A Landscape-Scale Optimisation Model to Break the Hazardous Fuel Continuum While Maintaining Habitat Quality View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11-07

AUTHORS

Javier León, Victor M. J. J. Reijnders, John W. Hearne, Melih Ozlen, Karin J. Reinke

ABSTRACT

Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires, a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem, we present a spatially explicit, multiperiod mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multiperiod plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used to illustrate the model but the approach can be implemented to prioritise treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint. More... »

PAGES

1-11

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10666-018-9642-2

DOI

http://dx.doi.org/10.1007/s10666-018-9642-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1109759690


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0502", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Science and Management", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/05", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Complutense University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.4795.f", 
          "name": [
            "School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia", 
            "Faculty of Mathematical Sciences, Complutense University of Madrid, Plaza de las Ciencias 3, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Le\u00f3n", 
        "givenName": "Javier", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Twente", 
          "id": "https://www.grid.ac/institutes/grid.6214.1", 
          "name": [
            "School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia", 
            "Department of Applied Mathematics, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Reijnders", 
        "givenName": "Victor M. J. J.", 
        "id": "sg:person.016404170454.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016404170454.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "RMIT University", 
          "id": "https://www.grid.ac/institutes/grid.1017.7", 
          "name": [
            "School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hearne", 
        "givenName": "John W.", 
        "id": "sg:person.01217624454.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217624454.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "RMIT University", 
          "id": "https://www.grid.ac/institutes/grid.1017.7", 
          "name": [
            "School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ozlen", 
        "givenName": "Melih", 
        "id": "sg:person.01151511254.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01151511254.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "RMIT University", 
          "id": "https://www.grid.ac/institutes/grid.1017.7", 
          "name": [
            "School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Reinke", 
        "givenName": "Karin J.", 
        "id": "sg:person.013252375615.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013252375615.44"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/s40064-015-1418-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005338760", 
          "https://doi.org/10.1186/s40064-015-1418-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40064-015-1418-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005338760", 
          "https://doi.org/10.1186/s40064-015-1418-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1890/es13-00007.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010679069"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/2041-210x.12470", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012035491"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/x2012-051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015063061"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2005.01.034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017342902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf15146", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018882134"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10479-015-1907-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020636363", 
          "https://doi.org/10.1007/s10479-015-1907-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf06051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024192704"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2008.05.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025041914"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf09131", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026743902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf05076", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027035144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/x07-162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030185576"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf09095", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035615853"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf02042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038261807"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf06064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038472994"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2008.01.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039528254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/f7030064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040671636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf06063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040840309"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2010.03.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041482343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s40725-015-0005-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042500648", 
          "https://doi.org/10.1007/s40725-015-0005-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2009.10.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042752513"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2004.04.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043151723"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/wf07052", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046311574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biocon.2008.11.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046578259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biocon.2013.06.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048487711"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foreco.2016.03.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049786263"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2013.07.026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052978605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1523-1739.2008.00934.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053230022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/141000671", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083719304"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/15m1020575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085328616"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.apm.2017.09.045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092048648"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scitotenv.2017.11.297", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099693565"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-11-07", 
    "datePublishedReg": "2018-11-07", 
    "description": "Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires, a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem, we present a spatially explicit, multiperiod mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multiperiod plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used to illustrate the model but the approach can be implemented to prioritise treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10666-018-9642-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136031", 
        "issn": [
          "1420-2026", 
          "1573-2967"
        ], 
        "name": "Environmental Modeling & Assessment", 
        "type": "Periodical"
      }
    ], 
    "name": "A Landscape-Scale Optimisation Model to Break the Hazardous Fuel Continuum While Maintaining Habitat Quality", 
    "pagination": "1-11", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "4923425b873aef6d6091b83002bcfbd9c9d22b352eb323d9e1c1412add0a2277"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10666-018-9642-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1109759690"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10666-018-9642-2", 
      "https://app.dimensions.ai/details/publication/pub.1109759690"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T13:33", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8659_00000610.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10666-018-9642-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10666-018-9642-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10666-018-9642-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10666-018-9642-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10666-018-9642-2'


 

This table displays all metadata directly associated to this object as RDF triples.

189 TRIPLES      21 PREDICATES      56 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10666-018-9642-2 schema:about anzsrc-for:05
2 anzsrc-for:0502
3 schema:author Na1c2a144c4244ca381119dce8ac99aa7
4 schema:citation sg:pub.10.1007/s10479-015-1907-4
5 sg:pub.10.1007/s40725-015-0005-9
6 sg:pub.10.1186/s40064-015-1418-4
7 https://doi.org/10.1016/j.apm.2017.09.045
8 https://doi.org/10.1016/j.biocon.2008.11.005
9 https://doi.org/10.1016/j.biocon.2013.06.022
10 https://doi.org/10.1016/j.ejor.2008.05.025
11 https://doi.org/10.1016/j.ejor.2013.07.026
12 https://doi.org/10.1016/j.foreco.2004.04.010
13 https://doi.org/10.1016/j.foreco.2005.01.034
14 https://doi.org/10.1016/j.foreco.2008.01.009
15 https://doi.org/10.1016/j.foreco.2009.10.005
16 https://doi.org/10.1016/j.foreco.2010.03.013
17 https://doi.org/10.1016/j.foreco.2016.03.014
18 https://doi.org/10.1016/j.scitotenv.2017.11.297
19 https://doi.org/10.1071/wf02042
20 https://doi.org/10.1071/wf05076
21 https://doi.org/10.1071/wf06051
22 https://doi.org/10.1071/wf06063
23 https://doi.org/10.1071/wf06064
24 https://doi.org/10.1071/wf07052
25 https://doi.org/10.1071/wf09095
26 https://doi.org/10.1071/wf09131
27 https://doi.org/10.1071/wf15146
28 https://doi.org/10.1111/2041-210x.12470
29 https://doi.org/10.1111/j.1523-1739.2008.00934.x
30 https://doi.org/10.1137/141000671
31 https://doi.org/10.1137/15m1020575
32 https://doi.org/10.1139/x07-162
33 https://doi.org/10.1139/x2012-051
34 https://doi.org/10.1890/es13-00007.1
35 https://doi.org/10.3390/f7030064
36 schema:datePublished 2018-11-07
37 schema:datePublishedReg 2018-11-07
38 schema:description Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires, a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem, we present a spatially explicit, multiperiod mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multiperiod plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used to illustrate the model but the approach can be implemented to prioritise treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint.
39 schema:genre research_article
40 schema:inLanguage en
41 schema:isAccessibleForFree false
42 schema:isPartOf sg:journal.1136031
43 schema:name A Landscape-Scale Optimisation Model to Break the Hazardous Fuel Continuum While Maintaining Habitat Quality
44 schema:pagination 1-11
45 schema:productId Nb4be4ec502de48698f08d59cb910e2b5
46 Ne247a3e3988f4b87833461adb60d6804
47 Ne4737cf4258c4686a7bfd5a7ed6ca2c7
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109759690
49 https://doi.org/10.1007/s10666-018-9642-2
50 schema:sdDatePublished 2019-04-10T13:33
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher Nbeaca628351e485191981190a7b99279
53 schema:url https://link.springer.com/10.1007%2Fs10666-018-9642-2
54 sgo:license sg:explorer/license/
55 sgo:sdDataset articles
56 rdf:type schema:ScholarlyArticle
57 N06421c40ca0e422aaf4e5438d1e6cec4 rdf:first sg:person.013252375615.44
58 rdf:rest rdf:nil
59 N1ee64828dfb042e18ce285ef84ffd3ec rdf:first sg:person.01151511254.56
60 rdf:rest N06421c40ca0e422aaf4e5438d1e6cec4
61 N7fab085dffcb402e80289a9b6cb0b685 rdf:first sg:person.01217624454.13
62 rdf:rest N1ee64828dfb042e18ce285ef84ffd3ec
63 N9b347fd793ac4bc79fc1b48f4767a98f rdf:first sg:person.016404170454.45
64 rdf:rest N7fab085dffcb402e80289a9b6cb0b685
65 Na1c2a144c4244ca381119dce8ac99aa7 rdf:first Nbcb4d69672ee42d6aefecdbaf5e0722c
66 rdf:rest N9b347fd793ac4bc79fc1b48f4767a98f
67 Nb4be4ec502de48698f08d59cb910e2b5 schema:name dimensions_id
68 schema:value pub.1109759690
69 rdf:type schema:PropertyValue
70 Nbcb4d69672ee42d6aefecdbaf5e0722c schema:affiliation https://www.grid.ac/institutes/grid.4795.f
71 schema:familyName León
72 schema:givenName Javier
73 rdf:type schema:Person
74 Nbeaca628351e485191981190a7b99279 schema:name Springer Nature - SN SciGraph project
75 rdf:type schema:Organization
76 Ne247a3e3988f4b87833461adb60d6804 schema:name doi
77 schema:value 10.1007/s10666-018-9642-2
78 rdf:type schema:PropertyValue
79 Ne4737cf4258c4686a7bfd5a7ed6ca2c7 schema:name readcube_id
80 schema:value 4923425b873aef6d6091b83002bcfbd9c9d22b352eb323d9e1c1412add0a2277
81 rdf:type schema:PropertyValue
82 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
83 schema:name Environmental Sciences
84 rdf:type schema:DefinedTerm
85 anzsrc-for:0502 schema:inDefinedTermSet anzsrc-for:
86 schema:name Environmental Science and Management
87 rdf:type schema:DefinedTerm
88 sg:journal.1136031 schema:issn 1420-2026
89 1573-2967
90 schema:name Environmental Modeling & Assessment
91 rdf:type schema:Periodical
92 sg:person.01151511254.56 schema:affiliation https://www.grid.ac/institutes/grid.1017.7
93 schema:familyName Ozlen
94 schema:givenName Melih
95 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01151511254.56
96 rdf:type schema:Person
97 sg:person.01217624454.13 schema:affiliation https://www.grid.ac/institutes/grid.1017.7
98 schema:familyName Hearne
99 schema:givenName John W.
100 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217624454.13
101 rdf:type schema:Person
102 sg:person.013252375615.44 schema:affiliation https://www.grid.ac/institutes/grid.1017.7
103 schema:familyName Reinke
104 schema:givenName Karin J.
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013252375615.44
106 rdf:type schema:Person
107 sg:person.016404170454.45 schema:affiliation https://www.grid.ac/institutes/grid.6214.1
108 schema:familyName Reijnders
109 schema:givenName Victor M. J. J.
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016404170454.45
111 rdf:type schema:Person
112 sg:pub.10.1007/s10479-015-1907-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020636363
113 https://doi.org/10.1007/s10479-015-1907-4
114 rdf:type schema:CreativeWork
115 sg:pub.10.1007/s40725-015-0005-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042500648
116 https://doi.org/10.1007/s40725-015-0005-9
117 rdf:type schema:CreativeWork
118 sg:pub.10.1186/s40064-015-1418-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005338760
119 https://doi.org/10.1186/s40064-015-1418-4
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.apm.2017.09.045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092048648
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/j.biocon.2008.11.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046578259
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.biocon.2013.06.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048487711
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.ejor.2008.05.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025041914
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.ejor.2013.07.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052978605
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.foreco.2004.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043151723
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.foreco.2005.01.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017342902
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.foreco.2008.01.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039528254
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.foreco.2009.10.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042752513
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.foreco.2010.03.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041482343
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.foreco.2016.03.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049786263
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.scitotenv.2017.11.297 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099693565
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1071/wf02042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038261807
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1071/wf05076 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027035144
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1071/wf06051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024192704
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1071/wf06063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040840309
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1071/wf06064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038472994
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1071/wf07052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046311574
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1071/wf09095 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035615853
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1071/wf09131 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026743902
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1071/wf15146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018882134
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1111/2041-210x.12470 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012035491
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1111/j.1523-1739.2008.00934.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1053230022
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1137/141000671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083719304
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1137/15m1020575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085328616
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1139/x07-162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030185576
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1139/x2012-051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015063061
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1890/es13-00007.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010679069
176 rdf:type schema:CreativeWork
177 https://doi.org/10.3390/f7030064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040671636
178 rdf:type schema:CreativeWork
179 https://www.grid.ac/institutes/grid.1017.7 schema:alternateName RMIT University
180 schema:name School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia
181 rdf:type schema:Organization
182 https://www.grid.ac/institutes/grid.4795.f schema:alternateName Complutense University of Madrid
183 schema:name Faculty of Mathematical Sciences, Complutense University of Madrid, Plaza de las Ciencias 3, 28040, Madrid, Spain
184 School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia
185 rdf:type schema:Organization
186 https://www.grid.ac/institutes/grid.6214.1 schema:alternateName University of Twente
187 schema:name Department of Applied Mathematics, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands
188 School of Science, RMIT University, GPO Box 2476, VIC 3001, Melbourne, Australia
189 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...