Item talk:Q44528

ORCiD:

 meta:
   status_code: 200
   timestamp: '2023-10-20T08:42:11.311752'
   url: https://orcid.org/0000-0003-3638-8572
 orcid:
   activities:
     educations:
       affiliation-group:
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1422359356390
         summaries:
         - education-summary:
             created-date:
               value: 1422359356390
             department-name: University Program in Ecology
             display-index: '0'
             end-date:
               day:
                 value: '15'
               month:
                 value: '05'
               year:
                 value: '2012'
             external-ids: null
             last-modified-date:
               value: 1422359356390
             organization:
               address:
                 city: Durham
                 country: US
                 region: NC
               disambiguated-organization:
                 disambiguated-organization-identifier: '3065'
                 disambiguation-source: RINGGOLD
               name: Duke University
             path: /0000-0003-3638-8572/education/694107
             put-code: 694107
             role-title: PhD
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '15'
               month:
                 value: 08
               year:
                 value: '2006'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1513633506381
         summaries:
         - education-summary:
             created-date:
               value: 1513633506381
             department-name: null
             display-index: '0'
             end-date:
               day:
                 value: '15'
               month:
                 value: '04'
               year:
                 value: '2004'
             external-ids: null
             last-modified-date:
               value: 1513633506381
             organization:
               address:
                 city: Stanford
                 country: US
                 region: CA
               disambiguated-organization: null
               name: Stanford University
             path: /0000-0003-3638-8572/education/5087332
             put-code: 5087332
             role-title: B.S. Symbolic Systems
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '15'
               month:
                 value: 09
               year:
                 value: '2000'
             url: null
             visibility: public
       last-modified-date:
         value: 1513633506381
       path: /0000-0003-3638-8572/educations
     employments:
       affiliation-group:
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1680620863129
         summaries:
         - employment-summary:
             created-date:
               value: 1680620755344
             department-name: Analysis & Prediction Branch, Integrated Modeling and
               Prediction Division
             display-index: '1'
             end-date: null
             external-ids: null
             last-modified-date:
               value: 1680620863129
             organization:
               address:
                 city: State College
                 country: US
                 region: PA
               disambiguated-organization:
                 disambiguated-organization-identifier: http://dx.doi.org/10.13039/100000203
                 disambiguation-source: FUNDREF
               name: U.S. Geological Survey
             path: /0000-0003-3638-8572/employment/20018279
             put-code: 20018279
             role-title: Ecologist
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '15'
               month:
                 value: '02'
               year:
                 value: '2023'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1680620669976
         summaries:
         - employment-summary:
             created-date:
               value: 1478105501922
             department-name: Data Science Branch, Integrated Information Dissemination
               Division
             display-index: '1'
             end-date:
               day: null
               month: null
               year:
                 value: '2023'
             external-ids: null
             last-modified-date:
               value: 1680620669976
             organization:
               address:
                 city: State College
                 country: US
                 region: PA
               disambiguated-organization:
                 disambiguated-organization-identifier: '2928'
                 disambiguation-source: RINGGOLD
               name: US Geological Survey
             path: /0000-0003-3638-8572/employment/2530363
             put-code: 2530363
             role-title: Ecologist
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '15'
               month:
                 value: '02'
               year:
                 value: '2016'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1554379611477
         summaries:
         - employment-summary:
             created-date:
               value: 1475195090818
             department-name: Office of Water Information
             display-index: '1'
             end-date:
               day:
                 value: '28'
               month:
                 value: '10'
               year:
                 value: '2016'
             external-ids: null
             last-modified-date:
               value: 1554379611477
             organization:
               address:
                 city: Middleton
                 country: US
                 region: WI
               disambiguated-organization:
                 disambiguated-organization-identifier: '2928'
                 disambiguation-source: RINGGOLD
               name: US Geological Survey
             path: /0000-0003-3638-8572/employment/2344338
             put-code: 2344338
             role-title: Data Scientist (contractor)
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '16'
               month:
                 value: '04'
               year:
                 value: '2016'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1475195455293
         summaries:
         - employment-summary:
             created-date:
               value: 1475195438121
             department-name: Center for Freshwater Limnology
             display-index: '0'
             end-date:
               day:
                 value: '15'
               month:
                 value: '04'
               year:
                 value: '2016'
             external-ids: null
             last-modified-date:
               value: 1475195455293
             organization:
               address:
                 city: Madison
                 country: US
                 region: WI
               disambiguated-organization:
                 disambiguated-organization-identifier: '5228'
                 disambiguation-source: RINGGOLD
               name: University of Wisconsin Madison
             path: /0000-0003-3638-8572/employment/2344391
             put-code: 2344391
             role-title: Postdoc
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '16'
               month:
                 value: '04'
               year:
                 value: '2015'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1475195148517
         summaries:
         - employment-summary:
             created-date:
               value: 1422359433898
             department-name: Natural Resources and the Environment
             display-index: '0'
             end-date:
               day:
                 value: '15'
               month:
                 value: '04'
               year:
                 value: '2015'
             external-ids: null
             last-modified-date:
               value: 1475195148517
             organization:
               address:
                 city: Durham
                 country: US
                 region: NH
               disambiguated-organization:
                 disambiguated-organization-identifier: '3067'
                 disambiguation-source: RINGGOLD
               name: University of New Hampshire
             path: /0000-0003-3638-8572/employment/694114
             put-code: 694114
             role-title: Postdoctoral Associate
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '01'
               month:
                 value: '06'
               year:
                 value: '2013'
             url: null
             visibility: public
       - external-ids:
           external-id: []
         last-modified-date:
           value: 1422359569494
         summaries:
         - employment-summary:
             created-date:
               value: 1422359569494
             department-name: Nicholas School of the Environment
             display-index: '0'
             end-date:
               day:
                 value: '25'
               month:
                 value: '05'
               year:
                 value: '2013'
             external-ids: null
             last-modified-date:
               value: 1422359569494
             organization:
               address:
                 city: Durham
                 country: US
                 region: NC
               disambiguated-organization:
                 disambiguated-organization-identifier: '3065'
                 disambiguation-source: RINGGOLD
               name: Duke University
             path: /0000-0003-3638-8572/employment/694125
             put-code: 694125
             role-title: Postdoctoral Associate
             source:
               assertion-origin-client-id: null
               assertion-origin-name: null
               assertion-origin-orcid: null
               source-client-id: null
               source-name:
                 value: Alison P. Appling
               source-orcid:
                 host: orcid.org
                 path: 0000-0003-3638-8572
                 uri: https://orcid.org/0000-0003-3638-8572
             start-date:
               day:
                 value: '15'
               month:
                 value: '05'
               year:
                 value: '2012'
             url: null
             visibility: public
       last-modified-date:
         value: 1680620863129
       path: /0000-0003-3638-8572/employments
     works:
       group:
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1038/s43017-023-00450-9
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1038/s43017-023-00450-9
             external-id-value: 10.1038/s43017-023-00450-9
         last-modified-date:
           value: 1689068898570
         work-summary:
         - created-date:
             value: 1689068898570
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1038/s43017-023-00450-9
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1038/s43017-023-00450-9
               external-id-value: 10.1038/s43017-023-00450-9
           journal-title:
             value: Nature Reviews Earth & Environment
           last-modified-date:
             value: 1689068898570
           path: /0000-0003-3638-8572/work/138450227
           publication-date:
             day:
               value: '11'
             month:
               value: '07'
             year:
               value: '2023'
           put-code: 138450227
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Differentiable modelling to unify machine learning and physical
                 models for geosciences
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1038/s43017-023-00450-9
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1111/1752-1688.13093
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1111/1752-1688.13093
             external-id-value: 10.1111/1752-1688.13093
         last-modified-date:
           value: 1680684226460
         work-summary:
         - created-date:
             value: 1672216714277
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1111/1752-1688.13093
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1111/1752-1688.13093
               external-id-value: 10.1111/1752-1688.13093
           journal-title:
             value: JAWRA Journal of the American Water Resources Association
           last-modified-date:
             value: 1680684226460
           path: /0000-0003-3638-8572/work/125434263
           publication-date:
             day: null
             month:
               value: '04'
             year:
               value: '2023'
           put-code: 125434263
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Near\u2010term forecasts of stream temperature using deep\
                 \ learning and data assimilation in support of management decisions"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1111/1752-1688.13093
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2022wr033880
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2022WR033880
             external-id-value: 10.1029/2022WR033880
         last-modified-date:
           value: 1680618379030
         work-summary:
         - created-date:
             value: 1678826704977
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2022wr033880
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2022WR033880
               external-id-value: 10.1029/2022WR033880
           journal-title:
             value: Water Resources Research
           last-modified-date:
             value: 1680618379030
           path: /0000-0003-3638-8572/work/130828584
           publication-date:
             day: null
             month:
               value: '04'
             year:
               value: '2023'
           put-code: 130828584
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'Stream Temperature Prediction in a Shifting Environment: Explaining
                 the Influence of Deep Learning Architecture'
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2022WR033880
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.31223/x5964s
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.31223/X5964S
             external-id-value: 10.31223/X5964S
         last-modified-date:
           value: 1662372743926
         work-summary:
         - created-date:
             value: 1662214810641
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.31223/x5964s
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.31223/X5964S
               external-id-value: 10.31223/X5964S
           journal-title: null
           last-modified-date:
             value: 1662372743926
           path: /0000-0003-3638-8572/work/118383357
           publication-date:
             day:
               value: '05'
             month:
               value: 09
             year:
               value: '2022'
           put-code: 118383357
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Machine learning for understanding inland water quantity, quality,
                 and ecology
             translated-title: null
           type: preprint
           url:
             value: https://doi.org/10.31223/X5964S
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/lno.12098
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/lno.12098
             external-id-value: 10.1002/lno.12098
         last-modified-date:
           value: 1660021481042
         work-summary:
         - created-date:
             value: 1652956867009
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/lno.12098
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/lno.12098
               external-id-value: 10.1002/lno.12098
           journal-title:
             value: Limnology and Oceanography
           last-modified-date:
             value: 1660021481042
           path: /0000-0003-3638-8572/work/113279349
           publication-date:
             day: null
             month:
               value: '07'
             year:
               value: '2022'
           put-code: 113279349
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Long\u2010term change in metabolism phenology in north temperate\
                 \ lakes"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/lno.12098
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1016/b978-0-12-819166-8.00121-3
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1016/b978-0-12-819166-8.00121-3
             external-id-value: 10.1016/b978-0-12-819166-8.00121-3
         last-modified-date:
           value: 1672594960712
         work-summary:
         - created-date:
             value: 1672594960712
           display-index: '1'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1016/b978-0-12-819166-8.00121-3
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1016/b978-0-12-819166-8.00121-3
               external-id-value: 10.1016/b978-0-12-819166-8.00121-3
           journal-title:
             value: Encyclopedia of Inland Waters
           last-modified-date:
             value: 1672594960712
           path: /0000-0003-3638-8572/work/125638852
           publication-date:
             day:
               value: '23'
             month:
               value: '05'
             year:
               value: '2022'
           put-code: 125638852
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id: null
             source-name:
               value: Alison P. Appling
             source-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
           title:
             subtitle: null
             title:
               value: Machine Learning for Understanding Inland Water Quantity, Quality,
                 and Ecology
             translated-title: null
           type: book-chapter
           url:
             value: http://dx.doi.org/10.1016/b978-0-12-819166-8.00121-3
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/hyp.14565
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/hyp.14565
             external-id-value: 10.1002/hyp.14565
         last-modified-date:
           value: 1667533893345
         work-summary:
         - created-date:
             value: 1650812560080
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/hyp.14565
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/hyp.14565
               external-id-value: 10.1002/hyp.14565
           journal-title:
             value: Hydrological Processes
           last-modified-date:
             value: 1667533893345
           path: /0000-0003-3638-8572/work/111975653
           publication-date:
             day: null
             month:
               value: '04'
             year:
               value: '2022'
           put-code: 111975653
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Can machine learning accelerate process understanding and\
                 \ decision\u2010relevant predictions of river water quality?"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/hyp.14565
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2021wr030138
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2021WR030138
             external-id-value: 10.1029/2021WR030138
         last-modified-date:
           value: 1654720133127
         work-summary:
         - created-date:
             value: 1646246575146
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2021wr030138
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2021WR030138
               external-id-value: 10.1029/2021WR030138
           journal-title:
             value: Water Resources Research
           last-modified-date:
             value: 1654720133127
           path: /0000-0003-3638-8572/work/109114107
           publication-date:
             day: null
             month:
               value: '04'
             year:
               value: '2022'
           put-code: 109114107
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Multi\u2010Task Deep Learning of Daily Streamflow and Water\
                 \ Temperature"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2021WR030138
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/hyp.14484
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/hyp.14484
             external-id-value: 10.1002/hyp.14484
         last-modified-date:
           value: 1654199699533
         work-summary:
         - created-date:
             value: 1645165335562
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/hyp.14484
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/hyp.14484
               external-id-value: 10.1002/hyp.14484
           journal-title:
             value: Hydrological Processes
           last-modified-date:
             value: 1654199699533
           path: /0000-0003-3638-8572/work/108414631
           publication-date:
             day: null
             month:
               value: '02'
             year:
               value: '2022'
           put-code: 108414631
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Long\u2010term suspended sediment and particulate organic\
                 \ carbon yields from the Reynolds Creek Experimental Watershed and\
                 \ Critical Zone Observatory"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/hyp.14484
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/essoar.10509644.1
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/essoar.10509644.1
             external-id-value: 10.1002/essoar.10509644.1
         last-modified-date:
           value: 1654170647468
         work-summary:
         - created-date:
             value: 1639749485050
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/essoar.10509644.1
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/essoar.10509644.1
               external-id-value: 10.1002/essoar.10509644.1
           journal-title: null
           last-modified-date:
             value: 1654170647468
           path: /0000-0003-3638-8572/work/104912989
           publication-date:
             day:
               value: '17'
             month:
               value: '12'
             year:
               value: '2021'
           put-code: 104912989
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Process learning of stream temperature modelling using deep
                 learning and big data
             translated-title: null
           type: preprint
           url:
             value: https://doi.org/10.1002/essoar.10509644.1
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/hyp.14400
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/hyp.14400
             external-id-value: 10.1002/hyp.14400
         last-modified-date:
           value: 1654164028478
         work-summary:
         - created-date:
             value: 1637930956327
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/hyp.14400
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/hyp.14400
               external-id-value: 10.1002/hyp.14400
           journal-title:
             value: Hydrological Processes
           last-modified-date:
             value: 1654164028478
           path: /0000-0003-3638-8572/work/103796104
           publication-date:
             day: null
             month:
               value: '11'
             year:
               value: '2021'
           put-code: 103796104
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Deep learning approaches for improving prediction of daily\
                 \ stream temperature in data\u2010scarce, unmonitored, and dammed\
                 \ basins"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/hyp.14400
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.31223/x55k7g
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.31223/X55K7G
             external-id-value: 10.31223/X55K7G
         last-modified-date:
           value: 1654127674429
         work-summary:
         - created-date:
             value: 1628258027128
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.31223/x55k7g
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.31223/X55K7G
               external-id-value: 10.31223/X55K7G
           journal-title: null
           last-modified-date:
             value: 1654127674429
           path: /0000-0003-3638-8572/work/98143701
           publication-date:
             day:
               value: '06'
             month:
               value: 08
             year:
               value: '2021'
           put-code: 98143701
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Near-term forecasts of stream temperature using process-guided
                 deep learning and data assimilation
             translated-title: null
           type: other
           url:
             value: https://doi.org/10.31223/X55K7G
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2021wr029579
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2021WR029579
             external-id-value: 10.1029/2021WR029579
         last-modified-date:
           value: 1654077240883
         work-summary:
         - created-date:
             value: 1623861032629
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2021wr029579
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2021WR029579
               external-id-value: 10.1029/2021WR029579
           journal-title:
             value: Water Resources Research
           last-modified-date:
             value: 1654077240883
           path: /0000-0003-3638-8572/work/95594436
           publication-date:
             day: null
             month:
               value: '07'
             year:
               value: '2021'
           put-code: 95594436
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Predicting Water Temperature Dynamics of Unmonitored Lakes\
                 \ With Meta\u2010Transfer Learning"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2021WR029579
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.31223/x5004x
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.31223/X5004X
             external-id-value: 10.31223/X5004X
         last-modified-date:
           value: 1654068967469
         work-summary:
         - created-date:
             value: 1621611551126
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.31223/x5004x
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.31223/X5004X
               external-id-value: 10.31223/X5004X
           journal-title: null
           last-modified-date:
             value: 1654068967469
           path: /0000-0003-3638-8572/work/94229514
           publication-date:
             day:
               value: '21'
             month:
               value: '05'
             year:
               value: '2021'
           put-code: 94229514
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Multi-task deep learning of daily streamflow and water temperature
             translated-title: null
           type: other
           url:
             value: https://doi.org/10.31223/X5004X
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1088/1748-9326/abd501
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1088/1748-9326/abd501
             external-id-value: 10.1088/1748-9326/abd501
         last-modified-date:
           value: 1653997614081
         work-summary:
         - created-date:
             value: 1608330133606
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1088/1748-9326/abd501
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1088/1748-9326/abd501
               external-id-value: 10.1088/1748-9326/abd501
           journal-title:
             value: Environmental Research Letters
           last-modified-date:
             value: 1653997614081
           path: /0000-0003-3638-8572/work/85516281
           publication-date:
             day:
               value: '18'
             month:
               value: '12'
             year:
               value: '2020'
           put-code: 85516281
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Exploring the exceptional performance of a deep learning stream
                 temperature model and the value of streamflow data
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1088/1748-9326/abd501
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2019wr024883
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2019WR024883
             external-id-value: 10.1029/2019WR024883
         last-modified-date:
           value: 1693628169119
         work-summary:
         - created-date:
             value: 1570816433990
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2019wr024883
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2019WR024883
               external-id-value: 10.1029/2019WR024883
           journal-title:
             value: Water Resources Research
           last-modified-date:
             value: 1693628169119
           path: /0000-0003-3638-8572/work/62997431
           publication-date:
             day: null
             month:
               value: '11'
             year:
               value: '2019'
           put-code: 62997431
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'AquaSat: A Data Set to Enable Remote Sensing of Water Quality
                 for Inland Waters'
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2019WR024883
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2019wr024922
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2019WR024922
             external-id-value: 10.1029/2019WR024922
         last-modified-date:
           value: 1693628169347
         work-summary:
         - created-date:
             value: 1573208577007
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2019wr024922
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2019WR024922
               external-id-value: 10.1029/2019WR024922
           journal-title:
             value: Water Resources Research
           last-modified-date:
             value: 1693628169347
           path: /0000-0003-3638-8572/work/64291960
           publication-date:
             day: null
             month:
               value: '11'
             year:
               value: '2019'
           put-code: 64291960
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Process\u2010Guided Deep Learning Predictions of Lake Water\
                 \ Temperature"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2019WR024922
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/lno.11154
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/lno.11154
             external-id-value: 10.1002/lno.11154
         last-modified-date:
           value: 1694317266088
         work-summary:
         - created-date:
             value: 1551655636650
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/lno.11154
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/lno.11154
               external-id-value: 10.1002/lno.11154
           journal-title:
             value: Limnology and Oceanography
           last-modified-date:
             value: 1694317266088
           path: /0000-0003-3638-8572/work/54829696
           publication-date:
             day: null
             month:
               value: 09
             year:
               value: '2019'
           put-code: 54829696
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'Metabolic rhythms in flowing waters: An approach for classifying
                 river productivity regimes'
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/lno.11154
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/lno.11127
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/lno.11127
             external-id-value: 10.1002/lno.11127
         last-modified-date:
           value: 1693346336668
         work-summary:
         - created-date:
             value: 1549399524239
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/lno.11127
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/lno.11127
               external-id-value: 10.1002/lno.11127
           journal-title:
             value: Limnology and Oceanography
           last-modified-date:
             value: 1693346336668
           path: /0000-0003-3638-8572/work/53666841
           publication-date:
             day: null
             month:
               value: '07'
             year:
               value: '2019'
           put-code: 53666841
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Enhancement of primary production during drought in a temperate
                 watershed is greater in larger rivers than headwater streams
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/lno.11127
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1029/2018gl081166
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1029/2018GL081166
             external-id-value: 10.1029/2018GL081166
         last-modified-date:
           value: 1653693640136
         work-summary:
         - created-date:
             value: 1553030035112
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1029/2018gl081166
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1029/2018GL081166
               external-id-value: 10.1029/2018GL081166
           journal-title:
             value: Geophysical Research Letters
           last-modified-date:
             value: 1653693640136
           path: /0000-0003-3638-8572/work/55477775
           publication-date:
             day:
               value: '16'
             month:
               value: '04'
             year:
               value: '2019'
           put-code: 55477775
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: "Detecting Signals of Large\u2010Scale Climate Phenomena in\
                 \ Discharge and Nutrient Loads in the Mississippi\u2010Atchafalaya\
                 \ River Basin"
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1029/2018GL081166
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1038/sdata.2018.292
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1038/sdata.2018.292
             external-id-value: 10.1038/sdata.2018.292
         last-modified-date:
           value: 1671585488899
         work-summary:
         - created-date:
             value: 1544537193294
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1038/sdata.2018.292
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1038/sdata.2018.292
               external-id-value: 10.1038/sdata.2018.292
           journal-title:
             value: Scientific Data
           last-modified-date:
             value: 1671585488899
           path: /0000-0003-3638-8572/work/51541390
           publication-date:
             day:
               value: '11'
             month:
               value: '12'
             year:
               value: '2018'
           put-code: 51541390
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: The metabolic regimes of 356 rivers in the United States
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1038/sdata.2018.292
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/2017jg004140
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1002/2017JG004140
             external-id-value: 10.1002/2017JG004140
         last-modified-date:
           value: 1693946076107
         work-summary:
         - created-date:
             value: 1517970729113
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/2017jg004140
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1002/2017JG004140
               external-id-value: 10.1002/2017JG004140
           journal-title:
             value: 'Journal of Geophysical Research: Biogeosciences'
           last-modified-date:
             value: 1693946076107
           path: /0000-0003-3638-8572/work/41405765
           publication-date:
             day: null
             month:
               value: '02'
             year:
               value: '2018'
           put-code: 41405765
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'Overcoming Equifinality: Leveraging Long Time Series for Stream
                 Metabolism Estimation'
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1002/2017JG004140
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/lno.10726
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url: null
             external-id-value: 10.1002/lno.10726
         last-modified-date:
           value: 1653571399405
         work-summary:
         - created-date:
             value: 1517544415234
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/lno.10726
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url: null
               external-id-value: 10.1002/lno.10726
             - external-id-normalized:
                 transient: true
                 value: 0024-3590
               external-id-normalized-error: null
               external-id-relationship: part-of
               external-id-type: issn
               external-id-url: null
               external-id-value: 0024-3590
           journal-title:
             value: Limnology and Oceanography
           last-modified-date:
             value: 1653571399405
           path: /0000-0003-3638-8572/work/41237442
           publication-date:
             day: null
             month:
               value: '10'
             year:
               value: '2017'
           put-code: 41237442
           source:
             assertion-origin-client-id: null
             assertion-origin-name:
               value: Alison P. Appling
             assertion-origin-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
             source-client-id:
               host: orcid.org
               path: 0000-0002-3054-1567
               uri: https://orcid.org/client/0000-0002-3054-1567
             source-name:
               value: Crossref Metadata Search
             source-orcid: null
           title:
             subtitle: null
             title:
               value: The metabolic regimes of flowing waters
             translated-title: null
           type: journal-article
           url: null
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 2073-4859
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: issn
             external-id-url: null
             external-id-value: issn 2073-4859
         last-modified-date:
           value: 1513633840174
         work-summary:
         - created-date:
             value: 1513633840174
           display-index: '1'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 2073-4859
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: issn
               external-id-url: null
               external-id-value: issn 2073-4859
           journal-title:
             value: The R Journal
           last-modified-date:
             value: 1513633840174
           path: /0000-0003-3638-8572/work/39763276
           publication-date:
             day: null
             month:
               value: 08
             year:
               value: '2016'
           put-code: 39763276
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id: null
             source-name:
               value: Alison P. Appling
             source-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
           title:
             subtitle: null
             title:
               value: 'sbtools: A Package Connecting R to Cloud-based Data for Collaborative
                 Online Research'
             translated-title: null
           type: journal-article
           url:
             value: https://journal.r-project.org/archive/2016-1/winslow-chamberlain-appling-etal.pdf
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1111/ecog.01880
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url: null
             external-id-value: 10.1111/ecog.01880
         last-modified-date:
           value: 1653559092265
         work-summary:
         - created-date:
             value: 1513633603982
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1111/ecog.01880
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url: null
               external-id-value: 10.1111/ecog.01880
             - external-id-normalized:
                 transient: true
                 value: 0906-7590
               external-id-normalized-error: null
               external-id-relationship: part-of
               external-id-type: issn
               external-id-url: null
               external-id-value: 0906-7590
           journal-title:
             value: Ecography
           last-modified-date:
             value: 1653559092265
           path: /0000-0003-3638-8572/work/39763247
           publication-date:
             day:
               value: 09
             month:
               value: '11'
             year:
               value: '2015'
           put-code: 39763247
           source:
             assertion-origin-client-id: null
             assertion-origin-name:
               value: Alison P. Appling
             assertion-origin-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
             source-client-id:
               host: orcid.org
               path: 0000-0002-3054-1567
               uri: https://orcid.org/client/0000-0002-3054-1567
             source-name:
               value: Crossref Metadata Search
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'geoknife: reproducible web-processing of large gridded datasets'
             translated-title: null
           type: journal-article
           url: null
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1111/oik.02385
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: https://doi.org/10.1111/oik.02385
             external-id-value: 10.1111/oik.02385
         last-modified-date:
           value: 1696222688308
         work-summary:
         - created-date:
             value: 1454004036620
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1111/oik.02385
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: https://doi.org/10.1111/oik.02385
               external-id-value: 10.1111/oik.02385
           journal-title:
             value: Oikos
           last-modified-date:
             value: 1696222688308
           path: /0000-0003-3638-8572/work/21969750
           publication-date:
             day: null
             month:
               value: '07'
             year:
               value: '2015'
           put-code: 21969750
           source:
             assertion-origin-client-id: null
             assertion-origin-name: null
             assertion-origin-orcid: null
             source-client-id:
               host: orcid.org
               path: 0000-0001-9884-1913
               uri: https://orcid.org/client/0000-0001-9884-1913
             source-name:
               value: Crossref
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Stoichiometric flexibility in response to fertilization along
                 gradients of environmental and organismal nutrient richness
             translated-title: null
           type: journal-article
           url:
             value: https://doi.org/10.1111/oik.02385
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1890/es14-00517.1
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url: null
             external-id-value: 10.1890/es14-00517.1
         last-modified-date:
           value: 1653559092272
         work-summary:
         - created-date:
             value: 1513633607253
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1890/es14-00517.1
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url: null
               external-id-value: 10.1890/es14-00517.1
             - external-id-normalized:
                 transient: true
                 value: 2150-8925
               external-id-normalized-error: null
               external-id-relationship: part-of
               external-id-type: issn
               external-id-url: null
               external-id-value: 2150-8925
           journal-title:
             value: Ecosphere
           last-modified-date:
             value: 1653559092272
           path: /0000-0003-3638-8572/work/39763248
           publication-date:
             day: null
             month: null
             year:
               value: '2015'
           put-code: 39763248
           source:
             assertion-origin-client-id: null
             assertion-origin-name:
               value: Alison P. Appling
             assertion-origin-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
             source-client-id:
               host: orcid.org
               path: 0000-0002-3054-1567
               uri: https://orcid.org/client/0000-0002-3054-1567
             source-name:
               value: Crossref Metadata Search
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'Reducing bias and quantifying uncertainty in watershed flux
                 estimates: the R package loadflex'
             translated-title: null
           type: journal-article
           url: null
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1086/677282
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: 
             external-id-value: 10.1086/677282
         last-modified-date:
           value: 1653359862273
         work-summary:
         - created-date:
             value: 1426517912353
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1086/677282
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: 
               external-id-value: 10.1086/677282
           journal-title:
             value: The American Naturalist
           last-modified-date:
             value: 1653359862273
           path: /0000-0003-3638-8572/work/15772159
           publication-date:
             day: null
             month:
               value: 09
             year:
               value: '2014'
           put-code: 15772159
           source:
             assertion-origin-client-id: null
             assertion-origin-name:
               value: Alison P. Appling
             assertion-origin-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
             source-client-id:
               host: orcid.org
               path: 0000-0002-3054-1567
               uri: https://orcid.org/client/0000-0002-3054-1567
             source-name:
               value: Crossref Metadata Search
             source-orcid: null
           title:
             subtitle: null
             title:
               value: Nutrient Limitation and Physiology Mediate the Fine-Scale (De)coupling
                 of Biogeochemical Cycles
             translated-title: null
           type: journal-article
           url: null
           visibility: public
       - external-ids:
           external-id:
           - external-id-normalized:
               transient: true
               value: 10.1002/2013jg002543
             external-id-normalized-error: null
             external-id-relationship: self
             external-id-type: doi
             external-id-url:
               value: 
             external-id-value: 10.1002/2013jg002543
         last-modified-date:
           value: 1653359862267
         work-summary:
         - created-date:
             value: 1426517906207
           display-index: '0'
           external-ids:
             external-id:
             - external-id-normalized:
                 transient: true
                 value: 10.1002/2013jg002543
               external-id-normalized-error: null
               external-id-relationship: self
               external-id-type: doi
               external-id-url:
                 value: 
               external-id-value: 10.1002/2013jg002543
           journal-title:
             value: J. Geophys. Res. Biogeosci.
           last-modified-date:
             value: 1653359862267
           path: /0000-0003-3638-8572/work/15772158
           publication-date:
             day: null
             month:
               value: 08
             year:
               value: '2014'
           put-code: 15772158
           source:
             assertion-origin-client-id: null
             assertion-origin-name:
               value: Alison P. Appling
             assertion-origin-orcid:
               host: orcid.org
               path: 0000-0003-3638-8572
               uri: https://orcid.org/0000-0003-3638-8572
             source-client-id:
               host: orcid.org
               path: 0000-0002-3054-1567
               uri: https://orcid.org/client/0000-0002-3054-1567
             source-name:
               value: Crossref Metadata Search
             source-orcid: null
           title:
             subtitle: null
             title:
               value: 'Floodplain biogeochemical mosaics: A multidimensional view
                 of alluvial soils'
             translated-title: null
           type: journal-article
           url: null
           visibility: public
       last-modified-date:
         value: 1696222688308
       path: /0000-0003-3638-8572/works
   history:
     claimed: true
     completion-date:
       value: 1377876574285
     creation-method: WEBSITE
     deactivation-date: null
     last-modified-date:
       value: 1696222687892
     source: null
     submission-date:
       value: 1377876547621
     verified-email: true
     verified-primary-email: true
   person:
     emails:
       email:
       - created-date:
           value: 1475857403840
         email: aappling@usgs.gov
         last-modified-date:
           value: 1475857452483
         path: null
         primary: true
         put-code: null
         source:
           assertion-origin-client-id: null
           assertion-origin-name: null
           assertion-origin-orcid: null
           source-client-id: null
           source-name:
             value: Alison P. Appling
           source-orcid:
             host: orcid.org
             path: 0000-0003-3638-8572
             uri: https://orcid.org/0000-0003-3638-8572
         verified: true
         visibility: public
       last-modified-date:
         value: 1475857452483
       path: /0000-0003-3638-8572/email
     name:
       created-date:
         value: 1460765093834
       credit-name:
         value: Alison P. Appling
       family-name:
         value: Appling
       given-names:
         value: Alison
       last-modified-date:
         value: 1678993036594
       path: 0000-0003-3638-8572
       source: null
       visibility: public
     researcher-urls:
       last-modified-date:
         value: 1678993077215
       path: /0000-0003-3638-8572/researcher-urls
       researcher-url:
       - created-date:
           value: 1678993077215
         display-index: 1
         last-modified-date:
           value: 1678993077215
         path: /0000-0003-3638-8572/researcher-urls/3720064
         put-code: 3720064
         source:
           assertion-origin-client-id: null
           assertion-origin-name: null
           assertion-origin-orcid: null
           source-client-id: null
           source-name:
             value: Alison P. Appling
           source-orcid:
             host: orcid.org
             path: 0000-0003-3638-8572
             uri: https://orcid.org/0000-0003-3638-8572
         url:
           value: https://www.usgs.gov/staff-profiles/alison-appling
         url-name: Profile at USGS
         visibility: public

USGS Staff Profile:

 '@context': https://schema.org
 '@type': Person
 affiliation: []
 description:
 - '@type': TextObject
   abstract: Data Scientist with the Water Resources Mission Area
   additionalType: short description
 - '@type': TextObject
   abstract: Alison Appling, Ph.D., (she/her) is a data scientist and ecologist who
     applies machine learning and other data-driven methods to predict and understand
     water resources dynamics.
   additionalType: staff profile page introductory statement
 - '@type': TextObject
   abstract: "Current RolesProject Manager: Predictive Understanding of Multiscale\
     \ Processes (PUMP)Task Lead: Advancing Machine Learning and Data Assimilation,\
     \ within the PUMP ProjectAlison studies the movement of energy, carbon, and\
     \ nutrients through rivers, lakes, and floodplains to better predict and understand\
     \ variations in water quality over space and time.As a machine learning modeler\
     \ and biogeochemist, she seeks modeling advances that bring together scientific\
     \ knowledge and data-driven models. \u201CProcess-guided deep learning\u201D\
     \ and \u201Cdifferentiable hydrology\u201D are two approaches on which she collaborates.As\
     \ a data scientist, she conducts analyses in ways that are reproducible, efficient,\
     \ and transparent, and she has developed tools and workflows to support others\
     \ in these goals.In her leadership roles, she facilitates fluid skill sharing\
     \ within teams and communities of practice, challenges individuals to excel\
     \ in their projects and careers, and coordinates across projects to realize\
     \ the Water Mission Area\u2019s vision of broadly reusable, integrated tools\
     \ for predicting water quantity and quality across the nation.Alison is based\
     \ in State College, PA, and is a member of the Analysis and Prediction Branch\
     \ in the Integrated Modeling and Prediction Division in the Water Mission Area.\
     \ She is on the USGS career track called Equipment Development Grade Evaluation\
     \ (EDGE)."
   additionalType: personal statement
 email: aappling@usgs.gov
 hasCredential:
 - '@type': EducationalOccupationalCredential
   name: "Ph.D. Ecology, 2012. Duke University, Durham, NC. \nConnectivity Drives\
     \ Function: Carbon and Nitrogen Dynamics in a Floodplain-Aquifer Ecosystem.\
     \ Advisors: E. S. Bernhardt and R. B. Jackson"
 - '@type': EducationalOccupationalCredential
   name: "B.S. Symbolic Systems, 2004. Stanford University, Stanford, CA. \nCoursework\
     \ in computer science, decision analysis, logic, linguistics, and psychology."
 hasOccupation:
 - '@type': OrganizationalRole
   affiliatedOrganization:
     '@type': Organization
     name: Water Resources Mission Area
     url: https://www.usgs.gov/mission-areas/water-resources
   roleName: Data Scientist
   startDate: '2024-05-12T15:43:21.898129'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Development Ecologist and Data Scientist, U.S. Geological Survey, 2019-Present
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Ecologist, U.S. Geological Survey, 2016-2019
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: 'Postdoctoral Fellow, USGS Powell Center and University of Wisconsin-Madison.
     Mentors: E. H. Stanley, J. S. Read, E. G. Stets, and R. O. Hall, 2015-2016'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: 'Postdoctoral Associate, University of New Hampshire. Mentor: W. H. McDowell,
     2013-2015'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: 'Postdoctoral Associate, Duke University. Mentor: J. B. Heffernan, 2012-2013'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: 'Ph.D. Student and Teaching Assistant: Organismal Diversity, Aquatic Field
     Ecology, and General Microbiology, University Program in Ecology, Duke University,
     2006-2012'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Research Technician, Stanford University & Carnegie Institution of Washington,
     2004-2006
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: 'Undergraduate Teaching Assistant: Programming Paradigms and Discrete Mathematics,
     Computer Science, Stanford University, 2001-2003'
 identifier:
 - '@type': PropertyValue
   propertyID: GeoKB
   value: https://geokb.wikibase.cloud/entity/Q44528
 - '@type': PropertyValue
   propertyID: ORCID
   value: 0000-0003-3638-8572
 jobTitle: Data Scientist
 knowsAbout:
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Data science
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Ecology
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Biogeochemistry
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Rivers and streams
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Machine learning
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Modeling
 memberOf:
   '@type': OrganizationalRole
   member:
     '@type': Organization
     name: U.S. Geological Survey
   name: staff member
   startDate: '2024-05-12T15:43:21.895471'
 name: Alison Appling, PhD
 url: https://www.usgs.gov/staff-profiles/alison-appling