Abstract

Food availability and diet selection are important factors influencing the abundance and distribution of wild waterbirds. In order to better understand changes in waterbird population, it is essential to figure out what they feed on. However, analyzing their diet could be difficult and inefficient using traditional methods such as microhistologic observation. Here, we addressed this gap of knowledge by investigating the diet of greater white-fronted goose Anser albifrons and bean goose Anser fabalis, which are obligate herbivores wintering in China, mostly in the Middle and Lower Yangtze River floodplain. First, we selected a suitable and high-resolution marker gene for wetland plants that these geese would consume during the wintering period. Eight candidate genes were included: rbcL, rpoC1, rpoB, matK, trnH-psbA, trnL (UAA), atpF-atpH, and psbK-psbI. The selection was performed via analysis of representative sequences from NCBI and comparison of amplification efficiency and resolution power of plant samples collected from the wintering area. The trnL gene was chosen at last with c/h primers, and a local plant reference library was constructed with this gene. Then, utilizing DNA metabarcoding, we discovered 15 food items in total from the feces of these birds. Of the 15 unique dietary sequences, 10 could be identified at specie level. As for greater white-fronted goose, 73% of sequences belonged to Poaceae spp., and 26% belonged to Carex spp. In contrast, almost all sequences of bean goose belonged to Carex spp. (99%). Using the same samples, microhistology provided consistent food composition with metabarcoding results for greater white-fronted goose, while 13% of Poaceae was recovered for bean goose. In addition, two other taxa were discovered only through microhistologic analysis. Although most of the identified taxa matched relatively well between the two methods, DNA metabarcoding gave taxonomically more detailed information. Discrepancies were likely due to biased PCR amplification in metabarcoding, low discriminating power of current marker genes for monocots, and biases in microhistologic analysis. The diet differences between two geese species might indicate deeper ecological significance beyond the scope of this study. We concluded that DNA metabarcoding provides new perspectives for studies of herbivorous waterbird diets and inter-specific interactions, as well as new possibilities to investigate interactions between herbivores and plants. In addition, microhistologic analysis should be used together with metabarcoding methods to integrate this information.

Highlights

  • Wetlands are one of the most important ecosystems in nature, and they harbor a variety of ecosystem services such as protection against floods, water purification, climate regulation and recreational opportunities (Brander, Florax & Vermaat, 2006)

  • Given the small number of sequences and coverage of species, the suitability and efficiency of atpF-atpH and psbK-psbI seem to be less reliable than others

  • Marker selection and reference library constructing for diet analysis

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Summary

Introduction

Wetlands are one of the most important ecosystems in nature, and they harbor a variety of ecosystem services such as protection against floods, water purification, climate regulation and recreational opportunities (Brander, Florax & Vermaat, 2006). Waterbirds are typically wetland-dependent animals upon which they could get abundant food and suitable habitats (Ma et al, 2010). Waterbird abundance and distribution could reflect the status of wetland structure and functions, making them important bio-indicators for wetland health (Fox et al, 2011). Among all factors affecting waterbird community dynamics, food availability is frequently considered to play one of the most important roles (Wang et al, 2013). Recently suitable food resources have tended to decrease or even disappear due to deterioration and loss of natural wetlands (Fox et al, 2011). Long-time monitoring and systematic studies of waterbird diets are essential to understand population dynamics of waterbirds, as well as to establish effective management programs for them (Wang et al, 2012)

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