Volume 10 Issue 1
Nov.  2019
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Article Contents
Abstract
Introduction
Materials and methods
Results
Discussion
Acknowledgements
References
Sylvia Margarita de la Parra‑Martínez, Luis Guillermo Muñoz‑Lacy, Alejandro Salinas-Melgoza, Katherine Renton. 2019: Optimal diet strategy of a large-bodied psittacine: food resource abundance and nutritional content enable facultative dietary specialization by the Military Macaw. Avian Research, 10(1): 38. DOI: 10.1186/s40657-019-0177-2
Citation: Sylvia Margarita de la Parra‑Martínez, Luis Guillermo Muñoz‑Lacy, Alejandro Salinas-Melgoza, Katherine Renton. 2019: Optimal diet strategy of a large-bodied psittacine: food resource abundance and nutritional content enable facultative dietary specialization by the Military Macaw. Avian Research, 10(1): 38. DOI: 10.1186/s40657-019-0177-2
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Optimal diet strategy of a large-bodied psittacine: food resource abundance and nutritional content enable facultative dietary specialization by the Military Macaw

  • 1.

    Departamento de Ciencias Biológicas, Centro Universitario de la Costa, Universidad de Guadalajara, Av. Universidad No. 203, Delegación Ixtapa, C.P. 48280 Puerto Vallarta, Jalisco, Mexico

  • 2.

    Comisión Nacional Para el Cono‑ cimiento y Uso para la Biodiversidad, Liga Periférico‑Insurgentes Sur 4903, Delegación Tlalpan, 14010 Mexico City, Mexico

  • 3.

    Facultad de Biología, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Michoacán, Mexico

  • 4.

    Estación de Biología Chamela, Instituto de Biología, Universidad Nacional Autónoma de México, Apartado Postal 21, San Patricio‑Melaque, Jalisco, Mexico

More Information
  • Corresponding author:

    Katherine Renton, krenton@ib.unam.mx

  • Received Date: 03 Jul 2018
  • Accepted Date: 16 Sep 2019
  • Available Online: 24 Apr 2022
  • Publish Date: 13 Oct 2019
    Graphical Abstract
    • Abstract
  • Background 

    Dietary specialization should arise when there is a relatively high abundance of a particular resource, where animals may select food items to obtain an optimal diet that maximizes energy intake. Large-bodied psittacines frequently exhibit a narrow dietary niche with specific habitat use, but few studies have determined whether psittacines select food resources, and how this influences habitat use.

    Methods 

    We established fruiting phenology transects to evaluate food resource availability for the large-bodied Military Macaw (Ara militaris) in semi-deciduous, deciduous, and pine-oak forest at two sites along the coast of Jalisco, during the dry season when macaws are nesting. We also determined Military Macaw diet by observations of foraging macaws along transect routes, and conducted bromatological analysis of the nutritional content of the most consumed resource.

    Results 

    Military Macaws used six plant species as food items during the dry season, and had a narrow dietary niche (Levins' B = 0.28), with 56% of foraging macaws consuming the seeds of Hura polyandra. No food resources were recorded in pine-oak forest during the dry season, with food resources and foraging by macaws concentrated in tropical deciduous and semi-deciduous forest, where H. polyandra was the most abundant fruiting tree species. When considering the proportional availability of food resources, we determined a broad Hurlbert dietary niche breadth of H = 0.67, indicating that Military Macaws consumed food resources according to their availability. Furthermore, the seeds of H. polyandra were an important source of protein, carbohydrates, minerals and moisture, and the hard fruit-casing means that these seeds are exclusively available for macaws.

    Conclusions 

    By concentrating their diet on the most abundant resources, Military Macaws may increase foraging efficiency in the dry season. The high nutrient content also means that concentrating the diet on seeds of H. polyandra may be an optimal foraging strategy for Military Macaws to meet their energy requirements during the breeding season.

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  • 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.

    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
     | Show Table
    DownLoad: CSV

    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
    DownLoad: Full-Size Img PowerPoint

    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.

    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.

    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.

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

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