2017 Fiscal Year Research-status Report
基礎生物学や保全学のための，地球規模アリ類多様性分布地図の高解像度化
| Project/Area Number |
17K15180
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| Research Institution | Okinawa Institute of Science and Technology Graduate University |
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Principal Investigator |
ECONOMO Evan 沖縄科学技術大学院大学, 生物多様性・複雑性研究ユニット, 准教授 (30648978)
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| Project Period (FY) |
2017-04-01 – 2019-03-31
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| Keywords | Biodiversity / Ants / Biogeography / Conservation / Ecoinformatics / Big data |
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| Outline of Annual Research Achievements |
In the past several decades, the consolidation of large comprehensive datasets has resolved a global picture of biodiversity of some vertebrate groups and (to some extent) plants. These data allow us to ask fundamental questions about the macroecology and macroevolution of biodiversity patterns, as well as provide an information base to guide global conservation. However, despite this progress, there is a major hole in our knowledge: no comprehensive datasets exist for invertebrate animals, which make up the majority of Earth’s biodiversity.
This project aims to develop a high-resolution database for ant species distributions as an exemplar invertebrate groups. In the past years we have assembled a database of 1.8 million species occurrence records (the Global Ant Biodiversity Informatics Database), and the overall goal of the current project is create a new high-resolution version 2.0 of this data and use it for biodiversity analysis. Specifically, the steps are to a) perform a large-scale georeferencing effort to assign latitude-longitude coordinates to as many records as possible, and b) model the range of each species using species-distribution modeling, and c) evaluate biodiversity patterns ants, and compare them with vertebrate groups and currently recognized conservation hotspots.
After the first year, the georeferencing step (a) has finished and has gone better than expected and we have been able to add points to more data records than we initially thought possible. We are working on the (b) species distribution modeling and (c) comparison steps at this time.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The project is progressing smoothly. The georeferencing step has been very complicated and took slightly longer than initially planned. However, we were much more successful than anticipated in attributing high-resolution records to different points. Over 95% of the data points are now associated with a latitude-longitude point. Moreover, although we initially planned to outsource this step, we decided to build the computational capacity within our own research project, and have assembled the georeferencing tools, databases, and infrastructure necessary to perform such operations. This will make it possible in the future to repeat and refine these steps. Thus, we consider the first phase of the project to be very successful. At the same time, we have been developing a pipeline for the next steps of the project, species distribution modeling and comparative analysis. We have already identified the general package of methods we intend to use, and the next step is to implement the methods.
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| Strategy for Future Research Activity |
We have thus far georeferenced around 1.8 million species distribution points. The next step is to develop an automated computational pipeline to perform species distribution modeling. We also need to develop ways to integrate uncertainty into the species distribution models. This is important because many of the data are referenced with some uncertainty (for example, a city or other administrative unit), and not a point with no error. After this step of SDM, we will compare with comparable patterns of diversity, endemism, complementarity, and other relevant metrics to vertebrate data. Finally, we will prepare and submit manuscripts. We are on track to have these remaining steps completed during FY2018.
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| Causes of Carryover |
The reason was because we had budgeted for outsourcing to help with the georeferencing. Instead, we decided to do this work ourselves which saved some costs. We plan to spend these funds by inviting expert collaborators to work with us on analyzing and interpreting the data, publication fees, and computer programmer consulting to help update the new data on our web interface (antmaps.org).
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