2019 Fiscal Year Annual Research Report
気候変動に伴う河川生態系のリスク評価：統計モデルとメソコスム実験の融合
| Project/Area Number |
19H04314
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| Research Institution | Hokkaido University |
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Principal Investigator |
G・MOLINOS JORGE 北海道大学, 北極域研究センター, 助教 (30767281)
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| Co-Investigator(Kenkyū-buntansha) |
石山 信雄 地方独立行政法人北海道立総合研究機構, 森林研究本部 林業試験場, 研究職員 (50780821)
末吉 正尚 国立研究開発法人土木研究所, 土木研究所(つくば中央研究所), 研究員 (70792927)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | 気候変動 / 河川生態系 / 水温予測 / 種間関係 / メソコスム実験 |
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| Outline of Annual Research Achievements |
According to the implementation plan, four study catchments were selected during the initial kick-off meeting (May 2019), representing different geographical zones and climatologic/environmental conditions: the Teshio and Kiso Rivers (Hokkaido), the Hiji River (Shikoku), and the Kiso River (Chubu/Mie) (Task 1, WP1 of implementation plan). A total of 193 temperature loggers were installed across these catchments during spring/summer 2019 (Task 2, WP1). Data from the loggers will be retrieved from this year (FY2020) to start building water temperature statistical predictive models as described in the research proposal (Task 3, WP1). During field work, macroinvertebrate (84), and fish (28) samples were taken to complement existing biological data (Task 2, WP1), which will be later used for modelling species distributions in the rivers during the 2nd and 3rd years of the project (WP2).
In terms of dissemination, a statistical software package for calculating climate change metrics was developed (VoCC R package) and published as a research paper (Garcia Molinos, et al. 2019. Methods Ecol. Evol., 10: 2195-2202. Impact Factor: 6.36). This software will be used later in the project to analyze patterns of future warming across the river networks. The project was presented (oral presentation) at the AGU fall meeting (December 2019, San Francisco). A second presentation had been accepted at the 67th Annual Meeting of the Ecological Society of Japan (Nagoya, March 2019), but the event was cancelled (coronavirus emergency).
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
The research project has gone according to the implementation plan described in the grant application. All tasks set for the first year were met satisfactorily, including the kick-off meeting and selection of study catchments (Task 1, WP1 in the implementation plan), the installation of the monitoring network in each catchment (Task 2, WP1), and collection of biological samples (Task 2, WP1). A second project meeting initially scheduled for the end of FY2019 had to be cancelled due to the coronavirus situation. Nonetheless, this has had no effect on the project as communication is kept fluent between the principal investigator and co-investigators through email and video conferences.
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| Strategy for Future Research Activity |
The research plan continues as originally planned for the project in general and FY2020. Monitored sites in all four catchments will be revisited in spring or autumn to retrieve recorded temperature data and collect extra biological samples. Currently, there is certain uncertainty as for when those visits will take place given the situation with the coronavirus spread in Japan. On this regard, we will comply with recommendations from authorities and our respective institutions. Delays for the field visits may translate into delays in the project deliverables in the short term. However, at this stage, the overall risk to the project is not significant given at current measurement rates the loggers have battery and capacity for storing data of up to 2-3 years. Where possible, the development of statistical models for the prediction of water temperatures and species distributions will start from autumn 2020. Similarly, where possible, project results will be continued to be presented at relevant national and international conferences.
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| Remarks |
Software package published:
J. Garcia Molinos et al. 2019. VoCC: The Velocity of Climate Change and related climatic metrics. R package version 1.0.0. https://doi.org/10.5281/zenodo.3382092
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Research Products
(2 results)
