Predicting habitat affinities of plant species using commonly measured functional traits

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....

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Published inJournal of vegetation science Vol. 28; no. 5; pp. 1082 - 1095
Main 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, De Patta Pillar, Valério, Onipchenko, Vladimir, Poschlod, Peter
Format Journal Article
LanguageEnglish
Published Hoboken John Wiley & Sons Ltd 01.09.2017
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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 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.
AbstractList 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.
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. 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.
Author Poschlod, Peter
Blonder, Benjamin
Kühn, Ingolf
Bahn, Michael
Shipley, Bill
Belluau, Michael
Kattge, Jens
Onipchenko, Vladimir
Hickler, Thomas
Manning, Peter
Cavender-Bares, Jeannine
Sack, Lawren
Ozinga, Wim A.
van Bodegom, Peter M.
De Patta Pillar, Valério
Sosinski, Enio
Soudzilovskaia, Nadejda A.
Penuelas, Josep
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Copyright Copyright © 2017 International Association for Vegetation Science
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Wageningen University & Research
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Snippet Questions: Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental...
Questions Heinz Ellenberg classically defined “indicator” scores for species representing their typical positions along gradients of key environmental...
Questions Heinz Ellenberg classically defined "indicator" scores for species representing their typical positions along gradients of key environmental...
QUESTIONS: Heinz Ellenberg classically defined “indicator” scores for species representing their typical positions along gradients of key environmental...
Questions Heinz Ellenberg classically defined “indicator” scores for species representing their typical positions along gradients of key environmental...
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SubjectTerms Alterra - Vegetatie, bos- en landschapsecologie
Alterra - Vegetation, forest and landscape ecology
Dry matter
dry matter content
Ecology
environmental factors
Environmental gradients
equations
Fertility
Germany
Habitat affinities
Habitat fertility
Habitats
Herbivores
Irradiance
Leaf area
Leaf dry matter content
Leaf size
Leaves
light intensity
Mathematical models
Morocco
New species
North America
Nutrients
Plant species
Position (location)
prediction
Predictions
Seed size
seed weight
Shade
Soil fertility
Soil moisture
Soil nutrients
soil water
Species classification
Specific leaf area
Understorey plants
Vegetatie, Bos- en Landschapsecologie
Vegetation, Forest and Landscape Ecology
Wetlands
Title Predicting habitat affinities of plant species using commonly measured functional traits
URI https://www.jstor.org/stable/26630214
https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fjvs.12554
https://www.proquest.com/docview/1933918374
https://www.proquest.com/docview/2020907696
http://www.narcis.nl/publication/RecordID/oai:library.wur.nl:wurpubs%2F530402
Volume 28
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