Predicting habitat affinities of plant species using commonly measured functional traits. (14th July 2017)
- Record Type:
- Journal Article
- Title:
- Predicting habitat affinities of plant species using commonly measured functional traits. (14th July 2017)
- Main Title:
- Predicting habitat affinities of plant species using commonly measured functional traits
- Authors:
- Shipley, Bill
Belluau, Michael
Kühn, Ingolf
Soudzilovskaia, Nadejda A.
Bahn, Michael
Penuelas, Josep
Kattge, Jens
Sack, Lawren
Cavender‐Bares, Jeannine
Ozinga, Wim A.
Blonder, Benjamin
van Bodegom, Peter M.
Manning, Peter
Hickler, Thomas
Sosinski, Enio
Pillar, Valério De Patta
Onipchenko, Vladimir
Poschlod, Peter - Editors:
- Mason, Norman
- Abstract:
- Abstract: Questions: Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful for designating ecological distributions. We tested a key tenent of trait‐based ecology, i.e. the ability to predict ecological preferences from species' traits. More specifically, can we predict Ellenberg indicator scores for soil nutrients, soil moisture and irradiance from four well‐studied traits: leaf area, leaf dry matter content, specific leaf area (SLA) and seed mass? Can we use such relationships to estimate Ellenberg scores for species never classified by Ellenberg? Location: Global. Methods: Cumulative link models were developed to predict Ellenberg nutrients, irradiance and moisture values from Ln‐transformed trait values using 922, 981 and 988 species, respectively. We then independently tested these prediction equations using the trait values of 423 and 421 new species that occurred elsewere in Europe, North America and Morocco, and whose habitat affinities we could classify from independent sources as three‐level ordinal ranks related to soil moisture and irradiance. The traits were SLA, leaf dry matter content, leaf area and seed mass. Results: The four functional traits predicted the Ellenberg indicator scores of site fertility, light and moisture with average error rates of <2 Ellenberg ranks out of nine. We then used the trait values of 423 and 421Abstract: Questions: Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful for designating ecological distributions. We tested a key tenent of trait‐based ecology, i.e. the ability to predict ecological preferences from species' traits. More specifically, can we predict Ellenberg indicator scores for soil nutrients, soil moisture and irradiance from four well‐studied traits: leaf area, leaf dry matter content, specific leaf area (SLA) and seed mass? Can we use such relationships to estimate Ellenberg scores for species never classified by Ellenberg? Location: Global. Methods: Cumulative link models were developed to predict Ellenberg nutrients, irradiance and moisture values from Ln‐transformed trait values using 922, 981 and 988 species, respectively. We then independently tested these prediction equations using the trait values of 423 and 421 new species that occurred elsewere in Europe, North America and Morocco, and whose habitat affinities we could classify from independent sources as three‐level ordinal ranks related to soil moisture and irradiance. The traits were SLA, leaf dry matter content, leaf area and seed mass. Results: The four functional traits predicted the Ellenberg indicator scores of site fertility, light and moisture with average error rates of <2 Ellenberg ranks out of nine. We then used the trait values of 423 and 421 species, respectively, that occurred (mostly) outside of Germany but whose habitat affinities we could classify as three‐level ordinal ranks related to soil moisture and irradiance. The predicted positions of the new species, given the equations derived from the Ellenberg indices, agreed well with their independent habitat classifications, although our equation for Ellenberg irrandiance levels performed poorly on the lower ranks. Conclusions: These prediction equations, and their eventual extensions, could be used to provide approximate descriptions of habitat affinities of large numbers of species worldwide. Abstract : Ellenberg Indicator values score Ellenberg's expert opinion concerning typical habitats of Central European plant species. In order to generalize Ellenberg scores for irradiance, soil fertility and soil moisture to new species and regions, we predicted these indicators from four traits: SLA, leaf dry matter content, leaf nitrogen and seed mass. These equations gave acceptable, but approximate, generalized predictions. … (more)
- Is Part Of:
- Journal of vegetation science. Volume 28:Number 5(2017:Sep.)
- Journal:
- Journal of vegetation science
- Issue:
- Volume 28:Number 5(2017:Sep.)
- Issue Display:
- Volume 28, Issue 5 (2017)
- Year:
- 2017
- Volume:
- 28
- Issue:
- 5
- Issue Sort Value:
- 2017-0028-0005-0000
- Page Start:
- 1082
- Page End:
- 1095
- Publication Date:
- 2017-07-14
- Subjects:
- Environmental gradients -- Habitat affinities -- Habitat fertility -- Leaf dry matter content -- Leaf size -- Seed size -- Shade -- Specific leaf area -- Soil moisture -- Soil nutrients -- Understorey plants -- Wetlands
Plant ecology -- Periodicals
Plant communities -- Periodicals
Plant populations -- Periodicals
581.7 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1654-1103 ↗
http://onlinelibrary.wiley.com/ ↗
http://mclink.library.mcgill.ca/sfx?url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&rfr_id=info:sid/sfxit.com:opac_856&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&sfx.ignore_date_threshold=1&rft.object_id=954925610940&svc_val_fmt=info:ofi/fmt:kev:mtx:sch_svc& ↗
http://www.opuluspress.se ↗ - DOI:
- 10.1111/jvs.12554 ↗
- Languages:
- English
- ISSNs:
- 1100-9233
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5072.277000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 8328.xml