Improvement on molecular sex identification primers for Passeriform bird species

Introduction

Global biodiversity is facing increasing threats due to climate change and anthropogenic impacts (Myers et al., 2000; Grenyer et al., 2006). Identification of important species, under risk of extinction, would be of great help to biologists in a more efficient allocation of limited funds to improve and conserve biological diversity by focusing on these unique species (Grenyer et al., 2006). A common practice to identify conservation values of species is to evaluate the rarity of the population of a species, its distribution ranges (He, 2012) and changes in habitat conditions as is practised in the IUCN Red List (The World Conservation Union, 2010). In recent years, the importance of evolutionary history has become recognized (Cadotte and Davies, 2010; Martyn et al., 2012) and many phylogenetic diversity (PD) indices for quantifying evolutionary heritage of species have been proposed in a number of studies (Faith, 1992, 2002; Faith et al., 2004; Tucker et al., 2012).

The avifauna of China is composed of around 1314 species of which 52 are said to be endemic (only found within the political boundaries of China, i.e., the mainland and Taiwan) (Lei and Lu, 2006). Conservation priorities of these endemic and other bird species in China have been widely established in previous studies (Lei et al., 2002a, 2007; Chen, 2007, 2008; Chang et al., 2013). However, the importance of conservation of endemic birds of China from a phylogenetic perspective has never been evaluated up till now. As such, the present report presents a way to fill such a knowledge gap by proposing conservation priority of endemic birds of China using a series of phylogenetic diversity metrics.

Materials and methods

The list of endemic birds of mainland China was obtained from various earlier studies (Lei and Lu, 2006; Lei et al., 2002a, 2007) and the World Bird Database (http://avibase.bsc-eoc.org/). Table 1 presents a list of species for the present study.

Table  1.  Conservation priorities of species based on alternative phylogenetic diversity metrics. IUCN categories: EN (endangered), VU (vulnerable), NT (near threatened), LC (least concerned), DD (data deficient). "-" denotes the IUCN information is not available. Codes for phylogenetic diversity metrics: ES (equal split), FP (fair proportions), ED (evolutionary distinctiveness), TD (taxonomic distinctiveness), PL (pendant edge's length) and Node-based I and W indices.

Species	ES	FP	ED	TD	PL	I	W	Combined	IUCN
Arborophila ardens	1.000	1.000	1.000	0.571	0.872	0.143	1.000	5.586	VU
Arborophila gingica	1.000	1.000	1.000	0.571	0.872	0.143	1.000	5.586	NT
Arborophila rufipectus	1.000	1.000	1.000	0.388	1.000	0.143	1.000	5.531	EN
Lophophorus lhuysii	0.832	0.835	0.835	0.793	0.918	0.500	0.286	4.999	VU
Alectoris magna	0.980	0.970	0.970	0.434	0.739	0.286	0.500	4.879	LC
Tragopan caboti	0.925	0.913	0.913	0.603	0.739	0.429	0.333	4.855	VU
Caprimulgus centralasicus	0.907	0.883	0.883	0.596	0.826	0.357	0.400	4.852	DD
Syrmaticus ellioti	0.742	0.738	0.738	0.806	1.000	0.571	0.250	4.845	NT
Syrmaticus reevesii	0.742	0.738	0.738	0.806	1.000	0.571	0.250	4.845	VU
Tetraophasis obscurus	0.832	0.835	0.835	0.793	0.670	0.500	0.286	4.751	LC
Certhia tianquanensis	0.782	0.786	0.786	0.788	0.712	0.643	0.222	4.719	NT
Phoenicurus alaschanicus	0.829	0.820	0.820	0.597	0.735	0.571	0.250	4.622	NT
Garrulax davidi	0.596	0.600	0.600	1.000	0.679	1.000	0.143	4.618	LC
Babax koslowi	0.596	0.600	0.600	1.000	0.679	1.000	0.143	4.618	NT
Sitta yunnanensis	0.782	0.786	0.786	0.788	0.58	0.643	0.222	4.587	NT
Garrulax bieti	0.678	0.662	0.662	0.81	0.639	0.929	0.154	4.534	VU
Chrysomma poecilotis	0.632	0.619	0.619	0.905	0.643	0.929	0.154	4.501	LC
Leucosticte sillemi	0.640	0.604	0.604	0.927	0.735	0.786	0.182	4.478	DD
Aegithalos fuliginosus	0.733	0.730	0.730	0.728	0.639	0.714	0.200	4.474	LC
Perisoreus internigrans	0.655	0.662	0.662	0.734	0.968	0.500	0.286	4.467	VU
Strix davidi	0.907	0.883	0.883	0.596	0.434	0.357	0.400	4.460	-
Paradoxornis paradoxus	0.634	0.618	0.618	0.873	0.580	0.929	0.154	4.406	LC
Paradoxornis conspicillatus	0.634	0.618	0.618	0.873	0.580	0.929	0.154	4.406	LC
Paradoxornis przewalskii	0.634	0.618	0.618	0.873	0.575	0.929	0.154	4.401	VU
Paradoxornis zappeyi	0.634	0.618	0.618	0.873	0.575	0.929	0.154	4.401	VU
Podoces biddulphi	0.655	0.662	0.662	0.734	0.895	0.500	0.286	4.394	NT
Garrulax elliotii	0.678	0.662	0.662	0.715	0.639	0.857	0.167	4.380	LC
Rhopophilus pekinensis	0.632	0.619	0.619	0.905	0.514	0.929	0.154	4.372	LC
Garrulax sukatschewi	0.678	0.662	0.662	0.683	0.639	0.857	0.167	4.348	VU
Leptopoecile elegans	0.733	0.730	0.730	0.728	0.498	0.714	0.200	4.333	LC
Carpodacus roborowskii	0.640	0.604	0.604	0.737	0.803	0.714	0.200	4.302	LC
Urocynchramus pylzowi	0.840	0.833	0.833	0.534	0.434	0.571	0.250	4.295	LC
Carpodacus eos	0.640	0.604	0.604	0.927	0.506	0.786	0.182	4.249	LC
Alcippe variegaticeps	0.751	0.726	0.726	0.534	0.580	0.714	0.200	4.231	VU
Alcippe striaticollis	0.632	0.619	0.619	0.715	0.575	0.857	0.167	4.184	LC
Phylloscopus hainanus	0.605	0.622	0.622	0.855	0.505	0.786	0.182	4.177	VU
Phylloscopus kansuensis	0.713	0.692	0.692	0.665	0.498	0.714	0.200	4.174	LC
Phylloscopus emeiensis	0.605	0.622	0.622	0.855	0.450	0.786	0.182	4.122	LC
Bonasa sewerzowi	0.936	0.926	0.926	0.540	0.016	0.429	0.333	4.106	NT
Garrulax lunulatus	0.556	0.560	0.560	0.905	0.434	0.929	0.154	4.098	LC
Garrulax maximus	0.556	0.560	0.560	0.905	0.434	0.929	0.154	4.098	LC
Oriolus mellianus	0.788	0.741	0.741	0.544	0.522	0.429	0.333	4.098	VU
Parus davidi	0.565	0.593	0.593	0.761	0.680	0.643	0.222	4.057	LC
Emberiza koslowi	0.604	0.601	0.601	0.800	0.506	0.714	0.200	4.026	NT
Latoucheornis siemsseni	0.604	0.601	0.601	0.800	0.506	0.714	0.200	4.026	LC
Liocichla omeiensis	0.716	0.665	0.665	0.534	0.514	0.714	0.200	4.008	VU
Parus superciliosus	0.565	0.593	0.593	0.761	0.522	0.643	0.222	3.899	LC
Chrysolophus pictus	0.761	0.741	0.741	0.743	0.016	0.571	0.250	3.823	LC
Parus venustulus	0.679	0.620	0.620	0.571	0.450	0.571	0.250	3.761	LC
Crossoptilon auritum	0.388	0.414	0.414	0.933	0.632	0.643	0.222	3.646	LC
Crossoptilon mantchuricum	0.388	0.414	0.414	0.933	0.632	0.643	0.222	3.646	VU

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The phylogenetic relationships between the 52 endemic birds of China's mainland are extracted from the BirdTree.org database (http://www.birdtree.org), which is derived from a full phylogeny of the global bird species in a previous study (Jetz et al., 2012). However one species, Ficedula beijingnic, was omitted from the tree files of the database. It was therefore decided to exclude this species for further analyses, while the remaining 51 species were used for analysis since these are all included in the retrieved phylogenetic trees. From the 3000 trees tested for possible phylogenetic affinities, the 51 endemic birds were retrieved and the resultant consensus tree, with average branch lengths, was obtained using the DendroPy python library (Sukumaran and Holder, 2010). Molecular dating of the tree was carried out using a penalized likelihood method (Sanderson, 2002). The result, a dated tree (Fig. 1), is used for all subsequent analyses.

Figure  1.  Consensus phylogenetic tree for 51 endemic birds of mainland China

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The following phylogenetic diversity indices are considered to offer a combined rank of conservation priority for endemic birds of China: node-based I and W indices (Posadas et al., 2001, 2004), an evolutionary distinctiveness index (ED) (Redding and Mooers, 2006; Redding et al., 2008), a taxonomic distinctiveness index (TD) (Cadotte and Davies, 2010), pendant lengths (PL) (Altschul and Lipman, 1990), equal splits (ES) (Redding and Mooers, 2006) and fair proportions (FP) (Isaac et al., 2007). All values for each index were then subjected to standardization in order to make a final combined ranking of these species.

As a comparison, the category of the IUCN Red list for each species was collected from BirdLife International (http://www.birdlife.org/) and included in Table 1. The abbreviations for each category are as follows: EN (endangered), VU (vulnerable), NT (near threatened), LC (least concerned) and DD (data deficient). When comparing the rankings of IUCN and PD indices, the IUCN categories are transformed into discrete integers, i.e., EN (1), VU (2), NT (3), LC (4) and DD (5). The Wilcox signed rank test and Pearson's correlation test were implemented to compare both rankings. A significant Wilcox signed rank or a non-significant Pearson's correlation coefficient implies that both rankings are fundamentally different.

Results

As shown in Table 1, the top five endemic birds based on the combined rankings of seven PD indices in order of priority, are Arborophila ardens, A. gingica, A. rufipectus, Lophophorus lhuysii and Alectoris magna. Their corresponding IUCN classes are VU, NT, EN, VU and LC, respectively. As seen, the PD-based ranking accurately identified the conservation importance of Arborophila rufipectus, an endangered species that should have a high priority for conservation.

Arborophila rufipectus has a very limited range of distribution in the southern part of Sichuan Province. The size of its adult population is estimated to be around 1000 (BirdLife International, http://www.birdlife.org/). Due to continuous hunting and habitat loss, it was classified as Critically Endangered in previous IUCN reports(1994, 1998). It is now still listed in the category of Endangered species. Based on a phylogenetic perspective this species, along with two other Arborophila species, has a very unique and long evolutionary history, when compared to other endemic birds (Fig. 1).

The PD-ranking for Arborophila ardens and Lophophorus lhuysii are also fairly accurate (top-1 and 4), both of which are listed as VU in the IUCN Red List (The World Conservation Union, 2010). This implies that both should deserve high conservation priority from an ecological perspective (based on IUCN ranking) as well as from an evolutionary (based on PD ranking) perspective.

In contrast, there are some inconsistencies between PD and IUCN rankings. For example, Arborophila gingica and Alectoris magna are ranked 2nd and 5th in the PD ranking for their unique evolutionary histories. However, in the IUCN ranking, these species are merely grouped into the categories of NT and LC.

Overall, the difference of rankings based on the IUCN Red List and the combined PD ranking is statistically significant (Wilcox signed rank test: V = 159, p < 0.001; Pearson's correlation coefficient: r = 0.217, p = 0.129). These tests show a significant difference between IUCN and PD rankings for endemic birds of mainland China.

Discussion

Conservation importance of endemic or rare species has been widely recognized (Linder, 1995; Lamoreux et al., 2006; Gaston, 2012). In the present study, I quantified the conservation importance of avian species, endemic to China, by utilizing a variety of phylogenetic diversity metrics. The results show a statistically significant difference between the priority rankings based on PD metrics and that derived from the IUCN Red list. Therefore, a PD-based conservation emphasis on endemic birds of China might offer some new views when establishing relevant conservation strategies by considering evolutionary heritage and genetic resources of these species.

The present study carried out analyses on 51 endemic birds. However, it might be a bit ambiguous given the number of endemic birds in China (Zhang, 2004), when one considers migration during the breeding season (Lei et al., 2002b). In a previous study, the number of endemic birds in China was believed to be around 100 (Lei et al., 2002a), while in a more recent publication, this number is said to be 105 (Lei and Lu, 2006). If the definition of endemic birds were extended to include, for example, Taiwan and Hong Kong, the number of endemic birds should be at least 70 (Zhang, 2004; Lei et al., 2002b). When considering only mainland China, the number of endemic birds should be at least 50, based on the information from the World Bird Database (http://avibase.bsc-eoc.org/). Therefore, the present study should be relatively accurate in suggesting conservation priorities for endemic birds in mainland China based on the phylogenetic diversity framework. Any re-analyses with the addition of a few more possible endemic birds should not greatly affect the quantitative results presented in the present study.

In this study, I have only used pure phylogeny-based diversity indices without considering other weighted phylogenetic diversity indices. Weighted phylogenetic diversity metrics such as the abundance-weighted PD index (Cadotte et al., 2010), the biogeography-weighted PD index (Tucker et al., 2012), the endemism-weighted PD index (Rosauer et al., 2009) and possibly other indices might provide more insights into conservation priorities because these can explicitly incorporate the role of some biological factors when studying the evolutionary history of species. For future implications, integration of other weighted phylogenetic diversity indices into the systematic conservation planning of birds would offer new insights and thus should be considered in the next levels of research.

Acknowledgements

This work was supported by the University of British Columbia and now supported by China Scholarship Council.