Ontology type: schema:ScholarlyArticle
2017-02-07
AUTHORSN. Kazanci, G. Turkmen, P. Ekingen, O. Basoren
ABSTRACTEastern Black Sea Region of Turkey is a sub-ecoregion of the Caucasus Ecoregion, and its Plecoptera fauna is similar to fauna of Caucasus with unique endemic species of the region. The Caucasus Ecoregion is one of the “WWF Global 200 Ecoregions,” and it is also included in the list of top 25 hotspots in the World. Running water ecosystems of Eastern Black Sea sub-ecoregion are the most sensitive to land use change and global climate change. High-altitude aquatic ecosystems are more strongly threatened by global climate change in the region. Plecoptera constitute the most important part of the biodiversity of running waters in the region. Among the benthic macroinvertebrate taxa, Plecoptera is the best indicator of ecological conditions of running waters. The influence of environmental variables on the distribution of twenty Plecoptera species in running water ecosystems (headwaters, crenon, epirhithron, metarhithron) was assessed using canonical correspondence analysis. Sampling was carried out in 2009 and 2011. Eleven end groups were generated from the TWINSPAN analysis. Isoperla rhododendri, Isoperla grammatica, Protonemura bifida, Protonemura eumontana and Perla caucasica were closely related to pH, dissolved oxygen and riparian vegetation. Brachyptera transcaucasica transcaucasica, Nemoura martynovia, Nemoura taurica and Protonemura eumontana were related to Mg and Cu. The results show that the Plecoptera assemblage composition was affected by DO, pH, EC, temperature, nitrite, Ca, Mg, Fe, Cu, Zn, Al, riparian vegetation, altitude and stream width. More... »
PAGES1307-1316
http://scigraph.springernature.com/pub.10.1007/s13762-017-1245-y
DOIhttp://dx.doi.org/10.1007/s13762-017-1245-y
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1083698833
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/2008/05",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Environmental Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biological Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0501",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Ecological Applications",
"type": "DefinedTerm"
},
{
"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/2008/0602",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Ecology",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey",
"id": "http://www.grid.ac/institutes/grid.14442.37",
"name": [
"Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey"
],
"type": "Organization"
},
"familyName": "Kazanci",
"givenName": "N.",
"id": "sg:person.014234374413.57",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014234374413.57"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey",
"id": "http://www.grid.ac/institutes/grid.14442.37",
"name": [
"Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey"
],
"type": "Organization"
},
"familyName": "Turkmen",
"givenName": "G.",
"id": "sg:person.015050432661.74",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015050432661.74"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey",
"id": "http://www.grid.ac/institutes/grid.14442.37",
"name": [
"Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey"
],
"type": "Organization"
},
"familyName": "Ekingen",
"givenName": "P.",
"id": "sg:person.011143450443.54",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011143450443.54"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey",
"id": "http://www.grid.ac/institutes/grid.14442.37",
"name": [
"Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey"
],
"type": "Organization"
},
"familyName": "Basoren",
"givenName": "O.",
"id": "sg:person.011741031043.23",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011741031043.23"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/bf03326175",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049915792",
"https://doi.org/10.1007/bf03326175"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00006774",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034681305",
"https://doi.org/10.1007/bf00006774"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/a:1015287708170",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052682832",
"https://doi.org/10.1023/a:1015287708170"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s002670010101",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023775104",
"https://doi.org/10.1007/s002670010101"
],
"type": "CreativeWork"
}
],
"datePublished": "2017-02-07",
"datePublishedReg": "2017-02-07",
"description": "Eastern Black Sea Region of Turkey is a sub-ecoregion of the Caucasus Ecoregion, and its Plecoptera fauna is similar to fauna of Caucasus with unique endemic species of the region. The Caucasus Ecoregion is one of the \u201cWWF Global 200 Ecoregions,\u201d and it is also included in the list of top 25 hotspots in the World. Running water ecosystems of Eastern Black Sea sub-ecoregion are the most sensitive to land use change and global climate change. High-altitude aquatic ecosystems are more strongly threatened by global climate change in the region. Plecoptera constitute the most important part of the biodiversity of running waters in the region. Among the benthic macroinvertebrate taxa, Plecoptera is the best indicator of ecological conditions of running waters. The influence of environmental variables on the distribution of twenty Plecoptera species in running water ecosystems (headwaters, crenon, epirhithron, metarhithron) was assessed using canonical correspondence analysis. Sampling was carried out in 2009 and 2011. Eleven end groups were generated from the TWINSPAN analysis. Isoperla rhododendri, Isoperla grammatica, Protonemura bifida, Protonemura eumontana and Perla caucasica were closely related to pH, dissolved oxygen and riparian vegetation. Brachyptera transcaucasica transcaucasica, Nemoura martynovia, Nemoura taurica and Protonemura eumontana were related to Mg and Cu. The results show that the Plecoptera assemblage composition was affected by DO, pH, EC, temperature, nitrite, Ca, Mg, Fe, Cu, Zn, Al, riparian vegetation, altitude and stream width.",
"genre": "article",
"id": "sg:pub.10.1007/s13762-017-1245-y",
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1036943",
"issn": [
"1735-1472",
"1735-2630"
],
"name": "International Journal of Environmental Science and Technology",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "6",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "14"
}
],
"keywords": [
"global climate change",
"Caucasus Ecoregion",
"riparian vegetation",
"water ecosystems",
"climate change",
"high-altitude aquatic ecosystems",
"Global 200 Ecoregions",
"unique endemic species",
"benthic macroinvertebrate taxa",
"land use change",
"canonical correspondence analysis",
"biodiversity hotspot",
"use change",
"aquatic ecosystems",
"macroinvertebrate taxa",
"TWINSPAN analysis",
"endemic species",
"assemblage composition",
"community composition",
"Plecoptera fauna",
"environmental variables",
"ecological conditions",
"Plecoptera species",
"Eastern Black Sea Region",
"correspondence analysis",
"Black Sea region",
"ecoregions",
"Eastern Black Sea",
"ecosystems",
"dissolved oxygen",
"Isoperla grammatica",
"Black Sea",
"Plecoptera",
"vegetation",
"Sea region",
"fauna",
"good indicator",
"hotspots",
"species",
"Cu",
"water",
"biodiversity",
"Mg",
"taxa",
"composition",
"Zn",
"region",
"Sea",
"caucasica",
"changes",
"altitude",
"taurica",
"DO",
"indicators",
"grammatica",
"Fe",
"Caucasus",
"EC",
"Ca",
"distribution",
"important part",
"list",
"world",
"variables",
"Turkey",
"part",
"influence",
"analysis",
"temperature",
"nitrite",
"al",
"oxygen",
"conditions",
"results",
"width",
"bifida",
"evaluation",
"group",
"technic",
"end groups"
],
"name": "Evaluation of Plecoptera (Insecta) community composition using multivariate technics in a biodiversity hotspot",
"pagination": "1307-1316",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1083698833"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s13762-017-1245-y"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s13762-017-1245-y",
"https://app.dimensions.ai/details/publication/pub.1083698833"
],
"sdDataset": "articles",
"sdDatePublished": "2022-08-04T17:04",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_741.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s13762-017-1245-y"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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/s13762-017-1245-y'
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/s13762-017-1245-y'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13762-017-1245-y'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13762-017-1245-y'
This table displays all metadata directly associated to this object as RDF triples.
186 TRIPLES
21 PREDICATES
111 URIs
96 LITERALS
6 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/s13762-017-1245-y | schema:about | anzsrc-for:05 |
2 | ″ | ″ | anzsrc-for:0501 |
3 | ″ | ″ | anzsrc-for:0502 |
4 | ″ | ″ | anzsrc-for:06 |
5 | ″ | ″ | anzsrc-for:0602 |
6 | ″ | schema:author | N2aeb705f1a474b9082467413ce638999 |
7 | ″ | schema:citation | sg:pub.10.1007/bf00006774 |
8 | ″ | ″ | sg:pub.10.1007/bf03326175 |
9 | ″ | ″ | sg:pub.10.1007/s002670010101 |
10 | ″ | ″ | sg:pub.10.1023/a:1015287708170 |
11 | ″ | schema:datePublished | 2017-02-07 |
12 | ″ | schema:datePublishedReg | 2017-02-07 |
13 | ″ | schema:description | Eastern Black Sea Region of Turkey is a sub-ecoregion of the Caucasus Ecoregion, and its Plecoptera fauna is similar to fauna of Caucasus with unique endemic species of the region. The Caucasus Ecoregion is one of the “WWF Global 200 Ecoregions,” and it is also included in the list of top 25 hotspots in the World. Running water ecosystems of Eastern Black Sea sub-ecoregion are the most sensitive to land use change and global climate change. High-altitude aquatic ecosystems are more strongly threatened by global climate change in the region. Plecoptera constitute the most important part of the biodiversity of running waters in the region. Among the benthic macroinvertebrate taxa, Plecoptera is the best indicator of ecological conditions of running waters. The influence of environmental variables on the distribution of twenty Plecoptera species in running water ecosystems (headwaters, crenon, epirhithron, metarhithron) was assessed using canonical correspondence analysis. Sampling was carried out in 2009 and 2011. Eleven end groups were generated from the TWINSPAN analysis. Isoperla rhododendri, Isoperla grammatica, Protonemura bifida, Protonemura eumontana and Perla caucasica were closely related to pH, dissolved oxygen and riparian vegetation. Brachyptera transcaucasica transcaucasica, Nemoura martynovia, Nemoura taurica and Protonemura eumontana were related to Mg and Cu. The results show that the Plecoptera assemblage composition was affected by DO, pH, EC, temperature, nitrite, Ca, Mg, Fe, Cu, Zn, Al, riparian vegetation, altitude and stream width. |
14 | ″ | schema:genre | article |
15 | ″ | schema:isAccessibleForFree | false |
16 | ″ | schema:isPartOf | N3c0bdac9e1e34e5782b9bc0bf087753c |
17 | ″ | ″ | Ne5564377bf414bdd9aa0521f86e8a9c8 |
18 | ″ | ″ | sg:journal.1036943 |
19 | ″ | schema:keywords | Black Sea |
20 | ″ | ″ | Black Sea region |
21 | ″ | ″ | Ca |
22 | ″ | ″ | Caucasus |
23 | ″ | ″ | Caucasus Ecoregion |
24 | ″ | ″ | Cu |
25 | ″ | ″ | DO |
26 | ″ | ″ | EC |
27 | ″ | ″ | Eastern Black Sea |
28 | ″ | ″ | Eastern Black Sea Region |
29 | ″ | ″ | Fe |
30 | ″ | ″ | Global 200 Ecoregions |
31 | ″ | ″ | Isoperla grammatica |
32 | ″ | ″ | Mg |
33 | ″ | ″ | Plecoptera |
34 | ″ | ″ | Plecoptera fauna |
35 | ″ | ″ | Plecoptera species |
36 | ″ | ″ | Sea |
37 | ″ | ″ | Sea region |
38 | ″ | ″ | TWINSPAN analysis |
39 | ″ | ″ | Turkey |
40 | ″ | ″ | Zn |
41 | ″ | ″ | al |
42 | ″ | ″ | altitude |
43 | ″ | ″ | analysis |
44 | ″ | ″ | aquatic ecosystems |
45 | ″ | ″ | assemblage composition |
46 | ″ | ″ | benthic macroinvertebrate taxa |
47 | ″ | ″ | bifida |
48 | ″ | ″ | biodiversity |
49 | ″ | ″ | biodiversity hotspot |
50 | ″ | ″ | canonical correspondence analysis |
51 | ″ | ″ | caucasica |
52 | ″ | ″ | changes |
53 | ″ | ″ | climate change |
54 | ″ | ″ | community composition |
55 | ″ | ″ | composition |
56 | ″ | ″ | conditions |
57 | ″ | ″ | correspondence analysis |
58 | ″ | ″ | dissolved oxygen |
59 | ″ | ″ | distribution |
60 | ″ | ″ | ecological conditions |
61 | ″ | ″ | ecoregions |
62 | ″ | ″ | ecosystems |
63 | ″ | ″ | end groups |
64 | ″ | ″ | endemic species |
65 | ″ | ″ | environmental variables |
66 | ″ | ″ | evaluation |
67 | ″ | ″ | fauna |
68 | ″ | ″ | global climate change |
69 | ″ | ″ | good indicator |
70 | ″ | ″ | grammatica |
71 | ″ | ″ | group |
72 | ″ | ″ | high-altitude aquatic ecosystems |
73 | ″ | ″ | hotspots |
74 | ″ | ″ | important part |
75 | ″ | ″ | indicators |
76 | ″ | ″ | influence |
77 | ″ | ″ | land use change |
78 | ″ | ″ | list |
79 | ″ | ″ | macroinvertebrate taxa |
80 | ″ | ″ | nitrite |
81 | ″ | ″ | oxygen |
82 | ″ | ″ | part |
83 | ″ | ″ | region |
84 | ″ | ″ | results |
85 | ″ | ″ | riparian vegetation |
86 | ″ | ″ | species |
87 | ″ | ″ | taurica |
88 | ″ | ″ | taxa |
89 | ″ | ″ | technic |
90 | ″ | ″ | temperature |
91 | ″ | ″ | unique endemic species |
92 | ″ | ″ | use change |
93 | ″ | ″ | variables |
94 | ″ | ″ | vegetation |
95 | ″ | ″ | water |
96 | ″ | ″ | water ecosystems |
97 | ″ | ″ | width |
98 | ″ | ″ | world |
99 | ″ | schema:name | Evaluation of Plecoptera (Insecta) community composition using multivariate technics in a biodiversity hotspot |
100 | ″ | schema:pagination | 1307-1316 |
101 | ″ | schema:productId | N0efbf9a178a947d286f98c254d43094c |
102 | ″ | ″ | Nc4fde3a040dc4639bf35c6f1382c28dc |
103 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1083698833 |
104 | ″ | ″ | https://doi.org/10.1007/s13762-017-1245-y |
105 | ″ | schema:sdDatePublished | 2022-08-04T17:04 |
106 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
107 | ″ | schema:sdPublisher | Nd140be2985e94afc9e95d9ea64f42e67 |
108 | ″ | schema:url | https://doi.org/10.1007/s13762-017-1245-y |
109 | ″ | sgo:license | sg:explorer/license/ |
110 | ″ | sgo:sdDataset | articles |
111 | ″ | rdf:type | schema:ScholarlyArticle |
112 | N022896f11d864d1d8b70e7dbe463d3f1 | rdf:first | sg:person.011741031043.23 |
113 | ″ | rdf:rest | rdf:nil |
114 | N0efbf9a178a947d286f98c254d43094c | schema:name | dimensions_id |
115 | ″ | schema:value | pub.1083698833 |
116 | ″ | rdf:type | schema:PropertyValue |
117 | N2aeb705f1a474b9082467413ce638999 | rdf:first | sg:person.014234374413.57 |
118 | ″ | rdf:rest | Nd9f41c09d453487981d67f38bb05461c |
119 | N3c0bdac9e1e34e5782b9bc0bf087753c | schema:issueNumber | 6 |
120 | ″ | rdf:type | schema:PublicationIssue |
121 | Nc4fde3a040dc4639bf35c6f1382c28dc | schema:name | doi |
122 | ″ | schema:value | 10.1007/s13762-017-1245-y |
123 | ″ | rdf:type | schema:PropertyValue |
124 | Nd140be2985e94afc9e95d9ea64f42e67 | schema:name | Springer Nature - SN SciGraph project |
125 | ″ | rdf:type | schema:Organization |
126 | Nd741c2fa256d45dfa5d525378d1b1f88 | rdf:first | sg:person.011143450443.54 |
127 | ″ | rdf:rest | N022896f11d864d1d8b70e7dbe463d3f1 |
128 | Nd9f41c09d453487981d67f38bb05461c | rdf:first | sg:person.015050432661.74 |
129 | ″ | rdf:rest | Nd741c2fa256d45dfa5d525378d1b1f88 |
130 | Ne5564377bf414bdd9aa0521f86e8a9c8 | schema:volumeNumber | 14 |
131 | ″ | rdf:type | schema:PublicationVolume |
132 | anzsrc-for:05 | schema:inDefinedTermSet | anzsrc-for: |
133 | ″ | schema:name | Environmental Sciences |
134 | ″ | rdf:type | schema:DefinedTerm |
135 | anzsrc-for:0501 | schema:inDefinedTermSet | anzsrc-for: |
136 | ″ | schema:name | Ecological Applications |
137 | ″ | rdf:type | schema:DefinedTerm |
138 | anzsrc-for:0502 | schema:inDefinedTermSet | anzsrc-for: |
139 | ″ | schema:name | Environmental Science and Management |
140 | ″ | rdf:type | schema:DefinedTerm |
141 | anzsrc-for:06 | schema:inDefinedTermSet | anzsrc-for: |
142 | ″ | schema:name | Biological Sciences |
143 | ″ | rdf:type | schema:DefinedTerm |
144 | anzsrc-for:0602 | schema:inDefinedTermSet | anzsrc-for: |
145 | ″ | schema:name | Ecology |
146 | ″ | rdf:type | schema:DefinedTerm |
147 | sg:journal.1036943 | schema:issn | 1735-1472 |
148 | ″ | ″ | 1735-2630 |
149 | ″ | schema:name | International Journal of Environmental Science and Technology |
150 | ″ | schema:publisher | Springer Nature |
151 | ″ | rdf:type | schema:Periodical |
152 | sg:person.011143450443.54 | schema:affiliation | grid-institutes:grid.14442.37 |
153 | ″ | schema:familyName | Ekingen |
154 | ″ | schema:givenName | P. |
155 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011143450443.54 |
156 | ″ | rdf:type | schema:Person |
157 | sg:person.011741031043.23 | schema:affiliation | grid-institutes:grid.14442.37 |
158 | ″ | schema:familyName | Basoren |
159 | ″ | schema:givenName | O. |
160 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011741031043.23 |
161 | ″ | rdf:type | schema:Person |
162 | sg:person.014234374413.57 | schema:affiliation | grid-institutes:grid.14442.37 |
163 | ″ | schema:familyName | Kazanci |
164 | ″ | schema:givenName | N. |
165 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014234374413.57 |
166 | ″ | rdf:type | schema:Person |
167 | sg:person.015050432661.74 | schema:affiliation | grid-institutes:grid.14442.37 |
168 | ″ | schema:familyName | Turkmen |
169 | ″ | schema:givenName | G. |
170 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015050432661.74 |
171 | ″ | rdf:type | schema:Person |
172 | sg:pub.10.1007/bf00006774 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1034681305 |
173 | ″ | ″ | https://doi.org/10.1007/bf00006774 |
174 | ″ | rdf:type | schema:CreativeWork |
175 | sg:pub.10.1007/bf03326175 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1049915792 |
176 | ″ | ″ | https://doi.org/10.1007/bf03326175 |
177 | ″ | rdf:type | schema:CreativeWork |
178 | sg:pub.10.1007/s002670010101 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1023775104 |
179 | ″ | ″ | https://doi.org/10.1007/s002670010101 |
180 | ″ | rdf:type | schema:CreativeWork |
181 | sg:pub.10.1023/a:1015287708170 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1052682832 |
182 | ″ | ″ | https://doi.org/10.1023/a:1015287708170 |
183 | ″ | rdf:type | schema:CreativeWork |
184 | grid-institutes:grid.14442.37 | schema:alternateName | Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey |
185 | ″ | schema:name | Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey |
186 | ″ | rdf:type | schema:Organization |