17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-1

ప❅⣲᪋⏝Ỉ⏣ᅵተ䛷䛾⬺❅⣽⳦᥋✀䛻䜘䜛䜲䝛⏕⫱ಁ㐍ຠᯝ䠖㻌䜲䝛᱂ᇵㄪᰝ䛸᰿ᇦᅵተ⣽⳦ྀゎᯒ㻌㏕⏣㻌 ⩫ 1䠈Ỉ⃝㻌 ⯙ⰼ 1䠈ሷὠ㻌 ᩥ㝯 2䠈㒌㻌 Ọ 1䠈ᆏୖ㻌 ఙ⏕ 1䠈⁪ᮏ㻌 ㈗ᘯ 3䠈ቑ෠㻌 ♸ྖ 1䠈⸨ཎ㻌 ᚭ 4䠈ጒᑿ㻌 ၨྐ 4,5䠈す⃝㻌 ᬛᗣ 1
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Ⲉᇛ኱Ꮫ㎰Ꮫ㒊䠈2 ᫂἞኱Ꮫ㎰Ꮫ㒊䠈3 Ⲉᇛ኱Ꮫᆅ⌫ኚື㐺ᛂ⛉Ꮫ◊✲ᶵ㛵䠈ᮾி኱Ꮫ኱Ꮫ㝔㎰Ꮫ⏕࿨⛉Ꮫ◊✲⛉䠈5 ᮾி኱Ꮫᚤ⏕≀⛉Ꮫ࢖ࣀ࣮࣋ࢩࣙࣥ㐃ᦠ◊✲ᶵᵓ䜻䞊䝽䞊䝗䠖❅⣲ᚠ⎔䠈㣗⣊⏕⏘䠈⏕⫱ಁ㐍䠈䜲䝛䠈ᅵተ⣽⳦⩌㞟㻌ᢒ㘓㻌㎰⪔ᆅ䜈䛾❅⣲⫧ᩱ䛾኱㔞ᢞධ䛿Ἑᕝ䜔†἟䛾ᐩᰤ㣴໬䜢ᘬ䛝㉳䛣䛧䛶䛚䜚䠈Ỉ⣔䛾❅⣲ởᰁ䜢㜵䛠䛯䜑䛻᪋⫧㔞䛾పῶ䛜ồ䜑䜙䜜䜛䠊Ỉ⏣ᅵተ䛛䜙ศ㞳䛥䜜䛯⬺❅⣽⳦ Azoarcus ᒓ KH32C ᰴ䜢䜲䝛✀Ꮚ䛻᥋✀䛩䜛䛸䠈ᐊෆᐇ㦂⣔䛻䛚䛔䛶❅⣲Ḟஈ᮲௳ୗ䛷䜲䝛ึᮇ⏕⫱䜢ಁ㐍䛥䛫䛯䠊ᮏ◊✲䛷䛿䠈KH32C ᰴ䜢᥋✀䛧䛯䜲䝛䜢❅⣲↓᪋⫧Ỉ⏣ᅡሙ䛷᱂ᇵ䛧䠈䜲䝛䛾⏕⫱䛚䜘䜃䜲䝛᰿ᇦᅵተ⣽⳦⩌㞟䜈䛾ᙳ㡪䜢ㄪᰝ䛧䛯䠊ᅵተ❅⣲䞉Ⅳ⣲㔞䛾␗䛺䜛 2 䛴䛾↓᪋⫧Ỉ⏣䛷ရ✀䛾␗䛺䜛䜲䝛䜢᱂ᇵ䛧䛯䛸䛣䜝䠈KH32C ᰴ䛾᥋✀䛻䜘䜚ప❅⣲䞉Ⅳ⣲㔞䛾Ỉ⏣ᅵተ䛷᪥ᮏᬕ䛾ึᮇ⏕⫱䛜ಁ㐍䛥䜜䛯䠊䛥䜙䛻䠈᪥ᮏᬕ䛾⋞⡿୰䛾ள㖄ྵ᭷㔞䛜ቑຍ䛧䛯䠊୍᪉䠈䜲䝛᰿ᇦᅵተ⣽⳦䛾䝯䝍䝀䝜䝭䜽䝇ゎᯒ䛛䜙䠈KH32C ᰴ䛾᥋✀䛿᪥ᮏᬕ᰿ᇦᅵተ䛾⣽⳦⩌㞟ᵓ㐀䛻ᙳ㡪䜢୚䛘䛯䛣䛸䛜♧䛥䜜䛯䠊❅⣲⫧ᩱపᢞධ䛾ᅡሙ䛻䛚䛔䛶䠈KH32C ᰴ䛾ᚤ⏕≀㈨ᮦ䛸䛧䛶䛾฼⏝䛜ᮇᚅ䛥䜜䜛䠊
1. 䛿䛨䜑䛻

⏣ᅡሙ䛷䜲䝛᱂ᇵ䜢ᐇ᪋䛧䛯䠊❅⣲䛿䠈⤯䛘䛪ᙧែ䜢ኚ໬䛥䛫䛺䛜䜙ᆅ⌫ୖ䜢ᚠ⎔Ⓨⱆ䛧䛯䜲䝛✀Ꮚ䠄᪥ᮏᬕ䠈䝍䜹䝘䝸䠈IR64䠈䝁䝅䝠䜹䝸䛧䛶䛔䜛䠊ᅵተ୰䛾ᚤ⏕≀䛿䠈❅⣲ᅛᐃ䠈◪໬䠈⬺❅䠈

䠄2017 ᖺ䛾䜏䠅䠅䜢 KH32C ᰴᠱ⃮ᾮ䛻 10 ศ㛫ᾐₕ䛧䠈␗໬ⓗ◪㓟㑏ඖ䛺䛹䛾཯ᛂ䜢㏻䛧䠈❅⣲ᚠ⎔䛾୍㒊䜢᥋✀䛸䛧䛯䠊KH32C ᰴ᥋✀䠄᥋✀༊䠅䛸ᮍ᥋✀䠄ᑐ↷༊䠅ᢸ䛳䛶䛔䜛 [1]䠊㎰⪔ᆅ䛷䛿䠈స≀䛾⏕⏘ᛶ䛾ྥୖ䛾䛯䛾䜲䝛✀Ꮚ䛿䠈⫱ⱑᚋ䠈↓᪋⫧Ỉ⏣ᅡሙ䛻⛣᳜䛧䛯䠊䜑䛻❅⣲⫧ᩱ䛜኱㔞䛻ᢞධ䛥䜜䛶䛔䜛䛜䠈୍㒊䛿స≀⏕⫱ึᮇ䠈ᗂ✑ᙧᡂᮇ䠈཰✭ᮇ䛻䜲䝛䛚䜘䜃䜲䝛᰿ᇦ䛻྾཰䛥䜜䛪ὶฟ䛧䠈Ἑᕝ䜔†἟䛾ᐩᰤ㣴໬䜢ᘬ䛝㉳ᅵተ䜢᥇ྲྀ䛧䛯䠊2017 ᖺ䛻䛿䠈ຍ䛘䛶✑ᥞ䛔ᮇ䛻䜲䝛䛣䛩䠊㐣๫䛺❅⣲⫧ᩱ䛾౑⏝䛻䜘䜛⎔ቃ䜈䛾㈇Ⲵ䜢៧᰿ᇦᅵተ䜢᥇ྲྀ䛧䛯䠊៖䛧䠈❅⣲⫧ᩱ䛾᪋⏝㔞䛾๐ῶ䛜ồ䜑䜙䜜䜛䛜䠈స≀᥇ྲྀ䛧䛯⏕⫱ึᮇ䠈ᗂ✑ᙧᡂᮇ䛾䜲䝛䛿஝⇱㔜㔞䜢䛾⏕⏘ᛶ䛾పୗ䛜ၥ㢟䛸䛺䜛䠊ᐃ䛧䠈⏕⫱㏿ᗘ䜢⟬ฟ䛧䛯䠊཰✭ᮇ䛻᥇ྲྀ䛧䛯䜲䝛䛾⇃ᮏ┴䛾⏣⏿㍯᥮Ỉ⏣ᅵተ䛛䜙䠈N2O 䜢ᙉຊ䛻㑏ඖ䛩䜛⬺❅⣽⳦ Azoarcus ᒓ KH32C ᰴ䛜ศ㞳䛥䜜䛯⋞⡿䛿䠈❅⣲䞉Ⅳ⣲㔞䛾ศᯒ䛚䜘䜃䜶䝛䝹䜼䞊ศᩓᆺ[2]䠊

⺯ග X ⥺ศᯒ⿦⨨䜢⏝䛔䛯↓ᶵඖ⣲䛾༙ᐃ㔞ⓗ䛺ศ

KH32C ᰴ䛾඲䝀䝜䝮ゎㄞ䛾ゎᯒ䛛䜙䠈⬺❅䛻㛵䜟䜛㑇ᯒ䜢⾜䛳䛯䠊

ఏᏊ⩌䛾䜋䛛䛻䠈❅⣲ᅛᐃ䜔Ⳓ⭷ከ⢾ྜᡂ䛻㛵䜟䜛䜲䝛᰿ᇦᅵተ䛿䠈඲❅⣲䠄TN䠅㔞䛚䜘䜃඲Ⅳ⣲䠄TC䠅㑇ఏᏊ䜽䝷䝇䝍䞊䛜ぢฟ䛥䜜䠈᳜≀䛸┦஫స⏝䛩䜛ྍ⬟㔞䜢 ᐃ䛧䛯䠊䜎䛯䠈ᅵተ DNA 䜢ᢳฟ䛧䠈⣽⳦䛾 16S

ᛶ䛜♧䛥䜜䛯[3]䠊ඛ⾜◊✲䛻䛚䛔䛶䠈KH32C ᰴ䜢䜲䝛rRNA 㑇ఏᏊ䜢ᶆⓗ䛸䛧䛯ᮎ➃ไ㝈᩿∦㛗ከᆺゎᯒ䠄᪥ᮏᬕ䠅✀Ꮚ䛻᥋✀䛧䠈❅⣲Ḟஈᐮኳ䝥䝺䞊䝖ୖ䛷᱂䠄T-RFLP䠅䜢⾜䛳䛯䠊ᚓ䜙䜜䛯 T-RFs 䝥䝻䝣䜯䜲䝹䛻ᇶ䛵ᇵ䛧䛯䛸䛣䜝䠈䜲䝛䛾ึᮇ⏕⫱䛜ಁ㐍䛥䜜䛯䠊䛝䠈䜽䝷䝇䝍䞊ゎᯒ䜢⾜䛳䛯䠊2015 ᖺ䛾᪥ᮏᬕ䛾䝃䞁䝥ᮏ◊✲䛷䛿䠈❅⣲↓᪋⫧Ỉ⏣ᅡሙ䛷 KH32C ᰴ䜢᥋䝹䛷䛿 Miseq 䛾䝯䝍䜰䞁䝥䝸䝁䞁䝅䞊䜿䞁䝇ゎᯒ䜒ే䛫✀䛧䛯䜲䝛䜢᱂ᇵ䛧䚸䜲䝛⏕⫱ㄪᰝ䛚䜘䜃䛭䛾᰿ᇦᅵ䛶⾜䛳䛯䠊ᚓ䜙䜜䛯㓄ิ䛿䠈97%䛾┦ྠᛶ䛷᧯సⓗศተ⣽⳦⩌㞟䛻ཬ䜌䛩ᙳ㡪䜢ㄪᰝ䛧䛯䠊㢮༢఩䠄OTU䠅䛻ศ㢮䛧䠈⣽⳦⩌㞟䛾ከᵝᛶゎᯒ䛚䜘

2. ᪉ἲ䜃ᖐᒓศ㢮⩌䛾᥎ᐃ䜢⾜䛳䛯䠊䜎䛯䠈㠀ィ㔞ከḟඖᑻ

2015 ᖺ䛚䜘䜃 2017 ᖺ䛻䠈Ⲉᇛ኱Ꮫ㎰Ꮫ㒊㝃ᒓᅜ㝿ᗘᵓᡂἲ䠄NMDS䠅䛚䜘䜃 Heatmap 䛻䜘䜛⣽⳦⩌䛾ື䝣䜱䞊䝹䝗㎰Ꮫ䝉䞁䝍䞊ෆ䛻タ⨨䛧䛯 2 䛴䛾↓᪋⫧Ỉែゎᯒ䜢⾜䛳䛯䠊ྛ OTU 䛾௦⾲㓄ิ䛿᳜≀⏕⫱ಁ㐍

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⣽⳦䠄PGPB䠅䝕䞊䝍䝧䞊䝇 [4] 䛸ẚ㍑䛧䛶䛭䛾┦ᑐᏑᅾ᭷ ↓ 䛷 ␗ 䛺 䛳 䛯 䠄 ᅗ 3 䠅 䠊 Heatmap ゎ ᯒ 䛾 ⤖ ᯝ 䠈㔞䜢᥎ᐃ䛧䛯䠊

Alphaproteobacteria ⥘䛾⣽⳦⩌㞟ືែ䛿᥋✀༊䛸ᑐ

3. ⤖ᯝ↷༊䛷␗䛺䜚䠈᥋✀༊䛷䛿⛉䝺䝧䝹䛻䛚䛔䛶┦ᑐᏑᅾ䜲䝛᰿ᇦᅵተ䛾 TN 㔞䛿䠈2015 ᖺ䛿 4.54-5.63 g/kg㔞䛜₞ῶ䛧䛯䠊᥎ᐃ䛥䜜䛯 PGPB 䛾┦ᑐᏑᅾ㔞䛿᥋✀䛰䛳䛯䛾䛻ᑐ䛧䠈2017 ᖺ䛷䛿 5.25-5.67 g/kg 䛷䠈2015༊䛷ቑຍ䛧䠈≉䛻⏕⫱ึᮇ䛷㢧ⴭ䛷䠈䜲䞁䝗䞊䝹-3-㓑㓟⏕⏘⣽⳦䛿 35%ቑຍ䛧䛯䠊᥎ᐃ䛥䜜䛯 PGPB 䛿ᖺ䛜 2017 ᖺ䜘䜚ప䛛䛳䛯䠊TC 㔞䛻䛴䛔䛶䜒ྠᵝ䛾ഴྥ

Alphaproteobacteria ⥘䛜ඃ༨䛧䛯䠊䛜 䜏 䜙䜜 䠈 2015 ᖺ 䛿 51.44-62.38 g/kg 䠈 2017 ᖺ 䛿
65.35-68.17 g/kg 䛰䛳䛯䠊䜲䝛䛾⏕⫱㏿ᗘ䛿䠈᪥ᮏᬕ䛿 2015 ᖺ䛾⏕⫱ึᮇ䛸ᗂ✑ᙧᡂᮇ䛷䛭䜜䛮䜜᥋✀༊䛜ᑐ↷༊䛾 1.9 ಸ䠈1.7
ಸ䛻ቑຍ䛧䠈2017 ᖺ䛷䛿 1.3 ಸ䠈1.0 ಸ䛷䛒䛳䛯䠄ᅗ 1䠅䠊䝁䝅䝠䜹䝸䛷䛿 2017 ᖺ䛾⏕⫱ึᮇ䛸ᗂ✑ᙧᡂᮇ䛷᥋✀༊䛿ᑐ↷༊䛾䛭䜜䛮䜜 0.5 ಸ䠈0.7 ಸ䛷䛒䛳䛯䠊䝍䜹䝘䝸䛿 2015 ᖺ䛾⏕⫱ึᮇ䠈IR64 䛷䛿 2017 ᖺ䛾ᗂ✑ᙧᡂᮇ䛻䛚䛔䛶䠈᥋✀༊䛷ᑐ↷༊䜘䜚⏕⫱䝇䝢䞊䝗䛜ῶᑡ䛧䛯䠊⋞⡿୰䛾ඖ⣲䛾኱༙䛷 KH32C ᰴ䛾᥋✀䛻䜘䜛᭷ព䛺ᕪ䛿䜏䜙䜜䛺䛛䛳䛯䠊୍㒊䛾ඖ⣲䛿 KH32C ᰴ䛾ᅗ 2䠊T-RFs 䝥䝻䝣䜯䜲䝹䛻ᇶ䛵䛟᪥ᮏᬕ᰿ᇦ䛾ᅵተ⣽⳦᥋✀䛻䜘䜚᭷ព䛻ቑῶ䛧䛯䛜䠈2015 ᖺ䛸 2017 ᖺ䛷ඹ㏻⩌㞟䛾䜽䝷䝇䝍䞊ゎᯒ䠊ୗ⥺䛿 KH32C ᰴ᥋✀༊䜢♧䛩䠊䛧䛶᭷ព䛻ቑῶ䛩䜛ඖ⣲䛿䛺䛛䛳䛯䠊KH32C ᰴ䛾᥋✀䛻䜘䛳䛶䠈⋞⡿୰䛾ள㖄ྵ᭷㔞䛿䠈2015 ᖺ䛷䛿᪥ᮏᬕEg䠈⏕⫱ึᮇ䠗Pf䠈ᗂ✑ᙧᡂᮇ䠗Fh䠈✑ᥞ䛔ᮇ䠗Hv䠈཰✭䛸䝍䜹䝘䝸䛷᭷ព䛻ቑຍ䠄ඹ䛻 30%䠅䛧䠈2017 ᖺ䛷䛿᪥ᮇ䠊ᮏᬕ䛷 10%⛬ᗘቑຍ䛧䛯䠊䜎䛯䠈᪥ᮏᬕ䛾㖡ྵ᭷㔞䛿
2015 ᖺ䛚䜘䜃 2017 ᖺ䛷⣙ 10%ቑຍ䛧䛯䠊⾲ 1䠊䝯䝍䜰䞁䝥䝸䝁䞁䝅䞊䜿䞁䝇䛻ᇶ䛵䛟᪥ᮏᬕ᰿ᇦᅵተ
⣽⳦⩌㞟䛾ከᵝᛶゎᯒ䠊Eg䠈⏕⫱ึᮇ䠗Pf䠈ᗂ✑ᙧᡂᮇ䠗Hv䠈཰✭ᮇ䠊

ᅗ 1䠊⏕⫱ึᮇ䛾᪥ᮏᬕ䛾⏕⫱㏿ᗘ

T-RFs 䝥䝻䝣䜯䜲䝹䛻ᇶ䛵䛟䜲䝛᰿ᇦᅵተ⣽⳦⩌㞟䛾䜽䝷䝇䝍䞊ゎᯒ䛾⤖ᯝ䠈2015 ᖺ䛾⏕⫱ึᮇ䛻䛚䛔䛶᥋✀༊䛾⣽⳦⩌㞟ᵓ㐀䛜ရ✀㛫䛷㢮ఝ䛧䛯䠊2017 ᖺ䛷䛿䠈᪥ᮏᬕ䛾᰿ᇦᅵተ⣽⳦⩌㞟䛿⏕⫱ᮇ㛫䜢㏻䛧䛶᥋✀༊䛷㢮ఝ䛩䜛ഴྥ䛻䛒䛳䛯䠄ᅗ 2䠅䛜䠈௚䛾ရ✀䛷䛭䛾ഴྥ䛿䜏䜙䜜䛺䛛䛳䛯䠊䝯䝍䜰䞁䝥䝸䝁䞁䝅䞊䜿䞁䝇ゎᯒ䛾⤖ᯝ䠈2015 ᖺ䛾᪥ᮏᬕ᰿ᇦ䛾ᅵተ⣽⳦⩌㞟䛾ከᵝᛶ䛿䜲䝛䛾⏕⫱ẁ㝵䛻䜘䜚᥎⛣䠄⾲ 1䠅䛧䠈㛛䝺䝧䝹ᅗ 3䠊䝯䝍䜰䞁䝥䝸䝁䞁䝅䞊䜿䞁䝇䛻ᇶ䛵䛟᪥ᮏᬕ᰿ᇦᅵተ

䛾⩌㞟ᵓ㐀䛿 Proteobacteria 㛛䛸 Acidobacteria 㛛䛜ඃ⣽⳦⩌㞟䛾 NMDS ゎᯒ䠊Eg䠈⏕⫱ึᮇ䠗Pf䠈ᗂ✑ᙧᡂ༨䛧䛯䠊NMDS ゎᯒ䛾⤖ᯝ䠈⣽⳦⩌㞟ᵓ㐀䛿⏕⫱ẁ㝵ᮇ䠗Hv䠈཰✭ᮇ䠊䛷㢮ఝ䛩䜛䛜䠈ྠ䛨⏕⫱ẁ㝵䛷䜒 KH32C ᰴ䛾᥋✀䛾

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4. ⪃ᐹ

ᘬ⏝ᩥ⊩

KH32C ᰴ䜢䜲䝛✀Ꮚ䛻᥋✀䛧❅⣲↓᪋⫧Ỉ⏣ᅡሙ

[1]Hayatsu M., Tago K., Saito M.: Various player in thenitrogen cycle: Diversity and functions of the
microorganisms involved in nitrification and denitrification,
Soil Sci. Plant Nutr., Vol. 54, pp. 33-45, 2008.

[2]

Tago K. et al.: Phylogenetic and functional diversity of
denitrifying bacteria isolated from various rice paddy andrice-soybean rotation fields, Microbes Environ., Vol. 26,
No.1, pp. 30-35, 2011.

[3]

Nishizawa T. et al.: Complete genome sequence of thedenitrifying and N2O-reducing bacterium Azoarcus sp. strain
KH32C, J. Bacteriol., Vol. 194, pp. 1255, 2011.

[4]

Chao Y. et al.: Structure, variation and co-occurrence of soil
microbial communities in abandoned sites of rare earth
elements mine, Environ. Sci. Technol., Vol. 50, pp.
11481-11490, 2016.

[5]

Fageria N. K., Baligar V. C.: Methodology for evaluation of
lowland rice genotypes for nitrogen use efficiency, J. Plant
Nutr., Vol. 26, No. 6, pp. 1315-1333, 2003.

[6]ᩪ⸨ࡽ㸸Ỉ✄ࡢ❅⣲฼⏝ຠ⋡࡟࠾ࡅࡿရ✀㛫ᕪ␗㸪᪥స⣖㸪➨ 75 ᕳ㸪ู 2 ྕ㸪pp. 4-5㸪2006㸬

[7]

Myers S.S., et al.: Increasing CO2 threatens human nutrition,
Nature, Vol. 510, pp. 139-142, 2014.

[8]

Caulfield L.E. and Black R.E.: Comparative quantificationof health risks: Global and regional burden of disease
attributable to selected major risk factors. Vol. 1, Ch. 5,
World Health Organization, 2014.

[9]

Hao H. et al.: Effect of different nitrogen fertilizer levels on
Fe, Mn, Cu and Zn concentration in shoot and grain quality
in rice (Oryza sativa), Rice Science, Vol. 14, No. 4, pp.
289-294, 2007.

䛷᱂ᇵ䛧䛯䛸䛣䜝䠈᪥ᮏᬕ䛷⏕⫱ಁ㐍ຠᯝ䛜䜏䜙䜜䠈
KH32C ᰴ䛾᥋✀䛻䜘䜛䜲䝛⏕⫱ಁ㐍ຠᯝ䛿䜲䝛䛾ရ✀䛻≉␗ⓗ䛷䛒䜛䛣䛸䛜♧䛥䜜䛯䠊䜲䝛䛾❅⣲྾཰㔞䜔❅⣲฼⏝ຠ⋡䠄཰㔞/❅⣲྾཰㔞䠅䛿䠈䜲䝛䛾ရ✀䠄㑇ఏᏊᆺ䠅䛻䜘䛳䛶␗䛺䜛䛣䛸䛜▱䜙䜜䛶䛔䜛[5,6]䠊䜎䛯䠈❅⣲᪋⫧㔞䛾ቑຍ䛻క䛔䜲䝛䛾❅⣲฼⏝ຠ⋡䛿ῶᑡ䛩䜛䛣䛸䛜ሗ࿌䛥䜜䛶䛔䜛[6]䠊ᅵተ TN䞉TC 㔞䛾ప䛔᮲௳䛻䛚䛔䛶䠈KH32C ᰴ䛾᪥ᮏᬕ✀Ꮚ䜈䛾᥋✀䛻䜘䜛⏕⫱ಁ㐍ຠᯝ䛜䜏䜙䜜䛯䠄ᅗ 1䠅䠊
኱Ẽ CO2 ⃰ᗘ䛾ୖ᪼䛻䜘䜚䠈䝁䝯䛾ள㖄䠈㕲ྵ᭷㔞䛜పୗ䛩䜛䛣䛸䛜㏆ᖺሗ࿌䛥䜜䛯[7]䠊⌧ᅾ䠈ୡ⏺䛾 31%䜒䛾ே䛜ள㖄Ḟஈ⑕䛰䛸᥎ᐃ䛥䜜䛶䛚䜚䠈ள㖄Ḟஈ⑕䛿ୡ⏺ⓗ䛻῝้䛺ၥ㢟䛸䛺䛳䛶䛔䜛[8]䠊⋞⡿୰䛾ள㖄ྵ᭷㔞䛿㐺ṇ㔞䛾❅⣲᪋⫧䛻䜘䜚ቑຍ䛩䜛䛸ሗ࿌䛥䜜䛶䛔䜛[9]䠊ᮏ◊✲⤖ᯝ䛛䜙䠈KH32C ᰴ䛿⋞⡿䠄᪥ᮏᬕ䠅䛾ள㖄ྵ᭷㔞䜢ቑᙉ䛥䛫䜛ᚤ⏕≀㈨ᮦ䛸䛧䛶฼⏝䛷䛝䜛ྍ⬟ᛶ䛜♧䛥䜜䛯䠊䛣䜜䜎䛷䛻䠈㑇ఏᏊ⤌᥮䛘ᢏ⾡䛾฼⏝䛻䜘䜚ⓑ⡿䛾ள㖄ྵ᭷㔞䛜ቑຍ䛧䛯䛸䛔䛖ሗ࿌䜒䛒䜛 [10] 䛜䠈᪥ᮏ䛻䛚䛔䛶㑇ఏᏊ⤌᥮䛘స≀䛾᱂ᇵ䛿ㄢ㢟䛸䛺䛳䛶䛔䜛䠊
ᅵተᚤ⏕≀⩌㞟䛿᳜≀䛾⏕⫱ẁ㝵䜔ရ✀[11]䠈᪋⫧[12,13] 䛺䛹䛻䜘䜚ᙳ㡪䜢ཷ䛡䜛䛣䛸䛜ሗ࿌䛥䜜䛶䛔䜛䠊ᅵተ⣽⳦⩌㞟䝥䝻䝣䜯䜲䝹䛻ᇶ䛵䛟ከኚ㔞ゎᯒ䛛䜙䠈[10] Masuda H. et al.: Overexpression of the barley
nicotianamine synthase gene HvNAS1 increase iron and zincconcentration in rice grains, Rice, Vol. 2, pp. 155-166, 2009.

KH32C ᰴ䛾䜲䝛✀Ꮚ䜈䛾᥋✀䛿䠈䜲䝛᰿ᇦᅵተ⣽⳦⩌ 㞟 ᵓ 㐀 䛻 ᙳ 㡪 䜢୚ 䛘 䜛 䛣䛸 䛜 ♧ 䛥䜜 䠄 ᅗ 2 䠈3 䠅 䠈
KH32C ᰴ䛾᥋✀䛜┤᥋ⓗ䜒䛧䛟䛿㛫᥋ⓗ䛻᰿ᇦᅵተ[11] van Overbeek L., van Elsas J. D.: Effects of plant genotype
and growth stage on the structure of bacterial communities
associated with potato (Solanum tuberosum L.), FEMS
Microbial. Ecol., Vol. 64, pp. 283-296, 2008.

⣽⳦⩌㞟䛻ᙳ㡪䜢ཬ䜌䛩䛣䛸䛜♧၀䛥䜜䛯䠊୍᪉䠈᰿ᇦ䛚䜘䜃᰿ᅪ䛾ᚤ⏕≀⩌䛜᳜≀䛻ᙳ㡪䜢୚䛘䜛䛣䛸䜒䜘䛟▱䜙䜜䛶䛔䜛䠊᰿ᇦ䛚䜘䜃᰿ᅪ䛻䛿䠈᳜≀䛾⏕⫱䜢

[12] Kamata M., Kawamura S., Sugino M.: Annual changes insoil nitrogen and microflora in paddy fields not fertilized
long-term and fertilized paddy fields, Mem. Fac. Agr. Kinki
Univ., Vol. 24, pp. 1-13, 1991.

ಁ㐍䛥䛫䜛᳜≀⏕⫱ಁ㐍᰿ᅪ⣽⳦⩌䠄PGPR䠅䛜Ꮡᅾ䛩䜛䛜䠈᳜≀⮬㌟䛜 PGPR 䜢ไᚚ䛧䛶䛔䜛䛸䛾ሗ࿌䜒䛒䜛[14]䠊

KH32C ᰴ䛾᥋✀䛻䜘䜚 PGPB 䛾┦ᑐᏑᅾ㔞䛜ቑ[13] Konishi N. et al.: Nitrate supply-dependent shifts incommunities of root-associated bacteria in Arabidopsis,
Microbes Environ., Vol. 32, No. 4, pp. 314-323, 2017.

ຍ䛧䛯䛸᥎ᐃ䛥䜜䛯䛣䛸䛛䜙䠈KH32C ᰴ䛾᥋✀䛿᰿ᇦᅵተ⣽⳦⩌㞟䛻䜒ᙳ㡪䜢ཬ䜌䛩䛣䛸䛜♧၀䛥䜜䛯䠊[14] Compant S., Clément C., Sessitsch A.: Plant
growth-promoting bacteria in the rhizo- and endosphere ofplants: Their role, colonization, mechanisms involved andprospects for utilization, Soil. Biol. Biochem., Vol. 42, pp.
669-678, 2010.

5. ⤖ㄽᮏ◊✲䛻䛚䛔䛶䠈䜲䝛✀Ꮚ䜈䛾 KH32C ᰴ䛾᥋✀䛜䜲䝛䛾ึᮇ⏕⫱䛚䜘䜃䜲䝛᰿ᇦᅵተ⣽⳦⩌㞟ᵓ㐀䛻ᙳ㡪䜢ཬ䜌䛩䛣䛸䛜♧䛥䜜䛯䠊䜲䝛䛾ึᮇ⏕⫱ಁ㐍䛿䜲䝛䛾ရ✀䛻䜘䜚ຠᯝ䛜␗䛺䜚䠈≉䛻᪥ᮏᬕ䛷䛿ప❅⣲䞉పⅣ⣲䛾㈋ᰤ㣴䛺ᅵተ䛻䛚䛔䛶ึᮇ⏕⫱ಁ㐍ຠᯝ䛜♧䛥䜜䛯䛣䛸䛛䜙䠈KH32C ᰴ䛿❅⣲⫧ᩱపᢞධ䛾ᅡሙ䛻䛚䛔䛶ᚤ⏕≀㈨ᮦ䛸䛧䛶䛾฼⏝䛜ᮇᚅ䛥䜜䜛䠊

1200

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P5-3

Ỉ✄᱂ᇵᢏ⾡䛾⎔ቃᙳ㡪ホ౯䠄㻸㻯㻭䠅䠖↓௦䛛䛝᱂ᇵ䛸␯᳜᱂ᇵ㻌ᚿᮧ㻌 䜒䛸Ꮚ 㻝䠈㧗ᶫⱥ༤ 㻝䠈ఀ⸨༓᫓ 㻞䠈῰㇂ඔ 㻞㻖䠈ᯘΎᛅ 㻟䠈ᯇ᳃ሀ἞ 㻝㻌㻝㎰◊ᶵᵓす᪥ᮏ㎰ᴗ◊✲䝉䞁䝍䞊䠈㻞 ⛅⏣┴㎰ᴗヨ㦂ሙ䠈㻌 㻟 ㎰◊ᶵᵓ୰ኸ㎰ᴗ◊✲䝉䞁䝍䞊䠈㻌㻖䠄⌧ᅾ䠅⛅⏣┴⏤฼ᆅᇦ᣺⯆ᒁ㻌䜻䞊䝽䞊䝗䠖㻌 ᗈᇦⓗ኱Ẽ⎔ቃ䛾ᙳ㡪䠈Ỉ⏣䠈 ᐊຠᯝ䜺䝇䠈ᐩᰤ㣴໬䠈䝷䜲䝣䝃䜲䜽䝹䜰䝉䝇䝯䞁䝖㻌ᢒ㘓㻌㏆ᖺ䠈Ỉ✄స䛷䛿Ỉ㉁ಖ඲䜔⏕ែ⣔ಖ඲䛺䛹䛾ከ㠃ⓗᶵ⬟䛻㓄៖䛧䛯ᢏ⾡䛜ᑟධ䛥䜜䛶䛝䛶䛔䜛䚹ᮏ◊✲䛷䛿䠈⛅⏣┴ඵ㑻₲ᖸᣅᆅ䛻䛚䛔䛶䠈័⾜ᢏ⾡䞉↓௦䛛䛝᱂ᇵ䞉␯᳜᱂ᇵᢏ⾡䛻䛴䛔䛶䠈䠨䠟䠝ᡭἲ䜢⏝䛔䛯⎔ቃᙳ㡪ホ౯䜢⾜䛔䠈ᆅ⌫ᬮ໬䞉ᐩᰤ㣴໬䛾⎔ቃ䜲䞁䝟䜽䝖䜢ホ౯䛧䛯䚹↓௦䛛䛝᱂ᇵ䛿⏣᳜๓䛾௦䛛䛝䜢┬䛟௦䜟䜚䛻⣽䛛䛟○ᅵ䛩䜛ᢏ⾡䛷䛒䜚䠈⏣᳜๓䛾ධỈ䝍䜲䝭䞁䜾䛜㐜䛔䛯䜑䠈‣Ỉ᫬䛾䝯䝍䞁Ⓨ⏕㔞䛜ῶᑡ䛩䜛䚹␯᳜䛿᱂᳜ᐦᗘ䜢ῶ䜙䛩ᢏ⾡䛷䠈ⱑస䜚䛻㛵䛩䜛䜶䝛䝹䜼䞊➼䛜㍍ῶ䛥䜜䜛䚹↓௦䛛䛝ᢏ⾡䛾ᑟධ䛻䜘䜚䠈 ᐊຠᯝ䜺䝇᤼ฟ㔞䛿័⾜᱂ᇵ䛾 㻢㻥䠂䛻ῶᑡ䛧䠈ᐩᰤ㣴໬䜲䞁䝟䜽䝖䜒⎔ቃᨵၿ䜢♧䛩㈇䛾್䛻ῶᑡ䛧䛯䚹␯᳜᱂ᇵ䛾 ᐊຠᯝ䜺䝇᤼ฟ㔞䛿័⾜᱂ᇵ䛾 㻥㻟䠂䛻ῶᑡ䛧䛯䚹⎔ቃ䜈䛾ᙳ㡪䜢ῶ䜙䛩䛯䜑䛻䛿䠈䛣䜜䜙䛾᱂ᇵ᪉ἲ䜢㐺ษ䛻ᑟධ䛧䛶䛔䛟ᚲせ䛜䛒䜛䚹
1. 䛿䛨䜑䛻

ῶᑡ䛜ᮇᚅ䛥䜜䜛䛊1䛋䚹␯᳜䛿䠈᱂ᇵᐦᗘ䜢័⾜䜘䜚ῶ䜙㏆ᖺ䠈Ỉ⏣䛷䛿┬ຊ໬䠈ప䝁䝇䝖໬䛸䛔䛳䛯⤒Ⴀ㠃䛻䛩᱂ᇵᢏ⾡䛾⥲⛠䛷䠈௒ᅇ䛿 21 ᰴ/m2 䛛䜙 15 ᰴ/m2ຍ䛘䠈Ỉ㉁ಖ඲䜔⏕ែ⣔ಖ඲䛸䛔䛳䛯ከ㠃ⓗᶵ⬟䛻㓄䜈䠏๭ῶ䜙䛧䛶⾜䛳䛯䚹ⱑ⟽ᩘ䛜័⾜䜘䜚ᑡ䛺䛔䛯䜑䠈៖䛧䛯ᢏ⾡䛾ᑟධ䛜່䜑䜙䜜䛶䛝䛯䚹⫱ⱑ䜔ⱑ㐠ᦙ䛾ປຊ䠈ᅵ䜔㎰⸆䠈ⱑ⟽䛺䛹䛾㈨ᮦ㈝䛜

Ỉ⏣䛿‣Ỉୗ䛷ᅵተ䛜㑏ඖ≧ែ䛸䛺䜚䠈ᐊຠᯝ䜺㍍ῶ䛥䜜䜛┬ຊప䝁䝇䝖ᢏ⾡䛷䛒䜛䚹័⾜䜘䜚Ⓩ⇍㏿ᗘ

䝇䠄GHG䠅䛷䛒䜛䝯䝍䞁䜺䝇䛜Ⓨ⏕䛩䜛䚹䛰䛜䠈᪂䛧䛔ᢏ䛜䜔䜔㐜䛟䛺䜛䛯䜑䠈㧗⾡䜢ᑟධ䛧䛯㝿䛾ᆅ⌫䜙䜒ᬑཬ䛜່䜑䜙䜜䛶䛔䜛䚹ᬮ໬䜔ᐩᰤ㣴໬䜈୚䛘䜛ᙳ㡪䜢䠈䝷䜲䝣䝃䜲䜽䝹㐣⛬䜢㏣䛳䛶᳨ウ䛧䛯஦౛䛿㠀ᖖ㞀ᐖ䜢ཷ䛡䛻䛟䛔䛸䛔䛖Ⅼ䛛䛺䛚䠈䛹䛱䜙䛾ᢏ⾡䜒ᑟධ䛻䜘䜛཰㔞䛾ቑῶ䛿䜏䜙䜜䛻ᑡ䛺䛟䠈༑ศ䛺ホ౯䛜䛺䛥䜜䛶䛔䛺䛔䚹䛪䠈ရ㉁䜒័⾜䛻ຎ䜙䛺䛛䛳䛯䚹ᮏ◊✲䛷䛿䠈Ỉ⏣䜈䛾ᬑཬ䛜່䜑䜙䜜䛶䛔䜛ᢏ⾡䛾

2.2 ౑⏝䝋䝣䝖ᑟධ䛜⎔ቃ䛻୚䛘䜛⥲ྜⓗ䛺ᙳ㡪䜢᫂䜙䛛䛻䛧䠈័⾜ゎᯒ䛻䛿䠈LCA 䝋䝣䝖䜴䜵䜰 SimaPro ver.8.4.0 䜢౑䛳ᢏ⾡䛸᪂ᢏ⾡䛸䜢ẚ㍑䛩䜛䛯䜑䠈LCA䠄䝷䜲䝣䝃䜲䜽䝹䜰䛯䚹ホ౯ᡭἲ䛻䛿䠈ᆅ⌫䝉䝇䝯䞁䝖䠅ᡭἲ䜢⏝䛔䛯⎔ቃᙳ㡪ホ౯䜢⾜䛳䛯䚹䜢䠈ᐩᰤ㣴໬䛻䛿 LIME 䜢⏝䛔䛯䚹ゎᯒ䛻⏝䛔䛯䜲䞁䝧2. ᪉ἲ䞁䝖䝸䝕䞊䝍䛾୺䛺䜒䛾䜢⾲䠍䛻♧䛩䚹

2.1 ㄪᰝᆅ䛸᱂ᇵᢏ⾡ᬮ໬䛻䛿 IPCC GWP 100a⾲㻌 㻝㻌 䜲䞁䝧䞁䝖䝸䝕䞊䝍㻌2011䡚2013 ᖺ䛻䠈⛅⏣㎰ヨ኱₲㎰ሙ䠄⛅⏣┴኱₲཰㔞D ࠶ࡓࡾ཰㔞⛣᳜䛛䜙䠓᭶ୖ᪪䛾୰ᖸ䛧䜎䛷⥅⥆ⓗ䛻‣Ỉ䛧䠈䛭䛾

⇞ᩱ

ᾘ㈝㔞

ᚋ䛿㛫᩿℺₅䛸䛧䛯䚹⫧ᩱ䛿㭜䜅䜣䝨䝺䝑䝖䛸⿕そᒀ⣲㎰ᴗᶵᲔ౯᱁㸪ᐇ⪏⏝ᖺᩘ㸪㈇ᢸ⋡䜢᪋⏝䛧䛯䠄ィ 6kgN/10a䠅䚹䝯䝍䞁䜺䝇䛿⏣᳜䛛䜙ⴠỈ䜎ࣁ࢘ࢫ㠃✚㸪ᐇ⪏⏝ᖺᩘ㸪㈇ᢸ⋡䛷䛾⣙䠏䛛᭶㛫䠈䜽䝻䞊䝈䝗䝏䝱䞁䝞䞊ἲ䛷 ᐃ䛧䛯䚹⫧ᩱၟရྡ㸪༢౯㸪౑⏝㔞㸪ᡂศྵ᭷⋡ホ౯ᑐ㇟䛸䛧䛯ᢏ⾡䛿䠈↓௦䛛䛝᱂ᇵ䛸␯᳜᱂ᇵ䛷㎰⸆ၟရྡ㸪༢౯㸪౑⏝㔞㸪✀㢮䛒䜛䚹↓௦䛛䛝᱂ᇵ䛿䠈௦䛛䛝䜢䛫䛪䠈䝻䞊䝍䝸䞊䛷⪔✀ⱑ༢౯㸪౑⏝㔞㉳䛧䛯ᚋ䛻䝗䝷䜲䝤䝝䝻䞊䛷 2䡚3 ᅇ○ᅵ䛩䜛䚹௦䛛䛝᫬㈨ᮦ

ၟရྡ㸪༢౯㸪౑⏝㔞㸪✀㢮䛾⃮Ỉ᤼ฟ䛜䛺䛔䛯䜑Ỉ㉁ಖ඲ຠᯝ䛜㧗䛔䜋䛛䠈Ỉ

࢞ࢫ

࣓ࢱࣥ

⁐⬺

❅⣲㈇Ⲵ㔞

ᮧ䠅䛾Ỉ⏣䛷Ỉ✄䠄䛒䛝䛯䛣䜎䛱䠅䛾᱂ᇵヨ㦂䜢⾜䛳䛯䚹✄䛾᰿άᛶ䛜㧗䜎䜚䠈㧗Ⓩ⇍ୗ䛷䛾ရ㉁పୗ䛜⏕䛨䛻䛟䛔䚹䜎䛯䠈⛣᳜๓䛾℺Ỉ䜢⛣᳜┤๓䜎䛷㐜䜙䛫䜛䛸䠈ᩳᏐ䠖⛅⏣┴Ỉ✄⤒Ⴀᣦᶆ䝕䞊䝍ᅵተ䛾㑏ඖ໬䛜䜔䜔ᢚไ䛥䜜䜛䛯䜑䠈䝯䝍䞁Ⓨ⏕㔞䛾䛭䛾௚䠖⌧ᆅ䛷䛾ᐇ

1䛚䜘䜃⪺䛝ྲྀ䜚ㄪᰝ⤖ᯝ➼1203

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018ᙳ㡪ホ౯䛿䠈⏣㠃䛛䜙䛾᤼ฟ䞉⇞ᩱᾘ㈝䞉ᶵᲔ〇㐀䞉௦䛛䛝༊䛷䛿䛭䛾㐣⛬䛾್䛜䝬䜲䝘䝇್䛸䛺䛳䛶䛚䜚䠈⫧ᩱ〇㐀䠄໬Ꮫ⫧ᩱ䞉᭷ᶵ⫧ᩱ䠅䞉㎰⸆〇㐀䞉㈨ᮦ➼〇㈇䛾ᙳ㡪䠈䛴䜎䜚䛣䛾ሙྜ䛿࿘ᅖ䛾Ỉ⎔ቃ䜢ί໬䛧䛶

㐀䛾 7 㐣⛬䛻༊ศ䛧䛶⾜䛳䛯䚹䛔䜛䛣䛸䜢♧䛧䛶䛔䜛䚹௚䛾㐣⛬䛿䝥䝷䝇್䛷ᐩᰤ㣴໬

3. ⤖ᯝ䜢ಁ㐍䛧䛶䛔䜛䛜䠈䛭䛾್䛿⏣㠃䛛䜙䛾᤼ฟ䛻䜘䜛ᙳ㡪

3.1 䝯䝍䞁䜺䝇Ⓨ⏕㔞䛸ẚ䜉䜛䛸䜟䛪䛛䛷䛒䜛䚹㻌⏣㠃䛛䜙䛾Ⓨ⏕㔞䛿ᖺ䛻䜘䛳䛶ᕪ䛜ぢ䜙䜜䛯䚹2011ᖺ䛸 2013 ᖺ䛿䠈↓௦䛛䛝༊䛾Ⓨ⏕㔞䛜௦䛛䛝༊䛾⣙༙ศ䛸ᑡ䛺䛛䛳䛯䛜䠈2012 ᖺ䛿ᕪ䛜ᑠ䛥䛛䛳䛯䠄ᅗ䠍䠅䚹3ᖺ㛫䛾⥲㔞䛷䜏䜛䛸䠈↓௦䛛䛝༊䛾Ⓨ⏕㔞䛿௦䛛䛝༊䛾 64䠂䛷䛒䜚䠈䝯䝍䞁Ⓨ⏕䛜ᢚไ䛥䜜䛶䛔䛯䚹័⾜᳜༊䛸␯᳜༊䛷䛿Ⓨ⏕㔞䛾ᕪ䛿ᑠ䛥䛟䠈␯᳜༊䛿័⾜᳜༊䛾 93䠂䛷䛒䛳䛯䚹* 䠖Ḟ missing䜶䝷䞊䝞䞊error bars䠖ᶆ‽೫ᕪ the standard deviation⪔㉳᪥ The plowing dates:
2011/5/18-26, 2012/4/19-20, 2013/5/9-10ᅗ䠍 䝯䝍䞁Ⓨ⏕㔞 Methane emissions䛊2䛋

3.2

ᅗ䠎㻌 ௦䛛䛝༊䞉↓௦䛛䛝༊䛾᤼ฟ㐣⛬ู䛾ᐊຠᯝ䜺䝇᤼ฟ㔞䛸ᐩᰤ㣴໬䜲䞁䝟䜽䝖䠄␯᳜᫬䠅

4. ⪃ᐹ
Ỉ✄䜈䛾᪂䛯䛺᱂ᇵᢏ⾡ᑟධ䛻䜘䜛⎔ቃᙳ㡪ホ౯䠄ᆅ⌫ᐊຠᯝ䜺䝇䠄GHG䠅᤼ฟ㔞௦䛛䛝༊䞉↓௦䛛䛝༊䛷䛾᤼ฟ㐣⛬ูᬮ໬䛸ᐩᰤ㣴໬䠅䜢⾜䛳䛯䚹ᐊຠᯝ䜺䝇᤼ฟ

㔞䛿䠈↓௦䛛䛝༊䛿௦䛛䛝༊䛾 69%䠈␯᳜༊䛿័⾜᳜ᐊຠᯝ䜺䝇༊䛾 93䠂䛻䛸䛹䜎䜚䠈ᆅ⌫ ᬮ໬ᢚไຠᯝ䛜䜏䜙䜜䛯䚹᤼ฟ㔞䜢ᅗ 2(a)䛻♧䛩䚹᤼ฟ㔞䛿䠈஧㓟໬Ⅳ⣲䠈䝯䝍䞁䠈ᐩᰤ㣴໬䜲䞁䝟䜽䝖䛿䠈↓௦䛛䛝༊䛷䛿㈇䛾್䜢♧䛧䠈୍㓟໬஧❅⣲䛾᤼ฟ㔞䜢䠈஧㓟໬Ⅳ⣲䛻᥮⟬䛧䛶♧Ỉ㉁⎔ቃ䛾ᨵၿ䛻㈉⊩䛧䛶䛔䜛䛣䛸䛜♧䛥䜜䛯䚹Ỉ✄䛩䚹స䛜⎔ቃ䜈୚䛘䜛ᙳ㡪䜢ᑠ䛥䛟䛩䜛䛻䛿䠈䛣䜜䜙䛾᱂ᇵ㐣⛬ู䛻䜏䜛䛸䠈⏣㠃䛛䜙䛾᤼ฟ㔞䛾๭ྜ䛜᭱䜒㧗䛾ᑟධ䜢㐺ษ䛻⾜䛖䛣䛸䛜ᚲせ䛷䛒䜛䚹䛟䠈௦䛛䛝༊䛷䛿᤼ฟ㔞඲య䛾 86%䠈↓௦䛛䛝༊䛷䛿䛺䛚䠈ᮏ◊✲䛿㎰ᯘỈ⏘┬䛂㎰ᯘỈ⏘ᴗ䞉㣗ရ⏘ᴗ

80%䜢༨䜑䛯䚹⏣㠃䛛䜙䛾᤼ฟ䛾኱㒊ศ䛜๓⠇䛷ㄝ᫂䛧䛯䝯䝍䞁䛷䛒䛳䛯䚹ḟ䛻ከ䛔䛾䛜໬Ꮫ⫧ᩱ〇㐀㐣⛬䛛⛉Ꮫᢏ⾡◊✲᥎㐍஦ᴗ䛃䛻䛚䛔䛶ᐇ᪋䛧䛯䜒䛾䛷䛒䜛䚹䜙䛾᤼ฟ䛷௦䛛䛝༊ 4.1%䠈↓௦䛛䛝༊ 5.9%䛷䛒䛳䛯䚹ᘬ⏝ᩥ⊩↓௦䛛䛝༊䛾 GHG ᤼ฟ㔞䛿௦䛛䛝༊䛾 69%䛸ᑡ䛺䛟䛺䜚䠈↓௦䛛䛝᱂ᇵ䛾ᑟධ䛻䜘䜛ᐊຠᯝ䜺䝇᤼ฟ㔞䛾ᢚไຠᯝ䛜䜏䜙䜜䛯䚹␯᳜༊䛾ᐊຠᯝ䜺䝇᤼ฟ㔞䛿័⾜᳜༊䛾 93䠂䛷䛒䛳䛯䚹
3.3 ᐩᰤ㣴໬䜲䞁䝟䜽䝖௦䛛䛝༊䠈↓௦䛛䛝༊䛾ᐩᰤ㣴໬䜲䞁䝟䜽䝖䠄≉ᛶ್
EPMC䠅䜢㐣⛬䛤䛸䛻ồ䜑䛯⤖ᯝ䜢ᅗ䠎(b)䛻♧䛧䛯䚹௦䛛䛝༊䛷䛿⏣㠃䛛䜙䛾᤼ฟ㐣⛬䛾ᐤ୚䛜኱䛝䛔䛜䠈↓

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[1]

ఀ⸨༓᫓䠈῰㇂ඔ䠈ᯘ㞞ྐ䠈῰㇂ᓅ䠖䇾ᮾ໭㎰ᴗ◊✲ᡂᯝ᝟ሗ䇿䠈㎰◊ᶵᵓ䠈䠄䜸䞁䝷䜲䞁䠅䠈ධᡭඛ<http://www.naro.
affrc.go.jp/org/tarc/seika/jyouhou/H24/kankyou/H24kankyo
u009.html>䠈䠄ཧ↷ 2018-5-2䠅

[2]

Motoko SHIMURA, Hidehiro TAKAHASHI, Chiharu ITO,
Makoto SHIBUYA, Kiyotada HAYASHI, and Kenji
MATSUMORI: Improvement Potential of Life Cycle
Greenhouse Gas Emissions from Paddy Fields: Assessing
Influence of Sparse Transplanting and Non-puddling, JARQ,
Vol. 51 No. 2, pp. 155-164, 2017.

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-4

An N-alkane δ13C for Assessing Sources of Terrestrial Organic Matterin Lacustrine Sediments in China
Yanhua Wang1, Yuping Liu1 and Xia Chen
1

School of Geography Science, Nanjing Normal University, 2 Jiangsu Center for Collaborative Innovation in
Geographical Information Resource Development and Application
Keywords: lake sediment, organic matter, n-alkane and δ13C
ABSTRACTTo assess sources of terrestrial organic matter in lacustrine sediments in China, three sediment cores were collected froman area of several square meters in a small catchment. Results show 126 years of sediment deposition, from year 1885 to
2011. The accumulation rates ranged from 2.69 to 8.46 mm a-1. All sediment samples were dominated by odd numberedn-alkanes (n-C16～n-C33), especially n-C17, n-C29 and n-C31 as the most abundant homologues. Aliphatic hydrocarbon
fractions are mainly composed of terrestrial higher plant-derived long-chain n-C29 and n-C31 alkanes. The most abundantcompounds have been described as typical constituents of trees and shrubs (C3 plants). The indicators indicate enhanced
eutrophication resulted from increased anthropogenic activities in the Taihu watershed.

1. INTRODUCTION

to 102 Bq kg-1. A constant CRS model gave 126 years of
sediment deposition, from year 1885 to 2011. The
accumulation rates ranged from 2.69 to 8.46 mm a-1.

The sedimentary organic matter (OM) is a heterogeneousand a complex mixture of organic compounds withdifferent chemical characteristics, originating fromautochthonous primary production and allochthonous
terrestrial materials (Wang et al., 2015 and references
therein). However, autochthonous and allochthonous
contributions in the complex environments of thewatershed with excursions to larger carbon stable
isotopes (δ13C) values make it difficult to determine
accurately the OM sources by n-alkanes distribution. The
principal aims of this study were: to identify sedimentary
OM sources and assess quantitatively the C3 plants
contribution to sedimentary OM.

All sediment samples were dominated by odd numberedn-alkanes (n-C16 ～n-C33), especially n-C17, n-C29 andn-C31 as the most abundant homologues. In this study,
aliphatic hydrocarbon fractions are mainly composed ofterrestrial higher plant-derived long-chain n-C29 andn-C31 alkanes. The values of bulk δ13C for organic matter(δ13CSOC) (by IRMS, USA) varied from -24‰ to -21‰.
The values of carbon isotopic compositions of long-chain
n-alkanes (δ13C27, δ13C29 and δ13C31) exhibited a range of-33‰ to -25‰, -35‰ to -28‰ and -31‰ to -26‰,
respectively.

2. METHOD

4. DISCUSSION
The n-alkanes distribution observed in this study agrees
with earlier observations in the Shuanglong catchment of
the Dianchi watershed (Wang et al., 2015). The terrestrial
higher plants may be the main sedimentary OM origin.
The most abundant compounds have been described as
typical constituents of trees and shrubs (C3 plants).

In present study, three sediment cores were collectedfrom an area of several square meters in a small
catchment. The core was sectioned at 1 cm intervals. The
sub-samples were crushed to a fine powder (particle size
≤ 0.15 mm). The activities of 226Ra and 210Pb were
determined using a high-resolution HPGe γ-spectrometry
system with 62% relative detection efficiency(GWL-120-15, USA). A constant CRS model was applied
to date the sediment core. The alkane compositions wereanalyzed by gas chromatograph (GC, HP 6890 II, Agilent,
USA) with a split/splitless injector and a flame ionization
detector (FID).

5. CONCLUSION

3. RESULTS

1)

The contribution of terrestrial C3 plants ranged from
41% to 95%.

2)

The sedimentary OM was mainly derived fromterrestrial higher plants with C3 metabolism.

3)

Increased human activities enhanced the OM inputs
and deposition in the watershed, resulting in muchworse ecosystem in the past decades.

The 210Pbex activities in the sub-samples ranged from 16

1

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

REFERENCES[1]

B. Aichner, U. Herzschuh, H.Wilkes, A. Vieth, J. Böhner: δDvalues of n-alkanes in Tibetan lake sediments and aquatic
macrophytes - a surface sediment study and application to a
16 ka record from Lake Koucha, Organic Geochemistry, Vol.
41, pp.779-790, 2010.

[2]

Y. Wang, H. Yang, J. Zhang, W. Gao, C. Huang, B. Xie:
Characterization of n-alkanes and their carbon isotopic
composition in sediments from a small catchment of the
Dianchi watershed, Chemosphere, Vol. 119, pp.1346-1352,
2015.

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-5

題名：基盤整備後ハス田地帯からの流出量調査について
飯尾 恒 1，吉田 繁樹 1,2，吉尾 卓宏 3，北村 立実 1，松本 俊一 1，黒田 久雄 41

茨城県霞ケ浦環境科学センター，2（現）茨城県農林水産部畜産課，3 茨城県農業研究所，4 茨城大学農学部
キーワード：ハス田，農業，流出負荷量，基盤整備
抄録

全国第 2 位の湖面積を有する霞ヶ浦の流域はレンコン栽培が非常に盛んな地域である。茨城県のレンコン
出荷量は全国 1 位であり，全国のレンコン収穫量・出荷量の半分近くを占めている。茨城県土浦市手野地区
はレンコン専作地帯で，1995 年から 2015 年にかけて日本で初めてハス田での基盤整備を実施し，コンクリート畦畔
整備や用排分離等を行った。本研究では基盤整備された手野地区において流出負荷量調査を行い，基盤整備による流出負荷量の影響を調査した。その結果，過去の手野地区における研究に比べ，差引排出負荷量が大きい値を示した。これらは用排分離を行った結果，田越灌漑の沈殿効果の消失した影響であることが考えられた。しかし，土浦市内の他の地区における差引排出負荷量と比較した場合，本研究の値はそれらと大きな差はないことから，一般的なハス田群からの流出する負荷量と同程度であることが示唆された。

1. はじめに霞ヶ浦は茨城県，栃木県及び千葉県の一部を流域と

2. 方法

する日本第 2 位の湖沼面積を有する湖沼である。しかし，湖沼面積が広く，水深が浅いなどの特徴や湖水の交換

2. 1. 調査地の概要

日数に約 200 日かかることから，元来水質汚濁が生じや調査地は茨城県土浦市手野地区のハス田群 148ha

すい湖沼でもある

を対象にした（図 1）。地区内に数戸の住宅が見られる

茨城県のレンコン作付面積は 1,610ha であり，その収が，土地利用のほとんどはハス田である。

穫量・出荷量は全国の半分近くを占めている [1]。レンコ

手野地区の排水は石田揚排水樋門へ集まり，霞ヶ浦

ンの収穫方法は水掘りと手掘りがあり，茨城県では水掘に自然排水している。ただし，大雨等の場合のみ石田

りにて収穫している。この水掘りは地下水をくみ上げ，ポ

排水機場からポンプを用いて強制排水を行っている。

ンプの水圧で泥を飛ばしレンコンを収穫するため，作業用水は石田揚排水樋門へ流れてくる排水を手野第一

効率は良いが濁水が生じやすい[2]。

用水機場にて地区東側に揚水しており，地区西側を流手野地区は，茨城県土浦市東北部の霞ヶ浦湖岸にれる境川の水を手野第二用水機場にて地区西側に揚位置するレンコン専作地帯である。手野地区のハス田水している。手野第一用水機場については石田揚排水は，もともと区画が小型不整形で道路は狭く屈曲し，用樋門から自然排水しているため，用水ポンプを稼働す

排水施設も未整備であった。このため，1995 年からると霞ヶ浦から一部流入が認められる。また，一部ハス2015 年にかけて日本で初めてハス田での基盤整備を

田は境川上流から分岐する用水路から取水している

実施し，コンクリート畦畔整備や用排分離等を行った。

（図 1）。

これまでに，手野地区では基盤整備完了前に流出負荷量調査が行われていたが，基盤整備完了後に調査は

2. 2. 調査方法

行われていない[3,4]。
そこで，本研究では基盤整備された手野地区におい手野地区において，2016 年 9 月から 1 年間調査て流出負荷量調査を行い，基盤整備による流出負荷量を実施した。採水は末端の用排水機場では自動採水器を用いて 24 時間間隔，用水機場と用水路では毎の影響を調査したので報告する。

週手動採水を行った。排水量は堤脚水路に設置した

1

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

自記水位計と電磁流速計の結果から算出した。取水量はポンプ稼働時間と流入水量から算出した。ハス田の調査はハス田に設置した自動採水器を用いて朝夕採水した。排水量は直角三角せきを用いて算出した。
水質分析は JIS 法（K 0102）に準拠して行った。

3. 結果と考察
手野地区はもともと田越灌漑でレンコン栽培を行っていたが，基盤整備に伴い畦畔のコンクリート化と用排分離を行った。
本研究で手野地区における流入水と排水を調査し

図 1 調査地点地図

た結果，過去の手野地区における研究に比べ，差引

手野地区は地区南側の（A）石田揚排水樋門から霞排出負荷量が大きい値を示した [3,4]。ハス田で田越ヶ浦に排水している。また，地区北側の境川から分岐す灌漑を行うと，下流のハス田を通過する最中に負荷る（C）用水路と，西側の（B）境川にある手野第二用水

量が削減することが知られている [5]。このことから，機場から取水している。（A）手野第一用水機場では排水を揚水している。

基盤整備により田越灌漑の負荷量削減作用が消失し：用水方向，

た結果，過去の研究に比べ差引排出負荷量が大きく：排水方向なったことが示唆された。しかし，土浦市内の他の地区における差引排出負荷量と比較した場合，本研
究の値はそれらと大きな差はないことから，一般的なハス田群からの流出する負荷量と同程度であることが示唆された [4]。

引用文献
[1]
[2]

農林水産省: 平成 28 年産野菜生産出荷統計, 2017.
沢田 英司: 新得産シリーズレンコン栽培から加工・販
売まで, 社団法人農山漁村文化協会, 2010.
[3] 黒田 久雄, 加藤 亮, 中曽根 英雄: ハス田群からの流出負荷量調査について, 農業農村工学会論文集, No.
265, pp. 47-53, 2010.
[4] 北村 立実, 吉尾 卓宏, 山本 麻美子, 塚本 威, 黒田 久雄: 河川から灌漑する霞ヶ浦湖岸ハス田地帯からの流出負荷特性, 農業農村工学会論文集, No. 286, pp.
11-17, 2013.
[5] 吉尾 卓宏, 山本 麻美子, 元木 努, 北村 立実, 片倉
洋一: ハス田から流出する汚濁負荷削減のための調査研
究（H18 ～ H21）, 茨城県霞ケ浦環境科学センター年報,
第 6 号, pp. 57-64, 2010.

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図 2 手野地区日平均水収支フローダイヤグラム217th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-6

Recent changes in the vertical distribution of Nitrogen and Phosphorous in a brackish lake Ogawarako of northeastern Japan.
Kazunori Shizuka1,2, Nagamitsu Maie3, Sakurako Nagayama3, Rikuo Yamabata3, Masayasu Nagasaki1, Noriaki Matsuya1, Wataru Kakino3, Hajime Tanji3.
Inland Water Fisheries Research Institute, Aomori Prefectural Industrial Technology Research Center, 2Graduate Schoolof Veterinary Sciences, Kitasato University, 3School of Veterinary Medicine, Kitasato University

1

Keywords: Brackish lake, Nutrient Dynamics, Eutrophication, Long-term monitoring, Nitrogen, Phosphorous
ABSTRACT

Lake Ogawarako is a brackish lake located in a rural area of the east part of Aomori Prefecture, the northernmost part of the main island of Japan. There, eutrophication, which leads to the dominance of cyanobacteria, has become a big problem as is the case with other brackish lakes. To cope with this problem, wesurveyed recent changes in the total amounts of total nitrogen (TN) and total phosphorous (TP) in the wholelake water (hereafter refer to ΣTN and ΣTP, respectively) and its vertical distribution from Oct. 2010 toAug. 2017. ΣTN and ΣTP were 1092±179 t and 109±29 t, respectively. About 22-63% of ΣTN and 38-79%
of ΣTP were distributed in the high-salinity layer of 15-21m, which composed only 13% of the lake water
volume. TN and TP amounts in this layer largely varied temporally, suggesting that they were contributing
significantly to the TN and TP amounts in the low-salinity layer. ΣTN decreased from 2015, and at the sametime, halocline also deepened from ca. 15 m to 17 m. Therefore, it is considered that TN in the high-salinity
layer were advected and diffused into the low-salinity layer, and outflowed from the lake. ΣTP tended toincrease during the survey period. However, after typhoon events in Aug-Sep 2016, it dropped sharply,
probably due to the flush out of massive amounts of water from the watershed and possibly due to adsorption of phosphate onto Andisol transported from the watershed.

1. INTRODUCTION

Most of river water flows into the lake from the southwest
and flow out to the north. Sea water sometimes runs backfrom Pacific Ocean, especially in summer and winter. In
recent years, high-salinity water with no oxygen is stagnated, forming halocline at around 16-18m.

Lake Ogawarako is a brackish lake with the fifth largest
surface area in Japan, where catches are among the highest
for inland fishery in Japan. Recently, it has become increasingly eutrophic, and water quality degraded as is seenby the blooming of cyanobacteria and production of unusual odor. To cope with these problems, it is necessary tounveil the dynamics of nitrogen and phosphorous in thelake water. Therefore, we investigated the vertical distribution of total nitrogen (TN) and total phosphorous (TP)in the lake water from Oct. 2010 to Aug. 2017, and discussed the influential factors including typhoon.
2. STUDY AREA
Lake Ogawarako is a brackish lake located in the northeastern part of the main island of Japan. The area is a temperate rainy climate (Cfa), with annual average temperature of 12.4˚C (max 25.1˚C; min -0.5˚C) and annual precipitation of 861 mm. It is a rural area and the main landuse of the watershed is forest and arable land. Surface areaand max and average depths of the lake are 62 km2, 26m(deepest among brackish lakes in Japan), and 11 m, respectively. Residence time of the lake water is about 1 year.

Fig. 1 Map of Lake Ogawarako[2]

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3. METHODS

and Aug. 2016.

Vertical water samples were collected using a Van Dorn
water sampler every 2 m at the center of the lake every
month from Apr. 2015 to Aug. 2017. Analysis of total nitrogen (TN) and total phosphorus (TP) was conducted bycontinuous flow analysis with an auto-analyzer (SWAAT,
BL-TEC). TN and TP data from Oct. 2010 to Mar. 2015
was cited from long term monitoring data collected by
Ministry of Land, Infrastructure, Transport, and Tourism,
and is publicly available in Water Information System(http://www1.river.go.jp/). The volume of the lake water
was calculated based on a digital bathymetric map of Geospatial
Information
AuthorityofJapan(http://www.gsi.go.jp/kankyochiri/lakedatalist.html) byusing SAGA GIS (ver. 2.3.2). TN and TP amounts were
calculated by multiplying TN or TP concentrations andwater volume of each depth section.

*
*
*

**
*

*
*

*

Fig. 2 Total amount of TN and TP in the wholewater body of Lake Ogawarako from Oct.
2010 to Aug. 2017. Bars with * were obtained
mathematically by spline interpolation.

4. RESULTS
4.1. Total nitrogen
Total amount of TN in the whole lake water body(ΣTN) ranged from 642 t to 1554 t, with an averageof 1092 t from Oct. 2010 to Aug. 2017. It increased
during Jan. to Apr., showing by 9% higher values
than other months (Fig. 2). ΣTN increased from800-1100 t in 2011 to 1100-1500 t in 2014, thenturned to decrease and was 800-1000 t in 2017.
When looking at vertical distribution, 43% on ave(min 22%, max 63%; Fig.3) of ΣTN was distributed
in 15-21 m depth section. When looking at intraannual variation, the TN amount remarkably increased in the <10m section from Jan. to Apr. Forinterannual variation, TN amount tended to decrease at < 10 m from 2015, and the TN amount in
15-21 m section decreased sharply from Aug. 2016,
after unusual disturbance by typhoons.

TN (t/0.1m)

4.2. Total phosphorous

TP (t/0.1m)

Total amount of TP in whole lake water body (ΣTP)
ranged from 61 t to 192 t with an average of 109 t fromOct 2010 to Aug. 2017 (Fig. 2). While no appreciable seasonal trend was observed, it increased from 60-130 t in2011 to 100-190 t in 2014, and kept the value until Aug.
2016. The ΣTP showed a sharp decrease to 70-120 t from
Sep. 2016, after extensive disturbance caused by a seriesof typhoons.
A large amount of TP was distributed between 1521 m section, which composed of ave 66% (min 38%, max
79%) of ΣTP (Fig.3). The amount remarkably increased
from Jan. to Apr. as was the case with TN. TP in 15-21m
section sharply decreased while TP <10 m increased in Feb.

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Fig. 3 Vertical distribution of the amount ofTN and TP in Lake Ogawarako from Oct. 2010
to Aug. 2017.

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

contribution of internal loading and could also due to theadsorption of phosphate onto Andisol, which was transported from the watershed into the lake as suspended solid.

5. DISCUSSION
Lake Ogawarako has halocline at around 15-18 m all
through the year. Since the mixing of lake water beyond
halocline is restricted, and in addition, TP and TN are
loaded from the bottom sediment under anoxic condition,
TN and TP concentrations in high-salinity water were ave
10 and 37 times higher than surface water, respectively.
Reflecting these, 22%-63% of ΣTN and 38%-79% of
ΣTP were distributed in 15-21 m section, where only 13%
of total water volume existed. Interestingly, the total
amount of TN and TP in 15-21 m zones changed significantly over time. Therefore, TN and TP in this section isconsidered to be the important source of those in the upper
section.

6. CONCLUSION
We investigated the actual status of N and P in the water
body of Lake Ogawara, a brackish lake in temperate region,and their recent changes. Further, we discussed the possible influential factors. Total amounts of N and P in thewhole water body of the lake is estimated to be 1092±179t and 109±29 t, respectively. On average, 43% of TN and
66% of TP were distributed in 15-21 m section, where only
13% of total water volume existed. The amount of N and
P in this section significantly changed intra-annually andinter-annually, and serving as the important nutrient sourceof the upper section. Total amount of N tended to decreasesince 2015 in association with the deepening of halocline.
Thus, changes in the vertical circulation is considered toinfluence largely on the water quality in the surface water.
Total amount of P tended to increase since 2011, but it decreased sharply after typhoon events in Aug-Sep. 2016.
This result suggested that P dynamics in the lake water isinfluenced strongly by extreme weather events. Concluding this research, water quality in Lake Ogawarako wasshown to be strongly affected by hydrology characteristicsof the lake. Further long-term monitoring and experimental verification are necessary to reveal the mechanismsof the changes in nutrient cycling caused by global warming, which changes lake/watershed hydrology and increases the number and extent of extreme weather events.

We found that TN and TP concentrations below
halocline zone changed dramatically when sea water inflowed from Pacific Ocean. Since the density of back-flow
sea water was much heavier than that of lake high-salinity
water, it went under the lake water, lifting it up. This probably caused advection diffusion of high salinity water andfollowed diffusion into the low-salinity layer with verticalmixing. This phenomenon was usually observed from Oct.
to Apr. unless the surface got frozen.

The ΣTN tended to be larger by 9% from Jan.-Apr.

than other months. This is probably because the relative
contribution of internal loading became larger during thisperiod with the decrease in the river water inflow, leading
to the prolonged retention time of the lake water. ΣTN(1092 t) and ΣTP (192 t) corresponded to 1.0 and 4.5 timesof their annual loading from the watershed[1] (TN: 1059 t㸪
TP: 24 t), respectively. This suggested that the amount of
N in the lake was more prone to be influenced by inflowing
water.

ACKNOWLEDGEMENTS
The authors would like to thank Hideki Ebina and otherstaff members of Lake Ogawara Fisheries Cooperative Association for their cooperation in the survey of Lake Ogawara. Part of the data used in this paper was cited fromthe water quality monitoring data conducted by Takase
River Management Office, Tohoku Regional Development
Bureau, Ministry of Land, Infrastructure, and Transport.
This work was supported by JSPS KAKENHI Grant Number 15K07532.

ΣTN turned to decrease after 2015, which change
was in accordance with when the depth of halocline layer
dropped from ca. 15m to 17m. As such, changes in the volume of high-salinity layer, which accumulates a large
amount of TN, probably causes changes in ΣTN in thelake. ΣTP turned to decrease after Sep 2016, and one
month before that, TP amount from low-salinity water section increased sharply. As such, the changes can be attributed to three typhoons landed/passed by in series. Especially, typhoon No. 10 (aka. Lionrock) landed Tohoku
district on Aug. 30, 2016 for the first time after 1951 mixed
the lake water severely, made P in the high-salinity layer
move up to low-salinity layer. Followed with that, a portion of TP in low-salinity layer was flushed out from thelake with massive amount of inflowing water from watershed. It is notable that the decrease was only observed for
TP. This could be due to the difference in the degree of

REFERENCES[1]

Nishida, S. and Suzuki, S. 2007. Variability of water quality
and nutrients cycle in Lake Ogawara, Fisheries Engineering,44, 39-43 (in Japanese).

[2]

Geospatial Information Authority of Japan. http://www.
gsi.go.jp/kankyochiri/lakedatalist.html

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-7

Evaluation of Available Water Resources and Nitrogen Runoff
in Northeast Thailand
Yuki Jikeya1, Koshi Yoshida1, Shigeya Maeda1 and Hisao Kuroda1
1

Ibaraki University, Japan

Keywords: TOPMODEL, Water balance, Nitrogen dynamics, Spatial distribution
ABSTRACTIn Northeast Thailand, the ratio of irrigated agricultural land is only 8% and others are rain-fed so thatclimate change makes agricultural production more unstable and also makes crucial damage to the societies
and economics in local area. To mitigate these issues, it is desirable to develop and disseminate enhanced
adaptation systems. In this study, water and nitrogen-load estimation model was developed and applied to
Northeast Thailand. Both calculated river discharge and nitrogen load were good agreement with observed
data. By using the proposed model, spatial distribution of available water and annual nitrogen load were
estimated, and histograms of nitrogen load from each land use was evaluated.
1. INTRODUCTION

2. METHOD

Meteorological Uncertainty caused by Global Climate
Change would have significant impact on agricultural
sector, because agricultural systems are strongly relatedwith local climate condition. Especially in Northeast
Thailand(Fig.1), the ratio of irrigated agricultural land is
only 8% and others are rain-fed so that climate change
makes agricultural production more unstable and also
makes crucial damage to the societies and economics inlocal area. To mitigate these issues, it is desirable todevelop and disseminate enhanced adaptation systems. In
this study, water and nitrogen-load estimation model wasdeveloped to assess the spatial distribution of available
water resources and nitrogen runoff, and applied to
Northeast Thailand.

2.1 TOPMODEL
To evaluate nitrogen transportation according to the riverwater flow, a distributed water-cycling model wasdeveloped and applied to analyze the water balance in thebasin [6]. TOPMODEL was employed for the rainfallrunoff analysis. This distributed model can include thespatial distributions of topography, land use, and soil
characteristics. Therefore, TOPMODEL is used widely forhydrological characteristic analysis, water management,water quality analysis, and future forecasting. Firstly,
TOPMODEL was proposed by Beven and Kirkby (1979)
based on the contributing area concept in hillslope
hydrology.
Because TOPMODEL requires only three parameters (i.e.,m, To, and Srzmax), the model is easy to link with GIS
data[1]. In addition, a dam operation model was combinedwith TOPMODEL to calculate water storage in thereservoirs [3].

Laos

2.2 Nitrogen balance model
For a nitrogen dynamics analysis in soil, Suga (2005)
mentioned that three type of nitrogen such as organic,ammonium, nitrate should be considered. In this study, aconceptual nitrogen balance model was developed byconsidering three pools in soil, organic N, ammonium N,
and nitrate N, as shown in Fig. 2. In this study, organic N
here is assumed as nitrogen contained in relatively firstly
decomposed organic matter which can be obtained by
autoclave-extractable nitrogen test. The soil N, present
mainly in organic form, is almost unavailable for plants.
The vegetation uses mostly inorganic forms of N, which
are made available by decomposition of organic matter.
Soil microorganisms convert the N contained in theThaiVietnam
CambodiaFig. 1

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

The observed and calculated daily nitrogen load at the
Yasothon station is shown in Fig. 4. Estimated correlation
coefficients R were 0.69. The data of total nitrogenconcentration in the Mun-Chi River Basin were measured
only once per month; therefore, there is a possibility thatpeak nitrogen load might not be observed in such data. The
current monitoring system of water quality data is manual,so if the frequency of monitoring were to be improved byusing an automatic monitoring system, the model
parameters also could be calibrated through better fitting.

organic matter through the process of mineralization.
Nitrates dissolve quickly in pore solution, which is taken
up by plants. On the other hand, this means that nitrate iseasily leached to groundwater. Ammonium N is lessmobile because it is strongly adsorbed on clay minerals
because of its positive charge.
3. RESULTS AND DISCUSSION
By using the proposed model, water and nitrogen balancesin Northeast Thailand were calculated at a resolution of 1
km × 1 km. The calculated river discharge was in good
agreement with the amounts observed at Yasothon stationfrom 1987 to 2003 (Fig. 3). The first 5 years of data wereused for parameter calibration, and the latter 12 years ofdata were used for validation. At the Yasothon station,Nash-Sutcliff efficiency (NSE) were 081 in the calibrationand validation periods. Model performance can beevaluated as “good”, if NSE > 0.75 [4].

Calculated nitrogen load (t/day)

To make clear the characteristics of nitrogen load fromdifferent land use, the histograms of nitrogen load fromeach land use were evaluated (shown in Fig. 5). In urban
grid cell, nitrogen load ranged very widely compare toother land use, however average nitrogen load was 15.6kg/ha/year, and it was larger than other land use. On theother hand, nitrogen load in forest was relatively small(0.84 kg/ha/year).

Observed nitrogen load (t/day)Fig. 2 Nitrogen Balance Model

Fig. 4 Obs and Cal nitrogen load at Yasothon station

Fig. 3 Observed and calculated river discharge at Yasothon station

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

Agriculture

Urban (¼1000)

grid number

ForestUrban(¼1000)Agriculture
Forestnitrogen load from each grid cell (kg/ha/year)

Fig. 5 Histograms of estimated nitrogen load from each grid cell

the impact assessment of different management strategies
for sanitation systems or farming practices.

4. CONCLUSION

In the future, climate change will accelerate thewater cycle and severe droughts often occur inNortheast Thailand. Especially in dry season,
nutrient concentration in large cities will increase
due to the shortage of available water resource
which dilute the nutrient concentration indrainage canal. And water environment in city will
be degraded. Therefore, suitable sanitation systemshould be introduced to the city which haverelatively large population density.

In this study, conceptual nitrogen balance model combinedwith TOPMODEL was developed and applied to Northeast
Thailand as the quantitative evaluation tool of the spatial
distribution of nitrogen loading from different land use.
Nash-Sutcliffe efficiency of river discharge at observed
station were more than 0.75 which model performance canbe evaluated as “good”. The correlation coefficients of
estimated average annual nitrogen-load at Yasothon station
were 0.69. By using the proposed model, spatial
distribution of annual nitrogen load was estimated andhistograms of nitrogen load from each land use was
evaluated. As a result, nitrogen load from large cities waslarge.

REFERENCES

To improve the model accuracy, further research is neededboth in field observation and model development. In
Northeast Thailand, long-term observed water quality data
is not available after 2004, however even in short-term
observation, basin wide monitoring data in tributary levelmay be helpful for more accurate parameter calibration. In
this study, we employed many assumptions to simplify thenitrogen balance model. For example, we neglected N
uptake in forest, assuming that most of forest are mature
with no net accumulation of biomass. This would bechanged for well-managed, semi-natural or disturbed
natural forest where uptake of N occurs. Because ofsparsity of data, we ignored the spatial and temporal
heterogeneity in fertilizer management within the basin(e.g. difference of N application rate and timing of
application). These problems may cause errors in thecalculation of N transformation processes. Despite all theuncertainties, our results provide a first insight in themagnitude and spatial distribution of nitrogen loading inNortheast Thailand, and this kind of model can be used in

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[1]

Ao, T., Ishihira, H. and Takeuchi K. 1999: Study of distributed
runoff simulation model based on the block type Topmodeland Muskingum-Cunge methods (in Japanese). Annual
Journal of Hydraulic Engineering, JSCE, 43, 7–12.

[2]

Beven, K.J. and Kirkby, M.J., 1979: A physically based
variable contributing area model of hydrology. Hydrological
Sciences Bulletin, 24(1), 43–69.

[3]

Hanasaki, N., Kanae, S., Oki T and K. Mushiake 2003:
Development of globally applicable reservoir operation model(in Japanese). Annual Journal of Hydraulic Engineering, JSCE,
47, 181–186.

[4]

Moriasi, D.N. , Arnold, J.G. , Van Liew, M.W. , Bingner, R.L. ,Harmel, R.D. and Veith, T.L. 2007: Model evaluation
guidelines for systematic quantification of accuracy inwatershed simulations. Transactions of the American Societyof Agricultural and Biological Engineers, vol.50(3), 885-900.

[5]Suga Y., Hirabayashi Y., Kanae S. and Oki, T., 2005: Changes
in river nitrate transport of the world resulting from increasein fertilizer use (in Japanese). Annual Journal of HydraulicEngineering, JSCE, 49(1), 495–500.

[6]

Yoshida, K. Azechi, I., Hariya, R., Tanaka, K., Noda, K., Oki,
K., Hongo, C., Honma, K. Maki, M. and H. Shirakawa, 2013;
Future Water Availability in the Asian Monsoon Region: A
Case Study in Indonesia, Journal of Developments in
Sustainable Agriculture, 8, 25-31.

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-8༳᪠἟ὶᇦ䛻䛚䛡䜛ฟỈ᫬䛾ᰤ㣴ሷ㢮⃰ᗘ䛸㻌⸴㢮ቑṪ䝫䝔䞁䝅䝱䝹䛾㛵ಀ㻌໭ᮧ㻌 ཭୍ 㻝䠈ᖹᒣ㻌 Ꮥᾈ㻌 㻝䠈ᑠᕝ㻌 ᩥ❶ 㻝㻌㻝ᅜ❧◊✲㛤Ⓨἲேᅵᮌ◊✲ᡤ㻌 Ỉ⎔ቃ◊✲䜾䝹䞊䝥㻌 Ỉ㉁䝏䞊䝮㻌䜻䞊䝽䞊䝗䠖⸴㢮ቑṪ䝫䝔䞁䝅䝱䝹䞉ᰤ㣴ሷ䞉㝆㞵᫬ὶฟ䞉༳᪠἟ὶᇦ䞉Ⅼ※ཬ䜃㠃※ởᰁ㻌ᢒ㘓㻌㛢㙐ᛶỈᇦ䛷䛾⸴㢮ቑṪ䛿Ỉ㉁ở⃮䛾୺せせᅉ䛾 㻝 䛴䛷䚸䛣䛾Ỉ㉁ở⃮పῶ䛾䛯䜑䛻䛿䚸⸴㢮ቑṪᅉᏊ䛸䛺䜛ᰤ㣴ሷ㢮㈇Ⲵ㔞䜢పῶ䛩䜛ᚲせ䛜䛒䜛䚹ฟỈ᫬䛾ᰤ㣴ሷ㈇Ⲵ㔞䛿᫂䜙䛛䛻䛺䜚䛴䛴䛒䜛䛜䚸⸴㢮ቑṪ䛸䛾㛵ಀ䛿୙᫂䛷䛒䜛䚹ฟỈ䛜⸴㢮ቑṪ䛻ᐤ୚䛩䜛䛛䛹䛖䛛䜢᫂䜙䛛䛻䛩䜛䛯䜑䚸༳᪠἟ὶධἙᕝ䛻䛚䛔䛶䚸ᅵᆅ฼⏝䛾␗䛺䜛 㻠ᆅⅬ䛷ฟỈ᫬䛻ᩘ᫬㛫㛫㝸䛷ἙᕝỈ䜢᥇Ỉ䛧䚸❅⣲䚸䝸䞁䚸㔠ᒓ⃰ᗘ䛸⸴㢮ቑṪ䝫䝔䞁䝅䝱䝹䠄 㻭㼘㼓㼍㼘㻌 㻳㼞㼛㼣㼠㼔㻌㻼㼛㼠㼑㼚㼠㼕㼍㼘䠖㻭㻳㻼䠅䜢 ᐃ䛧䚸᥇ỈᆅⅬẖ䛾ᰤ㣴ሷ㢮䛸 㻭㻳㻼 ὶฟ≉ᛶ䛾ᢕᥱ䚸㻭㻳㻼 䛸ᅵᆅ฼⏝䛚䜘䜃㔠ᒓ⃰ᗘ䛾㛵ಀ䛻䛴䛔䛶⤫ィゎᯒ䜢⾜䛳䛯䚹䛭䛾⤖ᯝ䚸㻭㻳㻼 ㈇Ⲵ㔞䛿䚸⏿䛾๭ྜ䛜ከ䛔ὶᇦ䛷䛿ฟỈ᫬䛻ቑ኱䛧䚸ᕷ⾤ᆅ䛾๭ྜ䛜ከ䛔ὶᇦ䛷䛿䚸ฟỈ᫬䛻ῶᑡ䛩䜛䛣䛸䛜䜟䛛䛳䛯䚹䜎䛯䚸㻹㼓㻞㻗䚸⁐Ꮡែ䝩䜴⣲䚸㻯㼍㻞㻗䛿䚸⸴㢮ቑṪ䛸ṇ䛾┦㛵䛜☜ㄆ䛥䜜䛯䚹㻌
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150

ᆅⅬB

㇜㣫⫱ᐦᗘ䠄㢌ᩘ㻛㼗㼙 㻞 䠅㣴໬≧ែ䛻䛒䜛䚹ㄪᰝἙᕝ䛿䚸ᅵᆅ฼⏝䛜␗䛺䜛᥇

Ỉ⏣

2500

200

䠄6.26km2䠅䛸す༳᪠἟䠄5.29km2䠅䛛䜙ᵓᡂ䛥䜜䚸ᐩᰤ┠䛧䚸≉ᚩⓗ䛺 4 ᆅⅬ䜢㑅ᐃ䛧䛯䚹ᅗ-1 䛻㧗ᓮᕝὶ

ᆅⅬB

ᆅⅬA

䛯䚹
༳᪠἟䛿༓ⴥ┴໭す㒊䛻఩⨨䛧䚸໭༳᪠἟

⏿

20
0

0

2. ᪉ἲ

᳃ᯘ

ᆅⅬB

⏝䛚䜘䜃㔠ᒓ⃰ᗘ䛾㛵ಀ䛻䛴䛔䛶⤫ィゎᯒ䜢⾜䛳

ᕷ⾤ᆅ

40

ᆅⅬB

ᰤ㣴ሷ㢮䛸 AGP 䛾ὶฟ≉ᛶ䛾ᢕᥱ䚸AGP 䛸ᅵᆅ฼

Ⲩᆅ

60

ᆅⅬA

ᐃ䛧䛯䚹᥇ỈᆅⅬẖ䛾

ᆅⅬA

Growth Potential䠖AGP䠅䜢

60

䛭䛾௚

80

ᆅⅬA

80

100

ᅵᆅ฼⏝๭ྜ䠄%䠅

❅⣲䚸䝸䞁䚸㔠ᒓ⃰ᗘ䛸⸴㢮ቑṪ䝫䝔䞁䝅䝱䝹䠄Algal㠃✚䠄km2 䠅䛺䜛 4 ᆅⅬ䛷ฟỈ᫬䛻ᩘ᫬㛫㛫㝸䛷ἙᕝỈ䜢᥇Ỉ䛧䚸

100ᅗ᥇ỈᆅⅬୖὶᇦࡢᅵᆅ฼⏝ࠊ㇜㣫⫱ࠊேཱྀᐦᗘ

1

1215

AGP㈇Ⲵ㔞(g/s)

㻝
㻜㻚㻡

ᆅⅬA
䐢
䐣
䐡
䐟䐠

ᆅⅬB

㻞㻜

ᆅⅬC

㻝

䐢 䐣

㻝㻜
䐤

䐥

䐡
䐟 䐠

䐡

䐤 䐥 㻜㻚㻡
䐟

䐢

ᆅⅬD

㻝

䐡 䐢

䐣
䐤

䐠

㻜

䐥

㻝㻜

䐣

㻜㻚㻡
䐟

䐠

䐤

㻞㻜

䐥

㻜
㻝㻞㻜

㻜
㻝㻞㻜

㻜
㻝㻞㻜

㻜
㻝㻞㻜

㻢㻜

㻢㻜

㻢㻜

㻢㻜

㻜
㻝㻡

㻜
㻝㻡

㻜
㻝㻡

㻜
㻝㻡

㻟㻜
㻜

㻝㻜

㻝㻜

㻝㻜

㻝㻜

㻝㻜

㻡

㻡

㻡

㻡

㻞㻜

㻜
㻜㻚㻟

㻜
㻜㻚㻟

㻜
㻜㻚㻟

㻜
㻜㻚㻟

㻟㻜
㻜

㻜㻚㻞

㻜㻚㻞

㻜㻚㻞

㻜㻚㻞

㻝㻜

㻜㻚㻝

㻜㻚㻝

㻜㻚㻝

㻜㻚㻝

㻞㻜

㻜
㻟㻜

㻜
㻝㻜㻜㻜
㻤㻜㻜
㻢㻜㻜
㻠㻜㻜
㻞㻜㻜
㻜

㻞㻜
㻝㻜
㻜

1/8
1/9
14᫬ 22᫬ 6᫬ 14᫬

㻟㻜
㻜
㻝㻜
㻞㻜

㻜
㻟㻜
㻜
㻝㻜
㻝㻜
㻤
㻤
㻢
㻢
㻠
㻠
㻞
㻞
㻜
㻜
1/8
1/9
1/8
1/9
1/8
1/9
14᫬ 22᫬ 6᫬ 14᫬ 14᫬ 22᫬ 6᫬ 14᫬ 14᫬ 22᫬ 6᫬ 14᫬㝆Ỉ㔞䠄mm/h䠅 㝆Ỉ㔞䠄mm/h䠅 㝆Ỉ㔞䠄mm/䡄䠅 㝆Ỉ㔞䠄mm/h䠅

PO4 -P䠄mgP/L䠅

NO3 -N䠄mgN/L)

AGP(mg/L)ὶ㔞䠄m3 /s䠅

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018ͤࣄࢫࢺࢢ࣒ࣛࡣ᫬㛫㝆Ỉ㔞ࠊὶ㔞ࡢᅗ୰ࡢձ~շࡣ 1/8~1/9 㛫ࡢ᥇Ỉ㏻ࡋ␒ྕ
ᅗ-3 ฟỈ᫬ࡢ㝆Ỉ㔞ࠊἙᕝὶ㔞ࠊAGPࠊNO3-NࠊPO4-P ⃰ᗘ࠾ࡼࡧ AGP ㈇Ⲵ㔞ᇦ䛾᥇ỈᆅⅬ䜢♧䛧䛯䚹ᅗ-2 䛻䛿ྛ᥇ỈᆅⅬ䜘䜚ୖὶ

1ᇦ䛾ᅵᆅ฼⏝➼䛾๭ྜ䜢♧䛧䛯䚹᥇ỈᆅⅬ A 䛿䚸㧗ᓮ䐠ᕝୖὶᇦ䛷⏿䛜 70䠂䜢༨䜑䚸㇜㣫⫱ᐦᗘ䛜㧗䛔䚹ᆅỈ⏣Ⅼ B 䛿ᆅⅬ A䚸C 䛾ୗὶ䛷ὶᇦ㠃✚䛜኱䛝䛟䚸⏿䛸᳃ᯘ➨஧୺ᡂศ 㻼㻯㻞㻌㻔㻟㻜㻚㻟㻑㻕䛜䚸ᕤሙ⏝ᆅ䛾๭ྜ䛜㧗䛟ேཱྀᐦᗘ䛿ప䛔䚹ᆅⅬ D 䛿㒔ᕷỈ㊰䛷ᕷ⾤ᆅ䛾๭ྜ䛜 53%䜢༨䜑䚸ேཱྀᐦᗘ䛜㧗䛔䚹ᆅⅬ C䚸D 䛾㇜㣫⫱ᐦᗘ䛿ప䛔䚹᥇Ỉ᪥䛿 H26 ᖺ 1 ᭶ 8䡚9 ᪥䛾㝆㞵᫬䛷䚸బ಴ほ䝕䞊䝍䛷䛿䚸⣼✚㝆㞵㔞䛿 24.5mm䚸㝆㞵䛾䝢䞊䜽䛿 1 ᭶ 8 ᪥ 23 ᫬㡭䛷䛒䛳䛯䚹ฟỈ᫬䛾ἙᕝỈ䛿㝆㞵㛤ጞ᫬䜢ྵ䜑 2䡚5 ᫬㛫㛫㝸䛷 7 ᅇ᥇Ỉ䛧䛯䚹ἙᕝỈ䛾Ỉ㉁ศᯒ㡯┠䛿䚸 SS䚸VSS䚸T-N 䚸T-P 䚸

AGP⃰ᗘ

䐤

䐡
䐢

-1

䐢

⏿
䐠
䐥 䐡
䐟
䐣
㇜㣫⫱䐤䐥
ᐦᗘ

PO4-P⃰ᗘ

0.2

ᕷ⾤ᆅ

0

䐟

-0.8 -0.6 -0.4 -0.2 0
-0.2

䐡
䐢 䐣

NO3-N⃰ᗘ0.4

䐣 -0.4
-0.6
-0.8

0.2

0.4

0.6

ேཱྀᐦᗘ
䐠

0.8

䐟
䐤

䐥

-1

➨୍୺ᡂศ 㻼㻯㻝㻌㻔㻡㻣㻚㻢㻑㻕

NH4-N䚸NO2-N䚸NO3-N䚸PO4-P䚸DOC䚸Na+ 䚸K+ 䚸Mg2+ 䚸ᅗ-4 ᅵᆅ฼⏝࡜ AGP ࡜୺ᡂศศᯒࡢ⤖ᯝCa2+䚸Cl- 䚸SO42-䚸Fe䚸Al䚸Mn䚸Zn䚸Cu䚸B䚸Mo䚸Ni䚸Co䚸

1216

ᅵᆅ฼⏝

0.8
0.6

䛷 65䠂䜢༨䜑䜛䚹ᆅⅬ C 䛿ᕷ⾤ᆅ䛾๭ྜ䛜 35䠂䛷䛒䜛

ᡤ䛾㞵㔞ほ

᳃ᯘ

2

1

D-Zn

D-Mo

D-Al

D-Fe

D-Se

D-Cu

D-Mn

SS

VSS

NH4-N

DOC

Cl -

Na+

K+

D-Co

D-Ni

D-TN

NO3-N

NO2-N

PO4-P

D-TP

SO42+

Ca2+

D-B

1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1

Mg2+

AGP䛸ྛỈ㉁ศᯒ್䛸䛾┦㛵ಀᩘ

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018ͤᅗ୰ࡢ D-㸸⁐Ꮡែࡢ␎
ᅗ-5 AGP ࡜ྛỈ㉁㡯┠࡜ࡢ┦㛵ಀᩘ
Se 䛷䛒䜚䚸㔠ᒓ䛿⸴㢮ቑṪ䛾ᚲ㡲ඖ⣲䜢୰ᚰ䛻㑅ᐃ䛧

NO3-N ࡣࠊฟỈᮇ㛫୰ࠊ⏿ࠊ㇜㣫⫱ᐦᗘ࡜㏆࠸఩⨨䛯䚹࡟ࣉࣟࢵࢺࡉࢀࠊPO4-P ฟỈ๓ࡣᕷ⾤ᆅ࡟ࠊฟỈ᫬

AGP ヨ㦂 2)䛿ḟ䛾䛸䛚䜚⾜䛳䛯䚹4 䜹ᡤ䛾ᆅⅬ䛷ᩘ᫬㛫㛫㝸䛷᥇Ỉ䛧䛯඲䛶䛾ヨᩱ䜢ࡣ⏿ࡢ㏆ࡃ࡟ࣉࣟࢵࢺࡉࢀࡓࠋ

ᐃᑐ㇟䛸䛧䚸Ꮝᚄ

3.3 ⸴㢮ቑṪᅉᏊ䛾ゎᯒ⤖ᯝ

0.45䃛m 䛾䝯䞁䝤䝺䞁䝣䜱䝹䝍䞊䛷䜝㐣䛧䚸䜝㐣ヨᩱ䜢

ᅗ-5 䛿䚸඲

300ml ᐜ୕ゅ䝣䝷䝇䝁䛻 100mL ྲྀ䜚䚸⥳⸴䛷䛒䜛䝮䝺䝭㉁䜹䝓䜻䝰䜢᳜✀䛧䛶 16 ᪥㛫ᇵ㣴䛧䚸⸴㢮ቑṪ㔞䜢஝⇱ᐃヨᩱ䜢⏝䛔䛶 AGP 䛸⁐Ꮡែ䛾ྛỈᐃ㡯┠䜢༢┦㛵ゎᯒ䛧䛯䛸䛝䛾┦㛵ಀᩘ䛷䛒䜛䚹❅⣲䚸䝸䞁䛜⸴㢮ቑṪᅉᏊ䛷䛒䜛䛣䛸䛿▱䜙䜜䛶䛔䜛䛜䚸㔜㔞䠄mg/L䠅䛸䛧䛶ồ䜑䛯䚹䛣䛾௚䛻䜒 AGP 䛸ṇ䛾┦㛵䜢♧䛩䜒䛾䛜䛒䛳䛯䚹AGP 䛸

3. ⤖ᯝ
3.1 ฟỈ᫬䛾 AGP 䛸ᰤ㣴ሷ⃰ᗘ䛾ኚ໬㧗䛔ṇ䛾┦㛵䠄r=0.6 ௨ୖ䠅䜢♧䛧䛯㡯┠䛿䚸Mg2+䚸⁐Ꮡែ-B䠄䝩䜴⣲䠅䚸Ca2+ 䛷䛒䜚䚸䛣䛖䛧䛯㔠ᒓ㢮䜒⸴㢮ቑ

ᅗ-3 䛻బ಴ほ ᡤ䛷䛾㝆Ỉ㔞䚸ྛ᥇ỈᆅⅬ䛾Ἑᕝὶ㔞䚸AGP䚸NO3-N䚸PO4-P 䛚䜘䜃 AGP ㈇Ⲵ㔞䠄⃰ᗘ㽢ὶ㔞䠅䜢♧䛧䛯䚹AGP 䛿䚸ᆅⅬ A 䛷䛿ฟỈᮇ㛫୰䛻኱䛝䛟ቑຍ䛩䜛䛣䛸䛿䛺䛛䛳䛯䚹ୗὶ䛾ᆅⅬ B 䛷䛿䚸ὶ㔞䝢䞊䜽๓䛻ቑຍ䛧䚸ὶ㔞䝢䞊䜽௨㝆䛻ῶᑡ䛧䛯䚹ᆅⅬ C䚸
D 䛿䚸ฟỈ๓䛻㧗䛟䚸ฟỈ᫬䛿ప䛟䛺䛳䛶䛔䛯䚹NO3-N⃰ᗘ䛿䚸ᆅⅬ A 䛷ฟỈ๓䛜᭱䜒㧗䛟䚸ฟỈ᫬䛿ᕼ㔘䛥䜜䛯䚹௚䛾ᆅⅬ䛷䜒ྠᵝ䛾ഴྥ䜢♧䛧䛯䚹PO4-P ⃰ᗘ䛿䚸
ᆅⅬ D 䛷ฟỈ๓䛜㧗䛟䚸ฟỈ᫬䛿పୗ䛩䜛ഴྥ䛸䛺䛳䛯䚹ฟỈ᫬䛾 AGP 䛾ኚ໬䛿ᅵᆅ฼⏝䛻䜘䛳䛶␗䛺䜛䛣䛸䛜☜ㄆ䛥䜜䛯䚹AGP ㈇Ⲵ㔞䛿䚸A䚸B ᆅⅬ䛷䛿ฟỈ᫬䛻ቑ኱䛧䚸C䚸D ᆅⅬ䛷䛿ฟỈ᫬䛻ῶᑡ䛧䛶䛔䛯䚹Ṫ䛻ᐤ୚䛧䛶䛔䜛ྍ⬟ᛶ䛜䛒䛳䛯䚹4. ⤖ㄽฟỈ᫬䛾ᰤ㣴ሷ㢮㈇Ⲵ㔞䚸ฟỈ䛾⸴㢮ቑṪ䜈䛾ᐤ୚䚸⸴㢮ቑṪ䛸㔠ᒓ䛾㛵ಀホ౯䜢┠ⓗ䛸䛧䛶䚸༳᪠἟ὶᇦ䛻䛚䛔䛶ฟỈ᫬䛾ᰤ㣴ሷ㢮䛸 AGP 䛾ὶฟ≉ᛶ䛾ㄪᰝ䜢⾜䛳䛯䚹AGP 䛸ᅵᆅ฼⏝䛚䜘䜃㔠ᒓ⃰ᗘ䛾㛵ಀ䛻䛴䛔䛶䛿୺ᡂศศᯒ䚸༢┦㛵ゎᯒ䛛䜙ホ౯䛧䛯䚹ᮏ◊✲䛷ᚓ䜙䜜䛯୺䛺▱ぢ䜢௨ୗ䛻♧䛩(1)㻌 ฟỈ᫬䛾 AGP ㈇Ⲵ㔞ゎᯒ䛾⤖ᯝ䚸AGP ㈇Ⲵ㔞䛿䚸⏿䛾๭ྜ䛜ከ䛔ὶᇦ䛷䛿ฟỈ᫬䛻ቑ኱䛧䚸ᕷ⾤

3.2 ୺ᡂศศᯒ࡟ࡼࡿᅵᆅ฼⏝࡜ AGP ࡢ㛵ಀᆅ䛾๭ྜ䛜ከ䛔ὶᇦ䛷䛿ฟỈ᫬䛻ῶᑡ䛩䜛䛣䛸䛜ᅵᆅ฼⏝䛸ฟỈ᫬䛾 AGP 䛾ኚ໬䛻䛴䛔䛶඲యീ䜢ᢕᥱ䛩䜛䛯䜑䚸୺ᡂศศᯒ䜢⾜䛳䛯䚹ᅗ-4 䛻䚸➨୍䚸➨஧୺ᡂศ䛻䛴䛔䛶ྛᅵᆅ฼⏝㡯┠䛾୺ᡂศ㈇Ⲵ㔞䝥䝻䝑䝖䜢♧䛩䚹➨୍୺ᡂศ䠄PC1䠅䛿䚸ᕷ⾤ᆅ䚸ேཱྀᐦᗘ䛜䠇᪉ྥ䛻䚸᳃ᯘ䚸⏿䛾๭ྜ䛜䠉᪉ྥ䛻ศᕸ䛧䛯䛣䛸䛛䜙䚸㞟Ỉᇦ䛾㒔ᕷ໬䛻㛵㐃䛩䜛ᡂศ䚸➨஧୺ᡂศ䛿䚸᳃ᯘ䚸Ỉ⏣䛜䠇᪉ྥ䛻䚸⏿䛾๭ྜ䛚䜘䜃㇜㣫⫱ᐦᗘ䛜䠉᪉ྥ䛻ศᕸ䛧䛯䛣䛸䛛䜙䚸⏿䛾๭ྜ䛸㇜㣫⫱ᐦᗘ䛻㛵㐃䛩䜛ᡂศ䛷䛒䜛䛸⪃䛘䜙䜜䜛䚹ḟ䛻䚸➨୍䚸➨஧୺ᡂศ䛻䛴䛔䛶䚸AGP䚸NO3-N䚸PO4-P 䛾୺ᡂศ㈇Ⲵ㔞䜢᥇Ỉ᫬㛫ẖ䛻⟬ฟ䛧䚸ᅗ-4 䛻㔜䛽䛶䝥䝻䝑䝖䛧䛯䚹
AGP 䛿䚸ฟỈ๓䛿䚸ᕷ⾤ᆅ䜔ேཱྀᐦᗘ䛻㏆䛔఩⨨䛻䝥䝻䝑䝖䛥䜜䚸ฟỈ᫬䛿᳃ᯘ䜔⏿䛾᪉ྥ䛻䝥䝻䝑䝖䛜⛣ື䛧䛯䚹䛣䛾ゎᯒ䛛䜙䜒 AGP 䛿䚸ฟỈ๓䛿ᕷ⾤ᆅ䚸ฟỈ᫬䛿⏿䜔᳃ᯘ䛾ᙳ㡪䜢ཷ䛡䜛䛣䛸䛜䜟䛛䛳䛯䚹䜟䛛䛳䛯䚹(2)㻌 ୺ᡂศศᯒ䛛䜙 AGP 䛸ᅵᆅ฼⏝䛾㛵ಀ䜢ゎᯒ䛧䛯⤖ᯝ䚸AGP 䛿䚸ฟỈ๓䛿ᕷ⾤ᆅ䚸ฟỈ᫬䛿⏿䜔᳃ᯘ䛾ᐤ୚䜢ཷ䛡䜛䛣䛸䛜䜟䛳䛯䚹(3)㻌 AGP 䛸ྛỈ㉁㡯┠䛾༢┦㛵ゎᯒ䛛䜙䚸⸴㢮ቑṪ䛻䛿䚸❅⣲䚸䝸䞁䛾௚䛻 Mg2+䚸⁐Ꮡែ-B䚸Ca2+䛜ᐤ୚䛧䛶䛔䜛ྍ⬟ᛶ䛜䛒䛳䛯䚹
ᘬ⏝ᩥ⊩

3

[1]

ᒸᮏ ௚㸸ὶᇦࢫࢣ࣮࡛ࣝぢࡓ≀㉁ືែ≉ᛶࡢᢕᥱ࡟㛵ࡍࡿ◊✲(2)ࠊ
ᖹᡂ 27 ᖺᗘୗỈ㐨㛵ಀㄪᰝᖺḟሗ࿌᭩㞟ࠊ
pp.123㹼172ࠊᅵᮌ◊✲ᡤ㈨ᩱ ➨ 4347ࠊ2017[2]᪥ᮏୗỈ㐨༠఍:ୗỈヨ㦂᪉ἲࠊpp.380㹼387ࠊ20121217

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-9

Biochemical Potential of Freshwater, Brackish, and Sea Sediments for
Removing Antimony from Water Environment
Satoshi Soda and Keina Oka
College of Science and Engineering, Ritsumeikan University
Keywords: antimony, bacteria, Lake Biwa, brackish lake
ABSTRACT

Biochemical potential of sediment samples for removing antimony from water phase was evaluated. The
sediment samples collected from Lake Biwa North and South Basins, Asoumi Sea (a brackish inland sea),
and Wakasa Bay were suspended in 20 mL solution containing 100 mg-Sb/L as K[Sb(OH)6] underanaerobic condition at 28oC for 3 weeks. The sediment samples of Lake Biwa showed biochemical
potentials for removing Sb from water phase by formation of orange precipitation (Sb2S3) although the Sb
removal was low (10-30%). The sediment samples of Asoumi Sea and Wakasa Bay showed highbiochemical potentials of Sb removal (80-90%) by formation of white precipitation (Sb2(OH)3). Bacterialcolonies with antimonate-reducing and Sb2S3-accumulating abilities were obtained from the sediment
samples of Lake Biwa and Asoumi Sea. Bacteria with the biochemical potential for soluble Sb removal
would be ubiquitously distributed in lakes and seas in Japan.
1. INTRODUCTION

shown in Table 1. The sediment samples were collectedfrom Lake Biwa North Basin near Chikubushima island,South Basin off the coast of Ogoto, Asoumi Sea which isa brackish inland sea, and Wakasa Bay in 2017.

Various natural, agricultural, and industrial processes cancause antimony contamination of surface waters. In Japan,
the effluent standard for antimony has not been established
yet in the Water Pollution Control Law, but antimony has
been selected as a monitoring-required water quality
parameter of Environmental Quality Standards for Water
Pollution. Actually, there have been reported that the Sb
concentration in river downstream of some factories
exceeds the guideline value (>= 0.02 mg/L).

2.2 The antimony removing test
A basal salt medium containing 100 mg-Sb/L
K[Sb(OH)₆], 2mM lactate as the sole carbon source,
20mM HEPES, 0.1 g/L KH2PO4, 0.1g/L K2HPO4, 0.48g/L
NH4Cl, 0.2g/L NaCl, 1.2mg/L H3BO3, 0.34mg/L CoCl2・
6H₂O, 0.18mg/L CuCl2・2H₂O, 0.2mg/L MnCl2・4H₂O,
0.44mg/L ZnCl2, 0.4g/L CaCl2, and 0.48 g/L (HS-BSM) or
0.048 g/L MgSO₄・7H₂O (LS-BSM) was used for the
antimony removing test (pH 7.2). For brackish and sea
sediment, 26 g/L NaCl was added to the media (pH 7.6).

However, removal processes for antimony from waterphase have not been fully established. An alternative forcost effective antimony removal might be biologicaltreatment using antimonate-reducing bacteria. Figure 1
shows a hypothetical mechanism of the Sb removal fromwater phase. Bacterial reduction of antimonate into
antimonite, resulting in formation of diantimony trioxide(Sb2O3) and stibnite (Sb2S3), is known to play an importantrole in detoxification of soluble antimony in the naturalenvironment[1-3]. Sb2O3 (Sb2(OH)3) and Sb2S3 are easily
removed from the aqueous phase because of its insoluble
characteristics.

Portions of the sediment sample (4mg wet weight) were
inoculated into 20 mL of HS-BSM or LS-BSM in 50-mL
serum bottles. Headspace of the bottles were replaced with
N2 gas for creating anaerobic condition. The bottles weresealed with rubber stoppers and capped with aluminum
crimp seals and incubated on a rotary shaker (100rpm) at
28°C. After 4weeks 1 mL of each culture was transferredto the fresh medium.
2.3 Analytical procedures

However, little is known about antimony-removing
bacteria in water environment in Japan. In this study, thebiochemical potential of lake and sea sediments forremoving antimony was evaluated.

Water samples (1 mL) were periodically collected from thebottles and centrifuged (21,900×g, 10 min) for removing
the cells and precipitates. The Sb concentration in thewater samples was determined by inductively coupledplasma optical emission spectrometry (ICP-OES Agilent
700 Series, Agilent Technologies, Inc.).

2. METHODS
2.1 Sediment samples

Bacteria were enumerated by the poured plate methodwith the LS-BSM and the HS-BSM with 15 g/L agar. The

Characteristics of sediment samples used in this study are

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

Electron acceptor
Sb(V)Electron donor
eOrganic
Antimonate
matterreducers
CO2
GrowthSO42-

Sb(III)
Precipitation

HSSb2O3, Sb(OH)3 ↓ Sb2S3↓
White

Organic matter
Sulfatereducers
CO2

OrangeFig.1 A hypothetical mechanism of biochemical removal of antimony from water phase.

Table 1. Sediment samples used in the antimony removing test
Sampling
Air /Water temp.
place
date
Lake Biwa North Basin (near2017/10/1 19℃/8℃
Chikubu island, Shiga Pref.)Lake Biwa South Basin (off the
2017/10/1 19℃/24℃
coast of Ogoto, Otsu, Shiga Pref.)Asoumi Sea (Miyazu, Kyoto
2017/9/19 20℃/22℃
Pref.)
Wakasa Bay (Matsubara beach,2017/9/7
25℃/25℃
Fukui Pref.)

120
110
100
90
80
70
60
50
40
30
20
10
0

Note

70m

ORP -270mV, grey, silty

4m

ORP -156mV, dark green,
silty, sandy, rotten-egg smell
ORP -420mV, black, rottenegg smell
Sandy, aerobic

10.5m
0.5m

(B)

Soluble Sb (mg/L)

Soluble Sb (mg/L)

(A)

Depth

0

10

20

30

40

50

60

Time (day)

70

80

90

100

120
110
100
90
80
70
60
50
40
30
20
10
0

0

10

20

30

40

50

60

Time (day)

70

80

90

100

Fig.2 Time courses of soluble antimony concentrations in the microbial cultures derived from sediment samples.
Cultures were enriched HS-BSM (A) and LS-BSM(B). Sediment samples were collected from Lake Biwa North Basin (open
diamonds), South Basin (closed squares), Asoumi Sea (closed triangles), and Wakasa Bay (open circles). Arrows indicate thetransfer of the culture into new medium.

from the HS-BSM within 1 week in the first test. Although
the Sb removal was low, the sediment samples of Lake
Biwa North Basin in the HS-BSM and of South Basin in
the LS-BSM and the HS-BSM formed specific orange
precipitation, indicating Sb2S3, as shown in Fig. 1.
Although the Sb removal did not increased, similar results
were obtained in the second and third tests.

plates were incubated in an anaerobic box (anaeropack
kenki, Sugiyama-gen, Co. Ltd.) at 25oC for 2weeks.
3. RESULTS AND DISCUSSION
3.1 Biochemical removal of Sb by sediment samples
Time courses of removal of soluble antimony by the
sediment samples are shown in Fig. 2. The sediment
sample of Lake Biwa South Basin removed 20% antimony

2

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

Table 2. Summary of the biochemical potential of the sediment samples for antimony removal
Sediment sample
Lake Biwa
Lake Biwa
Asoumi Sea
Asoumi Sea
Wakasa Bay
MediumNorth Basin
South Basin
HS-BSM
LS-BSM
HS-BSM
HS-BSM
HS-BSM
Precipitates’ color
OrangeOrangeWhite
OrangeWhite
Sb removal
1st: 0%
1st: 20%
1st: 90%
1st: 90%
1st: 90%
2nd: 50%
2nd: 10%
2nd: 85%
2nd: 80%
2nd: 90%
3rd: 30%
3rd: 30%
3rd: 85%
3rd: 80%
3rd: 85%4
3
3
3
Viable counts after
1.1×101.1×10
1.8×10
3.7×10<1.0×101rdthe 3 removal test
CFU/mL
CFU/mL
CFU/mL
CFU/mL
CFU/mL
Colonies on the
Yellowish
Yellow colonies
White colonies Yellow on wholeagar platesorange colonies
agar
3.2 Bacteria in the cultures derived from sediment
samples$

The sediment samples of Asoumi Sea and Wakasa Bay
showed high antimony removals of 80-90% from the LSBSM and the HS-BSM in the tests. The sediment samplesof Asoumi Sea formed orange precipitation in the LS-BSM.
However, the other sea sediment samples showed white
precipitation, indicating Sb₂(OH)₃, as shown in Fig. 1. The
sediment sample of Wakasa Bay in the HS-BSM formed
orange precipitate in the second test and white
precipitation in the third test, suggesting co-existence of
Sb2S3 forming bacteria and Sb2(OH) 3 forming bacteria.

%(&'LOXWLRQ 







Fig.3 Colonies in the microbial cultures derived fromsediment samples. Cultures were enriched from Lake
Biwa North Basin in HS-BSM (A), Lake Biwa South Basinin HS-BSM (B), Asoumi Sea in LS-BSM (C), Asoumi Sea
in HS-BSM (D), and Wakasa Bay in HS-BSM (E).

3.3 Bacteria related to Sb removal
Figures 3 shows colonies obtained from the bacterial
cultures. Yellowish-orange colonies of 103-104 CFU/mL
were formed on the HS-BSM from the bacterial culturesderived from the sediment samples of Lake Biwa.
Yellowish-orange colonies and white colonies wererespectively formed on the LS-BSM and the HS-BSM
from the bacterial culture derived from the sediment
sample of Asoumi Sea. Those bacterial colonies did notshow yellowish-orange under aerobic condition or on the
BSM excluding Sb under anaerobic condition. These
results suggests that bacteria forming yellowish-orange
colonies have antimonate-reducing and Sb2S3accumulating abilities.

would be widely distributed in lakes and seas in Japan.
ACKNOWLEDGEMENT
This study was supported by JSPS KEKENHI Grant Number
15K12230.

REFERENCES

4. CONCLUSION
The biochemical potential of the sediment samples for
antimony is summarized in Table 2. The freshwater
sediments of Lake Biwa showed biochemical potentials
for removing soluble antimony by formation of orange
precipitation (Sb2S3). The brackish sediment sample ofAsoumi Sea and the sea sediment sample of Wakasa Bay
showed high biochemical potentials for removing soluble
antimony by formation of white precipitation (Sb2(OH)3).
Bacteria with the biochemical potential for the Sb removal

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3

[1]

Abin, A.C. and Hollibaugh, T.J.: Dissimilatory antimonite
reduction and production of antimony trioxide microcrystals
by a novel microorganism. Environmental Science andTechnology, Vol. 48, pp. 681-688, 2014.

[2]

Nguyen, V. K. and Lee, U. J.: Isolation and characterization of
antimony-reducing bacteria from sediments collected in theVicinity of an antimony factory. Geomicrobiology Journal, Vol.
31, pp. 855-861, 2014.

[3]

Wanga, H., Chen, F., Mu, S., Zhang, D., Pan, X., Lee, J.D., andChang, S.J.: Removal of antimony (Sb(V)) from Sb minedrainage: Biological sulfate reduction and sulfide oxidationprecipitation. Bioresource Technology, Vol. 146, pp. 799-802.

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018P5-10

平成 27 年 9 月関東・東北豪雨の影響を受けた土壌の無機元素組
成および細菌群集構造解析
齋藤明葉 1，坂上伸生 1，成澤才彦 1，伊藤哲司 2，西澤智康 1
1

茨城大学農学部，2 茨城大学人文社会科学部

キーワード：河川氾濫，細菌群集構造，重金属汚染，常総市，流域管理
抄録
平成 27 年 9 月関東・東北豪雨により，常総市では鬼怒川で破堤・溢水が発生し，大量の土砂水が周辺地域の土壌生態系に流れ込んだ。豪雨災害によって引き起こされる被害は，住居や産業施設，農業資産などに留まらず，土壌生態系にも大きな影響をおよぼす。本研究では，関東・東北豪雨による浸水の影響を受けた土壌生態系に関する環境情報を収集・提供すること目的として，常総市における浸水地域土壌の化学性分析および土壌細菌群集構造の解析を行った。洪水堆積物の影響を受けた土壌の無機元素組成や希釈平板法による生細菌数の調査および土壌細菌群集構造の T-RFLP 解析を行った結果，氾濫により砂が堆積することで生じる土壌の理化学性の変化と同時に，土壌微生物性へも影響がおよんでいることが示唆された。土壌生態系に関わる総合的な情報を蓄積していくことで，浸水被害を受けた農耕地の機能回復に資する付加情報となることが期待される。

1. はじめにを採取した。また，2017 年 9 月に市北部の溢水箇所付

2015 年 9 月 7 日に発生した台風 18 号は，関東地方

近から市中部にかけて，自然堤防（u1）および浸水した

関東北部から東北地方南部を中心に豪雨をもたらし，9

水田や家庭菜園の土壌（U1～U5）を採取した（図 1）。採

月 7 日から 11 日までの総雨量は関東地方で 600mm，

取した土壌は pH(H2O)，含水率および全炭素・全窒素

東北地方で 500mm を超えた。このうち，9 月 9 日から 11

含量を測定した。また，加圧整形ディスクを作成し，エネ

日にかけて発生した豪雨は各地で河川氾濫を発生させ，ルギー分散型蛍光 X 線元素分析装置により元素組成の気象庁により「平成 27 年 9 月関東・東北豪雨」と命名さ

半定量分析を行った。

れた [1]。この豪雨により常総市では，鬼怒川で破堤・溢

微生物分析については，細菌群集構造を把握するた水が発生し，大量の土砂水が周辺地域の土壌生態系にめ，希釈平板法による生細菌数の調査および土壌細菌

流れ込んだ。これを受け，茨城大学では常総市におけ群集構造の T-RFLP 解析[2]を行った。

る大規模な水害に際し，支援協働研究を行う「茨城大学
平成 27 年関東・東北豪雨調査団」を結成し，これまでに調査を行ってきた。
豪雨災害によって引き起こされる被害は，住居や産業
施設，農業資産などに留まらず，土壌生態系にも大きな影響をおよぼす。本研究では，関東・東北豪雨による浸水の影響を受けた土壌生態系に関する環境情報を収集・提供すること目的として，常総市における浸水地域
土壌の化学性分析および土壌細菌群集構造の解析を
行った。
2. 方法
2016 年 11 月に市南部の介護施設内の家庭菜園土壌（浸水した D1，D2 および浸水しなかった微高地の d1）および浸水区域外の雑木林（d2）から表層土壌（0～5cm）

図 1 土壌採取地点および浸水被害範囲

1

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17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

3. 結果および考察
溢水箇所付近で採取した土壌（U1，U2，u1）は含水率，全炭素量および全窒素量が低く，既往研究[3]と同様に，粘土や有機物の含有量が非常に少なく，砂質の土壌が分布していた。
生細菌数は土壌中の水分量と比例関係にあるとされている[4]。生細菌数と含水率のグラフからは含水率が低いとき，生細菌数が減少する傾向見られた。細菌は団粒内部，すなわち，より小さい孔隙内に豊富に存在していると考えられる。土壌 pH が中性を示した U1，U2，および u1 は，新規に堆積した砂質土壌で構成されているため，生細菌数が低かったと推察される。
T-RFLP プロファイルに基づくクラスター解析（図 2）から，浸水土壌（U4，D1，D2，D3）と非浸水土壌（d1，d2）

図 3 T-RFLP プロファイリングに基づく正準対応分析の間で類似性が高かったが，土壌 U1，U2，U3，U5，u1とは類似性は低かった。細菌群集プロファイルに基づく

4. 結論

多変量解析法の CCA 解析（図 3）では，細菌群集の差2015 年 9 月の豪雨により常総市では鬼怒川の堤防の異は，主に含水率および pH による影響によるものであ

一部が破堤・溢水し，大量の土砂水が周辺地域の土壌ることが示され，また，含水率および土壌 pH が生菌数に生態系に流れ込んだ。浸水の影響を受けた土壌生態系

影響を及ぼしており，河川の氾濫により堆積した砂は土の化学性および生物性に関する環境情報を収集した結壌細菌群集構造にも影響を及ぼすことが示唆された。

果，氾濫により砂が堆積することで生じる土壌の理化学性の変化と同時に，土壌微生物性へも影響がおよんでいることが示唆された。土壌生態系に関わる総合的な情報を蓄積していくことで，浸水被害を受けた農耕地の機能回復に資する付加情報となることが期待される。
引用文献
[1]

気象庁: 平成 27 年 9 月関東・東北豪雨及び平成 27 年台
風 18 号による大雨等, 災害時自然現象報告書, 2015 年第1 号, 2015.

[2]

西澤智康・小松崎将一・金子信博・太田寛行, 末端制限断片（T-RFs）プロファイル情報に基づく土壌微生物群
集構造解析, 土と微生物, 64, 33-40, 2010.
[3] Matsumoto D, Sawai Y, Yamada M, Namegaya Y et al.:Erosion and sedimentation during the September 2015
flooding of the Kinu River, central Japan., Scientific Reports,
6, 1-10, 2016.

図 2 T-RFLP プロファイリングに基づく階層クラスター解析

[4]

1222

2

古坂澄石・服部勉・佐藤匡・都留信也ほか: 土の微生物, 1978

17th World Lake Conference, Lake Kasumigaura, Ibaraki, Japan, 2018

P5-12

駒止湿原開墾跡地におけるブナ生育に関わる共生菌類の探索と植樹試験への利用
猪瀬有美 1，高島勇介 1，郭 永 1，坂上伸生 1，西澤智康 1，渡邊眞紀子 2，成澤才彦 1
1

茨城大学農学部，2 首都大学東京都市環境学部

キーワード：耕作放棄地，湿原管理，植生回復，土壌再生，ブナ林
抄録
駒止湿原では，2000 年よりブナ稚樹の植樹が試みられてきたが，一部地域では生育が不良で植生回復に至っていない。本研究では，ブナ二次林および開墾跡地に生育するブナの共生菌類を調査し，生育促進に関わる外生菌根菌あるいは内生菌類を選抜し，ブナ稚樹への接種および植樹試験をおこなった。ブナ林から開墾跡地に掛けて調査区を設置して土壌コアおよびブナ実生を採取し，菌根形態型を調査したところ，菌根チップ総数および出現形態型数は，ブナ林区から開墾跡地にかけて減少する傾向にあった。次に，ブナ実生根部より根部内生菌を調査して選抜した 2 菌株を用いて，ブナ稚樹に接種して植樹試験をおこなった。今後，本研究で選抜した菌類による影響の調査を継続するとともに，同菌種を用いた実験室内での接種試験も行い，菌根菌-内生菌-宿主植物の相互関係を明らかにしていく。

1. はじめに調査区内外の放棄地区，境界区およびブナ林区から駒止湿原は福島県南会津町および昭和村の境界付

土壌コアおよびブナ実生を採集した。土壌コアについて近に位置しており，戦後の農地開墾により失われたブナは，コア内に含まれる菌根チップ数を計数し，含まれる林を回復させるため，2000 年よりブナ稚樹の植樹が試

形態型の割合を求めた．ブナ実生については，グリッド

みられてきた[1]。植樹されたブナは，一部地域では良好

シート法により菌根形成率を求めた。形態型別に形成率な生育を見せているものの，生育が不良で植生回復にを算出し，形態型に基づく外生菌根菌群集構造の類似

至っていない場所も認められる。本研究では，ブナの生性 を 比 較 し た 。 そ の 後 ， Cetyltrimethylammonium

育において重要な役割を担う外生菌根菌に着目してブ

bromide（CTAB）法により菌根チップから DNA を抽出し，ナ二次林および開墾跡地に生育するブナの共生菌類を菌根形成菌種の同定を行った。

調査し，ブナの生存・生育の促進に関わる外生菌根菌

次に，ブナ実生根部において形成頻度が高いまたはあるいは内生菌類を選抜し，ブナ稚樹への接種および低い形態型を基準に選抜した菌根片および非菌根（計植樹試験をおこなった。

156 片）を用いて，洗浄法および表面殺菌を行い，根部

2. 方法

内生菌の分離を行った。得られた分離菌株の培養菌糸2016 年 8 月にブナ林から開墾跡地に掛けて幅 10 m，から DNA を抽出し，菌種を同定した。以上の結果から，

長さ 30 m の調査区を設置した（図 1）。優占する植物種

調査地域においてブナと密接な関係にあると推察されるを考慮し，それぞれ 10 m×10 m のブナ林区、境界区お菌類 2 種を選抜して液体培養をおこない，樹高 30～50

よび開墾跡地として区分した。

cm 程度のブナ稚樹の根部に接種し，開墾跡地において植樹試験をおこなった。試験は共生菌 2 種と対照の 3区を設け，1 反復あたり 12 本，それぞれ 3 反復（計 108本）で植樹区を設定した。
3. 結果および考察
土壌コアおよびブナ実生より，これまでに 66 種類の菌根形態型が確認された。調査区内における土壌コア内の菌根チップ総数および出現形態型数は，ブナ林区から開墾跡地にかけて減少する傾向にあった。ブナ実生

図 1 駒止湿原周辺に設置した調査区の菌根形成率も同様の傾向を示した。調査地における
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外生菌根菌群集の特徴は，ブナ林区・境界区における選抜菌株は，1.5% Malt Extract 液体培地で培養し，ブナ実生のグループと開墾跡地におけるブナ実生のグ

菌糸懸濁液（1.0×10^X 菌糸片/mL）を作成した。現地

ループに分かれており開墾跡地ではブナ林内とは異なにおいて 4 m×5 m の植樹区を 9 つ（対象区，る菌類相であることがブナの生育の妨げになっているこ

Leptodontidium sp.区および C. geophilum 区を 3 反復）とが考えられた。

設置し，それぞれの区に 12 本のブナ稚樹を，1m 以上の間隔を空けて植樹した（図 3）。Leptodontidium sp.区お菌根チップから抽出した DNA により菌根形成菌種の同定を行った結果，外生菌根菌のみではなく，根部内

よび C. geophilum 区については，菌糸懸濁液を現地で生菌を含む系統群である Helotiales 目菌類が認められ希釈し，大型のビニール袋内でブナ稚樹の根部と接触たことから，ブナ実生の生育には，共生菌類として外生させることで接種した後，速やかに植樹をおこなった。こ菌根菌だけではなく根部内生菌も関与していることが考れらの稚樹については，主幹長や葉の葉緑素含量によえられた。そこで，ブナ実生根部より根部内生菌 97 菌株って生育評価を行っていく。

を分離し，うち 83 菌株を分子同定した。分離した 65 菌
株中，33 菌株が Helotiales 目菌類であり，その中で 21菌株が Leptodontidium 属菌であった。これらの菌類は主にブナ林区および境界区に認められ，菌根の形態型には依存せずに分離された（図 2）。放棄地区でも同属の L.
orchidicola が分離されたことから，調査区において，Leptodontidium 属菌はブナの生育と密接に関係していることが推察された。また，外生菌根菌として報告のある
図 3 現地植樹試験の様子

Cenococcum geophilum を菌根部から 2 菌株分離された。
4. 結論

以上より，現地における開墾跡地への植樹試験に用いる接種菌株として，根部内生菌 Leptodontidium sp.およ樹木の生育には共生菌類の関与が必要不可欠であり，

び外生菌根菌 C. geophilum を選抜した。

駒止湿原におけるこれまでの植樹活動でも，山引苗を利用するなど，従来の森林環境に学んだ取り組みが多数実施されている [2]。今後，本研究で選抜した菌類による影響の調査を継続するとともに，同菌種を用いた実験
室内での接種試験も行い，菌根菌-内生菌-宿主植物の相互関係を明らかにしていく。
引用文献

図 2 Leptodontidium 属菌が分離された菌根形態型

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[1]

駒止湿原保存方策調査検討委員会: 駒止湿原保存方策調査, 2004.

[2]

伊藤祥子・谷本祥子: 駒止開墾地におけるブナ山引き苗の植林と育苗に関する基礎的研究, 駒止湿原保存方策調査, pp. 111-111, 2004.