Dataset Information

Meta-barcoding insights into the spatial and temporal dietary patterns of the threatened Asian Great Bustard (Otis tarda dybowskii) with potential implications for diverging migratory strategies.

ABSTRACT: Food resources are often not sufficient to satisfy the nutritional and energetic requirements during winter conditions at high latitudes. Dietary analysis is a prerequisite to fully understanding the feeding ecology of a species and the nature of trophic interactions. Previous dietary studies of Asian Great Bustard (Otis tarda dybowskii) relied on behavioral observations, resulting in categorization of diet limited to broad taxonomic groupings. Here, we applied a high-throughput sequencing meta-barcoding approach to quantify the diet of resident and migratory Asian Great Bustard in three wintering sites during early winter and late winter. We detected 57 unique plant taxa in the bustard diet, among which 15 species were confirmed by a local plant database we generated. Both agricultural and natural foods were detected, indicating a relatively broad dietary niche. Spatiotemporal dietary changes were discovered, revealing diet differences among wintering sites and a general shift toward lower plant diversity later in winter. For the nonmigratory population, we detected a significantly more diverse array of plant species in their diet. We hypothesize that dietary variation between resident and migratory populations could be involved in the recent transition to partial migration in this species, although climate change can not be excluded. Collectively, these results support protecting unharvested grain fields and naturally unplowed lands to help conserve and promote population growth of Asian Great Bustard.

SUBMITTER: Liu G

PROVIDER: S-EPMC5792609 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Meta-barcoding insights into the spatial and temporal dietary patterns of the threatened Asian Great Bustard (<i>Otis tarda dybowskii</i>) with potential implications for diverging migratory strategies.

Liu Gang G Shafer Aaron B A ABA Hu Xiaolong X Li Linhai L Ning Yu Y Gong Minghao M Cui Lijuan L Li Huixin H Hu Defu D Qi Lei L Tian Hengjiu H Wang Bojun B

Ecology and evolution 20180108 3

Food resources are often not sufficient to satisfy the nutritional and energetic requirements during winter conditions at high latitudes. Dietary analysis is a prerequisite to fully understanding the feeding ecology of a species and the nature of trophic interactions. Previous dietary studies of Asian Great Bustard (<i>Otis tarda dybowskii</i>) relied on behavioral observations, resulting in categorization of diet limited to broad taxonomic groupings. Here, we applied a high-throughput sequencin ...[more]

PMID: 29435248

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Project description:The rapidly changing climate makes humans realize that there is a critical need to incorporate climate change adaptation into conservation planning. Whether the wintering habitats of Great Bustards (Otis tarda dybowskii), a globally endangered migratory subspecies whose population is approximately 1,500-2,200 individuals in China, would be still suitable in a changing climate environment, and where this could be found, is an important protection issue. In this study, we selected the most suitable species distribution model for bustards using climate envelopes from four machine learning models, combining two modelling approaches (TreeNet and Random Forest) with two sets of variables (correlated variables removed or not). We used common evaluation methods area under the receiver operating characteristic curves (AUC) and the True Skill Statistic (TSS) as well as independent test data to identify the most suitable model. As often found elsewhere, we found Random Forest with all environmental variables outperformed in all assessment methods. When we projected the best model to the latest IPCC-CMIP5 climate scenarios (Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 in three Global Circulation Models (GCMs)), and averaged the project results of the three models, we found that suitable wintering habitats in the current bustard distribution would increase during the 21st century. The Northeast Plain and the south of North China were projected to become two major wintering areas for bustards. However, the models suggest that some currently suitable habitats will experience a reduction, such as Dongting Lake and Poyang Lake in the Middle and Lower Yangtze River Basin. Although our results suggested that suitable habitats in China would widen with climate change, greater efforts should be undertaken to assess and mitigate unstudied human disturbance, such as pollution, hunting, agricultural development, infrastructure construction, habitat fragmentation, and oil and mine exploitation. All of these are negatively and intensely linked with global change.

Project description:Populations of Houbara Bustards have dramatically declined in recent years. Captive breeding and reintroduction programs have had limited success in reviving population numbers and thus new technological solutions involving molecular methods are essential for the long term survival of this species. In this study, we sequenced the 694 bp segment of COI gene of the four specimens of Asian Houbara Bustard (Chlamydotis undulata macqueenii). We also compared these sequences with earlier published barcodes of 11 individuals comprising different families of the orders Gruiformes, Ciconiiformes, Podicipediformes and Crocodylia (out group). The pair-wise sequence comparison showed a total of 254 variable sites across all the 15 sequences from different taxa. Three of the four specimens of Houbara Bustard had an identical sequence of COI gene and one individual showed a single nucleotide difference (G > A transition at position 83). Within the bustard family (Otididae), comparison among the three species (Asian Houbara Bustard, Great Bustard (Otis tarda) and the Little Bustard (Tetrax tetrax)), representing three different genera, showed 116 variable sites. For another family (Rallidae), the intra-family variable sites among the individuals of four different genera were found to be 146. The COI genetic distances among the 15 individuals varied from 0.000 to 0.431. Phylogenetic analysis using 619 bp nucleotide segment of COI clearly discriminated all the species representing different genera, families and orders. All the four specimens of Houbara Bustard formed a single clade and are clearly separated from other two individuals of the same family (Otis tarda and Tetrax tetrax). The nucleotide sequence of partial segment of COI gene effectively discriminated the closely related species. This is the first study reporting the barcodes of Houbara Bustard and would be helpful in future molecular studies, particularly for the conservation of this threatened bird in Saudi Arabia.

Project description:Species distribution models (SDMs) have become important and essential tools in conservation and management. However, SDMs built with count data, referred to as species abundance models (SAMs), are still less commonly used to date, but increasingly receiving attention. Species occurrence and abundance do not frequently display similar patterns, and often they are not even well correlated. Therefore, only using information based on SDMs or SAMs leads to an insufficient or misleading conservation efforts. How to combine information from SDMs and SAMs and how to apply the combined information to achieve unified conservation remains a challenge. In this study, we introduce and propose a priority protection index (PI). The PI combines the prediction results of the occurrence and abundance models. As a case study, we used the best-available presence and count records for an endangered farmland species, the Great Bustard (Otis tarda dybowskii), in Bohai Bay, China. We then applied the Random Forest algorithm (Salford Systems Ltd. Implementation) with eleven predictor variables to forecast the spatial occurrence as well as the abundance distribution. The results show that the occurrence model had a decent performance (ROC: 0.77) and the abundance model had a RMSE of 26.54. It is noteworthy that environmental variables influenced bustard occurrence and abundance differently. The area of farmland, and the distance to residential areas were the top important variables influencing bustard occurrence. While the distance to national roads and to expressways were the most important influencing abundance. In addition, the occurrence and abundance models displayed different spatial distribution patterns. The regions with a high index of occurrence were concentrated in the south-central part of the study area; and the abundance distribution showed high populations occurrence in the central and northwestern parts of the study area. However, combining occurrence and abundance indices to produce a priority protection index (PI) to be used for conservation could guide the protection of the areas with high occurrence and high abundance (e.g., in Strategic Conservation Planning). Due to the widespread use of SDMs and the easy subsequent employment of SAMs, these findings have a wide relevance and applicability than just those only based on SDMs or SAMs. We promote and strongly encourage researchers to further test, apply and update the priority protection index (PI) elsewhere to explore the generality of these findings and methods that are now readily available.

Dataset Information

Meta-barcoding insights into the spatial and temporal dietary patterns of the threatened Asian Great Bustard (Otis tarda dybowskii) with potential implications for diverging migratory strategies.

Publications

Meta-barcoding insights into the spatial and temporal dietary patterns of the threatened Asian Great Bustard (<i>Otis tarda dybowskii</i>) with potential implications for diverging migratory strategies.

Similar Datasets

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