Comparing convenience and probability sampling for urban ecology applications

Urban forest ecosystems confer multiple ecosystem services. There is therefore a need to quantify ecological characteristics in terms of community structure and composition so that benefits can be better understood in ecosystem service models. Efficient sampling and monitoring methods are crucial in...

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Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/22228
Acceso en línea:
https://doi.org/10.1111/1365-2664.13167
https://repository.urosario.edu.co/handle/10336/22228
Palabra clave:
Community structure
Conspecific
Ecosystem service
Forest inventory
Heterogeneity
Land use
Probability
Sampling
Service provision
Species diversity
Species richness
Urban ecosystem
Urban forestry
Vegetation structure
Italy
Beta diversity
Convenience sampling
Ecosystem services
Heterogeneity
Probability sampling
Pseudosampling
Urban ecosystem
Urban forest structure
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id EDOCUR2_8ed31cf9060810c7f2dcc1919d58ba50
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network_name_str Repositorio EdocUR - U. Rosario
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spelling 0292496f-1337-4aa8-bfc1-8c1555950e3d-1368d04f3-0ee7-4522-b98a-584e22667c6f-1184f8a71-5928-4a1b-82b1-ea7c21048a98-12af37fa3-ad1d-472b-ba95-ec17ff97dcb5-12020-05-25T23:55:49Z2020-05-25T23:55:49Z2018Urban forest ecosystems confer multiple ecosystem services. There is therefore a need to quantify ecological characteristics in terms of community structure and composition so that benefits can be better understood in ecosystem service models. Efficient sampling and monitoring methods are crucial in this process. Full tree inventories are scarce due to time and financial constraints, thus a variety of sampling methods exist. Modern vegetation surveys increasingly use a stratified-random plot-based sampling to reduce the bias associated with convenience sampling, even though the latter can save time and increase species richness scores. The urban landscape, with a high degree of conspecific clustering and high species diversity, provides a unique biogeographical case for comparing these two methodological approaches. We use two spatially extensive convenience samples of the urban forest of Meran (Italy), and compare the community structure, tree characteristics and ecosystem service provision with 200 random circular plots. The convenience sampling resulted in a higher species diversity, incorporating more rare species. This is a result of covering more area per unit sampling time. Pseudorandom subplots were compared to the random plots revealing similar Shannon diversity and sampling comparability indices. Measured tree variables (diameter at breast height, height, tree-crown width, height to crown base) were similar between the two methods, as were ecosystem service model outputs. Synthesis and applications. Our results suggest that convenience sampling may be a time and money saving alternative to random sampling as long as stratification by land-use type is incorporated into the design. The higher species richness can potentially improve the accuracy of urban ecological models, which rely on species-specific functional traits. © 2018 The Authors. Journal of Applied Ecology © 2018 British Ecological Societyapplication/pdfhttps://doi.org/10.1111/1365-2664.131670021890113652664https://repository.urosario.edu.co/handle/10336/22228engBlackwell Publishing Ltd2342No. 52332Journal of Applied EcologyVol. 55Journal of Applied Ecology, ISSN:00218901, 13652664, Vol.55, No.5 (2018); pp. 2332-2342https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047825235&doi=10.1111%2f1365-2664.13167&partnerID=40&md5=02230a85cb04a63d8fd48f2a0f5f10faAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCommunity structureConspecificEcosystem serviceForest inventoryHeterogeneityLand useProbabilitySamplingService provisionSpecies diversitySpecies richnessUrban ecosystemUrban forestryVegetation structureItalyBeta diversityConvenience samplingEcosystem servicesHeterogeneityProbability samplingPseudosamplingUrban ecosystemUrban forest structureComparing convenience and probability sampling for urban ecology applicationsarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Speak A.Escobedo F.J.Russo A.Zerbe S.10336/22228oai:repository.urosario.edu.co:10336/222282022-05-02 07:37:20.305751https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Comparing convenience and probability sampling for urban ecology applications
title Comparing convenience and probability sampling for urban ecology applications
spellingShingle Comparing convenience and probability sampling for urban ecology applications
Community structure
Conspecific
Ecosystem service
Forest inventory
Heterogeneity
Land use
Probability
Sampling
Service provision
Species diversity
Species richness
Urban ecosystem
Urban forestry
Vegetation structure
Italy
Beta diversity
Convenience sampling
Ecosystem services
Heterogeneity
Probability sampling
Pseudosampling
Urban ecosystem
Urban forest structure
title_short Comparing convenience and probability sampling for urban ecology applications
title_full Comparing convenience and probability sampling for urban ecology applications
title_fullStr Comparing convenience and probability sampling for urban ecology applications
title_full_unstemmed Comparing convenience and probability sampling for urban ecology applications
title_sort Comparing convenience and probability sampling for urban ecology applications
dc.subject.keyword.spa.fl_str_mv Community structure
Conspecific
Ecosystem service
Forest inventory
Heterogeneity
Land use
Probability
Sampling
Service provision
Species diversity
Species richness
Urban ecosystem
Urban forestry
Vegetation structure
Italy
Beta diversity
Convenience sampling
Ecosystem services
Heterogeneity
Probability sampling
Pseudosampling
Urban ecosystem
Urban forest structure
topic Community structure
Conspecific
Ecosystem service
Forest inventory
Heterogeneity
Land use
Probability
Sampling
Service provision
Species diversity
Species richness
Urban ecosystem
Urban forestry
Vegetation structure
Italy
Beta diversity
Convenience sampling
Ecosystem services
Heterogeneity
Probability sampling
Pseudosampling
Urban ecosystem
Urban forest structure
description Urban forest ecosystems confer multiple ecosystem services. There is therefore a need to quantify ecological characteristics in terms of community structure and composition so that benefits can be better understood in ecosystem service models. Efficient sampling and monitoring methods are crucial in this process. Full tree inventories are scarce due to time and financial constraints, thus a variety of sampling methods exist. Modern vegetation surveys increasingly use a stratified-random plot-based sampling to reduce the bias associated with convenience sampling, even though the latter can save time and increase species richness scores. The urban landscape, with a high degree of conspecific clustering and high species diversity, provides a unique biogeographical case for comparing these two methodological approaches. We use two spatially extensive convenience samples of the urban forest of Meran (Italy), and compare the community structure, tree characteristics and ecosystem service provision with 200 random circular plots. The convenience sampling resulted in a higher species diversity, incorporating more rare species. This is a result of covering more area per unit sampling time. Pseudorandom subplots were compared to the random plots revealing similar Shannon diversity and sampling comparability indices. Measured tree variables (diameter at breast height, height, tree-crown width, height to crown base) were similar between the two methods, as were ecosystem service model outputs. Synthesis and applications. Our results suggest that convenience sampling may be a time and money saving alternative to random sampling as long as stratification by land-use type is incorporated into the design. The higher species richness can potentially improve the accuracy of urban ecological models, which rely on species-specific functional traits. © 2018 The Authors. Journal of Applied Ecology © 2018 British Ecological Society
publishDate 2018
dc.date.created.spa.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-05-25T23:55:49Z
dc.date.available.none.fl_str_mv 2020-05-25T23:55:49Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1111/1365-2664.13167
dc.identifier.issn.none.fl_str_mv 00218901
13652664
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/22228
url https://doi.org/10.1111/1365-2664.13167
https://repository.urosario.edu.co/handle/10336/22228
identifier_str_mv 00218901
13652664
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 2342
dc.relation.citationIssue.none.fl_str_mv No. 5
dc.relation.citationStartPage.none.fl_str_mv 2332
dc.relation.citationTitle.none.fl_str_mv Journal of Applied Ecology
dc.relation.citationVolume.none.fl_str_mv Vol. 55
dc.relation.ispartof.spa.fl_str_mv Journal of Applied Ecology, ISSN:00218901, 13652664, Vol.55, No.5 (2018); pp. 2332-2342
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047825235&doi=10.1111%2f1365-2664.13167&partnerID=40&md5=02230a85cb04a63d8fd48f2a0f5f10fa
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Blackwell Publishing Ltd
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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