Effects of Hydrothermal Conditions on the Net Primary Productivity in the Source Region of Yangtze River, China

Effects of Hydrothermal Conditions on the Net Primary Productivity in the Source Region of Yangtze River, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Effects of Hydrothermal Conditions on the Net Primary Productivity in the Source Region of Yangtze River, China Zhe Yuan, Yongqiang Wang, Jijun Xu, Jun Yin, Shu Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.24647/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The ecosystems and natural environment of the Source Region of Yangtze River (SRYR) is highly susceptible to the climate change. Quantifying the response of vegetation Net Primary Productivity (NPP) to the changes of hydrothermal conditions is an important way to identify and predict global ecosystem dynamics. Methods: Using MODIS/Terra Yearly NPP data at 1km×1km spatial resolution, the spatial-temporal variation of NPP was analyzed at first. Then, correlations between NPP and hydrothermal conditions were evaluated with soil water content and accumulated temperature. Finally, a response model was built to analyze the sensitivity of the NPP to precipitation and temperature changes. Result: (1) NPP is generally lower in the western SRYR and increases gradually toward the east, with an average value of 85.2 gC/m 2 . The total NPP had increased by 1.42TgC per year from 2000 to 2014. The fastest change rate of NPP is presented in the Downstream region, followed by the middle stream region and Dam River Basin; (2) the NPP of one specific year has obvious relationship with the accumulated temperature of the same year and the soil water deficit of the previous year. The temperature is the dominant climate factor impacting vegetation growth in the SRYR; (3) It is shown an increase of NPP by 0.194 TgC (nearly 30%) with a 1-°C increase in annual mean temperature. While a 10% increase in annual precipitation corresponds to an increase in NPP by 0.517 TgC (nearly 5%). Conclusion: A warming, wetting and greening SRYR was detected in recent decade. The NPP in SRYR is more sensitive to changes in temperature than changes in precipitation. Toxicology Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Full Text Tables Table 1 Runoff coefficients for different slopes Slope 0 to 5° 0 to 10° 10 to 15° 15 to 20° 20 to 25° >25° Runoff coefficient ( α ) 0 0.04 0.12 0.2 0.27 0.35 Table 2 Response model of NPP to soil water deficit / accumulated temperature in five sub-regions and the entire SRYR Region Response models R Significance F Tuotuo River Basin NPP i =0.0003× SD i -1 +0.0015× AT 0 i -0.3379 0.817 1.22E-05 Dam River Basin NPP i =0.0018× SD i -1 +0.0034× AT 0 i -0.9506 0.827 6.53E-05 Qumar River Basin NPP i =0.0008× SD i -1 +0.0016× AT 0 i -0.3097 0.847 3.27E-05 Middle stream NPP i =0.0031× SD i -1 +0.0035× AT 0 i -0.8395 0.822 3.05E-05 Downstream NPP i =0.0025× SD i -1 +0.0072× AT 0 i -2.0869 0.774 2.79E-04 SRYR NPP i =0.0108× SD i -1 +0.0166× AT 0 i -4.3313 0.849 1.22E-05 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-15205","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":370909,"identity":"c5b4ae36-6cfd-4b0b-9ec1-93a0b2fa47de","order_by":1,"name":"Zhe Yuan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYLACxgYGBjZmxsYHHwxs5IjXws/O3Gw4oyDNmHgtkv3sbcI8Hw4nElRtcCP52cOfO2wYDA4ztjHbGDAnMLAfProBv5Y0cwPJM2lgLY9zDNjyGHjS0m7g15JgJmHYdhikpd04x4CnmEGCx4yAlvRvEolt/8G2SFsYSCQ2ENaSYyZxsO0Ag2QzUAuDgQFhLZJn3pRJNrYlM/AzMzYb9hgkGLMR8gvf8fRtkj/b7BjY+I8/fPDjz385fvbDx/BqUTgAoesbYCJs+JSDgHwDIRWjYBSMglEwCgBnukldS0iKlwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8525-2415","institution":"Changjiang River Scientific Research Institute","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Zhe","middleName":"","lastName":"Yuan","suffix":""},{"id":370910,"identity":"779d39fb-97c5-47c5-a418-ee4b18491e19","order_by":2,"name":"Yongqiang Wang","email":"","orcid":"","institution":"Changjiang River Scientific Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yongqiang","middleName":"","lastName":"Wang","suffix":""},{"id":370911,"identity":"1a94183d-b64d-4149-a98c-557fd7cabe69","order_by":3,"name":"Jijun Xu","email":"","orcid":"","institution":"Changjiang River Scientific Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jijun","middleName":"","lastName":"Xu","suffix":""},{"id":370912,"identity":"fd7f1ab3-7201-4f0c-a5cb-89aa6ba53ad0","order_by":4,"name":"Jun Yin","email":"","orcid":"","institution":"Hubei University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Yin","suffix":""},{"id":370913,"identity":"de5bc7dc-19b8-4618-a511-55d1ba0e1743","order_by":5,"name":"Shu Chen","email":"","orcid":"","institution":"Changjiang River Scientific Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shu","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2020-02-25 13:05:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.24647/v1","doiUrl":"https://doi.org/10.21203/rs.2.24647/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":554196,"identity":"d6202a71-c0a6-4df6-b47f-862041c29967","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11243107,"visible":true,"origin":"","legend":"Runoff coefficients for different slopes. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig01.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig01.jpg"},{"id":554197,"identity":"1c69207e-f325-403c-b38f-5a1e25e42402","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9770609,"visible":true,"origin":"","legend":"The spatial distribution of multi-year average NP. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig02.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig02.jpg"},{"id":554198,"identity":"657f9a64-d8ff-40f4-b89d-ec254412d10e","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":99746,"visible":true,"origin":"","legend":"Average NPP in different elevation","description":"","filename":"Fig03.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig03.png"},{"id":554199,"identity":"541c7a58-9013-4969-8af0-d12e53300a54","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":39546,"visible":true,"origin":"","legend":"Area percentages of regions with different grades in average annual NPP*\n*Note: Sub-region I to V represent Tuotuo River Basin, Dam River Basin, Qumar River Basin, Middle stream and Downstream, respectively.","description":"","filename":"Fig04.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig04.png"},{"id":554200,"identity":"3cbb08b1-5360-4259-a7b2-a0d152474936","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":56347,"visible":true,"origin":"","legend":"Changes in annual NPP in the SRYR*\n*Note: Sub-region I to V represent Tuotuo River Basin, Dam River Basin, Qumar River Basin, Middle stream and Downstream, respectively.","description":"","filename":"Fig05.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig05.png"},{"id":554201,"identity":"4b853c93-6e97-41c8-b8f2-f4b560ee164c","added_by":"auto","created_at":"2020-02-26 22:05:14","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":10301762,"visible":true,"origin":"","legend":"Spatial trends of NPP in SRYR. The small inset map in Fig. 6 shows that the spatial pattern of trend significance levels marked by “p”. The region filled in white is non-significant at p\u003e0.05. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig06.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig06.jpg"},{"id":554202,"identity":"d0ea9c35-60bf-4802-8e81-337accd0b15f","added_by":"auto","created_at":"2020-02-26 22:05:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":93428,"visible":true,"origin":"","legend":"Changes in annual effective precipitation (a) and accumulated temperature (b) in the SRYR","description":"","filename":"Fig07.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig07.png"},{"id":554203,"identity":"d570915e-336a-4204-a34f-fcb55675e92b","added_by":"auto","created_at":"2020-02-26 22:05:15","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":7579602,"visible":true,"origin":"","legend":"Spatial trends of soil water deficit and accumulated temperature in SRYR. The small inset map in Fig. 8 shows that the spatial pattern of trend significance levels marked by “p”. The region filled in white is non-significant at p\u003e0.05. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig08a.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig08a.jpg"},{"id":554204,"identity":"dbccd519-c4b8-4433-8ae5-d4f83dfb4fc6","added_by":"auto","created_at":"2020-02-26 22:05:15","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":179165,"visible":true,"origin":"","legend":"Correlation between NPP and soil water deficit: (a) Tuotuo River Basin; (b) Dam River Basin;(c) Qumar River Basin;(d) Middle stream; (e) Downstream and (f) SRYR","description":"","filename":"Fig09.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig09.png"},{"id":554205,"identity":"d91e6f29-59f0-4e82-8e32-6e3bd454a44d","added_by":"auto","created_at":"2020-02-26 22:05:15","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":187365,"visible":true,"origin":"","legend":"Correlation between NPP and accumulated temperature: (a) Tuotuo River Basin; (b) Dam River Basin; (c) Qumar River Basin; (d) Middle stream; (e) Downstream and (f) SRYR","description":"","filename":"Fig10.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig10.png"},{"id":554206,"identity":"53027a46-bc60-4c8d-a67d-f65ac5d4b5d8","added_by":"auto","created_at":"2020-02-26 22:05:16","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":8104055,"visible":true,"origin":"","legend":"Correlation Coefficient between NPP and soil water deficit (a) / accumulated temperature (b). Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig11.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig11.jpg"},{"id":554207,"identity":"dc77639d-c89a-41ba-aa30-e85df9b83601","added_by":"auto","created_at":"2020-02-26 22:05:16","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":101458,"visible":true,"origin":"","legend":"Sensitivity on soil water deficit/ accumulated temperature due to precipitation and temperature change in the SRYR: (a) soil water deficit affected by precipitation change; (b) soil water deficit affected by temperature change; (c) accumulated temperature affected by temperature change","description":"","filename":"Fig12.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig12.png"},{"id":554208,"identity":"68e7e825-5502-4045-8065-df3ec46bcdfe","added_by":"auto","created_at":"2020-02-26 22:05:16","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":76390,"visible":true,"origin":"","legend":"Sensitivity on NPP due to precipitation and temperature change in the SRYR","description":"","filename":"Fig13.png","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig13.png"},{"id":554209,"identity":"53114595-5d26-44c1-822a-00a7bc926907","added_by":"auto","created_at":"2020-02-26 22:05:16","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":9726605,"visible":true,"origin":"","legend":"Spatial distribution of different driving forces of changes in NPP from 2000 to 2014 in the SRYR. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig14.jpg","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Fig14.jpg"},{"id":788374,"identity":"5896ae33-79d3-472a-bd39-19645089ce9b","added_by":"auto","created_at":"2020-03-31 00:03:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":42342236,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-15205/v1/manuscript.pdf"},{"id":554212,"identity":"4bf6862e-7e43-400c-9913-474e082d16b1","added_by":"auto","created_at":"2020-02-26 22:05:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6151798,"visible":true,"origin":"","legend":"","description":"","filename":"submitmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/Manuscript.pdf"},{"id":554211,"identity":"debfeac3-ae9a-4432-ab6f-c1910391b6b1","added_by":"auto","created_at":"2020-02-26 22:05:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6111833,"visible":true,"origin":"","legend":"","description":"","filename":"submitmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/submit_manuscript.pdf"},{"id":554210,"identity":"05a415e3-c829-4580-920e-b44ddb468e99","added_by":"auto","created_at":"2020-02-26 22:05:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6111833,"visible":true,"origin":"","legend":"","description":"","filename":"submitmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/submit_manuscript.pdf"},{"id":554195,"identity":"06cfb72f-185f-4f25-a70d-4fda902be712","added_by":"auto","created_at":"2020-02-26 22:05:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6111833,"visible":true,"origin":"","legend":"","description":"","filename":"submitmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/d8264525-1f07-4701-b8bf-24998834976b/v1/submit_manuscript.pdf"},{"id":13490839,"identity":"1adaf274-8bff-4825-8fb1-56fadf55531d","added_by":"auto","created_at":"2021-09-16 22:25:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4042176,"visible":true,"origin":"","legend":"","description":"","filename":"submitmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-15205/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Effects of Hydrothermal Conditions on the Net Primary Productivity in the Source Region of Yangtze River, China","fulltext":[{"header":"Full Text","content":"\u003cp\u003eThis preprint is available for \u003ca href='/article/rs-15205/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e.\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eRunoff coefficients for different slopes\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0 to 5°\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0 to 10°\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e10 to 15°\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e15 to 20°\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e20 to 25°\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026gt;25°\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eRunoff coefficient\u0026nbsp;(\u003cem\u003eα\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Response model of NPP to soil water deficit / accumulated temperature in five sub-regions and the entire SRYR\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003eResponse models\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003eSignificance F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eTuotuo River Basin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0003×\u003cem\u003eSD\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0015×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e-0.3379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e1.22E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eDam River Basin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0018×\u003cem\u003eSD\u003csub\u003e\u0026nbsp;i\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0034×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e -0.9506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e6.53E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eQumar River Basin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0008×\u003cem\u003eSD\u003csub\u003e\u0026nbsp;i\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0016×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e -0.3097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e3.27E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eMiddle stream\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0031×\u003cem\u003eSD\u003csub\u003e\u0026nbsp;i\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0035×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e -0.8395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e3.05E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eDownstream\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0025×\u003cem\u003eSD\u003csub\u003e\u0026nbsp;i\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0072×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e-2.0869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e2.79E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eSRYR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cem\u003eNPP\u003csub\u003ei\u003c/sub\u003e\u003c/em\u003e=0.0108×\u003cem\u003eSD\u003csub\u003e\u0026nbsp;i\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e-1\u003c/sub\u003e+0.0166×\u003cem\u003eAT\u003c/em\u003e0\u003cem\u003e\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e-4.3313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e1.22E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.2.24647/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.24647/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: The ecosystems and natural environment of the Source Region of Yangtze River (SRYR) is highly susceptible to the climate change. Quantifying the response of vegetation Net Primary Productivity (NPP) to the changes of hydrothermal conditions is an important way to identify and predict global ecosystem dynamics. \u003c/p\u003e\u003cp\u003eMethods: Using MODIS/Terra Yearly NPP data at 1km×1km spatial resolution, the spatial-temporal variation of NPP was analyzed at first. Then, correlations between NPP and hydrothermal conditions were evaluated with soil water content and accumulated temperature. Finally, a response model was built to analyze the sensitivity of the NPP to precipitation and temperature changes. \u003c/p\u003e\u003cp\u003eResult: (1) NPP is generally lower in the western SRYR and increases gradually toward the east, with an average value of 85.2 gC/m 2 . The total NPP had increased by 1.42TgC per year from 2000 to 2014. The fastest change rate of NPP is presented in the Downstream region, followed by the middle stream region and Dam River Basin; (2) the NPP of one specific year has obvious relationship with the accumulated temperature of the same year and the soil water deficit of the previous year. The temperature is the dominant climate factor impacting vegetation growth in the SRYR; (3) It is shown an increase of NPP by 0.194 TgC (nearly 30%) with a 1-°C increase in annual mean temperature. While a 10% increase in annual precipitation corresponds to an increase in NPP by 0.517 TgC (nearly 5%). \u003c/p\u003e\u003cp\u003eConclusion: A warming, wetting and greening SRYR was detected in recent decade. The NPP in SRYR is more sensitive to changes in temperature than changes in precipitation.\u003c/p\u003e","manuscriptTitle":"Effects of Hydrothermal Conditions on the Net Primary Productivity in the Source Region of Yangtze River, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-02-26 22:05:12","doi":"10.21203/rs.2.24647/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5c11261-ad0e-4d56-a60d-d8685edbce4f","owner":[],"postedDate":"February 26th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62928,"name":"Toxicology"},{"id":62929,"name":"Epidemiology"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-02-26 22:05:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-15205","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-15205","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}