Biodiversity and evolutionary history: useful extensions of the PD phylogenetic diversity assessment framework
Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative...
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| Published in | Annals of the New York Academy of Sciences Vol. 1289; no. 1; pp. 69 - 89 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
United States
Blackwell Publishing Ltd
01.06.2013
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0077-8923 1749-6632 1749-6632 |
| DOI | 10.1111/nyas.12186 |
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| Abstract | Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting‐up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species‐level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence–absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs. |
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| AbstractList | Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting-up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species-level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence-absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs. Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting‐up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species‐level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence–absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs. Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting-up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species-level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence-absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs. [PUBLICATION ABSTRACT] Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting-up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species-level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence-absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs.Evolutionary biology is a core discipline in biodiversity science. Evolutionary history or phylogeny provides one natural measure of biodiversity through the popular phylogenetic diversity (PD) measure. The evolutionary model underlying PD means that it can be interpreted as quantifying the relative feature diversity of sets of species. Quantifying feature diversity measures possible future uses and benefits or option values. Interpretation of PD as counting-up features is the basis for an emerging broad family of PD calculations, of use to both biodiversity researchers and decision makers. Many of these calculations extend conventional species-level indices to the features level. Useful PD calculations include PD complementarity and endemism, Hill and Valley numbers incorporating abundance, and PD dissimilarities. A flexible analysis framework is provided by expected PD calculations, applied to either probabilities of extinction or presence-absence. Practical extensions include phylogenetic risk analysis and measures of distinctiveness and endemism. These support the integration of phylogenetic diversity into biodiversity conservation and monitoring programs. |
| Author | Faith, Daniel P. |
| Author_xml | – sequence: 1 givenname: Daniel P. surname: Faith fullname: Faith, Daniel P. email: danfaith8@yahoo.com.au organization: The Australian Museum, Sydney, Australia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23773093$$D View this record in MEDLINE/PubMed |
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Conserving cr 1993; 27 2010; 107 2013; 62 2007; 73 2012; 14 2011; 470 2013; 8 1996; 76 1992; 8 2010; 21 2011; 366 2009; 10 2010; 25 2010; 24 2000; 125 2008; 22 2012; 28 2012; 27 2007; 62 2007; 2 2005; 71 1980 7 2010; 2 2012; 24 2012; 23 2010; 5 2012; 22 2010; 4 2012; 21 2010; 7 1989 2009; 18 1988 2007; 445 2012; 180 2012; 39 2011; 4 2011; 6 2011; 8 1996; 10 2007; 13 1998; 66 2012; 50 1987; 69 2013; 339 2005; 8 2012; 43 1995; 71 2012; 2012 2013; 22 1973; 54 2002; 51 2008; 8 2008; 3 2011; 14 2012; 58 2009; 58 2010; 64 1994; 345 2013; 11 2003; 6 1971; 59 2011; 22 2008; 157 1996; 5 2008; 275 2012; 64 2012 2010 2010; 365 2008; 17 2009 2008 2011; 33 1992; 107 2006 2006; 6 2005 2008; 11 2006; 2 2007; 56 2002; 27 2011; 2011 2012; 3 2012; 1 2004; 18 2009; 6 2012; 279 2009; 3 2012; 7 2003; 300 2012; 4 2012; 5 1994; 2 1992; 61 2012; 8 e_1_2_7_104_1 e_1_2_7_7_1 IUCN Red List Standards and Petitions Subcommittee (e_1_2_7_87_1) 2006 e_1_2_7_19_1 e_1_2_7_60_1 e_1_2_7_83_1 e_1_2_7_100_1 e_1_2_7_123_1 e_1_2_7_41_1 e_1_2_7_64_1 Faith D.P. (e_1_2_7_15_1) 2008 e_1_2_7_11_1 e_1_2_7_45_1 e_1_2_7_68_1 e_1_2_7_26_1 e_1_2_7_49_1 e_1_2_7_116_1 e_1_2_7_90_1 McNeely J.A. (e_1_2_7_29_1) 1988 e_1_2_7_112_1 e_1_2_7_94_1 Shah N. (e_1_2_7_108_1) 2011; 2011 e_1_2_7_71_1 e_1_2_7_52_1 e_1_2_7_98_1 e_1_2_7_23_1 e_1_2_7_33_1 e_1_2_7_56_1 e_1_2_7_79_1 Kembel S.W. (e_1_2_7_37_1) 2012; 2012 Reid W.V. (e_1_2_7_30_1) 1989 Carroll S.P. (e_1_2_7_3_1) 2008 e_1_2_7_109_1 e_1_2_7_4_1 e_1_2_7_105_1 e_1_2_7_8_1 e_1_2_7_124_1 e_1_2_7_101_1 e_1_2_7_16_1 e_1_2_7_40_1 e_1_2_7_82_1 e_1_2_7_120_1 e_1_2_7_12_1 e_1_2_7_86_1 e_1_2_7_67_1 e_1_2_7_48_1 University of Georgia (e_1_2_7_44_1) 2012 e_1_2_7_117_1 e_1_2_7_113_1 e_1_2_7_51_1 e_1_2_7_70_1 e_1_2_7_93_1 e_1_2_7_24_1 e_1_2_7_32_1 e_1_2_7_55_1 e_1_2_7_74_1 e_1_2_7_97_1 e_1_2_7_20_1 e_1_2_7_36_1 e_1_2_7_59_1 e_1_2_7_78_1 Faith D.P. (e_1_2_7_21_1) e_1_2_7_5_1 e_1_2_7_106_1 e_1_2_7_9_1 Salani F.S. (e_1_2_7_75_1) 2011; 2011 e_1_2_7_102_1 e_1_2_7_17_1 e_1_2_7_62_1 e_1_2_7_81_1 e_1_2_7_121_1 e_1_2_7_13_1 e_1_2_7_43_1 e_1_2_7_66_1 e_1_2_7_85_1 Fancello L. (e_1_2_7_111_1) 2012; 2012 e_1_2_7_47_1 e_1_2_7_89_1 e_1_2_7_28_1 Flores G.E. (e_1_2_7_110_1); 7 e_1_2_7_118_1 e_1_2_7_114_1 e_1_2_7_73_1 e_1_2_7_50_1 e_1_2_7_92_1 e_1_2_7_25_1 e_1_2_7_77_1 e_1_2_7_54_1 e_1_2_7_96_1 e_1_2_7_35_1 e_1_2_7_58_1 e_1_2_7_39_1 e_1_2_7_6_1 Faith D.P. (e_1_2_7_63_1) 2006 e_1_2_7_107_1 e_1_2_7_80_1 e_1_2_7_103_1 e_1_2_7_18_1 e_1_2_7_84_1 e_1_2_7_122_1 e_1_2_7_61_1 e_1_2_7_2_1 e_1_2_7_14_1 e_1_2_7_42_1 e_1_2_7_88_1 e_1_2_7_65_1 e_1_2_7_10_1 e_1_2_7_46_1 e_1_2_7_69_1 e_1_2_7_27_1 Armitage D.W. (e_1_2_7_99_1) 2012; 3 e_1_2_7_119_1 e_1_2_7_91_1 e_1_2_7_115_1 e_1_2_7_72_1 e_1_2_7_95_1 e_1_2_7_53_1 e_1_2_7_76_1 e_1_2_7_22_1 e_1_2_7_34_1 e_1_2_7_57_1 Faith D.P. (e_1_2_7_31_1) e_1_2_7_38_1 |
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