Data

A dataset on spatial distribution and association patterns of three species from moist semi deciduous forest

Advanced Ecological Knowledge and Observation System
Wédjangnon, A. A. ; Sourou Kuiga, B. N. ; Houêtchégnon, T. ; Ouinsavi, C. A. I. N.
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25901/5dce7f2714885&rft.title=A dataset on spatial distribution and association patterns of three species from moist semi deciduous forest&rft.identifier=http://doi.org/10.25901/5dce7f2714885&rft.publisher=ÆKOS Data Portal, rights owned by Laboratoire d'Etudes et de Recherches Forestières&rft.description=Knowledge the spatial distribution and interspecific association patterns in tree species is essential in plant ecology to understand ecological mechanisms and dynamic process operating in spatial distribution of a tree population in a plant community. We measured and compiled datasets on three tropical tree species from a moist semi deciduous forest. We used the software Programita to perform univariate and bivariate point pattern analysis by Ripley's L-function. These datasets can be used to inform on possibilities of interaction of these species in forest stands. These datasets can be also used to access the capacity of each tree of Mansonia altissima var. altissima A. Chev. to be develop and grow or its exclusion probability within a plant community.&rft.creator=Anonymous&rft.date=2019&rft.coverage=This study was conducted in the moist semi-deciduous forest of Adakplamè in Republic of Benin, West Africa.&rft.coverage=northlimit=7.47936; southlimit=7.45000; eastlimit=2.59147; westlimit=2.56000; projection=GDA94&rft_rights=(C)2019 Laboratoire d'Etudes et de Recherches Forestières. Rights owned by Laboratoire d'Etudes et de Recherches Forestières. Rights licensed subject to Creative Commons Attribution 4.0 International.&rft_rights=Creative Commons Attribution 4.0 International&rft_subject=ECOLOGY&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Terrestrial Ecology&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Conservation and Biodiversity&rft_subject=Natural Resource Management (050209)&rft_subject=Ecological Modelling&rft_subject=ECOSYSTEM ASSESSMENT AND MANAGEMENT&rft_subject=ENVIRONMENT&rft_subject=Behavioural Ecology&rft_subject=Competition/Resource Partitioning&rft_subject=Ecological Succession&rft_subject=Restoration Ecology&rft_subject=Habitat Restoration&rft_subject=Special Management Populations&rft.type=dataset&rft.language=English ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25901/5dce7f2714885&rft.title=A dataset on spatial distribution and association patterns of three species from moist semi deciduous forest&rft.identifier=http://doi.org/10.25901/5dce7f2714885&rft.publisher=ÆKOS Data Portal, rights owned by Laboratoire d'Etudes et de Recherches Forestières&rft.description=Knowledge the spatial distribution and interspecific association patterns in tree species is essential in plant ecology to understand ecological mechanisms and dynamic process operating in spatial distribution of a tree population in a plant community. We measured and compiled datasets on three tropical tree species from a moist semi deciduous forest. We used the software Programita to perform univariate and bivariate point pattern analysis by Ripley's L-function. These datasets can be used to inform on possibilities of interaction of these species in forest stands. These datasets can be also used to access the capacity of each tree of Mansonia altissima var. altissima A. Chev. to be develop and grow or its exclusion probability within a plant community.&rft.creator=Anonymous&rft.date=2019&rft.coverage=This study was conducted in the moist semi-deciduous forest of Adakplamè in Republic of Benin, West Africa.&rft.coverage=northlimit=7.47936; southlimit=7.45000; eastlimit=2.59147; westlimit=2.56000; projection=GDA94&rft_rights=(C)2019 Laboratoire d'Etudes et de Recherches Forestières. Rights owned by Laboratoire d'Etudes et de Recherches Forestières. Rights licensed subject to Creative Commons Attribution 4.0 International.&rft_rights=Creative Commons Attribution 4.0 International&rft_subject=ECOLOGY&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Terrestrial Ecology&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Conservation and Biodiversity&rft_subject=Natural Resource Management (050209)&rft_subject=Ecological Modelling&rft_subject=ECOSYSTEM ASSESSMENT AND MANAGEMENT&rft_subject=ENVIRONMENT&rft_subject=Behavioural Ecology&rft_subject=Competition/Resource Partitioning&rft_subject=Ecological Succession&rft_subject=Restoration Ecology&rft_subject=Habitat Restoration&rft_subject=Special Management Populations&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International

(C)2019 Laboratoire d'Etudes et de Recherches Forestières. Rights owned by Laboratoire d'Etudes et de Recherches Forestières. Rights licensed subject to Creative Commons Attribution 4.0 International.

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These data can be freely downloaded via the Advanced Ecological Knowledge and Observation System (ÆKOS) Data Portal and used subject to the Creative Commons Attribution 4.0 International. Attribution and citation is required as described under License and Citation. We ask you to send citations of publications arising from work that use these data to TERN Eco-informatics at datacited@aekos.org.au and citation and copies of publications to wedjangnon_app@yahoo.com

Contact Information

Street Address:
Adigla Appolinaire WEDJANGNON
Université de Parakou
03BP 123
Ph: 0022997364888

wedjangnon_app@yahoo.com

Full description

Knowledge the spatial distribution and interspecific association patterns in tree species is essential in plant ecology to understand ecological mechanisms and dynamic process operating in spatial distribution of a tree population in a plant community. We measured and compiled datasets on three tropical tree species from a moist semi deciduous forest. We used the software Programita to perform univariate and bivariate point pattern analysis by Ripley's L-function. These datasets can be used to inform on possibilities of interaction of these species in forest stands. These datasets can be also used to access the capacity of each tree of Mansonia altissima var. altissima A. Chev. to be develop and grow or its exclusion probability within a plant community.

Date Submitted : 2019-11-15

Date Accepted : 2019-11-15

Data time period: 2017-01-25 to 2018-03-04

This dataset is part of a larger collection

Click to explore relationships graph

2.59147,7.47936 2.59147,7.45 2.56,7.45 2.56,7.47936 2.59147,7.47936

2.575735,7.46468

text: This study was conducted in the moist semi-deciduous forest of Adakplamè in Republic of Benin, West Africa.

Identifiers
  • Local : aekos.org.au/collection/shared/417710