Assessing Migration Patterns in [I]Passerina Ciris[I]
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A peer-reviewed version of this preprint was published in PeerJ on 7 April 2016. View the peer-reviewed version (peerj.com/articles/1871), which is the preferred citable publication unless you specifically need to cite this preprint. Linck E, Bridge ES, Duckles JM, Navarro-Sigüenza AG, Rohwer S. 2016. Assessing migration patterns in Passerina ciris using the world’s bird collections as an aggregated resource. PeerJ 4:e1871 https://doi.org/10.7717/peerj.1871 Assessing migration patterns in Passerina ciris using the world’s bird collections as an aggregated resource Ethan Linck, Eli S Bridge, Jonah Duckles, Alfonso G Navarro Sigüenza, Sievert Rohwer Natural history museum collections (NHCs) represent a rich and largely untapped source of data on demography and population movements. NHC specimen records can be corrected to a crude measure of collecting effort and reflect relative population densities with a method known as abundance indices. We plot abundance index values from georeferenced NHC data in a 12-month series for the new world migratory passerine Passerina ciris across its molting and wintering range in Mexico and Central America. We illustrate a statistically significant change in abundance index values across regions and months that suggests a quasi-circular movement around its non-breeding range, and use enhanced vegetation index (EVI) analysis of remote sensing plots to demonstrate non-random association of specimen record density with areas of high primary productivity. We demonstrate how abundance indices from NHC specimen records can be applied to infer previously unknown migratory behavior, and be integrated with remote sensing data to allow for a deeper understanding of demography and behavioral ecology across space and time. PeerJ PrePrints | https://doi.org/10.7287/peerj.preprints.1567v1 | CC-BY 4.0 Open Access | rec: 5 Dec 2015, publ: 5 Dec 2015 1 Assessing migration patterns in Passerina ciris using the world’s bird collections as an 2 aggregated resource. 3 4 Ethan Linck1*, Eli S. Bridge2, Jonah Duckles3, Adolfo G. Navarro-Sigüenza4, Sievert Rohwer1 5 1 Department of Biology and Burke Museum of Natural History and Culture, University of 6 Washington, Seattle, Washington, USA 7 2 Oklahoma Biological Survey, University of Oklahoma, Norman, Oklahoma, USA 8 3 Department of Information Techonology, University of Oklahoma, Norman, Oklahoma, USA 9 4 Departamento de Biología Evolutiva, Universidad Nacional Autónoma de México, México 10 D.F., México 11 * Corresponding author: [email protected]; University of Washington, Kincaid Hall Box 351800, 12 Seattle, WA 98115 13 14 ABSTRACT 15 16 Natural history museum collections (NHCs) represent a rich and largely untapped source of data 17 on demography and population movements. NHC specimen records can be corrected to a crude 18 measure of collecting effort and reflect relative population densities with a method known as 19 abundance indices. We plot abundance index values from georeferenced NHC data in a 12- 20 month series for the new world migratory passerine Passerina ciris across its molting and 21 wintering range in Mexico and central America. We illustrate a statistically significant change in 22 abundance index values across regions and months that suggests a quasi-circular movement 23 around its non-breeding range, and use enhanced vegetation index (EVI) analysis of remote 24 sensing plots to demonstrate non-random association of specimen record density with areas of 25 high primary productivity. We demonstrate how abundance indices from NHC specimen records 26 can be applied to infer previously unknown migratory behavior, and be integrated with remote 27 sensing data to provide a deeper understanding of demography and behavioral ecology across 28 time and space. 29 INTRODUCTION 30 31 Natural history museum collections (NHCs) represent a rich and largely untapped source 32 of data on demography, behavioral ecology, and population movements. (Lister and Group 2011, 33 Suarez and Tsutsui 2004). Housed in museums and herbaria worldwide, NHCs are unique among 34 extant biological datasets in their breadth, depth, and, for the most part, in lacking biases intrinsic 35 to data collected for a specific research goal. NHCs are particularly valuable in that the oldest 36 specimens in collections predate even the longest running ecological surveys (Magurran et al. 37 2010), and that the majority of specimens are associated with detailed provenance data (Lister 38 and Group 2011). The combination of these records into sortable databases spanning multiple 39 institutions provides an invaluable resource in approaching a wide range of biological questions 40 through careful scrutiny and meta-analysis. 41 NHCs have traditionally been used to assess biogeographic range changes (Boakes et al. 42 2010), phenological shifts (Robbirt et al. 2011), hybridization (Rohwer and Wood 1998) and 43 evolutionary change in morphology. Applications of molecular techniques to NHCs have 44 extracted DNA from historic specimens to use in phylogenetic analyses (Paabo et al. 2004), 45 performed stable isotope analyses to track diet and migration in birds (Inger and Bearshop 2008), 46 and examined environmental contamination through trace element analysis (Berg et al. 1966, 47 Hickey and Anderson 1968). While specimen collections have obvious utility in addressing 48 questions of population biology, particularly in gaining access into otherwise-unknown historical 49 population dynamics, a major shortcoming of these data is the absence of information on 50 collecting effort associated with any individual specimen. 51 One method of overcoming this shortcoming is the application of indices that are 52 corrected to a crude measure of effort (Miki et al. 2000, Barry et al. 2009). These abundance 53 indices are calculated by use of electronic natural history museum catalogs (such as VertNet.org) 54 to aggregate records of specimens from a particular region and time period that are expected to 55 have been collected in a similar manner to the focal species of a study. Abundance indices have 56 been successfully applied to show molt migration (Barry et al. 2009), population dynamics in 57 medicinal plants (Miki et al. 2000), and in assessing migratory double-breeding (Rohwer et al. 58 2012) and changes in community composition from massive environmental pertubations 59 (Rohwer et al. 2015). A logical extension of these analyses is to examine spatial and temporal 60 changes in abundance index values to infer month-to-month population-level movements, where 61 technology, cost and unpredictable behavior often prohibit geotagging individuals. However, 62 such use of aggregated collection records remains untested. 63 Here, we demonstrate how abundance indices can be applied to infer population-level 64 movements from month to month across a migratory species’ non-breeding range. We plot 65 abundance index values from georeferenced NHC data in a 12-month series for the new world 66 migratory passerine Passerina ciris across its molting and wintering range in Mexico and central 67 America. We illustrate a statistically significant change in abundance index values across regions 68 and months that suggests a quasi-circular movement around its non-breeding range, and use 69 enhanced vegetation index (EVI) analysis of remote sensing plots to demonstrate non-random 70 association of specimen record density with areas of high primary productivity. 71 72 METHODS 73 74 Study species. The Painted Bunting (Passerina ciris) is a migratory New World 75 passerine in the family Cardinalidae. Current taxonomy recognizes two subspecies of Painted 76 Bunting but the boundary between these races does not coincide with a nearly 500km gap 77 separating the east coast and the Midwestern breeding populations of Painted Buntings 78 (Thompson 1991). Further, these isolated breeding populations differ dramatically in their molt 79 scheduling, with the eastern population molting on its breeding range prior to migration and the 80 Midwestern population moving to the monsoon region of the southwestern United States and 81 northwestern Mexico where it pauses to molt before proceeding to its wintering range in 82 southern Mexico and Central America (Thompson 1991, Rohwer et al. 2005, V.G. Rohwer et al. 83 2009). 84 Across their range, Painted Buntings favor ecotones, brushy, weedy habitats in second 85 growth, and dense forest understory. Relatively little is known in detail about the species’ 86 movements following molt stopover, but progressive southward movements of populations along 87 the west coast of Mexico have been observed in the autumn (Rohwer 2014, pers. comm.; Contina 88 et al. 2013). 89 Calculating Abundance Indices. To track spatial and temporal changes in Painted 90 Bunting population densities during the wintering season, we employed a method of inferring 91 relative population densities from specimen collections data known as Abundance Indices. The 92 method, proposed in Rohwer et al. 2011 and developed independently by Miki et al. (2000), 93 adjusts for a major shortcoming of specimen collections data -- the absence of associated 94 information on collecting effort -- by producing an index that is corrected to a crude measure of 95 effort. This index is calculated by using electronic natural history museum catalogs (such as 96 VertNet.org) to aggregate records of specimens from a particular region and time period that are 97 expected to have been collected in a manner similar to the methods used to collect the focal 98 species of a study. 99 We used the formula for abundance index calculation proposed in Rohwer et al. (2015): 100 th 101 where xkr is number of specimens of the k species collected in r, the region and time period of 102 interest, and n is the number of specimens of all species that would be “expected” to be collected 103 using the same methods in that region and time period of interest. 104 Reference data. In order to calculate abundance indices for Painted Buntings, we 105 accessed two databases of specimen collection records: the Mexican Bird Atlas, and VertNet. 106 The Mexican Bird Atlas began compilation by A.