced vicariance. Nearly all taxa provided some level of prediction of the conservation values for others. However, despite an overall correlation of the patterns of species richness and complementarity, the efficiency of surrogacy was highly asymmetric; snails and insects were strong predictors of conservation priorities for vertebrates, but not vice versa. These results confirm predictions that taxon surrogates can be effective in highly diverse tropical systems where there is a strong history of vicariant biogeography, but also indicate that correlated patterns for species richness and/or complementarity do not guarantee that one taxon will be efficient as a surrogate for another. In our case, the highly diverse and narrowly distributed invertebrates were more efficient as predictors than the less diverse and more broadly distributed vertebrates.
Systematic Biology | 2002
Vicki A. Funk; Karen S. Richardson
Systematic data in the form of collections data are useful in biodiversity studies in many ways, most importantly because they serve as the only direct evidence of species distributions. However, collecting bias has been demonstrated for most areas of the world and has led some to propose methods that circumvent the need for collections data. New methods that model collections data in combination with abiotic data and predict potential total species distribution are examined using 25,111 records representing 5,123 species of plants and animals from Guyana; some methods use the reduced number of 320 species. These modeled species distributions are evaluated and potential high-priority biodiversity sites are selected based on the concept of irreplaceability, a measure of uniqueness. The major impediments to using collections data are the lack of data that are available in a useful format and the reluctance of most systematists to become involved in biodiversity and conservation research.
BioScience | 2004
Simon Ferrier; George V. N. Powell; Karen S. Richardson; Glenn Manion; Jake J.M. Overton; Thomas F. Allnutt; Susan S.E. Cameron; Kellie Mantle; Neil D. Burgess; Daniel D.R. Faith; John F. Lamoreux; Gerold Kier; Robert J. Hijmans; Vicki A. Funk; Gerasimos Cassis; Brian L. Fisher; Paul Flemons; David C. Lees; Jon C. Lovett; Renaat Van Rompaey
Abstract Global conservation assessments require information on the distribution of biodiversity across the planet. Yet this information is often mapped at a very coarse spatial resolution relative to the scale of most land-use and management decisions. Furthermore, such mapping tends to focus selectively on better-known elements of biodiversity (e.g., vertebrates). We introduce a new approach to describing and mapping the global distribution of terrestrial biodiversity that may help to alleviate these problems. This approach focuses on estimating spatial pattern in emergent properties of biodiversity (richness and compositional turnover) rather than distributions of individual species, making it well suited to lesser-known, yet highly diverse, biological groups. We have developed a global biodiversity model linking these properties to mapped ecoregions and fine-scale environmental surfaces. The model is being calibrated progressively using extensive biological data sets for a wide variety of taxa. We also describe an analytical approach to applying our model in global conservation assessments, illustrated with a preliminary analysis of the representativeness of the worlds protected-area system. Our approach is intended to complement, not compete with, assessments based on individual species of particular conservation concern.
Behavioral Ecology and Sociobiology | 1992
James W. A. Grant; Colin A. Chapman; Karen S. Richardson
SummaryWe tested the hypothesis that undefended home ranges are larger than defended home ranges using data collected from the literature for three groups of mammals. A matched-pairs analysis of populations within species or species within genera showed that undefended home ranges were larger than defended home ranges for carnivores and male ungulates, but not for primates. Primates may have been an exception because they violated a key assumption of the hypothesis, that defence costs increase with the size of the defended area. Undefended home ranges were 5.4 and 15.2 times larger than defended home ranges for carnivores and male ungulates, respectively. Whether or not a home range is defended is an important source of variation that should be included in future studies of home range size.
Ecography | 2006
Jane Elith; Catherine H. Graham; Robert P. Anderson; Miroslav Dudík; Simon Ferrier; Antoine Guisan; Robert J. Hijmans; Falk Huettmann; John R. Leathwick; Anthony Lehmann; Jin Li; Lúcia G. Lohmann; Bette A. Loiselle; Glenn Manion; Craig Moritz; Miguel Nakamura; Yoshinori Nakazawa; Jacob C. M. Mc Overton; A. Townsend Peterson; Steven J. Phillips; Karen S. Richardson; Ricardo Scachetti-Pereira; Robert E. Schapire; Jorge Soberón; Stephen E. Williams; Mary S. Wisz; Niklaus E. Zimmermann
Diversity and Distributions | 2007
Simon Ferrier; Glenn Manion; Jane Elith; Karen S. Richardson
Biological Journal of The Linnean Society | 2005
Vicki A. Funk; Karen S. Richardson; Simon Ferrier
Systematic Biology | 2002
Vicki A. Funk; Ann K. Sakai; Karen S. Richardson
Oikos | 1989
Colin A. Chapman; Lauren J. Chapman; Karen S. Richardson
BioScience | 2004
Simon Ferrier; George V. N. Powell; Karen S. Richardson; Glenn Manion; J. Overton; Thomas F. Allnutt; K. Mantle; Neil D. Burgess; Faith D.P; G. Kier; Robert J. Hijmans; Vicki A. Funk; Gerasimos Cassis; Brian L. Fisher; Paul Flemons; David C. Lees; Jon C. Lovett; R.S.A.R. Van Rompaey; J.C. Solomon
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Commonwealth Scientific and Industrial Research Organisation
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